ALBERT

Description: ABSTRACT The present study investigates the characteristics of active and break cycles associated with the Indian summer monsoon (ISM) during developing and decaying phase of El Niño and in the years in which Indian Ocean Dipole (IOD) co-occurred with El Niño (co-occurred years). Observations show that break days are more in number (∼2–3 times) and long lasting (∼15–20 days) than active days in El Niño developing summers and vice versa for decay years. During El Niño developing years, northward propagation is well organized with significant anomalies in both active and break phases. The increased convection associated with active phase persists longer over Indian Ocean, than over the monsoon region, while the reduced convection in break phase propagates faster from ocean to land and persists there for a longer time. Compared to break events, active events have slower (faster) propagation over the monsoon (oceanic) region during El Nino decay years. The present study put forward the argument that the contrasting persistent circulations over Indo-western Pacific regions favour particular phase of intra-seasonal oscillation (ISO) in developing and decay phase of El Nino. These long-lasting circulations advect anomalous dry (moist) air to ISM region for longer period, resulting in long-lasting break (active) events in El Niño developing (decay) years. During co-occurrence years, the number of break (active) days is reduced by two to three times compared to the developing (decaying) phase of El Niño. It is found that 30- to 60-day scale ISO is strongly modulated, than 10 - to 20-day scale, by the changes in seasonal mean state associated with El Nino. Thus, this study demonstrates that the ISO characteristics such as its variance, northward propagation, spatial distribution and duration of active and break days are strongly modulated by seasonal background anomalies over the Indo-Pacific region.

Description: ABSTRACT The World Meteorological Organization (WMO) Lead Centre for Long-Range Forecast Multi-Model Ensemble (WMO LC-LRFMME) has been established to collect and share long-range forecasts from the WMO designated Global Producing Centres (GPC). In this study, the seasonal skill of the deterministic multi-model prediction of GPCs in WMO LC-LRFMME is investigated. The GPC models included in the analysis cover 30 years of common hindcast period from 1981 to 2010 and real-time forecast for the period from DJF2011/2012 to SON2014. The equal-weighted multi-model ensemble (MME) method is used to produce the MME forecast. We show that the GPC models generally capture the observed climatological patterns and seasonal variations in temperature and precipitation. However, some systematic biases/errors in simulation of the climatological mean patterns and zonal mean profiles are also found, most of which are located in mid-latitudes or high latitudes. The temporal correlation coefficients both of 2 m temperature and precipitation in the tropical region (especially over the ocean) exceed 95%, but drop gradually towards high latitudes and are even negative in the polar region for precipitation. The prediction skills of individual models and the MME over 13 regional climate outlook forum (RCOF) regions for four calendar seasons are also assessed. The prediction skills vary with season and region, with the highest skill being demonstrated by the MME forecasts for the regions of the tropical RCOFs. These predictions are strongly affected by the ENSO over Pacific Islands, Southeast Asia and Central America. Additionally, Southeast of South America and North Eurasian regions show relatively low skills for all seasons when compared to other regions.

Description: ABSTRACT This study examines the trends in reference evapotranspiration (ET o ) in Turkey by analysing data from 77 weather stations for a 32-year period (1975–2006). ET o values were calculated using the Penman–Monteith method using air temperature, wind speed, relative humidity, and sunshine hours data. Trends in annual and monthly ET o were determined using the Mann–Kendall trend test with the trend-free prewhitening procedure. The magnitude of trends was estimated by calculating the Sen's slope. The collective or field significance of the trends was evaluated using Walker test. The possible causes of changes in ET o were discussed by analysing the trends in air temperature, wind speed, relative humidity, and solar radiation data collected at the same stations. The implications of ET o trends for crop water requirements were evaluated. The analyses showed that the majority of stations (88%) in Turkey had annual ET o between 750 and 1200 mm during the 32-year period and ET o decreased gradually from south to north. From 1975 to 2006, 58% of stations had upward trends in annual ET o . Upward trends were statistically significant at the 0.05 level for 32% of stations. The rates of changes in annual ET o were on average 1.20 mm year −2 . The trends detected in monthly ET o were mostly upward with an average magnitude between −0.01 and 0.14 mm month year −1 . Trends detected at the annual timescale and for the majority of the months provided the field significance at the 0.05 level. Analysis of other climatic data showed that upward trends in air temperatures, downward trends in wind speeds, and downward trends in relative humidity were widespread over Turkey for the same time period. Changes in these three parameters could explain the majority of the changes in ET o rates. The ET o changes affect crop water requirements and increase the demand for irrigation.

Description: ABSTRACT We explore the occurrence of intraseasonal summer heat waves in southeastern Patagonia (SEPG, 46°–52°S; 65°–70°W) since the late 19th century by means of the Twentieth Century Reanalysis version 2 (20CRv2). In total, we identify 201 cases for 1872–2010 using criteria of intensity and persistence. In SEPG, the corresponding intraseasonal temperature signals are centred around the first day of each cluster of days fulfilling those conditions (named day 0). The mean warm deviation lasts for approximately 2 weeks and exhibits a mean temperature peak of 4.3 °C on day 0 (the warmest day in the mean signal). In a regional context, the mean temperature perturbation associated with these heat waves affects a broad area on both sides of the Andes. The warming in SEPG is caused by temperature advection and enhanced radiative heating, following a high pressure system over southern South America (SSA). This atmospheric perturbation is embedded in a wave-train-like pattern along the South Pacific. As part of this pattern, a cyclonic anomaly progresses eastward over the Tasman Sea in Oceania, moving from southeastern Australia (day −6, causing a dry anomaly there) over New Zealand (day −3, inducing a wet anomaly on its Southern Island). The anomalous circulation triggered by the wave train leads thus to a teleconnection between SSA and Oceania, documented in a previous work for the interannual scale. Two thirds of the heat wave events are linked to enhanced ascent in the South Atlantic Convergence Zone (SACZ) and around one third of the events within 1957–2010 are associated with extreme absolute maximum temperatures observed at a station-based record from SEPG. Finally, possible spatial modulations of the wave train pattern at the interannual and interdecadal timescales are discussed.

Description: ABSTRACT The Pacific-Japan (PJ) pattern affects interannual variability in the East Asian and western North Pacific (WNP) summer monsoons. This teleconnection pattern is characterized by a meridional dipole of anomalous circulation and precipitation between the tropical WNP and the midlatitudes. This study develops a long index of the PJ pattern using station-based atmospheric pressure data to track the PJ variability from 1897 to 2013. This index is correlated with a wide array of climate variables including air temperature, precipitation, Yangtze River flow, Japanese rice yield and the occurrence of tropical cyclones over the WNP (especially those that make landfall on the Chinese and Korean coast). For the recent three decades, the PJ index reproduces well-known correlations with El Niño-Southern Oscillation (ENSO) in the preceding boreal winter and Indian Ocean temperature in the concurrent summer. For the 117-year period, this ENSO-PJ relationship varies on interdecadal time scales, with low correlations in the 1920s and from the 1940s to 1970s, and recurrences of significant correlations at the beginning of the 20th century and the 1930s. In accordance with the modulation, the magnitude and regional climate effect of the PJ variability have changed. These results highlight the importance of interdecadal modulations of climate anomalies in the summer WNP and the need of long-term observations to study such modulations.

Description: ABSTRACT The aim of this article is to present a methodology that describes the relationship between two time series according to their oscillatory modes. Cross-wavelet analysis is used to analyse the connection between the outputs of the empirical mode decomposition (EMD). The combined EMD and cross-wavelet methodology is used for the description of the connection between the annual mean streamflow of Quebec rivers and the North Atlantic Oscillation index (NAO). The relationship between the two time series is analysed by cross-wavelet analysis at the level of the mode of oscillation extracted from the EMD algorithm. The resulting cross-spectra are obtained individually for 18 stations and show intermittent intensity in these relationships between 1970 and 1990 for different oscillation modes. To highlight its particularity, the present methodology is compared with the results of a similar combination of multiresolution analysis (MRA) and cross-wavelet analysis. It shows that EMD isolates clearer bands of frequencies than MRA. Finally, a multi-site analysis is proposed, which performs a principal component analysis of the cross-spectra. This analysis illustrates the evolution of the relationships according to the geographic location. Finally, the advantages and limitations of the proposed methodology are discussed.

Description: ABSTRACT Hot summer days may lead to reduced thermal discomfort, labour productivity, and higher morbidity and mortality for vulnerable groups. The projected climate change may raise this thermal discomfort in the future. To implement measures to prevent adverse health conditions, robust estimates of the future human thermal comfort (HTC) are required. This study analyses the future HTC for both coastal and inland Dutch cities and countryside. The future conditions are based on the KNMI-06 climate scenarios. Using these scenarios, observed weather data from 1976 to 2005 are transformed to future weather design data representative for 2050. Subsequently, HTC expressed in the physiological equivalent temperature (PET) is estimated for these future scenarios. A substantial increase of heat stress abundance is foreseen in all climate scenarios, for both urban and rural areas, particularly, under the most intense warming. In these scenarios, the frequency of hours with heat stress will more than double, and the increase will develop faster in an urban canyon than in rural areas. In urban areas, PET shows a maximum as function of sky-view factor (SVF), i.e. for a smaller SVF a wind speed reduction increases the PET on one hand and shading reduces the PET on the other hand.

Description: ABSTRACT El Niño phenomenon is the leading mode of sea surface temperature interannual variability. It can affect weather patterns worldwide and therefore crop production. Crop models are useful tools for impact and predictability applications, allowing to obtain long time series of potential and attainable crop yield, unlike to available time series of observed crop yield for many countries. Using this tool, crop yield variability in a location of Iberia Peninsula (IP) has been previously studied, finding predictability from Pacific El Niño conditions. Nevertheless, the work has not been done for an extended area. The present work carries out an analysis of maize yield variability in IP for the whole 20th century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate-dependent time series of crop yield for the whole region, and to use these yield to analyse the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature–yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The potential usefulness of this study is to apply the relationships found to improving crop forecasting in IP.

Description: ABSTRACT There is growing evidence of significant changes in components of the Antarctic climate system, an important issue given the influence Antarctica has on global climate. It is important to infer to what extent these regional changes could be attributed to human-induced processes and to what extent to natural variability. Standard methods such as linear trend estimates or piecewise linear trends can be inadequate because they may result in erratic, non-systematic results, particularly if different scales of variability are present in each record and various records are to be compared. The Orcadas Antarctic Station (Argentina), with daily surface meteorological observations since April 1903, provides Antarctica's longest observational record. This study analyses the Orcadas seasonal surface temperature variability. Multidecadal variability and short-term trends are studied to provide an improved assessment of climate evolution and necessary information for the determination of mechanisms driving regional/local change. A combined method using wavelet transform (WT), non-linear statistical model approaches and derivative of fits is developed. This methodology is also applied for validation and comparison to the Gomez ice core oxygen isotope record for the 1857–2006 and 1903–2006 time intervals. Significant quasi 50-year and quasi 20-year variability bands were obtained, both for the quarterly and seasonal Orcadas temperature records, with warming (cooling) periods detected between 1903–1912, 1927–1961 and 1972–2004 (1912–1927 and 1962–1972). If seasons are considered, the only one with a fairly sustained warming is summer, where actual cooling is observed only at the beginning, prior to the early 1930s. Quasi 50-year variability was also detected in the Gomez record. Long periods are obtained in the model fits, longer than the time series, which varied with window length. Although not representing variability cycles, they could represent the best fit of the non-linear, non oscillating asymptotic stationary component of the series, i.e. a non-linear trend.

Description: ABSTRACT This article presents a climatology of total cloud cover (TCC) in the area of the three inland Eurasian seas (Black, Caspian, and Aral Sea). Analyses are performed on the basis of 20 years of data (1991–2010), collected from almost 200 ground stations. Average TCC is 49%, with broad spatial and seasonal variability: minimum TCC values are found in summer and to the southeast, whereas maximum values correspond to winter and to the northwest. For the whole area, linear trend analyses show that TCC did not vary during the study period. We only detected a statistically significant positive trend (+1.2% decade −1 ) in autumn. We obtained different results for the regions delimited by means of a principal component analysis: a clear decrease, both for the annual, spring, and summer series, was detected for the south of Black Sea, while increasing TCC was found for the annual, autumn, and winter series in the north Caucasus and the west and north of Black Sea. We also analysed the TCC data from global gridded products, including satellite projects [International Satellite Cloud Climatology Project (ISCCP), Pathfinder Atmospheres Extended (PATMOS-x), cLoud, Albedo & Radiation (CLARA)], reanalyses [ERA-interim, National Centers for Environmental Prediction/Department of Energy (NCEP/DOE), Modern-Era Retrospective Analysis for Research and Applications (MERRA)], and surface observations [Climatic Research Unit (CRU)]. Although all these products capture the seasonal evolution over the study area, they differ substantially both among them and in relation to the ground observations: reanalyses produce much lower values of TCC, while ISCCP and CLARA provide a summer minimum that is too high. Trend analyses applied to these data generally showed a decrease in TCC; only CRU and NCEP/DOE tally with the ground data as regards the absence of overall trends. These results are discussed in relation to previous studies presenting trends of other variables such as sunshine duration, diurnal temperature range, or precipitation; we also discuss the connections with changes in synoptic patterns and environmental changes, in particular in the Aral Sea region.

Description: ABSTRACT The Southern Annular Mode (SAM) is a natural climate mode of variability whose discovery can be traced back at least as far as the beginning of the 20th century, before human activities produced enough gases to noticeably change the climate. However, recent observed changes in the SAM are linked to increases of greenhouse gases and stratospheric ozone depletion, hence assigning SAM's alterations, in large part, to human activities. In this study, the 20th century reanalysis data were used to establish the SAM's prominent shifts during the years 1917, 1961 and 1997. The first shift coincides with abrupt greenhouse gas increases and the latter shifts are attributed to stratospheric ozone level changes. The East Africa ‘Short Rains’ (EASR) index derived from the Global Precipitation Climatology Center (GPCC) dating back to the beginning of the 20th century, demonstrates coinciding shifts with the SAM index. However, the SAM's influence on EASR appears to be achieved through a meridional dipole that is formed in the sea-level pressure of the Indian Ocean basin, with one pole over the Tropics and the other over the extratropics. When this dipole pattern is weakly developed as the period between 1961 and 1997, the SAM is decoupled from the EASR and the Indian Ocean Dipole (IOD) demonstrates a dominant role in modulating the EASR. The SAM is also linked to the IOD through its control of the Mascarene High variability, hence connecting the SAM to the dominant circulation variability in the Indian Ocean. Although the El Nino Southern Oscillation is strongly correlated to EASR, it is not related to the epochal variability in the rainfall. Therefore, the slow modulation in EASR is linked to the SAM whose shifts are triggered by gases emanating from human influences.

Description: ABSTRACT The Hawaiian Islands have one of the most spatially diverse rainfall patterns on earth. Knowledge of these patterns is critical for a variety of resource management issues and, until now, only long-term mean monthly and annual rainfall maps have been available for Hawai‘i. In this study, month-year rainfall maps from January 1920 to December 2012 were developed for the major Hawaiian Islands. The maps were produced using climatologically aided interpolation (CAI), where the station anomalies were interpolated first, and then combined with the mean maps. A geostatistical method comparison was performed to choose the best interpolation method. The comparison focuses on three kriging algorithms: ordinary kriging (OK), ordinary cokriging (OCK), and kriging with an external drift (KED). Two covariates, elevation and mean rainfall, were tested with OCK and KED. The combinations of methods and covariates were compared using cross-validation statistics, where OK produced the lowest error statistics. Station anomalies for each month were interpolated using OK and combined with the mean monthly maps to produce the final month-year rainfall maps.

Description: ABSTRACT E-OBS(European Observations) is a gridded climate data set which contains maximum temperature, minimum temperature, and precipitation on a daily time step. The data can be as fine as 0.25° in resolution and extends over the entire European continent and parts of Africa and Asia. However, for studying regional or local climatic effects, a finer resolution would be more appropriate. A continental data set with resolution would allow research that is large in scale and still locally relevant. Until now, a climate data set with high spatial and temporal resolution has not existed for Europe. To fulfil this need, we produced a downscaled version of E-OBS, applying the delta method, which uses WorldClim climate surfaces to obtain a 0.008 ° (about 1 × 1 km) resolution climate data set on a daily time step covering the European Union. The new downscaled data set includes minimum and maximum temperature and precipitation for the years 1951–2012. It is analysed against weather station data from six countries: Norway, Germany, France, Italy, Austria, and Spain. Our analysis of the downscaled data set shows a reduction in the mean bias error of 3 °C for mean daily minimum temperature and of 4 °C for mean daily maximum temperature. Daily precipitation improved by 0.15 mm on average for all weather stations in the validation. The entire data set is freely and publically available at ftp://palantir.boku.ac.at/Public/ClimateData .

Description: ABSTRACT In this study, we investigated changes in the precipitation characteristics for China from 1960 to 2012 based on a recent daily precipitation dataset of 666 climate stations and robust non-parametric trend detection techniques. We divided all precipitation events into four non-overlapping categories: light, moderate, heavy and very heavy based on percentile thresholds. We then established the trends for annual total and precipitation of different intensity categories, and examined their regional and seasonal variations. The results show that there was little change in annual total precipitation for entire China, but distinctive regional patterns existed. In general, precipitation increased in the west and decreased in east. Precipitation of different intensities, in general, changed in the same direction as the mean, but heavy and very heavy precipitation events had higher rates of change than mean precipitation. The exception was the southeast region, where despite the slight decrease in mean precipitation, heavy and very heavy precipitation still increased significantly. In addition, we used multiple regression models to explore the contribution of changes of frequency and intensity to total precipitation change, and the contributions of changes of precipitation at different intensities to total precipitation change. For western China, total precipitation change was associated more with frequency change, whereas in eastern China intensity contributed more. For precipitation amount, moderate, heavy and very heavy precipitations contributed to the total change, with little contribution from light precipitation change. For frequency, changes in light and moderate precipitation frequencies dominated the total change, with very little contributions from heavy and very heavy precipitation frequency changes. In addition, we examined the linkage between summer precipitation in eastern China and the East-Asian Summer Monsoon (EASM), found that the northern decrease and southern increase in summer precipitation was likely caused by the weakening of EASM over the study period.

Description: ABSTRACT Southeastern South America (SESA) rainfall is influenced by the tropical Pacific, Atlantic and Indian Oceans. At the same time, these tropical oceans interact with each other inducing sea surface temperature anomalies in remote basins through atmospheric and oceanic teleconnections. In this study, we employ a tool from complex networks to analyse the collective influence of the three tropical oceans on austral spring rainfall variability over SESA during the 20th century. To do so we construct a climate network considering as nodes the observed Niño3.4, Tropical North Atlantic (TNA), and Indian Ocean Dipole (IOD) indices, together with an observed and simulated precipitation (PCP) index over SESA. The mean network distance is considered as a measure of synchronization among all these phenomena during the 20th century. The approach allowed to uncover two main synchronization periods characterized by different interactions among the oceanic and precipitation nodes. Whereas in the 1930s El Niño and the TNA were the main tropical oceanic phenomena that influenced SESA precipitation variability, during the 1970s they were El Niño and the IOD. The influence of El Niño on SESA precipitation variability might be understood through an increase of the northerly transport of moisture in lower-levels and advection of cyclonic vorticity in upper-levels. On the other hand, the interaction between the IOD and PCP can be interpreted in two possible ways. One possibility is that both nodes (IOD and PCP) are forced by El Niño. Another possibility is that the Indian Ocean warming influences rainfall over SESA through the eastward propagation of Rossby waves as suggested previously. Finally, the influence of TNA on SESA precipitation persists even when the El Niño signal is removed, suggesting that SST anomalies in the TNA can directly influence SESA precipitation and further studies are needed to elucidate this connection.

Description: ABSTRACT How boreal summer intraseasonal oscillation (BSISO) modulates the probability and spatial distributions of extreme rainfall occurrence over populous southern China was examined, using the newly proposed BSISO indices and two high-resolution rain-gauge-based rainfall datasets in China. The probability density function of May–August rainfall in southern China is skewed towards large values in phases 2–4 of the first component and in phases 5–7 of the second component of BSISO life cycle, during which the probability of extreme rainfall events at the 75th (90th) percentile increases by 30–50% (over 60%) relative to the non-BSISO period. The devastating floods with prolonged extreme rainfall in southern China over the three past decades occurred coincidently with these BSISO phases. The first component of BSISO, associated with 30–60-day eastward/northeastward-propagating ISO, is more favourable for the rainfall extreme over in-land China. In contrast, the second component of BSISO, related to the 10–30-day northwestward propagating ISO, tends to link with the rainfall extreme along the southeast coast of South China. Moisture budget indicates that the favourable environment for rainfall extreme is associated with southwesterly moisture convergence over southern China, while the moisture advection contributes insignificantly. This study suggests a potential for monitoring and probabilistic prediction of extreme rainfall events in southern China based on the real-time BSISO indices.

Description: ABSTRACT The sea surface temperature (SST) in the Bay of Bengal (BoB) during the period 1960–1995 showed a decadal cycle, riding over a warming trend. The disruption of the decadal cycle was noticed post-1995 and was followed by a slowdown in the sea surface warming. The cause for the disruption of the SST decadal cycle was the weakening of the link between SST and sunspot number. The rising trend in the SST is due to the increasing atmospheric CO 2 concentration. The post-1995 SST slowdown was due to the increasing influence of the number of depressions, cyclones and severe cyclones in the BoB, the occurrence of which showed an upward trend. Using Price–Weller–Pinkel model we show that cyclonic systems deepen the mixed-layer through enhanced mechanical-mixing with cooler sub-surface waters, thereby reducing the mixed-layer temperature and consequently the SST. This process opposes the SST rise due to increasing atmospheric CO 2 concentration. The net effect of the wind-mixing caused by the increased number of depressions, cyclones and severe cyclones and the increased CO 2 concentration is a SST slowdown in the BoB. This mechanism differs from the SST slowdown mechanisms suggested for the Atlantic and the Pacific.

Description: ABSTRACT In the last few years, there has been an increasing application of gridded precipitation data sets for studies analysing seasonal and interannual precipitation variability as well as for performing validation analysis of climate and regional models. Consequently, the purpose of the present study is to analyse the representation of temporal variability and spatial patterns of precipitation in South America for the period 1971–2010, derived by three data sets based exclusively on rain gauge information (Climate Research Unit – CRU, Global Precipitation Climatology Centre – GPCC and University of Delaware – UDel), in order to identify discrepancies and/or agreements among them. Further analysis is performed for three particular sub-regions within the continent (southern sector of southeastern South America – SSESA, central South America – CSA and southeastern Brazil – SEBR). Results show that the three products represent key spatial features of precipitation analogously. Significant coherence in capturing the temporal variability, associated with the dominant modes of variability, is found in all sub-regions, though they differ largely in some areas, especially in CSA. Overall, depending on the region, the gridded products behave differently, without one particular data set standing out as an outlier in all the analysed cases.

Description: ABSTRACT Land and water management in semi-arid regions requires detailed information on precipitation distribution, including extremes, and changes therein. Such information is often lacking. This paper describes statistics of mean and extreme precipitation in a unique data set from the Mount Kenya region, encompassing around 50 stations with at least 30 years of data. We describe the data set, including quality control procedures and statistical break detection. Trends in mean precipitation and extreme indices calculated from these data for individual rainy seasons are compared with corresponding trends in reanalysis products. From 1979 to 2011, mean precipitation decreased at 75% of the stations during the ‘long rains’ (March to May) and increased at 70% of the stations during the ‘short rains’ (October to December). Corresponding trends are found in the number of heavy precipitation days, and maximum of consecutive 5-day precipitation. Conversely, an increase in consecutive dry days within both main rainy seasons is found. However, trends are only statistically significant in very few cases. Reanalysis data sets agree with observations with respect to interannual variability, while correlations are considerably lower for monthly deviations (ratios) from the mean annual cycle. While some products well reproduce the rainfall climatology and some the spatial trend pattern, no product reproduces both.

Description: ABSTRACT Precipitation variability at inter- and intra-annual scales may influence land-use management decisions in semi-arid savannas worldwide, and in particular, over the Kavango-Zambezi Transfrontier Conservation Area (KAZA) in southern Africa. Over KAZA, spatiotemporal precipitation variability forced by the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) is important to local and regional-scale decisions for planting, livestock grazing, and wildlife migration patterns. We investigate the annual water year (October–September) and early rainy season [October–November–December (OND)] precipitation patterns during 60 years before and after a 1970s shift in the global ocean–atmosphere system for this region in southern Africa. The coincidence of the number of wet (upper tercile) and dry (lower tercile) years and OND seasons during the various phases of ENSO and IOD are compared prior to (1950–1975) and after (1980–2008) the 1970s climate shift over KAZA. Since the 1970s climate shift, KAZA has been significantly drier and observed fewer wet years and OND seasons. ENSO is the dominant forcing of precipitation differences over southern Africa before and after the 1970s climate shift, with IOD playing a secondary role. However, when ENSO and IOD phases are analysed simultaneously, El Niño and positive IOD events are significantly related to dry periods. The forcing of atmospheric circulation over southern Africa before and after the 1970s climate shift during El Niño and La Niña events is significantly different. Prior to the 1970s climate shift, atmospheric circulation during El Niño (La Niña) favoured strong (weak) precipitation increases (decreases). Afterward the 1970s climate shift, atmospheric circulation during La Niña (El Niño) favoured strong (weak) precipitation decreases (increases). The shifting nature of climate modes, especially ENSO, and respective influence on rainfall variability for southern Africa is important to understand to better inform seasonal climate forecasts to improve operational decision-making for land-use and water management decisions in semi-arid savanna regions.

Description: ABSTRACT A unique approach for downscaling daily precipitation extremes from historical analogues is presented. While various analogue methods have been developed for the purpose of downscaling local climate data, few have placed an emphasis on downscaling daily extremes. Unlike previous approaches, the new method utilizes a two-step procedure in which the occurrence of extreme precipitation on a given target day is first determined based on the observed probability of extreme precipitation on that day's closest historical analogue days. Then, if extreme precipitation occurred on the selected analogue day, the historical precipitation observations associated with the analogue day are used to ascribe precipitation amounts on the corresponding target day. The method is developed and tested for a very strict definition of extreme precipitation (partial duration series events), as well as a more lenient definition of extreme precipitation (95th percentile of non-zero precipitation events). The analogue approach is more skillful than climatology at identifying the occurrence of both partial duration series (PDS) and 95th percentile events. In both cases, the analogue method slightly underestimates the observed occurrence of extreme precipitation. Return period precipitation amounts estimated from the downscaled PDS are similar to, but generally lower than those calculated from observed PDS. Over the entire study domain (157 stations in New York State and surrounding regions of adjacent states and Canada), the median difference between downscaled and observed 5-year (100-year) return period precipitation amounts is less than 5% (10%). These median differences are smaller than those obtained from historical dynamically downscaled climate model simulations.

Description: ABSTRACT The summer time cloud diurnal cycle over western Iberia is analysed here using a satellite climate data record of fractional cloud cover based on 9 years of Meteosat Second Generation observations which is distributed by the EUMETSAT's Climate Monitoring Satellite Applications Facility. These observations were complemented with a corresponding mean cloud diurnal cycle using SYNOP reports on six locations over the studied domain. It is shown that the main coastal mountain range separates regions that are characterized by two very different cloud regimes: stratocumulus-topped boundary layer convection dominates the region towards the coast and continental cumulus convection dominates the region to the east of these mountains. To explain the observed variability, a long-term regional climate model [Weather Research and Forecasting model (WRF)] simulation over Iberia was used. A comparison of the observations against model output for the common period between observations and simulation shows that although the model generally underestimates cloudiness, it is able to represent the diurnal cycle in a realistic manner. It is shown that the observed cloud diurnal evolution is linked to the thermal circulations generated by the land-sea contrast and orography. The extent to which the cloud deck penetrates inland is closely related to the coastal orography: although smaller hills tend to enhance cloudiness, larger mountains block the progression of the marine boundary layer further inland, as it behaves as a density current. Larger mountains also produce katabatic flow and a rather strong subsidence aloft during the night. The warming due to this subsidence helps the blocking of the cloud deck as it is partially responsible for evaporating clouds, as shown by a potential temperature budget analysis.

Description: ABSTRACT High-quality temperature estimates with good spatio-temporal coverage are necessary for completely understanding the influences of warming climate on cryosphere and hydrological systems in High Mountain Asia (HMA). In this study, we compare reanalysis temperature data from ERA-Interim and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) with station observations in HMA during 1979–2011. The results indicate that although reanalysis temperature data can capture the warming trends in HMA, the trend magnitudes are clearly underestimated by reanalysis data. In particular, the increase in summer temperature cannot be identified from the NCEP/NCAR reanalysis. For ERA-Interim, temperature increases are underestimated in the north and northwest of HMA; for NCEP/NCAR, the warming magnitudes show evident biases in the Pamir, Himalayas, and southeastern Tibetan Plateau. Considering that high-frequency signals and periodical fluctuations among the three datasets are in good agreement, and based on the wavelet transform method, the low-frequency component decomposed from the temperature time series of ERA-Interim and NCEP/NCAR reanalyses is adjusted by that derived from station observations. The resulting homogenized reanalysis temperature data show much better spatio-temporal consistency with station data. The differences in monthly and annual temperature anomalies between station and homogenized ERA-Interim and NCEP/NCAR reanalysis data become more convergent. The homogenized temperature time series are better correlated with station data at annual and seasonal timescales.

Description: ABSTRACT The mean climatology, seasonal and interannual variability and trend of wind speeds at the hub height (80 m) of modern wind turbines over China and its surrounding regions are revisited using 33-year (1979–2011) wind data from the Climate Forecast System Reanalysis (CFSR) that has many improvements including higher spatial resolution over previous global reanalysis products. Mean 80-m wind speeds are consistently higher over China Seas and the ocean areas than over land, and inside China high winds are found in areas of Inner Mongolia and the Tibetan Plateau. There is a considerable seasonal variability that reflects primarily the influence of East and Southeast Asia Monsoon with generally higher speeds in winter followed by summer, and weaker winds in autumn, followed by spring. There is also a strong interannual variability, and regions of larger amplitude of variability coincide with regions of higher mean winds. A decreasing trend, dominated by a sharp decline beginning in 2005, is seen across China and the surrounding seas in summer and autumn, and the summer trends over land and over ocean appear to be related respectively to the Pacific Decadal Oscillation (PDO) and the East Asian summer monsoon. Trends are not consistent across the region in spring and winter, however, with positive trends over some areas in northeastern and northwestern China, Mongolia and tropical oceans whereas negative trends in other regions. Nearly all areas of China experience mean annual 80-m wind speed less than 6.9 m s −1 (wind power classes of 1–2) except for some areas of Inner Mongolia where mean annual 80-m wind speeds exceed 6.9 m s −1 (Classes 3 or higher, suitable for wind energy development). China Seas and ocean areas generally fall in Class 3 or above, with the Taiwan and Luzon Straights reaching the highest Class 7.

Description: ABSTRACT Capturing the intensity and return period of extreme rainfall events in the historic record and projecting them into the future are essential to managing, planning, and designing infrastructure. In this study, we assess the performance of the combination of four General Circulation Models (GCMs) and six Regional Climate Models (RCMs) that comprise the North American Regional Climate Change Assessment Program (NARCCAP) and evaluate their performance in simulating rainfall extremes in the continental United States. We adopt a regionalization method to objectively delineate 12 regions in the continental United States with relatively homogenous annual maximum 24-h rainfall patterns from the North American Regional Reanalysis (NARR) data set. We then compare the Intensity–Duration–Frequency (IDF) curves generated from control simulations of NARCCAP models with those from NARR in each of these regions. We find significant spatial variability of model performance. The models perform reasonably well in many parts of the country, but poorly in the southeastern United States. The GCM providing boundary conditions strongly influences results – output from those RCMs driven by the Community Climate System Model (CCSM) and Canadian Global Climate Model version 3 (CGCM3) matched the NARR data best. Performance of individual RCMs also varied, often in response to nudging, wherein the regional model is constrained by the GCM fields. We also measure changes in bias-corrected IDF curves generated from NARCCAP projections of the future. In most regions, most models project intensified 24-h rainfall events in the future (exceptions include some model-projected decreases in southern California, the extreme north-central US, Florida, and the Texas Plains). This study provides a valuable means of assessing NARCCAP models' performance in simulating rainfall extremes at the regional scale and understanding how the GCMs, RCMs, and spatial variability affect model performance.

Description: ABSTRACT Climate data from the southwest coast of the Caspian Sea (CS) were statistically analysed to find connections with large-scale atmospheric variabilities and regional impacts. The study area is characterized by a subtropical humid climate. This enclave of high precipitation is extremely important for Iranian food production and is recognized for its high biodiversity. The data sets were investigated for inconsistencies before carrying out the main investigations, and several problems have been identified. The results show three distinct climatic periods in the temperature time series since 1956: 1956 to 1975 with values near to the overall mean, 1977 to 1995 with values lower by 0.5 °C and from 1996 to 2010 with values higher by 0.5 °C. These periods can be positively correlated with rapid sea level changes of the CS. Moreover, an agreement exists between the three climatic periods and the North Atlantic Oscillation (NAO) variability. The sea surface temperature of the southern CS is shown to be the driving force of the 2 m temperatures in the study area. While temperature changes are in accordance with NAO variability, the precipitation variations show connections with ENSO and less with NAO. The trends of precipitation during the period are diverse but display mostly a weak decrease, while the trends of temperature display a clear increase, larger than that for global mean temperatures, overlaid with inter-decadal variations.

Description: ABSTRACT This paper studies how the anthropogenic-induced global warming affects the East Asian winter monsoon (EAWM) by using 26 Coupled Model Intercomparison Project phase 5 (CMIP5) models. The simulated present-day EAWM is evaluated and future projections under RCP4.5 and RCP8.5 scenarios are presented in terms of the climatology and interannual variability. All 26 models can well reproduce the spatial pattern of EAWM climatology and 16 out of the 26 models can reasonably capture major features of interannual variability. The projection made by 26-model ensemble mean indicate that winter surface air temperature averaged over 20°–60°N, 100°–140°E will increase by 3 °C in RCP4.5 and 5.5 °C in RCP8.5 towards the end of the 21st century. The corresponding regional mean precipitation will increase by 12.3% in RCP4.5 and 21.8% in RCP8.5. The strong warming over high-latitude North Pacific due to melting sea ice in the Bering Sea and Okhotsk Sea leads to significant intensification and a northward shift of the Aleutian Low, resulting in prominent increase in the low-level northerly along the coastal regions of northeastern Asia. At 500 hPa the characteristic East Asian Trough is projected to weaken slightly and tilt more eastward with latitude. The selected 16-model ensemble mean projects future enhanced interannual variability of surface air temperature and sea-level pressure over mid-latitude North Pacific and high-latitude East Asia (EA) and reduced variability over eastern China, suggesting that the EAWM will be more variable in the high-latitude EA and mid-latitude North Pacific but less variable in East China. Accordingly, the year-to-year precipitation variability will be significantly enhanced over high-latitude EA. Majority of the 26 models project that the leading mode of EAWM interannual variation (the ‘northern mode’) will become more dominant in the warmer climate.

Description: ABSTRACT Crop loss due to drought is a complex issue, because it changes according to the drought intensity and duration, and the developmental stage of the plants when drought occurs. In order to assess the drought-induced decline in crop harvest, drought variability and the yield sensitivity of winter wheat, maize, sugar beet, and sunflower to drought during their growing seasons is investigated in the Republic of Moldova. This is then used as an example of the response of non-irrigated crops to increasing drought tendency in south-eastern Europe. The quantification of drought was done by using the standardized precipitation evapotranspiration index (SPEI) at 1- to 12-month lags during the period from 1951 to 2012. The relationship between drought at various time scales and the standardized yield residuals series (SYRS) for individual crops over the country and the Balti chernozem steppe of Moldova (represented by Balti experimental site) for the 1962–2012 farming years were investigated. In order to detect the trends and the shifts in the SPEI time series over 62 years, the non-parametric, Mann–Kendall and Pettitt tests were used for each month of the year to cover the main life cycle of the crops. The trend analysis of agricultural drought emphasizes an increasing trend from June to October, and becomes significant in the southern region at the 95% level during July to September. The SPEI highlights the main periods of dry/wet persistence and the regional characteristics of drought which are present in the Southern region, and make this region more prone to severe drought persistence, mostly during the last decade. Drought during the plant reproductive stages may significantly reduce grain yield potential, the relation between the SYRS and the SPEI explaining up to 62% of the low-yield variability.

Description: ABSTRACT In the face of limited or no precipitation data, global precipitation data sets (GPDs) may provide a viable alternative to gauge or ground radar data. This study aims to provide guidance to the choice of GPDs targeting scales relevant to water resources management in data poor regions. Specifically, the 34 000 km 2 Kilombero Valley in central Tanzania, where water resource management is seen as integral to poverty reduction and food security, is used as a case study for performance evaluation of seven GPDs and their ensemble mean against the Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis research-grade product v7 (TRMMv7). The GPDs include one satellite rainfall product [Climate Prediction Center morphing technique v1.0 CRT (CMORPH)], three reanalysis products [Climate Forecasting System Reanalysis (CFSR), European reanalysis interim (ERA-i) and Modern Era Retrospective-Analysis for Research and Applications (MERRA)] and three interpolated data sets [Climate Research Unit Time Series 3.21 (CRU), Global Precipitation and Climatology Center v6 data set (GPCC) and University of Delaware Air Temperature and Precipitation v3.01 data set (UDEL)]. Standard statistical performance measures and spatial patterns were evaluated for the common overlap time period 1998–2010. For this region, the principal seasonality of the climatology was well represented in all GPDs; however, the intraseasonal variability and the spatial precipitation patterns were less well represented. The ensemble mean and GPCC had the best performance with regard to the analysis of the time series while CMORPH and GPCC had the best performance with regard to the spatial pattern analysis. These results indicate that the spatial scale intended for application is a major factor impacting the suitability of a given GPD for hydrometrological studies that form a basis for development of water management strategies.

Description: ABSTRACT This study investigates the effect of varying the vertical level of a synoptic circulation classification on its predictive skill with respect to surface temperature, rainfall, solar radiation and wind in Trentino, a mountainous region in the South-Eastern Alps. A synoptic climatology based on the same data set and classification method presented in part I of the present article, in fact, showed that seasonal anomalies of mean daily temperature, daily rainfall, daily solar irradiation and mean daily wind intensity vary not only among weather types and seasons but also within the same type and season for different vertical levels. This analysis quantifies the ability of the method to classify synoptic circulation in classes associated with distributions of atmospheric variables different from climatology and to identify the occurrence of extreme events. The statistical metrics presented in the article demonstrate that the differences in predictive skill between classifications applied to distinct levels are comparable in magnitude to those between different atmospheric variables and seasons for the same level. The level of 500 hPa generally provides the largest predictive skill with respect to total daily rainfall, daily solar irradiation and daily temperature range in all seasons. On the other hand, the largest skill with respect to wind intensity is found for sea level pressure and 850 hPa circulation types. Large seasonal variations are also evident, with the colder seasons providing the largest predictive skill. Combinations of circulation types derived at two vertical levels increase the skill, although an optimal combination of levels could not be found even for the same atmospheric variable and season.

Description: ABSTRACT In this paper, we analyse observed changes in characteristics of sub-daily heavy summer precipitation and erosive precipitation events for the Czech Republic, taking into consideration 51 years of data (1961–2011) for 17 stations. The sub-daily data were checked for consistency with the daily control records, and unreliable data were removed from the data set. Subsequently, four statistical tests were applied to assess the homogeneity of the data set. The trend magnitude was estimated using the Theil–Sen slope estimator, and two tests were applied to evaluate its significance. For most of the indices, the tests did not indicate inhomogeneity, with the exception of characteristics related to rainfall intensity. The trends are positive for most of the stations and most precipitation characteristics, and significant positive trends are much more frequent than negative trends. The analysis revealed a significant increase in the contribution of heavy precipitation to the precipitation total in half of the stations at short aggregation levels.

Description: ABSTRACT This study evaluates the simulation of the spring Arctic Oscillation (AO)-western North Pacific linkage based on the 16 state-of-the-art climate models from the Coupled Model Intercomparison Project Phase 5. The validation focuses on the predominant process connecting the spring AO with the East Asian summer monsoon: the formation and persistence of the spring AO-associated cyclonic anomaly over western North Pacific (WPCA) from spring to summer. The results indicate that 8 of 16 models can reproduce both the formation and persistence of the WPCA. Because the formation of the WPCA is directly related to the existence of the spring upper-level North Pacific atmospheric dipole (NPAD), the analyses suggest that a given model can reproduce the spring AO-associated NPAD if the model is capable of simulating the spring AO-associated deceleration of the subtropical westerly jet and the transient eddy activities around the westerly jet exit. Furthermore, the westerly jet anomalies are closely related to the simulated mean state of the westerly jet and the AO Pacific component, which could be further attributed to the simulated sea surface temperature biases over the equatorial Western Pacific.

Description: ABSTRACT Climate variability has major impacts on crop yields and food production in South Asia. The spatial differences of the impact are not, however, well understood. In this study, we thus aim to analyse the spatio-temporal relationship between precipitation and rice yields in the Ganges–Brahmaputra–Meghna region. The effects of rainfall variation on yields were analysed with regression models using the Standardized Precipitation Index (SPI) as an explanatory variable. Our results indicate that in large part of the study region, a strong relationship between precipitation and rice yields exists and the SPI at various lags chosen as the predictor variable performed well in describing the inter-annual yield variability. However, the study demonstrated large spatial variations in the strength of this relationship or optionally in the suitability of the chosen methodology for investigating it. In the mid-plains of the Ganges, which represent very important agricultural areas, precipitation variability has a strong impact on rice yields, while in downstream Ganges as well as in Brahmaputra, where precipitation is more abundant, the relationship was less pronounced. Where the performance of the regression models was weaker, it is likely that yield variation depended on other factors such as management practices or on other climate factors such as temperature. The results further showed that the SPI at 1, 3, 6 and 12 month lags calculated for the monsoon time (June–October) are most commonly the best at explaining the rice yield variability. The SPI can thus be considered a very useful predictor of rice yield variability in some parts of the study region, demonstrating that they could be used for agricultural applications and policy decisions to improve the region's food security.

Description: ABSTRACT Features and interdecadal variability of droughts were assessed over the East Asian monsoon region (20°–50°N, 103°–149°E) using the standardized precipitation index (SPI) and the gridded rainfall data set (1978–2007) at 0.5° resolution. To assess the spatial and temporal patterns of droughts, seven homogeneous rainfall zones that exhibit unique rainfall regimes and long-term variability over the region were used. The statistical analysis method known as the theory of runs was used to identify and characterize drought events. A run was defined as a portion of SPI drought series in which all values were below the selected threshold level. Run-length and run-sum were used to define the drought duration and drought severity, respectively. The study revealed unique drying and wetting patterns for different zones in the region. Interdecadal analysis of droughts over the past three decades revealed a significant increase in drought duration and severity in the low rainfall zones, whereas a significant decrease appeared in the high rainfall zones. In particular, the duration and severity dwindled to zero with no major drought event over the eastern and the East Sea coastal region of Japan during the last decade (1998–2007). These patterns pose serious threats of increasing droughts in the low rainfall zones and flooding in the high rainfall zones. The spectral analysis, using the Fast Fourier Transform, was performed to identify the cyclic patterns of SPI time series in each zone, which revealed dominant cycles of 15, 7.5, and 3.4 years in the different zones. These results suggest the possible influence of interdecadal Pacific Oscillations and North Atlantic Oscillations on droughts in the region, although these relations remain a challenging task.

Description: ABSTRACT Heavy rainfall months of more than 450 mm occur in all 56 meteorological stations in eight climatic zones of Vietnam during the rainy season from April to September in the north (〉20°N), from August to December in the centre and from May to November in the south (〈12°N). The severity of an El Niño Southern Oscillation (ENSO) episode, expressed as the integral of sea surface temperature anomaly (SSTA) in the central tropical Pacific over the duration, shows a 4.6-fold (2.3-fold) increase in number of heavy rainfall months during La Niña (El Niño) per unit change in severity during the 1960–2009 period, suggesting a twin peak occurrence with both ENSO extremes. A heavy rainfall index (HRI) links heavy rainfall months to the rainy season duration, and allows evaluation of the rainfall severity per station, climatic zone and ENSO cycle. For the deltas and central climatic zones, seasonal rainfall and number of heavy rainfall months are significantly higher at the p  〈 0.05 level during La Niña than during El Niño episodes. Interpolated seasonal rainfall shows distinct differences between regions, with location having a larger effect than ENSO cycles on monthly rainfall amounts. Twenty-year return monthly rainfall derived from generalized Pareto distributions for peak over thresholds range from 475 mm in the central highlands to 2185 mm in the central coast. The spatial and temporal patterns of heavy monthly rainfall help explain flooding and paddy inundation which occur at least twice as frequent during La Niña as compared to El Niño conditions, particularly in Central Vietnam. The relation of HRI with both 20-year return levels and ENSO cycles offers opportunities for fast screening of impacts in a wider region of Southeast Asia. Because ENSO cycles have an impact on flooding and paddy inundation, it provides prospects for early warning, differentiated for different zones and rainfall regimes.

Description: ABSTRACT Recent studies have pointed out the statistical occurrence of dual-season droughts detected in tree-ring chronologies over the southwestern US region that is not well described by instrumental observed records of the 20th century. In this study, a multi-statistical approach that evaluates persistent dual-season drought using a mode-of-variability oriented approach is proposed, considering a new network of tree-ring earlywood (EW)- and latewood-adjusted (LW adj ) chronologies from throughout southwestern North America. To determine dominant patterns of spatiotemporal variability, empirical, orthogonal functions, canonical correlation analysis, and multi-taper-method singular value decomposition analyses were applied, with focus on variability from inter-annual to centennial periods and highlighting the multi-decadal signals inherent to proxy record network. During the instrumental period, we demonstrate that EW and LW adj networks of tree-ring chronologies are able to capture the associated precipitation responses of cool and warm season atmospheric teleconnections. Considering the four-century period of the complete tree-ring network, we explore the possibility of a dual summer–winter variability signal in the low-frequency climate regime. EW and LW adj seem to be coherent in-phase at the very low-frequency scale (50–100 years spectral band). This provocative result is supported by major historic documented multi-year droughts of the region since 1650. Thus, the temporal variation of these chronologies time series and its associated spatial pattern strongly suggest that this low-frequency mode might represents an important spatiotemporal variation of droughts in the Southwest; however, the source of this signal is still an open question and of great interest for drought planning and resource management in the region.

Description: ABSTRACT Spatiotemporal patterns of precipitation regimes in terms of precipitation amount and number of precipitation days at different time scales are investigated using the entropy-based methodologies in the Huai River basin, China. Trends of precipitation variability are quantitatively evaluated using the modified Mann–Kendall trend test method. Correlations between the largest 7-day precipitation amount (R × 7day) and precipitation variability within 1 year are also analysed. Results indicate the following: (1) there is increasing nonuniformity of annual precipitation amount and annual precipitation days from south to north in the Huai River basin, indicating larger precipitation variability in the northern parts. Transition of precipitation changes is evident in the basin which is reflected by decreasing precipitation variability in the north and increasing precipitation variability in the south. (2) The disorder indices (DIs) exhibit variations at different time scales. In general, precipitation variability is larger at shorter time scales, such as daily, and is smaller at longer time scales, such as annual. (3) Significant relations are identified between the DI and extreme precipitation events, i.e. significant relations between apportionment DI and the largest 7-day precipitation amount and it is particularly the case in the central and southwestern parts. Thus, it can be said that higher precipitation variability is due to higher frequency of extreme precipitation regimes. Results of this study are of practical significance for planning and management of water resources and agricultural irrigation and agricultural activities during climate change and particularly for enhancement of measures for mitigation of consequences of climate change.

Description: ABSTRACT The aim of this study was to provide a better understanding of how vegetation and building geometry influence the spatial distribution of air temperature and nocturnal cooling rates (CR) in a high-latitude city. Intra-urban thermal variations were analysed in two seasons (May–September and November–March) and in different weather conditions (clear, calm and cloudy, windy) in Gothenburg, Sweden. Simultaneous air temperature measurements were conducted for 2 years (2012–2013) at ten fixed park and street sites characterized by varying type and amount of vegetation, building geometry, openness and surface cover. Several spatial characteristics, including sky view factor (SVF) as well as the cover and volume of buildings and trees, were calculated within circular areas of radii ranging from 10 to 150 m. Spatial characteristics were found to explain air temperature distribution in the studied area to a large extent throughout the day and year, in both clear, calm as well as cloudy, windy conditions. The highest correlations were found for weighted calculation areas accounting for the influence of both nearest (10 m) and wider (25–150 m) surroundings. Park sites remained cooler than built-up areas, with the most pronounced cooling effect (0.8 °C) on clear, calm days of the warm season. The most important factor governing CR around sunset was SVF. However, on clear, calm nights of the warm season, they were also enhanced by vegetation, indicating the influence of evapotranspiration. Minimum night-time air temperature was governed mostly by the presence of buildings. Within the street canyon, a daytime cooling and night-time warming effect of a street tree was observed, particularly in the warm season. The study shows the importance of various spatial characteristics describing openness, amount of vegetation and building geometry in analysing intra-urban variations in daytime and night-time air temperature.

Description: ABSTRACT This paper examines the skill of seasonal precipitation forecasts over Iran using one two-tiered model, three National Multi-Model Ensemble (NMME) models, and two coupled ocean–atmosphere or one-tiered models. These models are, respectively, the ECHAM4.5 atmospheric model that is forced with sea surface temperature (SST) anomalies forecasted using constructed analogue SSTs (ECHAM4.5-SSTCA); the IRI-ECHAM4.5-DirectCoupled, the NASA-GMAO-062012 and the NCEP-CFSv2; and the ECHAM4.5 Modular Ocean Model version 3 (ECHAM4.5-MOM3-DC2) and the ECHAM4.5-GML-NCEP Coupled Forecast System (CFSSST). The precipitation and 850 hPa geopotential height fields of the forecast models are statistically downscaling to the 0.5° × 0.5° spatial resolution of the Global Precipitation Climatology Centre (GPCC) Version 6 gridded precipitation data, using model output statistics (MOS) developed through the canonical correlation analysis (CCA) option of the Climate Predictability Tool (CPT). Retroactive validations for lead times of up to 3 months are performed using the relative operating characteristic (ROC) and reliability diagrams, which are evaluated for above- and below-normal categories and defined by the upper and lower 75th and 25th percentiles of the data record over the 15-year test period of 1995/1996 to 2009/2010. The forecast models' skills are also compared with skills obtained by (a) downscaling simulations produced by forcing the ECHAM4.5 with simultaneously observed SST, and (b) the 850 hPa geopotential height NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric Research) reanalysis data. Downscaling forecasts from most models generally produce the highest skill forecast at lead times of up to 3 months for autumn precipitation – the October-November-December (OND) season. For most seasons, a high skill is obtained from ECHAM4.5-MOM3-DC2 forecasts at a 1-month lead time when the models' 850 hPa geopotential height fields are used as the predictor fields. For this model and lead time, the Pearson correlation between the area-averaged of the observed and forecasts over the study area for the OND, November-December-January (NDJ), December-January-February (DJF) and January-February-March (JFM) seasons were 0.68, 0.62, 0.42 and 0.43, respectively.

Description: ABSTRACT The complexity, predictability and predictive instability of the Western Mediterranean Oscillation index (WeMOi) at monthly scale, years 1856–2000, are analysed from the viewpoint of monofractal and multifractal theories. The complex physical mechanism is quantified by: (1) the Hurst exponent, H , of the rescaled range analysis; (2) correlation and embedding dimensions, μ * and d E , together with Kolmogorov entropy, κ , derived from the reconstruction theorem; and (3) the critical Hölder exponent, α o , the spectral width, W , and the asymmetry of the multifractal spectrum, f ( α ). The predictive instability is described by the Lyapunov exponents, λ , and the Kaplan–Yorke dimension, D KY , while the self-affine character is characterized by the Hausdorff exponent, H a . Relationships between the exponent β , which describes the dependence of the power spectrum S ( f ) on frequency f , and the Hurst and Hausdorff exponents suggest fractional Gaussian noise (fGn) as a right simulation of empiric WeMOi. Comparisons are made with monthly North-Atlantic Oscillation and Atlantic Multidecadal Oscillation indices. The analysis is complemented with an ARIMA(p,1,0) autoregressive process, which yields a more accurate prediction of WeMOi than that derived from fGn simulations.

Description: ABSTRACT The complexity of impacts resulting from extreme precipitation events varies with the spatial extent of precipitation extremes. Characteristics of precipitation extremes, defined by the top 5% of 3-day accumulated precipitation, including their spatial coherence and relationships to two contrasting synoptic phenomena, were examined at stations across the Northwestern United States. The spatial coherence of precipitation extremes generally decayed with distance between stations. However, distinct geographic variability in region-wide coherence of precipitation extremes was present with overall higher coherence west of the Cascades, and lower coherence in the lee of the Cascades and Northern Rocky Mountains. Illustrative patterns of coherence were also seen with respect to atmospheric circulation regimes; atmospheric rivers favoured broadly coherent extremes occurring primarily west of the Cascades during fall and winter, while closed lows favoured more isolated precipitation extremes in the lee of the Northern Rocky Mountains and Cascades, occurring primarily during spring. Geographic variability in spatial coherence, direction of maximum coherence and seasonality of extremes suggest that extreme precipitation events result from the interaction of atmospheric circulation and complex topography.

Description: Situated along the coast of southern China and facing the South China Sea, Hong Kong has been experiencing a significant rise in sea level by about 2.9 mm year −1 since the 1950s. For a densely populated coastal city prone to storm surge impacts during the passages of tropical cyclones, accentuated by the threat of sea-level rise as a result of global warming and local vertical land displacement, projection of the sea-level change for Hong Kong is essential for local risk assessment and long-term planning of adaptation measures. This study presented the projection of sea-level change in Hong Kong and its adjacent waters under the Representative Concentration Pathway 4.5 and 8.5 (RCP4.5 and RCP8.5) scenarios in the 21st century based on climate projections by models in phase 5 of Coupled Model Intercomparison Project, in combination with contributions from land ice and land water storage determined from published literatures, and local vertical land displacement as estimated by using continuous high-precision GPS observations in Hong Kong. The results show that the sea level in Hong Kong and its adjacent waters is projected to rise by 0.67 (0.50–0.84) m and 0.84 (0.63–1.07) m in 2081–2100 relative to 1986–2005 under RCP4.5 and RCP8.5, respectively, about 0.2 m higher than the global mean values projected by the Fifth Assessment Report of Intergovernmental Panel on Climate Change. The higher projected sea-level rise in Hong Kong and its adjacent waters as compared with the global mean values is primarily due to local vertical land displacement which contributes around 28% and 23% of the projected sea-level rise in 2081–2100 relative to 1986–2005 in the two respective RCP scenarios.

Description: ABSTRACT In this study, the detrended fluctuation analysis (DFA) method is used to analyse the drought and flood index (DFI) of the past 531 years in 20 stations over east central China. It is found that the variation of the DFI exhibits long-range correlation. The long-range correlation gradually decreases from northwest to southeast over the studied region. Moreover, the recurrence times of droughts or floods also show long-range correlation. The long-range correlation in the DFI data will disappear if the DFI data are randomly shuffled, which was also found in the recurrence time of the randomly shuffled DFI series for each station. The results show that long-range correlation is an intrinsic property of drought or flood events, which could result in the long-range correlation of the corresponding recurrence times. At present, the prediction skill of droughts/floods in Asian-Australian monsoon region is relatively low, particularly in most of China. The long-range correlation of the DFI provides a theoretical basis for climate predictions of droughts/floods and may help improve model performance by amending the model configuration, in terms of addressing parameterization problems and improving atmosphere–ocean coupling.

Description: ABSTRACT This work analysed the changes in air temperature in 25 meteorological stations in the Altiplano and the surrounding Andean slopes of Bolivia and Peru, and their relationship with El Niño-Southern Oscillation (SO) and the Pacific Decadal Oscillation (PDO). The analysis focused on annual, warm season (DJF) and cold season (JJA) maximum and minimum temperatures. All analyses were undertaken during 1965–2012, but some analyses were also from 1945 and 1955 when data were available. Principal component analysis was applied to the annual and seasonal series to identify spatial differences of changes in maximum and minimum air temperature. There was an overall increase of temperatures since the mid-20th century. The most intense and spatially coherent warming was observed for annual and warm season maximum temperature, with warming rates from 0.15 to 0.25 °C decade −1 . Changes in the cold season maximum temperature were more heterogeneous, and statistically significant trends were mostly in the Bolivian Altiplano. Minimum temperatures increased, but there was higher spatial variability and lower rates of warming. Maximum temperature was negatively correlated with the Southern Oscillation index (SO) in the warm season, and positively correlated with the SO in the cold season; there were less statistically significant correlations with the PDO, that exhibited inverse sign than those for SO. The strongest correlations were in the region near Lake Titicaca. The negative correlation of minimum temperatures with SO and the positive correlation of minimum temperatures with PDO were lower than the observed for maximum temperature. The changes in temperature and correlations with SO and PDO were highly dependent on the selected period, with stronger trends in the last 30–40 years. This suggests reinforcement of warming rates that cannot be only explained by SO and PDO variability.

Description: ABSTRACT In this study, we investigate the influence of global climate oscillations on the local temperature and precipitation over the United Arab Emirates (UAE), which is one of the driest regions in the world with very high temperatures and low precipitation. The identification and assessment of remote interactions (teleconnections) are carried out by using ground station and gridded data sets. Monthly rainfall data from six ground stations over the UAE for the period of 1982–2010 is used in this study along with the long-term gridded precipitation and temperature data from the Global Precipitation Climatology Center and Global Historic Climatic Network. Linear correlations, wavelet analysis, and cross-wavelet analysis have been applied to identify the relation between climate indices and precipitation (temperature). The analysis reveals that the strong variability in precipitation is closely associated with the Southern Oscillation Index (SOI) and the Indian Ocean Dipole Index (IOD) during the months of August–March, September–January, respectively. In case of temperature, the strong variability is associated with the North Atlantic Oscillation Index (NAO) and the East Atlantic Oscillation Index (EAO) during the months of April–October, July–December. Spatial analysis of cross-wavelet reveals that the winter precipitation is significantly influenced by SOI and temperature during summer by the NAO. This research concludes that the negative phases of SOI (NAO) play a significant role in the increase of precipitation (decrease in summer temperatures) over the UAE region.

Description: ABSTRACT Interannual variability and long-term changes of summer temperature extremes and hot spells in Moscow during 1949–2012 are investigated using air temperature station data, the National Centres for Environmental Prediction/the National Centre for Atmospheric Research (NCEP/NCAR) reanalysis and the Climatic Research Unit (CRU) data sets. Significant interdecadal changes in different characteristics of the temperature extremes are revealed. It is shown that summertime warming detected in the Moscow region in recent decades is not solely due to an increase in the number of hot days, but also due to a decrease in the number of cold days. Statistically significant positive (negative) trends in the number of anomalously hot (cold) days since the mid 1970s are detected. Respective trend values are 5%/decade –1 for the positive trends and −6%/decade –1 for the negative trends. We find that in 1981–2012 the number of summer seasons with extremely hot days has doubled with respect to earlier period (1949–1980). However, we do not find statistically significant trend-like changes in the duration of the hot events in Moscow. A chronology of temperature extremes in Moscow has been constructed. This can be used as a diagnostic tool allowing the detection of extremes. Typical regional sea level pressure patterns associated with air temperature extremes in Moscow are defined and briefly described.

Description: ABSTRACT This study evaluates the capability of regional climate models (RCMs) in simulating extreme rainfall events over Southern Africa, and in reproducing the characteristics of widespread extreme rainfall events (WERE) in the Western Cape (South Africa). We obtained simulation datasets of nine RCMs from the Co-ordinated Regional Downscaling Experiment (CORDEX) and compared them with observation datasets from the Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) as well as with the reanalysis dataset (ERAINT) that forced the simulations. A self-organising map was used to classify the WEREs into 12 nodes. The contribution of each RCM to each node was compared with the contributions of GPCP, TRMM and ERAINT. Using ERAINT dataset, we analysed the synoptic-scale atmospheric condition associated with each node. The results show that, in simulating the spatial distribution of the extreme rainfall event over Southern Africa, only four RCMs perform better than the forcing reanalysis (ERAINT) while two RCMs perform worse than the reanalysis. All the RCMs underestimate the threshold of extreme rainfall over Western Cape, poorly simulate the inter-annual variability of the WEREs ( r ≤ 0.3), but correctly reproduce the maximum frequency of the WEREs in Autumn (March–May). The WEREs in the Western Cape may be broadly grouped into four synoptic rainfall patterns. The first pattern links WEREs with tropical rainfall activities (tropical-temperate troughs); the second pattern shows isolated WEREs; the third and fourth patterns link WEREs with rainfall activities in the mid-latitudes (frontal systems) and over the Agulhas Current, respectively. While most RCMs overestimate the frequency of the first pattern, they all underestimate the frequency of the second pattern but simulate the frequencies of the third and fourth patterns well. The results of this study should help in improving the RCM simulations over Southern Africa and in downscaling impacts of climate change on extreme rainfall events over the region.

Description: ABSTRACT The research objectives were to describe heat waves (HWs) in Central Europe and define the synoptic situations that cause their occurrence. In this article, a hot day was defined as a day when the maximum temperature was above the 95th annual percentile and an HW was considered a sequence of at least five hot days. In the analysed multi-year period and study area, 11 HWs were observed in the north and 51 HWs were observed in the south. The occurrence of HWs was mainly connected with positive anomalies of sea level pressure and with the 500 hPa level, which shows the presence of high-pressure systems. HWs were also accompanied by positive T850 and precipitable water (PW) anomalies.

Description: ABSTRACT A statistical-dynamical downscaling method is used to estimate future changes of wind energy output ( Eout ) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

Description: ABSTRACT Atmospheric teleconnections have an important influence on the variability of the Mediterranean climate. This region has a unique and sensitive climate due to its complex topography and atmospheric circulation, thus making it challenging in climate simulations. This article focuses on the representation of five teleconnections in and around the Mediterranean region and how they affect one another and the region. The Regional Climate Model, RegCM4, has been used to simulate the climate from 1969 to 1999 for a domain covering the Mediterranean and the surrounding region. A generalized method for calculating the indices for these patterns was identified and the corresponding indices were constructed from the modelled data and compared with reanalysis data. The modelled data was found to be highly correlated with the 20th Century Reanalysis data and the probability density functions (PDFs) were very similar to the reanalysis data, showing that the teleconnections were successfully represented within the model. Maps of the influence of these teleconnections on temperature, precipitation and wind were also comparable to the reanalysis data, thereby suggesting that model data can be used for future projections of teleconnections and their effects on these parameters. With the use of this high-resolution data, inter-pattern relationships suggested in previous studies (such as that between the Mediterranean Oscillation and North sea-Caspian Pattern) became more evident. This article also shows how the influence of teleconnections on winds affects the circulation and hence the temperature and precipitation of the region.

Description: ABSTRACT The Mediterranean coast of Spain often experiences intense rainfall, sometimes reaching remarkable amounts of more than 400 mm in one day. The aim of this work is to study possible changes of extreme precipitation in Spain for this century, simulated from several Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. Eighteen climate projections (nine models under RCP4.5 and nine RCP8.5 scenarios) were downscaled using a two-step analogue/regression statistical method. We have selected 144 rain gauges as the rainiest of a network by using a threshold of 250 mm in one day for a return period of 100 years. Observed time-series have been extended using the ERA40 reanalysis and have subsequently been used to correct the climate projections according to a parametric quantile–quantile method. Five theoretical distributions (Gamma, Weibull, Classical Gumbel, Reversed Gumbel and Log-logistic) have been used to fit the empirical cumulative functions (entire curves, not only the upper tail) and to estimate the expected precipitation according to several return periods: 10, 20, 50 and 100 years. Results in the projected changes for 2051–2100 compared to 1951–2000 are similar (in terms of sign and value) for the four return periods. The analysed climate projections show that changes in extreme rainfall patterns will be generally less than the natural variability. However, possible changes are detected in some regions: decreases are expected in a few kilometres inland, but with a possible increase in the coastline of southern Valencia and northern Alicante, where the most extreme rainfall was recorded. These results should be interpreted with caution because of the limited number of climate projections; anyway, this work shows that the developed methodology is useful for studying extreme rainfall under several climate scenarios.

Description: ABSTRACT Air temperatures have increased globally over the past decades, while rainfall changes have been more variable, but are taking place. In South Africa, substantial climate-related impacts are predicted, and protected area management agencies will need to respond actively to impacts. It is critical for management agencies to understand the way in which climate is changing locally to predict impacts and respond appropriately. Here, for the first time, we quantify observable changes in temperature and rainfall in South African national parks over the past five to ten decades. Our results show significant increases in temperatures in most parks, with increases being most rapid in the arid regions of the country. Increases in the frequency of extreme high temperature events were also most pronounced in these regions. These results are consistent with other climate studies conducted in these areas. Similar increases were identified for both minimum and maximum temperatures, though absolute minimum temperatures increased at greater rates than absolute maxima. Overall, rainfall trends were less obvious, but a decrease in rainfall was observed for the southern Cape (in three parks), and an increase was detected in one park. The observed temperature changes over the last 20–50 years have in several instances already reached those predicted for near future scenarios (2035), indicating that change scenarios are conservative. These results provide individual parks with evidence-based direction for managing impacts under current and projected changes in local climate. They also provide the management agency with sub-regional information to tailor policy and impact monitoring. Importantly, our results highlight the critical role that individual weather stations play in informing local land management and the concerns for parks that have no local information on changes in climate.

Description: ABSTRACT Desertification is an international environmental challenge which poses a risk to portions of over 100 countries. Research into desertification and climate change has the potential to contribute to natural resources management and adaptation to climatic and other changes in Earth systems. An Earth system model of intermediate complexity (EMIC), the McGill Paleoclimate Model-2 (MPM-2) was used to explore the climatic biogeophysical effects of desertification in different latitude bands from 1700 to 2000 AD. It was found that latitudinal-band desertification attributable to forest and grass removal caused global cooling, land surface albedo increasing and precipitation reduction in the Northern Hemisphere as well as heat transport increasing in global ocean. These results highlighted global climate reaction to local desertification and demonstrated that the location of the desertification projected a potentially differential impact on local and global climate. That was, desertification in 0°–15°N gave a somewhat minor effect on global and local climate; desertification in 45°–60°N caused a significant reduction in global temperature while desertification in 15°–30°N induced a prominent reduction in local temperature. In response to desertification, surface albedo change as a forcing was the dominant biogeophysical driver of climate over the Northern Hemisphere while precipitation change as a response was probably the primary driver of climate over the Southern Hemisphere. Overall, the regional desertification may cause a global climatic effect, especially concerning desert expansion along the 15°–30°N and 45°–60°N latitude bands, which led to a more prominent effect on the Earth's climate and even oceanic circulation. The results of this study provide useful information when comparing the effects of desertification in different latitude bands on climate.

Description: ABSTRACT The spatial structure and temporal evolution of the intraseasonal variability (ISV) of the subsurface ocean temperature (STA) in the equatorial Pacific associated with the two flavours of El Niño [i.e. the canonical or eastern Pacific (EP) El Niño and the central Pacific (CP) El Niño] are investigated using observations and 1.5-layer linear reduced gravity model. Results suggest that the ISV characteristics show some differences in the two types of El Niño, although both oscillate along the thermocline in the form of the intraseasonal equatorial Kelvin wave (IEKW), which is excited in the western tropical Pacific by the zonal wind stress associated with the Madden–Julian oscillation (MJO). First, the period of dominant mode of the STA ISV during CP El Niño broadly distributes in 50–80 days with the spectra peaking in 60–65 days. By contrast, the spectrum of STA ISV during EP El Niño shows a peak in 75–80-day period. This indicates that the wave speed is faster in the CP El Niño than in EP El Niño. Second, the ISV activity peaks in previous spring during the developing phase of EP El Niño, whereas during CP El Niño it becomes the most active during the mature phase. Third, the strongest IEKW occurs in the CP around the dateline during CP El Niño and attenuates quickly east of 130°W due to strong eddy viscosity dissipation, while the IEKW during the EP El Niño propagates efficiently from the western to the eastern Pacific with a relative weak diffusion.

Description: ABSTRACT Mount Kenya is an equatorial mountain whose climatic setting is fairly simple (two rainy seasons in March–May, the Long Rains, and October–December, the Short Rains) though concealing significant spatial variations related to elevation and aspect (part I, Camberlin et al. , 2014). This part II is dedicated to the sensitivity of sorghum yields to climate variability in space and time, with a focus on the intra-seasonal characteristics of the rainy seasons. To that aim we use the crop model SARRA-H calibrated for the region and fed with rainfall, temperature, wind speed, humidity and solar radiation data over the period 1973–2001 at three stations located on the eastern slopes of Mount Kenya. The crop model is run independently for the two rainy seasons. Four groups of simulations are conducted by varying the initialization date of the simulation, the sowing dates and the type of soil, in order to test sorghum sensitivity to water availability. Evidence is found that potential sorghum yields are dominantly controlled by variations in seasonal rainfall amounts: mean yields are higher at higher and wetter locations, and are higher during the wettest rainy season and years. However, beyond this apparent simplicity, more complex aspects emerge of the crop–climate relationships. First, the yield–elevation relationship is altered at high elevation due to lower temperature. Second, despite a strong link with the seasonal rainfall amounts, we evidence an underlying role of some intra-seasonal rainfall characteristics such as the number of rainy days (itself mainly determined by the rainy season duration) or the occurrence of long dry spells. Third, unseasonal rains occurring after the end of the rainy season, especially after the Short Rains, play a role in final crop yield. Fourth, variations of climate variables such as solar radiation by modulating the potential evapotranspiration concur to yield variations at the wettest locations.

Description: ABSTRACT Climate variability modulates spatio-temporal variability of dry spells (DSs) and wet spells (WSs) within a river basin and will affect water resources management practices leading to various impacts on the socio-economic development in river basins. In this study, we evaluated spatio-temporal variability of DS and WS in Huai River basin (HRB), China, by developing copula-based severity-duration-frequency (SDF) curves. The result shows that the upper reach and the southern part of middle reach of HRB are prone to both DS and WS; however, the duration and severity of WS are comparatively higher in comparison to DS. It was observed that DS is more frequent in spring and summer, whereas WS in summer and autumn. The choice of copula plays an important role in deriving the SDF curves, and an inappropriately chosen copula function may result in a large bias of SDF estimation. The arch12 copula was found to be the best choice in the majority of stations for deriving the SDF curves. The constructed SDF curves primarily shows two major patterns for DS and WS, i.e. concave down pattern and convex up pattern. The frequency of extreme DS decreases from 1960s to 1990s, and increases after 2000s, while the frequency of extreme WS increases from 1970s to 1990s and then decreases from 1990s to 2000s. The results in this study can provide useful information for designing conservation structures and to develop water allocation strategies at different temporal scales.

Description: ABSTRACT Careful planning of the use of water resources is critical in the semi-arid eastern Mediterranean region. The relevant areas are characterized by complex terrain and coastlines, and exhibit large spatial variability in seasonal precipitation. Global seasonal forecasts provide only partial information of the precipitation as a result of their coarse spatial resolution. We present two statistical downscaling methods of global forecasts, both identifying past-analogue synoptic-weather patterns and their connection to precipitation at specific stations. The first method utilizes a classification of the large-scale weather patterns into regimes, and the other identifies the closest past analogues directly without grouping the weather events. The validation of the algorithms using NCEP/NCAR reanalyses and past precipitation observations at 18 stations shows that both methods provide good skill in predicting mean precipitation amounts and quantiles of the precipitation distribution, and in reproducing the observed inter-annual and spatial variability. Both methods show good correlations between predicted and observed precipitation amounts (∼0.8), and the downscaled precipitation reproduces the observed differences between the stations, which are not available in the coarse global models. Based on these results, we downscaled the operational global-seasonal forecasts issued by the NCEP CFS1.0 ensemble. This approach could also have utility in climate change scenario downscaling.

Description: ABSTRACT Small Island Developing States in the tropical western Pacific are among the most vulnerable to climate change. While a great deal of information on the observed climate change trends and their cause is available for many other regions and for the globe as a whole, much less information has been available specifically for the Pacific. Here, we show that warming over the past 50 years in the western Pacific is evident in recently homogenized tropical station data, and in gridded surface temperature data sets for the region. The warming has already emerged from the background climate variability. The observational data and Coupled Model Intercomparison Project Phase 5 climate model output are used to show that the observed warming was primarily caused by human-forced changes to the earth's radiative balance. Further warming is projected to occur in the same models under all three Representative Concentration Pathways (RCPs) considered (RCP2.6, RCP4.5 and RCP8.5), with the magnitude far exceeding the warming to date under the two scenarios with higher emissions (RCP4.5 and RCP8.5).

Description: ABSTRACT The contribution by tropical cyclones (TCs) to extreme rainfall in Australia is examined using daily rainfall measurements from over 2000 rain gauges. Analyses focus on the period beginning with regular satellite monitoring of TCs (1969/1970) through the year 2012/2013 and consider daily and multi-daily annual maximum rainfall series. Our results indicate that TCs play a prominent role in extreme rainfall over much Australia, with more than half of the highest annual rainfall events associated with these storms over the coastal regions and in particular over Western Australia. Moreover, the TC fractional contribution to extreme rainfall increases as we focus on the largest rainfall events, with approximately 66–100% of annual maxima in excess of 100 mm (∼4 inches) over Western Australia associated with TCs at over one third of the locations. Given the well-established controls on Australian TC activity by the El Niño–Southern Oscillation (ENSO), we also examined the relationship between extreme rainfall associated with TCs and ENSO using logistic regression. A larger probability of having an annual rainfall maximum related to TCs occurs during La Niña years, consistent with enhanced Australian cyclogenesis during these phases of ENSO. We also highlighted regional differences in the link between ENSO and extreme rainfall events, highlighting the stronger connection along the coastal areas and in particular over Western Australia.

Description: ABSTRACT Impacts of coupled air–sea interaction and large-scale nudging were examined through regional climate simulation of the East Asian summer monsoon (EASM). A slab ocean model (SOM) was coupled with a regional climate model (RCM) to investigate the impact of two-way air–sea interaction, and the spectral nudging was applied to examine the effect of large-scale nudging. The control run without coupled air–sea interaction and large-scale nudging had significantly large systematic errors in simulated oceanic precipitation, monsoon circulations, and subtropical high. The errors resulted from an erroneous physical process caused by uncoupled air–sea interaction. The experiment with a SOM reduced the unreasonable physical process because simulated sea surface temperature (SST) decreases with enhanced ocean surface mixing from intensified low-level wind. Therefore, coupled air–sea interaction in the SOM run improved the simulations of seasonal mean precipitation, monsoon circulations, and subtropical high. In the experiment with a SOM and large-scale nudging, simulated precipitation and synoptic fields were further improved because the spectral nudging decreased the systematic error of large-scale circulations between model solution and large-scale forcing. Simulated results indicated that adjusting simulated SST to atmospheric conditions by coupling an ocean model with a RCM and improving boundary conditions by implementing large-scale nudging are necessary for advanced simulation of the EASM using RCMs.

Description: ABSTRACT This study evaluates the forecast skill of the fourth version of the Canadian coupled ocean–atmosphere general circulation model (CanCM4) and its model output statistics (MOS) to forecast the seasonal rainfall in Malaysia, particularly during early (October–November–December) and late (January–February–March) winter monsoon periods. CanCM4 is the latest component of the Canadian Seasonal to Inter-annual Prediction System (CanSIPS), which is a multi-seasonal climate prediction system developed particularly for Canada but applicable globally. Generally, CanCM4's skill in reproducing the climatology during winter is not as good as in other seasons because of the model's inability to simulate the regional synoptic circulations over the western Maritime Continent. In particular, the model fails to forecast the cold surges and Borneo vortex circulations that play critical roles in moisture horizontal advection. Moreover, its forecast skill during the early winter monsoon period is poorer than during the late period. Interestingly, forecast skill is enhanced when MOS models are applied as the MOS utilizes the predictive signals in the quasi-global predictors from the CanCM4 forecast system. The predictability can be traced to the conventional El Niño–Southern Oscillation (ENSO) and ENSO Modoki signals that are present in the CanCM4 forecast MOS predictor fields. The quasi-global sea-surface temperature and quasi-global sea-level pressure fields are found to be the most useful predictors. Interestingly, CanCM4 forecast signals associated with the Indian Ocean Dipole also contribute to the skill. Skill enhancement is particularly significant for northern Borneo during early monsoon periods in medium- and long-lead forecasts when the CanCM4 has minimal direct skill in the region.

Description: ABSTRACT The El Niño Southern Oscillation (ENSO) is one of the main factors influencing global climate variability and consequently has a major effect on crop yield variability. However, most studies have been based on statistical approaches, which make it difficult to discover the underlying impact mechanisms. Here, using process-based crop model Model to Capture the Crop-Weather relationship over a Large Area (MCWLA)-Maize, we found a consistent spatial pattern of maize yield variability in association with ENSO between MCWLA-Maize model outputs and observations. During El Niño years, most areas of China, especially in the north, experience a yield increase, whereas some areas in the south have a decrease in yields. During La Niña years, there is an obvious decline in yields, mainly in the north and northeast, and a general increase in the south. In-depth analyses suggest that precipitation P rather than temperature T and solar radiation S during the maize growing season is the main cause of ENSO-induced maize yield variability in northern and northeastern China. Although a 2 °C change of T can affect maize yields more than a 20% change of P , greater changes of P contribute more to maize yield variability during ENSO years. In general, maize yields in drier regions are much more sensitive to P variability than those in wetter areas. All changes in meteorological variables, including T, P, S , and vapour pressure deficit (V PD ) during ENSO years, affect yield variability mainly through their effects on water stress. Our results suggest that more effective agricultural information can be provided to government decision makers and farmers by developing a food security warning system based on the MCWLA-Maize model and ENSO forecast information.

Description: ABSTRACT We analysed the long-term trend and interannual variability in summer (JJA) precipitation over eastern Siberia (90°–140°E, 50°–70°N) for the period 1979–2007. An increasing trend in summer precipitation was observed over large areas (Yenisei and Lena river basins) of eastern Siberia. Summer mean 850-hPa geopotential height decreased from Siberia to the marginal seas north of Siberia, with the largest decreases occurring over the northern part of eastern Siberia, while increasing trends were found around Mongolia, inducing a significant increase in westerly moisture flux and its convergence over eastern Siberia. Empirical orthogonal function (EOF) analysis of detrended summer precipitation revealed the leading modes of the interannual variability. The first leading mode (EOF1) represents interannual variation around the central Siberian Plateau and the middle reaches of the Lena river basin, related to the enhancement of a low-level cyclonic circulation centred on 65°N, 100°E around eastern Siberia. The circulation pattern of EOF1 closely matches the trend pattern over Siberia, indicating that a deeper quasi-stationary trough appears with increasing frequency in recent decades. The second leading mode (EOF2) shows a dipole pattern between the middle reaches of the Lena river basin and the western part of the Central Siberian Plateau. Wet summers in the Lena river basin are related to a stationary trough centred at around 60°N, 130°E. These leading patterns are related to the change in position of the stationary trough and the ridge of the wave train structure along the Arctic polar jet across the northern Eurasian continent.

Description: ABSTRACT This study shows a synoptic climatology of warm fronts in Southeastern South America (SESA). Data from Climate Forecast System Reanalysis (CFSR) was used to identify warm fronts from 1979 to 2010. The identification method was based on the magnitude of meridional gradient of 850-hPa equivalent potential temperature ( θ e) and 850-hPa wind fields. Composites of the most important atmospheric variables were constructed from 1 day before until 1 day after the formation of the warm front. An average frequency of two warm fronts per month is observed, with higher frequencies in austral winter. Most warm fronts precede the formation of extratropical cyclones over Uruguay and form because of the southward movement of previous cold/stationary fronts. Warm fronts form on average around southern Paraguay, northeastern Argentina and western part of southern Brazil and Uruguay, coupled to the eastern edge of the Chaco Low (CL) and the Northwestern Argentinean Low (NAL) where north/northwesterly flow predominates. An upper-level wave of wavenumber eight supports warm frontogenesis. Location and intensity of synoptic systems associated with a warm front event differ from winter to summer. Elevated instability is commonly present near warm fronts, and the average warm-front slope is 1 : 110, agreeing with other studies. Instability indices increase after the warm-front passage, leading to greater rainfall 1 day after the warm front forms.

Description: ABSTRACT Long instrumental climate records suffer from inhomogeneities due to, e.g. relocations of the stations or changes in instrumentation, which may introduce sudden jumps into the time series. These inhomogeneities may mask or strengthen true trends. Relative homogenization algorithms use the difference time series of a candidate station with neighboring stations to identify such breaks (changepoints). Modern multiple breakpoint methods search for the optimum segmentation, which is characterized by minimum internal variance within the segments and maximum external variance between the segment means. We analyse the accuracy of these homogenization methods and concentrate on the uncertainty in the position of the break. Due to unavoidable random noise in the difference time series, the segmentation method may find a shifted break position, which attains a higher external variance than the true one. Different lengths of potentially exchanged subsegments are considered; that one providing the largest external variance will be chosen as possibly erroneous optimum. We will show that the variances of shifted segmentations can be approximated by a Brownian motion with drift, where the signal-to-noise ratio (SNR) defines the drift size. Available formulae for one-sided and continuous Brownian motion with drift are expanded to two-sided and discrete processes as they occur in praxis. The error probability increases strongly for SNRs lower than 1. Thus, when the internal variance is larger than the variance introduced by the breaks, the probability of finding the right break position is small.

Description: ABSTRACT A singular value decomposition (SVD) analysis was performed jointly on the daily intensity of extreme rainfall (DIER) over Argentina and sea surface temperature (SST) anomalies from 17.5°N–90°S to describe and understand the influence of the large-scale variability of the SSTs on the regional extreme rainfall events for spring summer, autumn and winter. Three main leading modes were identified in agreement with previous works. Mode 1 activity is strongly related to El Niño-Southern Oscillation (ENSO). Warm anomalies in the central-eastern tropical Pacific and western Indian Ocean induce circulation anomalies extended along the South Pacific and the development of a continental-scale circulation gyre in South America promoting moisture convergence, and in turn favouring DIER positive anomalies, in eastern Argentina. The combined influence of SST anomalies in the tropical Atlantic and western tropical Pacific characterizes Mode 2 activity, which induces an anticyclonic (cyclonic) circulation gyre in southeastern South America promoting anomalous moisture convergence (divergence) and thus positive (negative) DIER anomalies in eastern Argentina in spring and fall (summer and winter). Finally, Mode 3 activity is also influenced by SST anomalies in tropical central-eastern Pacific from winter to summer. The associated teleconnections contribute to the development of a cyclonic circulation mainly influencing southeastern South America (SESA) circulation to the north of 30°S from summer to winter, and further south in spring.

Description: ABSTRACT A spatiotemporal analysis of two well-known agricultural drought indices, the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index at a 9-month scale (SPI-9), is presented for Sri Lanka. The analysis was conducted based on monthly precipitation and temperature data from January 1881 to December 2010 using 13 stations distributed across the three climatic zones of the country. Principal component analysis shows that the first two principal components of PDSI and SPI-9 are spatially comparable and could physically represent the two main monsoons. A wavelet analysis of these principal components' scores for both indices indicates a stronger association between the Northeastern monsoon and El-Niño in recent decades. Correlation analysis with agricultural metrics suggests that different indices might be appropriate for each of the climatic zones in Sri Lanka. PDSI correlated best with the intermediate zone districts; SPI-9 correlated best with the dry zone districts; but neither index correlated well with the wet zone districts.

Description: ABSTRACT Across the western United States, seasonal-scale El Niño-Southern Oscillation (ENSO) teleconnections have been extensively described. Less attention has been paid to spatial and temporal details of these relationships that might be particularly important to managers and decision makers. Here, we explore intra-seasonal relationships between the Southern Oscillation Index (SOI) and average temperature, wet-day temperature, overall precipitation amount, precipitation frequency, and rain/snow partitioning at 138 Global Historical Climatology Network weather stations across the Pacific Northwest of the United States. Results of this study indicate that ENSO influences were generally more pronounced along the coast and in the northern Idaho/western Montana region than in the lee of the Cascades. There was a distinct seasonality in response, with stronger correlations in the late winter (February–March) than in the autumn (October–November) or mid-winter (December–January). The fraction of stations demonstrating correlations to SOI has changed over time, with a trend towards greater spring teleconnections in recent decades.

Description: ABSTRACT This study presents the results of dynamically downscaled climate simulations over Italy produced with the COSMO-CLM model. Three simulations forced by ERA-Interim Reanalysis were conducted respectively at a spatial resolution of 0.22°, 0.125° and 0.0715° over the period 1979–2011. The results were analysed in terms of 2-m temperature and precipitation with the aim of assessing the model's ability to reproduce these important features of the Italian climate. The results were validated by comparing model output with different independent observational datasets. Values of temperature and precipitation show a general good agreement with observations, with a fair reduction of errors in all seasons as the resolution is increased. Two simulations at a spatial resolution of 0.0715°, driven by the global model CMCC-CM, were performed over the period 1971–2100, employing the IPCC RCP4.5 and RCP8.5 scenarios. Climate projections show a significant warming expected in Italy at the end of the 21st century, along with a general reduction in precipitation, particularly evident in spring and summer.

Description: ABSTRACT The relationship between atmospheric blocking and extreme precipitation in summer in Romania during the period 1962–2010 is investigated. Percentile-based indices (R90p) for extreme precipitation events are calculated using data recorded at a large number of meteorological stations (98) covering the entire country. The dominant mode of variability of these indices has a monopolar structure and is related to two distinct atmospheric circulation blocking patterns. High frequency of blocking in the 0°–40°E sector is associated with high frequency of extreme precipitation events over Romania. This is due to enhanced synoptic scale activity associated with advection of relatively high potential vorticity from northeast towards Romanian region, as well as with enhanced synoptic scale activity in the Mediterranean region. Enhanced blocking activity in the 50°–70°E sector favours an eastward extension of Atlantic jet, and the associated instabilities are related to extreme precipitation events over large parts of central and Eastern Europe. We argue that these two distinct blocking patterns explain a substantial part of extreme precipitation variability in Romania during summer.

Description: ABSTRACT Many arid and semi-arid regions have sparse precipitation observing networks, which limits the capacity for detailed hydrological modelling, water resources management and flood forecasting efforts. The objective of this work is to evaluate the utility of relatively high-spatial resolution rainfall products to reproduce observed multi-decadal rainfall characteristics such as climatologies, anomalies and trends over Saudi Arabia. Our study compares the statistical characteristics of rainfall from 53 observatories over the reference period 1965–2005, with rainfall data from six widely used gauge-based products, including APHRODITE, GPCC, PRINCETON, UDEL, CRU and PREC/L. In addition, the performance of three global climate models (GCMs), including CCSM4, EC-EARTH and MRI-I-CGCM3, integrated as part of the Fifth Coupled Model Intercomparison Project (CMIP5), was also evaluated. Results indicate that the gauge-based products were generally skillful in reproducing rainfall characteristics in Saudi Arabia. In most cases, the gauge-based products were also able to capture the annual cycle, anomalies and climatologies of observed data, although significant inter-product variability was observed, depending on the assessment metric being used. In comparison, the GCM-based products generally exhibited poor performance, with larger biases and very weak correlations, particularly during the summertime. Importantly, all products generally failed to reproduce the observed long-term seasonal and annual trends in the region, particularly during the dry seasons (summer and autumn). Overall, this work suggests that selected gauge-based products with daily (APHRODITE and PRINCETON) and monthly (GPCC and CRU) resolutions show superior performance relative to other products, implying that they may be the most appropriate data source from which multi-decadal variations of rainfall can be investigated at the regional scale over Saudi Arabia. Discriminating these skillful products is important not only for reducing uncertainty in climate, hydrological and environmental assessments but also for advancing model developments in the region.

Description: Temperature anomalies in the lower stratosphere (namely, at 50-hPa) poleward of 30°N (hereafter, T 50 ) are analysed from reanalysis daily products (i.e. ERA-40 and NCEP/NCAR) in order to detect those regions with statistically significant trends of T 50 during the common 1957–2002 period. We also analyse radiosonde data in order to validate the reanalyses results. The analyses are conducted for the extended polar winter (i.e. from November to May) in order to relate T 50 changes to the northern polar vortex variability. In relation to the previous literature, the novelty of this study is double: first, temporal evolution is considered according to regions with similar T 50 temporal variability in the Northern Hemisphere; second, trend analyses of stratospheric temperatures are obtained with the use of running windows with variable width of each principal component series computed from monthly mean values. Two main stratospheric regions were identified from both reanalyses, with a statistically significant cooling within the study period: one over the high latitudes and a second one tracing a subtropical ring. The first one was detected in November, December and May during several decades, particularly at the beginning and in the middle of the study period (i.e. 1957–1985). The second region (i.e. the subtropical ring) showed overall cooling for all months along the study period. In addition, the lower stratospheric temperature over northern Europe exhibited an outstanding cooling in May for the whole study period. The results obtained from both reanalyses are practically identical, a fact that provides robustness thereto. Radiosonde data confirm the above-mentioned results, but the magnitude of the trends given by reanalysis products is substantially overestimated in the winter months over high latitudes.

Description: ABSTRACT Twenty-one climate models from Coupled Model Intercomparison Project Phase 3 (CMIP3) and thirty-one models from the project's Phase 5 (CMIP5) were used to evaluate model reproducibility in assessing interannual variability of summer precipitation in Pan-Asian monsoon region. The results show that both the multi-model ensemble means of the best eight models and of the thirty-one CMIP5 models are more skilful than those of the CMIP3 models in simulating the climatological pattern and the dominant mode of summer precipitation in Pan-Asian monsoon region. CMIP5 models show improved skill in representing the main characteristic of the first mode of summer precipitation in Pan-Asian monsoon region, which is a meridional tripole pattern from north to south occurring east of the 80°E region. That is, owing to the improved El Niño–Southern Oscillation (ENSO) pattern and the relationship between Antarctic oscillation in the southern Pacific Ocean (AAO SP ) and ENSO, the first dominant mode of summer precipitation in Pan-Asian monsoon region are captured by CMIP5 models, which indicates that these models are more skilful in simulating the air–sea interaction of the Southern Hemisphere.

Description: ABSTRACT Various studies have been performed on drought hazard assessment at the national or regional scales, but few studies to date at the global scale, especially on global agriculture. In this paper, we utilized an agricultural drought hazard index (DHI), based on both drought severity and drought occurrence rate, derived from 3-month scale Standardized Precipitation Index (SPI) and the phenology data of main crops (rice, maize, wheat, barley, sorghum and soybean) to assess the agricultural drought hazard grades of the world during 1980–2008. The results indicated that area percentages of high and very high agricultural drought hazard zones were approximately 23.57 and 27.19% of the total agricultural area in the world. Moreover, those zones mostly were distributed in central United States, southeastern South America, most of Europe, southwestern Russia, both southern Congo and Nigeria, east-central and southwest China, Southeast Asia and eastern Australia, and most of those areas were also located in semi-humid or humid climate zones. In addition, some regions above were also found to be the very high agricultural drought hazard zones for the main crops: East-central and southwest China for wheat, maize, rice and soybean; Europe for wheat, maize and barley; Southeast Asia for rice; both central United States and southeastern South America for wheat, maize, soybean and sorghum.

Description: ABSTRACT In this work, we have carried out a comparison study between measured and modelled direct and global ultraviolet (UV) (300–400 nm) spectral irradiances and the determination of the surface effective albedo at the high altitude Izaña Observatory [IZO; 2400 m above sea level (a.s.l.)] located in Tenerife (Canary Islands, Spain). The spectral measurements were performed with a Bentham spectroradiometer during the Quality Assurance of Solar Ultraviolet Spectral Irradiance Measurements (QASUME) comparison campaign in June 2005. The simulations were obtained with the LibRadtran radiative transfer model. The model input parameters, such as total ozone and aerosol optical depth (AOD), were measured at IZO. The comparison between measured and modelled direct solar radiation component was made at 0.5 nm spectral resolution, showing excellent agreement, with differences below 5% for solar zenith angle (SZA) 〈 60°. These differences were attributed to the effect of the underlying surface albedo due to the frequent existence of a sea of clouds below the station altitude. The underlying surface albedo was determined using different methods. In spite of the variability of this parameter through the day due to the strong influence and variable structure of these underlying clouds, the mean of this effective surface albedo in the UV region gives a value between 0.2 and 0.5 in the UV range, 10 times higher than the local surface albedo (0.02–0.05).

Description: ABSTRACT We studied rainfall characteristics of Brazil for the period 1979–2011. This is an update for an earlier study with data from 1958 to 1978. We compared the three consecutive wet and dry months in the two data sets. In the northern most part rainy season earlier was in April to July and now it is occurring later. In a large part of the south central region the rainy season in austral summer and dry season in austral winter did not change. However, to the east of this region rainy season in the latter data occurs earlier. Calculation of linear tendencies showed, that over the northern Amazon region there is a significant increase of rainfall. This agreed with previous results. Over this region dry season is becoming drier and wet season wetter. In the west of Northeast Brazil (NEB) there is an increase of rainfall. In southeast Brazil there is a region of highly significant decrease of rainfall in both wet and dry seasons. This is confirmed in our analysis on river discharges in Sao Paulo and Minas Gerais states. The negative tendencies in rainfall have great impact on the hydroelectric generation not only in this region but also at the national level because the hydroelectric dams furnish energy on a national level. The increase in rainfall in Northern Amazon is probably associated with Atlantic warming that resulted in higher moisture transport from east. The decrease of rainfall in southeast Brazil seems to be associated with the plummet of rain producing systems from south due to increase of mean sea level pressure in the south.

Description: ABSTRACT This paper presents a comparison of statistical methods for automated random error detection in historic radiosonde temperatures through a rigorous simulation study. We simulate temperature data designed to mimic observed radiosonde temperature time series from ten climate regions and three pressure levels and contaminate this simulated data with errors that are similar to those occurring in the historical record. Robust estimates of centre and spread of the temperatures are used to standardize values and flag potentially erroneous observations, and five approaches for selecting subsets of observations upon which to base these estimates are tested. Two robust estimators, one of which is designed to work well for asymmetric distributions and gives different estimates of standard deviation for each tail of the distribution, are investigated. We use a logistic regression model to assess the effects of climate, pressure level, record length, contamination percentage, error type, and window size on each method combined with each estimator in terms of both correctly and incorrectly identified errors. Temperature distributions are not always symmetric, and based on the simulation, we find that the asymmetric estimator makes fewer mistakes in error identification, and we illustrate its application with a case study at a Russian station.

Description: ABSTRACT The Bay of Bengal (BoB) basin in the North Indian Ocean reports the highest number of tropical cyclones, and the frequency is much higher almost five times compared with the Arabian Sea (AS). Semi-enclosed nature of this basin in conjunction with its funnel shape steers the cyclone pathway striking the land. Historical reports signify that most deadly cyclones with highest catastrophe and death tolls occurred in this basin. The four maritime states located in the east coast of India are highly vulnerable to tropical cyclones. Hence, there is a need to understand the risk factors attributed from extreme winds, storm surge, and associated coastal inundation. Historical data signify higher frequency of post-monsoon cyclones compared with pre-monsoon cyclones in the BoB. This study aims to develop a synthetic track or the most probable cyclone track for each state located along the east coast of India. The synthetic track is a general guidance for numerical models, with utility to evaluate and assess the risk factors along coastal belts. This study also deals with aspects on frequency and cyclogenesis locations in the BoB based on analysis from historical data. Results for decadal scale variability signify that in the present decade, the eastern BoB is quite conducive for cyclogenesis. In this region, oceanic thermal field exhibits a warming trend, and found to extend up to water depth of 600 m. In addition, this study also evaluates the energy metrics such as Power Dissipation Index (PDI), and Accumulated Cyclone Energy (ACE) for tropical cyclones that occurred during past four decades in the BoB. The results signify that PDI for tropical cyclones in the present decade is six times higher when compared with the past. The study has practical applications for mapping coastal vulnerability in a changing climate.

Description: ABSTRACT This study evaluates the 14 global climate models in the Coupled Model Intercomparison Project Phase 5 in capturing the extreme climate events and the agricultural climate indices over China. Future climate event changes in different Representative Concentration Pathway scenarios in China are projected using the Reliability Ensemble Average method. The models can simulate the basic spatial distribution characteristics of indices and simulate temperature indices better than precipitation indices. The models overestimate the number of wet days over China, which is related to the tendency that rainfall is simulated too often and too lightly in models. The underestimation of the number of very heavy precipitation events is detected in most models, while overestimation occurred in northern China and the Qinghai-Tibet Plateau region. Some factors, such as the complex topography, the moist convection schemes in models, and the ability to simulate large-scale circulation, may result in the performances for precipitation. Higher active accumulated temperature and more summer days are projected, while the accumulated negative temperature and frost days are projected to decrease with the warming climate. Northern China would become wetter when the number of wet days (R1mm) increases. Extreme wet events are projected to be more probable in South and Central China and the Southwest Region, with increases in very heavy precipitation days (R20mm) in all scenarios. These changes in extreme climate events and agricultural climate indices would inevitably affect agriculture in China.

Description: ABSTRACT This paper reports the second part of a study that aims to understand the thermally driven local flows and their interaction with each other over the province of Istanbul. The first part of the research evaluates a series of sensitivity simulations involving perturbations to the landscape. The present one includes an analysis of the real case simulations with an evaluation of the model performance. The second part also uses the same meso-scale model (OMEGA) with the same model configuration as in the first part. The model is able to reproduce the large-scale fields. Comparison of model-estimated fields with the radiosonde measurements over Istanbul also yields satisfactory results. The model is also able to capture the diurnal change of surface meteorological parameters such as temperature and wind speed, but there are over- and underestimations. The real case simulations indicate a clear cycle of land and sea breeze circulations in both summer and winter. In agreement with the sensitivity cases, a convergence zone occurs over the province due to the merge of two sea breezes in both seasons. In summer case, the convergence takes place at 1100 LST, and in winter case, it occurs at 1500 LST. Development of a channeled flow along the Bosphorus is also observed in the real case simulations. Return flows are observed above 1 km height during the summer case and above 300 m height during the winter case. The northerly flow induced by the urban heat island effect prevents the inland penetration of the southerly sea breeze over the province. Thus, the northerly sea breeze moves faster, surmounts the southerly one over the south of the province, where the urban area is located, and dominates the airflow over Istanbul, especially in the afternoon.

Description: ABSTRACT Through optimizing the daily precipitation climatology, a new high-resolution (0.25° × 0.25° lat./lon.) gridded daily precipitation analysis over Mainland China was developed based on the optimal interpolation (OI) method. This product, based on about 2400 gauge stations over Mainland China from 1955 to the present, is called the China Gauge-based Daily Precipitation Analysis (CGDPA). In this study, using independent precipitation observations as the benchmark, CGDPA and the Climate Prediction Center Unified gauge dataset (CPC_UNI) from the National Oceanic and Atmospheric Administration (NOAA) are validated from May to September of 2008–2010 on a 0.5° × 0.5° lat./lon. grid. The CGDPA has smaller bias and root mean square error, and higher spatial correlation with the validation data than CPC_UNI. Further investigation indicates that this improvement is mainly owing to the larger number of gauges used in the CGDPA. The East Asia gauge analysis (EA_Gauge) is also introduced to comparatively evaluate the capabilities of monitoring precipitation events with different rainfall rates over Mainland China. CGDPA can capture more strong rainfall events while CPC_UNI and EA_Gauge tend to smooth the precipitation structure and miss more local strong rainfall events with precipitation larger than 25 mm day −1 over Mainland China. The long-term precipitation time series described by the CGDPA and EA_Gauge agree very well while CPC_UNI substantially underestimates precipitation especially over the sparse-gauged regions and after 1982. CGDPA is thus suggested as a readily available input to applications over Mainland China, whenever possible.

Description: ABSTRACT The present study aims to examine the role of air–sea interactions and upper ocean processes in determining the tropical Indian Ocean (TIO) seasonal sea surface temperature (SST) bias in Climate Forecast System version 1 (CFSv1) and version 2 (CFSv2) free runs. CFSv1 displayed dipole like east–west SST bias over the equatorial Indian Ocean from boreal summer to winter and is consistent with errors (bias) in surface winds and upper ocean advection. Large zonal gradients in sea level pressure (SLP) bias and the associated surface wind biases are primarily responsible for the upper ocean current bias. However, over the southern Indian Ocean and parts of Arabian Sea, strong bias in heat flux and mixed layer depth (MLD) have mainly contributed for the SST biases in CFSv1. Equatorial current system is better represented in CFSv2 compared to CFSv1. Improvement in the representation of land-surface processes appears to be contributing towards improving atmospheric circulation and SLP gradients in CFSv2, which may be responsible for the improved ocean circulation. Importantly, east–west dipole like SST bias prevalent in CFSv1 is absent in CFSv2. However, there is a prominent systematic basin-wide TIO cold SST bias in CFSv2. Large biases in surface heat flux (net negative bias) and MLD (deeper) are mainly responsible for SST biases in CFSv2. Negative net heat flux bias in CFSv2 is primarily due to specific humidity bias-induced excess latent heat flux (LHF). Deepening of MLD is mainly due to strong convective mixing, a resultant of anomalous LHF release, which in turn leads to negative SST bias. Models comparison reveals that although representation of SST in CFSv2 is better than in CFSv1, it is essential to improve further the equatorial ocean dynamics and off-equatorial thermodynamics in the form of moist processes and radiative parameterization in order to reduce SST bias in CFSv2.

Description: ABSTRACT The impact of climate change on extreme precipitation events in the Oldman (ORB), Bow, (BRB) and Red Deer (RRB) River Basins of southern Alberta, Canada, was assessed using six extreme climate indices for the rainy period of May–August (MJJA), and 9-km resolution Special Report on Emission Scenarios (SRES) A2 and A1B climate scenarios of four Coupled Model Intercomparison Project Phase 3 (CMIP3) Global Climate Models (GCMs) dynamically downscaled by a regional climate model, MM5. R95p of the three study sites showed an increase of 4% for the 2050s (2041–2070) and 10% for the 2080s (2071–2100) period, whereas R99p increased by 39% (2050s) and 42% (2080s) which suggest a projected increase in the volume of precipitation expected in future very wet and particularly extremely wet days. Similarly, R20mm, P30yr, RX1day and RX5day are also projected to increase by about 15% by the mid- and late 21st century in the three study sites. However, compared to BRB and RRB, ORB located in the southernmost part of the study site is projected to undergo a relatively higher increase in both temperature and precipitation intensity, which is assessed in terms of indices such as P30yr, RX1day and RX5day. On the other hand, RRB and BRB are projected to experience higher increase in R20mm, which suggest a relatively higher increase in the number of very heavy precipitation days projected for these two basins. Overall, these results suggest that in the 2050s and 2080s, southern Alberta will be expected to experience more frequent and severe intensive storm events in the MJJA season that could potentially increase the risk of future flooding in this region.

Description: ABSTRACT It is of great importance to investigate links between hydrological drought and climate indices, which helps to further reveal the cause of hydrological drought from a perspective of climate change, thus helping guiding future drought prediction and control. For a case study in the Columbia River basin, the Standardized Streamflow Index (SSI) was employed to characterize hydrological drought. The heuristic segmentation method was applied to identify change points of annual streamflow series spanning 1960–2012 in the Columbia River basin, and the cross-wavelet analysis was utilized to reveal the correlations between monthly climate indices and SSI. The primary results are as following: (1) monthly SSI has a statistically significantly increasing trend in November and December and a noticeably decreasing trend in June and July in the main stream of the basin; (2) generally, hydrological drought risk in this basin is high, and that in the Snake River is higher than the main stream of the Columbia River; (3) El Niño Southern Oscillation (ENSO) and Arctic Oscillation (AO) play a major role in affecting hydrological drought in the Columbia River basin, and ENSO index mainly affects SSI at a relatively short time scale (2–7 years), while AO primarily impacts SSI at a relatively long time scale (more than 10 years); (4) anthropogenic activities intensify hydrological drought in the Columbia River basin, and they primarily influence the linkages between climate indices and hydrological drought at intra-annual scale (less than 12 months), however, which do not change the basic pattern of their correlations.

Description: ABSTRACT The sensitivity of the East Asian Monsoon (EAM) precipitation prediction skill to the variabilities of the tropical Indian and Pacific sea surface temperature (SST), the North Atlantic Oscillation (NAO), and the heating and snow cover over the Tibetan Plateau is evaluated in the framework of a linear Markov model. It is found that the tropical Indo-Pacific SST helps to improve the prediction of EAM precipitation over oceanic regions and some localized areas over land, while the Indian Ocean alone does not show significant impact on prediction. The remote effects of NAO improve the prediction in the middle and lower reaches of the Yangtze and Huaihe River valleys in boreal spring, fall and winter, and over oceanic areas in boreal summer and fall. The predictive skill of our model is not sensitive to the inclusion of the sensible heating and snow cover over the Tibetan Plateau, probably because their effects are implicitly present in the original EAM model.

Description: ABSTRACT In order to find out the optimal setting for downscaling the Coupled Model Inter Comparison Project Phase 5 (CMIP5) database, this study describes the most suitable domain, convection and land-surface schemes within Regional Climate Model version 4 (RegCM4) over the Middle East and North Africa (MENA) domain. The activity is carried out in compliance with COordinated Regional climate Downscaling EXperiment (CORDEX) initiative, where domain suitability is assessed through seven simulations for the period 2001–2005. After the selection of domain, eight simulations are carried out to find better performing convection and land-surface schemes within RegCM4 for the same time period of 5 years. These experiments are conducted using ERA-Interim reanalysis datasets; however, the selection of optimal settings is also validated using other reanalysis datasets. Finally, using the same settings, data of five CMIP5 general circulation models (GCMs) are also downscaled to assess the applicability of RegCM4. Statistical measures, such as correlation coefficient, bias, root mean square difference and standard deviation, are taken into consideration to compare the simulated data against the gridded Climatic Research Unit (CRU) and Tropical Rainfall Measuring Mission (TRMM) datasets. RegCM4-simulated rainfall and temperature show better spatial distributions and magnitudes against observations, as compared to ERA-Interim data, which may be considered as an added value of the model. In analysing rainfall and temperature data for the 11 sub-domains (each an 8° × 8° box), the region encompassing the area 7°S–45°N and 27°W–76°E, named CORDEX-MENA/Arab domain, is found to be the most cost effective and suitable domain. Further analysis over this domain shows Biosphere and Atmosphere Transfer Scheme (BATS) to be the better performing land-surface scheme, whilst Grell with Fritsch–Chappell closure (GFC) comes up as the most suitable option for convection scheme in the model. Of five CMIP5 datasets downscaled using RegCM4, rainfall and temperature patterns of four are similar to the reanalysis and observations. Therefore, it is recommended that RegCM4 may be employed with the aforementioned settings in downscaling the CMIP5 multi-model database for climate change impact and adaptation studies for the region in future.

Description: ABSTRACT This study analyzes temperature projections in the Koshi River Basin in Nepal using data obtained from ten General Circulation Models (GCMs) for three IPCC Special Range of Emission Scenarios (SRES): B1, A1B and A2. Low resolution data of minimum and maximum temperature obtained from the selected GCMs was downscaled using the statistical downscaling model Long Ashton Research Station Weather Generator (LARS-WG) for ten stations located in two physiographic regions of the study area: the Middle Mountains (1500–2700 m) and the Siwalik Hills (700–1500 m). The projected temperature and differences in projections among individual GCM projections for changes in the mean value of seasonal and annual T min and T max are presented for three future periods: 2011–2030 (2020s), 2046–2065 (2055s) and 2080–2099 (2090s). We also analyzed the baseline period and future T min and T max data through seven indices, as recommended by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Results show that the LARS-WG model performs well when downscaling T min and T max . An increase in seasonal as well as mean annual minimum and maximum temperature is projected for all three future periods. Projected warming, as well as the differences among projections from different GCMs, increases with time for each of the three scenarios. The cold years during the 2055s and 2090s are expected to be hotter than the hot years during the baseline period. The increase in temperature, as well as the range of uncertainty, is expected to be higher in the Mountains than in the Hills. The number of summer days and tropical nights is expected to increase during all three future periods. The temperature of the coldest day, coldest night, warmest day and warmest night is also expected to increase in both the regions during all three future periods.

Description: ABSTRACT Studying long-term variations and trends in grid datasets is often complicated by variations in the station network used for spatial interpolation. The increase in station density over time gives rise to inhomogeneities in the datasets. Here we introduce a gridded dataset of monthly precipitation for the entire Alpine region with a grid-spacing of 5 km that extends over more than 100 years (1901–2008), is largely unaffected by network variations and still exploits information from recent dense observations. It is derived by a reconstruction procedure that combines data from several thousand stations over recent decades with long-term and almost continuous station series at much coarser resolution (120 stations). Our dataset is a recalculation and update of a previous and similarly constructed dataset that ended in 1990. The reconstruction method is modified for the present application and an entirely new high-resolution reference was used for calibration. The reconstruction explains more than 80% of the month-by-month variance in Switzerland and Austria where the long-term station network is comparatively denser. We also demonstrate that the reconstruction can effectively filter out artifacts in trend patterns due to local inhomogeneities in the data and the station network. Precipitation trends calculated with the updated grid dataset are qualitatively similar with those found previously, but statistical significance has partly changed. A likely reason for these discrepancies is decadal variations, notably in winter, and this calls for prudence in the interpretation of trend results from conventional tests.

Description: ABSTRACT In this study, we examined the annual precipitation amounts, the seasonality over global land and their linear trends, as well as the uncertainties in two observations (precipitation reconstruction and Global Precipitation Climatology Centre), and then compared them with historical runs by multiple models. Overall, the large-scale patterns of both the climatology of the annual precipitation amount and the seasonality are consistent between the two observations. Nevertheless, some noticeable differences existed, particularly in the regions with fewer gauge observations, such as northern Africa and the Tibetan Plateau. For long-term changes, significant drying trends during 1948–2005 were observed in the tropical areas of northern Africa, accompanied by significant wetting trends in the polar region of Canada. The seasonality change during the period was dominated by a decreasing trend in precipitation, especially in the western portion of Russia. The model simulations of the Coupled Model Intercomparison Project, Phase 5 (CMIP5) reproduced the climatological mean state of annual precipitation and its seasonality in the observations, as well as to some extent the zonal mean trends of precipitation amounts, but did not reproduce the zonal mean trends of seasonality. The two-dimensional distribution of linear trends of annual precipitation and seasonality simulated by CMIP5 models showed little consistency with their observational counterparts. One possibility for the inconsistencies was that they were largely determined by internal variations of the climate system rather than external forcings. In contrast, it might also suggest a challenge for state-of-the-art climate models to correctly simulate the spatial distribution of responses of annual precipitation amounts and seasonality to the evolution of external forcings. Our results suggest that, in addition to the precipitation amount, seasonality should be used as a metric to assess the ability of a climate model to simulate current climate conditions and project future climate change.

Description: ABSTRACT This study evaluates the classifications of atmospheric circulation patterns collected in the COST733 database (COST733cat) in terms of their ability to stratify daily surface temperature and precipitation in 12 domains covering the whole of Europe. The classifications differ in the classification methods used, in the number of types, the variable(s) classified, the number of days in a sequence that are classified and in whether the classification is based on year-round or seasonal data. Several classification methods that perform fairly well are identified; they include a simple k-means clustering, a k-means clustering preceded by hierarchical cluster analysis, Litynski's method, and a classification based on circulation prototypes. On the other hand, there are a couple of classification methods that do not provide a good stratification of temperature and precipitation: orthogonally and obliquely rotated principal component analysis in a T-mode, Lund's correlation method, Kirchhofer's sums-of-squares method, and Erpicum's method. Some methods tend to perform better on large domains, while others tend to perform better on smaller domains; however, the sensitivity of most classification methods to the domain size appears to be small. Several methods exhibit a geographical dependence of their performance, e.g. the method based on circulation prototypes tends to perform better in the northern domains, while Jenkinson–Collison and Erpicum's methods perform better in the southern domains. Classifications of 4-day sequences are usually better in stratifying surface temperature than ordinary instantaneous classifications; the opposite is true for precipitation. Adding a mid-tropospheric variable (500 hPa heights or 1000/500 hPa thickness) to sea level pressure as a classified variable improves the skill of classifications in stratifying temperature.

Description: ABSTRACT Atmospheric and oceanic reanalyses are used widely by the climate science community. These products provide full three-dimensional state fields and gapless time series, along with the confidence of being constrained by observational measurements, for atmospheric scientists and oceanographers to use in analyses of the climate system. However, as ubiquitous as reanalysis data are, it is not often considered how a scarcity of measurements in certain poorly observed regions, or over the course of a long period of time in which the observational system has changed significantly, impacts the realism of the data. This study explores this question using tropical surface pressures from the Twentieth Century Reanalysis to hindcast an index of the Madden–Julian Oscillation (MJO) over the 20th century. We show that by changing the choice of surface pressure predictor locations, and being aware of the observational measurements that have been assimilated by the reanalysis system, it is possible to control the estimated centennial-scale trend in MJO activity from nearly zero to an increase of 30% over the 20th century. We emphasize that this is an apparent trend as it arises solely from the use of reanalyzed surface pressures from locations that have either been poorly observed or have experienced significant changes in the observing system over the 20th century. This highlights the need to be aware of the observational measurements (or lack of them), particularly their density in space and time, that have been assimilated by a reanalysis system.

Description: ABSTRACT The coastal China areas stretching from tropical to temperate zone represent major environmental and economic assets. However, knowledge of climate change and its impact in coastal seas, which is very critical for marine resource and risk-management issues, is relatively poor compared with that on land. Here, we show that the coastal China seas experienced a long-term surface warming with a rate of 0.015 °C year −1 and an obvious sea level rise along the coast, particularly along the East China Sea with a rate of more than 3.2 mm year −1 since the late 1950s. The Eurasian atmospheric circulation underwent clearly inter-decadal changes in the past decades due to the tropical ocean thermal changes including warming hiatus and conversely influenced the higher latitude coastal marine conditions through regional air–sea interaction. Marine climate variables including sea surface temperature, sea surface height, and atmospheric cyclonic circulation have formed a favourable condition for phytoplankton blooms such as harmful algae blooms (e.g. red tides) and Enteromorpha prolifera blooms (green tides). These algae blooms could strongly lower oxygen levels in the seawater and have been posing threats for the health of coastal and marine ecosystems since the late 1970s. The impacts and key risks of climate change risks in coastal China seas and the coastal zone are reviewed and analysed as follows: frequent occurrences of red tides and green tides, distribution shifts of marine species and changes in their seasonal behaviour, reduction of coastal habitat, decline of marine ecosystem services, flooding and coastal inundation, seawater intrusion, and threats to coastland community security and marine industries, etc. Furthermore, the accumulated effects of human activity, such as reclamation, sewage discharge, and overfishing, have led to an apparent increase in climate-related vulnerabilities. Adaptation issues and risk-management strategies in response to climate change are discussed and proposed as well.

Description: ABSTRACT With significant impacts on the regional weather and climate, interdecadal climate variability is of great importance in understanding historical observations and predicting the climate in the near future. Using the currently available observation-based products, this study evaluates the ability of climate models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) to simulate the dominant interdecadal variability in the Pacific, i.e. the Interdecadal Pacific Oscillation (IPO). Our results indicate that compared with the CMIP3 models, the CMIP5 models exhibit slightly better performance in reproducing the observed interdecadal variability patterns of both sea surface temperature (SST) and sea level, and also exhibit smaller inter-model spread. Climate models tend to simulate more realistic interdecadal variability patterns for SST than for sea level. A prominent deficiency among CMIP3 and CMIP5 models lies in the northwestern tropical Pacific, where the observations show large sea level variations associated with the IPO, but the simulations are usually much weaker or even of the wrong sign. These biases can be generally associated with the inaccurate representation of wind forcing patterns at the corresponding latitudes (∼12°N). We further suggest that the air–sea coupling may play a role in the bias of interdecadal wind patterns in coupled climate models, and the representation of climatological mean states in climate models could influence the simulated interdecadal variability patterns. This study provides necessary skill information on climate models for further studying the Pacific interdecadal variability, as well as for better distinguishing the climate change signal from internal climate variability.

Description: ABSTRACT This study examines climatic impact of urbanization on the variability of the urban heat island (UHI) effect over Greater Ho Chi Minh City metropolitan area (GHCM), since the late 1980s, using the dynamical downscaling with very high-resolution regional climate model coupled to an urban canopy model (RCM/UCM). This is the first application of RCM/UCM to a city in developing countries in Southeast Asia in assessing the impacts of the past land-use and anthropogenic heat release during the selected three periods (ca. 1989, 1999, and 2009). The main findings are as follows: First, agreement between simulated results (for case of ca. 2009 urban) and observation demonstrates that the RCM/UCM is able to reproduce the urban climate of GHCM. Second, the evolution of spatial distribution of UHI is closely associated with urban expansion. The increase in the surface air temperature was about 0.3 °C in the pre-existing urbanized area and about 0.6 °C in newly urbanized area in the last 20 years. Main factor of these changes is conversion of agriculture or grassland into urban structure, which results in increase in sensible heating and decrease in latent heating. In addition, in the central GHCM, the urbanization impact was estimated at 0.31 °C, while the temperature increase was observed at 0.64 °C in the last 20 years. This suggests that the urbanization may contribute about half to the increase of surface air temperature in the central GHCM.

Description: ABSTRACT Ensembles of regional climate models are widely used to obtain climate change signals and to evaluate associated uncertainties over a specific region. These models are forced by general circulation models (GCMs) at their lateral boundaries. The most recent multi-model ensembles projects – ENSEMBLES and CORDEX – rely on a limited set of about 10 GCMs per greenhouse gas emission scenario. It was shown previously that in particular, RCM temperature responses tend to cluster according to their driving GCM. Therefore, it is important to better understand the relation among the driving models. In multi-model ensembles as large as CMIP5, in which models tend to correlate due to their similar origin, model selection or weighting becomes an important issue. This study evaluates the distribution of climate change signals in the CMIP5 ensemble for temperature and precipitation over the Greater Alpine region and shows that different reasonable methods of model selection considerably influence the resulting temperature spread in the climate change signals at the end of the century relative to 1980–2009: excluding those GCMs with a poor representation of Alpine climate leads to a difference in spread of more than 1 °C compared to a selection strategy where all models are included and given the same weight. It is highlighted that the largest amount of spread can be retained with a weighting scheme based on a cluster analysis. Furthermore, we show in bivariate analyses that our understanding of the interplay between temperature and precipitation significantly depends on the model selection strategy. Hence, this work may have important implications for current and future design and analysis of multi-model projects such as CMIP5 and CORDEX.

Description: ABSTRACT Many tropical islands have limited water resources with historically increasing demand, all potentially affected by a changing climate. The effects of climate change on island hydrology are difficult to model due to steep local precipitation gradients and sparse data. This work uses 10 statistically downscaled general circulation models (GCMs) under two greenhouse gas emission scenarios to evaluate the uncertainty propagated from GCMs in projecting the effects of climate change on water resources in a tropical island system. The assessment is conducted using a previously configured hydrologic model, the Precipitation Runoff Modelling System (PRMS) for Puerto Rico. Projected climate data and their modelled hydrologic variables versus historical measurements and their modelled hydrologic variables are found to have empirical distribution functions that are statistically different with less than 1 year of daily data aggregation. Thus, only annual averages of the projected hydrologic variables are employed as completely bias-corrected model outputs. The magnitude of the projected total flow decreases in the four regions covering Puerto Rico, but with a large range of uncertainty depending on the makeup of the GCM ensemble. The multi-model mean projected total flow decreases by 49–88% of historical amounts from the 1960s to the 2090s for the high emissions scenarios and by 39–79% for the low emissions scenarios. Subsurface flow contributions decreased the least and groundwater flow contributions decreased the most across the island. At locations critical to water supply for human use, projected streamflow is shown to decrease substantially below projected withdrawals by 2099.

Description: ABSTRACT Koshava is a local wind usually observed in the cold part of the year over the large part of Serbia, parts of Romania, parts of Hungary, and east Croatia. The main characteristics of the Koshava wind are its high wind speed, southeasterly direction, persistence, and gustiness. This paper analyses the synoptic [Mediterranean cyclones (MCs) and Eurasian anticyclones (EAs)] as well as the mesoscale contributors to the Koshava wind. Time and spatial features of the pressure systems have been analysed using an automatic cyclone tracking scheme. The results show that the MCs and EAs that generate Koshava are approximately 1000 km away from the Koshava region. It is demonstrated that the strong anticyclones are the main trigger for the Koshava wind. Less than 3% of the Koshava winds occurred without the occurrence of either an anticyclone or a cyclone. The Synoptic Koshava Index (SKI), developed in this study and defined as the difference between the area-averaged mean sea level pressures in the anticyclone and cyclone regions, has been shown to be a good indicator of the Koshava occurrence. Koshava has also been investigated from the perspective of the gap flow windstorm. The across-mountain pressure difference, Δ P , is the most important mesoscale contributor to the Koshava characteristics. The across-mountain potential temperature difference, Δ θ , together with Δ P , can be successfully used to predict Koshava's occurrence. A simple (linear) probabilistic model for forecasting the Koshava mean hourly wind speed has been constructed. The results demonstrate that the occurrence of the Koshava wind can be predicted with the significantly higher accuracy than the Koshava mean hourly speed. The correlation between Koshava and winds at higher levels is small.

Description: ABSTRACT Using the ozone data set from the satellite observations and the atmospheric reanalysis data sets during 1979–2005, we examine the variability of a tropopause-lower stratosphere (TS) teleconnection a and its relationship with the ozone change over the Northern Hemisphere (NH) during summer. The TS teleconnection has an approximate opposite phase to that in the upper-troposphere Asian-Pacific Oscillation (APO), and the TS teleconnection index (the TS index) is also related well to the APO index. Corresponding to a higher TS index, the ozone generally decreases in the NH mid-high latitudes (near 40°N and the Far East of Russia). This link between the TS teleconnection and the ozone is physically supported by the changes of the background atmospheric circulation. When the TS index is higher, the decrease of the ozone is closely associated with an increase of the local tropopause height. The upward and downward motion variations in the upper troposphere and the lower stratosphere in the east and west parts of the anomalous anticyclones associated with the TS index strengthen the exchanges of the ozone between the troposphere and the lower stratosphere, which may cause a decrease of the ozone. The horizontal advection of the ozone could also contribute to the ozone decreases over these regions.

Description: ABSTRACT Understanding how hydrological extremes would respond to global warming and its associated uncertainties is important for better designing mitigation and adaption strategies to cope with global change. Very few works have investigated the changes in future hydrological extremes and, especially, the more devastating joint hydrological extremes over China. In this article, two combinations of joint extremes [i.e. high runoff/high soil moisture (HRHS) and low runoff/low soil moisture (LRLS)] are designed for analysis. To derive the scenarios of hydrological conditions, the bias-corrected daily climate projections from five global circulation models (GCMs) under the historical and Representative Concentration Pathways 8.5 (RCP8.5) emission scenarios are used to drive the calibrated Variable Infiltration Capacity (VIC) model from 1951 to 2099 over China. Results show notable increase of occurrence of HRHS in Northeast China, LRLS in Northwest and South of China under 2 °C global warming. The spatial pattern of changes in joint extremes tends to remain stable with global temperature increase up to 3 °C. Compared with the individual extreme risk, joint extreme are much more concentrated in Northwest and South China and the magnitude of changes is several times larger. Larger areas experiencing changes are found when using lower standards of extreme definition. Because hydrological regime may change gradually in response to climate change, the threshold derived from present regime may lead to misrepresentation of extreme risk analysis. This was demonstrated by the ten times smaller magnitude of changes when adopting the updated transient threshold representing the changing hydrological regime, thus providing a low-boundary of potential changes in extremes. Our results highlight the importance of considering the changing hydrological regime in addition to choosing various levels of threshold for extreme definition in order to cover the full range of possible extreme changes in a warming climate.

Description: ABSTRACT Weather typing, based on surface pressure charts, has been one of the principal means of analysis in synoptic climatology. Here, we use an automated scheme to derive weather types (WTs) and also calculate Lamb weather types (LWTs) for the Falkland Islands. The WTs are based on sea-level pressure data estimated using two reanalysis products: one that extends from 1948 to 2014 and another that just uses station pressure data as input and extends back to 1871. The WTs can be used to derive counts of gale days and these will be compared with storminess estimates based on the rate of change of daily-average pressure measurements at the principal observational site (near the capital, Port Stanley) on the islands. A particular emphasis of the paper is the reliability of the results taking into account that we are using reanalysis datasets from a very data-sparse region of the world. More gale days are estimated during the period from about 1880 to the mid-1910s and since the 1980s. Fewer gale days are evident during other periods, particularly from the mid-1910s to 1947. As these changes are not evident in the storminess measure derived from the sub-daily pressure series for the Port Stanley region, the results in terms of gale-day counts are very suggestive of being due to differences in the quality of the reanalysis during the different periods. The reanalysis appears better the higher the number of gale days estimated. The opening of the Panama Canal in 1914 dramatically reduced the number of ships, and hence observations, rounding Cape Horn. The paper also relates seasonal counts of the LWTs and WTs to recently developed long series of temperature and precipitation for the Port Stanley region.