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Climate disasters such as floods and droughts often bring heavy losses to human life, national economy, and public safety. El Niño/Southern Oscillation (ENSO) is one of the most important inter-annual climate signals in the tropics and has a global impact on atmospheric circulation and precipitation. To address the impact of climate change, accurate ENSO forecasts can help prevent related climate disasters. Traditional prediction methods mainly include statistical methods and dynamic methods. However, due to the variability and diversity of the temporal and spatial evolution of ENSO, traditional methods still have great uncertainty in predicting ENSO. In recent years, with the rapid development of artificial intelligence technology, it has gradually penetrated into all aspects of people's lives, and the climate field has also benefited. For example, deep learning methods in artificial intelligence can automatically learn and train from a large amount of sample data, obtain excellent feature representation, and effectively improve the performance of various learning tasks. It is widely used in computer vision, natural language processing, and other fields. In 2019, Ham et al. used a convolutional neural network (CNN) model in ENSO forecasting 18 months in advance, and the winter ENSO forecasting skill could reach 0.64, far exceeding the dynamic model with a forecasting skill of 0.5. The research results were regarded as the pioneering work of deep learning in the field of weather forecasting. This paper introduces the traditional ENSO forecasting methods and focuses on summarizing the various latest artificial intelligence methods and their forecasting effects for ENSO forecasting, so as to provide useful reference for future research by researchers. [ABSTRACT FROM AUTHOR]

The article presents the research results aimed at determining the impact of meteorological droughts on groundwater droughts in the Gwda River catchment (northern Poland). The analysis was based on the Standardised Precipitation Index (SPI) and Standardised Groundwater Index (SGI) in various cumulation periods (1, 6, 12, 18, 24, 30 and 36 months) from 1986-2015. Monthly groundwater levels measured in wells and monthly sums of precipitation from meteorological stations in the vicinity of those wells were used to assess the relationships between droughts. During the study period from 1986-2015, three to 43 meteorological droughts and one to five groundwater droughts were identified. Meteorological droughts were most numerous for the shortest cumulation period (1 month), while droughts for the longer accumulation of 24 to 36 months were less numerous. The SPI and SGI indices were most strongly correlated over the annual cycle in the upper part of the catchment (between the Sępólno Wielkie station and well I-33_1). The correlation coefficient r was highest (0.69) between SPI-18 and SGI-1. Correlations were much lower in the middle of the catchment, where the maximum annual r coefficient was 0.39. There was no correlation between droughts in the lower catchment (r=0.14). The correlations presented for the Gwda catchment indicate that the relationship between droughts is not clear. [ABSTRACT FROM AUTHOR]

In the past 50 years, an increasing number of drought events have greatly affected the production and life of the people in Northeast China (NEC). The climatic conditions and sensitivities vary greatly in NEC due to complex terrain, large geographical range across latitudes and longitudes and different weather system effects. So, NEC is used to explore traditional geographical boundaries for meteorological drought research. In the paper, climate regionalization is performed by spatial hierarchical cluster approach based on the gridded dataset of monthly precipitation and temperature with a spatial resolution of 0.5°×0.5° in China from 1961 to 2016. Then, standardized precipitation index is employed to explore the temporal evolution of drought events, and wavelet method is used to detect drought periodicity in each sub-climatic region of NEC. The results show that: (1) Spatially, NEC can be divided into eight sub- climatic regions, namely, semi- arid agro- pastoral areas in the West Liaohe Plain, humid agro-forestry areas in the eastern mountainous areas of Jilin and Liaoning provinces, semi-arid pastoral areas in Hulun Buir Plateau, semi-humid and semi-arid agro-pastoral areas in central Northeast China, humid agro- forestry areas in the eastern mountainous areas of Heilongjiang and Jilin provinces, humid forestry areas in the north of Da Hinggan, humid and semi-humid agro-forestry areas in Hulun Buir Plateau and Heihe, and humid agricultural areas in Sanjiang Plain. (2) There are obvious differences for the temporal evolution of drought events in different sub-climatic regions, but three obvious drought periods, namely, late 1960s, late 1970s to early 1980s, and late 1990s to 2000s, can be found in each sub-region. The frequency and impact of droughts in NEC were the largest between 2000 and 2010, especially in the central and western parts of the study region. (3) There are significant drought periods of 11 years and 3- 8 years in the eight sub- climatic regions of NEC, and the first main cycles of drought variation are not completely consistent. It is a very important step to divide a region into homogeneous sub-regions based on one or more climatic variables in climate studies. Therefore, the results of this paper have practical significance for identifying the drivers of climate variability specific to each sub- climatic region, establishing drought monitoring programs for climate homogeneous regions and managing water resources. [ABSTRACT FROM AUTHOR]

Quantitatively evaluation of satellite precipitation and potential evapotranspiration products with the high resolution, wide coverage and dynamic continuity is an important foundation for drought monitoring over mainland China. This paper examined the accuracy of products and the utility of drought monitoring using the newly released long-term (more than 30 years) satellite precipitation products (climate hazards group infrared precipitation with station, CHIRPS) data version 2.0 and potential evapotranspiration products (global land-surface evaporation: the Amsterdam methodology, GLEAM) dataset. We selected standardized precipitation evapotranspiration index (SPEI) and six statistical and classification measures indexes to evaluate accuracy and the utility of CHIRPS and GLEAM-Ep (potential evapotranspiration derived from GLEAM), with China Gauge-based Precipitation Daily Analysis dataset (CGDPA) and potential evapotranspiration calculated by Penman-Monteith (PM-Ep) as evaluation reference data sets. The results showed that CHIRPS and GLEAM-Ep performed well in eastern and southwest of China. However, their performance in western China was uncertain due to the sparsity of meteorological stations. SPEIs (SPEI value calculated by the CHIRPS and GLEAM-Ep) had a good performance on drought monitoring in eastern and southwestern China. Values of correlation coefficient (CC) between SPEIs and SPEIm (SPEI value calculated by the CGDPA and PM-Ep) were more than 0.6 in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China, especially in relatively humid areas, which the correlation coefficient values were more than 0.7 and the root mean-squared error (RMSE) values were less than 0.8. In order to further evaluate the performance of SPEIs in drought monitoring at spatial and temporal scales, the SPEIs3 (SPEIs at three-month scale) and SPEIm3 (SPEIm at three-month scale) in southeastern China, southwestern China, the middle and lower reaches of the Yangtze River region and northern China were compared. SPEIs3 had a better simulation effect on the evolution process of the ratio of drought area in those regions during1981-2016. And the success ratio of simulating drought duration was about 0.93, 0.57, 0.71 and 0.81, respectively. Moreover, SPEIs3 displayed a high accuracy over the four regions in capturing drought, which was the spatial distribution of typical drought events on specific month. In conclusion, SPEI based on long-term CHIRPS and GLEAM-Ep could be applied to monitor and evaluate drought in eastern and southwestern China. This paper can provide reliable reference for monitoring and warning of drought events and water resources management in those regions. [ABSTRACT FROM AUTHOR]

Using remote sensing data to monitor large area drought is one of the important methods of drought monitoring at present. However, the traditional remote sensing drought monitoring methods mainly focus on monitoring single drought response factors such as soil moisture or vegetation status, and the research on comprehensive multi-factor drought monitoring is limited. In order to improve the ability to resist drought events, this paper takes Henan Province of China as an example, takes multi-source remote sensing data as data sources, considers various disaster-causing factors, adopts random forest method to model, and explores the method of regional remote sensing comprehensive drought monitoring using various remote sensing data sources. Compared with neural network, classification regression tree and linear regression, the performance of random forest is more stable and tolerant to noise and outliers. In order to provide a new method for comprehensive assessment of regional drought, a comprehensive drought monitoring model was established based on multi-source remote sensing data, which comprehensively considered the drought factors such as soil water stress, vegetation growth status and meteorological precipitation profit and loss in the process of drought occurrence and development. [ABSTRACT FROM AUTHOR]

The Mediterranean region is a unique area characterized by a large spectrum of atmospheric phenomena, some of which have a high impact on many aspects of human activities, safety and wellbeing. The area is long considered as a hot spot of such atmospheric phenomena deserving multidisciplinary scientific attention. The scientific research that has been carried out on these high impact atmospheric processes that occur in the Mediterranean area is indeed widespread and the available international literature is very extensive. The paper touches initially the temperature and precipitation regimes, followed by a discussion of floods and droughts. The exciting cyclogenetic patterns of explosive cyclones and medicanes are presented in separate sections. The lightning activity and the presence of dust and other pollutants are also presented herein. The atmospheric chemistry of the region which is increasingly becoming of utmost importance for the area under study is distinctly discussed. Attempts to modify the weather (the precipitation, in particular) are outlined too. The effects of climatic change on various atmospheric processes are considered throughout this paper, in addition to a dedicated section on temperature and precipitation. [ABSTRACT FROM AUTHOR]

The Swarm satellite is equipped with the Global Positioning System (GPS) receiver and ac⁃ celerometer, which can be used to restore Earth’s temporal gravity field model. Firstly, the terrestrial wa⁃ ter storage (TWS) variability and 2015-2016 drought induced TWS deficits in the Amazon basin are esti⁃ mated from the Swarm time ⁃ variable gravity field model between December 2013 and December 2016. Then, the estimated results from Swarm data are compared to the results derived from Gravity Recovery and Climate Experiment (GRACE), three hydrological models （Global Land Data Assimilation System (GLDAS)， Climate Predication Center (CPC)， National Centers for Environmental Prediction (NCEP)) and 4 virtual stations (AMZ_076， AMZ_152， AMZ_ 228 and AMZ_215). Finally, the precipitation and temperature data are employed to study the origination of the drought event in the Amazon basin. The re⁃ sults indicate that the TWS derived from Swarm, GRACE, hydrological models, and virtual stations are in high consistency in the space/time distribution; Swarm provided a new perspective in detecting TWS, which has a potential to substitute GRACE satellite in studying the extremely drought and flood in the Ama⁃ zon basin. The results in this paper may provide a reference in understanding Earth’s mass transformation by Swarm. [ABSTRACT FROM AUTHOR]

[Display omitted] • The proposed MSDI can capture the occurrence of drought. • There was a tendency of aridity with a mutation point of 1983. • The drought severity was the heaviest in the DXJB, with an average MSDI of –0.75. • The most severe drought event occurred from September 1988 to October 1990. • ENSO had the largest influence on the drought variation in the XJB. The reasonable and appropriate drought indicator is a crucial instrument for drought investigation and assessment, which can objectively compare the severity, duration, and frequency of drought events, so as to achieve the purpose of accurately monitoring and evaluating drought. However, a univariate drought index is often difficult to precisely describe the complex drought situation, and it is urgent to establish a multivariate comprehensive drought index to identify and reveal the drought characteristics. Based on Copula models, combined with meteorological factors precipitation and hydrological factors runoff, this paper constructed a Multivariate Standardized Drought Index (MSDI), which can characterize meteorological drought and hydrological drought simultaneously and evaluate the spatial–temporal evolution characteristics of drought over the Xijiang River Basin (XJB) in South China. The results indicated that: (1) the proposed MSDI can capture the occurrence of drought as sensitively as the Standardized Precipitation Index (SPI), and can represent the termination of drought as effectively as the Standardized Runoff Index (SRI), which can comprehensively depict the drought situation in the XJB, China; (2) since the 1980 s, there was a tendency of aridity with a mutation point of 1983 in the downstream of Xijiang River (DXJB), and the worst comprehensive drought occurred in 1989; (3) among the tributaries, the comprehensive drought severity was the heaviest in the DXJB, with an average MSDI value of –0.75; (4) based on the run theory and Copula model, the most serious drought event occurred from September 1988 to October 1990, with a drought severity of 33.36, a drought duration of 27 months, and a drought return period exceeding 50 years; and (5) the drought evolution was significantly influenced by abnormal atmospheric circulation factors, while ENSO had the largest influence on the drought variation in the XJB, followed by sunspot. [ABSTRACT FROM AUTHOR]

It is expected that climate warming will be experienced through increases in the magnitude and frequency of extreme events, including droughts. This paper presents an analysis of observed changes and future projections for meteorological drought for four different time scales (1 month, and 3, 6 and 12 months) in the Beijiang River basin, South China, on the basis of the standardized precipitation evapotranspiration index (SPEI). Observed changes in meteorological drought were analysed at 24 meteorological stations from 1969 to 2011. Future meteorological drought was projected based on the representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, as projected by the regional climate model RegCM4.0. The statistical significance of the meteorological drought trends was checked with the Mann-Kendall method. The results show that drought has become more intense and more frequent in most parts of the study region during the past 43 years, mainly owing to a decrease in precipitation. Furthermore, long-term dryness is expected to be more pronounced than short-term dryness. Validation of the model simulation indicates that RegCM4.0 provides a good simulation of the characteristic values of SPEIs. During the twenty first century, significant drying trends are projected for most parts of the study region, especially in the southern part of the basin. Furthermore, the drying trends for RCP8.5 (or for long time scales) are more pronounced than for RCP4.5 (or for short time scales). Compared to the baseline period 1971-2000, the frequency of drought for RCP4.5 (RCP8.5) tends to increase (decrease) in 2021-2050 and decrease (increase) in 2051-2080. The results of this paper will be helpful for efficient water resources management in the Beijiang River basin under climate warming. [ABSTRACT FROM AUTHOR]

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987–2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. The large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. The frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. This bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. The results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region. [ABSTRACT FROM AUTHOR]

In this paper a conceptual instrument that confers an integral vision to Risk Management process due to intense drought is proposed. The use of methods such as the experts criterion enabled the adaptation of theories and universal standards of Risk Management on environmentally sustainable bases. The result is a conceptual model with essential characteristics as the interrelation between the pressure-state-impactresponse indicators with the strategic, systemic and participatory approaches that provide potentiality for decision-making facing increasingly frequent and prolonged events caused by precipitations scarcity. [ABSTRACT FROM AUTHOR]

In this paper, we investigate space time patterns of meteorological drought events in the Greater Alpine Region (GAR) of Europe. A long-term gridded dataset of monthly precipitation sums spanning the last 210 years is used to assess abnormally dry states using a shortfall below a monthly precipitation percentile threshold. These anomalies are calculated for 1, 3, 6, and 12 monthly moving averages. Contiguous areas of grid points below the threshold are indicating drought areas which are analyzed with respect to their drought severity. The severity is quantified by taking the average deviation from the threshold and the size of the drought area into account. The results indicate that the most severe dry anomalies in the GAR occurred in the 1860s, the 1850s, and the 1940s. However, no significant trends of dry anomaly severity are found over the last 210 years. A spatial clustering analysis of the detected drought areas shows distinct spatial patterns, with the Main Alpine Crest as a frequent divide between dryer areas in the north and wetter areas in the south, or vice versa. The patterns are highly significant and similar for all averaging time scales. The clusters are more clearly defined in winter than in summer. Droughts in the north are most frequent in the second half of the nineteenth century, while in the south and east, they are most frequent in the late twentieth century. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) play vital roles in the western United States and related regions globally, not only producing heavy precipitation and flooding, but also providing beneficial water supply. This paper introduces a scale for the intensity and impacts of ARs. Its utility may be greatest where ARs are the most impactful storm type and hurricanes, nor'easters, and tornadoes are nearly nonexistent. Two parameters dominate the hydrologic outcomes and impacts of ARs: vertically integrated water vapor transport (IVT) and AR duration [i.e., the duration of at least minimal AR conditions (IVT ≥ 250 kg m–1 s–1)]. The scale uses an observed or predicted time series of IVT at a given geographic location and is based on the maximum IVT and AR duration at that point during an AR event. AR categories 1–5 are defined by thresholds for maximum IVT (3-h average) of 250, 500, 750, 1,000, and 1,250 kg m–1 s–1, and by IVT exceeding 250 kg m–1 s–1 continuously for 24–48 h. If the AR event duration is less than 24 h, it is downgraded by one category. If it is longer than 48 h, it is upgraded one category. The scale recognizes that weak ARs are often mostly beneficial because they can enhance water supply and snowpack, while stronger ARs can become mostly hazardous, for example, if they strike an area with antecedent conditions that enhance vulnerability, such as burn scars or wet conditions. Extended durations can enhance impacts. Short durations can mitigate impacts. [ABSTRACT FROM AUTHOR]

This paper assesses the spatiotemporal characteristics of agricultural droughts and wet conditions in the Free State Province of South Africa for the period between 1960 and 2013. Since agriculturally, the Free State Province is considered the bread basket of the country, understanding the variability of drought and wet conditions becomes necessary. The Standardised Precipitation Index (SPI) computed from gridded monthly precipitation data was used to assess the rainfall extreme conditions. Hot spot analysis was used to divide the province into five homogenous clusters where the spatiotemporal characteristics for each cluster were analysed. The results show a west to east increase in seasonal average total precipitation. However, the eastern part of the province demonstrates higher occurrences of droughts, with SPI ≤ − 1.282. This is despite the observation that the region shows a recent increase in droughts unlike the western region. It is also noted that significant differences in drought/wet intensities between clusters are more pronounced during the early compared to the late summer period. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) is responsible for the climatic variability in the Northern Hemisphere, in particular, in Europe and is related to extreme events, such as droughts. The purpose of this paper is to study the correlation between precipitation and winter (December-January-February-March (DJFM)) NAO both for the historical period (1951-2000) and two future periods (2001-2050 and 2051-2100). NAO is calculated for these three periods by using sea level pressure, while precipitation data from seven climate models following the representative concentration pathway (RCP) 8.5 are also used in this study. An increasing trend in years with positive DJFM NAO values in the future is defined by this data, along with higher average DJFM NAO values. The correlation between precipitation and DJFM NAO is high, especially in the Northern (high positive) and Southern Europe (high negative). Therefore, higher precipitation in Northern Europe and lower precipitation in Southern Europe are expected in the future. Cross-spectral analysis between precipitation and DJFM NAO time series in three different locations in Europe revealed the best coherence in a dominant cycle between 3 and 4 years. Finally, the maximum drought period in terms of consecutive months with drought is examined in these three locations. The results can be used for strategic planning in a sustainable water resources management plan, since there is a link between drought events and NAO. [ABSTRACT FROM AUTHOR]

Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α < 0.05 level) to the SPI-3. Moreover, the implemented fuzzy model compared to decision tree-based forecast model shows better forecast skills. [ABSTRACT FROM AUTHOR]

Highlights • Large basins are homes to millions of people who depend on water for survival. Water drives the economic engine. • Use of publicly available model output and satellite data. • Analysis of extreme events: droughts and floods. Abstract Numerous large river basins of the world have few and irregular observations of the components of the terrestrial hydrological cycle with the exception of stream gauges at a few locations and at the outlet along with sparsely distributed rain gauges. Using observations from satellite sensors and output from global land surface models, it is possible to study these under-observed river basins. With populations greater than a billion people, some of these rivers (e.g., the Ganga-Brahmaputra, the Yangtze, the Nile and the Mekong) are the economic engines of the countries they transect, yet thorough assessment of their flow dynamics and variability in regard to water resource management is still lacking. In this paper, we use soil moisture (0–2 m) and surface runoff from the NASA Global Land Data Assimilation System (GLDAS), evapotranspiration, and Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and rainfall from the Tropical Rainfall Measuring Mission (TRMM) and total water storage anomaly from the Gravity Recovery and Climate Experiment (GRACE) to examine variability of individual water balance components. To this end, understanding the inter-annual and intra-seasonal variability and the spatial variability of the water balance components in the major river basins of the world will help to plan for improved management of water resources for the future. [ABSTRACT FROM AUTHOR]

Drought is a natural hazard which can cause harmful effects on water resources. To monitor drought, the use of an indicator and determination of wet and dry period trend seem to have an important role in quantifying the drought analysis. In this paper, in addition to the comparison of Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), based on the most appropriate probability distribution function, it was tried to examine the trends of dry and wet periods based on the mentioned indices. Accordingly, the meteorological data of 30 synoptic stations in Iran (1960-2014) was used and the trend was analyzed using the Mann-Kendall test by eliminating the effect of any significant autocorrelation coefficients at 95% confidence level (modified Mann-Kendall). Comparing results between the time series of RDI and SPI drought indices based on statistical indicators (RMSE < 0.434, R2 > 0.819 and T-statistic < 0.419) in all studied stations revealed that the behavior of the two indices was roughly the same and the difference between them was not significant. The trend analysis results of RDI and SPI indices based on modified Mann-Kendall test showed that the variation of dry and wet periods was decreasing in most of the studied stations (five cases were significant). In addition, the results of the trend line slope of dry and wet periods related to the drought indices in the studied area indicated that the slope was negative for SPI and RDI indices in 70% and 50% of stations, respectively. [ABSTRACT FROM AUTHOR]

Highlights • Drought events are identified based on an improved 3-D clustering algorithm. • Space-time drought characteristics are analyzed. • An increasing drought thermal stress has been detected within the past 35 years. Abstract Understanding the space-time structure and characteristics of drought is crucial for drought risk mitigation and forecasting efforts. In this paper, the drought events are identified by an improved 3-dimensional clustering algorithm. The 3-month Standardized Precipitation Evapotranspiration Index (SPEI3) is calculated based on the Climatic Research Unit (CRU) dataset from January 1966 to December 2015 to construct the longitude-latitude-time space. The characteristics of these identified events are described by a series of indicators such as duration, severity, intensity, affected area, centroids and track path after which the spatial pattern and temporal evolution are studied. In addition, the Vegetation Health Index (VHI), Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) are also included to investigate the possible impact of drought on the vegetation health. Results show that a total of 60 persisting drought events for at least 3 months have been identified in Central Asia. The most severe drought event occurred between May 1974 and January 1976 with a duration of 21 months and an affected area of 5.77 million km2. Most events have a duration between 3 and 5 months. In addition, the droughts in Central Asia tend to have an east-west trajectory. Seasonally, the study area experienced more drought months in spring and summer. During the recent 35 years, there has been a slowly increasing thermal stress and a significantly decreasing soil moisture stress that causes an overall decreasing drought stress on vegetation health. [ABSTRACT FROM AUTHOR]

Drought (similarly as flooding) is considerably the gravest agrometeorological extreme connected with climate change and bringing the highest losses in an agricultural production. The objective of this paper is to study the spatial and temporal variability of the Aridity Index (AI) in the Czech Republic, per decade, during the 55-year period (1961 - 2015). AI is a climatic index, which is important for recording of the drought phenomenon evolution. The climatic data used, include monthly precipitation totals and air temperature from 120 meteorological stations operated by the Czech Hydrometeorological Institute. The potential evapotranspiration was calculated based on the modified algorithm Penman-Monteith. The data processing was done by the statistical tools of Microsoft Excel and the Geographical Information Systems (Clidata GIS, ArcGIS 10). The results of the analysis showed, that during the decade 1961 - 1970, almost the whole area of the Czech Republic is classified as "wet" with AI values ranging above 0.60, but over the next years (1971 - 2015), areas of the south Moravia (e.g. Dyjsko-svratecký ravine, Valticko-lednický area, surroundings of Brno city), and also Prague city and Poohří river basin shifted gradually to "sub-humid" climate zone with AI < = 0.60. Especially, during the pre-last decade of the study period 1991 - 2000. [ABSTRACT FROM AUTHOR]

Drought is the most widespread and insidious natural hazard, presenting serious challenges to ecosystems and human society. The daily Standardized Precipitation Evapotranspiration Index (SPEI) has been developed to identify the regional spatiotemporal characteristics of drought conditions from 1960 to 2016, revealing the variability in drought characteristics across Southwest China. Daily data from142 meteorological stations across the region were used to calculate the daily SPEI at the annual and seasonal time scale. The Mann-Kendall test and the trend statistics were then applied to quantify the significance of drought trends, with the following results. 1) The regionally averaged intensity and duration of all-drought and severe drought showed increasing trends, while the intensity and duration of extreme drought exhibited decreasing trends. 2) Mixed (increasing/decreasing) trends were detected, in terms of intensity and duration, in the three types of drought events. In general, no evidence of significant trends (P < 0.05) was detected in the drought intensity and duration over the last 55 years at the annual timescale. Seasonally, spring was characterized by a severe drought trend for all drought and severe drought conditions, while extreme drought events in spring and summer were very severe. All drought intensities and durations showed an increasing trend across most regions, except in the northwestern parts of Sichuan Province. However, the areal extent of regions suffering increasing trends in severe and extreme drought became relatively smaller. 3) We identified the following drought hotspots: Guangxi Zhuang Autonomous Region from the 1960s to the 1990s, respectively. Guangxi Zhuang Autonomous Region and Guizhou Province in the 1970s and 1980s, and Yunnan Province in the 2000s. Finally, this paper can benefit operational drought characterization with a day-to-day drought monitoring index, enabling a more risk-based drought management strategy in the context of global warming. [ABSTRACT FROM AUTHOR]

This paper describes the improvements in the simulation of a heavy rainfall event due to the assimilation of surface wind observations from the Oceansat-2 scatterometer using ensemble Kalman filter (EnKF) technique. A heavy rainfall event over the southern peninsular region of India during the northeast Indian monsoon season is investigated in this paper using the Advanced Research Weather Research and Forecasting model. A control (CTRL) run where no surface wind observations are assimilated, as well as a 3-D variational (3DVar) run and an EnKF run wherein surface wind observations are assimilated using the 3DVar and EnKF techniques, is performed. Results indicate that the EnKF assimilation run simulates various meteorological fields, including precipitation fields during the rainfall event, better than the CTRL and the 3DVar runs. Qualitative and quantitative comparisons with Tropical Rainfall Measurement Mission precipitation observations indicate that the rainfall simulation shows improvement due to EnKF assimilation as compared with the other two model runs. Vertical profiles of area-averaged and time-averaged relative vorticities and temperature anomalies around the low-pressure system are also better reproduced in the EnKF experiment. Considering the importance of accurate real time simulations of heavy rainfall events associated with the Indian monsoon season, this paper provides encouraging results on the utility of EnKF technique as applied over the Indian region. [ABSTRACT FROM PUBLISHER]

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability ( p ) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62 ≤ p ≥ 0.8 in all the stations, though, the p -values for 10 day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days <0.30, but less reliable in the months of March, August and October (CV-RD > 0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. [ABSTRACT FROM AUTHOR]

The characterization of droughts and their impacts is very dependent on the time scale that is involved. In order to obtain an overall drought assessment, the cumulative effects of water deficits over different times need to be examined together. For example, the recently developed joint deficit index (JDI) is based on multivariate probabilities of precipitation over various time scales from 1- to 12-months, and was constructed from empirical copulas. In this paper, we examine the Gaussian copula model for the JDI. We model the covariance across the temporal scales with a two-parameter function that is commonly used in the specific context of spatial statistics or geostatistics. The validity of the covariance models is demonstrated with long-term precipitation series. Bootstrap experiments indicate that the Gaussian copula model has advantages over the empirical copula method in the context of drought severity assessment: (i) it is able to quantify droughts outside the range of the empirical copula, (ii) provides adequate drought quantification, and (iii) provides a better understanding of the uncertainty in the estimation. [ABSTRACT FROM AUTHOR]

The purpose of this research was to identify major drought events on the Spanish mainland between 1961 and 2014 by means of two drought indices, and analyze the spatial propagation of drought conditions. The indices applied were the standardized precipitation index (SPI) and the standardized evaporation precipitation index (SPEI). The first was calculated as standardized anomalies of precipitation at various temporal intervals, while the second examined the climatic balance normalized at monthly scale, incorporating the relationship between precipitation and the atmospheric water demand. The daily meteorological data from Spanish Meteorological Archives (AEMet) were used in performing the analyses. Within the framework of the DESEMON project, original data were converted into a high spatial resolution grid (1.1 km2) following exhaustive quality control. Values of both indices were calculated on a weekly scale and different timescales (12, 24 and 36 months). The results show that during the first half of the study period, the SPI usually returned a higher identification of drought areas, while the reverse was true from the 1990s, suggesting that the effect from atmospheric evaporative demand could have increased. The temporal propagation from 12- to 24-month and 36-month timescales analyzed in the paper seems to be a far from straightforward phenomenon that does not follow a simple rule of time lag, because events at different temporal scales can overlap in time and space. Spatially, the propagation of drought events affecting more than 25% of the total land indicates the existence of various spatial gradients of drought propagation, mostly east-west or west-east, but also north-south have been found. No generalized episodes were found with a radial pattern, i.e., from inland to the coast. [ABSTRACT FROM AUTHOR]

Regional precipitation patterns may change in a warmer climate, thereby increasing flood and drought risks. In this paper, annual, annual maximum, intense, heavy, moderate, light, and trace precipitation are employed as indicators to assess changes in precipitation patterns under two scenarios in which the global mean temperature increases by 1.5 °C and 2.0 °C relative to pre-industrial levels using the regional climate model COSMO-CLM (CCLM). The results show that annual precipitation in China will be approximately 2.5% higher under 1.5 °C warming relative to the present-day baseline (1980–2009), although it will decrease by approximately 4.0% under an additional 0.5 °C increase in global mean temperature. This trend is spatially consistent for regions with annual precipitation of 400–800 mm, which has experienced a drying trend during the past half century; thus, limiting global warming to 1.5 °C may mitigate these drying conditions. The annual maximum precipitation continues to increase from present day levels to the 2.0 °C warming scenario. Relative to the baseline period, the frequency of trace and light precipitation days exhibits a negative trend, while that of moderate, heavy, and intense precipitation days has a positive trend under the 1.5 °C warming scenario. For the 2.0 °C warming world, the frequency of days is projected to decrease for all precipitation categories, although the intensity of intense precipitation increases. Spatially, a decrease in the number of precipitation days is expected to continue in central and northern China, where a drying trend has persisted over the past half century. Southeastern China, which already suffers greatly from flooding, is expected to face more heavy and intense precipitation with an additional 0.5 °C increase in global mean temperature. Meanwhile, the intensity of intense precipitation is expected to increase in northern China, and the contribution of light and moderate precipitation to the annual precipitation is expected to decrease in southeastern China. Therefore, flood risk in northern China and drought risk in southern China should draw more attention for a global air temperature increase from 1.5 °C to 2.0 °C. [ABSTRACT FROM AUTHOR]

The statistical characteristics of precipitation play important roles not only in flood and drought risk assessments but also in water resource management. This paper implements a statistical analysis to study the spatial and temporal variability in precipitation in the upper reaches of the Hongshui River basin (UHRB), southwestern China, by analysing time series of daily precipitation from 18 weather stations during the period of 1959 to 2015. To detect precipitation concentrations and the associated patterns, three indices, the precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period (PCP), were used. The relationships between the precipitation concentration indices (PCI, PCD, and PCP) and geographic variables (latitude, longitude, and elevation), large-scale atmospheric circulation indices, and summer monsoon indices were investigated to identify specific dependencies and spatial patterns in the precipitation distribution and concentration. The results show that high PCI values were mainly observed in the northeastern portion of the basin, whereas low PCI values were mainly detected in the southwest. The Mann-Kendall test results demonstrate that the majority of the UHRB is characterized by nonsignificant trends in the PCI, PCD, and PCP from 1959 to 2015. The PCP results reveal that rainfall in the UHRB mainly occurs in summer months, and the rainy season arrives earlier in the eastern UHRB than in the western UHRB. Additionally, the PCD results indicate that the rainfall in the western UHRB is more dispersed throughout the year than that in the eastern UHRB. Compared with other geographical factors, longitude is the most important variable that governs the spatial distribution and variations in annual precipitation and the precipitation concentration indices. Due to a combination of topography, the Indian subtropical high, and monsoon weakening, precipitation may be more concentrated in one period, especially in the eastern part of the basin, which increases the risk of drought. [ABSTRACT FROM AUTHOR]

Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes, like heat and drought occurring simultaneously, may have a greater impact on society than their univariate counterparts and have recently become an active field of study. In this paper, we use a 12-member ensemble of high-resolution (7 km) regional climate simulations with the regional climate model COSMO-CLM over central Europe to analyze the climate change signal and its uncertainty for compound heat and drought extremes in summer by two different measures: one describing absolute (i.e., number of exceedances of absolute thresholds like hot days), the other relative (i.e., number of exceedances of time series intrinsic thresholds) compound extreme events. Changes are assessed between a reference period (1971–2000) and a projection period (2021–2050). Our findings show an increase in the number of absolute compound events for the whole investigation area. The change signal of relative extremes is more region-dependent, but there is a strong signal change in the southern and eastern parts of Germany and the neighboring countries. Especially the Czech Republic shows strong change in absolute and relative extreme events. [ABSTRACT FROM AUTHOR]

The interplay between extreme events in the Amazon’s precipitation and the anomaly in the temperature of the surrounding oceans is not fully understood, especially its causal relations. In this paper, we investigate the climatic interaction between these regions from 1999 until 2012 using modern tools of complex system science. We identify the time scale of the coupling quantitatively and unveil the non-stationary influence of the ocean’s temperature. The findings show consistently the distinctions between the coupling in the recent major extreme events in Amazonia, such as the two droughts that happened in 2005 and 2010 and the three floods during 1999, 2009 and 2012. Interestingly, the results also reveal the influence over the anomalous precipitation of Southwest Amazon has become increasingly lagged. The analysis can shed light on the underlying dynamics of the climate network system and consequently can improve predictions of extreme rainfall events. [ABSTRACT FROM AUTHOR]

In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China. [ABSTRACT FROM AUTHOR]

ABSTRACT Water scarcity is a critical issue in Iberia but few studies have investigated future drought over the region. The few that do are continental or global studies and do not report the range of possible future projections. In this paper, historical drought and future projections of drought were examined, using observed and downscaled rainfall data from climate models, for the main Iberian international basins (Douro, Tagus and Guadiana). Two drought indices were used, the standardized precipitation index ( SPI) and the drought severity index ( DSI). However, problems were found in the distribution fitting required for the calculation of SPI which render this index inadequate for assessing droughts in Iberia. The skill of CMIP5 climate models in representing historical drought for the Douro, Tagus and Guadiana is very variable with some not showing enough persistence of dry conditions, and others simulating droughts that are too long and too severe. Nevertheless, the observed range of drought conditions for these basins was encompassed by the ensemble members. Furthermore, we found no relationship between performance in simulating mean large-scale circulation and model ability to reproduce the historical drought characteristics for the region. All models project an intensification of drought conditions for the three basins. However, some only project small increases, while most project extreme multi-year droughts by the end of the century. We found that climate model future projections are neither related to their performance in simulating historical drought nor to their large-scale circulation patterns. This result emphasises the need for climate change impact studies to take into account the whole range of climate model projections in order to provide the best information for robust adaptation. Choosing one or a subset of climate models based on historical performance would not lead to a credible and justified reduction in uncertainty. [ABSTRACT FROM AUTHOR]

Consecutive dry days (CDDs) can serve as an effective measure of extreme precipitation and seasonal droughts. Using daily rain gauge data from 718 stations in China for the years 1961-2012, this paper documents the spatial and temporal characteristics of CDDs in the cold season (November to March) and the warm season (April to October). The results show that the long-term linear trends in CDDs have significant regional and seasonal differences. In the cold season, 57 % of the stations record decreases in CDDs, whereas in the warm season, 67 % of the stations record increasing trends. Applying the Ensemble Empirical Mode Decomposition (EEMD) to CDDs in selected regions, we found that 3-year oscillations account for most of the variance in CDDs, and this interannual variability is more pronounced in the cold season than in the warm season. Particularly in South China, CDDs in the cold season are most affected by oscillation of about a 3.3-year period. The decadal oscillations in CDDs over North China and the middle-lower reaches of the Yangtze River show larger variance than do other regions. Over North China, decadal variations in CDDs in both seasons are similar, with high phases during the 1990s and greater amplitude during the last 20 years, whereas over middle-lower reaches of Yangtze River, the amplitudes of decadal oscillations in CDDs decreased since the 1990s in both seasons. In terms of secular trends, significant increases in CDDs over Southwest China in the cold season and South China in the warm season are noteworthy as they contribute largely to CDD variance and experience sharper slopes in recent years. [ABSTRACT FROM AUTHOR]

The aim of this study is to test how effective and physically correct are the mathematical approaches of operational indices used by relevant National Agencies across the globe. To do so, the following indices were analysed Standardized Precipitation Index (SPI) -1, 3, 6, 12 and 24, Standardized Precipitation – Evapotranspiration Index (SPEI) – 1, 3, 6, 12 and 24, Effective Drought Index (EDI) and Index of Drying Efficiency of Air (IDEA). To make regions more comparable to each other and follow the spatial development of drought SPI index was advised by World Meteorological Organisation to be used widely by official meteorological services. The SPI and SPEI are used for Drought Early Warning in the USA, National Drought Mitigation Center and NASA, and in the EU by the European Drought Centre (EDC) and in the Balkan Region by National Meteorological Agencies. The EDI Index has wide application in Asia. In this paper four different issues were investigated: 1) how the mathematical method used in a drought indicator's computation influence drought indices' (DI) comparative analyses; 2) the sensitivity of the DIs on any change of the length of observational period; 3) similarities between the DIs time series; 4) and how accurate DIs are when compared to historical drought records. Results suggest that it is necessary to apply a few crucial changes in the Drought Monitoring and Early Warning Systems: 1) reconsider use of SPI and SPEI family indices as a measure of quality of other indices; and for Drought Early Recognition Programs 2) switch to DIs with a solid physical background, such as EDI; 3) Adopt solid physics for modelling drought processes and define the physical measure of drought, e.g. EDI and IDEA indices; 4) investigate further the IDEA index, which, supported by our study as well, is valuable for simulation of a drought process. [ABSTRACT FROM AUTHOR]

After the frequent and long drought episodes of the 1980s, a plethora of case studies have shown that West Africa remains a hot spot in the continent where despite its numerous water resources, extreme rainfall variability remains a profound challenge to the availability of freshwater for agriculture and ecosystem services. In this paper, we assess the recent flux in water availability over West Africa by investigating variations in net-precipitation (i.e. the maximum available freshwater flux) using wavelet analysis. Net-precipitation was obtained as a residual of the atmospheric water balance, and its variability compared to precipitation, temperature, evaporation, soil moisture and normalized difference vegetation index using wavelet power transforms and coherence analysis. Results from the study indicate that the variance in water flux over the region has been progressively reducing, suggesting a relative reduction in extreme hydrological conditions. Also, the wavelet coherence analysis revealed that the observed decreasing rate of available freshwater is highly coupled to a low frequency modulating El-Nino activity that induced lower changes in rainfall variance, as well as higher evaporation variance. Spatial trends in the annual-scaled average wavelet power indicated that the south-western parts of the region experienced the most reduction in rainfall flux. The highest deficit in net-precipitation flux was found in the dry sub-humid climatic zone, which is drained by major regional rivers, including the Niger and Volta. Considering the long-term variability in freshwater (i.e. from 1979 to 2010), we found the 1980s to be the driest decade and the 1990s being its recovery period, while the 2000s proved to be a considerably dry decade, suggesting a strong multi-decadal variability. [ABSTRACT FROM AUTHOR]

ABSTRACT After the frequent and long drought episodes of the 1980s, a plethora of case studies have shown that West Africa remains a hot spot in the continent where despite its numerous water resources, extreme rainfall variability remains a profound challenge to the availability of freshwater for agriculture and ecosystem services. In this paper, we assess the recent flux in water availability over West Africa by investigating variations in net-precipitation (i.e. the maximum available freshwater flux) using wavelet analysis. Net-precipitation was obtained as a residual of the atmospheric water balance, and its variability compared to precipitation, temperature, evaporation, soil moisture and normalized difference vegetation index using wavelet power transforms and coherence analysis. Results from the study indicate that the variance in water flux over the region has been progressively reducing, suggesting a relative reduction in extreme hydrological conditions. Also, the wavelet coherence analysis revealed that the observed decreasing rate of available freshwater is highly coupled to a low frequency modulating El-Niño activity that induced lower changes in rainfall variance, as well as higher evaporation variance. Spatial trends in the annual-scaled average wavelet power indicated that the south-western parts of the region experienced the most reduction in rainfall flux. The highest deficit in net-precipitation flux was found in the dry sub-humid climatic zone, which is drained by major regional rivers, including the Niger and Volta. Considering the long-term variability in freshwater (i.e. from 1979 to 2010), we found the 1980s to be the driest decade and the 1990s being its recovery period, while the 2000s proved to be a considerably dry decade, suggesting a strong multi-decadal variability. [ABSTRACT FROM AUTHOR]

• This paper presents a unique dataset that brings together data from meteorological sources on weather anomalies and night light emissions in 0.5 by 0.5-degree grid cells for the entire globe for the period 1992-2013. • This dataset allows researchers to investigate the economic impact of weather anomalies at an unprecedented geographical resolution. • We find that storms, excessive precipitation and cold spells indeed reduce the growth of economic activity visibly in the emission of night light at the local level. • We also show these negative effects do not tend to last long and generally cause positive spillovers in neighboring areas. How do weather anomalies affect the economy at the local level? This paper presents a new data set that links weather data to annual average night-light emission data for 24.000 0.5° × 0.5° grid-cells around the globe for the period 1992–2013. Interpreting night-light emission as a proxy for economic activity, these data allow one to investigate how weather anomalies affect economic activity. Global coverage avoids selection bias, while high spatial resolution avoids averaging out heterogeneity in local impacts at higher aggregation levels. Our data show significant effects on the local growth of night-light for storms, excessive precipitation, droughts, and cold spells. Moreover, we find evidence for significant spatial spillovers to neighboring areas. Our results suggest that these offsetting spillovers are typically local. As positive and negative effects average out in larger areas, our results call for the analysis of economic effects of weather anomalies at a high geographical resolution. Finally, our results are driven by events in lower income regions. As climate change is expected to make weather patterns more erratic, our new data can inform emerging debates on how this will affect the economy in both science and politics. [ABSTRACT FROM AUTHOR]

Various meteorological studies require probabilistic modeling such as the flood, drought, and wet and dry spell occurrences. The most commonly employed approaches are based on the binomial probability distribution function (pdf), which is valid for homogeneous temporal and spatial probabilities. However, in practice, heterogeneous probabilities are very common, and in this case, the classical binomial pdf cannot be employed. This paper presents a rigorous probabilistic methodology for heterogeneous probabilities by considerations from the random field concept. The general form of the binomial pdf is derived and it is shown that for homogeneous probabilities it yields the classical binomial pdf exactly. The necessary analytical formulations are derived with the assumption that the meteorological occurrences at a set of sites or time periods (day, month, and year) are independent from each other. The probability statements derived in this paper are helpful in predicting the regional and temporal probable potential future meteorological occurrences. The application of the proposed methodology is presented for annual precipitation occurrences at six meteorology stations around Istanbul, Turkey. [ABSTRACT FROM AUTHOR]

A comprehensive risk management strategy for dealing with drought should include both short-term and long-term planning. The objective of this paper is to present an early warning method to forecast drought using the Standardised Precipitation Index (SPI) and a non-homogeneous Markov chain model. A model such as this is useful for short-term planning. The developed method has been used to forecast droughts at a number of meteorological monitoring stations that have been regionalised into six (6) homogenous clusters with similar drought characteristics based on SPI. The non-homogeneous Markov chain model was used to estimate drought probabilities and drought predictions up to 3 months ahead. The drought severity classes defined using the SPI were computed at a 12-month time scale. The drought probabilities and the predictions were computed for six clusters that depict similar drought characteristics in Victoria, Australia. Overall, the drought severity class predicted was quite similar for all the clusters, with the non-drought class probabilities ranging from 49 to 57 %. For all clusters, the near normal class had a probability of occurrence varying from 27 to 38 %. For the more moderate and severe classes, the probabilities ranged from 2 to 13 % and 3 to 1 %, respectively. The developed model predicted drought situations 1 month ahead reasonably well. However, 2 and 3 months ahead predictions should be used with caution until the models are developed further. [ABSTRACT FROM AUTHOR]

ABSTRACT Trend analysis of precipitation and drought will play a significant role in the future development and sustainable management of water resources. It is the main purpose of this paper to analyse meteorological droughts and trends. The variability of the standardized precipitation index ( SPI) was investigated at 1, 3, 6, 9, 12 and 24 monthly intervals. The trends of 1, 3, 6, 9, 12 and 24 monthly SPI results were analysed by applying linear regression and the Mann- Kendall and Spearman's rho tests at the 5% significance level. The linear slopes of the trends were calculated with a technique proposed by Sen. Meteorological data from eight meteorological stations in the Aegean region of Turkey were used for the period 1960-2013. The monthly precipitation trend decreases in December, January, February and March in all regions according to the linear regression analysis results. Annual precipitation decreased at five stations. In drought analysis by the SPI, in a short time period (such as 3 months) drought is more frequent but shorter, and as the period increases the duration of drought also increases but frequency decreases. Winter droughts are beginning to occur in the class of 'severe' in recent years. In this study carried out for different time periods according to SPI values in all stations, the highest ranges are in the normal and mild drought degrees. In addition, severe and extreme droughts are also seen intensely frequently. Trend analysis of precipitation and drought is compared. The trend analyses of precipitation are in parallel with the results of drought analyses. [ABSTRACT FROM AUTHOR]

As shown by several authors, drought monitoring by the Standardized Precipitation Index (SPI) presents some uncertainties, mainly dependent on the choice of the probability distribution used to describe the cumulative precipitation and on the characteristics (e.g., length and variability) of the dataset. In this paper, the uncertainty related to SPI estimates has been quantified and analyzed with regards to the case study of the Abruzzo region (Central Italy), by using monthly precipitation recorded at 75 stations during the period 1951-2009. First, a set of distributions suitable to describe the cumulative precipitation at the 3-, 6-, and 12-month time scales was identified by using L-moments ratio diagrams. The goodness-of-fit was evaluated by applying the Kolmogorov-Smirnov test, and the Normality test on the derived SPI series. Then the confidence intervals of SPI have been calculated by applying a bootstrap procedure. The size of the confidence intervals has been considered as a measure of uncertainty, and its dependence on several factors such as the distribution type, the time scale, the record length, and the season has been examined. Results show that the distributions Pearson type III (PE3), Weibull (WEI), Generalized Normal (GNO), Generalized Extreme Value (GEV), and Gamma (GA2) are all suitable to describe the cumulative precipitation, with a slightly better performance of the PE3 and GNO distributions. As expected, the uncertainty increases as the record length and time scale decrease. The leading source of uncertainty is the record length while the effects due to seasonality and time scale are negligible. Two-parameter distributions make it possible to obtain confidence intervals of SPI (particularly for extreme values) narrower than those obtained by three-parameter distributions. Nevertheless, due to a poorer goodness of fit, two-parameter distributions can provide less reliable estimates of the precipitation probability. In any event, independently of the type of distribution, the SPI estimates corresponding to extreme precipitation values are always characterized by a relevant uncertainty. This is due to the explosion of the probability variability that occurs when precipitation values approach the tails of the supposed distribution. [ABSTRACT FROM AUTHOR]

Natural disasters are a major concern in Bangladesh, particularly drought which is one of the most common disaster in Bangladesh. Drought needs to be explained spatially to understand its spatiotemporal variations in different areas. In this paper, the meteorological drought has been shown by using the Standardized Precipitation Index (SPI) method and illustrated through the Inverse Distance Weighted (IDW) method across Bangladesh. We used rainfall data of 30 meteorological stations in Bangladesh during the study period of 1981–2010. The results indicate that drought has been fluctuating and it has become a recurrent phenomenon during the study period. The SPI depicted the drought conditions that plunged dramatically in 1981, 1982, 1985, 1987, 1989, 1992, 1994, and 1996 and then gradually improved in 2004, 2006, and 2009 in the country. The present study demonstrated that drought occurred in Bangladesh on an average of 2.5 years. Drought was more prominent in the northern, south-western, and eastern regions in Bangladesh compared to the rest of the areas of the country. The outcomes of the present study will help in during disaster management strategies, particularly drought, by initiating effective plans and adaptation remedies in different areas of Bangladesh. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

Drought indices are commonly used for detection, monitoring and evaluation of drought events. One of the most commonly used drought indices is the Standardized Precipitation Index (SPI). This paper presents the effect of theoretical distribution selection on SPI values, and the analysis of drought events for five selected meteorological stations in Slovenia. We found that the SPI on the annual time scale shows a similar pattern of occurrence of dry and wet periods at Ljubljana-Bežigrad, Novo mesto, and Trieste meteorological stations; something similar can be said for the Celje and Maribor-Tabor stations. The analysis of the correlations between the standardized data river discharge and precipitation data for the selected river basin of the River Pesnica shows the strongest correlation between the SPI-2 and standardized discharges. [ABSTRACT FROM AUTHOR]

The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., 'idealized but realistic' forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. [ABSTRACT FROM AUTHOR]

The aim of the present paper was to improve understanding of the rainfall dynamics in Bas-Congo and Kinshasa provinces, in Democratic Republic of Congo (DRC). The first objective of the study was achieved by analysing the spatial correlations of monthly, seasonal, annual and individual monthly rainfall amounts of Kinshasa and Bas-Congo. The second objective was achieved through investigating and quantifying the temporal trends and their spatial variations. The results demonstrated notably high average inter-station correlation of +0.63 for dry season series, followed by monthly rainfall series with an average inter-station correlation of +0.58. However, there was no station with a stable monthly rainfall regime, i.e. with mean precipitation concentration index lower than 10% (it varies between 14.2 and 21.9%). Moreover, Kinshasa experienced an increase of rainfall with an average annual rate of change of +4.59 mm/year for the period 1961–2006. The results will be helpful for efficient water resources management and for mitigating the adverse impacts of future extreme drought or flood occurrences.Editor M.C. Acreman Associate editor N. Verhoest [ABSTRACT FROM PUBLISHER]

China is a nation that is affected by a multitude of natural disasters, including droughts and floods. In this paper, the variations of extreme drought and pluvial patterns and their relations to the large-scale atmospheric circulation have been analyzed based on monthly precipitation data from 483 stations during the period 1958–2010 in China. The results show the following: (1) the extreme drought and pluvial events in China increase significantly during that period. During 1959–1966 timeframe, more droughts occur in South China and more pluvial events are found in North China (DSC-PNC pattern); as for the period 1997–2003 (PSC-DNC pattern), the situation is the opposite. (2) There are good relationships among the extreme drought and pluvial events and the Western Pacific Subtropical High, meridional atmospheric moisture flux, atmospheric moisture content, and summer precipitation. (3) A cyclone atmospheric circulation anomaly occurs in North China, followed by an obvious negative height anomaly and a southern wind anomaly at 850 hPa and 500 hPa for the DSC-PNC pattern during the summer, and a massive ascending airflow from South China extends to North China at ~50∘N. As for the PSC-DNC pattern, the situation contrasts sharply with the DSC-PNC pattern. [ABSTRACT FROM AUTHOR]

In common with much of the western United States, the Pacific Northwest (defined in this paper as Washington and Oregon) has experienced an unusual number of droughts in the past decade. This paper describes three of these droughts in terms of the precipitation, temperature, and soil moisture anomalies, and discusses different drought impacts experienced in the Pacific Northwest (PNW). For the first drought, in 2001, low winter precipitation in the PNW produced very low streamflow that primarily affected farmers and hydropower generation. For the second, in 2003, low summer precipitation in Washington (WA), and low summer precipitation and a warm winter in Oregon (OR) primarily affected streamflow and forests. For the last, in 2005, a lack of snowpack due to warm temperatures during significant winter precipitation events in WA, and low winter precipitation in OR, had a variety of different agricultural and hydrologic impacts. Although the proximal causes of droughts are easily quantified, the ultimate causes are not as clear. Better precipitation observations in the PNW are required to provide timely monitoring of conditions leading to droughts to improve prediction in the future. [ABSTRACT FROM AUTHOR]