ALBERT

Description: ABSTRACT In the study, the clear-sky aerosol radiative effects have been quantified at 52 European sites using empirical and radiative transfer modelling approaches. Furthermore, the trends of the aerosol radiative effects are also determined for the period of 2001–2012. The aerosol radiative effects are simulated using the Mesoscale Atmospheric Global Irradiance Code radiation code with aerosol and water vapour climatology. The annual mean of the surface aerosol radiative effects in clear-sky situations over Europe is −7.1 ± 2.9 W m −2 . The trends of the aerosol radiative effects are derived assigning radiative effects to monthly Moderate Resolution Imaging Spectroradiometer aerosol optical depth time series applying linear fitting. In the indirect approach, the clear-sky situations are selected from daily surface solar radiation observations from the Word Radiation Data Centre, and the trends of the aerosol radiative effects are delimitated in these clear-sky radiation time series. The two approaches give good fit, based on the direct approach the annual trend of the aerosol radiative effects on clear-sky solar surface radiation is −4.41 W m −2 per decade for the period of 2001–2013, while in the case of the indirect approach, this trend is found to be −4.46 W m −2 per decade. The seasonal trends of the aerosol radiative effects vary between −7.57 and −0.17 W m −2 per decade indicating stronger decreases in summertime. The results are presented for four sub-regions of Europe detecting negative changes in all cases with a stronger decrease in the central, north-eastern and southern part of the continent. The trends of the aerosol radiative effect have the same magnitude as the trends detected in clear-sky solar surface radiation, and are an order of magnitude higher than the radiative effects of water vapour (0.20 W m −2 per decade).

Description: ABSTRACT This paper documents the changes in climate extremes over Indonesia during the past three decades (1983–2012) based on a subset of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The extreme indices were calculated based on the quality controlled daily observational data (minimum and maximum temperature and precipitation) from 88 weather stations. Overall, we found significant and spatially coherent trends of warming in the temperature indices over Indonesia, consistent with other studies conducted at different countries within the Southeast Asia. The frequency of cool days (TX10p) and cools nights (TN10p) had decreased whereas warm days (TX90p) and warm nights (TN90p) were observed more frequently. Averaged over the country, the annual mean of daily maximum (TXmean) and minimum temperature (TNmean) had increased significantly by 0.18 and 0.30 °C decade −1 , respectively. Other temperature indices also showed significant warming trends. In contrast, trends in the precipitation extremes indices were generally not significant and less spatially coherent. However, a tendency towards wetter conditions was observed, in agreement with the results at the global scale. The daily precipitation intensity (SDII) had increased significantly over the country by 0.21 mm day −1  decade −1 during the period studied. At the regional scale, we observed a significant wetting trend in the annual highest daily amount (RX1day) and the rainfall amount contributed by the extremely very wet days (R99p) in the northern part of the country. The wetting trends of a number of extreme precipitation indices were depicted prominently in December–January–February (DJF) and/or March–April–May (MAM) seasons, both at country and regional levels. However, for the southern region of Indonesia, a drying tendency was observed for June–July–August (JJA), September–October–November (SON) and MAM.

Description: ABSTRACT Based on the daily rainfall data since 1889 in Curitiba, one of the largest cities in southern Brazil, a trend towards increased precipitation and more intense rainfall can be seen. The annual and seasonal volume of rainfall has increased, amounts greater than 10, 20 and 40 mm being observed more often, but with a reduction in the number of rainy days and the number of days with rainfall below 10 mm. Seasonal 95th percentile series have increased in summer, fall and winter. In addition, several indices of climate extremes presented significant increasing trends: monthly maximum 1-day precipitation, annual total precipitation greater than 95th and 99th percentiles, number of consecutive dry days and the daily intensity index. Generalized extreme value (GEV) distribution function parameters also indicated higher occurrence of extremes detected by the increase in both the scale parameter σ and the location parameter μ in summer, fall and winter. The return time for severe rainfall declined in the second half of the period compared to the first, indicating more frequent occurrence of future extreme events. The main climate indices affecting the 95th percentile series were sea surface temperature (SST), South Atlantic Convergence Zone (SACZ) and Southern Oscillation Index (SOI) during spring, and Atlantic Multi-decadal Oscillation (AMO), Large-Scale Index for South America Monsoon (LISAM) and SOI during the summer, which explained variability of the extremes at around 20 and 13%, respectively in each season. Regarding the variability of summer, fall and spring total rainfall, they presented values around 20% for the explained variance due to climate indices. Other factors should be investigated to explain the variability such as urbanization, air pollution and local circulations. Dominant oscillation periods in the time series constructed with one monthly extreme appeared at 3 to 8-year (inter-annual) cycles, with 12 years (decadal) and around 30–64 years on the inter-decadal scale. These oscillations have resonance with SOI, SACZ and Southern Annular Mode (SAM) indices (high frequencies), and Pacific Decadal Oscillation (PDO) and AMO (low frequency).

Description: ABSTRACT Climate change affects mean and extreme temperature and precipitation, increasing the risk of related disasters. Assessing the performance of current models in simulating these aspects is therefore crucial to future projection and policymaking. Based on a large ensemble (LE; 30 members) of the Community Earth System Model (CESM-LE), this study seeks to answer the following two questions: (1) Are the simulated trends of mean and extreme temperature and precipitation over China consistent with observations? (2) What is the range of model uncertainty due to internal variability? The results show that CESM-LE can capture the trends of observed annul mean temperature and extremely low temperature days (ELD) over 16–26% of China, but has difficulty in reproducing the observed trends in extremely high temperature days (EHD). For precipitation, CESM-LE demonstrates similar capability in reproducing the observed trends in annual mean precipitation and extreme precipitation days (EPD). For consecutive dry days (CDD), the decreasing trends over part of northwestern China can be captured, but the increasing trends over northern China cannot be reproduced by CESM-LE. Regarding the uncertainty of the model resulting from natural internal variability, because all 30 ensemble members of CESM use the same model and external forcing, CESM-LE's spread (uncertainty) is mainly due to internal variability. Larger uncertainty in simulated trends is found over northern China and the Tibetan Plateau for annual mean temperature, over northeastern China and the Huang-Huai region for ELD, and over the Tibetan Plateau for EHD. The trends in annual mean precipitation show uniform uncertainty over nearly all of China, except for the northwest. Larger uncertainty trends appear over southern and northwestern China for EPD, and over the Tibetan Plateau and northern China for CDD.

Description: ABSTRACT This study presents the spatio-temporal winter snow albedo analysis over different mountain ranges of north-west Himalaya (NWH) for a period of approximately 24 years. Here we assess the temporal albedo variations in past two decades (1991–2010) in comparison to the recent 14 years (2000–2014). The field collected manual data of two representative observatories of Lower Himalaya (LH) and Great Himalaya (GH), and six automatic weather stations in LH, GH and Karakoram Himalaya (KH) were analysed. Satellite derived MODIS albedo data (MOD10A1) over these stations between 2001 and 2014 were analysed. A good correlation ( r  = 0.59) was observed between monthly average MODIS retrieved albedo and field collected albedo for GH with a relative error of 11%. In past two decades, a statistically significant (99%) decreasing rate of −0.011 per year in winter snow albedo was observed over GH (1993–2010), while in recent decade (2001 onward), no statistically significant increasing trend was observed. The change in albedo of GH is attributed to winter mean air temperature, which shows a significant rise in the past two decades, but there has been a hiatus in winter mean air temperature rise in recent decade. The higher winter mean air temperature above 0 °C since beginning of the study period (1991 onward) kept albedo of moist/wet snow approximately stable in LH. Further, insignificant increasing trend of albedo was observed over KH range in recent decade, and it is attributed to persistent very low temperatures and an increase in the frequency of snowfall days. This albedo study over NWH supports the recently reported findings on Himalayan snow cover and glacier variations during different durations.

Description: ABSTRACT Recent projections of climate change from general circulation and regional climate models over southern Europe and the Mediterranean basin show strong warming and pronounced decrease in precipitation over large portion of the region, especially in the summer. While the role of vegetation in modulating the region's climate is widely recognized, most, if not all, of these climate change projections do not account for the response of the dynamic biosphere to the potential climate changes. In this study we investigate the role of climate–vegetation interactions in a regional climate model (RegCM3) linked to a dynamic vegetation model (CLM-DGVM). High spatial resolution (20 km) simulations of future climate with static vegetation (i.e. vegetation fixed at the present day state) show surface temperature increases across the entire southern Europe/Mediterranean domain in 2085–2089 relative to 1985–1989 due to the radiative and physiological effects of CO 2 increase. In terms of precipitation the simulations exhibit substantial precipitation decreases for most of the domain and both summer and winter seasons. Accounting for the effects of structural vegetation changes significantly alters the simulated climate change effects over these areas, but most substantially over the Mediterranean where vegetation feedback reduces summer warming by 1 K and reverts the 28% precipitation decrease to a 4% increase. These results emphasize the importance of including vegetation feedback in the projections of climate change impacts on the Mediterranean climate including extreme climatic events and storms.

Description: ABSTRACT Vegetation types are generally classified based only on remote sensing vegetation data, and yet they cannot reflect their connection with climate. Climatic vegetation types reflect the regional vegetation characteristics in terms of climate. The distribution of global climatic vegetation types were identified by K-means method based on vegetation and climate data. Fourteen climatic vegetation types were classified based on vegetation and climate data. Every type had distinct climate and vegetation characteristics. The regions with similar normalized difference vegetation index (NDVI) values but with different climate values such as tropical desert and temperate desert could be distinguished. Our new updated climatic vegetation types agreed ‘fair’ with Koeppen climate types and climate type of Zhang and Yan while agreed ‘good’ with vegetation types when checked with Kappa test.

Description: ABSTRACT A detailed understanding of past temporal patterns and spatial expression of temperature variations is important to place recent anthropogenic climate change into a longer term context. In order to fill the current gap in our understanding of northwest European temperature variability, point-by-point principal component regression was used to reconstruct a spatial field of 0.5° temperature grids across Scotland. A sequence of reconstructions utilizing several combinations of detrending and disturbance correction procedures, and a selection of tree-ring parameters [including ring width (RW), maximum latewood density (MXD) and blue intensity (BI)] was used in an evaluation of reconstruction skill. The high resolution of the reconstructed field serves also as a diagnostic tool to spatially assess the temperature reconstruction potential of local chronologies. Best reconstruction results, reaching calibration r 2  = 65.8% and verification r 2  = 63.7% in central Scotland over the 1901–1976 period, were achieved using disturbance-corrected and signal-free detrended RW chronologies merged with BI data after low-pass (high-pass) filtering the RW (BI) chronologies. Calibration and verification r 2  〉 50% was attained for central, north and east Scotland, 〉40% in west and northwest, and 〉30% in southern Scotland with verification of nearly all grids showing some reconstruction skill. However, the full calibration potential of reconstructions outside central Scotland was reduced either due to residual disturbance trends undetected by the disturbance correction procedure or due to other climatic or non-climatic factors which may have adversely affected the strength of the climate signal.

Description: ABSTRACT Intraseasonal precipitation, wind, and vertically integrated moisture flux variability were assessed from June to August between 1998 and 2009. To that end, we used daily precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and ERA-Interim reanalysis. The composites of precipitation anomalies showed that during the intraseasonal enhancement of convective activity over the area assessed, increased precipitation occurs over the northern coast of South America; the opposite is true during the decrease in intraseasonal convective activity. The convective activity over the region of maximum precipitation variance is intraseasonally enhanced during 210 days, whereas the decrease occurs during 194 days. During the days on which the convective activity over the region of maximum precipitation variance was enhanced (decreased) by the Madden–Julian oscillation, the frequency of African easterly waves (AEWs) cases was greater (lower). The most significant average characteristics observed during this period were the displacement of positive precipitation anomalies toward the north and the intensification of the flux toward the tropical North Atlantic Ocean. This pattern disfavours precipitation over the northern coast of South America. On the other hand, during the dry period of Madden–Julian oscillation, there was a decrease in AEWs cases which, although there was negative precipitation anomalies over the northern coast of South America, there were positive anomalies over northwest South America. Therefore, the increase (decrease) in convective activity over the region of maximum precipitation variance favours (disfavours) the frequency of AEWs over this region and, consequently, the precipitation over the northern coast of South America decreases (increases) during the dry season (June to August).

Description: ABSTRACT Previous studies suggest that climate change impacts significantly on the hydro-climatic processes within the Ganges–Brahmaputra–Meghna (GBM) River Basin (RB). This study examines the observed climate characteristics and potential strengths and limitations of three global high-resolution reanalyses and satellite remote-sensing products over the GBM RB for period 1980–2013 by (1) estimating trends and interannual variations of precipitation and temperature, and (2) isolating precipitation variations likely associated with El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The surface temperature trends show widespread warming across the basin with a maximum increase of 0.6 °C decade −1 over western Nepal and southern Tibet from 1980 to 2013. Rainfall changes from 1980 to 2013 indicate pronounced decline over high rainfall regions of northeast India, Bhutan, Nepal, and Bangladesh, especially from 1998 to 2013. Basin-wide averaged trends show rainfall decline of up to 39 mm decade −1 in June–August in the Brahmaputra–Meghna RB from 1998 to 2013. Temperature variability based on Principal Component Analysis indicates that the first mode is associated with sea surface temperature (SST) warming in the Arabian Sea and the western tropical Pacific Ocean, while the second mode appears to be significantly correlated to SST anomalies in the western (eastern) tropical Indian (Pacific) Ocean. ENSO and IOD events are found to significantly influence rainfall variability contributing to about 10–20% (ENSO) and 8–10% (IOD) of the annual rainfall, mainly over Bhutan, Nepal, Bangladesh, and north-eastern India. Among the three reanalysis products: European Centre for Medium-Range Weather Forecasts (ECMWF) retrospective analysis (ERA-Interim), Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR), ERA-Interim (and MERRA) agrees well with the observed precipitation (temperature) data sets while, CFSR shows the least skills in representing the spatio-temporal variations of precipitation and temperature.

Description: ABSTRACT This study has investigated the influence of the decadal component of the Pacific Decadal Oscillation (PDO) on the Indian monsoon in observations and coupled climate model. A major part of the conventionally defined PDO is shown to be dominated by interannual variability. By extracting the pure decadal part of the North Pacific variability, this study has shown that the Indian monsoon rainfall exhibits different relations with the conventionally defined PDO and the pure decadal component of the PDO. This result may have implications for decadal prediction of the monsoon. The analysis suggests that the warm (cold) phase of pure decadal variability of PDO is associated with deficit (excess) rainfall over the west central part of India. In contrast, the conventional warm (cold) PDO index is associated with deficit (excess) rainfall over most of India. The warm phase of the pure decadal PDO opposes the moisture flow beyond 20°N over the Indian monsoon region via the meridional winds extending from the North Pacific and leads to reduced rainfall over west central India. The Community Climate System Model version 4 of the National Center for Atmospheric Research shows reasonable simulation of the decadal PDO mode in both the North Pacific sea surface temperature and the Indian monsoon rainfall and the relation between them. Further, the observed and simulated PDO–monsoon relation is substantiated through a regionally de-coupled experiment. The coupled model experiment also provides supporting evidence for the mechanism involving the intermediary role played by the tropical Pacific Ocean in the PDO–monsoon relation.

Description: ABSTRACT This study explores the sensitivity of high-resolution mesoscale simulations of urban heat island (UHI) in the Chicago metropolitan area (CMA) and its environs to urban physical parameterizations, with emphasis on the role of lake breeze. A series of climate downscaling experiments were conducted using the urban-Weather Research and Forecasting (uWRF) model at 1-km horizontal resolution for a relatively warm period with a strong lake breeze. The study employed best available morphological data sets, selection of appropriate urban parameters, and estimates of anthropogenic heating sources for the CMA. Several urban parameterization schemes were then evaluated using these parameter values. The study also examined (1) the impacts of land data assimilation for initialization of the mesoscale model, (2) the role of urbanization on UHI and lake breeze, and (3) the effects of sub-grid scale land-cover variability on urban meteorological predictions. Comparisons of temperature and wind simulations with station observations and Moderate Resolution Imaging Spectroradiometer satellite data in the CMA showed that uWRF, with appropriate selection of urban parameter values, was able to reproduce the measured near-surface temperature and wind speeds reasonably well. In particular, the model was able to capture the observed spatial variation of 2-m near-surface temperatures at night, when the UHI effect was pronounced. Results showed that inclusion of sub-grid scale variability of land-use and initializing models with more accurate land surface data can yield improved simulations of near-surface temperatures and wind speeds, particularly in the context of simulating the extent and spatial heterogeneity of UHI effects.

Description: ABSTRACT The seasonal variation of the atmospheric structure, vertical shear, stability, and rainfall distribution over the island of Kyushu, southern Japan, is studied using 16 years of observational data, from 1998 to 2013. Over 20 000 twice-daily rawinsonde observations from the cities of Kagoshima (southern Kyushu) and Fukuoka (northern Kyushu) are utilized along with daily precipitation data from 120 Japan Meteorological Agency stations located across the island. Understanding the local atmospheric circulation and climatological behaviour of the island is important both locally due to the island's large population and regionally, due to its position in relation to the tracks of typhoons generated annually over the Pacific ocean and make landfall here, the rainy season associated with the Asian monsoon, and the large number of active volcanoes located on or near the island, emitting volcanic gases and ash on a daily basis. Using a categorisation based on convective available potential energy and precipitable water, three sounding categories are distinguished, described using the origins of the air masses involved, as seen from trajectory modelling: continental (dry), oceanic (moist/unstable), and mixed (moist/stable). Mean soundings for each category are examined, along with information on their annual and seasonal variability. Each sounding category is linked with a rainfall response: low amounts of rainfall, heavy convective rainfall, and heavy, non-convective rainfall, respectively. Despite the large difference in the potential for heavy rainfall rates, average daily rainfall rate is similar for the two moist categories, but peak rainfall rates for convective rainfall are twice as large as those for non-convective. Despite the simplicity of the criteria, the three sounding categories are statistically robust and exhibit a relatively small amount of variability. The monthly combination of the sounding categories is shown to be a deciding factor in the seasonal variation of the atmospheric circulation, weather, and precipitation over the island.

Description: ABSTRACT The development of Adapted Caussinus–Mestre Algorithm for homogenising Networks of Temperature series (ACMANT), one of the most successful homogenisation methods tested by the European project COST ES0601 (HOME) has been continued. The third generation of the software package ‘ACMANT3’ contains six programmes for homogenising temperature values or precipitation totals. These incorporate two models of the annual cycle of temperature biases and homogenisation either on a monthly or daily time scale. All ACMANT3 programmes are fully automatic and the method is therefore suitable for homogenising large datasets. This paper describes the theoretical background of ACMANT and the recent developments, which extend the capabilities, and hence, the application of the method. The most important novelties in ACMANT3 are: the ensemble pre-homogenisation with the exclusion of one potential reference composite in each ensemble member; the use of ordinary kriging for weighting reference composites; the assessment of seasonal cycle of temperature biases in case of irregular-shaped seasonal cycles. ACMANT3 also allows for homogenisation on the daily scale including for break timing assessment, gap filling and ANOVA application on the daily time scale. Examples of efficiency tests of monthly temperature homogenisation using artificially developed but realistic test datasets are presented. ACMANT3 can be characterized by improved efficiency in comparison with earlier ACMANT versions, high missing data tolerance and improved user friendliness. Discussion concerning when the use of an automatic homogenisation method is recommended is included, and some caveats in relation to how and when ACMANT3 should be applied are provided.

Description: ABSTRACT Snow cover extent, duration, and properties were simulated (1979/1980–2013/2014) for the Rio Olivares Basin (548 km 2 ) in central Chilean Andes, in an effort to understand conditions and trends (linear) at a basin scale. The National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications products, together with the snow modelling software package SnowModel allowed simulations of first-order atmospheric forcings (mean annual air temperature (MAAT) and water-equivalent precipitation) and terrestrial snow features (snow cover extent, duration, snow water-equivalent depth, snow density, and runoff generated from snow melt). Simulated snow cover extent and depletion curves were verified against Moderate Resolution Imaging Spectroradiometer-derived snow cover data. For the Rio Olivares Basin, MAAT was −2.9 ± 0.6 °C with a mean 0° isotherm at 3325 m a.s.l. The greatest temporal and spatial changes in temperature over the 35-year period occurred in January and at the highest elevations, respectively. Mean annual precipitation was 1.86 ± 0.60 m w.e., indicating an increase in precipitation of ∼0.1 m w.e. 100 m −1 increase in elevation. On average, ∼90% of the basin precipitation fell as snow, varying from 70% at ∼2600 m a.s.l., to 95% at ∼4200 m a.s.l. In 20 out of 35 years the snow cover extent went to 0% (no basin snow cover) by end-of-summer (during March), and the snow duration increased on average by ∼10 days 100 m −1 increase in elevation. Approximately 85% of the basin outlet freshwater runoff originated from snowmelt, making snowmelt a dominant contributor to water resources. Snowmelt-derived basin runoff was dominated by variability in snow precipitation rather than by variability in MAAT.

Description: ABSTRACT This contribution employs instrumental records to analyse the temporal and spatial variability of monthly, seasonal and annual maximum wind gusts (MWGs) in the Czech Republic. The development of an observation network capable of measuring wind gusts, the possible technical weaknesses of wind measurements and problems with establishing homogeneity in wind-gust data are described. For the 1961–2014 period, quality-checked data from 19 synoptic stations of the Czech Hydrometeorological Institute throughout the territory of the Czech Republic are examined, divided into three altitudinal groups. In terms of the spatial variability of MWGs, correlation coefficients between stations decrease more strongly in relation to station distance rather than altitude. Spatial correlations are better expressed (by higher correlation coefficients) in the winter half-year than in the summer half-year. Linear trends in monthly, seasonal and annual MWGs for the 19 synoptic stations, for their three altitudinal groups, and for the entire Czech Republic show statistically significant decreases (deepest in November and autumn), with the exception of spring (for stations above 300 m) and summer. The 10 highest MWG events of all are selected. The spatial distribution of wind gusts for two prominent windstorms, Kyrill (18–19 January 2007) and Emma (1–2 March 2008), are presented. Changes in MWGs series are compared with fluctuations in atmospheric circulation responding to the North Atlantic Oscillation. Decreasing MWG trends are discussed with respect to diminishing storminess and surface wind speeds (wind stilling) recorded during recent decades in Europe, as well as over other continents.

Description: ABSTRACT This study analyzes the spatiotemporal variability of rainfall and temperature (minimum, maximum and average) trends at 47 stations throughout the Brazilian Legal Amazon for the period 1973–2013. Annual, wet season and dry season trends were quantified by Sen's slope for each station and the entire region. The Mann–Kendall test was used to determine the statistical significance of the trends. For the whole region, minimum, maximum and average annual temperatures showed increasing trend of approximately 0.04 °C per year. The rainfall showed an insignificant trend for most stations for annual and seasonal series. Nevertheless, some stations showed significant increasing trends in the annual and wet season rainfalls while a few stations showed decreasing trends for the dry season rainfall. A positive trend of the annual range between wet and dry season rainfall was found in some stations, caused mainly by an increasing trend in wet season rainfall.

Description: ABSTRACT Quality controlled homogenized regional anomaly series of temperature and precipitation are obtained for the central Pyrenees for the period 1910–2013. A 0.1 °C decade −1 positive trend is found for minimum and maximum annual temperature exceeding the significance level of 0.05 for the whole studied period. A significant warming is found in all seasons except boreal spring in minimum temperature and winter in maximum temperature. The annual regional precipitation anomaly series shows a high inter-annual variability and a slightly negative non-significant trend of −0.6% decade −1 . Non-significant negative trends of precipitation are found in all seasons for the whole period examined. Considering the recent period 1970–2013, values of temperature trends are generally higher than those obtained for the whole period. For this latest period, all maximum temperature trends are significant while only the minimum temperature trend in winter is non-significant. Spring is the season that presents the greatest warming, with 0.9 °C decade −1 for maximum temperature and 0.4 °C decade −1 for minimum temperature. Evaluating the same period for precipitation anomalies, trends in the annual, winter and summer series remain negative, while spring and autumn trends are positive although non-significant. This series represents the longest homogenized climate data set available for the central Pyrenees region, including the newly recovered period 1910–1949, offering new possibilities for climate analysis and paleoclimate proxy calibration.

Description: ABSTRACT A marked seasonality in the occurrence of Madden–Julian Oscillation (MJO) events is well known. The core region of oscillation is located at low latitudes (between the equator and 15°) in the summer hemisphere. The eastward progression of MJO signal interacts with the monsoon circulation and modulates the advance period of Indian summer monsoon (ISM). The analyses suggest that the mean advance period of ISM (41 days) is comparable with the life cycle of the MJO (30–60 days). The advance period of ISM has been categorised into normal, fast and slow-advance years to decide the pace of the monsoon during progression of monsoon. During the period 1983–2015, the fastest progress of the monsoon was seen in the year 2013 (fastest advancement in the last 33 years) and slowest progress of monsoon was seen in the year 2002 (most lethargic advancement in the last 33 years). The results of the analyses show that variation in daily MJO-amplitude during fast-advancement years is more as compared with the normal and slow-advancement years. The normal-advancement years mostly occur during MJO phase 1 and phase 2 and fast-advancement years frequently occur during MJO phase 2; however, slow-advancement years are found to occur during MJO phase 5 and phase 6. The MJO phase 2 is the most frequent phase and MJO phase 8 is the least frequent phase during advance of monsoon. However, the highest amplitude is recorded during MJO phase 8. The strong (weak) monsoon current is modulated by strong (weak) MJO phases.

Description: ABSTRACT This study compares the multivariate predictions of daily temperature, temperature range, precipitation, surface wind and solar radiation of a single-model analogue approach with an original multi-model analogy over 12 regions in Europe and Maghreb. Both approaches are based on two-level analogue models where atmospheric predictors are either dynamic or thermodynamic. In the multi-model approach, independent analogue models with predictand-specific predictors are used. In the single-model one, a unique analogue model and its associated set of predictors is applied to all predictands. Testing numerous large-scale predictors, we first identify the best predictor sets for each modelling strategy. Those obtained for the single-model approach are significantly different from those of the predictand-specific models. This is especially the case for local temperature and wind speed. Both methods perform similarly for precipitation, temperature range and radiation. We next assess the ability of both approaches to simulate physically coherent multivariate weather scenarios. With the single-model method, weather scenarios are obtained for each prediction day from observations sampled simultaneously on one analogue day. The physical consistency between variables is thus automatically fulfilled each day. This allows the single-model method to reproduce well the observed inter-predictand correlations, especially the significant correlations between radiation and precipitation and between radiation and temperature range. These results suggest a hybrid analogue model using a single-model for radiation, temperature range and precipitation, combined with a univariate approach for wind. Two options are proposed for temperature for which either the predictand-specific method or a single-model approach with an additional correction are conceivable. This hybrid approach leads to a possible compromise between reasonable univariate prediction skills and realistic inter-predictands correlations, both classically required for many impact studies.

Description: ABSTRACT Southeast Brazil (SE Brazil) is the most densely populated region in Brazil. Previous studies have shown evidence of positive trends in average precipitation and extreme events in a few locations, suggesting the increase in rainfall-related hazards with potential impacts to urbanized areas of SE Brazil. This study provides a comprehensive analysis of the spatial variability of trends in extreme precipitation over SE Brazil focusing on regional and local scales. We examine two daily rainfall datasets with more than 70 years of data: individual stations and gridded observed precipitation data. Our results indicate that the frequency of both rainy days and extreme daily precipitation events have increased in Sao Paulo state. Conversely, precipitation has become more concentrated in fewer events in Rio de Janeiro and Espirito Santo states where both data sets indicate positive trends in the intensity of extreme daily rainfall. The increases in frequency and intensity of extreme events have both contributed to positive trends in total seasonal and average daily precipitation over Sao Paulo. Additionally, the individual stations indicate negative trends in the number of light rainy days over large urbanized areas in the state of Sao Paulo. The spatial patterns of trends indicate that they are influenced by the proximity of large urban centres and topographic features, and also suggest variations and changes in the major climatic systems affecting precipitation regimes over SE.

Description: ABSTRACT Geostationary Operational Environmental Satellite (GOES) visible imagery was used to identify lake-effect (LE) clouds in the North American Great Lakes region for the cold seasons (October–March) of 1997/1998 through 2013/2014 to provide a comprehensive climatological description of the seasonal and interannual variability of LE cloud bands. During the average cold season, at least 60% of days each month had LE clouds over some portion of the Great Lakes region and nearly 75% of all LE days had LE clouds present over several lakes simultaneously. Wind-parallel bands (WPB) are observed far more frequently than any other type of LE over Lakes Superior, Michigan, and Huron during the months of December, January, and February. Over Lake Erie, the occurrence of days per month with WPB was found to be approximately 5–10% greater than days with shore-parallel bands (SPBs) throughout the entire cold season. The greatest frequency of SPB occurrences in the Great Lakes region was over Lake Ontario during the months of January and February (∼20% of days). In addition, Lake Ontario was the only lake where the frequencies of WPB and SPB occurrences were fairly similar each month. The annual frequency of WPB occurrences are the most variable among the Great Lakes, decreasing in frequency from the western lakes toward the eastern lakes. Lake Ontario has the largest annual frequency of SPB occurrences and the greatest variation in SPB annual frequency. Lake Huron has the second largest annual frequency of SPB days with small interannual variation. The primary differences of the annual frequency of lake-to-lake (L2L) LE occurrences when compared with previous research were a greater variability in the L2L annual frequency of Superior-to-Michigan connections, greater frequency of Michigan-to-Huron connections, and less frequent occurrences for Superior-to-Huron and Michigan-to-Erie connections.

Description: ABSTRACT The skill in predicting intraseasonal characteristics of synoptic type occurrences at the seasonal time scale over the all-year rainfall region of South Africa (35°–33°S and 21°–27°E) is assessed by utilizing an ensemble of simulations performed using the GloSea5 coupled ocean–atmosphere model. Hindcasts of daily sea-level pressure fields of 14 austral spring [September–October–November (SON)] and summer [December–January–February (DJF)] seasons, initialized in August and November, respectively, are analysed. The skill assessment is achieved through the use of self-organizing maps. Deterministic and probabilistic assessment of synoptic type frequency forecasts indicate that intraseasonal circulation variability over the Cape south coast region is marginally predictable at seasonal time scales, more so during SON than DJF. In particular, the results obtained demonstrate that there is potential for the skillful seasonal prediction of the anomalous frequency of occurrence of high-impact rainfall events associated with cut-off lows within SON seasons.

Description: ABSTRACT This article specifies a multi-factor long memory process, namely Gegenbauer process, particularly adapted for data with slow damping correlations and cyclical patterns, and explores the use of this representation in the inter-annual climate variability range capture by indices of the El Niño Southern Oscillation (ENSO). The empirical results suggest that sea surface temperature (SST) indices are stationary long memory processes. It is found that the indices in the eastern and central Pacific exhibit different dynamics. The variability of the eastern equatorial Pacific SST indices (Niño 1 − 2 and Niño 3) is characterized by a large component of long-memory behaviour associated with the quasi-biennial and the semi-annual frequency. In contrast, the variability of the central Pacific SST indices (Niño 3.4 and Niño 4) is characterized by a large component of long-memory behaviour associated with the annual and the semi-annual frequency. These results are consistent with recent studies that suggest that ENS0 SST anomalies in the equatorial Pacific can be considered to consist of two processes. The use of Gegenbauer processes can be considered as an alternative competitive procedure in the analysis of cyclical long memory climatological time series from a different time series perspective.

Description: ABSTRACT Lamb's weather types classification has been used here to analyse the characteristics of raindrops in relation with the meteorological situation. A rainfall gathering campaign has been carried out in Leon [northwesterly (NW) Spain] over 34 months. An optical disdrometer has been used to determine drop sizes and the meteorological situations have been classified from the pressure values at surface level in 16 grid points over the study zone. The results have revealed seasonal differences in the average duration of the rain events: 40 min in winter and 12 in summer. In the study period, the rainiest weather types were the cyclonic types, and the air flows from the north and the west. The raindrop sizes follow a gamma distribution with a higher mode in the case of the weather types with air masses from the west and the southwest. The only exception lies in the purely directional weather types, where a higher mode is found in the case of rain events with eastern flows.

Description: ABSTRACT The scientific debate on the impact of climate change on hurricane intensity/strength continues. Regardless of its causes, the consequence of increasing hurricane intensity is undeniably immense among coastal residents. In this study, we investigate how various objective measures of hurricane strength affect people's perception of changing hurricane strength over time. We utilize original survey data to examine the relationship between perceived and actual shift in hurricane strength. In this article, hurricane strength is indicated as maximum wind speed at landfall, storm surge, and economic damage. We find that the characteristics of hurricane strength associated with the most recent landfall are much more closely associated with perceptions of changing hurricane strength than objectively measured trends. This result is consistent with availability bias, suggesting that perceptions are associated with most accessible and retrievable events. We also find that people's belief in climate change play a powerful role in one's perception of changing hurricane strength. Political predispositions are found to affect one's perceptions of changing hurricane strength. Compared to Democrats and Independents, Republicans are far less likely to believe that climate is changing and thus they tend to not believe that hurricanes are becoming stronger. Given that this study focuses on how physical characteristics of past hurricane events influence individual perceptions of hurricane strength shift, future research should focus on how expectations of future climate and weather-related events influence individual attitudes and behaviours.

Description: ABSTRACT The response of field-grown vegetables to adverse weather conditions is strongly coupled to the timing of adverse events, the sensitivity of the growth stage of the impacted crop and the management actions that are taken. To estimate the long-term yield response to changes in temperature and precipitation as well as the short-term response to key adverse weather events (e.g. heavy precipitation, drought and heat stress) on the yields of vegetable crops, we used several statistical approaches with six daily impact-indicators, the four monthly drought indices and the climate trends. Our study integrated a newly available historical yield dataset at the district level (the finest spatial resolution) for all highly marketable vegetables (celeriac, late carrots, root parsley, early kohlrabi, summer savoy cabbage, late cauliflower, late cabbage, onions, green peas, tomatoes, salad and pickling cucumbers) and a high-resolution historical climate dataset (seven daily meteorological variables at a 10 × 10 km resolution) over a 54-year period in the Czech Republic (CZ). Different indices were used to reflect different dimensions of water and heat stress, which have different impacts on vegetable growth and yield. We find positive long-term impacts of recent warming on fruiting vegetables (from 4.9 to 12.2% °C −1 ) but decreases in the yield stability of traditionally grown root vegetables in the warmest areas of the country. Short-term extreme temperature variabilities (days with heat stress) were found to be the dominant type of adverse event for tomato and cucumber production due to its effect on increased soil water demand, which increased transpiration rates, whereas changes in both the diurnal temperature ranges and minimum temperature ( T min) were associated with minimal risk of frost damage. Brassicas vegetables are widely irrigated in the CZ, but irrigation does not fully mitigate drought effects; hence, short-term extreme precipitation variability largely controls crop production in the growing districts. The high frequencies of dry days and days with heavy precipitation within the critical growth stages of brassicas reflect a competition between more dry days and greater precipitation intensity on wet days. The yield variability of bulbs is largely explained by both short-term extreme precipitation and temperature variability (drought-heat stress), which reflects the predominantly rain-fed system of onion cultivation. Both drought and heat stress and changes in T min were important in explaining yield losses of root vegetables. Legumes had the lowest risk of multiple stresses during their short growth cycle, but droughts remain the dominant type of adverse event. Years with yield gains were substantially more common than years with yield losses for brassicas, bulbs and legumes vegetables in all of the cultivated regions.

Description: ABSTRACT As the recent global warming hiatus has attracted worldwide attention, we examined the robustness of the warming hiatus in China and the related dynamical mechanisms in this study. Based on the results confirmed by the multiple data and trend analysis methods, we found that the annual mean temperature in China had a cooling trend during the recent global warming hiatus period, which suggested a robust warming hiatus in China. The warming hiatus in China was dominated by the cooling trend in the cold season, which was mainly induced by the more frequent and enhanced extreme-cold events. By examining the variability of the temperature over different time scales, we found the recent warming hiatus was mainly associated with a downward change of decadal variability, which counteracted the background warming trend. Decadal variability was also much greater in the cold season than in the warm season, and also contributed the most to the previous accelerated warming. We found that the previous accelerated warming and the recent warming hiatus, and the decadal variability of temperature in China were connected to changes in atmospheric circulation. There were opposite circulation changes during these two periods. The westerly winds from the low to the high troposphere over the north of China all enhanced during the previous accelerated warming period, while it weakened during the recent hiatus. The enhanced westerly winds suppressed the invasion of cold air from the Arctic and vice versa. Less frequent atmospheric blocking during the accelerated warming period and more frequent blocking during the recent warming hiatus confirmed this hypothesis. Furthermore, variation in the Siberian High and East Asian winter monsoon season supports the given conclusions.

Description: ABSTRACT To quantitatively describe the Late Holocene palaeoclimatic history of the southern slopes of the Tianshan Mountains in Xinjiang, China, we collected 74 surface pollen samples (from −154 to 4285 m), together with 81 fossil samples from Swan Lake. Based on modern pollen assemblage and redundancy analysis (RDA) of surface pollen data, five pollen zones were divided (alpine cushion vegetation, alpine meadow, subalpine meadow steppe, montane desert, and typical desert zones). Modern pollen–climate transfer functions were developed to quantitatively reconstruct palaeoclimate of the area using the weighted averaging partial least squares regression method. Reconstructed mean annual precipitation and mean annual temperature results suggest that a dry/warm or humid/cold climate pattern prevailed over the past 4200 aBP. Notably, three cold and humid stages were detected at 4200–4000 cal. aBP, 3700–2000 cal. aBP, and 1170–930 cal. aBP. Moreover, a humid ‘Medieval Warm Period’ (MWP) occurred not only on the northern slopes but also on the southern slopes of the Tianshan Mountains. However, based on palaeo-environmental records and on archaeological documents, it would appear that a dry MWP occurred in southern parts of south Xinjiang, with this being different from the MWP on the Tianshan Mountains. Interactions between monsoon and the westerly airflows might account for this difference. The data will improve understanding of past atmospheric circulation systems in the different parts of Xinjiang and will help to predict the future climate in the world.

Description: ABSTRACT In order to clearly classify El Niño–Southern Oscillation (ENSO) events into eastern Pacific (EP) and central Pacific (CP) types, we develop two new indices defined as pattern correlation coefficients (PCCs) between monthly sea surface temperature (SST) anomalies (SSTAs) and first two leading empirical orthogonal function modes of tropical Pacific (20°S–20°N, 110°E–70°W) SSTAs. These new indices not only show close relationships with ENSO indices derived from several previous methods, but also demonstrate reasonable abilities to distinguish between two types of ENSO event. The major characteristic features of the EP-type and CP-type ENSO forcings are well captured from SST responses regressed onto each new index. Furthermore, the monthly frequencies of occurrences derived from two indices are quite similar to variation patterns of phase-locking behaviours of two types of ENSO event.

Description: ABSTRACT An impact of global warming on the first-flowering date (FFD) of cherry, peach and pear in north-eastern Asia are investigated using the Korean national scenario. For the study, we used the dynamically downscaled daily temperature with 12.5 km horizontal resolution derived from five regional climate models (RCMs) under the same lateral forcing from HadGEM2-AO on the basis of Historical (1981–2010) and four Representative Concentration Pathway (RCP) (2021–2100) scenarios. According to our analysis of the Historical simulations, the five RCMs and phenological model have good capability in simulating temperature and FFD with uncertainties of about 2.4–3.4 °C and 8.4–13.9 days, respectively, while well reflecting the topographical effect. On the basis of the highest emission scenario (RCP8.5), the temperature increments of 4.8 °C induce an acceleration in blooming rate, thereby advancing the FFDs of cherry, peach and pear by the end of the 21st century by about 14.5, 15.8 and 14.5 days, respectively, compared with the current reference simulation (Historical). We found high availability of the Korean national scenarios with moderate reliability. We believe that the next generation of the Korean national downscaling project considering diverse lateral forcing will offer better performance and more useful projections to end users.

Description: ABSTRACT This study investigated the climatic influence on the corn sowing date in the Midwestern United States by comparing the survey data of corn cultivation with meteorological records in nine states for the last 36 years (1979–2014). The results show that the year-to-year changes in the sowing date were significantly affected by springtime air temperature and precipitation in the nine states, although large state-to-state differences were found in the degree of sowing date–meteorology relationship. We determined that the 36-year climatological warm period (CWP) with daily mean temperatures ≥10 °C plays an important role in the state-to-state differences. For the states with longer CWPs, the influence of air temperature (precipitation) was generally weaker (stronger). This observed counteractive relationship should be considered for crop modelling for more effective assessment of the impact of climate change on agriculture. Copyright © 2016 John Wiley & Sons, Ltd.

Description: ABSTRACT In this article, we investigate indicators for lightning activity by analysing the data of surface heat flux, Bowen ratio (ratio of sensible to latent heats) and cloud base height for a period of 16 years (1998–2013) over Indo-Gangetic Plain (IGP) (25°–27°N, 80°–88°E), Indian land excluding IGP (8°–36°N, 68°–98°E) and 10 years (2000–2009) over Indian seas [Arabian Sea (5°–20°N, 65°–80°E) + Bay of Bengal (5°–20°N, 80°–98°E)]. Lightning activity varies with the surface heat flux, Bowen ratio and cloud base height over India. Over Indian land, annual lightning flash counts are found to be more by 32 and 24% than those over IGP and Indian seas, respectively. Total heat flux (sensible + latent) and lightning flash counts show a strong correlation coefficient of 0.75 for Indian land and 0.73 for IGP relative to that of Bowen ratio with lightning flash count (0.63 for Indian land and 0.19 for IGP). Hence, the total heat flux represents the best parameter for describing lightning activity over IGP and Indian land. Bowen ratio ≥1 in pre-monsoon increases lightning flash counts over IGP and Indian land. Cloud base height (a measure of moisture) and lightning flash counts show values in the order as Indian land 〉 Indian seas 〉 IGP. Geographic asymmetry of Indian land, IGP and Indian seas drive the continental and sea surface–atmosphere interactive processes that corroborate: (1) asymmetric synoptic scale delivery of moisture to Indian land and IGP from Indian seas revises the Bowen ratio, cloud base height and lightning activity, (2) increase in lightning activity with the total heat flux over Indian land and (3) enhance the lightning activity with the cloud base height/liquid condensation level.

Description: ABSTRACT Interpolating soil moisture at the regional scale (10 4 –10 7  km 2 ) is challenging because in situ observations tend to be sparse, and hydrometeorological conditions and soil characteristics have significant spatial variability. This study is the first to apply the reduced optimal interpolation (ROI) method to soil moisture. The ROI method uses both in situ and variable infiltration capacity (VIC) simulated-soil moisture to generate interpolated soil moisture surfaces in Oklahoma. The ROI method is based on an empirical orthogonal function (EOF) analysis that identifies the leading spatial modes of soil moisture variation based on the model simulation and then applies these EOFs using the temporal variations in the observed soil moisture. The interpolated soil moisture surfaces generated using ROI are compared with Cokriging, which also uses VIC simulations as a secondary input, and the inverse distance weighting (IDW) approach. The accuracy of all three interpolation methods are evaluated using soil moisture measurements from 65 stations. The ROI method is significantly more accurate than IDW and it also outperforms Cokriging. We demonstrate that ROI can be used to accurately depict the spatial patterns of soil moisture at the local and regional level.

Description: ABSTRACT In 2015, large parts of Europe were characterized by extraordinary high summer temperatures, accompanied by very dry conditions, particularly in central-eastern Europe. Several major heat episodes occurred from the end of June until mid-September. We provide an ad-hoc evaluation of the observed climatological extremes in a secular context, by using a set of long station time series in daily resolution. Our data set comprises 42 temperature and 43 precipitation records, predominantly starting already in the 19th century. To investigate local record values, the individual full record length is analysed for each station, while regionally averaged analyses are presented for the core study period of 1901–2015. The study area covers Europe's central latitudes (44° to 52°N), extending from England in the west up to the central Ukraine in the east. During summer 2015, various indices representing extremely high maximum and minimum temperatures (strongly) exceeded previous record high values, mainly in an area extending from eastern Germany to western Ukraine. Additionally, severely to extremely dry conditions with unusually frequent dry days were prevailing particularly in the (central-) eastern part of the study area. Drought indices combining temperature and precipitation revealed drought conditions comparable or even worse than those of former extreme summers like 2003.

Description: ABSTRACT The impacts of El Niño (EN) on the rainfall over South America are investigated considering three EN types differing in the locations of the maximum sea surface temperature (SST) anomalies in the equatorial Pacific: the Central-Pacific (CP), Eastern-Pacific (EP) and the Mixed (MIX) types. The largest positive (SST) anomalies for the EP and CP types occur, respectively, in the eastern and central sectors of the tropical Pacific during all seasons. The SST anomaly pattern for the MIX-EN resembles that of the EP–EN during its onset stage, and of the CP–EN during its mature and demise stages. The different SST anomaly patterns affect the large-scale (Walker circulation and the tropospheric Rossby-wave trains) and local (South American low-level jet – SALLJ) atmospheric circulation patterns in different ways and lead to distinct precipitation anomaly patterns over South America. Variations in the position and longitudinal extension of the downward motions of the EN-related eastward-displaced Walker circulation explain the differences in the dryness over equatorial South America. For the CP–EN, a double Walker cell defines a more zonal configuration of the equatorial dryness over South America during the first three analysed seasons. This feature is not noted for the other two EN types. The Rossby-wave train pattern path depends on the EN types and seasons. In consequence, the associated local atmospheric circulation patterns depend also on the season and EN types. In all seasons, an intense SALLJ for the EP EN contrasts with weak or inexistence SALLJ for the other two EN types. Thus, a wetter condition over southeastern South America, southern and eastern Brazil occurs for the EP EN in relation to the other EN types. The results shown here, in particular considering the MIX EN type, have not been discussed before and might be useful mainly for climate monitoring purposes.

Description: ABSTRACT The relationship between interannual variability of Zimbabwe rainfall and atmosphere–ocean interaction processes is established using high-resolution rainfall station datasets. Empirical orthogonal function (EOF) analysis is used to extract the spatiotemporal modes that explain most of the variations in the rainfall pattern. Results suggest strong homogeneity in the rainfall pattern that is dominantly described by EOF mode 1. The correlation analysis of mode 1 with sea surface temperatures (SSTs) supports the assumption that El Niño Southern Oscillation (ENSO) has a significant influence on Zimbabwe summer rainfall. Significant correlations exist between rainfall and SSTs over large regions of the tropical Indian and Pacific Oceans. The seasonal response of rainfall to the southern annular mode is reflected in both modes 1 and 2. Mode 1 suggests homogeneity in rainfall variations within the country and mode 2 describes the north–south rainfall fluctuations in the country. Although the magnitudes of their loadings are small, modes 3 and 4 extracted distinct rainfall regions within the country. This could be attributed to the use of more reliable, higher resolution rainfall data. These findings will assist to bring profound improvements to seasonal rainfall forecasting techniques around the country.

Description: ABSTRACT Precipitation in the Tibetan Plateau (TP) reaches its peak in summer. The seasonal projection skill of a statistical downscaling model (SDM) for summer precipitation in the TP was compared with that of direct model output. The SDM, which is based on canonical correlation analysis (CCA), significantly increased the projection skill. The CCA reveals the flow patterns behind the seasonal projection skill of summer precipitation in the TP between 1961 and 2012 and quantifies its relative contributions. East Asia 500 hPa geopotential height (ZG500), tropical Indian Ocean sea surface temperature (SST) and east Asia 850 hPa meridional water vapour flux (MWVF850), obtained from the Max Planck Institute Earth System Model, low-resolution (MPI-ESM-LR) simulations for phase 5 of the Coupled Model Intercomparison Project under the representative concentration pathway (RCP) 2.6, RCP4.5 and RCP8.5 scenarios are considered as potential predictors. The SDMs are established in 1961–2005, validated in 2006–2012 and applied in 2013–2100. The ensemble canonical correlation (ECC) is also applied to improve projection skill. The following results are obtained: (1) The SDM projection skill for each predictor is higher than that of the MPI-ESM-LR climate model, and ECC performs even better. (2) Spatial correlation patterns of different predictors with influence on the TP are well recognized by CCA. The high relevance of ZG500 can be explained by the thermal adaptation theory, that of SST exhibits a canonical Indian Ocean Dipole mode, and MWVF850 shows a simple water vapour link. (3) The amount of summer precipitation in the TP will slightly decrease under RCP2.6 by −3.4 mm decade −1 , whereas RCP4.5 and RCP8.5 reveal an increase by 2.4 and 18.4 mm decade −1 , respectively.

Description: ABSTRACT The infrastructure design is primarily based on rainfall intensity–duration–frequency (IDF) curves, and the existing IDF curves are based on the concept of stationary extreme value theory (EVT) (i.e. the occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. Based on recent developments in the EVT, recent studies proposed a method for developing non-stationary rainfall IDF curve by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. Upon detecting a significant trend in the extreme rainfall series, directly applying the linear trend to develop non-stationary IDF curves may increase the bias of the non-stationary model. Hence, it is important to develop non-stationary GEV model which has less bias than the stationary model by modelling nonlinear trend in the series. In this study, we try to develop non-stationary GEV models with less bias by modelling nonlinear trend in the series using multi-objective genetic algorithm (MOGA). In addition, the proposed GEV model is compared with the stationary GEV model and the linear trend-based non-stationary GEV model. Furthermore, the Wilmington city and the Hyderabad city non-stationary IDF curves are developed and compared with stationary IDF curves. From the study results, it is observed that the proposed MOGA-based method is able to build the good quality and less bias non-stationary GEV models by modelling nonlinear trend in the series. In addition, it is also observed that the usage of linear trend for modelling non-stationarity in the time series sometimes increase the bias of non-stationary model.

Description: ABSTRACT Heatwaves have been linked to increased rates of human mortality and morbidity. Given these adverse health impacts, it is crucial to improve our understanding of future changes in these extreme events to inform health impacts studies and adaptation planning. While this information would be most beneficial at a local scale, Global Climate Models provide projections on much coarser resolutions. Regional Climate Models, such as those used in the New South Wales/Australian Capital Territory Regional Climate Modelling (NARCliM) project, provide simulations at a finer scale more appropriate for regional assessments. This study uses NARCliM output to investigate the ability of a Regional Climate Model ensemble to represent heatwave characteristics through the Excess Heat Factor, an index that includes factors that are known to be important to the heat-health relationship. Both uncorrected and bias-corrected model output is evaluated against observationally-derived heatwave characteristics for the period 1990–2009. The effect of bias-correction on future changes in heatwave characteristics is also assessed. Overall, the simulations provided a good representation of the recent climate and bias-correction did not greatly change simulated heatwave characteristics. Some regions were more affected by bias-correction than others, with bias-correction being most beneficial for coastal regions. We emphasise that these results may not apply to all indices measuring extreme heat, and demonstrate that results for an index based on a fixed absolute temperature threshold are substantially affected when bias-correction is applied. While supporting bias-correction, this study demonstrates that it is not necessarily required when evaluating a relative measure such as the Excess Heat Factor.

Description: ABSTRACT Developing high-quality long-term data sets at uniform space–time resolution is essential for improved climate studies. This article processes the outputs from two global and regional climate models, the Community Climate System Model (CCSM3) and the Regional Climate Model driven by the Hadley Centre Coupled Model (RegCM3). The results are bias-corrected time series of atmospheric variables corresponding to Intergovernmental Panel on Climate Change (IPCC's) historical (20C3M) and future (A2) climate scenarios over the Amazon Basin. We use a series of simple but effective interpolation approaches to produce hourly climate data sets at 1° by 1° grid cells. A quantile-based mapping approach is used to reduce the biases of temperature and precipitation in CCSM3 and RegCM3. Adjustments are also made on specific humidity and downwelling longwave radiation to avoid inconsistency between those variables and bias-corrected temperature values. We also interpolated an already bias-corrected Parallel Climate Model data set (PCM1) from 3-hourly to the hourly resolution. The final climate data sets can be used as forcing of ecosystem and hydrologic models to study climate changes and impact assessments over the Amazon Basin.

Description: ABSTRACT For over three decades, Iraq has suffered from climate variability and desertification. Rainfall rates have decreased with abnormal high-temperature degrees, recurrence of dust storms has been increasing and many agricultural areas have turned into barren land. In this article, to study these climatic variations and detect important climate indices in Iraq, ten indices (total rainfall, average temperature, maximum temperature, minimum temperature, number of days of dust rising, number of days of dust storm, relative humidity, atmospheric pressure at sea surface level, total evaporation and wind speed) were investigated at 24 meteorological stations in Iraq for 30 years. January in winter, July in summer and annual rates of climate indices were analysed through a factor analysis method. As a result, total rainfall, minimum, maximum and average temperature were found as the strongest indices of the two seasons in Iraq. However, in the annual rates, the total rainfall indicator ranked last in the second component of the factor analysis. The contour lines for the factors of rainfall and maximum temperature offered a clear guide to patterns of the characteristics in winter, summer and annual rates. The northern regions were characterized by high values of rainfall in winter in comparison to the central and southern parts of Iraq. However, high temperatures were found in Baghdad and the southern regions in summer, which showed more than 45 °C.

Description: ABSTRACT Sea surface temperature (SST) is an important oceanic variable that impacts regional and global climate. This paper examines the relation of summer (June to August) surface air temperature (SAT) variability over Saudi Arabia (1948–2013) with SST over the Atlantic, Pacific and Indian Oceans. The SAT over Saudi Arabia shows an abrupt increase around the 1980s (i.e. 1986). Partial correlations between SAT and different SST indices indicate that the Indo-Pacific warm pool (IPWP) has a more significant effect on SAT than does the tropical North Atlantic (TNA), tropical South Atlantic (TSA) or Western Hemisphere warm pool (WHWP). Hence, the change in IPWP SST can be considered as one of the factors linked to increase SAT over Saudi Arabia. The only significant relationship between El Niño and SAT is found in the Niño 4 region. Moreover, interactions between the tropical Atlantic meridional gradient mode and SAT are undetectable in the summer season, indicating that the TNA and TSA may have effectively independent roles on SAT over Saudi Arabia. The tropical Atlantic, through TNA and TSA, may influence the IPWP SST which modifies the strength of the Indian monsoon low, and in turn, has a strong influence on Saudi Arabia SAT variability.

Description: Remote sensing has shown an immense capability for large-scale estimation of air temperature ( T air ), one of the most important environmental state variables, using land surface temperature ( LST ) data. Following recent investigations on the T air –LST relationship, in this article, we propose an advanced statistical approach to this realm. We tested the approach for estimation of T air in eastern part of Iran using MODIS daytime and nighttime LST products and 11 auxiliary variables including Julian day, solar zenith angle, extraterrestrial solar radiation, latitude, altitude, reflectance at various visible and infrared bands and vegetation indices. Fourteen statistical models constructed through a stepwise regression analysis were evaluated along a 5-year period (2000–2004) using MODIS and meteorological station data. Results of this study indicated that the statistical approach performed reasonably well, where our final proposed model could estimate average T air with validation mean absolute error of 2.3 and 1.8 °C at daily and weekly scales, respectively. Nighttime LST , Julian day, altitude and solar zenith angle indicated to be the most effective variables capturing most variations of T air in the study region. Variables influenced by land surface and land cover properties including reflectance at different bands and vegetation indices showed a negligible effect on the T air -LST relationship within the study area. It was indicated that the proposed models generally performed better for lower altitude regions.

Description: ABSTRACT In this study, fast climate system responses to CO 2 , aerosols and sulfate aerosols are studied based on simulations of Coupled Model Inter-comparison Project Phase 5 (CMIP5) atmospheric models. We demonstrate that the fast climate adjustments caused by CO 2 forcing lead to decreases in global annual mean cloud fractions, evaporation and precipitation and to increases in the global annual mean net radiative forcing and atmospheric water vapour content. The inhibition of rainfall is primarily caused by the reduced oceanic precipitation. Regionally, Africa, South Asia, East Asia and Australia exhibit pronounced increases in rainfall, which are presumably attributed to the strengthened summer monsoon caused by the increased land–sea thermal contrast. Aerosols and sulfate aerosols exhibit only a slight effect on the global hydrological cycle before global surface temperature changes. However, by affecting the land–sea thermal contrast, they can have profound effects on regional-scale hydrological cycles, such as those over southern Africa, South Asia and East Asia in the boreal summer. Moreover, the cloud fast feedback under the aerosol forcing is highly associated with the way of dealing with aerosols in the atmospheric model.

Description: ABSTRACT The teleconnections of different types of El Niño Southern Oscillation (ENSO) to the Indian summer monsoon are investigated in observations and models. We find that, not all regions in India are strongly affected by ENSO, so we focus on two regional teleconnections: (1) a negative rainfall signal around central north east (CNE) India and ‘hilly’ region during El Niño (and vice versa for La Niña) and (2) similar signal for parts of southern peninsular region. Using correlations, it is found that 〉50% of the fifth phase of the Coupled Model Inter-comparison Project models capture these two regional teleconnections, with first captured by 〉80% of models. Furthermore, using a compositing technique that may better capture asymmetries in response to warm and cold events, the authors find that most models again agree on the sign of regional teleconnection around the CNE and hilly region, suggesting the robustness of ENSO signal in that region. The peninsular teleconnection is less well simulated in models. We find a clear connection between the Walker circulation and Indian summer monsoon rainfall around central India in models.

Description: ABSTRACT Measurements of global radiation E g made in the first half of the 20th century are reviewed. The thermoelectric pyranometers used to measure E g in the United States, Western Europe and Russia are described and the published sources of data available up to and including the 1957 International Geophysical Year are documented together with the few analyses of this data which have been reported. Two 100-year-long series measured at Potsdam, Germany and Washington, DC in the United States are presented to illustrate the potential value of the early measurements in understanding the changes in E g which have occurred in the last 60 years.

Description: ABSTRACT Regional climate models (RCMs) include both terrestrial and atmospheric compartments and thereby allow studying land–atmosphere feedback, in particular, the impact of land-use land cover driven by biogeophysical processes on regional climate. In this study, a method is developed to separate the signals from the noise in RCM simulations of the effects of changes in land use, using perturbed initial boundary conditions (PICs). We want to know how many ensemble members are required to identify robust and statistically significant land-use land cover change (LULCC) effects from RCM LULCC studies. The method is applied to a case study of urbanization and deforestation, for which LULCC scenarios are implemented in the RCM Weather Research and Forecasting (WRF). Based on WRF ensemble simulations with PICs for 2010, the signal-to-noise ratio (SNR) is used to identify areas with pronounced effect of an LULCC or, rather, the parametrization of the land-use classes. While in the urbanization scenarios clear and statistically significant signals are found for air temperature and for both latent- and sensible heat (SNR values up to 24), the effects are less pronounced for precipitation, and for deforestation in general (SNR values 〈 1). For the case study of urbanization and precipitation, the impact of the ensemble size is studied in order to derive robust conclusions about the effects of LULCC on precipitation. We conclude that single RCM realizations of different land-use representations are not sufficient to derive LULCCinduced signals, particularly not for precipitation. Small ensemble sizes led to concluding there were significant LULCC-induced precipitation signals, but these disappeared when the ensemble size was increased. Our regional analysis suggests the need for ensemble sizes well above 10 for precipitation.

Description: ABSTRACT From a local point of view, in May/June, there is an important and positive 2 m temperature trend at Palma (Mallorca), which is simultaneous and highly correlated with a strong increase in the 500 hPa geopotential height. This study analyses this fact as well as the observed tendencies in a wider seasonal and geographical context. We confirm the particularly high correlation between 2 m temperature and 500 hPa geopotential during the warm months as opposed to the much weaker correlation in winter. This suggests that mechanisms for thermal changes act differently throughout the year in this region. Besides the direct radiative effect, warm season near-surface temperatures are linked to the presence of deep anticyclones, which effectively determine the northern edge of the Hadley cell. Accordingly, the strong warming trend in the area of Palma during the warm months of the year is purportedly related to the poleward extension of the Hadley cell. The fact that May/June shows the highest low-level temperature trend among all bi-monthly series is a common regional feature over a relatively wide area over the Western Mediterranean. Different geographical patterns emerge in other periods of the year. In July/August, the strongest low-level warming area drifts to the east-northeast, towards Ukraine and Russia. Coincidentally, the 500 hPa geopotential tendencies show a coherent pattern, with an intense positive trend ridge over the Western Mediterranean area in May/June, and a displacement of this ridge to the north-east in July/August. We show the connection between 500 hPa geopotential height and near-surface temperature by means of a multiple lineal regression that attributes half of the local temperature tendency in Palma to the intensification of a 500 hPa ridge centred over the Western Mediterranean and surroundings.

Description: ABSTRACT Typhoon is usually one of main reasons to damage the buildings, infrastructures, water operations, and human life in summer in East Asia, which includes China, Japan, and Korea. Typhoons can be considered multivariate extremes that consists of climate variables that affect wind and precipitation. Copula models can be used to investigate the dependence between random variables. In this study, we used copula models to investigate the optimal marginal distribution for the relations between the wind speed and the precipitation of typhoons at the Jeju weather station in South Korea. We used the 10-min average wind speed (W10) and the total precipitation (PT) from 65 typhoon events that had affected the Jeju station. Two case studies were considered using the typhoon data. Case one included all typhoon events, and case two included 39 typhoon events with the following thresholds: W10 ≥ 10 m s −1 and PT ≥ 50 mm. The marginal distributions for the copula models included the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Weibull (WBU) distributions as well as three copula models: Clayton, Frank, and Gumbel copulas. Each step was checked by the robust diagnostic, the probability plot correlation coefficient (PPCC) test, and the goodness-of-fit test ( S n statistic). The Frank copula model with GLO (W10) – GPA (PT) had the best performance in both cases. The results of this study present the key steps needed to identify an optimum copula for a bivariate distribution in applications related to atmospheric sciences and provides an example of how this applies to wind velocity and precipitation from typhoons.

Description: ABSTRACT Using station data from the United States Historical Climatology Network, we preformed a running trend analysis of temperature, precipitation and drought in the Alabama–Coosa–Tallapoosa and Apalachicola–Chattahoochee–Flint river basins for the time period 1895–2012 on annual and monthly timescales. Our study found that long-term precipitation and temperature trends were statistically detectible but relatively slight in the order of an increase at 3 mm per decade for precipitation and a decline of 0.02 °C per decade for temperature. Running trend analyses for the time period 1895–2012 found field-significant and relatively large annual precipitation increases and temperature decreases between the 1950s and early 1980s associated with the 'warming hole'. The magnitude of precipitation trends for the aforementioned period was in the range of 7 mm per year for precipitation and 0.6 °C per decade for temperature. For temperature, we observed generally decreasing maximum, minimum and mean temperatures in the 1960s and 1970s and increasing temperatures from the 1970s to present. Minimum temperatures particularly showed a strong increase in recent summer months in the range of 0.3 °C per decade. Trends in the diurnal temperature range showed a recent narrowing during summer and fall months. Differences in the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) did not show a strong effect of temperature on drought for this region.

Description: ABSTRACT ‘Tipping points’ (TPs) are thresholds of potentially disproportionate changes in the Earth's climate system associated with future global warming and are considered today as a ‘hot’ topic in environmental sciences. In this study, TP interactions are analysed from an integrated and conceptual point of view using two qualitative Boolean models built on graph grammars. They allow an accurate study of the node TP interactions previously identified by expert elicitation and take into account a range of various large-scale climate processes potentially able to trigger, alone or jointly, instability in the global climate. Our findings show that, contrary to commonly held beliefs, far from causing runaway changes in the Earth's climate, such as self-acceleration due to additive positive feedbacks, successive perturbations might actually lead to its stabilization. A more comprehensive model defined TPs as interactions between nine (non-exhaustive) large-scale subsystems of the Earth's climate, highlighting the enhanced sensitivity to the triggering of the disintegration of the west Antarctic ice sheet. We are claiming that today, it is extremely difficult to guess the fate of the global climate system as TP sensitivity depends strongly on the definition of the model. Finally, we demonstrate the stronger effect of decreasing rules (i.e. mitigating connected TPs) over other rule types, thus suggesting the critical role of possible ‘stabilizing points’ that are yet to be identified and studied.

Description: ABSTRACT Spatiotemporal variations of extreme precipitation regimes are both caused by the climate change and the natural climate variability. The trends of extreme precipitation indices as an issue of climate change and the possible teleconnection with the ocean–atmospheric modes as an issue of natural climatic variability have been analysed in China. Ten extreme precipitation indices have been used in this study, and the station-based extreme precipitation indices were gridded into 1°latitude × 1°longitude using the angular distance weighting method. For extreme precipitation, an index is more likely influenced by the local topography if it represents the more extreme precipitation and then the regional response of this index to climate changes is more complex. Results of the trends of extreme precipitation indices indicated that three zones can be generally identified in China, namely: (1) a significant drying tendency can be confirmed along the strip stretching in the northeast and southwest direction; (2) northwest China is dominated by a wetting tendency and slight increase of precipitation intensity; and (3) southeast China exhibits a slight wetting tendency but significant intensifying precipitation. The wetting tendency in northwest China may be caused by increasing precipitation during November, December, January, and February. Besides, the teleconnections between precipitation extremes and El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) were also analyzed, and results showed that the regional responses of precipitation extremes to ENSO, IOD, NAO, and PDO varied for the climate indices at different stages, such as the precipitation extremes generally tend to be decreasing in the central part of China at the same year of positive ENSO while increasing in the east part of China a year after the positive ENSO. This study provides insights into regional response of weather extremes to global climate indices in China, and these are valuable for developing measures to mitigate the hazards due to weather extremes.

Description: ABSTRACT A decadal change on relationship between winter rainfall over Southern China (SCWR) and Western Pacific warm pool heat content (WPHC) was detected by a sliding correlation analysis. The decadal turning point occurred around 1993. Before 1993, the relationship between SCWR and WPHC was quite weak with a correlation coefficient of −0.17. During this epoch, the WPHC-related anomalous troposphere circulation, sea surface temperature (SSTA) and outgoing longwave radiation (OLRA) were mainly confined to the Pacific Ocean. Therefore, the corresponding climate system anomalies cannot influence SCWR. However, after 1993, the relationship between SCWR and WPHC became significant and reached a correlation coefficient of −0.81. The troposphere circulation anomalies along with the SSTA and OLRA pattern that were associated with WPHC during this epoch significantly shifted northwestward and intensified, resulting in a direct impact on SCWR. A possible mechanism was put forth to explain the decadal enhanced relation between SCWR and WPHC. In the context of the increased and northwestward-shifted climatological maximum WPHC, the concurrent intensified and northwestward-shifted SST and atmospheric circulation anomaly pattern contributes to the decadal enhanced relation between SCWR and WPHC. On one hand, because of the increased and northwestward-shifted maximum sea surface temperature, the convection became more sensitive to the SSTA over Indian Ocean and Maritime Continent, thus dragged the Philippines anticyclonic/cyclonic anomaly northwestward via Kevin wave and Rossby wave response, which can directly affect SCWR. On the other hand, the increased and northwestward-shifted SSTA anchored the convection anomalies in South China Sea (SCS) and Maritime Continent, impacting the SCWR via anomalous descending/ascending motion of the anomalous local meridional cell.

Description: ABSTRACT The precipitation regime over the Mediterranean basin is investigated for the period 1979–2010 using monthly mean satellite data from the Global Precipitation Climatology Project (GPCPv2). The results show that a clear contrast exists between the more rainy northern part of the study region (Southern Europe) and the drier southern area (North Africa, Iberian Peninsula) and between the western sides (rainsides) of the Iberian, Italian and Balkan peninsulas and their eastern sides (rainshadows). The mean annual precipitation averaged over the study area is P = 593 ± 203 mm year −1 , but it has a strong spatial variability ranging from 20 mm year −1 (North Africa) to 1500 mm year −1 (Alps). A significant seasonal variability exists, with the early winter and late autumn months (November and December) being the wettest with precipitation amounts larger than 60 mm month −1 . The GPCPv2 satellite precipitation data are satisfactorily correlated with rain gauge measurements from 433 stations within the study area (correlation coefficient R = 0.78 for all stations on a yearly basis, with values ranging between 0.72 and 0.82, depending on the season) with a slight overestimation. They also compare well with the higher spatial and temporal resolution Tropical Rainfall Measuring Mission (TRMM) data, which supports the validity of the present study.

Description: ABSTRACT The East Asia/Pacific (EAP) teleconnection can substantially modulate weather anomalies over eastern Asia during summer. Wavelet analyses, including ensemble mean power spectrum and accumulated frequency of significant components, highlight 10–30-day oscillations in the EAP index. The influences of these low-frequency oscillations on weather anomalies are further investigated via both phase-dependent and lead-lag composites. On 10–30-day scales, a tripole structure of precipitation anomalies and a temperature seesaw form concurrently over adjacent regions along eastern Asia. These anomalies last for about 1 week, constituting anomalous weather spells with possible extreme values around the peak/valley phases. For cold spells over Northeast Asia during positive phases, the low-frequency easterly is the determinant factor. On one hand, it advects cold air from the sea east of the land. On the other hand, it conveys moisture to form low-based clouds, which are effective in inhibiting incoming solar radiation. While, for cold spells over central-eastern Siberia during negative phases, regional-scale precipitation and cold advections conveyed by anomalous northerlies combine to make contributions. Both hot spells over central-eastern Siberia/Northeast Asia during positive/negative phases mainly result from the adiabatic heating and increasing solar radiation, both of which are attributed to strong descent in response to upper-level convergences. In addition to great intensity, the high-impact property of these simultaneous weather anomalies also arises from their long duration and large spatial extent. By taking advantages of the quasi-periodicity of the 10–30-day oscillations, better predictions of these simultaneous weather anomalies/extremes would be anticipated.

Description: ABSTRACT Optimal tropical ocean regions for forcing precipitation changes over Australia are identified from maps of sensitivity of Australian precipitation to tropical sea surface temperature (SST) anomalies. These sensitivity maps are derived by a series of atmospheric general circulation model simulations with prescription of an array of SST anomaly patches over the tropics. The results show that the Australian precipitation changes are most sensitive to SST anomalies over the Indo-Pacific Warm Pool. There are competing opposing sensitivities such that warming over the Indian side of the Warm Pool increases precipitation, whereas that over the Pacific side decreases it. These sensitivity maps are validated by use in reconstruction of historical series of Australian precipitation with realistic interannual variability. The present results imply that monitoring and predicting the signs and magnitudes of SST anomalies over the critical Indo-Pacific Warm Pool may improve the prediction skills of Australian precipitation changes.

Description: ABSTRACT Aerosol trends and rates of change were analysed between 2003 and 2013, over both land and ocean, using MODerate resolution Imaging Spectroradiometer (MODIS) monthly aerosol optical thickness (AOT) products (MYD08). Unlike previous research, the ensemble empirical mode decomposition (EEMD) was implemented in this study. Results show that sustained positive or negative trends are globally observed in most areas during the study period. However, increasing rates were decelerated and even became downward trends over western North America, central South America, East China Sea and southeastern China. Comparing EEMD results with linear regression, it is evident that the increasing and decreasing rates from the EEMD method are much stronger. Zonally averaged trends clearly indicate an opposite trend between the southern and northern hemispheres. In addition, this study demonstrates that linear regression may not fit trends statistically in some areas, such as central South America and part of the Indian Ocean. Around 32.74% (12 816) of pixels exhibit low correlation ( r 2  = 0.5) between linear and nonlinear trends from EEMD. Approximately 12.46% (4877), 6.56% (2567) and 1.85% (724) of pixels experience significant variations against the F -test, autoregressive process of the first-order for EEMD and linear regression, respectively. The rates of change observed in this study can be used in analysing the long-term effects of aerosols on climate change and earth's radiative budget.

Description: ABSTRACT We examine secular changes and multidecadal climate variability on a seasonal scale in northern France over the last 500 years and examine the extent to which they are driven by large-scale atmospheric variability. Multiscale trend analysis and segmentation procedures show statistically significant increases of winter and spring precipitation amounts in Paris since the end of the 19th century. This changes the seasonal precipitation distribution from one with a pronounced summer peak at the end of the Little Ice Age to an almost uniform distribution in the 20th century. This switch is linked to an early warming trend in winter temperature. Changes in spring precipitation are also correlated with winter precipitation for time scales greater than 50 years, which suggests a seasonal persistence. Hydrological modelling results show similar rising trends in river flow for the Seine at Paris. However, such secular trends in the seasonal climatic conditions over northern France are substantially modulated by irregular multidecadal (50–80 years) fluctuations. Furthermore, since the end of the 19th century, we find an increasing variance in multidecadal hydroclimatic winter and spring, and this coincides with an increase in the multidecadal North Atlantic Oscillation (NAO) variability, suggesting a significant influence of large-scale atmospheric circulation patterns. However, multidecadal NAO variability has decreased in summer. Using Empirical Orthogonal Function analysis, we detect multidecadal North Atlantic sea-level pressure anomalies, which are significantly linked to the NAO during the Modern period. In particular, a south-eastward (south-westward) shift of the Icelandic Low (Azores High) drives substantial multidecadal changes in spring. Wetter springs are likely to be driven by potential changes in moisture advection from the Atlantic, in response to northward shifts of North Atlantic storm tracks over European regions, linked to periods of positive NAO. Similar, but smaller, changes in rainfall are observed in winter.

Description: ABSTRACT The limited historical observational sampling of the ocean gives rise to uncertainty in time series of global ocean temperature anomalies calculated from those observations. Without knowledge of the true global state of the oceans, it is difficult to characterize the errors caused by these sampling issues. One way to quantify them is to use climate model data. Pseudo observational time series can be constructed from the model data using knowledge of where observations occurred. Comparison of these with time series constructed from the full model fields yields information about how observational sampling impacts time series of the temperature change in the modelled world. This can then be related back to the time series generated from the real observations. In this study, climate model data were used to investigate sampling errors in 0–700 m global average ocean temperature anomaly time series calculated using a straightforward gridding approach. The sampling had two impacts. First, sampling causes issues with constructing a climatology that is representative of the long-term average state of the ocean. Climatology errors were shown to have the potential to cause systematically changing errors in anomaly time series. Second, some regions of the ocean were poorly observed prior to improvements brought about by the Argo project. This was found to cause spurious variability, both year to year and over multi-year time scales. The latter had similar magnitude to the actual multi-year variability seen in the model data but was smaller than the model's long-term temperature change. The features of these errors depend on the ocean state and therefore varied between climate model runs. More sophisticated methods used to calculate ocean temperature time series are expected to be less impacted by sampling. Nevertheless, sampling errors will still occur and therefore this type of study is recommended even for those techniques.

Description: ABSTRACT Within the scope of the two major international projects of long-term reanalysis for the 20th century coordinated by the National Oceanic and Atmospheric Administration and European Centre for Medium-Range Weather Forecasts, the Instituto Dom Luiz from the University of Lisbon has digitized a large number of long-term daily and monthly climate records from stations in Portugal and former Portuguese colonies. We have recently finished the digitization of precipitation values from Ponta Delgada (capital of the Azores Archipelago), obtaining an almost complete daily precipitation series, with the exception of some years (1864–1872; 1878–1879; 1888–1905; 1931; 1936; and 1938) for which only monthly values are available. At daily resolution, we have used a comprehensive assessment on different characteristics of rain spells (consecutive days with rainfall accumulation). The distribution of precipitation presents an evident seasonal pattern and reveals large inter-annual and intra-annual variability, increasing considerably in the last 3 decades. The frequency of dry years decreases almost by half between the first and the second part of the record, whereas wet years increase up to three times. This is mainly due to more intense events that are reflected by higher rain-spell yields (amount of precipitation) and rain-spell intensity (amount of precipitation per day) values. Most of the extreme precipitation events occurred during the last 2 decades, and they generally correspond to dates with cyclonic conditions over the North Atlantic. We have also looked into the influence of large-scale modes of climate variability on the precipitation regime of the Azores Archipelago. As expected, theNorth Atlantic Oscillation (NAO) has a major impact on the precipitation regime of Ponta Delgada both in winter and summer. However, our results show a non-stationary NAO influence and the impact of other large-scale modes (including the Atlantic Multidecadal Oscillation and El Niño-Southern Oscillation) increases when this influence becomes weaker.

Description: ABSTRACT This study investigates the interannual variation of heat wave frequency (HWF) in South Korea during the past 42 years (1973–2014) and examines its connection with large-scale atmospheric circulation changes. Korean heat waves tend to develop most frequently in late summer during July and August. The leading Empirical Orthogonal Function accounting for 50% of the total variance shows a mono-signed pattern over South Korea, suggesting that the dominant mechanisms responsible for the heat wave are linked in a spatial scale much larger than the nation. It also exhibits a regional variation with more occurrences in the southeastern inland area. The regression of the leading principal component (PC) time series of HWF with large-scale atmospheric circulation identifies a north–south dipole pattern between the South China Sea and Northeast Asia. When this large-scale circulation mode facilitates deep convection in South China Sea, it tends to weaken moisture transport from the South China Sea to Northeast Asia. Enhanced deep convection in the South China Sea triggers a source of Rossby wave train along southerly wind that generates positive geopotential height anomalies around Korea. The anomalous high pressure pattern is accompanied by large-scale subsidence in Korea, thereby providing a favourable condition for extreme hot and dry days in Korea. This study highlights that there is a decadal change of the relationship between Korean heat waves and large-scale atmospheric circulation patterns. The tropical forcing tends to be weakened in the recent decade, with more influences from the Arctic variability from the mid-1990s.

Description: ABSTRACT We highlight improvements to the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) in the latest Release 3.0 (R3.0; covering 1662–2014). ICOADS is the most widely used freely available collection of surface marine observations, providing data for the construction of gridded analyses of sea surface temperature, estimates of air–sea interaction and other meteorological variables. ICOADS observations are assimilated into all major atmospheric, oceanic and coupled reanalyses, further widening its impact. R3.0 therefore includes changes designed to enable effective exchange of information describing data quality between ICOADS, reanalysis centres, data set developers, scientists and the public. These user-driven innovations include the assignment of a unique identifier ( UID ) to each marine report – to enable tracing of observations, linking with reports and improved data sharing. Other revisions and extensions of the ICOADS' International Maritime Meteorological Archive common data format incorporate new near-surface oceanographic data elements and cloud parameters. Many new input data sources have been assembled, and updates and improvements to existing data sources, or removal of erroneous data, made. Coupled with enhanced ‘preliminary’ monthly data and product extensions past 2014, R3.0 provides improved support of climate assessment and monitoring, reanalyses and near-real-time applications.

Description: ABSTRACT Snow cover presence, duration, properties, and water amount play a major role in Earth's climate system through its impact on the surface energy budget. Snow cover conditions and trends (1979–2014) were simulated for South America – for the entire Andes Cordillera. Recent data sets and SnowModel developments allow relatively high-resolutions of 3-h time step and 4-km horizontal grid increment for this domain. US Geological Survey's Global Multi-resolution Terrain Elevation Data 2010 topography, Global Land Cover (GlobCover), Randolph Glacier Inventory (v. 4.0) glacier, and NASA modern-era retrospective analysis for research and applications data sets were used to simulate first-order atmospheric forcing (e.g. near-surface air temperature and precipitation, including the fraction of precipitation falling as snow) and terrestrial snow characteristics (e.g. snow cover days, snow water equivalent depth, and snow density). Simulated snow conditions were verified against moderate-resolution imaging spectroradiometer-derived snow cover extent and 3064 individual direct observations of snow depths. Regional variability in mean annual air temperature occurred: positive trends in general were seen in the high Andes Cordillera, and negative trends at relatively lower elevations both east and west of the Cordillera. Snow precipitation showed more heterogeneous patterns than air temperature due to the influence from atmospheric conditions, topography, and orography. Overall, for the Cordillera, much of the area north of 23°S had a decrease in the number of snow cover days, while the southern half experienced the opposite. The snow cover extent changed ∼−15% during the simulation period, mostly between the elevations of ∼3000 and 5000 m above sea level (a.s.l.). However, below 1000 m a.s.l. (in Patagonia) the snow cover extent increased. The snow properties varied over short distances both along and across the Andes Cordillera.

Description: ABSTRACT The impacts of the Madden-Julian oscillation (MJO) on precipitation over Northeast Brazil (NEB, also known as Nordeste) are evaluated based on daily raingauge data from 492 stations over 30-year period (1981–2010). Composites of precipitation, outgoing longwave radiation and moisture-flux anomalies are performed for each phase of the MJO, and over all four seasons, based on the Jones–Carvalho MJO index. To distinguish the MJO signal from other patterns of climate variability, daily data are filtered using a 20–90 day band-pass filter; only days classified as MJO events are considered in the composites. The results show strong seasonality of the MJO's impact on precipitation. The most spatially coherent signals of precipitation anomalies occur in the austral summer, when about 80% of the raingauge stations showed increased precipitation in phases 1–2 and suppressed precipitation in phases 5–6 of the oscillation. Although the MJO impacts precipitation on intraseasonal timescales in all seasons in most locations, these impacts vary in magnitude and depend on the phase of the oscillation. Precipitation anomalies over NEB are explained by the interaction of convectively coupled Kelvin-Rossby waves with the dominant climatic features in each season. During the austral summer and spring, westerly regimes increase precipitation over most NEB. In the austral winter and fall, precipitation anomalies exhibit more complex spatial variability. In these seasons, precipitation anomalies in coastal areas depend on the strength of the South Atlantic anticyclone, which is largely modulated by Rossby waves. The strengthening of the anticyclone intensifies the convergence of the trade winds in coastal areas and precipitation windward of the coastal range. Conversely, the intensification of the subsidence is responsible for precipitation deficits in the lee side of the range. These conditions are typically observed when easterly regimes dominate over tropical South America and NEB decreasing moisture flow from the Amazon.

Description: ABSTRACT The Advanced Research version of Weather Research and Forecasting (WRF-ARW) model was used to generate a downscaled, 10-km resolution regional climate dataset over the Red Sea and adjacent region. The model simulations are performed based on two, two-way nested domains of 30- and 10-km resolutions assimilating all conventional observations using a cyclic three-dimensional variational approach over an initial 12-h period. The improved initial conditions are then used to generate regional climate products for the following 24 h. We combined the resulting daily 24-h datasets to construct a 15-year Red Sea atmospheric downscaled product from 2000 to 2014. This 15-year downscaled dataset is evaluated via comparisons with various in situ and gridded datasets. Our analysis indicates that the assimilated model successfully reproduced the spatial and temporal variability of temperature, wind, rainfall, relative humidity and sea level pressure over the Red Sea region. The model also efficiently simulated the seasonal and monthly variability of wind patterns, the Red Sea Convergence Zone and associated rainfall. Our results suggest that dynamical downscaling and assimilation of available observations improve the representation of regional atmospheric features over the Red Sea compared to global analysis data from the National Centers for Environmental Prediction. We use the dataset to describe the atmospheric climatic conditions over the Red Sea region.

Description: ABSTRACT Long-term time series of climatological data measured at meteorological stations provide one of the most authentic annals of climate in the past. However, there are a host of factors that affect measurements of climate parameters and make the data unsuitable for direct use and analysis. Serial completion and homogenization thus have to be undertaken in order to draw valid conclusions about the climate, or to apply the time series in impact studies. This study reports on gap filling and homogenization results of climatological elements in the headwater region of the Upper Blue Nile Basin from 1980 to 2013. Firstly, approaches for reconstruction of the time series from neighboring stations using different techniques were compared and selected. Neighboring stations were selected based on horizontal distance and coefficient of correlation. Secondly, the reconstructed time series were homogenized using Multiple Analysis of Series for Homogenization (MASH). The results show improved spatial coherence of the final data series. Higher spatial coherence was revealed for maximum temperature than for minimum temperature and rainfall. For rainfall and minimum and maximum temperatures, the coefficient of correlation weighting method outperforms other candidate methods, such as the normal ratio method (NRM), the modified NRM, and the inverse distance weighting method. Rainfall series for half of the stations considered were found to be homogeneous, and thus inhomogeneity corrections were not applied. Inhomogeneity in the remaining stations either underestimates or overestimates annual rainfall series. All stations revealed inhomogeneity in the mean annual maximum and minimum temperature series. These serially complete and homogenized data on rainfall, and minimum and maximum temperatures of the present study can be used for climate change and hydrological studies in the basin.

Description: ABSTRACT In this article, we presented a variety of modelling approaches for the El Niño Southern Oscillation (ENSO) time series data trying to capture two features that are present in the data, in particular the persistence and the seasonal structure. For this purpose, we use long memory models based on fractional integration. The results indicate that the four ENSO series examined (El Niño 1–2; El Niño 3, El Niño 4 and El Niño 3.4) can be described in terms of a seasonal I ( d ) model with an order of integration higher than 0 and smaller than 1 in all four cases. The lowest degree of persistence is found in the series corresponding to El Niño 1.2, with an order of seasonal integration of 0.39. This seasonal fractional differencing parameter, however, is found to be higher than 0.5 (and thus non-stationary) for the remaining three series.

Description: ABSTRACT Spatial patterns of rainfall in Hawai‘i are among the most diverse in the world. As the global climate warms, it is important to understand observed rainfall variations to provide context for future changes. This is especially important for isolated oceanic islands where freshwater resources are limited, and understanding the potential impacts of climate change on the supply of freshwater is critical. Utilizing a high-resolution gridded data set of monthly and annual rainfall for Hawai‘i from January 1920 to December 2012, seasonal and annual trends were calculated for every 250-m pixel across the state and mapped to produce spatially continuous trend maps. To assess the stability of these trends, a running trend analysis was performed on 34 selected stations. From 1920 to 2012, over 90% of the state experienced drying trends, with Hawai‘i Island, and in particular the western part of the island, experiencing the largest significant long-term declines in annual and dry season rainfall. The running trend analysis highlighted the multi-decadal variability present in these trends, and revealed that the only region in the state with persistent annual and dry season trends through the study period is the western part of Hawai‘i Island; for most other regions, the drying trends were not significant until the most recent part of the record was included. These results support previous studies that indicate drying across the state over recent decades, and reveal the timing of upward and downward trends as well as important spatial details for natural resource management in Hawai‘i.

Description: ABSTRACT In this study, simulations over Southeast Asia (15°S–40°N, 80°–145°E) at 36 km resolution were conducted for the period 1989–2007 using the Regional Climate Model version 4.3 (RegCM4.3) under the framework of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (or SEACLID/CORDEX-SEA) project. Forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), 18 experiments were carried out using different combinations of cumulus parameterization and ocean flux schemes. Twelve extreme indices for both rainfall and temperature were estimated from the model output. A statistical omega index was used to measure the degree of similarity among the 18 experiments in phase and shape. The results showed relatively high similarities among the experiments over mainland Asia compared to those over the Maritime Continent for both seasonal and inter-annual variability. The extreme rainfall indices had a lower omega compared to that of temperature. Observed daily rainfall and temperature data at 52 meteorological stations over the SEA region were used to validate the simulated extreme indices. The results showed that extreme temperature indices were generally underestimated across the region. Systematic biases for each simulated rainfall index were also identified. A score ranking system was established to compare the relative performance of the 18 experiments over the 52 selected stations objectively. It was shown that the experiments with the Massachusetts Institute of Technology (MIT)-Emanuel scheme performed relatively better than the other convective schemes. The combination of the MIT-Emanuel convective scheme with the Biosphere–Atmosphere Transfer scheme (BATS1e) ocean flux scheme produced the best performance.

Description: ABSTRACT The Berkeley Earth surface temperature (BERK) project provides gridded global temperature anomaly products using an automated geostatistical approach to adjust station data for systematic biases. Despite its widespread usage, the BERK data set has not been evaluated at the national-scale, especially in data-sparse high latitude environments. This study provides an evaluation of the BERK product across all of Canada using 333 climate stations made available from the homogenized Environment Canada station network (HTcan). Comparison between co-located monthly air temperature anomalies for the two data sets suggests small differences between the two products for mean surface (∼2 m) air temperature. However, the relatively minimal bias in mean temperature is a consequence of contrasting cold and warm biases in minimum and maximum air temperatures, respectively, that are larger but effectively even out when averaged together. The BERK product is shown to exhibit systematic underestimation of recent regional warming in northern Canada which when combined with an overestimation of warmth earlier in the record results in an observable reduction in warming rates for minimum and mean temperature anomalies since 1950. The temporal evolution and spatial pattern of the observed biases suggest that the BERK-automated adjustments to station data in northern Canada miss some inhomogeneities in the raw station data. These results highlight the need for enhanced data recovery and homogenization efforts in data-sparse high latitude regions and emphasize the importance of national-scale climate data sets for evaluating global gridded products. We also recommend caution when using the BERK minimum and maximum monthly air temperature products for long-term trend analyses.

Description: ABSTRACT In this work, we use observational and reanalysis data to demonstrate the prominent role which is played by the Kalahari Desert in the modulation of the maximum surface air temperature (SAT max ) over southern Africa during austral summer. It is not only the El Niño Southern Oscillation (ENSO) related modification of the middle and upper troposphere but the coupling to the desert surface through cloud development mechanisms which contribute immensely to the SAT max extremes. This is achieved through the convective cloud enhancement mechanisms linked to the tropical temperate troughs and suppression processes forced by the Botswana Upper High during La Niña and El Niño events, respectively. However, significant ENSO impact on the regional SAT max is restricted to the setting in of the Indian Ocean basin-wide sea surface temperature (SST) mode in December. This SST mode is unique and specifically characterizes the distinctive nature of the canonical version of the ENSO extremes. In this regard, the prominent anomalous warming and cooling of SAT max is predominantly explained by the canonical El Niño and La Niña events, respectively. On the other hand, ENSO ‘modoki’ cases appear not only to have notably reduced impacts on SAT max but have effects which are opposite in sign relative to their canonical ENSO counterparts. Therefore, factors which modulate ENSO characteristics, be they natural or anthropogenic, should have strong implications on the environment, water resource availability and societies of southern Africa.

Description: ABSTRACT Extratropical and subtropical cyclones, and their associated fronts, produce the majority of rainfall and extreme weather in the mid-latitudes around the world. In the Southern Hemisphere in particular, where observations are sparse, we have limited knowledge of their long-term variability and trends. While the long time period of the 20th Century Reanalysis (20CR) offers potential to assess longer-term changes, the lack of observational data sets makes it difficult to assess its reliability. We assess the skill of the 20CR at representing mid-latitude cyclones through a case study on the east coast of Australia. In this region, a comprehensive database has recently been developed of all severe floods between 1871 and 2012, of which 〉70% are associated with a coastal low-pressure system. Through use of the full 20CR 56-member ensemble, we are able to identify the majority of severe Australian east coast lows as early as the late 19th century, as well as recreate the cyclone tracks for some of the most severe events. The analysis shows that the full ensemble can be used for a long-term assessment of interannual variability in cyclone frequency from at least 1911, despite large inhomogeneities in the ensemble mean pressure fields.

Description: ABSTRACT Southern South America (SSA), considered as the continental region south of 20°S, has experienced significant precipitation variability and trends in the last decades. This article uses monthly quality-controlled precipitation data from rainfall stations with continuous observations during at least 100 years to quantify long-term trends as well as interannual-to-centennial variability. Several statistical methods are applied to the data, primarily to detect jumps and look for changes due to relocation of the gauge stations, as well as to identify significant trends. Most of the regions have registered an increase in annual rainfall, largely attributable to changes in the warm season. On the other hand, during winter most stations in Argentina and Brazil do not have significant trends, although eastern Patagonia registered an increase in precipitation and Chile, a marked decrease in rainfall. In order to look into the physical mechanisms behind the observed variability, the changes in mean sea level pressure and precipitable water are quantified for different sub-periods. Also explored is the variability related to the Hadley cell width and strength over the region around SSA. Results show that the Hadley cell has shrunk and shifted towards the equator in winter over the area, which has caused an enhancement of the sinking motion over much of Argentina, Chile and Brazil, while likely increasing the baroclinicity (and associated precipitation) over Patagonia. In summer, the strength of the subsidence decreased and this was associated with an increase of the low-level moisture advection, favouring more rainfall. The observational evidence presented here suggests that the zonal asymmetry in the change of the Hadley cell position over SSA could be linked to the presence of the Andes Cordillera.

Description: ABSTRACT This study develops a method for characterizing snow climatology in the Andes Mountains using the 8-day maximum binary snow cover product from the Moderate Resolution Imaging Spectroradiometer sensor. The objectives are to: (1) identify regions with similar snow patterns and (2) identify snow persistence zones within these regions. Within a study area between 8° and 39°S, snow regions are defined using the (1) minimum elevation of snow cover, (2) rate of change of snow persistence with elevation, and (3) timing of the minimum elevation snow cover. In tropical latitudes (8°–23°S), snow cover is constrained to high elevations (〉5000 m), and these areas have steep changes in snow persistence with elevation. Minimal differences in the elevation of snow on the east and west sides of the range suggest that temperature is a primary control on snow presence. Snow cover has minimal seasonal variability in the Tropics between 8° and 14°S, but it peaks in austral fall (March) after the wet season from 14° to 23°S. In mid-latitudes (south of 23°S) snowline decreases in elevation with increasing latitude, and snow persistence changes with elevation are more gradual than in tropical regions. Snow cover peaks in the austral winter throughout the mid-latitudes. Differences in elevations of snow accumulation between the east and west sides of the Andes are greatest between 28° and 37°S, where high mountain peaks produce a strong orographic effect and precipitation shadow. Within the snow regions, four snow zones are defined based on the average fraction of the year that snow persists: (1) little or no snow, (2) intermittent, (3) seasonal, and (4) permanent snow zones. Tropical latitudes have snow cover only on the highest peaks. Areas of seasonal and permanent snow zones are greatest between latitudes 28° and 37°S as a result of higher precipitation than mountains further north and higher elevations than mountains further south.

Description: ABSTRACT A synoptic climatology using mean sea level pressure and 500-hPa geopotential height composites is conducted for strong along-channel winds that occur through five of the channels dissecting British Columbia's coast. Seasonal (winter, summer) and directional (inflow, air moving from the coast inland; outflow, air moving from inland towards the coast) partitioning of the winds, results in four distinct along-channel winds that occur: summertime inflow, summertime outflow, wintertime inflow and wintertime outflow. Composite analyses using reanalysis data and in situ observations are used to examine each wind type at all locations. Wintertime composites produce patterns that are distinct from the overall winter climatology, in which outflows occur when an arctic surface high-pressure area on the inland side of the coastal mountains is accompanied by the presence of an area of low surface pressure in the northeastern Pacific. Inflow composites in the winter indicate low-pressure areas associated with mid-latitude cyclones over the Gulf of Alaska. Summertime composites are similar to the overall summer climatology; therefore, other approaches are applied to explain these winds. We analyse 104 summertime inflow events at three locations using surface analysis charts for 13 summer seasons. The analysis reveals the importance of fronts at the time of inflows, with fronts associated with almost half of the events. Non-hierarchical clustering analysis is applied for the summertime inflow events. The clustering analysis gives a better explanation of the summertime inflows than the composites. This is achieved by grouping events into different clusters, allowing for better illustration of the variance between the clusters.

Description: ABSTRACT The mean climatology, inter-model variability and spatio-temporal patterns of temperature and precipitation over West Africa from Coupled Model Intercomparison Project 5 (CMIP5), CMIP5_SUBSET [ensemble of global climate models driving COordinated Regional climate Downscaling EXperiment (CORDEX)] and CORDEX multi-model ensembles are evaluated and intercompared for the monsoon season (June–September). We find that, while CORDEX fails to outperform the simulated mean climatology of temperature by the CMIP5 ensembles, it substantially improves precipitation and provides more realistic fine-scale features tied to local topography and landuse. This improved performance over the region is found to depend more on the internal models physics than the driving boundary conditions and results from a more consistent and realistic simulation of monsoon precipitation across the various regional climate models (RCMs). Rotated empirical orthogonal function (REOF) analysis indicates that the CORDEX ensemble captures better the spatio-temporal variability of both temperature and precipitation (first REOF mode), in particular depicting the warming and Sahel precipitation recovery in recent decades over West Africa. On the other hand, the spatial patterns and associated time series of the last two REOF modes in CORDEX mostly follow the CMIP5_SUBSET pointing towards a strong role of the boundary forcing in the RCM simulation of precipitation variability.

Description: ABSTRACT Previous assessments of historical trends of measured surface temperature in South Africa have all shown a general upward trend, in both mean and extreme values, over recent decades. In addition, some regional differences in trends have been identified. Most of these studies focused on the period from about 1961 up to the last year that could be included before publication, and only climate stations situated in the same position for the entire analysis period were analysed. A data homogenization procedure enabled the combination of time series of stations from which trend analysis could be applied, extending the common analysis period for this study back to around 1931. The trend results, based on the World Meteorological Organization Expert Team on Climate Change Detection and Indices, continue to show the general warming trend shown in previous analyses, with a general increase in extreme warm events and a general decrease in extreme cold events across South Africa. The analysis of seasonal trends show that, while there are noteworthy differences on a regional basis, austral summer shows on average the strongest warming, followed by autumn, winter and spring. The central interior, which exhibited significant cooling in previous analyses, now shows non-significant or similar trends when compared to the other parts of South Africa. There is no countrywide acceleration in the warming trends, but some regional consistencies in the temporal changes in trends could be determined, i.e. increases in trends in the central interior and decreases in trends along most of the coastal region.

Description: ABSTRACT This article introduces a web-based climate information resource: an El Niño Southern Oscillation ENSO-based monthly climatology for the United States, available on AgroClimate.org . Climate variability affects land managers and decision makers in a variety of ways. The ENSO is one of the leading drivers of seasonal and year-to-year climate variability. Understanding the historical rainfall and temperature anomalies associated with ENSO can be an important way for decision makers to learn how they might anticipate climate variability. We used the ENSO record from 1950 to 2013 to develop an ENSO-specific climatology. This allows decision makers to pinpoint the combinations of location and month in which there are substantial ENSO-associated rainfall or temperature anomalies. Learning about the timing of historical ENSO-driven climate impacts can be an important first step for decision makers to develop management adjustments that could make the most positive outcomes based on the available climate information.

Description: ABSTRACT This investigation encompasses the first presentation of the log-board , which was the primary source used to compile logbooks on board Royal Navy vessels in the 18th century. All wind force and weather descriptions during the day were entered on the log-board before they were transcribed to the logbook, which is why the logbook should be approached as a secondary source. This study shows that although Royal Navy logbooks represent valuable compilations of what was written on the log-board, it cannot be ascertained exactly how the logbooks were compiled. Seven logbooks from the Cumberland for August 1782 were evaluated by comparing them to the log-board from the same vessel, and the purpose was to determine the validity of logbook wind and weather entries. The results show that wind direction was most consistently transcribed according to the log-board and, furthermore, that a majority of the wind force entries derived from the 1 p.m. entry on the log-board. The kappa statistic shows that both wind force and weather conditions were most consistently copied from the 1 p.m. entry on the log-board. The study concludes that the first wind force and weather entries in the logbooks were not made at noon when the vessel was positioned. While the positioning of the vessel was made at the end of the nautical day, the first wind force and weather entries most likely describe the conditions 23 h earlier.

Description: ABSTRACT Model-based studies on urban heat islands can be seriously affected by errors in near-surface air temperature ( T 2), especially if errors differ between cities and their rural surroundings. Furthermore, errors in T 2 strongly depend on selected parameterisation schemes, in particular on the planetary boundary layer (PBL) scheme and the urban canopy model (UCM). We developed the Central Europe Refined analysis (CER), a dataset generated by dynamically downscaling a global atmospheric reanalysis with the Weather Research and Forecasting (WRF) model for Central Europe (30 km), Germany (10 km), and the region of Berlin-Brandenburg (2 km). CER data were analysed to study urban–rural and intra-urban differences in T 2 for Berlin as well as to test the sensitivity of T 2 against two different PBL schemes, a mosaic approach, and three UCMs with different levels of complexity. Results were evaluated using data from 22 weather stations. All tested configurations simulated T 2 with small deviations from observations. The PBL schemes predominantly control the deviation of T 2. From the tested PBL schemes, the Bougeault–Lacarrére scheme performed better than the Mellor–Yamada–Janjić scheme. The application of different UCMs and the mosaic approach also influenced the deviations, but not as strongly as the PBL schemes. The performance of the UCMs regarding the representation of intra-urban and urban–rural differences showed that differences were largest when using a complex multi-layer UCM. Overall, the simplest model showed lowest deviations. We conclude that more research on UCMs is required because complex UCMs showed potentials but did not outperform the simple slab model.

Description: ABSTRACT Rainfall is a primary component of the water cycle, and its variability is associated with drought and flood events. This study investigates the trends in annual and seasonal rainfall at 14 rainfall stations in Shaanxi Province, China, using an innovative trend analysis (ITA), Mann–Kendall test and linear regression analysis. Moreover, using ITA, annual rainfall is analysed for different rainfall intensities, and seasonal rainfall is analysed for extreme values. The results show non-uniform trends in rainfall intensities on a regional and seasonal scale. Annual rainfall shows a significant decreasing trend in the Wei River Basin and north of the Loess Plateau. Overall, the trend is reinforced with the increase of rainfall intensity. A few stations show significant trends in seasonal rainfall. Spring rainfall is the major contributor to the decline in annual rainfall. Heavy rainfall (more than 90th percentile) in summer exhibits a marked downward trend mainly in the basin, which makes it possible for flooding to abate along the Wei River. Light rainfall (less than 10th percentile) shows a prevailing increasing trend in summer, but a decreasing trend in other seasons. From north to south, the seasonal trends become clearer and stronger. In terms of management, more attention should be paid to autumn droughts in the Wei River Basin. A quantitative measurement of a trend for ITA is proposed. Comparison of the three methods endorses the ITA method. Moreover, the ITA shows many advantages, such as graphical results and for observing sub-trends. It is hoped that this study can provide support for water resources planning, for coping with droughts and floods and for future development of the ITA method.

Description: ABSTRACT The goal of this study was to better understand the spatial variations in the daily average, maximum and minimum air temperatures on Jeju Island, South Korea, by interpolating between observed temperature data that are distributed across a mountainous region. This spatial interpolation was performed in two steps: filling in the ungauged station data using principal component regression, and then downscaling the station-based data to obtain a spatially gridded data set using the Precipitation-elevation Regressions on Independent Slopes Model. Whereas the conventional practice of interpolating data does not include filling in ungauged data, our approach is particularly useful because most ungauged data correspond to high-elevation regions. Using the proposed approach, we were able to reasonably construct the spatial distribution of the temperatures on Jeju Island. Our trend analysis showed that the temperatures increased significantly in the summer and decreased in the winter. Furthermore, the positive temperature trends generally become larger at higher elevation when the average positive trends are significant in the summer.

Description: ABSTRACT This study investigates impacts of two types of La Niña events, eastern Pacific (EP) La Niña and central Pacific (CP) La Niña, on Australian summer rainfall during 1951–2009. Results show that Australian summer rainfall is sensitive to the change in the location of sea surface temperature (SST) anomalies in equatorial Pacific. During CP La Niña, maximum cold SST anomaly is located in the equatorial CP west of 150°W, and significant northeasterly wind anomalies tend to prevail over northeastern Australia during austral summer. This brings more moist and warm flow from the tropics to Australia and leads to significant positive rainfall anomalies over northern and eastern Australia. In contrast, during EP La Niña, maximum cold SST anomaly is confined to equatorial EP east of 150°W and atmospheric circulation anomalies tend to be weak. As a result, rainfall anomalies are generally weak over Australia in EP La Niña. The differences in the Australian summer rainfall anomalies between CP La Niña and EP La Niña are attributed to the differences in atmospheric circulation anomalies. Specifically, the atmospheric circulation anomalies over tropical Pacific tend to be stronger and located more westward in CP La Niña. Higher climatological SST in the equatorial CP than equatorial EP, larger magnitude and westward shift of cold SST anomaly centre in CP La Niña than EP Niña may explain stronger and westward shift of the atmospheric anomalies in CP La Niña. Atmospheric model numerical experiments confirm the contribution of stronger circulation response in CP La Niña to the positive rainfall anomalies in Australia. Results in this study suggest that it is important to classify the La Niña events into different types when predicting Australian summer rainfall.

Description: ABSTRACT Drought is a natural hazard developing slowly and affecting large areas which may have severe consequences on society and economy. Due to the effects of climate change, drought is expected to exacerbate in various regions in future. In this study, the impact of climate change on drought characteristics is assessed, and statistical methods are employed to analyse the significance of projections. This is the first study utilizing 21 recently available downscaled global climate models generated by NASA (NEX-GDDP) to evaluate drought projections over various regions across the United States. Drought is investigated through a multi-model dual-index dual-scenario approach to probabilistically analyse drought attributes while characterizing the uncertainty in future drought projections. Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index values at the seasonal scale (3 months) are used to project and analyse meteorological drought conditions from 1950 to 2099 at 0.25° spatial resolution. Two future concentration pathways of RCP4.5 and RCP8.5 are considered for this analysis. Accounting for the combined effects of precipitation and temperature variations reveals a considerable aggravation in severity and extent of future drought in the western United States and a tendency toward more frequent and intense summer droughts across the Contiguous United States.

Description: ABSTRACT Israel's location in a semi-arid region along the eastern coast of the Mediterranean Sea makes the prediction of winter precipitation socially and environmentally important. In 1982, Tzvetkov and Assaf proposed a connection between heat content (HC) in the Eastern Mediterranean (EM) in fall and precipitation over Israel in the following winter. We revisit their hypothesis using 21 years of remotely sensed sea surface temperature and sea surface height. The HC of the EM's upper layer is derived from these remotely sensed measurements under a reduced gravity approximation. Our results show a correlation of R = 0.6 between HC in the fall off the coastline of Lebanon and precipitation in Haifa, Tel-Aviv and Jerusalem. The depletion of HC during winter correlates moderately ( R = 0.4) with precipitation in the three cities. Thus, according to our analysis, the upper layer HC in the EM in fall significantly impacts winter precipitation over Israel. Still, from a separate analysis, the atmospheric short-term condition seems to be important as well.

Description: ABSTRACT The seasonal distribution of mean precipitation and heavy rainfalls during 1960–2013 was analysed based on daily precipitation totals from 168 rain gauging stations in the Vosges Mountains area, north-eastern France. Concerning mean precipitation, an ancient Hrudička's index designed as a half-time of precipitation during a year, surprisingly well expresses the seasonality of precipitation and its clear correlation with the mean annual totals in the studied region. The annual course of mean precipitation leads to a distinction of four groups of stations with respect to the position of stations: MT, mountainous stations with maxima of precipitation in winter and an overall highest mean annual totals; LSp, stations situated on leeward slopes of the Vosges Mountains with two maxima of precipitation (primary in winter and secondary in summer); URP, leeward stations located in the Upper Rhine River Plain with the most humid summer season, and the lowest mean annual totals; WSd, windward stations not influenced by the Vosges Mountains, with relatively evenly distributed precipitation, and slight maxima in autumn. For the heavy precipitation, 1–10-days totals have been considered to be ‘heavy’ subsequent to applying the three common methods – peaks over threshold (POT), block maxima (BM), and return period estimates based on generalized extreme value distribution. Varying criteria have been employed. The BM method for annual maxima indicates that the heavy rainfall generally occurs during the most humid season although it can also occur anytime during the year. The POT and return period estimates methods reveal that the seasonality of extremes is threshold-dependent and that probably the threshold sensitivity is also related to the degree of orographic influence – higher occurrence of summer events in the lee while lesser occurrence of winter events in mountains, at higher threshold and shorter duration of event.

Description: ABSTRACT Valleys can trap cold air to form Valley Cold Pools (VCPs). Characterized by stable stratification and weak winds, VCPs, especially those that last over multiple days, can produce adverse effects such as poor visibility and severe air pollution. Using the gridded data set of the North American Regional Reanalysis (NARR) for the period of 1979 through 2012, this study examines the climatology of VCPs in the western United States with a focus on spatial and temporal variability. The results reveal a widespread occurrence of short-lived (1–2 days) VCPs over both the mountainous areas of the West and the Northern Plains. Longer VCP episodes, however, tend to be limited to large basins/valleys in the Northwest and the Intermountain West. The leading mode of variability in the annual number of cold-season multi-day VCP event anomalies appears to be linked to a sea-surface temperature anomaly pattern typically found during the warm phase of Pacific Decadal Oscillation. Corresponding to the positive phase of the leading mode of variability is an anomalous 500-hPa ridge over the western United States induced by a Rossby wave train, which, by blocking cold-air intrusions and producing mid-level subsidence warming, leads to more persistent VCP episodes in the western United States. In addition to large-scale wintertime circulation anomalies, local surface temperature anomalies also contribute to the variability.

Description: ABSTRACT Irrigation and rain-fed agriculture, the main agricultural practices in the middle and southern Loess Plateau area, impact the regional climate in different ways. Based on 38 meteorological stations in the middle and southern Loess Plateau area, the effects of agricultural irrigation on climatic variables from 1960 to 2005 were evaluated. Climatic trends from non-irrigated areas were used as a reference. Trends in climatic variables for the growing season and the summer period are negatively correlated with the percentage of cultivated land within a 3 km radius of the meteorological stations. Trends for the average summer temperature ( T a ), maximum temperature ( T max ), minimum temperature ( T min ) and the diurnal temperature range (DTR) decreased by 0.065, 0.073, 0.054 and 0.025 °C per decade, respectively. Summer net solar radiation (SR) decreased by 0.0325 MJ m −2  day −1 per decade and summer relative humidity (RH) increased by 0.255% per decade with a 10% increase in the area of cultivated land. The climatic effects on meteorological stations in irrigated areas are compared to the trends of non-irrigated areas in the study region. The expansion of irrigation has had a noticeable cooling effect on summer T a , T max , T min and DTR with values of 0.192, 0.193, 0.142 and 0.058 °C (10 years) −1 , respectively. Irrigation increased RH by 0.916% per decade and net radiation reduced by 0.230 MJ m −2  day −1 per decade. On monthly scales, these effects were more obvious in June and August. The dependence of climatic trends on the proportion of cultivated land can be attributed to agricultural irrigation. The changes in climatic differences for T a , T max , T min , RH and SR corresponded with the expansion of irrigation. The cooling effects induced by irrigation have also partly masked the effects of greenhouse gas-induced warming.

Description: ABSTRACT High mountains are some of the most vulnerable regions to climate change and therefore a matter of global concern. Here, the climatic growth factors of conifers and their course in time and space along an elevational gradient in the northwestern Himalayan part of India were studied. Increment cores of Juniperus semiglobosa and Cedrus deodara (xeric species), and Abies pindrow and Picea smithiana (mesic species) were collected from thirteen sites. Tree-ring width and maximum latewood density were measured and cross-dated. The time-series were standardized and site- and species-level chronologies were built. Static and moving bootstrap correlation and response functions between the tree-ring chronologies and monthly climatic variables were computed. The largest climate changes in the region were increasing winter and early-spring temperatures and decreasing monsoon precipitation. The growth of all species was negatively correlated with pre-monsoon temperature, as the higher temperatures probably increased evapotranspiration and caused water deficit. The phenomenon was most pronounced in May, but also in June for the Juniperus at the northernmost, highest, and driest sites. The pre-monsoon temperature signal of the drought-prone Juniperus and Cedrus endured, while the signal of the climate-susceptible Abies and Picea at the mesic sites was unstable. Namely, the May temperature signal of Picea became significant since the second half of the last century whereas the signal of Abies shifted from May to April. This apparently related to the earlier onset of spring due to the accelerated warming in the region. Besides, maximum latewood density of Picea and Abies negatively correlated with May and June temperature, respectively. Additionally, the Cedrus benefitted from winter precipitation and the Abies and Picea from pre-monsoon rainfall. Counterintuitively, we detected no direct effect of monsoon precipitation decrease on the conifers because their growth was driven by pre-monsoon conditions, which changed only slightly.

Description: ABSTRACT We have analyzed series of air, near-surface and shallow ground temperatures under four land cover types, namely bare clayey soil, sand, short-cut grass and asphalt; the samples were collected between 2002 and 2013 and monitored at the Geothermal Climate Change Observatory Sporilov, Prague (50°02.43′N, 14°28.54′E, 226 m a.s.l.). A comparison of all of the obtained temperature series revealed a strong dependence of the subsurface thermal regime on the respective surface cover material. The ground ‘skin’ temperature was generally warmer than the surface air temperature over all monitored surfaces; however, the temperatures over different land cover types differed significantly. Asphalt exhibited the highest temperatures, and temperatures below the grassy surface were the lowest. Special attention was paid to assessing the value of the ‘temperature offset’, the instant value of which sometimes varied dramatically, on both daily and annual scales, by up to 30+ K; however, on a long-time scale, the temperature offset was generally constant and reflected the surface material. The characteristic 2003–2013 mean values for the individual covers are as follows: asphalt 4.1 K, sand 1.6 K, clay 1.4 K and grass 0.2 K. All four surface covers revealed typical daily and inter-annual cycles, which were monitored and are discussed in detail. Incident solar radiation was the primary variable for determining the amount and temporal changes of the temperature offset values. A linear relationship between air–ground temperature differences and incident solar radiation was detected. The mean slope of the linear regression between both variables is clearly surface cover dependent. The greatest value, 3.3 K per 100 W m −2 , was found for asphalt cover; rates of 1.0–1.2 apply to bare soil and sand cover, and a negative slope of −0.44 K per 100 W m −2 represents grass cover.

Description: ABSTRACT Trends in near-surface air temperature and precipitation over South America are examined for the periods 1975–2004 and 1955–2004, respectively, using multiple observational and climate model data sets. The results for observed near-surface air temperature show an overall warming trend over much of the continent, with the largest magnitudes over central Brazil. These observed trends are found to be statistically significant using pre-industrial control simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) as the baseline to estimate natural climate variability. The observed trends are compared with those obtained in natural-only CMIP5 simulations, in which only natural forcings (i.e. volcanoes and solar variability) are included, and in historical CMIP5 simulations, in which anthropogenic forcings (i.e. changes in the atmospheric composition) are further incorporated. The historical CMIP5 simulations are more successful in capturing the observed temperature trends than the simulations with natural forcings only. It is suggested that anthropogenic warming is already evident over much of South America. Unlike the warming trends, observed precipitation trends over South America are less spatially coherent with both negative and positive values across the continent. Significant positive trends are found over South America in only one of the data sets used, and over a region that roughly encompasses the southern part of La Plata Basin (southern Brazil, Uruguay, and northeastern Argentina) in all data sets used. The historical CMIP5 simulations do not capture this feature. No firm conclusions are reached, therefore, for anthropogenic influences on precipitation changes in the period selected for study.

Description: ABSTRACT Extreme climate events over a wide Chinese area are investigated with the regional climate model COSMO-CLM at high resolution (0.125°) through the use of some extreme indicators. Two hindcast simulations, driven respectively by ERA-Interim reanalysis and the global model CMCC-CM over the period 1979–2011 have been analysed in order to check the model's ability to represent a subset of climate indicators for precipitation and temperature, as a preliminary step to assess changes regarding extreme weather events expected under greenhouse gas concentration variations. The effort to increase resolution in a regional model has interesting benefits in representing extreme indices, especially in complex orography areas. Results show that the model provides a good representation of the spatial climatology of the indices considered, with high correlation values between the model and observations. Future climate changes concerning extreme events have been investigated, employing the IPCC RCP4.5 and RCP8.5 scenarios. Projections reveal that temperature indicators are characterized by positive trend values, highlighting an increase in minimum and maximum temperatures over the period 2041–2070, especially over southeast China. Extreme precipitation events are generally projected to increase over the whole region considered, especially under RCP8.5 scenario.

Description: ABSTRACT Visibility impairment, one of the restricting phenomena for aviation, results from light scattering and absorption. In this study, the historical visibility database for the period of 1981–2010 is used to obtain extinction coefficient according to the Koschmieder theory in the four busiest airports in Iran, including Tehran-Mehrabad, Mashhad, Shiraz and Isfahan. The long-term trend of extinction coefficient and its seasonal variations are investigated using 10th and 90th percentiles of extinction data to show the visual range in each airport. Correlation of the long-term visibility trend with relative humidity (RH) and cloudiness is also examined. The comparison of seasonal mean extinctions shows the noticeable effect of local climate. The highest extinction coefficient value in each airport is seen during winter, while the lowest value occurs in summer. The seasonal mean extinction coefficient level in winter is about 0.1 km −1 higher than those of the other seasons. This is likely due to pollutants trapped by the stagnant cold air that partly obstruct visibility and increase the extinction in wintertime. There is not an outstanding variation of the tenth percentile of the extinction coefficient in the four airports. The low variation may relate to the definition of the upper threshold in visibility. Analysis shows that there is a positive correlation between extinction and humidity in all the airports that indicates the increase of scattering by hygroscopic particles with increasing humidity, such effect would be accentuated in high RH. The same result is seen for different percentages of cloudiness. To minimize the effects of humidity and cloudiness on the long-term visibility trend, the days with the relative humidity values more than 70% and cloudiness of more than 5/8 of the sky are removed from the visibility trend analysis. The trends of the screened days are nearly parallel to the trends of raw data, but with a slight difference in each airport. The overall filtered long-term trends show the increase of extinction coefficient at all the airports that emphasize the effect of pollution on the trend of light extinction within the whole period of this study. Eliminating the meteorological factors from the raw data does not change the overall increasing trend of extinction at Tehran and Isfahan airports. It suggests that the changes in air quality are responsible for the long-term visibility degradation at these two stations that are located in the two most highly industrialized and polluted cities in Iran.

Description: ABSTRACT This article presents a detailed comparison of ten precipitation products over the central southwest Asia (CSWA) region. The spatial characteristics and temporal variations of wintertime precipitation over CSWA region are assessed using four gauge-only [Asian Precipitation – Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Climate Prediction Center Unified Rain gauge (CPC-uni), Global Precipitation Climatology Center Full Data Reanalysis (GPCC) and Climate Research Unit (CRU)]; three satellite-derived (3B42-V6, 3B42-V7 and GPCP-1DD) and three reanalysis [Climate Forecast System Reanalysis (CFSR), ERA-Interim and Modern-Era Retrospective Analysis for Research and Applications (MERRA)] precipitation products. The analysis is performed for two different periods: (1979–2007) for the gauge-only/reanalyses and (1998–2007) for the satellite-derived products. Using an ensemble average of four gauge-only observational data sets as our reference, we carry out comprehensive qualitative assessment of the uncertainties/biases associated with each data set. Additionally, we examine the relationship pattern between CSWA wintertime precipitation and El Niño-Southern Oscillation (ENSO) phases. In the gauge-only category, APHRODITE and GPCC perform better than CPC-uni and CRU data sets in terms of the spatial and temporal variations of skill matrices. Overall, GPCC shows the best performance (including the precipitation sensitivity to ENSO events) and is the preferable observational data set for long-term climatological analysis over the CSWA region. Among the satellite-derived precipitation products, 3B42-V7 displays the most realistic wintertime precipitation distribution pattern when compared to 3B42-V6 and GPCP-1DD; however, efforts are needed to further improve the accuracy of satellite-derived products over the dry arid and semi-arid areas of CSWA. In the reanalysis category, MERRA's performance is relatively better than CFSR and ERA-Interim, although significant biases exist in all of the reanalyses due to overestimation of precipitation over the mountainous regions of CSWA.

Description: ABSTRACT Monthly rain amounts (MRA) recorded at Fabra Observatory (Barcelona, NE Spain) since 1917–2010, are analysed from two complementary points of view. First, mono- and multifractal characteristics of MRA are compared with those corresponding to the monthly Western Mediterranean Oscillation index (WeMOi), which affects the rainfall regime at the western Mediterranean region. Monofractality is analysed through Hurst and Hausdorff exponents, and a power law describing the dependence of MRA power spectra on frequency. The reconstruction theorem permits to quantify the complexity of the physical process by means of the correlation dimension and the Kolmogorov entropy. In agreement with this theorem, the predictive instability is also evaluated through the Lyapunov exponents. The multifractality is characterized by the critical Hölder exponent, as well as by the asymmetry and spectral width of the multifractal spectrum. Second, three predictive processes for MRA are tested. One of them is based on the assumption that MRA could be simulated by fractional Gaussian noise. The other two are, by one hand, an ARIMA( p ,1,0) process for MRA; on the other hand, an adaptation of the ARIMA process for MRA taking as arguments preceding WeMOi. Finally, relationships between MRA and WeMOi confirm that outstanding MRA use to be coincident with negative WeMOi. An explanation is also proposed for the non-negligible number of MRA corresponding to positive WeMOi.

Description: ABSTRACT A dust storm climatic regionalization of the Arabian Peninsula (AP) that aims to categorize the region into several cohesive sub-regions is conducted. This approach was carried out by grouping together similar wet season climatological features of dust storm activity (DSA). A common period of 30 years (1983–2013) for 38 meteorological weather stations across the AP was utilized. The mathematical, statistical and subjective methods that are employed in the process of regionalization resulted in dividing the region into three sub-regions. Each of the sub-regions north, northwestern and central, northeast and south, west and coastal shows distinct features of its own. Subsequently, the temporal trend of the representative station (key station) for each sub-region is examined. It is found that only the northeastern part of the region has a significant positive trend over the last 30 years. However, this positive increase in DSA is not associated with an increase in wind speed. This study assists future research in exploring the relationship between large-scale forcing and the AP sub-regional DSA. As well, this could enhance regional DSA forecast and future projections.

Description: ABSTRACT Since 1999, the increased frequency of dry conditions over East Africa, particularly during the March–May (MAM) season, has heightened concerns in a region already highly insecure about food. The underlying mechanisms, however, are still not yet fully understood. This article analyses a proxy for daily convection variations over a large region encompassing East Africa and the whole Indian Ocean basin by applying a cluster analysis to more than 30 years of daily outgoing longwave radiation (OLR). Focusing on the MAM season to investigate relationships with East African long rains, four recurrent convection regimes associated with wet/dry conditions in East Africa are identified. Interestingly, all four regimes are related to western/central Pacific sea surface temperatures (SSTs) and rainfall. Wet regimes are associated with cool and dry/warm and wet conditions over the Maritime Continent (MC)/tropical Pacific east of the date line. Dry regimes exhibit opposite SST/rainfall dipole patterns in the Pacific compared to wet regimes, with the Indian Ocean found to modulate impacts on East African rainfall. Significant relationships between off-equatorial warming in the west Pacific and a more frequent dry regime in May since 1998–1999 suggest an earlier onset of the monsoon and Somali jet, consistent with the recent abrupt shift observed in East African long rains and their modulation at multi-decadal time scales of the Pacific.

Description: ABSTRACT Radiosonde data are valuable to the research community because they provide observations for multiple decades and can be used to validate model output. However radiosonde data often suffer from quality issues, which has undermined their credibility. Therefore, corrections for biases and changepoints are needed to remedy the situation. Homogenization of monthly radiosonde specific humidity ( q ) from the 1970s to the present has been performed on selected stations over the Southwest Pacific (SWP) at three pressure levels (i.e. 850, 700 and 500 hPa). A three-step procedure involving (1) adjustments for two sampling biases, (2) detecting secular changepoints (i.e. discontinuities) using both statistical techniques and metadata validation, and (3) an innovative break size estimate approach, has been implemented to achieve this aim. In the last step, a discontinuity-free pseudo- q is constructed from saturated specific humidity q s which itself is derived from an already homogenized temperature ( T ) time series. This pseudo- q serves as a reference that not only distinguishes artificial from natural changepoints but also helps to estimate the magnitudes of the discontinuity. On the decadal time scale, the adjusted q ( q adj ) exhibits spatially more consistent moistening at the 850 hPa level over most of the region and a contrast at 500 hPa between the moistening in the tropics and a drying in the subtropical South Pacific. Mean regional trend estimates are ∼1.8% (850 hPa), −0.2% (700 hPa) and 1.3% (500 hPa) per decade. A climatological comparison with the three latest reanalysis products – CFSR, ERA-Interim and MERRA, suggests the reanalyses have significant negative biases over Southeast Asia (SEA) at all three levels. Over Australia the biases are negative at 850 hPa while positive at 500 hPa. The reanalysis products tend to be more similar among themselves in the estimates of q , as compared to the radiosonde measurements of q and q adj . The homogenized radiosonde q , when assimilated into reanalysis, is likely to lead to a more realistic model of the hydrological cycle.

Description: ABSTRACT Generalized linear models (GLMs) are used in understanding the impact of predictors on a dependent variable. The aim of this study is to fit GLMs to daily rainfall totals using potential predictors. First, the appropriate probability distributions within a specific family, the Tweedie family, were determined for daily rainfall totals from four stations of Peninsular Malaysia from 1983 to 2012. Within the Tweedie family, the Poisson Gamma (PG) distribution was found appropriate to model both components: occurrence (dry/wet days) and amount (rainfall totals on wet days) of rainfall simultaneously. Then, the PG-GLMs were fitted to rainfall data with a sine term, a cosine term, lagged rainfall, NINO3.4 and Southern oscillation index (SOI) as predictors. Finally, the models were compared using the Likelihood ratio test and the Akaike information criterion. Initially, considering the cyclic pattern of rainfall data, models with only sine and cosine terms (the base model) were fitted. Then the lagged rainfall and climatological variables were added each time to the base model. Diagnostic QQ plots indicate that the models fit the data well. The models were fitted using the first 60% of data and validated using the remainder. The models capture the various characteristics of observed datasets reasonably well. Including single climatological variables in the model significantly improves the fit compared to the base model with lagged rainfall (except for the south-east coastal station, Mersing), however, including both climatological predictors in the same model does not improve the model significantly. The model with SOI is only favoured for the east coastal station, Kuala Terengganu, and the model with NINO3.4 fits better to the inland and west coastal stations. The models are useful in understanding the impact of the studied climatological variables and to predict the amount and probability of rainfall.