ALBERT

Description: Potential increases in the risk of extreme weather events under climate change can have significant socio‐economic impacts at regional levels. These impacts are likely to be particularly high in South Asia where Bangladesh is one of the most vulnerable countries. Regional climate models (RCMs) are valuable tools for studying weather and climate at finer spatial scales than are typically available in global climate models. Quantitative assessment of the likely changes in the risk of extreme events occurring requires very large ensemble simulations due to their rarity. The weather@home setup within the climateprediction.net distributed computing project is capable of providing the necessary very large ensembles at regionally higher resolution, but has only been evaluated over the South Asia region for its representation of seasonal climatological and monthly means. Here, we evaluate how realistically the HadAM3P‐HadRM3P model setup of weather@home can reproduce the observed patterns of temperature and rainfall in Bangladesh with focus on the modelled extreme events. Using very large ensembles of regional simulations, we find that there are substantial spatial and temporal variations in rainfall and temperature biases compared with observations. These are highest in the pre‐monsoon, which are largely caused by timing issues in the model. Modelled mean monsoon and post‐monsoon temperatures are in good agreement with observations, whereas, there is a dry bias in the modelled mean monsoon rainfall. The rainfall bias varies both spatially and with the dataset used for comparison. Despite of these biases, the model simulated temperature and rainfall extremes in summer monsoon over Bangladesh are approximately representative of the observed ones. At the wettest parts of north‐east Bangladesh, rainfall extremes are underestimated compared to GPCC and APHRDITE but are within the range of CPC observations. Therefore, the weather@home RCM, HadRM3P can be used to study the changing risks of extreme weather events over Bangladesh.

Description: ABSTRACT An analytical study was conducted to assess the long-term influence, role, and impacts of El Niño-Southern Oscillation (ENSO) on Puerto Rico's precipitation patterns and significant moisture deficits (droughts). Detection and attribution was addressed by evaluating local rainfall measures and ENSO-related data to (1) detect ENSO signals and patterns, (2) quantify the magnitude of any impacts, and (3) determine if ENSO may be an important factor for local prediction of future droughts. Data were evaluated at different time periods and two spatial scales (island-wide and internal climate regions of Puerto Rico). Although a signal was detected, it was weak, in both directions, varied regionally, and has inconsequential impacts. No evidence was found for a major control by ENSO over local monthly, seasonal, and yearly rainfall for any climate regions on the island. These results indicate that ENSO is not a main factor causing droughts in Puerto Rico for the study period and thus should not be a factor in predicting the potential for local dry periods or large precipitation deficits in the future. Any presumed teleconnections between Puerto Rico's dry periods and ENSO are not based on current climatological evidence. Thus, local drought prediction efforts should be focused on finding major causes of local rainfall variation other than ENSO. ENSO's signal was detected in Puerto Rico using different methods but actual impacts on rainfall for the past century are minimal to none at any time and spatial scales.

Description: ABSTRACT The sub-monthly intra-seasonal 8–24-day period (SIS8-24) timescale variability of the summer (1 November to 31 March) rainfall over South America (SA) under distinct inter-annual (IA) backgrounds was analysed using the Tropical Rainfall Measure Mission (TRMM) based daily total precipitation data for the 1998–2012 period. The IA backgrounds refer to the El Niño (EN) and La Niña (LN) years. First, the summer daily precipitation anomaly fields were subject to the empirical orthogonal function (EOF) analysis. Using the first and the second principal component time series filtered at the SIS8-24 timescale, positive and negative events were selected. The first SIS8-24 mode features a precipitation anomaly dipole with centres over southeastern SA (SESA) and central and eastern tropical SA both extending southeastwards into the adjacent Atlantic Ocean. The second mode features a precipitation anomaly pattern similar to that previously documented for the oceanic South Atlantic convergence zone (SACZ). The SIS8-24 precipitation anomaly patterns for the positive (negative) events show differences in the anomaly intensities between EN and LN years, but with almost the same locations of the anomaly centres. These differences result from the variability inter-SIS8-24 events, as indicated by the distinct paths of the SIS8-24 Rossby wave train patterns in the subtropics, although they are regionally locked over tropical SA. The relation between the SIS8-24 and IA variabilities might occur through variations in the Rossby wave train patterns. The Rossby wave trains of both timescales, depending on their phases, reinforce or weaken the rainfall anomalies over SA, in such a way that the rainfall anomalies over SA show similar patterns but with distinct magnitudes for EN and LN composites. The South American precipitation responses to the combined SIS8-24 and IA variability timescales stratified according to the IA backgrounds have not been studied before and might be useful for operational forecasting services. The sub-monthly intra-seasonal 8–24-day period (SIS8-24) timescale variability of the summer (1 November to 31 March) rainfall over South America (SA) under distinct inter-annual (IA) backgrounds was analysed using the Tropical Rainfall Measure Mission (TRMM) based daily total precipitation data for the 1998–2012 period. The IA backgrounds refer to the El Niño (EN) and La Niña (LN) years. The first mode features a precipitation anomaly dipole with centres over southeastern SA (SESA) and the second mode features a precipitation anomaly pattern similar to that previously documented for the oceanic South Atlantic convergence zone (SACZ).

Description: ABSTRACT Observational analyses of changing climate extremes over the West Africa region have been limited by the availability of long and high-quality datasets. To help address this gap, a climate extremes indices workshop was held in the Gambia in December 2011 with participants from 14 West African countries. The resulting analysis utilized 15 annual indices derived from observed daily temperatures and 10 annual indices derived from observed daily precipitation. The analysis was conducted for 166 meteorological stations in 13 countries for 2 periods: 1960–2010 and 1981–2010. The analyses of trends in the annual mean temperature indices have identified statistically significant increases of 0.16 °C/decade and 0.28 °C/decade for mean annual maximum and mean annual minimum temperatures, respectively, averaged over all available land stations in the region during the last 50 years. The seasonal-temperature-related indices show significant patterns of warming in all seasons. The annual mean of daily minimum temperature has increased more than the annual mean of daily maximum temperature leading to a decreasing trend in the diurnal temperature range. Warm days and warm nights have become more frequent, and cold days and cold nights have become less frequent. The analyses of precipitation-based indices indicate spatially non-coherent changes throughout the study area with few statistically significant trends over the longer period. Exceptions to this are the simple daily intensity index and maximum 5-day precipitation, which show significant increasing regional trends over both the shorter and longer periods. Additionally, over the recent period (1981–2010) most of the precipitation related indices show significant trends towards wetter conditions. However, this period of increased rainfall follows a decade of significantly drier conditions in the region – it is not clear whether the recent upward trends reflect the ‘recovery’ from this long drought period or represents a long-term response to warming. Climate extremes indices were derived from daily temperature and precipitation data from 166 observing stations in 13 West African countries, and combined to provide a regional assessment of changing extremes for 1960–2010 and 1981–2010. Statistically significant warming trends indicate more frequent warm days and nights and less frequent cold days and nights. Precipitation-based indices indicate weak spatial patterns with few significant trends over 1960–2010, but over 1981–2010 show significant trends towards wetter conditions.

Description: ABSTRACT One of the major obstacles to using numerical weather prediction models for guidance on mitigating urbanization's impact on local and regional climate is the lack of detailed and model ready morphological data at urban scale. The World Urban Database and Access Portal Tool (WUDAPT) is a recent project developed to extract climate relevant information on urban areas, in the form of local climate zones (LCZs), out of remote sensing imagery. This description of the urban landscape has been tested and used for parameterization of different urban canopy models (UCM) for mesoscale studies. As detailed information is usually bounded within cities' centres, crowdsourced and remote sensing data offer the possibility to move beyond the old barriers of urban climate investigations by studying the full range of variation from the urban core to the periphery and its related impacts on local climate. Thus, for this study we sought to compare the relative impact of using the WUDAPT methodology versus a simplified definition of the urban morphology extracted out of detailed GIS information to initialize a regional weather model and compare the output against official and crowdsourced weather station networks. A case study over Vienna, Austria was conducted using the weather research forecasting (WRF) model, coupled with the building effect parameterization and building energy models (BEP–BEM) in five distinct seasonal periods. Results demonstrated that using detailed GIS data to derive morphological descriptions of LCZs for mesoscale studies provided only a marginal overall improvement over using the default WUDAPT parameters based on the ranges proposed by Stewart and Oke (2012). The findings also highlighted the importance of developing techniques that are better at capturing the morphological heterogeneity across the entire urban landscape and thus improve our understandings of UCM performance over urban areas. A case study over Vienna, Austria was conducted using the Weather Research Forecasting (WRF) model, coupled with the building effect parameterization and building energy models (BEP–BEM) in five distinct seasonal periods. Results demonstrated that using detailed morphological descriptions of LCZs for mesoscale studies provided only a marginal overall improvement over using the default WUDAPT parameters. The findings also highlighted the importance of developing techniques that are better at capturing the variation of urban morphology and thus improve UCM performance over urban areas.

Description: ABSTRACT Based on historical and RCP8.5 experiments, along with 25 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, we evaluate the skills of the CMIP5 models in simulating the subtropical westerly jet (SWJ) and its effect on the projected summer rainfall over central Asia (CA). The historical experiments show that 23 models can well simulate the changes in the position and strength of the SWJ. Further analysis finds that 21 models can capture the relationship between the SWJ position change and summer rainfall over the domain of 55–85°E and 35–50°N and 17 models can capture the relationship between the SWJ strength change and summer rainfall over the domain of 55–75°E and 45–55°N, where 15 models can capture the relationships between both SWJ strength and position change with summer rainfall. Based on the SWJ change among the 15 models, except for the HadGEM2-CC model, the 500 hPa winds of the rest 14 models well match the summer rainfall over CA. So the 14 models are used to do next analysis. In the last 50 years of the 21st century, only the inmcm4 model presents the change in the SWJ strength, and the rest 13 models present the changes in the SWJ position. Among above 13 models, 10 models maintain the relationships between the SWJ position change and summer rainfall over the domain of 55–85°E and 35–50°N into the future. Under the background of global warming, the changes in the SWJ position are well related to the sea surface temperatures (SSTs) over the Indian Ocean in the future. The SST warming over the Indian Ocean results in the South Asian summer monsoon weakening, corresponding to an anomalous anticyclone over the low-level troposphere of the monsoon regions; this situation results in an anomalous cyclone at the upper level of the troposphere of the northwestern flank of the monsoon heating regions due to Matsuno–Gill-type responses, which favour the SWJ axis shifting further south. In addition, we also compare the current projected summer rainfall over CA from our selected models with other selected previous models using different methods. The ensemble results show that more summer rainfall occurring in most of Kazakhstan and Xinjiang Province of northwestern China is more likely in the future; in the rest of the countries of CA, there are uncertainties regarding future rainfall changes. The first two leading EOF modes of the summer zonal wind anomaly at 200 hPa over 25–55°N, 40–80°E for 1961–2004 in (a) and (b). The normalized principal component (PC) corresponding to the leading modes of EOF1 (c) and EOF2 (d).

Description: ABSTRACT Quantile estimates are generally interpreted in association with the return period concept in practical engineering. To do so with the peaks-over-threshold (POT) approach, combined Poisson-generalized Pareto distributions (referred to as PD-GPD model) must be considered. In this article, we evaluate the incorporation of non-stationarity in the generalized Pareto distribution (GPD) and the Poisson distribution (PD) using, respectively, the smoothing-based B-spline functions and the logarithmic link function. Two models are proposed, a stationary PD combined to a non-stationary GPD (referred to as PD0-GPD1) and a combined non-stationary PD and GPD (referred to as PD1-GPD1). The teleconnections between hydro-climatological variables and a number of large-scale climate patterns allow using these climate indices as covariates in the development of non-stationary extreme value models. The case study is made with daily precipitation amount time series from southeastern Canada and two climatic covariates, the Arctic Oscillation (AO) and the Pacific North American (PNA) indices. A comparison of PD0-GPD1 and PD1-GPD1 models showed that the incorporation of non-stationarity in both POT models instead of solely in the GPD has an effect on the estimated quantiles. The use of the B-spline function as link function between the GPD parameters and the considered climatic covariates provided flexible non-stationary PD-GPD models. Indeed, linear and nonlinear conditional quantiles are observed at various stations in the case study, opening an interesting perspective for further research on the physical mechanism behind these simple and complex interactions. Using statistical tools like the cross-wavelet analysis illustrated in the figure, common features of variability are found between precipitation extreme events and the Artic Oscillation index at the Upper Stewiacke station located in Nova Scotia (Canada). Using this index as covariate, we developed non-stationary Poisson-generalized Pareto models, which allow observing conditional quantiles with concave form. The proposed models are more flexible than classical extreme value non-stationary models which often used prior assumption of linear dependence.

Description: ABSTRACT It is generally agreed that models that better simulate historical and current features of climate should also be the ones that more reliably simulate future climate. This article describes the ability of a selection of global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to represent the historical and current mean climate and its variability over northeastern Argentina, a region that exhibits frequent extreme events. Two types of simulations are considered: Long-term simulations for 1901–2005 in which the models respond to climate forcing (e.g. changes in atmospheric composition and land use) and decadal simulations for 1961–2010 that are initialized from observed climate states. Monthly simulations of precipitation and temperature are statistically evaluated for individual models and their ensembles. Subsets of models that best represent the region's climate are further examined. First, models that have a Nash–Sutcliffe efficiency of at least 0.8 are taken as a subset that best represents the observed temperature fields and the mean annual cycle. Their temperature time series are in phase with observations ( r 〉 0.92), despite systematic errors that if desired can be corrected by statistical methods. Likewise, models that have a precipitation Pearson correlation coefficient of at least 0.6 are considered that best represent regional precipitation features. GCMs are able to reproduce the annual precipitation cycle, although they underestimate precipitation amounts during the austral warm season (September through April) and slightly overestimate the cold season rainfall amounts. The ensembles for the subsets of models achieve the best evaluation metrics, exceeding the performance of the overall ensembles as well as those of the individual models. The northeast region of Argentina present hydro-climatic variability at various time scales and undergoes changes in extreme events that could be exacerbated in the coming decades. Reliable projections of future climate require models that adequately represent the regional climate system. This paper evaluates the ability of 27 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate the observed climate and selects a subset of 9 models for temperature and 7 models for precipitation. The multi-model ensembles using selected GCMs improve the performance of each individual GCM.

Description: ABSTRACT Aerosol optical depth (AOD) has become one of the most crucial parameters for climate change assessment. This study presents long-term (2002–2016) spatio-temporal distributions and trends in AOD over East Africa (EA) retrieved from the moderate-resolution imaging spectroradiometer (MODIS) Aqua [Dark Target (DT) and Deep Blue (DB)] and multi-angle imaging spectroradiometer (MISR). An inter-comparison of AODs retrieved from different algorithms noticed significant positive correlations ( r  = 0.72 − 0.87) with MISR underestimating MODIS. Moderate (〉0.5–0.8) to high (≥0.8) correlations in AOD exhibited over EA, with a few regions representing low (0–0.5) positive correlations. The spatial patterns of annual mean AOD were generally characterized by low (〈0.2), moderate (0.2–0.35) and high (〉0.35) centres over EA. The seasonal mean AODs over EA were found high (low) during the local dry (wet) seasons, with annual mean (±σ) values of 0.20 ± 0.01, 0.18 ± 0.01 and 0.20 ± 0.02 as observed by DT, DB and MISR, respectively. A single peak distribution of frequencies in AOD was observed by the three sensors in the interval 0.1–0.2, signifying a generally less polluted environment dominated by particular aerosol type. Linear trend analysis revealed an increase in AOD by 0.52, 0.57 and 0.74% year −1 as detected by MISR, DT and DB, respectively, and were consistent with those noted in key meteorological parameters. Furthermore, annual and seasonal spatial trends and tendencies revealed a general increase in AOD over EA, being positive and significant over the northern part of EA. Later, classification of major aerosol types over major cities in EA revealed dominance of continental (74.47%) followed by the mixed (16.22%) and biomass-burning/urban-industrial (8.02%) aerosols, with minor contributions from desert dust (1.03%) and clean maritime (0.32%) type of aerosols. AOD retrieved from MODIS and MISR compared well over East Africa (EA), exhibiting moderate to high correlations. Spatial AOD patterns over EA characterized by low, moderate and high AOD centers. Significant positive trends in AOD were noticed over the northern parts of EA, consistent with those found in key meteorological parameters. Dominant aerosol types revealed varying percentage contribution over EA.

Description: ABSTRACT Southern Peru receives over 60% of its annual climatological precipitation during the short period of January–March. This rainy season precipitation exhibits strong inter-annual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. Improving existing seasonal prediction models of summertime precipitation could aid in water resource planning and allocation across this water-limited region. While various underlying mechanisms modulating inter-annual variability have been proposed by past studies, operational forecasts continue to be largely based on rudimentary El Niño-Southern Oscillation (ENSO)-based indices, such as Niño3.4, justifying further exploration of predictive skill. To bridge the gap between understanding precipitation mechanisms and operational forecasts, we perform systematic studies on the predictability and prediction skill of southern Peru's rainy season precipitation by constructing statistical forecast models using best available weather station and reanalysis data sets. We construct a simple regression model, based on the principal component (PC) tendency of tropical Pacific sea surface temperatures (SST), and a more advanced linear inverse model (LIM), based on the empirical orthogonal functions of tropical Pacific SST and large-scale atmospheric variables from reanalysis. Our results indicate that both the PC tendency and LIM models consistently outperform the ENSO-only based regression models in predicting precipitation at both the regional scale and for individual station, with improvements for individual stations ranging from 10 to over 200%. These encouraging results are likely to foster further development of operational precipitation forecasts for southern Peru. In this article, we first re-examined the characteristics of southern Peru precipitation and its relationship with ENSO by using newly collected rain gauge data and reanalysis data sets. Then we reviewed the current forecast skill of existing and potential existed forecasts. At last we introduced two simple statistical models to predict southern Peru precipitation anomalies at both regional and station levels, with both models demonstrating improvement over existing models based on retrospective forecast experiments.

Description: ABSTRACT Pan evaporation ( E pan ) is reported to have exhibited a decreasing trend in many regions of the world over the past several decades. However, recently, the latest studies have discovered the inconsistent phenomenon that the E pan of some regions showed an increasing trend with climate change. E pan is regarded as a critical indicator that plays a significant role in atmospheric evaporative demand, and its trend has an important significant indication to climate change and ecological environment changes. In this article, we adopted the PenPan model and the method of the total short-wave irradiance of the pan to reparameterize the PenPan-20 model for the Qinghai–Tibet Plateau (QTP). In addition, we employed sensitivity and a contribution model to analyse the attribution of changes in E pan under climate change over the QTP in 1970–2011. The results showed that the PenPan model can be applied to QTP. Furthermore, the results showed significant decreasing trends of E pan in 1970–2001 and insignificant increasing trends of E pan in 2002–2011. Therefore, we compartmentalized the two periods to analyse the cause of changing E pan by sensitivity and contribution rate. Trend analysis determined that the combined effects of decreasing net radiation and wind speed contributed to the decreasing of E pan in 1970–2001, and the increasing vapour pressure deficit contributed to the increasing of E pan in the study area in 2002–2011. Meanwhile, sensitivity analysis revealed that net radiation was the most sensitive factor. In addition, the results of analysis of the contribution rate were consistent with trend analysis. The dominant factor of changing E pan varied in different periods via qualitative and quantitative analysis. Distribution of meteorological sites and elevation of the Qinghai–Tibetan Plateau.

Description: ABSTRACT In the southwest Pacific (SWP) tropical cyclones (TCs) account for 76% of the regions natural disasters and have substantial economic, physical and environmental impacts on people and places. Therefore, information is needed to better understand when and where TCs are likely to occur, as this can aid in preparedness and planning. While there is a well-established relationship between Pacific Ocean sea surface temperature (SST) variability and tropical cyclogenesis (TC genesis) in the SWP, it does not fully explain the historical spatial and temporal variability observed. Therefore, this study aims to look beyond the Pacific and establish a new relationship between Indian Ocean SST variability and SWP TC genesis. This is achieved by statistically relating indices of Indian Ocean SST variability to SWP TC genesis positions. The physical mechanisms driving these observed relationships are then established by studying changes in the environmental conditions conducive to TC genesis. This analysis shows that Indian Ocean SST variability significantly modulates the clustering of SWP TC genesis, where warmer (cooler) SSTs in the eastern and western regions of the Indian Ocean result in a statistically significant north/east (south/west) migration of TC genesis by up to 950 km. Importantly, this relationship is shown to be consistent when the El Niño/Southern Oscillation (ENSO, the dominant Pacific mode) is in an inactive phase (ENSO neutral). Favourable TC genesis parameters including warm SSTs, increased relative humidity, anomalously negative 700 hPa vorticity, anomalously negative and low absolute 200–850 hPa vertical wind shear account for the observed shift in clustering. Furthermore, we show that the combined effect of ENSO/Indian Ocean SST variability results in varying risk profiles for island nations of the region, with the two climate modes either enhancing or suppressing individual impacts. Significantly, the findings from this study provide an opportunity for meteorological agencies to improve seasonal SWP TC outlooks. TC genesis, KDE contours and MCC for positive/negative phases of IOD E, IOD W and II during ENSO neutral conditions (NDJFMA). TC genesis, KDE contours and MCC for ENSO neutral seasons is also included for reference (bold frame).

Description: ABSTRACT The role that the Indonesian Throughflow plays on climate is investigated in an alternative scenario, expected during glacial ages. The equatorwards shift of the Southern Hemisphere westerlies found in glacial ages acts to decrease the Agulhas Leakage (AL) and the thermohaline circulation (THC) in the Atlantic. Recent results suggest that these changes are followed by an increased THC in the Pacific, through an inter-basin seesaw mechanism. The enhanced circulation in the Pacific demands thermocline water to cross the equator towards northern latitudes, which shifts the water source of the throughflow from the low-salinity North Pacific to the relative saltier South Pacific. It is shown that in this equilibrium, the salinity anomalies of the throughflow impact the inter-basin seesaw towards the restoration of the modern climate, enhancing the North Atlantic Deep Water (NADW) formation and decreasing the THC in the Pacific. These results are consistent with paleo-observations and provide new insights to interpreting the climate changes in glacial periods. The present investigation has found that in an alternative climate, where the thermohaline circulation in the Pacific ocean is intensified towards an Atlantic-like circulation, the Indonesian Throughflow acts to restore the circulation as it is known for the modern climate. Furthermore, our results show that many aspects observed in the tropical Pacific in glacial times, inferred from paleo-observations, might be explained by the impacts of the throughflow and its connection with the inter-basin seesaw mechanism.

Description: ABSTRACT The summer rainfall in China in 2016 exhibited a substantial intraseasonal feature, with an intensification in June and July but a suppression in August over the Yangtze River Basin and North China. The Madden–Julian oscillation (MJO) during the summer and its impact on rainfall in China are investigated by conducting observational analyses and diagnostic linear baroclinic model (LBM) experiments. A significant MJO activity in the summer is observed with three MJO episodes corresponding to three stages of rainfall in China. The LBM is utilized to diagnose the circulation response to the tropical heating forcing associated with each MJO episode. The results suggest that much of the atmospheric circulation linked to the anomalous rainfall is attributed to the strong MJO episodes. During June–July (August), the enhanced (suppressed) convection over the tropical Indian Ocean along with the suppressed (enhanced) convection over the South China Sea (SCS) to the western Pacific excite an ‘East Asian–Pacific’ north-eastward-propagating Rossby wave train, inducing anomalous low-level anticyclonic (cyclonic) flows over the northern SCS and the western North Pacific but cyclonic (anticyclonic) flows over North China. They lead to a westward (eastward) shift and strengthening (weakening) of the western Pacific subtropical high, thus favouring the intensification (suppression) in rainfall over the Yangtze River Basin and North China along with the opposite variation over South China. Relative to the first MJO episode, the MJO convection in the second episode causes a northward movement of the anomalous rainfall band from the Yangtze River Basin to North China. Apart from the impact on the above regions, the first (second and third) MJO episode favours an increase (reduction) in rainfall over Northeast China. A significant Madden–Julian oscillation (MJO) activity in the 2016 summer is observed with three MJO episodes corresponding to three stages of rainfall in China. The transition of the rainfall pattern is closely related to the propagation of the MJO. The atmospheric circulation linked to the anomalous rainfall can be modulated by the anomalous MJO convection through exciting a Rossby wave train and thus leading to the variability of the western Pacific subtropical high.

Description: ABSTRACT India is very prone to heat waves during April–June. The intra-annual variability of heat wave episodes over the east coast of India has been studied using 16-year NCMRWF global forecast system (NGFS) retrospective data. The objective of this study is threefold: (1) identification of heat wave episodes over the east coast of India, (2) intra-annual variability of heat wave episodes, and (3) which physical mechanism(s) is responsible for its occurrence and long-lasting? A total of ten heat wave episodes (100 hot days) were obtained for the period 2000–2015. The intensity of heat wave is found to be maximum (minimum) for 2015 (2007) episode. The average duration of heat wave episodes was 10 days, with the longest episode lasting for 20 days in the year 2003. Moreover, an average duration of severe heat wave is 3.5 days longer than that of a normal heat wave. The common feature observed in all heat wave cases is the presence of anticyclone in the upper troposphere and associated persistence high. This can cause sinking motion, which leads to surface warming due to adiabatic compression. The lack of soil moisture (SM) induces a positive feedback between the surface and the air above it, which amplifies the sensible heating and thereby increases surface temperature. The prevailed westerly anomalies over the study region which reduce the land–sea breeze result in heat wave. The heat wave episodes exhibit a significant intra-annual variability. Intensity of heat waves averaged over the east coast of India has shown an increase of 0.06 °C per heat wave. The geopotential height anomaly, vertical velocity, and SM exhibit significant intra-annual variability between the episodes and become decisive parameters for the maintenance and variability. The correlation coefficient between the maximum temperature and SM is found to be −0.56, indicating the importance of SM regulating the intensity of heat waves. Time-series of area-averaged maximum temperature ( T max ) (top panel), representing the intensity of heat wave, and the corresponding T max anomalies are shown in bars (bottom panel), illustrating the intra-annual variability of heat waves. The dashed black (red) lines represents climatological temperature + 4 (5) °C, respectively.

Description: ABSTRACT Recent and historical austral summer and winter rainfall characteristics have been widely investigated across southern Africa. However, a notable gap of knowledge remains for the Namibian region. This article presents the first extensive 19th century (1845–1900) hydro-climate history for central Namibia, derived from documentary evidence. Unpublished and published data sources were scrutinized in various archives and libraries in Germany, Switzerland, Namibia and South Africa. Missionary Carl Hahn's detailed diaries are the most valuable source of information for the earliest period until 1859. Other important sources of information include the Rhenish Missionary Society (RMS) annual reports and monthly ‘Berichte’ (news), station chronicles, official annual reports for the colonial period (1894 onwards) and letters/diaries by traders, travellers, etc. Climate information was transcribed, translated and organized chronologically. Using a five-point categorization system ranging from very wet (+2) to very dry (−2), each year was classified according to overall rainfall conditions during the rain season. A portion of the chronology is compared with instrumental rainfall data for Okahandja, Windhoek and Rehoboth and confirms good agreement. Possible associations between El Niño-Southern Oscillation (ENSO) phases and subsequent austral summer rainfall conditions are explored for central Namibia. Wetter years (42%) are over-represented in comparison to dry years (38%) during the second half of the 19th century in central Namibia, with a high percentage (42%) constituting either extremely wet or extremely dry years. Inter-annual rainfall variability between 1845 and 1900 seems more pronounced than elsewhere in southern Africa during this period. Extreme to very strong and prolonged El Niño (e.g. 1876–1878) and La Nina (e.g. 1865–1866) phases account for rare hydro-climatic synchronicity between southern African sub-regions and between continents of the Southern Hemisphere. Negligible relative rainfall trend for central Namibia from 1845 to 1900. Very high inter-annual hydro-climatic variability over central Namibia from 1845 to 1900. Extended and very strong to severe ENSO phases produce extreme climatic conditions and rare hydro-climatic synchronicity across southern African summer rainfall sub-regions, and even across continents of the Southern Hemisphere.

Description: ABSTRACT As an important bottom-up driver of ecosystem processes, rainfall is intrinsically linked to the dynamics of vegetation and species distributions through its effects on soil moisture content and surface water availability. Rainfall effects are thus spatially and temporally specific to different environmental role-players. Knowledge of its spatio-temporal pattern is therefore essential to understanding natural ecosystem flux and potential climate change effects. Climate change poses a serious threat to protected areas in particular, as they are often isolated in fragmented landscapes and confined within hard park boundaries. In consequence, a species' natural movement response to resulting climate-induced niche shifts is often obstructed. Long-term, accurate and consistent climate monitoring data are therefore important resources for managers in large protected areas like the Kruger National Park (Kruger). In this article we model local rainfall measurements as a function of global rainfall surfaces, elevation and distance to the ocean using a generalized additive mixed effects model to produce fine-scale (1 km 2 ) monthly rainfall surfaces from July 1981 to June 2015. Results show a clear seasonal cycle nested within an oscillating multi-decadal trend. Most noticeably, seasonality is shifting both temporally and spatially as rainfall moves outside of the typical dry/wet periods and areas. In addition, high-rainfall seasons are generally receiving more rainfall while low-rainfall seasons are receiving less. Northwestern regions of the park are experiencing more extreme annual rainfall differences, while far northern and southern regions show greater seasonality changes. The well-described north–south and east–west rainfall gradient is still visible but the spatial complexity of this pattern is more pronounced than expected. Taken together, we show that Kruger's spatio-temporal rainfall patterns are changing significantly in the short to medium term. The resulting raster data set is made freely available to promote holistic ecosystem studies and support longer-term climate change research ( http://dataknp.sanparks.org/sanparks/ ). Using generalized additive mixed effects models to explore the variability of local rainfall observations as a function of global rainfall surfaces, elevation and distance to the ocean. Results suggest significant change in spatio-temporal patterns of rainfall in the Kruger National Park, South Africa from 1985 to 2015.

Description: ABSTRACT We investigate methodological uncertainties associated with the standardized precipitation index (SPI) that result from limited record length, trends, and outliers. We use long, homogenous records from 14 Italian stations to investigate how specific features in the precipitation record affect construction of an underlying gamma probability function. We apply a resampling scheme to the long records in order to estimate confidence intervals associated with a range of precipitation characteristics. Stability in parameter estimation increases nonlinearly as record length increases. The resulting SPI estimates for 30-year reference periods have considerably more uncertainty than those made from 60-year records. In general, increasing record length beyond 60-years has limited benefits and, in the presence of a trend, may increase uncertainty. Extreme events also have significant influence on SPI estimates, even for records exceeding 60 years. Despite using stations from different geographic regions, each with unique precipitation characteristics, we find consistent confidence interval estimates across stations. These confidence intervals can be applied to specific time series to identify how trends, changes in variability, and outliers during a particular reference period influence SPI values. Estimates of the standardized precipitation index (SPI) have inherent uncertainties associated with limited record length, trends, and outliers. Despite the uniqueness of individual precipitation records, there is consistency in SPI confidence interval estimates across stations and distinct patterns based on record length. Such estimates can be applied to specific time series to identify how trends, changes in variability, and outliers during a particular reference period influence SPI values.

Description: ABSTRACT UK seasonal mean temperature and precipitation conditions are extremely variable from one year to the next but in the last decade have featured several cool, wet summers and mild, wet winters interspersed with some notable cold winter episodes. Jet stream variability is a major determinant of these fluctuations and is often represented by the North Atlantic Oscillation (NAO) index. Recent work has shown some evidence of promising predictability in the winter NAO from 1 to 2 months ahead, while summer predictability remains very limited. Although the phase and magnitude of the NAO influences total UK rainfall, there are regional variations which it does not explain. Here we examine the relationship between UK regional summer and winter precipitation and temperature and a range of North Atlantic atmospheric circulation indices. While the NAO shows a significant relationship with temperature in both seasons and summer rainfall over most of the UK, the picture in winter is more complicated, with other circulation indices such as the East Atlantic pattern explaining rainfall anomalies in southern England. Other indices also show significant relationships with precipitation in regions where the NAO does not. Because UK weather is determined by the interplay between different circulation indices, attention should be given to developing seasonal forecasts of other circulation indices to complement the NAO forecasts. We also find that some potential drivers of jet stream variability are significantly associated with UK temperature and rainfall variability, particularly in summer. This provides further scope for producing seasonal forecasts based directly on these drivers. Improved seasonal forecasts will be useful to a range of end users in agriculture, energy supply, transport and insurance industries and can be extended to other UK weather variables such as extreme rainfall events and storm frequency, and related metrics such as wind power capacity and solar energy. The winter North Atlantic Oscillation is predictable from a few months ahead, but does not explain all regional UK precipitation and temperature anomalies. We examine associations between a number of circulation indices and UK summer and winter temperature and rainfall patterns. The East Atlantic and Scandinavian patterns explain significant regional variations in UK weather, and some drivers of summer jet stream variability are directly associated with summer temperature and precipitation variability. There is potential to develop improved regional seasonal forecasts.

Description: ABSTRACT The North Pacific subtropical front (NPSTF) of sea surface temperature (SST) is an important subtropical feature in the North Pacific. In this study, we reveal that the inter-annual variability of the spring NPSTF has a robust correlation with the El Niño-Southern Oscillation (ENSO) in the following winter over the period of 1961–2016. When there is a strong spring NPSTF, anomalous cyclonic and anticyclonic circulations in the low troposphere occur to its north and south, respectively. The northeasterly wind anomaly associated with the anticyclonic circulation increases the climatological northeasterly wind over the subtropical Northeast Pacific, resulting in SST decrease via the wind–evaporation–SST feedback. The SST and wind perturbations propagate southwards from the subtropical to the eastern central equatorial Pacific in summer and grow via the Bjerknes feedback from summer to winter, eventually leading to a La Niña event in winter. A strong spring NPSTF induces an anomalous anticyclonic circulation to its south through both transient eddy activity and atmospheric heat source anomaly. The enhanced air temperature gradient due to a strong NPSTF increases the atmospheric baroclinicity, favouring an enhanced transient eddy activity over the NPSTF and to the north. The enhanced transient eddy activity triggers a significant negative height anomaly to the north via high-frequency transient eddy feedback forcing, which is conductive to an anticyclonic circulation over the subtropical North Pacific through the downstream effect of Rossby waves. On the other hand, the convergence and increased atmospheric baroclinicity related to the strong NPSTF act to enhance precipitation over the NPSTF and to the north, corresponding to the increased atmospheric heat source, which can also excite an anomalous anticyclonic circulation over the subtropical North Pacific. The spring NPSTF is negatively correlated with the ENSO in the following winter. Anticyclonic circulation due to a strong NPSTF in spring generates negative SST anomalies over the subtropical Northeast Pacific, which grow via the WES and Bjerknes feedback to a La Nina event in winter. Both transient eddy activity and atmospheric heat source play roles in the NPSTF inducing the anticyclonic circulation in spring.

Description: ABSTRACT This study provides an assessment of recent changes in near-surface air temperature over the central Adriatic region of Italy, focusing on extreme events at annual and seasonal scales. It investigates trends in selected indices calculated from quality controlled and homogenized daily temperature data recorded from 1980 to 2012 at 34 meteorological stations distributed over the territory. The results reveal overall warming tendencies, particularly pronounced in spring and summer, with significant increases in the duration of warm spells (WSDI) and in the frequency of warm days (TX90p) and warm nights (TN90p), summer days (SU) and tropical nights (TR). Moreover, cold-related extremes (cold spell duration (CSDI), cool days (TX10p) and cool nights (TN10p), frost days (FD) and icing days (ID)) show significant reductions, although of lower magnitudes, thus confirming the recent warming over the study domain. Prevalent increasing tendencies are also observed for absolute extreme temperature indices (highest and lowest daily values of maximum and minimum temperatures), but with more mixed and less uniform spatial patterns. Finally, the influence of large-scale circulation modes on temperature extremes is examined. The results highlight the presence of significant correlations between most of the selected extreme temperature indices and the East-Atlantic pattern, in particular for the warm season. This study examines trends in extreme temperature indices in the central Adriatic region of Italy for the period 1980–2012. The results show overall warming tendencies, particularly pronounced in spring and summer, with significant increases (reductions) in hot (cold) extremes. This study also investigates the influence of large-scale circulation patterns on extreme temperature variability and the results reveal that the registered recent warming is significantly correlated with the East Atlantic pattern.

Description: ABSTRACT This study analysed the characteristics of climate change (including temporal trend and spatial distribution of temperature and precipitation) in Yunnan Province, China during 1961–2011 based on the observed data from 22 meteorological stations, and its relationship with land use/cover change (LUCC) was also discussed. The results showed that: (1) Significant increasing trend in temperature was observed at the annual scale, especially for the period 1987–2011. At the seasonal scale, such trend was the most prominent in winter. (2) Temporally, the annual precipitation showed a non-significant decreasing trend, which was dominant by the rainy season; spatially, the annual precipitation showed the east-to-west and north-to-south increasing trends over this region. (3) This study analysed the impacts of elevation and geographical location on climate change patterns, and the statistical equations to estimate the annual temperature and precipitation as well as their changing rates were established based on longitude, latitude and elevation. (4) Through analysing the relationship between climate change and the LUCC, the correlation between the LUCC and temperature was stronger than that between the LUCC and precipitation. The results would be valuable for researchers and managers to better understand the characteristics of climate change as well as its relationship with the LUCC and to make better decisions in future. This article analysed the characteristics of climate change (including temporal trend and spatial distribution of temperature and precipitation) in Yunnan Province, China, for the period 1961–2011. This article investigated the impacts of elevation and geographical location on climate change, and the statistical equations to estimate the annual temperature and precipitation as well as their changing rates were established based on longitude, latitude and elevation. This article preliminarily presented the possible impacts of urbanization through analysing the relationship between climate change and land use/cover change.

Description: ABSTRACT Despite an increasing body of evidence from observed data that climate change is having a significant impact on different types of biogeophysical systems in the Midwest and Great Lakes region, there still remain critical questions of how quickly and how much climate will be altered over this region in the future. For this evaluation, we make use of 31 global climate model (GCM) projections from the Coupled Model Intercomparison Project, Phase 5 (CMIP5). Based on changes in temperature ( T ) and precipitation ( P ) over the Midwest, we selected ten GCM scenarios which (1) simulate historical climate well and (2) successfully capture the range of future climate from the entire CMIP5 ensemble. We then downscaled T and P projections to 1/16° gridded data sets for two different emission scenarios (RCP4.5 and RCP8.5) for three 30-year future periods using the Hybrid Delta (HD) statistical downscaling approach which was proven to be applicable for daily-scale application by a validation work using historical data. T is projected to increase across all seasons, with ensemble mean changes up to 6.5 °C by 2100 for the RCP8.5 scenarios. P increases up to 30% in spring and winter with decreasing snowfall to precipitation ratio, while summer P decreases moderately (−15%) by the 2080s. Changes in daily extreme events show similar seasonal patterns including increasing daily extreme P events in winter and decreasing P in summer. Growing season P may actually increase, however, despite projected P reductions in the warmest summer months. Regional warming results in decreased heating degree days (−1639 °C days, −32%) and increasing cooling degree days (+318 °C days, +957%) by 2080s, with overall net reductions in energy demand. Despite an increasing body of evidence that climate change is having a significant impact on different types of biogeophysical systems in the Midwest and Great Lakes region, there still remain critical questions of how quickly and how much climate will be altered over this region in the future. This study provides future daily temperature and precipitation at high resolution (1/16°) which can be used in many regional impact assessments, and also analyses the projected mean and extreme climate events.

Description: ABSTRACT Large-scale patterns of ocean surface temperature can influence weather across the globe and understanding their interaction with the local climate can improve seasonal forecasting of local temperature and precipitation. Here we focus on the combined interactions of the El Niño-Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO) in the Alabama–Coosa–Tallapoosa (ACT) and Apalachicola–Chattahoochee–Flint (ACF) river basins of the southeastern United States. Nonparametric ranks-sum tests of individual and coupled impacts of these teleconnections on the annual study area climate (1895–2009) found significant impacts. A positive AMO phase was associated with decreased precipitation and increased mean temperature while the negative AMO phase was associated with increased precipitation and decreased temperature. While an El Niño event generally increases regional precipitation, El Niño during a positive AMO or PDO phase resulted in precipitation below the long-term average in our study area. Because of many instances of El Niño being shared between AMO and PDO phase, the effects of the PDO and AMO on El Niño could not be distinguished. La Niña was associated with negative precipitation and increased temperature. The effects of La Niña on the temperature and precipitation anomaly were significantly increased during positive AMO and PDO phases. The coupled impacts of the aforementioned teleconnections demonstrate the necessity of including the effects of the AMO and the PDO when using ENSO-based forecasts. The significant shifts on the effects of teleconnections on area climate from AMO negative phase to AMO positive phase cast doubt on seasonal prediction for the study area based on the recent history (i.e. the use of the period 1950–2000 to predict seasonal climate since 2000). While an El Niño event generally increases regional precipitation, El Niño during a positive AMO or PDO phase resulted in precipitation below the long-term average in our study area. Because of many instances of El Niño being shared between AMO and PDO phase, the effects of the PDO and AMO on El Niño could not be distinguished. The effects of La Niña on the temperature and precipitation anomaly were significantly increased during a positive AMO and PDO phases.

Description: ABSTRACT We review recent climate changes over the Tibetan Plateau (TP) and associated responses of cryospheric, biospheric, and hydrological variables. We focused on surface air temperature, precipitation, seasonal snow cover, mountain glaciers, permafrost, freshwater ice cover, lakes, streamflow, and biological system changes. TP is getting warmer and wetter, and air temperature has increased significantly, particularly since the 1980s. Most significant warming trends have occurred in the northern TP. Slight increases in precipitation have occurred over the entire TP with clear spatial variability. Intensification of surface air temperature is associated with variation in precipitation and decreases in snow cover depth, spatial extent, and persistence. Rising surface temperatures have caused recession of glaciers, permafrost thawing, and thickening of the active layers over the permafrost. Changing temperatures, precipitation, and other climate system components have also affected the TP biological system. In addition, elevation-dependent changes in air temperature, wind speed, and summer precipitation have occurred in the TP and its surroundings in the past three decades. Before projecting multifaceted interactions and process responses to future climate change, further quantitative analysis and understanding of the change mechanisms is required. Responses of hydrosphere, cryosphere, and biosphere to changing climatic system on the TP. SOS means the start of vegetation growing season and EOS represents end of vegetation growing season.

Description: ABSTRACT The main objective of this study was to project changes in the evolution of drought characteristics (frequency, duration and magnitude) during the 21st century in lowlands, highlands and mountainous regions in the Czech Republic (CR). We focused on the multi-scalar nature of droughts as a function of the variables that govern the balance of moisture during climate change, such as precipitation, which supplies moisture, and temperature, which modulates evapotranspiration. Thereby, this issue is addressed with two drought indices, i.e. the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI), for various lags (1, 3, 6, 12 and 24 months). To assess the impact of climate change on drought characteristics, a set of eight regional climate models (RCMs) simulations were selected for further analysis driven by five different global circulation models (GCMs) carried out in the frame of Euro-CORDEX. Future drought changes were developed for the two representative concentration scenarios (RCP4.5 and RCP8.5). For the temporal evolution of the droughts, the monthly drought indices were calculated over the entire study period from 1961 to 2100. The SPEI showed a higher frequency in the categories of severe droughts and extreme droughts than the SPI, while the SPEI yielded fewer events in the extreme wet categories. The probability distribution of the SPEI-6 under the RCP8.5 scenario shifted more than one and a half standard deviations in lowlands at the end of the century, peaking at −1.65 (with a probability of 10.5%). This meant that severe droughts, according to the current climate criteria, will become the new norm in the period 2071–2100. Outlook of the temporal evolution of the SPEI and SPI at a 12-month lag for observed (1961–2015) and the projected historical (1970–2005) and future (2006–2100) drought and wetness events under the pathway scenarios for RCMs of the Euro-CORDEX runs in the lowland region. Outlook of the drought frequency (%) per region at 6-month lag (SPEI/SPI) for historical (1961–2005 or 1970–2005: Hist) and future (2006–2100: Fut) simulations for eight RCMs of the Euro-CORDEX runs under the RCP8.5 scenario. Box plots–central line: median; box: interquartile range (IQR); whiskers: outlier limits (1.5 × the IQR). Region I is characterized by the warmest climate in the country, the highest potential evapotranspiration during the growing season and the most intensive agriculture (lowlands). Region II is characterized by a moderate-temperature regime and less intensive agriculture (highlands). Region III is mostly forested and is characterized by limited agricultural production (mountainous).

Description: ABSTRACT The fragile ecosystem, scarce water resources, and limited ecosystem resilience of Xinjiang, China make the region especially vulnerable to climate change. Researchers need reliable analyses of climate change trends to formulate regional mitigation and adaption strategies and to support sustainable development. Therefore, two statistical downscaling methods and the combination of a Mann–Kendall test with Co-Kriging interpolation were used to investigate the spatiotemporal characteristics of climate change in Xinjiang based on the ensemble of 37 general circulation models (GCMs) in 2021–2060. The reliabilities of single run and ensemble downscaling results of GCMs were evaluated by 69 meteorological stations over the period 1965–2004. The correlation coefficients (CC) with the observations for precipitation and temperature ranged between 0.4–0.8 and 0.9–0.99 in the reference period, respectively. CC improved to 0.87 and was close to 1 after downscaling for precipitation and temperature, respectively. A pronounced increase of ca . 0.27–0.51 °C decade −1 was projected overall, and especially for Representative Concentration Pathway (RCP) 8.5 in northern Xinjiang. In general, the precipitation changed by −1.66 to 6.83% decade −1 while varying seasonally and spatially; a declining tendency emerged in the western regions of Xinjiang during summer. More extreme rainfall events are predicted to occur in summer and autumn months, while warmer extremes would be concentrated in August. The climate in Xinjiang will continue to become warmer and wetter. Nevertheless, Western Xinjiang will experience a warmer and drier climate in summer and autumn. These projections of climate change in the near future are able to provide useful information for the development of potential mitigation measures and adaptation strategies. Multiple circulation mechanisms are also suggested accounting for the changes in precipitation and temperature which will benefit the understanding of the possible drivers of climate variability in this region. The location of Xinjiang Uygur Autonomous Region and meteorological stations used in this study. An inset map shows the location of Xinjiang within China.

Description: ABSTRACT Understanding the spatio-temporal variability of rainfall over mountainous regions such as the Andes is crucial for the maintenance of water resources and ecosystems. This study provided a comprehensive analysis of the signal, statistical significance and spatial pattern of rainfall trends in central and southern Peruvian Andes (CSPA) from 1965 to 2010. Rainfall from 47 quality-controlled rain gauge stations was examined using the hydrologic calendar year. Total and extreme rainfall indices proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated and trends were examined with Mann–Kendall test and Sen's slope estimator. Significant regional patterns of changes in rainfall extremes were investigated and compared with previous studies. Four major regions of stations were identified based on principal component analysis and clustering techniques: Amazon, central Pacific, southern Pacific and Titicaca basins. Statistically significant trend patterns showed that the annual total rainfall has decreased in the Amazon basin, despite the increase in the number of rainy days and some extreme rainfall indices. Decrease in 1-day and 5-day yearly maximum rainfall was observed in central Pacific, along with an increase in the number of wet days. Positive trends in indices related to the intensity of very strong daily rainfall were detected in southern Pacific. Titicaca basin showed an increase in the intensity of rainfall extremes. Rainfall variability and trends were evaluated during contrasting El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Most stations in the CSPA exhibited positive (negative) anomaly of total and extreme rainfall indices (consecutive dry days) during La Niña (El Niño) years. Positive (negative) anomalies of annual total rainfall and consecutive dry days during positive (negative) PDO occurred in the Amazon, southern Pacific and Titicaca basins, respectively. The ENSO–PDO conditions may have influenced the complex and mostly non-statistically significant long-term trends in CSPA. Trends in total and extreme rainfall indices over central and southern Peruvian Andes during 1965–2009 water years: (a) wet days annual rainfall (PRCPTOT), (b) consecutive dry days (CDD), (c) very wet day rainfall (R95p) and (d) percentage of wet days (Wdays).

Description: ABSTRACT Errors are quite large in the simulated carbon and water fluxes obtained by global models used for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, and reducing those errors is important for improving our confidence about these models and their projections. Errors in model parameter values are a major cause of those large modelling errors but can be significantly reduced if model parameter values are optimized. While parameter optimizations have been carried out at local sites or regional scales, parameter optimizations have been rarely conducted at the global scale because of the high computing costs required to optimize a large (〉100) number of model parameters. In this study, we used an adaptive surrogate modelling based optimization (ASMO) method to maximize the match between simulated monthly global gross primary production (GPP) and latent heat flux (LE) derived by two global land surface models (LSMs) and the model-data products for global GPP and LE from the 1982–2008 period generated by the Max Plank Institute. The ASMO method only required a few hundred model runs to find the optimal values of all optimized parameters for the two global LSMs [the Australian Community Atmosphere-Biosphere-Land Exchange (CABLE) and joint UK land environment simulator (JULES)]. Our results show that up to 65% of the model errors can be reduced by parameter optimization for most of the plant functional types (PFTs) and that the model performances of CABLE and JULES are significantly improved at 72 and 93% of the land points, respectively. At last, we discuss the limitations of this work and recommend that parameter optimization based on surrogate modelling using various observational data sets and acceptable prior information of uncertainties in model structure and observations should be considered as a key step in improving the performance of global LSMs or model intercomparisons. Automatic parameter optimization of global land surface models for global gross primary production and latent heat flux can be achieved with 〈700 model runs. Parameter optimization can significantly improve carbon and water cycle simulation at land point, PFT (as shown in the image), and global scales. Parameter optimization using various observational data sets is recommended as a key step in improving land model performance.

Description: ABSTRACT Previous studies documented that El Niño (EN) events are in general associated with negative phases of the Southern Annular Mode (SAM). EN 2015–2016 (EN15–16) was one of the three strongest events ever recorded. However, it was associated with a SAM positive phase of extreme intensity. Furthermore, while the negative linear relationship between ENSO and SAM during the most recent period (1986–2014) was significant and associated with a narrow uncertainty band, the combined condition of both climate patterns in the EN15–16 event was an outlier. The EN15–16 influence on the austral summer circulation anomalies at the extratropical and polar regions of the Southern Hemisphere was considerably altered by the strong SAM positive phase, which was evident not only at the troposphere but also at the stratosphere. Such circulation changes resulted in unusual regional impacts, such as negative anomalies of surface air temperature in western Antarctic Peninsula and negative precipitation anomalies in southeastern South America, ever recorded for previous strong EN events. Further research is needed to better understand the mechanisms explaining the SAM behaviour during 2015–2016 and its implication for climate predictability on seasonal timescales. Previous studies documented that El Niño (EN) events are in general associated with negative phases of the Southern Annular Mode (SAM). EN 2015–-2016 (EN15–-16) was one of the three strongest events ever recorded. However, it was associated with a SAM positive phase of extreme intensity. That combination of climate patterns altered the response of the extratropical circulation in the Southern Hemisphere (SH) typically expected in strong EN. Therefore, the purpose of this work is to analyse the main characteristics of the SAM activity between 2015 and 2016, and its role in modulating the EN15–-16 influence on the climate anomalies in the SH. Boxplots of the detrended SAM values associated with the Historical EN events (blue) and 7 strongest EN events (red) for ASO, SON, OND, NDJ, DJF, and JFM. Crosses indicate the SAM values for the seasons of 2015–-2016.

Description: ABSTRACT We analyse recent trends and variability of observed near-surface wind speed from 19 stations across Saudi Arabia (SA) for 1978–2013. The raw wind speed data set was subject to a robust homogenization protocol, and the stations were then classified under three categories: (1) coast, (2) inland and (3) mountain stations. The results reveal a statistically significant ( p  〈 0.05) reduction of wind speed of −0.058 m s −1 dec −1 at annual scale across SA, with decreases in winter (−0.100 m s −1 dec −1 ) and spring (−0.066 m s −1 dec −1 ) also detected, being non-significant in summer and autumn. The coast, inland and mountain series showed similar magnitude and significance of the declining trends across all SA series, except for summer when a decoupled variability and opposite trends of wind speed between the coast and inland series (significant declines: −0.101 m s −1 dec −1 and −0.065 m s −1 dec −1 , respectively) and the high-elevation mountain series (significant increase: +0.041 m s −1 dec −1 ) were observed. Even though wind speed declines dominated across much of the country throughout the year, only a small number of stations showed statistically significant negative trends in summer and autumn. Most interestingly, a break in the stilling was observed in the last 12-year (2002–2013) period (+0.057 m s −1 dec −1 ; not significant) compared to the significant slowdown detected in the previous 24-year (1978–2001) period (−0.089 m s −1 dec −1 ). This break in the slowdown of winds, even followed by a non-significant recovery trend, occurred in all seasons (and months) except for some winter months. Atmospheric circulation plays a key role in explaining the variability of winds, with the North Atlantic Oscillation positively affecting the annual wind speed, the Southern Oscillation displaying a significant negative relationship with winds in winter, spring and autumn, and the Eastern Atlantic negatively modulating winds in summer. Wind speed declined significantly across Saudi Arabia for 1978–2013. A recent break in the stilling has been detected for 2002–2013. Atmospheric circulation modes partly explain the variability of surface winds.

Description: ABSTRACT In this study, potential impacts of the North Pacific subarctic frontal zone (SAFZ) variation, including its intensity variation and meridional shift, upon the subseasonally varying North Pacific storm track are investigated by using the 100-year reanalysis data sets. Regression analysis indicates that the changes in the SAFZ intensity and meridional position have significant influence on the North Pacific storm track, which intensifies with the strengthening of the SAFZ and moves northwards following the northwards shift of the SAFZ. However, the storm-track response pattern exhibits distinct differences from one calendar month to another. Specifically, the storm-track response to the SAFZ intensity variation is strongest in February and March; while its response to the SAFZ meridional shift is most pronounced in November and December. However, the storm-track response is relatively weak in January. Further analysis shows that the intensified (or northwards shifted) SAFZ would result in changes in the near-surface baroclinicity and hence affects the storm track, while the weak storm-track response in January is not the result of the anomalous near-surface baroclinicity. The investigation of the local energetics reveals that changes in the baroclinic energy conversion (BCEC) associated with the SAFZ variation are consistent with the storm-track anomalies, indicating that the BCEC plays a crucial role in modulating the subseasonal changes in the storm-track response. In January, the weakened BCEC contributes to the reduced storm-track response to the SAFZ variation. This study revealed that the storm track intensifies with the strengthening of the subarctic frontal zone (SAFZ) and moves northwards following the northwards shift of the SAFZ as shown in the figure. The storm-track response to the SAFZ intensity variation is strongest in February and March, while its response to the SAFZ meridional shift is most pronounced in November and December. The storm-track response is relatively weak in January.

Description: ABSTRACT Soil moisture affects hydro-climate processes by altering water and energy exchanges between land surface and atmosphere. Understanding of the predictability of soil moisture is not only important for a skillful forecasting of seasonal hydro-climate, but also for agricultural drought early warning. This paper assesses seasonal forecast skill and potential predictability of soil moisture directly produced by climate models, and investigates an optimal combination of different models over China. A set of 29-year hindcasts for soil moisture from six North American Multi-model Ensemble (NMME) models are verified against ERA Interim reanalysis. Results show that soil moisture predictability, which is defined by anomaly correlation under a perfect model assumption, is higher than forecast skill in all models, suggesting that soil moisture prediction may have a room for improvement. Except the CESM model, NMME climate forecast models with higher predictability also have higher forecast skill, where predictability is positively correlated with forecast skill with p 〈 0.01 across different lead times. Soil moisture forecast skill from NMME simple arithmetic mean is higher than any individual models, and the skill is further improved through an optimization of model weights with a cross validation procedure. As compared with simple ensemble mean, the optimized superensemble mean reduces root mean squared error by 19 and 7% for seasonal mean soil moisture forecast during winter and summer seasons, respectively, and increases correlation by about 10%. This study suggests that soil moisture forecasts directly produced by climate models, when combined appropriately, can provide useful information for climate service. Seasonal mean soil moisture predictability ( x -axis) versus forecast skill ( y -axis) in terms of anomaly correlation at different lead time. Different colors represent different models. All statistics are calculated by using NMME hindcasts during 1982–2010.

Description: ABSTRACT Regional climate models (RCMs) from the North American Regional Climate Change Assessment Program (NARCCAP) are compared with the two gridded precipitation data sets [Climate Prediction Center (CPC) and the University of Washington (UW)] and the North American regional reanalysis (NARR) to examine if RCMs are able to reproduce very heavy precipitation under similar physical conditions seen in observations. The analysis focuses on contemporary climate (1982–1999) in an upper Mississippi region during the summer (June–July–August) months and utilizes output from NARCCAP RCMs forced with a reanalysis and atmosphere–ocean global climate models (AOGCMs). The NARCCAP models generally reproduce the precipitation frequency versus intensity spectrum seen in observations up to around 25 mm day −1 , before producing overly strong precipitation at high intensities. CRCM simulations produce lower precipitation amounts than the rest of the models and observations past the 25 mm day −1 threshold. Further analysis focuses on precipitation events exceeding the 99.5th percentile that occur simultaneously at several points in the region, yielding ‘widespread events’. Apart from the CRCM and EPC2 simulations, models and observations produce peaks in widespread events during 0300–0900 UTC, although the models typically produce slightly weaker intensities compared to observations. Widespread precipitation falls too frequently throughout the day, especially between 1500 and 2100 UTC, compared to observations. Composite precipitation shows inter-model differences in magnitude and location of widespread events. Examination of additional fields shows that NARCCAP models produce credible representations of very heavy precipitation and their supporting environments when compared to the NARR. Composite daily precipitation during widespread very heavy events for observations and RCM simulations. Contour scale for all plots is on the bottom right, in mm day −1 . Each plot uses the native RCM projection, which accounts for the subtle differences in the region covered. Observations are transformed to the NARR grid for comparison.

Description: ABSTRACT Aspects of forecast skill in predicting seasonal characteristics using global climate models (GCMs) are assessed over South Africa. The GCMs output is configured to predict number of rainfall days at South African Weather Service stations exceeding pre-defined threshold values for the austral summer seasons and to predict the rainfall totals of the onset months of the rainy seasons for eight homogeneous rainfall regions of South Africa. Using canonical correlation analysis (CCA) as statistical downscaling technique through model output statistics, the forecast skill levels of coupled ocean–atmosphere and uncoupled atmospheric models are determined through retro-actively generated hindcasts. Both downscaled models have skill in predicting low and high number of rainfall days exceeding pre-defined thresholds for the austral summer seasons as well as rainfall totals of onset months. In addition to the forecast verification results, CCA pattern is performed to determine the dominating atmospheric circulation systems predicted to be controlling rainfall variations for the seasons and months of interest. CCA patterns for both the GCMs indicate that usually when there are anomalously negative (positive) predicted 850 hPa geopotential heights over South Africa, there are anomalously wet (dry) conditions over most parts of South Africa. The work has paved the way for the operational production of seasonal rainfall characteristics over South Africa in real time. This study established that the two climate models run at the South African Weather Service are capable of predicting number of rainfall days exceeding pre-defined thresholds for the austral summer seasons as well as the onset months of the rainy seasons. It was also found that in general similar atmospheric circulation systems are responsible for seasonal rainfall and number of rainfall days within seasons.

Description: ABSTRACT Homogeneous meteorological data are a prerequisite for reliable climatological studies. This paper investigates the homogeneity of wind data from 213 m high Cabauw tower located in The Netherlands. The wind measurements are conducted at 10, 20, 40, 80, 140 and 200 m above ground. The analysed data cover the period from February 1986 to January 1997 and from April 2000 to December 2015. This study presents the first homogeneity analysis of wind data from a tall meteorological mast. Homogeneities of wind speed and wind direction series were investigated independently using the ReDistribution Method. Overall, the wind measurements at Cabauw tower are very homogeneous. The only wind speed inhomogeneity was detected at 200 m above ground and it seems to be, at least to a certain extent, caused by the rapid expansion of the town of Lopik in the 1990s. Lopik's growth to the west, however, only influenced the east winds on the Cabauw tower. Small inhomogeneities in wind direction data were detected at 20, 40 and 80 m levels, whereas a fairly large inhomogeneity was observed at 10 m above ground. Several potential causes of inhomogeneities in wind direction data are discussed, but the major contributor could not be determined with certainty. In addition, the homogeneity of real measurements from Cabauw tower is compared against the synthetically created wind data for Cabauw tower using the Monte-Carlo method of random sampling. The results show that the detected anomalies are not due to the random noise in the time series. The first homogeneity analysis of wind data from a tall meteorological tower. Wind data from the 213 m high Cabauw tower in The Netherlands have several weak wind direction inhomogeneities and a single wind speed inhomogeneity. The potential causes for inhomogeneities determined and discussed.

Description: ABSTRACT North-East Indian Monsoon rainfall (NEIMR) during October–December is of immense socio-economic importance to the agriculture-dependent population in the southeastern peninsular India. NEIMR is subject to extreme year-to-year and intra-seasonal variability that needs to be understood to enhance climate resilience. In this study, we employed hidden Markov model to characterize the spatio-temporal variations of NEIMR at pentad time step and its probability of occurrence during 1982–2014. The results indicated the dominant presence of three rainfall states during the NEIMR season, which were the wet (State-1), coastal wet (State-2), and dry (State-3) states. Seasonal total NEIMR was significantly and positively correlated with the frequency of State-1, whereas it was negatively correlated with that of State-3, indicating a crucial role of the rainfall states in determining water requirements in the southeastern peninsular India. The rainfall states were associated with distinctive atmospheric circulation and surface temperature conditions, particularly the wet (State-1) and dry (State-3) conditions. Wet conditions were characterized by enhanced cyclonic activities and increased moisture convergence at 850 hPa over the southeastern peninsular India and its neighbouring oceanic regions (Bay of Bengal and Indian Ocean). In contrast, dry conditions were associated with anticyclonic circulation and reduced moisture convergence at 850 hPa. The plausible physical mechanisms behind the wet (dry) condition could be that anomalous warmer (cooler) land temperature above 20°N induced lower (higher) sea level pressure anomalies and drove anomalous southwesterly (northeasterly) surface winds over the NEIMR region. These anomalous surface winds and the associated lower level cyclonic (anticyclonic) circulations could enhance (suppress) moisture transport from the convergence regions over the Bay of Bengal and northern Indian Ocean into the southern peninsular India. This study revealed the pentad variability of NEIMR with the classified three rainfall states and identified the key atmospheric circulation and surface temperature conditions linked to these rainfall states. This study revealed the pentad variability of North-East Indian Monsoon rainfall (NEIMR) with the classified rainfall states. The plausible physical mechanisms behind the wet state of NEIMR could be that anomalous warmer land temperature induced lower sea level pressure and drove anomalous southwesterly surface winds. These anomalous surface winds and the associated lower level cyclonic circulations could enhance moisture transport from the convergence regions over the Bay of Bengal and northern Indian Ocean into the southern peninsular India.

Description: ABSTRACT The far eastern tropical Pacific experienced a rapid, marked warming in early 2017, causing torrential rains along the west coast of South America with a significant societal toll in Peru and Ecuador. This strong coastal El Niño was largely unpredicted, even a few weeks before its onset, and it developed differently from either central or eastern events. Here we provide an overview of the event, its impacts and concomitant atmospheric circulation. It is proposed that a remotely forced, sustained weakening of the free tropospheric westerly flow impinging the subtropical Andes leads to a relaxation of the southeasterly (SE) trades off the coast, which in turn may have warmed the eastern Pacific throughout the weakening of upwelling in a near-coastal band and the lessening of the evaporative cooling farther offshore. As depicted in this GPM radar image, torrential rains afflicted the otherwise arid coast of Ecuador and Peru from January to April 2017, resulting in a death toll of at least 200 and widespread damage to civil works and infrastructure. The storms occurred in connection with a very strong and largely unpredicted coastal El Niño, whose essential features and plausible trigger mechanism are described here.

Description: ABSTRACT The article demonstrates the impact of atmospheric circulation on the long-term variability of cloudiness (amount and certain cloud genera) in Kraków based on midday observations of the amount and genera of clouds in the period from 1 January 1906 to 31 December 2015. There was found statistically significant (although rather moderate) correlation between circulation indices and the frequency of cloud cover consisting of a single cloud genus or a group of clouds. The 11-year moving averages of frequency of occurrence of one-genus cloud cover show periods of alternating increasing/decreasing trends, some of which are multi-decadal. Decreasing trends, lasting till now, are shown for Cirrostratus , Nimbostratus and Stratus beginning from the 1920s to 1930s and for Altostratus from the 1970s. The Cirrus , Stratocumulus and Cumulus trends are generally increasing from the 1920s, 1950s and 1950s, respectively. The article demonstrates the impact of atmospheric circulation on the long-term variability of cloudiness (amount and certain cloud genera) in Kraków. There was found statistically significant (although rather moderate) correlation between circulation indices and the frequency of cloud cover consisting of a single cloud genus or a group of clouds.

Description: ABSTRACT This study explores the possible causes of rainfall distribution over the two major oceanic raining regions of the north Bay of Bengal (nBoB) and the east equatorial Indian Ocean (eEIO). Despite 17% difference in vertically averaged humidity, there is almost 34% difference in mean rainfall over these two regions. The climatological seasonal [June–September (JJAS)] mean (standard deviation) rainfall over nBoB region is always higher (lower) than that over the eEIO region in all the independent data used. The eEIO region has a much larger percentage of low stratiform and convective rainfall (〈5 mm day −1 ) distribution as compared to nBoB, which is totally opposite in case of moderate stratiform and convective rainfall (〉5 mm day −1 ) distribution. This is further substantiated by a much lower values of outgoing long-wave radiation (OLR) in nBoB (〈200 W m −2 ) as compared to the eEIO (217 W m −2 ) region. Mean Hadley circulation along with relative vorticity/divergence profile supports more intense (gentle) updrafts over nBoB (eEIO) region. Latent heat (LH) is almost three times at the upper level (∼8 km) in case of nBoB as compared to eEIO; however, at the lower level (∼3 km) LH is marginally higher over eEIO region. Microphysical variables, namely cloud ice optical thickness and cloud ice water path, are in much larger quantities over nBoB as compared to eEIO. Furthermore, the cold (warm) rain processes dominate among other microphysical processes over nBoB (eEIO) region. Thus, the interplay among large-scale dynamics, thermodynamics and microphysics is very crucial in the formation of deep clouds and convective rain over the nBoB region and similarly shallow clouds and stratiform rain over the eEIO region. This study will be very useful to guide present-day coupled models for proper representation of different rain components over the nBoB and eEIO region. Schematic of different types of cloud and their associated processes over the (a) nBoB region and (b) eEIO region.

Description: ABSTRACT This article analysed two typhoon seasons (1998 and 2016) over the western North Pacific (WNP) with similar preceding background conditions of the tropical Pacific sea surface temperature (SST). Following the strong El Niño event in the preceding winter, the typhoon season was inactive in 1998 while active in 2016. Compared with 1998, the monsoon trough (MT) in 2016 shifted more eastwards, leading to an increase of the mid-level water vapour, lower-tropospheric relative vorticity and upper-tropospheric divergence, and a decrease of the vertical wind shear. Additionally, the eastwards extension of the MT in 2016 induced more active tropical depression (TD)-type waves than those in 1998. The analysis of the energy budget suggested that the eastwards shift of the MT during the 2016 typhoon season provided increased eddy kinetic energy for typhoon genesis, due to the joint contributions of the meridional shear of the mean zonal winds and the zonal wind convergence over the WNP. Moreover, the WNP entered a La Niña-like SST pattern after July 2016. The relatively slower developing process of this pattern sustained the warmer SST anomalies and the anomalous cyclonic circulation, which the eastwards extension of the MT can be attributed. Hence, compared to 1998, the active typhoon season in 2016 is attributed to the eastwards extension of the MT, more active TD-type wave activities, and slow developing process of a La Niña-like SST pattern in 2016 typhoon season. Numbers of typhoon geneses over the WNP (0–30°N, 100°–180°E) during May–December in 1998 (blue bars) and 2016 (red bars).

Description: ABSTRACT Precipitation data of finer timescale and higher spatial density are crucial for continuous hydrological modelling and flood risk assessment. Disaggregation methods are often used to transform the coarser-timescale precipitation data into finer resolutions. The nonparametric approach based on method of fragments (MOF) has received broad attention in precipitation disaggregation literature, given its superiority in reproducing the at-site statistical attributes. However, a detailed literature review has shown that the MOF-based resampling approaches are mainly focused in the single-site precipitation disaggregation context, which may subject to limitations such as the unavailability of at-site precipitation records and the incapability to preserve the inter-site correlation structure. To address these issues, we propose three resampling approaches based on MOF. The first approach is a single-site interval-based resampling approach which only draws subdaily fragment vectors from at-site record. The second one extends the first one to a regionalized version where subdaily fragment vectors are drawn from both the at-site and neighbouring stations. The third one is a multi-site approach developed to preserve the observed inter-site correlation. The performances of the three methods are evaluated with applications to daily-to-hourly precipitation disaggregation at six rain gauges in Singapore and eight precipitation stations in Wangkuai reservoir catchment in northern China. An elaborate list of performance measures, including standard validation statistics, spatial correlation, inter-day connectivity, annual extreme analysis, and intra-day dry and wet spell characteristics are used to assess the performance. The proposed three methods are shown to be effective in reproducing the at-site attributes, and no significant deterioration of performance is observed when moving from the single-site method to the regionalized and multi-site versions. As expected, the multi-site approach is the only one method that is able to reconstruct the spatial correlation in the disaggregated precipitation field. The approaches can be applied for daily-to-subdaily precipitation disaggregation in different regions. Three resampling approaches, i.e. the singe-site interval-based resampling, the regionalized approach, and the multi-site approach based on method of fragments are proposed for daily-to-hourly precipitation disaggregation. All three approaches are capable of reproducing the at-site statistical attributes. Only the multi-site approach is able to reconstruct the spatial correlation in the disaggregated precipitation field.

Description: In this study six wooden Stevenson screen configurations (five aspirated, one non-aspirated) were evaluated at the Centre for Atmospheric Research Experiments in Egbert, Ontario, Canada. The field experiment was performed over a 1-year period to evaluate aspirated and non-aspirated Stevenson screen configurations used at the Meteorological Service of Canada’s Automated Weather Stations. The results show the non-aspirated screen is warmer than the aspirated screen duct location by 0.11 °C on average with a significant increase in the maximum daily temperature of 0.22 °C due to radiant heating effects. Temperature differences up to 2.1 °C were observed between the aspirated and non-aspirated screens with a mean increase of 0.46 °C following 30-min periods of mean global radiation greater than 200 W/m 2 and mean wind speed less than 2 m/s. Temperature differences between the two screens are more variable with standard deviations up to 0.3 °C for wind speeds below 2 m/s. The maximum daily temperature for the historic minimum and maximum thermometer locations and upper regions of the aspirated screen is also found to be significantly warmer during radiant heating conditions. The three locations within the aspiration duct provided very similar results with mean differences of −0.02 and −0.01 °C below the probe uncertainty. The aspirated Stevenson screen with motor off produced low overall bias with lower maximum daily temperatures and higher minimum daily temperatures compared to the aspirated screen. Comparison between the historic wooden frame and new aluminium mounting is not significant with the wooden frame cooler by 0.02 °C overall. Differences between the new aluminium and new plastic ducts showed similar results of 0.02 and 0.01 °C overall. The aspirated Stevenson screen configuration is recommended at new Automatic Weather Station installations where AC power is available. The non-aspirated type B Stevenson screen exhibits increased temperature relative to the aspirated screen due to relative heating particularly during periods of global radiation greater than 200 W/m 2 and wind speed less than 2 m/s. For increased wind speeds the influence is diminished due to natural aspiration of the non-aspirated screen. The temperature differences between the two screens are more variable with standard deviations up to 0.3°C for wind speeds below 2 m/s.

Description: This study addresses the impact of projected changes to northeast monsoon on rice yield during rabi season (September–December) in Tamil Nadu by using a three-step approach. First, coarse-resolution global climate models that realistically capture the mean monsoon characteristics were selected. Second, lateral and boundary conditions taken from selected global models’ projections are employed to run a high-resolution regional climate model. Third, climate variables from regional model being fed into panel data regression model. For different scenarios and for mid and end of century projections, in conjunction with projected rainfall, a comprehensive assessment is carried out to underscore the sensitivities of maximum and minimum temperatures under different stages of rice production, viz. vegetative, reproductive and maturity phases, and to the concept of growing degree days (GDD, cumulative heat effect). Irrespective of scenarios, in response to an increase in projected monsoon rainfall and surface temperature conditions, the regression model estimates an increase of rice yield of about 10–12% by mid-century and 5–33% by the end of the century. In the regression model, the baseline coefficients were estimated from observed rainfall and temperature available from India Meteorological Department (IMD). The projected changes in rice yield, however, remain unchanged for baseline coefficients estimated from regional climate model outputs (forced by reanalysis products) rainfall and temperature. The robust results obtained here provide confidence to the findings. This study addresses the impact of northeast monsoon on rice yield during rabi season in Tamil Nadu, southern India by using a high-resolution regional climate model. A comprehensive assessment is performed to underscore the sensitivities of maximum and minimum temperatures and growing degree days under different stages of rice production viz., vegetative, reproductive and maturity phases. Irrespective of scenarios, the regression model estimates an increase of rice yield of about 10–12% by mid-century and 5–33% by the end of the century.

Description: This study demonstrates a methodology to construct short-duration rainfall intensity–duration–frequency (IDF) curves and to quantify the variability in the rainfall intensities for different return periods with respect to the changing climate. A dynamical downscaling approach using the regional climate model (RCM) Weather Research and Forecasting (WRF) has been used to assess present and future climates using the downscaling of an ensemble of three global climate models (GCMs) (CSIRO-ACCESS1.3, MPI-ESM-MR ECHAM6 and NIES-MIROC5) under the Coupled Model Intercomparison Project phase 5 (CMIP5). Furthermore, a statistical approach using the well-known simple scaling method has been applied to extend the 6-hourly WRF precipitation output to the finer temporal scale of 10 min. The short-duration IDF curves were then constructed for the present and future climates under two representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5. A preliminary examination for this case study over Bac Ninh, an industrial area in the northern Vietnam, shows that there is a substantial increase in short-duration rainfall intensity in the future with respect to the baseline climate. The highest increase is towards the end of the century (2071–2100) ranging from 56 to 61% for a 10- and 100-year return period for 24-hr duration, respectively, while the increase is about 40–45% for the 10-min duration. These results strongly suggest that severe flooding in the future climate over the study region may be likely. The study results might be useful for policymakers and infrastructure planning and for insurance companies around the study area. Projection of simple scaling log–log-scale IDF curve for Bac Ninh using ensemble WRF: return periods (a) 10 years, (b) 25 years, (c) 50 years, (d) 100 years; (1) 2011–2040, (2) 2041–2070, (3) 2071–2100.

Description: In this study, we derive new time-series of monthly-mean surface air temperature for Switzerland that range back to 1864 and represent area-mean conditions over the country and three major sub-regions. The methodology integrates data from a small sample (19 stations) of homogenized long-term series and from a high-resolution (2 km) grid dataset over a short (20 years) period. The statistical combination defines an objective weighting of station data that delivers reliable and time-consistent area-mean estimates, despite coarse and biased coverage with stations in early years. The methodology also quantifies the uncertainty of the estimates. Validation of the method reveals plausible patterns of station weights, and estimation errors of about 0.1 °C, much smaller than inter-annual variations. The new series suggest a warming in Switzerland of almost 1.5 °C from the early-industrial period (1864–1900) till the latest WMO standard period (1981–2010), with a linear trend of 1.29 °C per 100 years between 1864 and 2016. The warming is found to be larger in autumn than in other seasons, larger to the north of the Alps than to the south, and larger below (above) 1000 m asl in winter (summer). In all series, the warming is modulated by inter-decadal variations. Current global temperature datasets exhibit less warming for Switzerland than the present analysis. The pattern of disagreement suggests that a network-wide change in Swiss temperature measurements around 1980 may have been missed in the homogeneity adjustments at global data archives. It is desirable that these archives are better aligned with the latest quality processing of the original data owners. The study derives new time-series of monthly-mean surface air temperature for Switzerland that range back to 1864 and represent area-mean conditions over the country and three major sub-regions. The method integrates data from a small sample of homogenized long-term series and from a high-resolution grid dataset over a short 20-year period. The statistical combination defines an objective weighting of station data that delivers reliable and time-consistent area-mean estimates together with uncertainty information.

Description: ABSTRACT A statistical analysis of 100-year historic Southern Annular Mode (SAM) time series is carried out, for a set of indices calculated by different methods, in view to understanding their value as simple indicators of climate variability and of the physical processes involved, particularly for the early part of the 20th century. Historic SAM time series available in the literature are analysed together with ones calculated using the 20th-century reanalysis. A preliminary analysis and comparison is carried out using standard time and space correlations. Distinct differences are observed in the linear relations between the SAM index time series before and after 1950s. A detailed study is carried out using wavelet transform (WT) analysis, in order to better determine the spectral nature and non-stationarity of the timeseries. The WT spectra reveal an aperiodic, non-stationary evolution in all cases, with differences in the spectral signature of the various SAM indices during the 20th century. Preferred oscillation periods mainly appear between 2 and 20 years. Important differences between the SAM indices arise from different behaviour on the interannual time scale even in more recent years, as well as non-stationarity and phase differences on longer time scales. A wavelet coherency (WTC) analysis between the 20th-century-reanalysis-derived SAM time series shows that differences may also arise for indices calculated from the same data source, particularly during the earlier part of the sample. WTC differences appear at times of perturbed El Niño-Southern Oscillation (ENSO) events. Results using linear as well as a mutual information analysis suggest links between SAM, ENSO, and Pacific-South American patterns of variability, which may depend on the SAM time series definition. Such behaviour could be due to a combination of factors including the geographic coverage of the SAM calculation methods and data quality, as well as ENSO-SAM relationships. A statistical analysis of 100-year historic Southern Annular Mode (SAM) timeseries is carried out, for a set of indices calculated by different methods. A Wavelet transform spectra reveal an aperiodic, non stationary evolution in all historical SAM indices, with differences in the spectral signature during the 20th Century. Results using linear as well as a mutual information analysis suggest links between SAM, ENSO and Pacific-South American patterns of variability, which may depend on the SAM time series definition. Correlation patterns between SAM timeseries and sea-level pressure anomaly timeseries at grid points for SH pressure fields provided by 20CR.

Description: The integrated kinetic energy (IKE) of a tropical cyclone (TC), a volume integration of the surface winds around the centre of the TC, is computed from a comprehensive surface wind (National Aeronautics and Space Administration’s (NASA) cross-calibrated multi-platform [CCMP]) analysis available over the global oceans to verify against IKE from wind radii estimates of extended best-track data maintained by NOAA for the North Atlantic TCs. It is shown that CCMP surface wind analysis severely underestimates IKE largely from not resolving hurricane force winds for majority of the Atlantic TCs, under sampling short-lived and small-sized TCs. The seasonal cycle of the North Atlantic TC IKE also verifies poorly in the CCMP analysis. In this article we introduce proxy IKE (PIKE) based on the kinetic energy of the winds at the radius of the last closed isobar (ROCI), which shows promise for a wide range of TC sizes including the smaller-sized TCs unresolved in the CCMP data set. The composite track density (number of TCs based on non-zero values of 34–50-kt IKE per 2 × 2° cell) plot of North Atlantic TCs for the years 2004–2011 from (a) EBT, (b) CCMP and (c) combined (a) and (b).

Description: Large climate variations have been detected from paleoclimatic records in some regions of South America during the last 500 years. Among them, the Altiplano and the subtropical Andes regions exhibited wetter-than-normal conditions during the 17th century within the paleoclimatic period known as Little Ice Age (LIA). On the other hand, both regions experienced drier-than-normal conditions in the second part of the 20th century in association with the recent global warming period (GWP). This study provides an assessment of the ability of four models of the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3)/fifth phase of the Coupled Model Intercomparison Project (CMIP5) experiments in reproducing those regional rainfall changes and the associated large-scale circulation features. Climate models can represent qualitatively the temperature changes observed in South America in both periods, LIA and GWP, as compared to the control run, but they do not properly describe the associated precipitation changes. However, they can simulate, in some extent, the large-scale circulation changes that previous works identified as important in driving the precipitation changes in both regions. Therefore, the assessment allows to detect the following changes in LIA (GWP): (a) equatorwards (polewards) displacement of the southern branch of the Hadley cell, in turn associated with wetter (drier) conditions in subtropical south America; (b) negative (positive) upper-level zonal wind changes related with positive (negative) December, January and February (DJF) rainfall changes in the Altiplano; and (c) positive (negative) low-level zonal wind changes associated to positive (negative) JJA rainfall changes in the subtropical Andes, being in turn related to hemispheric wind changes resembling a negative (positive) phase of the southern annular mode. The assessment of PMIP3/CMIP5 experiments allows to detect the following changes in South America during Little Ice Age (recent global warming period): (a) equatorwards (polewards) displacement of the southern branch of the Hadley cell, associated with wetter (drier) conditions in subtropical south America; (b) negative (positive) upper-level zonal wind changes related with positive (negative) DJF rainfall changes in the Altiplano; and (c) positive (negative) low-level zonal wind changes associated to positive (negative) June, July and August (JJA) rainfall changes in the subtropical Andes.

Description: Assessing the long-term drought changes is of large interest for understanding the impact of climate change on water resources. Here we have attempted to assess the long-term drought changes (1948–2012) over China using the self-calibrating Palmer drought severity index with Penman–Monteith (scPDSI PM ) and Thornthwaite (scPDSI Th ) methods for potential evapotranspiration (PET) estimations, respectively, so as to understand the impact of different PET methods on drought assessment. Both scPDSI PM and scPDSI Th appear to have drying trends in the humid and transitional climatic regions, which are particularly significant in the north China. Compared to scPDSI PM , the scPDSI Th data have resulted in exaggerated drought severity in the north China since 1980s, and such exaggeration is particularly significant for extreme droughts in terms of the occurrences and the intensity. In the dry climatic regions of northwest China, both scPDSI PM and scPDSI Th appear to exhibit adequate wetting trends; however, both data have shown drying trends of intensity when drought occurs, indicating there are more extreme dry conditions in the context of generally wetting background. Surprisingly, scPDSI PM is found to result in exaggerated droughts rather than scPDSI Th in the northwest China. Both scPDSI PM and scPDSI Th show significant drying trends in the north China, where the scPDSI Th droughts are largely exaggerated. Slightly wetting trends are shown in both scPDSI PM and scPDSI Th in the northwest China, where there are however significantly increased droughts. Either the Penman–Monteith or the Thornthwaite method for PET estimations can lead to exaggerated droughts in different regions in the warming climate. Pixel-wise linear trends for (a) scPDSI PM and (b) scPDSI Th , respectively, during 1948–2012.

Description: Observed sea surface temperature (SST) anomalies in the central eastern equatorial Pacific exhibit two kinds of phase evolution, that is, transition and no-transition, for both the eastern Pacific (EP) and central Pacific (CP) El Niño events. The transition type of El Niño is characterized by a strong decay after its peak and followed by a rapid transition to a La Niña event in the subsequent winter, while the no-transition type of both EP and CP El Niño is featured by a weaker decay after its mature phase and fails to develop a La Niña event in the decaying year. For the EP El Niño, the intensity of the anomalous easterly over the western equatorial Pacific in the transition type is stronger than that in the no-transition type, which is likely determined by the coupling of the Indian Ocean dipole (IOD) during the developing phase and the Indian Ocean basin-wide mode (IOBM) during the decaying phase. For the CP El Niño, larger differences of easterly wind anomalies between the transition type and no-transition type are found over the central eastern equatorial Pacific during the decaying year, which is also likely related to the IOD and IOBM coupling process. In addition, the rapid decay of warm subsurface (80–160 m) temperature anomalies in the central eastern equatorial Pacific during the decaying phases is crucial for the phase transition for the two types of El Niño, together with the eastwards propagation of cold subsurface (100–200 m) temperature anomalies in the western equatorial Pacific. What is more, analyses of the mixed-layer heat budget show that the phase evolution of the EP El Niño depends on dynamic forcing (zonal advection) due to the difference of anomalous mixed-layer ocean currents, while the CP El Niño’s different phase evolution is mainly caused by thermodynamic process, that is, net surface heat flux anomalies. Temporal evolutions of (a) normalized Niño3 index for EP El Niño events and (b) normalized Niño4 index for CP El Niño events. Numbers 0 and 1 in the parentheses denote the developing year and the following year, respectively. Solid and dashed lines indicate transition and no-transition types, respectively. Thick line represents the corresponding composite.

Description: This study demonstrates the fidelity of Climate Forecast System version 2 (CFSv2) in three horizontal resolutions: T62, T126 and T382, during boreal winter. As the Madden–Julian oscillation (MJO) is the major mode of variability during boreal winter, the emphasis of the study is on the fidelity of the models in capturing the MJO variability. CFSv2 shows moderate skill in simulating the intra-seasonal oscillation and the skill is sensitive to the resolution of the model. Boreal winter mean precipitation shows the tendency of the model to overdo the double Intertropical Convergence Zone (ITCZ) that increases with resolution. Twenty to hundred days band-pass-filtered rainfall variances also indicate that the dominant variances are overestimated with increase in resolution. The characteristic eastwards propagation is not captured by the model at all the resolutions. In an attempt to understand the limitation of the model, composites of specific humidity are analysed which show that the model’s moisture profile is rather better represented at lower resolution than the higher ones. Analyses of relative humidity profile as a function of rainfall rates show that all the model resolutions fail to reproduce the lower-level moistening prior to deep convection. Observational studies have shown shallow convection to be responsible for this low-level moistening. Furthermore, analysis of mean stratiform rainfall indicates that spectrum of rainfall variability is not simulated by the model and increasing the resolution could not improve the cloud processes. This study therefore indicates that the fundamental moist convective processes do not improve in the model and neither its bias in capturing the intra-seasonal variability vis-à-vis MJO through increasing resolution. This can therefore be a basis for improving the moist convective processes with emphasis on the improvement of the shallow convection within boundary layer and also for the inclusion of scale dependencies in parameterized processes. Keeping in mind the inclination of modelling community towards high-resolution models, analysis of MJO simulated by CFSv2 at three different horizontal resolutions with the finest being at 28 km is performed which indicates that merely increasing the resolution of the model does improve the skill unless the parameterization schemes are also retuned accordingly or include resolution dependencies.

Description: Exceptional dry spells, in this study referred to as very long dry spells (VLDS), are natural hazards to which the Mediterranean region is extremely vulnerable, with socio-economic and environmental impacts. In this study, they are characterized in terms of location, spatial extent, duration, temporal variability and associated atmospheric circulations. The main objective is to assess the performance of five HyMeX/Med-CORDEX regional climate simulations to detect and reproduce VLDS in comparison with the E-OBS observed daily gridded data. Models accurately reproduce the occurrence of precipitation around the Mediterranean Basin, and therefore the occurrence of VLDS, with at least 51% of the E-OBS VLDS reproduced by the regional simulations. They also accurately simulate the spatio-temporal characteristics. A second objective is to identify the synoptic atmospheric patterns associated with VLDS. A clustering analysis shows that all models accurately reproduce the main VLDS spatial patterns, associated with anticyclonic conditions above the affected regions. The simulated VLDS occurrence is strongly related to the amplitude of the sea level pressure and 500-hPa geopotential height anomalies as well as the location of the maximum anomalies. All VLDS events are associated with anticyclonic conditions except those occurring in the eastern Mediterranean, where they are generally not associated with a specific meteorological event but with the usual summer weather regime. The main objective is to assess the performance of five HyMeX/Med-CORDEX regional climate simulations to detect and reproduce VLDS in comparison with the E-OBS observed daily gridded data. Models well reproduce the occurrence of precipitation around the Mediterranean Basin, and therefore the occurrence of VLDS and their spatio-temporal characteristics. However, models tend to detect VLDS slightly shorter and less extent compared to the E-OBS. Fraction of VLDS days at each grid point with respect to the total studied days in the whole Mediterranean domain computed from the E-OBS data set (a), and simulated biases for CCLM4 (b), Reg_CM4 (c), ALADIN52 (d), LMDZ4 model (e) and LMDZ4-NEMOMED8 model (f). The grey shaded area indicates the absence of data for the analysis.

Description: Prediction of climate extremes is challenging, especially for non-Gaussian extremes in urban areas where the majority of people live, since the Gaussian assumption used in linear regression is violated and the urbanization effect needs to be considered. In this study, the first-order difference method is introduced to take these difficulties into account. Statistical prediction of the non-Gaussian annual occurrence of hot days in downtown Hong Kong, which is highly urbanized, is used to illustrate this method. With the help of the first-order difference of the annual occurrences, which follows a Gaussian distribution, the difference series is used as the predictant to find predictors and to construct a prediction model by using traditional linear regression. The difference is first predicted and is then added to the observed value at the preceding time to obtain the predicted annual occurrence. The historical urbanization effect is thus obtained directly from the observations at the preceding time. The prediction results are found desirable. The broad application potential and conditions in which this method should be used are also discussed. Time series of annual occurrence of hot days (blue curve) in Hong Kong for the period 1947–2016 (a) and its normality tests (b, c). In (a), the linear trend estimated by the WS2001 (red line) and the 11-year running mean (black curve) are also plotted. In (b), the blue bars are the target data under testing and the red line is the fitted Gaussian distribution. The p 〉 .05 in the Jarque–Bera test indicates that the target data are normally distributed. In the quantile–quantile plot (c), red circles indicate the distribution of the target data and the black solid lines represent the Gaussian distribution, with the 95% confidence intervals shown as black dashed lines. The approximate linearity of the circles suggests that the target data are normally distributed. (d), (e) and (f) are the same as (a), (b) and (c), respectively, but for the year-to-year increment of hot days.

Description: Credible information about the properties and changes of extreme events on the regional and local scales is of prime importance in the context of future climate change. Within the EU-COST Action VALUE a comprehensive validation framework for downscaling methods has been developed. Here we present validation results for extremes of temperature and precipitation from the perfect predictor experiment that uses reanalysis-based predictors to isolate downscaling skill. The raw reanalysis output reveals that there is mostly a large bias with respect to the extreme index values at the considered stations across Europe, clearly pointing to the necessity of downscaling. The performance of the downscaling methods is closely linked to their specific structure and setup. All methods using parametric distributions require non-standard distributions to correctly represent marginal aspects of extremes. Also, the performance is much improved by explicitly including a seasonal component, particularly in case of precipitation. With respect to the marginal aspects of extremes the best performance is found for model output statistics (MOS), weather generators (WGs) as well as perfect prognosis (PP) methods using analogues. Spell-length-related extremes of temperature are best assessed by MOS and WGs, spell-length-related extremes of precipitation by MOS and PP methods using analogues. The skill of PP methods with transfer functions varies strongly across the methods and depends on the extreme index, region and season considered. Indices, codes and associated performance measures for extremes of precipitation and temperature ( T min  = minimum temperature; T max  = maximum temperature).

Description: We present the Caribbean's Virgin Islands’ climate variability over the last 60 years from indices of extreme temperature and precipitation, as well as their quantitative support for a recent climatic shift (1983.2 ± 5.5 years). The region's climate indices (defined via time series averages) and trends (defined via linear least squares regression fitting) of extreme temperature and precipitation were cross-examined from 1952, 1961, 1978, and 1983–2014 to diagnose: the area's climatic extremes; a climatic transition's role in assessing decadal climate anomaly rates; and to provide an analytically independent test of the transition's existence. Analyses relied on the use of varying physical constraints to include weighting from statistical and non-statistical uncertainties in our climatic outcomes. We report that diurnal warming and enhanced precipitation accompanied each interval, however, non-negligible deviations existed in comparisons between the same anomalies in any 2 intervals. Our Virgin Islands’ long (1952, 1961–2014) versus short (1978, 1983–2014) climate variation comparisons provide evidence for the manifestation of decadal (or longer) shifts, and thus, biases, in recent Caribbean reports. Our climatic transition's overlap with the renowned 1976/1977 Pacific event insinuates a local Caribbean teleconnection, and contributes to the evidence growing globally for 1980s’ shifts in an abundance of feedback measures of Earth's energy budget. We present the Virgin Islands' climate variability over the last 60 years, from indices of extreme temperature and precipitation, as well as their quantitative support for a recent climate shift. This work diagnoses a shift's role in accessing decadal climate anomalies, and reveals biases in recent Caribbean climate reports. The shift's overlap with the renowned 1976/1977 Pacific event insinuates a teleconnection, and contributes to the evidence growing globally for 1980s' shifts in an abundance of feedback measures of Earth's energy budget.

Description: The extreme El Niño events, such as those which occurred in 1982–1983, 1997–1998, and 2015–2016, exerted devastating impacts in many parts of the globe. Hence, it is crucial to understand the precursors of such extreme events. Nevertheless, each El Niño event has its own characteristics even in the initiation. Here, we show that the development of early-spring equatorial central Pacific warming forced by the increased solar radiation due to a suppressed convection was a crucial factor in developing the 1982–1983 extreme El Niño event. The central Pacific warming anomalies in the spring of 1982 were induced by atmospheric subsidence connected to the northern subtropical Pacific convection, subsequently reinforced by a reduced evaporative cooling via westerly anomalies. On the other hand, springtime warming anomalies over the equatorial central and eastern Pacific regions during other extreme El Niño events were induced mainly by oceanic dynamical processes. Composite maps of the 925-hPa level anomalous (a) zonal wind (U925, shadings, at intervals of 0.1 m/s) and horizontal winds (UV925, vectors, wind speed 〉 0.5 m/s highlighted by thickened black vectors) and (b) upper ocean temperature (indicating the upper ocean heat content, OHC, shadings, at intervals of 0.1 °C) averaged over the equatorial band of 5°S–5°N during FMA(0) for the 20 El Niño events for the period of 1958–2016. (c) Relationship between the WP-wind ( x -axis) and OHC ( y -axis) indices during FMA(0) for the respective El Niño events (see Section 2). Scatters indicate each of the 20 El Niño events and the size of markers is proportional to the El Niño amplitudes as following the Niño-3.4 index intensities during DJF(0/1) (c.f., Figure S1). Extreme (moderate) El Niño events are marked with red (blue) markers. Temporal evolutions of the 3-month averaged (d) Niño-4 and (e) Niño-3.4 indices for the three extreme El Niño events of 1982–1983 (red), 1997–1998 (blue), and 2015–2016 (purple) and the 17 moderate El Niño events averaged anomalies (black) with the 95% confidence intervals shaded on the original anomalies. See Section 2 for the El Niño event classification. The lags are taken 2 and 1 year before (Yr(−1) and Yr(0)) and 1 year after (Yr(+1)) El Niño event has peaked. Winds including U925, UV925, and WP-wind index are from NCEP R1 data; OHC and OHC index are from SODAv2.2.4 and GODAS (only for the 2015–2016 El Niño event) data; Niño-4 and Niño-3.4 indices are from ERSSTv4 data.

Description: Seasonal snow cover over the Tibetan plateau (TP) has unique features in terms of global snow cover distribution because of the high mountains and vital surface water storage functions in non-humid regions of Southwest China and surrounding Asian countries. Limited by the complex topography and relatively low spatial resolution of satellite observations, the characteristics of snow phenology and the factors for snow phenology changes remain still unclear. Using multisource data for the period 2001–2014, this study quantifies the climatology of snow phenology and explores its attribution factors. The results show that the snow onset date ( D o ) and snow end date ( D e ) were 4.9 (±7.7) and 108.1 (±5.9) in day of year (DOY), respectively, and the snow duration days ( D d ) were 103.2 (±13.4) over the TP during the study period. The characteristics of satellite observed D d was similar to subzero temperature days derived from ground observations. The 14-year anomalies in snow phenology features regional disparity over the TP, with increased D d in the central TP and shortened D d in the Tarim River, endorheic drainage basins, and upper reaches of the Brahmaputra River. In contrast to previous findings in northern mid-latitudes, changes in D d over the TP during 2001–2014 were mainly induced by anomalies in D o , which can be further attributed to the declines in accumulation season temperature over the TP. Seasonal snow cover over the Tibetan plateau (TP) has unique features in terms of global snow cover distribution maps. Limited by its complex topography and spatial resolution of satellite snow products, the characteristics of snow phenology and the factors for snow phenology changes are still not clear. By using fine resolution satellite observations and ground records, this study investigate the climatology and anomaly of snow phenology over the TP and explored its attribution factors for the period 2001–2014, which is important in probing the response of snow cover to climate change over the TP.

Description: Recent findings have raised the debate on increase in tropical cyclone activity (TCA) in major tropical ocean basins like North Atlantic and western North Pacific. To address the similar evidence in North Indian Ocean (NIO) basins, an attempt has been made in the present study to investigate TCA in NIO basins in the context of warmer climate during the satellite era (1981–2014). The most suitable cyclone energy metric called accumulated cyclone energy (ACE) is estimated for this purpose. A statistical change-point analysis is conducted to detect the shift in ACE during the study period. Environmental factors influencing TCA are investigated to infer possible causes in the observed variability. The results indicate the increasing trend in ACE in NIO during satellite era with statistical significance of 95%. The frequency and duration of intense cyclones (wind speed 〉64 knots) show notable increase in recent years. However, a decreasing trend is observed in total frequency. The change-point analysis of ACE in NIO reveals objectively that the shift occurs in 1997, with 20.8 ACE during 1981–1996 and 41.4 ACE during 1997–2014. The analysis reveals that increase in number and duration of very severe cyclonic storm (VSCS) (wind speed 〉64 knots) in the recent epoch (1997–2014) is the major cause for the observed twofold increase in ACE. Also, the mean genesis location of intense BoB cyclones exposes a longitudinal eastwards shift of 2.3° in the recent epoch, which could have aided the longevity of intense cyclones. Analysis of sea surface temperature (SST), upper ocean heat content (UOHC) and genesis potential index (GPI) climatology shows a positive agreement to the observed shift in genesis. The analysis of seven environmental factors shows substantial agreement with the increase and variability of ACE. Predominantly, atmospheric water vapour and SST show better correlation (.72 and .66) with ACE in NIO. The cyclone energy metric called accumulated cyclone energy (ACE) indicates an increasing trend in north Indian Ocean and its basin Arabian Sea and Bay of Bengal. The frequency and duration of intense cyclones (〉64 knots) show notable increase in recent years. The change-point analysis of ACE in NIO reveals objectively that the shift occurs in 1997, with 20.8 ACE during 1981–1996 and 41.4 ACE during 1997–2014. Also, the mean genesis location of intense BoB cyclones exposes a longitudinal eastwards shift of 2.3° in the recent epoch, which could have aided the longevity of intense TCs.

Description: There is overwhelming evidence that the climate system has warmed since the instigation of instrumental meteorological observations. The Fifth Assessment Report of the Intergovernmental Panel on Climate Change concluded that the evidence for warming was unequivocal. However, owing to imperfect measurements and ubiquitous changes in measurement networks and techniques, there remain uncertainties in many of the details of these historical changes. These uncertainties do not call into question the trend or overall magnitude of the changes in the global climate system. Rather, they act to make the picture less clear than it could be, particularly at the local scale where many decisions regarding adaptation choices will be required, both now and in the future. A set of high-quality long-term fiducial reference measurements of essential climate variables will enable future generations to make rigorous assessments of future climate change and variability, providing society with the best possible information to support future decisions. Here we propose that by implementing and maintaining a suitably stable and metrologically well-characterized global land surface climate fiducial reference measurements network, the present-day scientific community can bequeath to future generations a better set of observations. This will aid future adaptation decisions and help us to monitor and quantify the effectiveness of internationally agreed mitigation steps. This article provides the background, rationale, metrological principles, and practical considerations regarding what would be involved in such a network, and outlines the benefits which may accrue. The challenge, of course, is how to convert such a vision to a long-term sustainable capability providing the necessary well-characterized measurement series to the benefit of global science and future generations. Instigating and maintaining a reference network for climate would aid future generations in understanding climate change. Such measurements require strict adherence to metrological best practices and sustained support. This article explores what would be required to make such a network work. Figure is the schematic of the instrumentation at a typical USCRN station in the CONUS. The triplicate configuration of temperature sensors is repeated in the three precipitation gauge weighing mechanisms and in the three sets of soil probes located around each tower.

Description: In this study, the relationship between the East Asian winter monsoon (EAWM) and the Arctic oscillation (AO) and El Niño southern oscillation (ENSO) are reanalysed using long-term reanalysis data. The AO and ENSO influence the EAWM by means of a significant inter-decadal oscillation with a periodicity of approximately 60 years. When the linkage between the AO and EAWM is strengthened (weakened), the ENSO has a weakened (strengthened) relationship with the EAWM. The AO and ENSO alternately affect the EAWM for approximately 30 years. Furthermore, an analysis is completed regarding the possible mechanism of the inter-decadal relationship between the EAWM and ENSO, as well as the AO. Such an inter-decadal relationship could be due to the phase transition of the Pacific multi-decadal oscillation (PMO). When the PMO is positive, sea surface temperatures (SSTs) in the Bering Strait and Alaska Current region are warmer than average, which results in a decrease in the East Asian trough and an increase in the Aleutian low and northeastern Pacific vertical wave activity flux. In this case, the vertical wave activity flux propagates upward and is reflected in the polar vortex, which significantly strengthens the relationship between the Asia-Pacific climate and AO. Simultaneously, during the positive phase of the PMO, the increase in the SST in the eastern South Pacific is stronger than in the west, which leads to a weakening of the east–west temperature gradient and southern oscillation. Thus, the relationship between the ENSO and Asia-Pacific region is significantly weakened and vice versa. The results of this study deepen the understanding of the Asia-Pacific climate and may improve the inter-decadal prediction of the Asia-Pacific regional climate in the future. In this study, we found that the Pacific multi-decadal oscillation (PMO) can modulate the effect of Arctic oscillation (AO) and El Niño southern oscillation (ENSO) on the East Asian winter monsoon (EAWM), during the different PMO phases, when the linkage between the AO and EAWM is strengthened (weakened), the ENSO has a weakened (strengthened) relationship with the EAWM. The AO and ENSO alternately affect the EAWM for approximately 30 years (as shown in (a)).

Description: ABSTRACT Large-scale atmospheric circulation patterns have a strong influence on hydrologic variability in the southeastern United States (SEUS). These climatic indices are often linked with anomalous climatic conditions and thus can be useful to forecast either water surplus or deficit conditions over the region. This study provides an assessment of the watershed-scale influence of hydroclimatological teleconnections in the context of drought predictability. The interrelationship between several climate indices is assessed with the monthly percentiles of soil water storage (SW), precipitation (PCP), surface run-off (SURQ), and potential evapotranspiration (PET) for 50 watersheds in the South Atlantic Gulf region of the SEUS. The hydrologic variables are simulated by implementing SWAT models for each watershed at a HUC-12 resolution for a period of January 1982 through December 2013. The study highlights the strong correlation between the climate indices and watershed-scale hydrologic variables and provides important insights on the effect of seasonality and the dynamics of water balance components on the predictability of drought at watershed-scale. Among all hydrologic variables evaluated, soil moisture shows a stronger relationship with the climate indices compared to PCP, SW, and SURQ. The interrelationship between watershed hydrology and climate indices is found to be stronger during fall (September–November) and winter seasons (December–February) with high correlation of SW and PCP with the climate indices, especially in the Carolinas, Georgia, and parts of Florida. Simulated SW corresponds strongly with the Palmer drought severity index (PDSI) in terms of its response to climate indices, indicating that SW can be an effective predictor of drought in the region. Graphical summary of the watershed scale drought predictability analysis for the Southeastern US.

Description: The weakening in the relationship between the South China Sea summer monsoon onset (SCSSMO) and the low-level cross-equatorial flow (CEF) in May is investigated using the ERA-Interim reanalysis data sets during 1979–2016. The SCSSMO–SCSCEF relationship has experienced a significant inter-decadal change, and the correlation coefficient becomes weaker after the late 1990s. The correlation has shifted from the significant negative value in the earlier decade to insignificant in the later decade. This inter-decadal change is robust under several sensitive tests and largely independent of the El Niño-Southern Oscillation signal. One possible explanation is the change in mechanisms driving the SCSSMO over the course of the two periods. Before the late 1990s, the northwards march of the intertropical convergence zone, which has a close relationship with the SCSCEF, is mainly responsible for the SCSSMO. After the late 1990s, warming of the western North Pacific favours more tropical cyclones and disturbances during May. The westwards movement of these tropical disturbances would affect the SCSSMO and help explain why the SCSSMO–SCSCEF relationship became weaker in the later decade. (a) The time series of SCSSMO (bar) and SCSCEF (curves) in May of different levels (including 850 hPa, 925 hPa, and 10 m; data from ERAInterim), (b) the 11-year sliding correlation (partial correlation) between the SCSSMO and SCSCEF (after removing ENSO signal in May or preceding winter); the dashed line denotes the 90% confidence level; (c) same as (b), but for the 925 hPa SCSCEF calculated by NCEP/NCAR, NCEP-DOE, and averaged from May 1 to June 8 (which contains 90% of the SCSSMO) by ERA-Interim; (d) the composited 925 hPa SCSCEF with respect to SCSSMO during 1979–1998 and 1999–2016 (date 0 is defined as the onset, while the signs of “−” and “+” denote the dates before and after the onset). Thin and thick lines denote the daily and 5-day mean of composited SCSCEF, respectively.

Description: The February–May rainfall season, locally known as Belg, contributes up to 40% of the annual rainfall over northeastern, central and southwestern Ethiopia. Its contribution exceeds 50% over southern and southeastern Ethiopia. The Belg season is characterized by significant inter-annual and intra-seasonal variability. However, there are only a few studies addressing the characteristics of this season. Interactions between extratropical and tropical systems across the Red Sea region play a major role in modulating the rainfall pattern during this season. It is shown in this article that the North Atlantic Oscillation (NAO) seems to play a major role in the variability of the Belg rains on the sub-seasonal time scale. The Belg rains are negatively correlated with the NAO index over much of the region, with southern and southeastern Ethiopia exhibiting relatively highest correlation values. NAO rainfall anomaly composites also indicate that the negative (positive) phase of the NAO tends to enhance (suppress) the Belg rains. Two modes of regional circulation patterns that modulate Belg rainfall variability have also been identified in this study. A ridge/trough pattern, featuring two anomalous mid- to upper-level warm anticyclones and one cold cyclonic trough in the region between the northeast Atlantic and the Arabian Peninsula, tends to suppress the Belg rainfall due to reduced tropical–extratropical interactions. In contrast, a tripole structure with two anomalous mid- to upper-level cold cyclonic troughs and one warm anticyclone tends to enhance rainfall during the Belg season of Ethiopia. It is further shown in this article that the Madden–Julian Oscillation (MJO) tends to modulate rainfall during the Belg season. Composites of circulation anomalies at 500 hPa (above) shows a tripole circulation pattern in the form of anticyclone–cyclone–anticyclone (ACA) for dry Belg (a)–(d) and cyclone–anticyclone–cyclone (CAC) for wet Belg (e)–(h). The ACA and CAC patterns indicate influence of tropical/extratropical interactions in modulating the Ethiopian Belg rainfall. NAO-related anomalies in the North Atlantic are also linked to anomalies in the Red Sea region through the tripole pattern.

Description: Based on reanalysis and observational data sets, the present study reveals that the variability of summer rainfall in the low-latitude highlands of China (CLLH) is significantly correlated to the sea surface temperature (SST) configuration from the Greenland Sea (GS) southeastwards to the subpolar region of North Atlantic (NASR). The SST configuration orientated in northwest–southeast direction exerts its impact on the summer rainfall coming into the CLLH via modifying the activity of cold air in the northeast CLLH. When SST is warmer than normal in the GS and colder than normal around the NASR, a teleconnection with an anomalous cyclone over the Europe, an anomalous anticyclone around the Lake Baikal and an anomalous cyclone over the East Asia will be forced out by the dispersion of Rossby wave on the spherical surface of the earth. The teleconnection traversing Europe–East China is favourable to transportation of cold air from the East Siberian southwestwards to the CLLH and thus gives rise to the increase of summer rainfall in the CLLH. When SST is colder than normal in the GS and warmer than normal around the NASR, the similar teleconnection with opposite phase is forced out, causing a less than normal summer rainfall in the CLLH. Patterns of the first EOF–CCA pair of (a) summer rainfall anomaly (units: mm) in the CLLH and (b) SST anomaly (units: °C) in the GS–NASR. Contour intervals are 30 mm in (a) and 0.1 °C in (b). Solid lines mark the positive values and dashed lines mark the negative values. The bold line denotes zero. Areas shaded from light to dark denote the correlation coefficients passing the significance test at 90, 95 and 99% confidence level, respectively. (c) Normalized time series of the first EOF–CCA patterns. Blue line denotes the SST series, and red line denotes the CLLH summer rainfall series. The gauge stations are indicated by black dots in (a).

Description: Using precipitation data from weather stations in China and reanalysis data from National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the inter-annual and inter-decadal variability of early-summer (May–June) and late-summer (July–August) precipitation (hereinafter referred to as MJP and JAP, respectively) over northeast China (NEC) and their background circulation during 1951–2016 were analysed. The following new findings have been highlighted: (a) There are significantly different inter-annual and inter-decadal variability characteristics between MJP and JAP over NEC. The inter-annual variability of MJP is independent from that of JAP, while the inter-decadal variability of the former is opposite to that of the latter. A significant shift to more MJP (less JAP) occurred in the early 2000s (late 1990s). (b) In terms of the inter-annual timescale, the large-scale atmospheric circulations-associated MJP is notably different from JAP over NEC. The variation in MJP is mainly dominated by the northeast China low (NECL) and the Okhotsk blocking high (OBH), while JAP is mainly influenced by the western Pacific subtropical high (WPSH), the NEC south wind (NESW), and the NECL. (c) On the inter-decadal timescale, MJP is associated with the inter-decadal variation of the East Asia/Pacific (EAP) teleconnection, while JAP is closely related to the inter-decadal variation of the NECL and NESW. When the EAP is in a positive phase, MJP is more than average. Furthermore in late summer, the strong NECL and NESW are both of benefit to the convergence of water vapour from the tropical southwest and East Asian subtropical westerlies over NEC, which contributes to the more JAP than average. (a) Locations of the 24 weather stations in northeast China (NEC) whose data are used in this study. (b) Time series of May–June precipitation (MJP) and July–August precipitation (JAP) in NEC during 1951–2016, which are standardized. (c) The 11-year-sliding correlation coefficients between MJP and JAP. Horizontal red dotted line indicates 95% confidence level estimated using Student's t test.

Description: Aridity is a permanent feature of climate based on long-term climatic conditions over a region. Climatic indices are reliable tools to explore climate type, and climatologists have proposed various indices to classify climate and investigate the aridity or humidity in any region. In this study, we examined spatiotemporal variations of aridity in Iran during the last six decades from 1954 to 2013, using the de Martonne aridity index ( I DM ), which is calculated based on precipitation and temperature. Data used in this study were extracted from the Global Precipitation Climatology Centre and the University of Delaware gridded data sets, respectively. Both data sets have global high-resolution (0.5° × 0.5°) coverage, and temporally span more than a century of data (from 1901). According to the data obtained from these data sets, more than 80% of Iran has an arid and semi-arid climate (annually), although the spatial pattern of I DM varies throughout the year. Using the Mann–Kendall test showed a negative significant trend in I DM in 20% of Iran's total area in spring, and less than 7% in the other seasons of the year. Overall, it can be concluded that there were no significant trends in aridity for most parts of Iran during the last six decades. Results of this study showed a spatiotemporal non-significant negative or positive trend in aridity, in most of the months and seasons of the year and also annually, in Iran, using the de Martonne aridity index ( I DM ) and the Mann–Kendall (MK) trend test, based on Global Precipitation Climatology Centre and the University of Delaware gridded data sets.Spatial pattern of MK Z-values for the annual I DM time series during 60 years period from 1954 to 2013.

Description: Lapse rate (LR) of near-surface (2 m) air temperature is essential for determining spatially distributed and gridded air temperature interpolated from in situ observational sites. However, due to the limitation of sparse observational networks, high-resolution LRs are not usually available on regional scales, especially in mountainous regions. The purpose of this study is to estimate LRs for the entire Tibetan Plateau (TP) using observed air temperature and moderate-resolution imaging spectroradiometer (MODIS) night-time land surface temperatures (LSTs) and to analyse the spatio-temporal changes of the estimated LRs. First, diurnal cycles of LRs derived from in situ observations in three subregions of the TP were analysed, which shows that the LRs in the western and northeastern regions were shallow in the cold season and steep in the warm season, whereas the southeastern region exhibited a different pattern. Further comparisons revealed that the LRs for night-time air temperatures better represented the LRs for daily mean air temperatures than the daytime ones, and the night-time MODIS LSTs correlated well with the night-time air temperatures, especially for the MODIS Terra data sets. Therefore, the night-time MODIS LSTs from the Terra data sets were used to estimate high-resolution (10 km) LRs for the daily mean temperatures over the entire TP. Estimated LRs over most areas of the TP were shallower than the commonly used environmental LR (−6.5 K/km). The LRs in the southeastern region were steeper than those in the northeastern region, while steeper LR values occurred in the northwestern region with lower temperatures and less humidity. Study region with subregions and spatial distribution and elevation of the 85 stations (denoted by blank circles). The colour represents the DEM (m) from the shuttle radar topography mission (SRTM). The range of station elevations (solid bar with diagonal) as well as the number of stations in each region (solid bar). Further division of regions 2 and 3 into regions A–D occurred to validate estimated daily mean temperature and LR.

Description: Using gridded precipitation data remapping from rain-gauge observations of the time period of 2001–2015 winter months (December, January and February), this study examines the spatio-temporal characteristics of the climatological diurnal winter precipitation in Taiwan. Our results show that the timings of the maximum values of the diurnal precipitation in Taiwan exhibit clear east–west regional differences, with night-time maxima over eastern Taiwan but early morning maxima over western Taiwan. Analyses also show that the climatological characteristics of diurnal winter precipitation documented in this study are not controlled by some unusual, heavy precipitation events and can be seen as the common features. By examining the changes in meteorological variables (including winds, relative humidity and temperature) extracted from the in situ observations and the MERRA (Modern-Era Retrospective Analysis for Research and Applications) reanalysis, this study further suggests that (a) the radiative cooling effect and (b) the surface wind convergence induced by the interaction between the local orography, the local land–sea breeze and the large-scale diurnal circulation changes over the East Asian–western North Pacific (EAWNP) region are two of the possible formation mechanisms responsible for the spatio-temporal differences of the climatological diurnal winter precipitation in Taiwan. This finding sheds light on the importance of understanding the role of the large-scale diurnal circulation changes over the EAWNP region in modulating local diurnal precipitation properties during the winter months. This study examines the spatio-temporal characteristics of the climatological diurnal winter precipitation in Taiwan. The figure shows the phase diagram depicting the timing of the occurrence of the maximum values of the winter precipitation during the day over Taiwan. It is noted that the timings of the maximum values of the diurnal precipitation in Taiwan exhibit clear east–west regional differences, with night-time maxima over eastern Taiwan but early morning maxima over western Taiwan. Possible formation mechanisms are also discussed.

Description: This study on cold-air pool formation in the wide Cerdanya Valley in the Pyrenees mountain range was conducted using available observational information from September 2010 to August 2014. Cold-air pools occur during almost 60% of the nights, mainly during winter. Cold pools develop even under significant synoptic pressure gradients. Additionally, drainage currents transporting air down-valley occur most of the nights. In particular one representative cold-air pool event has been analysed in detail by a high-resolution mesoscale simulation, combined with an analysis of data from both ground-based stations and satellites. Radiative processes dominate the evolution of cold-air pools, together with turbulence in the lowest layers, while drainage flows down from the high mountains mainly through the tributary valleys and from the valley sidewall slopes play a key role in bringing air to the pool. Cold pool formation begins approximately 1 hr after sunset, and it extends across most of the valley bottom, with a very strong thermal inversion close to the surface that has a depth of up to 100 m in the lowest parts of the valley. Wind veers down-valley along the main axis 2–3 hr after sunset and the wind direction is approximately maintained until after sunrise. This study on cold-air pool formation in the wide Cerdanya Valley in the Pyrenees mountain range was conducted using available observational information from September 2010 to August 2014. Cold-air pools occur during almost 60% of the nights, mainly during winter. Cold pools develop even under significant synoptic pressure gradients. Additionally, drainage currents transporting air down-valley occur most of the nights. In particular, one representative cold-air pool event has been analysed in detail by a high-resolution mesoscale simulation. (c) Difference between the local spatial deviation of the LST at the end of the night (October 1–2, 2011) and at the beginning. The blue polygon notes the area selected as the Cerdanya main valley, also imposing an altitude lower than 1,500 m asl. Crosses show the AWS locations.

Description: Precipitation falling in the Snowy Mountains region of south-east Australia is a critical resource—providing water for hydroelectricity, as well as irrigated agriculture and environmental flows throughout the economically important Murray River system. Improved understanding of the drivers of precipitation variability is therefore a key research aim. Focussing on synoptic types responsible for delivering precipitation ≥10 mm per day, an analysis is presented of the large-scale atmospheric circulation drivers (“teleconnections”) of seasonal synoptic type frequency using cross-wavelet and boosted regression tree methods. Results demonstrate that relationships are not stationary over the period 1900–2012, and complex interactions between teleconnections and synoptic atmospheric circulation drive precipitation variability. Importantly, we demonstrate that teleconnections do not act in isolation. Relationships with the tropical Pacific Ocean are shown to be key drivers of synoptic types associated not only with the dominant tropical moisture pathways to the Snowy Mountains, but also with extra-tropical sources. Tropical sea surface temperatures are therefore shown to drive synoptic type frequency and facilitate the dominance of synoptic types with tropical moisture sources, most notability since the 1950s. Understanding the causes of precipitation and variability of precipitation in areas such as the Snowy Mountains is critical for regional water resource management. A number of climate drivers influence precipitation in this region. This research demonstrates that relationships are not stationary over time, and represents a step forward in understanding the complex interactions between teleconnections and synoptic atmospheric circulation that drive precipitation variability.

Description: Regional assessments of trends in climate extremes are necessary for countries to make informed decisions about adaptation strategies and to put these changes into a global context. A workshop bringing together several Southeast Asian countries has delivered a new set of daily weather observations suitable to analyse the changes in temperature and precipitation extremes between 1972 and 2010. The use of a consistent and widely tested methodology in this study allows a direct comparison with results from other parts of the world. Trends in a range of climate extremes indices were assessed focusing on spatial variation in these trends. For most locations temperature trends obtained in this study appear broadly consistent with previous assessments; for some locations stronger trends have been detected through the inclusion of new data. In contrast to earlier studies, evidence of trends in precipitation extremes is emerging, with significant increasing trends in both regional and subregional data. In addition, large correlations between regional rainfall extremes and large-scale features such as El Niño-Southern Oscillation and the Indian Ocean Dipole were identified. Finally, the observed trends are compared with a regional climate model reconstruction of the historical period. It was found that the model captures very well the trends and spatial variation of temperature extremes across the region, albeit with an underestimation of the more extreme indices. In contrast, the trends in precipitation extremes are largely overestimated, particularly in the western side of Southeast Asia. Location of the 121 stations assessed for this study and the limits of the four subregions. Background is the region orography.

Description: Understanding how different climate factors interact and impact rice yield is essential for effective agricultural management strategies and policies. However, the potential impacts are less clear at the regional scale. In this work, we used the latest version of the ORYZA crop model to evaluate the impacts of climate change and carbon dioxide (CO 2 ) on rice yields in the Sichuan Basin of China based on high-quality agricultural experimental, meteorological and soil data and the incorporation of future climate data generated by five general circulation models (GCMs) under three newly released representative concentration pathway (RCP) 2.6, 4.5 and 8.5 scenarios. Considering climate change alone, our modelling results indicated a continuing rice reduction for most stations by 2–17, 4–28 and 1–43% under the RCP2.6, 4.5 and 8.5 scenarios, respectively; when considering the CO 2 fertilizer effect, rice yields increased by 3–10, 4–13 and 5–20% under the RCP2.6, 4.5 and 8.5 scenarios, respectively. However, for most stations, the CO 2 fertilizer effect could not completely offset the negative impacts of climate change on rice yields. In addition, temperature and radiation were the main climate factors that cause yield variation by affecting the rice maturity periods (DAE), spikelet fertility factor (SPFERT) and spikelet number (NSP). The uncertainty arising from the climate models was less than 10% under the RCP2.6 scenario, 15% under the RCP4.5 scenario and 20% under the RCP8.5 scenario, indicating good consistency in rice yield simulations. These findings offer insight into the physiological mechanisms and the degree of climate change impacts on rice yields, thus informing appropriate adaptive strategies for rice planting in the Sichuan Basin, China. We use the ORYZA v3 model, coupled with climate data generated by five general circulation models (GCMs) under three representative concentration pathways (RCPs) (2.6, 4.5 and 8.5), to simulate climate change impacts on rice yields in the Sichuan Basin of China. We collect high-quality meteorological, soil and agricultural experimental data at the plot scale to calibrate, validate and evaluate the crop model. We identify the main factors that affect rice yields, explore the degree and the physiological mechanisms of climate change on rice yields and quantify the uncertainty arising from climate models.

Description: This article presents the results of an investigation into air temperature conditions in northern Nordaustlandet (NE Svalbard) based on meteorological observations made by German soldiers towards the end of World War II (1944/1945) and 4 months after its end. Traditional analysis using mean monthly data was supplemented by a detailed analysis based on daily data: maximum temperature, minimum temperature and diurnal temperature range. The latter kind of data made it possible to study such aspects of climate as the number of “characteristic days” (i.e., the number of days with temperatures exceeding specified thresholds), day-to-day temperature variability, and duration, onset and end dates of thermal seasons. The results from Nordaustlandet for the warmest period of the early 20th century warming period (ETCWP) were compared with temperature conditions both historical (the end part of the Little Ice Age) and contemporary (different sub-periods taken from the years 1981–2017) to estimate the range of warming during the ETCWP. Analysis reveals that the expedition year 1944/1945 in Nordaustlandet was, in the majority of months, the warmest of all analysed periods, that is, both historical and contemporary periods. The study period was markedly warmer than 1981–2010 (mean annual −6.5 vs. −8.4 °C) but colder than the periods 2011–2016 (−5.7 °C) and 2014–2017 (−5.8 °C). The majority of mean monthly air temperatures in the ETCWP lies within two standard deviations of the modern 2014–2017 mean. This means that values of air temperature in the study period lie within the range of recent temperature variability. All other thermal characteristics show changes in accordance with expectations associated with general warming of the Arctic (i.e., a decrease in diurnal temperature range and number of cold days, and an increase in number of warm days). The latter days were most common in the ETCWP. This article presents the results of an investigation into air temperature conditions in northern Nordaustlandet (NE Svalbard) based on meteorological observations made by German soldiers towards the end of World War II (1944/1945). The results from Nordaustlandet for the warmest period of the early 20th century warming period (ETCWP) were compared with temperature conditions both historical (the end part of the Little Ice Age) and contemporary (different sub-periods taken from the years 1981–2017) to estimate the range of warming during the ETCWP. Map shows the activity of German meteorological stations, 1940–1945.

Description: The eastern Mediterranean (EM) is expected to be influenced by climate changes that will significantly affect ecosystems, human health and socio-economic aspects. One aspect of climate change in this vulnerable area is the length of the seasons, especially that of the rainy winter season against the warm and dry summer. Here, the synoptic seasons’ definition of Alpert, Osetinsky, Ziv, and Shafir (2004a) was applied to an ensemble of eight Coupled Model Inter-Comparison Project phase 5 (CMIP5) models, under RCP8.5 and RCP4.5 scenarios, to predict the changes in the lengths of EM seasons during the 21st century. It is shown that the ensemble adequately represents the annual cycle of the main synoptic systems over the EM. The analysis further suggests that at the end of the 21st century, the duration of the synoptic summer, characterized by the occurrence of the Persian Trough, is expected to be lengthened by 49%, while the synoptic winter, characterized by the occurrence of the Cyprus Low, is expected to be shortened by 56% under the RCP8.5 scenario. This may lead to substantial changes in the hydrological regime and water resources, reduce the potential of dry farming, increase the risk of fires and air pollution and change the timing of seasonal health hazards. The “synoptic seasons” definition was applied to an ensemble of eight CMIP5 models to predict the change in the length of EM seasons during the 21st century under the RCP8.5 and RCP4.5 scenarios. The duration of the synoptic summer, characterized by the occurrence of the Persian Trough, is expected to be lengthened by 49%, while the synoptic winter, characterized by the occurrence of the Cyprus Low, is expected to be shortened by 56% (see the figure). This may lead to substantial changes in the hydrological regime, reduce the potential of dry farming, increase the risk of fires and change the timing of seasonal health hazards.

Description: Using the monthly reanalysis data sets of National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) for 1961–2015, the inter-decadal change in inter-annual water vapour transport over the tropical Indian Ocean–western Pacific during summer and the related mechanisms were analysed in this article. The results show that two major modes of anomalous water vapour transport over the tropical Indian Ocean–western Pacific (60°–140°E, 10°S–30°N) experienced a significant inter-decadal change in the mid-1980s. The first mode (EOF1) shows that the anticyclonic water vapour transport over the northwestern Pacific moves significantly southwards after the mid-1980s. Before the mid-1980s, the anomalous water vapour originates from the subtropical western Pacific and moves through the South China Sea to eastern China. However, the anomalous water vapour mainly originates from the tropical western Pacific and moves through the South China Sea to eastern China after the mid-1980s. The second mode (EOF2) reflects the enhanced effect of the anomalous water vapour transport over the tropical Indian Ocean on East Asia after the mid-1980s. Before the mid-1980s, the distribution of the water vapour anomalies is uneven over the tropical Indian Ocean and the magnitude of water vapour is relatively small, so it has a weak effect on rainfall over East Asia. After the mid-1980s, anomalous anticyclonic water vapour transport originates from the tropical Indian Ocean and moves along the Arabia Sea, Indian Peninsula and Indo-China Peninsula and then forms an anomalous cyclonic water vapour transport over south China. Furthermore, the possible causes of the inter-decadal transition in anomalous water vapour transport are investigated for the two major modes. The significant inter-decadal transition in anomalous water vapour transport is associated with the enhanced effect of the sea surface temperature (SST). Before the mid-1980s, the relationships between the two major modes and the SST of the tropical oceans are relatively weak. After the mid-1980s, the EOF1 becomes significantly regulated by the El Niño-Southern Oscillation (ENSO) in the previous winter, and the positive (negative) phase of the principal component of the first mode (PC1) corresponds to significantly positive (negative) SST anomalies over the tropical northern Indian Ocean and Maritime Continent during the same period. For EOF2, the anomalous water vapour transport over the tropical Indian Ocean is related to the enhanced inter-annual variability of tropical Indian Ocean dipole (TIOD) after the mid-1980s. The EOF1 of standardized summertime water vapour transport over the tropical Indian Ocean–western Pacific for the period 1961–1985: (a) spatial pattern, (c) the corresponding normalized PC1, (b), (d) the same as (a), (c), but for the period 1986–2015.

Description: Global climate change is likely to affect reference evapotranspiration (ET 0 ) and the use of water resources for vegetation management. Our goals were to identify spatio-temporal characteristics of ET 0 and factors controlling the change in ET 0 and to project spatio-temporal changes in the Qilian Mountains of China under the future climate conditions. Changes in ET 0 were estimated by the Penman–Monteith method for 22 meteorological stations from 1960 to 2015. We quantified the attributions of climatic factors with the differentiation equation method. Then, we assessed the spatio-temporal changes in projected ET 0 with CanESM2 model outputs and statistical downscaling model for three representative concentration pathways (RCP) scenarios for years 2016–2100. We found that annual ET 0 averaged across the region was 1001.5 mm, with an insignificant decrease of −0.43 mm/year during 1960–2015. The lowest values were present in the alpine region in the central area, while the highest ET 0 was detected in the western region. An annual and seasonal “evaporation paradox” existed in the Qilian Mountains during the past few decades. Mean daily air temperature measured ( T mean ) and wind speed ( U 2 ) were the dominant factors in ET 0 change. However, the decreasing trend in ET 0 may be due to a diminished effect of T mean triggered by short-wave radiation ( R s ), actual vapour pressure ( e a ), and wind speed ( U 2 ), but especially by the substantial reduction in U 2 at most stations. Compared with the baseline, ET 0 is likely to increase by 6.31–7.20, 6.11–10.41, and 6.58–17.66%, respectively, under RCP scenarios of 2.6 (very low forcing scenario), 4.5 (medium stabilization scenario), and 8.5 (very high emission scenario), but RCP2.6 ET 0 rates level off and even decline after 2050 while RCP4.5 rates climb only marginally after 2050. Thus, ET 0 projected with the CanESM2 model displayed an upwards trend in the Qilian Mountains, especially the central alpine region. ET 0 showed insignificant decreasing trends with increasing significant air temperature. Wind speed was the most important factor influencing ET 0 changes. Projected ET 0 displayed an upwards trend in the Qilian Mountains, especially the central alpine region. Increasing of evapotranspiration in the future may raise ecological water demand and aggravate water shortage.

Description: ABSTRACT Using daily output from 29 climate models provided by the Coupled Model Intercomparison Project Phase 5, we project signals in 12 extreme temperature indices and 12 extreme precipitation indices relative to 1986–2005 over China associated with a 2 °C global warming above pre-industrial levels under representative concentration pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). The model output reflects the following projected changes: (1) It is robust and statistically significant that warm extremes are more frequent, more persistent, and more intense than those during the baseline period of 1986–2005, and local signals emerge from natural internal variability over most of China. In particular, southern China faces severe heat stress in summer based on warm extreme indices. (2) It is robust and statistically significant that there are fewer cold extremes in China. Most models show no significant changes in the longest duration and intensity of most cold extremes in southern China and northwest China. (3) The multi-model median shows that more frequent and more intense wet extremes that deliver greater amounts of extreme precipitation occur in China, with a regional mean increase of 16.7–42.8 mm (8–42%) in total amount of annual wet extremes, but these changes are not significant and do not exceed natural internal variability over most of the country. Spatially, the Tibetan Plateau and northeast China have robust and significant changes in part of precipitation extremes, and some changes begin to emerge from natural internal variability at local scale. There are benefits to limiting global warming for China, including less frequent and less persistent warm extremes when comparing 1.5 °C with 2 °C of global warming and a later occurrence of significant changes in climate extremes when compared an intermediate mitigation scenario RCP4.5 with a high emission scenario RCP8.5. The multi-model median changes relative to the period 1986–2005 and signal-to-noise ratios for the annual warmest night (TNx, units: °C) over China associated with a 2 °C global warming as simulated by 29 CMIP5 models under RCP8.5. More than 80% of statistically significant models agree on the sign and signal-to-noise ratio is greater than 1.0, which is presented in colour with solid circles. More than 80% of statistically significant models agree on the sign and signal-to-noise ratio is less than 1.0, which is presented in colour with hollow circles. Less than 50% of models have a statistically significant signal, which is presented in colour only.

Description: ABSTRACT Decadal variations in autumn (September–October–November, SON) precipitation over North Central China since the 1940s are investigated using observations and reanalysis data. They are found to be significantly correlated negatively with the Pacific Decadal Oscillation (PDO). Further analyses indicate that the inter-decadal changes in SON precipitation over North Central China result from anomaly patterns in the large-scale atmospheric circulation in the mid-latitude Northern Hemisphere associated with the PDO. Specifically, during the negative phase of the PDO (1945–1976 and 2003–2014), an anomalous low pressure and cyclonic circulation are seen west of Lake Baikal, while positive pressure anomalies are located over the East Asia-Japan-North Pacific region, which weakens the East Asian trough (EAT). The weakened EAT favours southerly winds over North Central China. The negative pressure anomalies around Mongolia and Lake Baikal induce large-scale ascent motion to the west of the EAT, which also produces southerly advection of warm and moist air into North Central China, leading to increased precipitation there. These results reinforce the notion that PDO has a large impact on SON rainfall over North Central China on decadal timescales and highlight the need to further examine how the PDO induces the Eurasia atmospheric teleconnection pattern (e.g. East Atlantic/Western Russia pattern). Decadal variations in autumn (September–October–November, SON) precipitation over North Central China since the 1940s are investigated using observations and reanalysis data. They are found to be significantly correlated negatively with the Pacific Decadal Oscillation (PDO). The inter-decadal changes in SON precipitation over North Central China result from anomaly patterns in the large-scale atmospheric circulation in the mid-latitude Northern Hemisphere associated with the PDO.

Description: ABSTRACT A reconstruction of annual to multi-decadal precipitation based on ring-width of Cedrus deodara (Himalayan cedar or deodar) was carried out in the Lidder (Liddar) Valley, Kashmir Himalaya. A composite tree-ring chronology demonstrated a significant direct relationship with April–June precipitation. A modified version of point-by-point regression methodology was used to reconstruct April–June precipitation since 1723 C.E. This reconstruction accounts for 40% of the total variance of the actual precipitation in the calibration period. The reconstruction shows a prolonged decadal dry period between 1822 and 1887 C.E., the driest period in the reconstruction. The wettest period occurred during the early 19th century and latter part of the 20th century. Extreme dry and wet events have been identified in the reconstruction on the basis of percentile distribution. The reconstruction was compared with documented extreme flood, famines and drought events in Kashmir Valley occurring in those 288 years. The composite 500 mb height-anomaly maps suggest the prospect to study the long-term atmospheric circulation variability over the Kashmir Valley and surrounding region using tree-ring data. The impact of westerlies in the precipitation patterns was also evident in analysis of composite 500 mb height anomaly. Furthermore, the reconstruction was validated through comparison with independent records and spatial correlation with gridded precipitation and drought. Tree-ring-based April–June precipitation reconstruction from Lidder Valley, Kashmir Himalaya from 1723 to 2010 C.E. This reconstruction is based on large number of tree-ring samples and robust methodology as compared to earlier studies from the region. The reconstruction has coherence with documented extreme flood, famines and drought events in Kashmir Valley. The impact of westerlies in the precipitation patterns was also evident in analysis of composite 500 mb height anomaly.

Description: ABSTRACT Periods of extreme cold impact the mid-latitudes every winter. Depending on the magnitude and duration of the occurrence, extremely cold periods may be deemed cold air outbreaks (CAOs). A systematic CAO index and ranking system was developed from 20 surface weather stations from 1948 through 2016, based on a set of criteria concerning magnitude, duration, and spatial extent. Standard deviations in temperature were used to identify extreme temperatures relative to the station. A total of 49 CAOs occurred during the 67-year period, with the majority occurring during mid-winter. The number of CAOs proved to be largely dependent on the stations latitude and maritime influence. The duration, magnitude, and spatial extent were dependent on the time of the winter season in which the CAO occurred. Furthermore, two prominent clusters of an increased number of CAOs occurred during the 67-year period, suggesting multi-decadal circulations may be a factor in CAOs. In this article, it was found that 49 cold air outbreaks have occurred in the eastern United States from November 1948 through March 2016. The number of CAOs proved to be largely dependent on the stations latitude and maritime influence. The duration, magnitude, and spatial extent were dependent on the time of the winter season in which the CAO occurred. Furthermore, two prominent clusters of CAOs occurred during the 67-year period, suggesting multi-decadal circulations may be a factor in CAOs.

Description: ABSTRACT Establishing long-term records of rainfall variability is essential for understanding changes in the magnitude and frequency of extreme events. The need is particularly pressing for much of Africa, where the instrumental meteorological record rarely stretches back beyond the early 20th century. This study extends the rainfall record for present-day Malawi back to the mid-19th century through the analysis of historical documentary materials from British and African archives. Textual evidence within documents is used to construct a semi-quantitative chronology of rainfall variability spanning the period 1858–1900. Widespread and severe droughts are identified during the austral summer rainy seasons of 1861–1863, 1877–1879, 1885–1888, and 1892–1894, and two unusually wet periods in 1889–1892 and 1894–1898. Instrumental rainfall data from Cape Maclear, Bandawe, and Kaningina spanning the period 1876–1880 – the earliest so far discovered for Malawi – are compared with nearby long-term records from the Global Historical Climatology Network database. These analyses confirm the classifications for the equivalent years in the semi-quantitative chronology. The results of this study are considered alongside other annually resolved rainfall reconstructions for the southern African summer rainfall zone to assess the spatial extent of late 19th century drought and wetter episodes and to explore the distribution of teleconnections arising from historical El Niño events. The very strong 1877 El Niño event was associated with drought from northern Malawi to the Eastern Cape. In contrast, drier conditions during the strong 1885 El Niño extended from Malawi as far south as the southern Kalahari, with Lesotho and KwaZulu-Natal experiencing relatively wet conditions. The very strong 1891 El Niño was associated with very wet conditions from Malawi to KwaZulu-Natal. In contrast, wetter conditions only extended as far south as Zimbabwe following the moderate 1896 El Niño. The study concludes with suggestions on how to extend historical climate information for the region. Annual rainfall reconstruction for northern (region 1), central (region 2), and southern (region 3) Malawi derived from historical documentary sources. CR indicates confidence rating from highest (3) to lowest (1); a value of 0 indicates insufficient evidence to generate a classification. Inset shows average rainfall for Blantyre and Zomba Agricultural College downloaded from the GHCN database; note that data are not available for these stations for 1893–1895. El Niño years are also indicated.

Description: ABSTRACT A 31-year tropical cyclone (TC) size climatology (1980–2010) is established using the NCEP Climate Forecast System Reanalysis for the western North Pacific (WNP) and the North Atlantic (NA). The size of a TC, defined as the azimuthally averaged radius of 17 m s −1 wind near the sea surface, is estimated using the strong relationship between TC size and azimuthally averaged winds in the outer-core region of the TC. The estimation method is verified by comparing the TC size climatology established using the QuikSCAT satellite data. The monthly and annual variations in both climatologies agree with each other. Based on this 31-year data set, the mean TC sizes over the WNP and NA are 2.01° and 1.61° latitude, respectively. TC size in both basins exhibits temporal intra-seasonal and annual as well as spatial variations. Inter-annual TC size variations in the WNP are highly correlated ( r = 0.816) with El Niño-Southern Oscillation events. In WNP, the highest percentage of large TCs occurs near 25°N, which agrees with previous modelling and observational studies. The azimuthally averaged wind in the outer-core region of the tropical cyclone (TC) in CFSR is found to be highly correlated to TC size. The TC size is estimated by using this strong relationship and establishes a 31-year TC size climatology. The climatology could be used for study the TC size intra-seasonal, annual and inter-decadal as well as spatial variations.

Description: ABSTRACT Extreme rainfall events have large impacts on society and are likely to increase in intensity under climate change. For design and management decisions, particularly regarding hydraulic works, accurate estimates of precipitation magnitudes are needed at different durations. In this article, an objective approach of the regional frequency analysis (RFA) has been applied to precipitation data for the island of Sicily, Italy. Annual maximum series for rainfall with durations of 1, 3, 6, 12, and 24 h from about 130 rain gauges were used. The RFA has been implemented using principal component analysis (PCA) followed by a clustering analysis, through the k -means algorithm, to identify statistically homogeneous groups of stations for the derivation of regional growth curves. Three regional probability distributions were identified as appropriate from an initial wider selection of distributions and were compared – the three-parameter log-normal distribution (LN3), the generalized extreme value (GEV) distribution, and the two component extreme value (TCEV) distribution. The regional parameters of these distributions were estimated using L-moments and considering a hierarchical approach. Finally, assessment of the accuracy of the growth curves was achieved by means of the relative bias and relative root-mean-square error (RMSE) using a simulation analysis of regional L-moments. Results highlight that for the lower return periods, all distributions showed the same accuracy while for higher return periods the LN3 distribution provided the best result. The study provides an updated resource for the estimation of extreme precipitation quantiles for Sicily through the derivation of growth curves needed to obtain depth–duration–frequency (DDF) curves. In this article, an objective approach of the regional frequency analysis (RFA) has been applied to precipitation data for the island of Sicily, Italy. The study provides an updated resource for the estimation of extreme precipitation quantiles for Sicily through the derivation of growth curves needed to obtain depth–duration–frequency (DDF) curves.

Description: ABSTRACT In this study, the regional climate of the Korean Peninsula is dynamically downscaled using a high-resolution regional climate model forced by two representative concentration pathway scenarios of Hadley Centre Global Environmental Model version 2-Atmosphere and Ocean (HadGEM2-AO) using multiple regional climate models. Changes in extreme precipitation indices are investigated. Through the evaluation of the present climate, a multi-model ensemble reasonably reproduces the long-term climatology of extreme precipitation indices over South Korea despite some systematic errors. Both mean and extreme precipitation intensities for 80 years in the future (2021–2100) increase compared to those of the present. However, the increasing rates of indices related to precipitation intensities are different according to sub-period, season, and emission scenarios. Mean and extreme precipitation intensities of the future climate increase during the summer when most extreme precipitation events occur over the Korean Peninsula. Also, abnormal extreme precipitation can increase during future summers due to increasing variances of indices related to extreme precipitation intensity. Increasing extreme summer precipitation over South Korea is proportional to the increases in convective precipitation compared to non-convective precipitation. This indicates that future changes in summer precipitation, with regard to intensity and frequency, over South Korea, among representative concentration pathway scenarios, are more related to a change in convective instability rather than synoptic condition. This figure shows multi-model ensemble (MME) rate of change in six indices between future (2021–2100) and present (1981–2005) scenarios (%). Dashed lines denote the areas where all RCMs reproduce the same sign of indices. Overall extreme precipitation intensity as well as mean precipitation intensity increases in the future. Also, model results from the five RCMs are consistent in the regions with a high rate of change for the indices, implying that the changes in indices are highly reliable in that region.

Description: ABSTRACT This article presents a climatological study of the tropical Atlantic surface wind convergence, one of the main drivers of the marine intertropical convergence zone (ITCZ) precipitations, including coastal northeastern Brazilian and West African rainfalls. Climatological monthly mean surface wind convergence budget, as well as that of their month-to-month variations, is analysed over the 2000–2009 decade, using ocean–atmosphere reanalyses and satellite-derived data sets. Sea surface temperature (SST) influence is particularly investigated via comparison of its Laplacian with that of sea level pressure. Results for monthly means reveal that the Lindzen-Nigam paradigm does hold in regions of deep convection but only on their flanks. In deep convection regions, the budget analysis suggests the entrainment due to elevated heating by cumulus convection as the leading term. Elsewhere, over the ‘open ocean ITCZ’ meridional flanks, as well as over the ‘coastal one’ (Gulf of Guinea and northeastern Brazilian coasts), the pressure contribution is positive and largely dominated by its component below the boundary layer closely related to the SST. Horizontal advection is also found important over these areas, but with the pressure as the first-order driver. Otherwise, month-to-month variations of ITCZ are controlled by the geostrophy within the pressure contribution tightly dominated by the free tropospheric component. July-mean climatology (2000–2009) and QuickSCAT (a), CFSR (b), and ERAI (c) surface wind (vectors) and divergence (colour, 10 −6  s −1 ). Reynolds SST (a) and SST from reanalyses (b), (c) are represented on black contours (1 °C interval). Precipitation from GPCP in blue contours (3 mm day −1 interval) in order to point out the ITCZ position.

Description: ABSTRACT The present study compares the Indian summer monsoon rainfall (ISMR) prediction skill of monsoon mission climate forecast system version 2 (CFSv2-T382) with that of the seasonal prediction models participating in US National Multi-Model Ensemble (NMME) project. In general, the present-day models simulate cooler than observed sea surface temperature (SST) in majority of the Tropics and extratropics. The model rainfall has strong dry bias over major continental regions and wet bias over tropical oceans. Meanwhile, prediction of the boundary forcing such as SST is essential for driving the atmospheric response through teleconnections. It is noted that even though the prediction skill for SST boundary forcings like El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) is not at the best in CFSv2-T382 compared to a few of the NMME models, it shows better skill for ISMR hindcasts initialized at 3-month lead time (February IC). This may be attributed to the better teleconnection pattern of ENSO and IOD in CFSv2-T382, which has minimum biases in equatorial Indo-Pacific region. It also has a better ISMR–SST teleconnections in the Tropics with a pattern correlation of around 0.6. In many of the NMME models, the better prediction skill of the inter-annual variability of SST indices is not transformed into the improvement of ISMR skill through teleconnections. It is therefore concluded that having good prediction skill for major SST boundary forcings is not sufficient, but capturing the appropriate teleconnections of these SST boundary forcings in the model is critical for the better prediction of ISMR. The study points out that the present-day seasonal prediction systems need to be improved in their simulation of tropical SST–monsoon teleconnections, which can improve the seasonal prediction skill of Indian summer monsoon further. One area where the immediate focus is required is the Indian Ocean SST and ISMR teleconnection. Along with good prediction skill for major SST boundary forcings such as El Niño and IOD, their appropriate teleconnection spatial patterns also need to be captured well for the better prediction of the land precipitation like Indian summer monsoon rainfall. Here in the study, even though majority of the models has better skill for Nino3.4 index and IOD index, their spatial teleconnection pattern is higher for CFSv2-T382 (pattern correlation of 0.8) and also has less bias in tropical region. Thus as seen in the figure, it has better Indian summer monsoon rainfall (ISMR)–SST relationship (PCC = 0.6) compared to all other models and hence CFSv2-T382 has better skill (0.55) for ISMR, while skill is less than 0.1 for the models with PCC values very less. Spatial pattern of correlation between ISMR and seasonal SST anomalies from (a) observations, (b)–(p) individual model hindcasts and (o) MME of all models. Statistically significant (90% confidence level) correlations are stippled.

Description: ABSTRACT In this study, moisture sources for different intensities of summer (June–July–August) rainfall over the Chinese Loess Plateau (CLP) were investigated by performing a transient simulation for the period 1979–2009 using the Lagrangian particle dispersion model FLEXPART. The results showed that continental areas surrounding the CLP, namely northwestern China–eastern central Asia and central eastern China, were major moisture source regions for summer rainfall over the CLP and that oceanic moisture originated from the East China Sea, the South China Sea, the Bay of Bengal, and the Arabian Sea played a secondary role. The moisture contribution of northwestern China–eastern central Asia to the CLP significantly decreased with increasing intensity of rainfall, whereas the contribution of central eastern China to the CLP slightly increased. Moreover, the moisture contribution of oceanic source regions to the CLP increased with the increased rainfall intensity. The East China Sea and the Bay of Bengal were the two most substantial oceanic moisture source regions for the 0–5th percentile (0–P5th) to 50th–75th percentile (P50th–P75th) rainfall classes, whereas the South China Sea and the Bay of Bengal were the two most substantial oceanic moisture source regions for the 75th–95th percentile (P75th–P95th) and the 95th–100th percentile (P95th–P100th) rainfall classes. Ratios of moisture uptake over each source region to the total moisture release in the CLP for the P95th–P100th summer rainfall during 1979–2009 (unit: %). The ratios of the moisture finally released in the CLP and the unreleased moisture plus the moisture loss en route are represented in black and grey bars, respectively. The abbreviations of the source region are as follows: NCEC stands for northwestern China–eastern central Asia, CE for central eastern China, SCS for the South China Sea, ECS for the East China Sea, AS for the Arabian Sea, and BOB for the Bay of Bengal.

Description: ABSTRACT The changes in mean and extreme climate in China during 2020–2060 are detected with both Weather Research and Forecasting and RegCM4, by downscaling the simulations from EC-EATTH and IPSL-CM5A under both the RCP4.5 and RCP8.5 scenarios. The climate changes under the two scenarios exhibit similar patterns, with stronger intensity under the RCP8.5 scenario. For the mean precipitation, increases are projected in most regions, with the largest relative increase in the Tarim Basin. Slight drought mainly occurs in the south-eastern part of China. The frequency of drizzle rain is expected to decrease in all the sub-regions, but the moderate to heavy rainfall as well as the storm would occur more frequently, especially on the Tibetan Plateau. The whole country would experience much warmer climate in the future, with the strongest warming over the Tibetan Plateau. By detecting the changes in climate extremes, it is indicated that less dry extremes would occur in the wet areas of China, while more dry events in the arid and semiarid regions. The wet extreme indices would increase in most regions, especially in the wet areas. The surface air temperature tends to become extremely warmer in the future over the whole country, with the strongest change over the Tibetan Plateau. The changes in mean and extreme climate depend strongly on the driving global climate models, with wetter and warmer climate in the downscalings over IPSL-CM5A, and the model physics of the regional climate models also exert great impact on the projections. Finally, the possible mechanisms for the changes of extreme precipitation are discussed. The enhanced summer monsoon in the future transports more moisture to China, which could lead to more summer precipitation. As a result, the wet extremes tend to increase. The changes in mean and extreme climate in China during 2020–2060 are detected with both Weather Research and Forecasting and RegCM4, by downscaling the simulations from EC-EATTH and IPSL-CM5A under both the RCP4.5 and RCP8.5 scenarios. The future climate in China would become extremely warmer and heavy rainfall would occur more frequently, especially when downscaling IPSL-CM5A and under the RCP8.5 scenario. The enhanced summer monsoon in the future transports more moisture to China, leading to more summer precipitation, and thus the wet extremes tend to increase.

Description: ABSTRACT This study quantifies the spatial–temporal distribution of the near-surface temperature lapse rate (TLR) on the southeastern Tibetan Plateau (SETP) on the northern slopes of the eastern Himalayas, using the jackknife regression model. A 20-year (1985–2004) climatic data set of 16 stations between the elevation range of 3553–4801 m asl was used for this investigation. Controls for the spatial–temporal variation on TLRs and causes of higher mean square error (MSE) from the jackknife regressions were also analysed. Dry convection due to increasing sensible heating at lower elevations associated with clear skies, the effect of cold air surges, cloud/fog, as well as pronounced long-wave radiation loss due to snow cover at higher elevation, results in the super-dry adiabatic TLR in the dry winter. In response to the effects of high rainfall and humidity, intense latent heating at higher elevation due to moist adiabatic cooling causes TLRs to decrease significantly in summer. The variation in net radiation due to differences in moisture, rainfall, cloud cover and air mass between higher (fewer) and lower (higher) elevations further contributes to reducing TLRs values in this season. Observed steeper values of TLRs at higher elevations and more shallow values at lower elevations are due to the thermal contrast between snow-free ground and snow-covered mountain terrain, as well as the effect of variations in air mass and moisture. Based on derived values, this article also estimates near-surface temperature at higher elevations and analyses the precision of estimated values. Measurement of the lowest discrepancy (bias) between observed and estimated values from this study suggests that the estimation skills of the model are good enough. More precisely, including the smallest MSE from the jackknife regression and biases of the estimated values can be made for summer, perhaps due to the moisture controlled throughout the SETP, i.e. associated with the Indian monsoon. Higher MSE and biases are observed during winter and are due to the substantial effects of westerlies, as well as the station's geographical coordinate, local topography and microclimate. The MSE and the estimated biases are lowest at high-elevation stations and are associated with the lower contaminating effects of the surface. This estimation model, using derived values from this investigation, could be useful for glacier-hydro-climatic and ecological modelling in this region. Dry convection due to increasing sensible heating at lower elevations associated with clear skies, the effect of cold air surges, cloud/fog, as well as pronounced long-wave radiation loss due to snow cover at higher elevation results in the super-dry adiabatic TLR in the dry winter. In response to the effects of high rainfall and humidity, intense latent heating at higher elevation due to moist adiabatic cooling, as well as variation in net radiation between higher and lower elevations, causes TLRs to decrease significantly in summer. Steeper values of TLRs at higher elevations and more shallow values at lower elevations are due to the thermal contrast between snow-free ground and snow-covered mountain terrain, as well as the effect of variations in air mass and moisture. Based on derived values, this article also estimates near-surface temperature at higher elevations and analyses the precision of estimated values. More precisely, including the smallest MSE from the jackknife regression and biases of the estimated values can be made for summer, perhaps due to the moisture controlled throughout the SETP. Higher MSE and biases are observed during winter and are due to the substantial effects of westerlies, as well as the station's geographical coordinate, local topography and microclimate.