Search

ABSTRACT It has been broadly reported that future climate change will most likely affect the spatio‐temporal distribution of water resources and consequently droughts. There is a prevailing notion that an increase in temperature and frequency of heat waves are expected to result in more intense droughts in the coming years. In this study, we aimed to evaluate the effect of the potential evapotranspiration (PET) method selection on future drought projections over Poland. In our study, simulations of the Soil and Water Assessment Tool (SWAT) model were conducted, utilising an ensemble of six EURO‐CORDEX projections, spanning the period from 2006 to 2100 under the RCP8.5 scenario. Two model setups with two different PET methods (Penman‐Monteith—PM and Hargreaves—HAR) were used. For drought conditions evaluation we selected the Standardized Precipitation Index (SPI) and Standardized Precipitation‐Evapotranspiration Index (SPEI) for meteorological drought, Standardized Streamflow Index (SSI) for hydrological drought, and Standardized Soil Moisture Index (SMI) for agricultural drought. The meteorological and hydrological droughts were calculated using a 12‐month time aggregation window, while agricultural drought was calculated using a 3‐month window. Climate projections revealed that by 2080s annual mean temperature and precipitation increase is expected by up to +3.4°C and +10.3% respectively. Under future climate conditions duration and severity of meteorological droughts are projected to decrease. PM method leads to a higher PET increases (1.35 mm year−1) than the HAR method (1.1 mm year−1) throughout the century which entail diverging signal of change for agricultural and hydrological droughts. PM‐ and HAR‐based simulations indicate increase in the total duration and cumulative severity of agricultural droughts, buthowever, for HAR‐based projections, the increase is much less. For hydrological droughts the signal of change is similar for both PET methods, but considerably distinct in magnitude. Considering the entire simulation period, by the end of the century cumulative severity of hydrological droughts is projected to decrease, with a much more pronounced decline for HAR (70% reduction) than for the PM method (35% reduction). Our study demonstrated that methodological choices are crucial to the assessment of future drought risk under climate change. [ABSTRACT FROM AUTHOR]

This study assesses the intensity, spatial distribution and temporal variability of extreme precipitation events (EPEs) on different time scales relevant to agriculture and water resources during the 1901–2016 period over Argentina's Austral Chaco (ACh). EPEs were identified using a nonparametric approach for the Standardized Precipitation Index (SPI). The leading modes of SPI's variability were detected using the Singular Spectrum Analysis. We also compile and control the quality of precipitation observations in a scarcely monitored region. The limited number of stations conditions the interpolation of the GPCC v2018 database here used, mainly during the early twentieth century. The EPEs characterized by SPI at a 24‐month time scale, which favour long‐lasting water excesses or deficits with hydrological impacts, underwent two differentiated long‐term periods: a dry one before 1960 and a wet one from 1960 to 2005. Consistently, seasonal wet EPEs were more frequent during the wet period while seasonal droughts were more frequent and with larger spatial extent during the dry period. Seasonal EPEs, represented by the SPI at 3‐month time scale, can impact agriculture during the crops' critical growth period. Since 2006, the long‐term wetting trend has been reversed. If this behaviour continues into the coming decades, more droughts and less wetness might be expected. The EPEs present a large interannual variability with 6.3‐ and 9‐year significant cycles that, combined with long‐term trends, favoured extremely wet/dry EPEs. Most of the wet/dry EPEs occurred during El Niño/La Niña events. Although this relationship is not straightforward, we found a discriminant ENSO signal between October of the year when an ENSO event starts and February of the next year. Finally, severely dry/wet EPEs tend to have large spatial extent in the ACh region. The central‐eastern ACh region experiences the most extreme wet and dry conditions, which makes this area more prone to extreme EPEs. [ABSTRACT FROM AUTHOR]

We studied spatial and temporal patterns of precipitation–temperature (P–T) relationships through correlations between monthly standardized precipitation index (SPI) and monthly temperature anomalies in individual climatic seasons over Europe. In the observed data (represented by E‐OBS), positive correlations (wet–warm/dry–cold relationships) prevail during winter over most of Europe, while negative values (dry–warm/wet–cold) are dominant in summer. In the next step, an ensemble of seven regional climate models (RCMs) from the CORDEX project driven by the ERA‐Interim reanalysis were examined as to their reproduction of the regional patterns of the P–T correlations. In winter, the RCMs yielded overly strong positive P–T correlations over northern Europe, while the correlations were too weak in the south compared to observed data. During summer, the biases were generally larger; the RCMs were able to capture the overall negative P–T correlations but these tended to be too weak over northern Europe. This deficiency was found to be linked to simulated differences in shortwave radiation (a proxy for cloud cover) between dry and wet months. In western, central, and southeastern Europe, by contrast, most RCMs yielded too strong negative correlations in summer, and overly large decreases of relative humidity during dry months probably contributed to these errors. The results pointed up issues that should be addressed as the reported RCMs' deficiencies may lower credibility of projected compound dry–hot events in climate change scenarios. [ABSTRACT FROM AUTHOR]

It is a good practice to follow common guidelines in the computation of Standardized Precipitation Index (SPI) data sets as part of operational drought monitoring systems. In the European Drought Observatory (https://edo.jrc.ec. europa.eu/), reference statistics are computed following the World Meteorological Organization Guidelines on the Calculation of Climate Normals, where a definition of the reference period for monitoring applications is introduced as the most recent 30-year period finishing in a year ending with 0. In this study, the temporal consistency of the SPI time series computed using the fifthgeneration European Centre for Medium-range Weather Forecast reanalyses model precipitation data set is tested over Europe to quantify the effect of the transition from one baseline period (1981–2010) to another (1991–2020) and to evaluate the capability of these static baselines to reproduce the behaviour of non-stationary SPIs (nSPIs). The results of the comparison suggest that the threshold commonly used to identify droughts (SPI = −1) is only marginally affected by the change in reference period (mean absolute deviation, MAD = 0.15 ± 0.1) for short-term SPI, whereas larger differences (MAD up to 0.6) can be observed over certain areas (i.e., Southern Italy and Eastern Europe) for longer accumulation periods (i.e., SPI-9 or SPI-12). Examples show that changes in drought classification from extremely dry (SPI < −2) to moderately dry (SPI < −1) are not uncommon, which may lead to misinterpretation by users. Finally, analyses against nSPI highlight an overall good correspondence between stationary and nSPIs, even if both static baselines displayed difficulties in reliably capturing the magnitude of nSPI for the entire 10-year period for which they should be used. In this regard, it has been demonstrated that more spatially uniform results can be achieved with 5-year updates, with a good matching (MAD <0.25) for SPI-1 and an acceptable matching (MAD < 0.50) for SPI-12 over more than 80% of Europe. [ABSTRACT FROM AUTHOR]

We applied the informational approach of the Fisher‐Shannon method to study the time series of Standardized Precipitation Index (SPI) derived from monthly rainfall data at 133 gauging stations in Northeast (NE) Brazil. The climate in the study region ranges from tropical humid in the coastal area Zona de Mata to tropical semiarid inland Sertão, passing through a sub‐humid transition region Agreste. The time span is from 1962 to 2012, and SPI was calculated for 1, 3, 6, and 12 ‐ month time scales. We calculate information quantifiers Shannon entropy power (SEP) and Fisher information measure (FIM) that quantify signal disorder and structural organization, respectively, and define its position in the Fisher Shannon plane (FS). We find that the SPI‐1 series that describes short term dry/wet conditions display a higher degree of organization (higher FIM) and a lower degree of disorder (lower SEP) than SPI's that describe medium and long term conditions (SPI‐3, SPI‐6, and SPI‐12). By analysing the spatial distribution of information quantifiers, we find that short term dry/wet conditions (SPI‐1) show the lowest disorder and highest organization degree in the deep inland Sertão region and highest disorder and lowest organization degree in the coastal Zona de Mata region, while long term conditions (SPI‐12) show the opposite trend. For medium‐term conditions (SPI‐3 and SPI‐6), the SEP is highest and FIM lowest in the transition sub‐humid Agreste region. Our findings indicate that information theory‐based methods, particularly FS have the potential to discriminate among different climatic regimes. [ABSTRACT FROM AUTHOR]

We analysed long‐term variability and trends in meteorological droughts across Western Europe using the Standardized Precipitation Index (SPI). Precipitation data from 199 stations spanning the period 1851–2018 were employed, following homogenisation, to derive SPI‐3 and SPI‐12 series for each station, together with indices on drought duration and severity. Results reveal a general absence of statistically significant long‐term trends in the study domain, with the exception of significant trends at some stations, generally covering short periods. The largest decreasing trends in SPI‐3 (i.e., increasing drought conditions) were found for summer in the British and Irish Isles. In general, drought episodes experienced in the last two or three decades have precedents during the last 170·years, emphasizing the importance of long records for assessing change. The main characteristic of drought variability in Western Europe is its strong spatial diversity, with regions exhibiting a homogeneous temporal evolution. Notably, the temporal variability of drought in Western Europe is more dominant than long‐term trends. This suggests that long‐term drought trends cannot be confirmed in Western Europe using precipitation records alone. This study provides a long‐term regional assessment of drought variability in Western Europe, which can contribute to better understanding of regional climate change during the past two centuries. [ABSTRACT FROM AUTHOR]

Drought patterns are better understood by analysing the joint dependence among long‐term drought characteristics: severity, duration, and frequency. Changes in these drought characteristics are also likely due to potential climate change, for instance, increased drought severity and duration, increased frequency of drought events, and increased spatial extent of drought impacts. In this study, we performed a regional‐scale analysis of potential changes in meteorological drought characteristics in a tropical region in India under a warming future climate scenario. The meteorological drought characteristics were computed using the Standardized Precipitation Index. The Coordinated Regional Downscaling Experiment South Asia Regional Climate Model future precipitation simulation under the RCP 4.5 scenario was bias‐corrected and utilized for future drought frequency analysis. Regionalization of meteorological drought characteristics was performed using the simple k‐means clustering technique to identify the homogeneous regions for baseline and future periods. Bivariate copula was utilized to model the dependence among the drought characteristics in order to develop the S‐D‐F curves. The changes in regionalization and regional S‐D‐F curves under future potential climate change were then investigated. The results of the study suggest an increase in drought severity by 2–3% for long‐term droughts (duration more than 5 months) in the future as indicated by upward shift and changes in the slope of the regional S‐D‐F curves. There is a projected increase in the occurrence of long‐term droughts in the future when compared to short‐term (duration of 1 to 3 months) droughts. We also observed a considerable spatial shift of drought hotspots, the severe drought‐prone regions lie in the eastern part of the study region in the future. Future projections of regional S‐D‐F curves and Spatio‐temporal drought characteristics obtained from the proposed framework may be utilized for devising drought mitigation strategies. [ABSTRACT FROM AUTHOR]

Meteorological droughts have large impacts on society and the environment. A better understanding and quantification of their occurrences can be highly relevant for the development of proper climate change mitigation, adaptation and resilience strategies. Here we examine meteorological droughts from observed data covering the 1971–2000 period for the Fulda catchment in Germany by means of the Standardized Precipitation Index. The joint dependency of drought duration and severity is modelled by a copula function, which relates their univariate distributions in a functional relationship. Recurrence intervals are further calculated as a function of the joint relationship and univariate marginals. Future projections are investigated in which downscaled EURO‐CORDEX Regional Climate Model (RCM) projections for the period 2021–2050 are used together with the three Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5, in order to analyse and compare future joint patterns of duration and severity of events. We find that drought duration and severity present a clear interdependency supporting the choice of a bivariate model. Results suggest substantial differences in the future joint relationship duration–severity. Depending on the RCM and RCP, drought patterns show different magnitude of changes in the future. The projected changes are different for the different returns periods. RCP8.5 shows more severe events and longer drought durations than RCP2.6 and RCP4.5. The uncertainties of the projected patterns also depend on the RCP and RCM and are larger for higher return periods. [ABSTRACT FROM AUTHOR]

Iran has a predominantly arid and semi‐arid climate where the drought hazards and their variability are the crucial concerns for water resources management. This study assesses the characteristics and trends of meteorological droughts features in different climate regions of Iran. Monthly rainfall data are analysed using Standardized Precipitation Index (SPI) to reconstruct meteorological droughts for different time steps (1, 3, 6, 9 and 12). The drought events are decomposed into three features, namely Severity (S), Duration (D) and Peak (P) to assess their spatial variations in different climate regions. The Mann–Kendall (MK) test is used to detect the trends in drought features in different climate regions. The percentage area (PA) of increasing/decreasing trend in drought features is computed to assess the spatial variations of trends in each region. Besides, SPI is compared with Standardized Precipitation Evapotranspiration Index (SPEI) to understand the importance of evapotranspiration on meteorological droughts. The high correlations between SPI and SPEI indicate that the results obtained using SPI would not vary if a similar analysis is conducted using SPEI. The results obtained using SPI reveal that short‐duration droughts (6 months or less) are more frequent and severe in the northwest and the north along the Caspian plains while the longer‐duration droughts (more than 6 months) are more frequent and severe in the south, southeast and southwest. Overall, the northwest region of Iran is found most susceptible to droughts in terms of S, P and D. Moderate (40% < PA < 60%) or significant (PA > 60%) increase in the drought features are observed in all climate regions for shorter SPI (3 months or less) except northwest, while no drought feature is found to increase significantly for SPI‐12. Overall, the higher increase in drought S, P and D are found in the central arid region and at higher altitudes. [ABSTRACT FROM AUTHOR]

It is generally accepted that El Niño–Southern Oscillation (ENSO) is the main modulator of rainfall variability over Northern South America in the interannual scale. Assuming that, an index is proposed to quantify this expected interannual variability in time series of rainfall. The result is the exposure assessment to the effects of droughts, measured with the Standardized Precipitation Index (SPI) for the monthly scale. The SPI is calculated from rainfall series, and wavelet analysis is used to estimate the variance for different frequencies present in the signal. The Wavelet Interannual Variability Index (WIVI) is calculated as the sum of the wavelet coefficients over a predetermined range of modes of variability (with periods longer than 2 year and shorter than 8 years). The index was tested using a dataset of rainfall records from Tocantins state, Central Brazil. Most of the series ranged from 1974 to 2012. On average, the series had 3.2% of gaps which were not filled to avoid the effect of artificial trends on the data. The state lies mostly over the Cerrado biome and is a new frontier of agricultural development in Brazil. According to the results, the Northern region is under higher exposure of interannual variability, with higher values of WIVI. The assessment is in agreement with large‐scale features of South American climate, specifically considering the influences of the Pacific and Atlantic Oceans and their patterns of sea surface temperature (SST). Interannual variability of rainfall was quantified by applying wavelet decomposition to time series of Standardized Precipitation Index (SPI). The wavelet variance for time scales of 2–8 years was quantified for 36 stations over Tocantins, Central Brazil. The variability within those scales was normalized as the Wavelet Index of Interannual Variability (WIVI). According to results, the Northern region is under higher exposure of interannual variability, with higher values of WIVI. The assessment is in agreement with large‐scale features of South American climate, specifically considering the influences of the Pacific and Atlantic Oceans and their patterns of sea surface temperature (SST). [ABSTRACT FROM AUTHOR]

ABSTRACT: Enhancing the capability of both standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) for quantifying wet and dry events under distinct climate conditions is of paramount importance. The different recommendations of recent studies regarding the best distribution to calculate the SPEI and the lack of studies addressing the effect of different parameters estimation methods on the SPI motivated us to apply and adapt distinct testing methodologies to select candidate models for calculating these standardized drought indices (SDI). The study is based on two data sets. The first represents a tropical–subtropical region of Brazil. The second comprises the same weather stations that were used for developing the original version of the SPEI. The study also emphasized the performance of the models within the range of typical SDI values [−2.0 : 2.0]. Along with goodness‐of‐fit tests, we calculated the mean absolute errors between the indices values estimated from the candidate distributions, and their corresponding theoretical values derived from the standard normal distribution. The two‐parameter gamma and the generalized extreme value distributions are, respectively, recommended for general use in SPI and SPEI algorithms (1–12‐month timescales). The unbiased probability weighted moments are recommended to estimate the distributions parameters. The study also described a trade‐off between choosing the best model for the central part and for the tails of the distributions. This trade‐off suggests that the methodologies used to select models for the SDI algorithms may have to decide which part of the distribution (central or tails) should be emphasized. The behaviour of the errors among different wet/dry categories showed that both indices were only capable of representing drought and floods in a similar probabilistic way within the range [−2.0 : 2.0]. This feature supports our decision to emphasize model performances within such range. [ABSTRACT FROM AUTHOR]

ABSTRACT: Ocean and atmospheric patterns associated with the most severe and most persistent droughts in the Mexican Altiplano region are explored. The standardized precipitation index on a time scale of 12 months was used and compared with time series of other atmospheric conditions to identify major dry episodes from 1970 to 2012. The time series were derived from the second mode of a varimax‐rotated empirical orthogonal functional analysis from the mean summer rainfall series observed at weather stations located in the Mexican Altiplano from 1970 through 2000. The results showed that the longest and most persistent episode occurred from 1998 through 2001, while the most severe dry episode occurred in 2011–2012, when the Pacific Decadal Oscillation was in a negative phase and the Atlantic Multidecadal Oscillation in a positive phase, both in combination with a La Niña event. A large upper‐level anticyclone over the north‐central United States is related to droughts in the Altiplano. Under these conditions, the droughts were linked to a large anticyclone positioned over the central‐north of the United States, with consequent negative anomalies of specific humidity over central‐northern Mexico. Concurrent with droughts in the interior of Mexico, are positive rainfall anomalies along the central Pacific coast of Mexico near the study area. Under different atmospheric conditions, opposite anomalous behaviour between the coast and interior can exist. The mechanism driving this see‐saw behaviour between the west coast of Mexico and the Altiplano is explored. [ABSTRACT FROM AUTHOR]

ABSTRACT: Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather‐pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI‐based drought months. The new weather‐pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation‐based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra‐pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification‐based analyses in the UK. [ABSTRACT FROM AUTHOR]

ABSTRACT Tajikistan is an exceptionally vulnerable Central Asian country in the face of climate change due to its' high exposure and sensitivity to climate change combined with poor adaptation capacity. Therefore, comprehensive climate data are needed for efficient planning of mitigation and adaptation. Here, the key spatio-temporal features of Tajikistan's climate were analysed based on historical data from 52 stations with the longest time-series covering nearly 80 years. In addition, bias-corrected CMIP5 climate models were used to simulate future temperature and precipitation conditions across a range of time periods and greenhouse gas emission scenarios. The results show that the mean annual temperatures have risen in Tajikistan since the 1930s, average rate of change being approximately 0.1 °C decade−1. For precipitation, only a weak signal of change could be detected. The high-resolution (30 arc seconds) spatial analyses reveal the strong control of topography on Tajikistan's climate with such coupling leading mean annual air temperatures to vary from −13.7 °C (eastern mountain regions) to 17.3 °C (low-altitude plains). Similarly, the mean annual precipitation vary from less than 50 mm to over 1000 mm, spring being the wettest of the seasons. The future climate simulations suggest drastic increase in air temperatures; at the end of this century the temperature multi-model mean can be approximately 2 °C (Representative Concentration Pathways, RCP2.6) to 7 °C ( RCP8.5) higher compared to 1961-1990. Precipitation scenarios indicate increase in the eastern part of the country and decrease in the west. Finally, the applied spatial uncertainty analyses stress the need for the future development of the climate station network especially in high-elevation areas associated with complex topography. These results show the pronounced climatic variation in Tajikistan and the expected near- and long-term changes in air temperature and precipitation conditions, thus forming a sound basis for future planning of national mitigation and adaptation activities. [ABSTRACT FROM AUTHOR]

ABSTRACT: Spatio‐temporal drought characteristics related to weak, moderate, and strong El Niño events in the Indonesian region were investigated. The empirical orthogonal function (EOF) patterns of normalized monthly precipitation and Standardized Precipitation Index (SPI) for the period 1950–2010 were analysed; the influence of El Niño events are better represented by SPI. The effects of El Niño events on meteorological drought were investigated based on a composite analysis. The effects of El Niño were more obvious during June–July–August and September–October–November, while they were not significant in March–April–May especially during weak and moderate El Niño events. Spatial distributions of affected areas varied by season, intensity of El Niño events, and local factors. During moderate and strong El Niño events, meteorological drought was more common in southern Sumatra, Java, Bali, Nusa Tenggara, southeastern Kalimantan, Sulawesi, Maluku, and Papua. Based on the spatial and temporal variability of droughts, the monthly or seasonal meteorological drought outlook can be improved by using SPI focusing more on the regions and seasons that are affected by El Niño events. The multi‐model ensemble (MME) forecast of SPI performed better for the target months of September to November even at medium lead times. The months are consistent with the period of serious El Niño effects on drought, implying that serious drought conditions during the most harshly affected season can be predicted using the MME forecast. [ABSTRACT FROM AUTHOR]

This work created a 250-year historic drought catalogue by applying the Standardized Precipitation Index (SPI) to the Island of Ireland precipitation network (1850-2015) and a reconstructed precipitation series from 1765. Documentary sources from newspaper archives spanning the last 250 years, together with other historical sources are used to (1) add confidence to the quantitative detection of drought episodes and (2) gain insight to the socio-economic impacts of historic droughts. The results show that Ireland is drought prone but recent decades are unrepresentative of the longer-term drought climatology. A large decline in 30-year accumulated SPI-12 values is evident from around the 1990s onwards. During the years 1850–2015 seven major drought rich periods were identified with an island-wide fingerprint in 1854–1860, 1884–1896, 1904–1912, 1921–1923, 1932–1935, 1952–1954 and 1969–1977. These events exhibit substantial diversity in terms of drought development, severity and spatial occurrence. Two exceptionally long events are found in the record: the continuous drought of 1854–1860 and the drought of 1800–1809 (in fact a series of three droughts with brief interludes). Over the last 250 years, droughts have resulted in agricultural hardship, water resource crises and failures and preceded some of the major famines of the eighteenth and nineteenth centuries. This work shows that newspaper archives can be used to trace the progression of drought events and impacts and we thus advocate their wider use in corroborating quantitative assessments. The resulting catalogue challenges prevailing perceptions about drought in Ireland while strengthening the evidence base for future drought and water resource planning across the island. [ABSTRACT FROM AUTHOR]

Correlations between wet/dry variations and El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO) across the Pearl River basin were analysed at annual and seasonal time scales using the Pearson correlation and moving correlation coefficient. The basin was divided into homogeneous climate zones using the fuzzy C-means method. The influences of ENSO, NAO, IOD, and PDO on annual and seasonal wet/dry variations and impacts of warm and cold episodes of these indices on Standardized Precipitation Index-based dry and wet conditions were investigated. Furthermore, the mechanisms of the influences were tried to be analysed from the perspective of moisture transmission. The results indicated that: (1) IOD, NAO, and ENSO are the principle factors driving annual, wet, and dry seasonal precipitation variations, respectively. Moreover, opposite correlations can be identified between precipitation and IOD, NAO, and ENSO in the same/previous year; (2) Correlations between precipitation variations at different time scales and climate indices are strongly stable. Furthermore, climate indices tend to have more significant and stable impacts on precipitation variations during the dry season than on annual precipitation and precipitation variations during the wet season; (3) There exist differentmoisture convergence and divergence phenomena in the Pearl River basin under anomalous year of climate indices, so the annual, wet, and dry seasonal precipitation characteristic will be affected; (4) ENSO exhibits remarkable impacts on the variations of dry conditions; and meanwhile ENSO and IOD have significant impacts on the variations of wet conditions. In general, the cold phase of climate indices tends to trigger a higher risk of droughts, and the warm phase of climate indices tends to cause higher rates of extreme wet conditions. Taking different climate indices as predictors, this study may help forecast precipitation variations at different time scales. [ABSTRACT FROM AUTHOR]

ABSTRACT Correlations between wet/dry variations and El Niño-Southern Oscillation ( ENSO), North Atlantic Oscillation ( NAO), Indian Ocean Dipole ( IOD), and Pacific Decadal Oscillation ( PDO) across the Pearl River basin were analysed at annual and seasonal time scales using the Pearson correlation and moving correlation coefficient. The basin was divided into homogeneous climate zones using the fuzzy C-means method. The influences of ENSO, NAO, IOD, and PDO on annual and seasonal wet/dry variations and impacts of warm and cold episodes of these indices on Standardized Precipitation Index-based dry and wet conditions were investigated. Furthermore, the mechanisms of the influences were tried to be analysed from the perspective of moisture transmission. The results indicated that: (1) IOD, NAO, and ENSO are the principle factors driving annual, wet, and dry seasonal precipitation variations, respectively. Moreover, opposite correlations can be identified between precipitation and IOD, NAO, and ENSO in the same/previous year; (2) Correlations between precipitation variations at different time scales and climate indices are strongly stable. Furthermore, climate indices tend to have more significant and stable impacts on precipitation variations during the dry season than on annual precipitation and precipitation variations during the wet season; (3) There exist different moisture convergence and divergence phenomena in the Pearl River basin under anomalous year of climate indices, so the annual, wet, and dry seasonal precipitation characteristic will be affected; (4) ENSO exhibits remarkable impacts on the variations of dry conditions; and meanwhile ENSO and IOD have significant impacts on the variations of wet conditions. In general, the cold phase of climate indices tends to trigger a higher risk of droughts, and the warm phase of climate indices tends to cause higher rates of extreme wet conditions. Taking different climate indices as predictors, this study may help forecast precipitation variations at different time scales. [ABSTRACT FROM AUTHOR]

ABSTRACT East China ( EC) has experienced a number of severe droughts in recent decades. Understanding the characteristics of droughts and their persistence will provide operational guidelines for water resource management and agricultural production. This study uses a logistic regression model to measure the probability of drought occurrence in the current season given the previous season's Standardized Precipitation Index ( SPI) and Southern Oscillation Index ( SOI) as well as drought persistence. Results reveal large spatial and seasonal variations in the relationship between the previous season's SPI and the drought occurrence probability in a given season. The drought persistence averaged over the entire study area for all the four seasons is approximately 34% with large variations from season to season and from region to region. The East and Northeast regions have the largest summer drought persistence (∼40%) and lowest fall drought persistence (∼28%). The spatial pattern in winter and spring drought persistence is dissimilar with stronger winter and weaker spring drought persistence in the Southwest and Northeast relative to other regions. Logistic regression analysis indicates a stronger negative relationship in summer-to-fall (or between fall drought occurrence and summer SPI) than other inter-season relationships. Most of the stations with significant relationships in summer-to-fall lie in the East and the southern part of the North region. Significant negative relationships in winter-spring and fall-winter are primarily located on the western portion of the study area. A significant negative spring-summer relationship exists in the North region. Further, spring drought occurrence has a statistically significant positive relationship with winter SOI in the Southeast. Fall drought occurrence and summer SOI are negatively correlated in the northwest portion of EC (i.e. the border of North and Southwest regions). Overall, this study demonstrates that the impact of previous season SPI and SOI on current season drought varies substantially from region to region and from season to season. This study also shows stronger drought persistence in summer than in other seasons. In other words, the probability of fall drought occurrence is closely related to summer moisture conditions in the EC. [ABSTRACT FROM AUTHOR]

ABSTRACT Prediction of droughts has a great importance in the management and planning of water resources. This study developed an adaptive neuro-fuzzy inference system ( ANFIS) based model for prediction of droughts, and evaluated its applicability in the seven homogeneous rainfall zones of the East Asian monsoon region (20°-50°N, 103°-149°E). Standardized Precipitation Index ( SPI) was used to characterize the drought events. SPI series were computed for each zone using a 30-year (1978-2007) gridded rainfall dataset (0.5° grid resolution) at the corresponding grid points. The influence of sea surface temperature anomalies ( SSTA) on droughts was assessed using a lagged-correlation between global gridded SSTA (0.2° grid resolution) and the SPI of each zone. SSTA were used as a potential predictor variable based on the premise that the land-sea thermal contrast is a major driver of the monsoon. The model was trained and validated using a 25-year (1978-2002) dataset, with different configurations to obtain the optimum model structure and a set of suitable predictors. The performance of the model was demonstrated by comparing the model simulated results with the observed drought index and drought categories using a 5-year (2003-2007) independent checking dataset. The model predicted the drought categories accurately for 50 to 70% cases in checking period for different zones. The results showed the viability of the proposed model for drought prediction with substantial enhancement in accuracy when past SSTA were used as a predictor compared with the use of only past SPI data. [ABSTRACT FROM AUTHOR]

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

ABSTRACT This article addresses the regional impacts of climate change on precipitation and meteorological drought over Southern South America ( SSA) through a CMIP5 multi-model ensemble based on 15 General Circulation Models ( GCMs) forced under two different greenhouse gas concentration pathways ( RCP4.5 and RCP8.5). An assessment of the biases in the representation of the precipitation annual cycle was performed over the 1979-2008 period over five regions within SSA, based on a comparison between the GCMs precipitation outputs with the Global Precipitation Climatology Centre ( GPCC) dataset. The multi-model ensemble well reproduces the shape of the annual cycle of precipitation over most of SSA, although the monthly totals were overestimated (underestimated) over the North-West and South (North-East and Central-East) regions. Changes in precipitation and meteorological drought characteristics were identified by the difference for early (2011-2040) and late (2071-2100) 21st century values with respect to the 1979-2008 baseline, using the standardized precipitation index as a short- and long-term drought indicator. Future climate conditions are expected to modify the regional characteristics of meteorological droughts over SSA, but the range of uncertainty in the expected changes is high. A significant increase in the number of drought events in all the regions for most of the 21st century sub-periods is projected for the multi-model ensemble. The mean duration of drought events will be shorter, with no significant changes in the severity of droughts and the occurrence of multi-decadal changes in the number of critical dry months is likely, although the significance in the changes depends on the region, future time horizon and greenhouse gas concentration pathways. These results overlap with a projected increase in precipitation over most of the regions, which has a strong seasonality and, therefore, will have some implications upon the future meteorological drought developments and the agricultural and hydrological practices in SSA. [ABSTRACT FROM AUTHOR]

The Standardized Precipitation Index ( SPI), a well-reviewed meteorological drought index recommended by the World Meteorological Organization ( WMO), and its more recent climatic water balance variant, the Standardized Precipitation-Evapotranspiration Index ( SPEI), both rely on selection of a univariate probability distribution to normalize the index, allowing for comparisons across climates. Choice of an improper probability distribution may impart bias to the index values, exaggerating or minimizing drought severity. This study compares a suite of candidate probability distributions for use in SPI and SPEI normalization using the 0.5° × 0.5° gridded Watch Forcing Dataset ( WFD) at the continental scale, focusing on Europe. Several modifications to the SPI and SPEI methodology are proposed, as well as an updated procedure for evaluating SPI/ SPEI goodness of fit based on the Shapiro-Wilk test. Candidate distributions for SPI organize into two groups based on their ability to model short-term accumulation (1-2 months) or long-term accumulation (>3 months). The two-parameter gamma distribution is recommended for general use when calculating SPI across all accumulation periods and regions within Europe, in agreement with previous studies. The generalized extreme value distribution is recommended when computing the SPEI, in disagreement with previous recommendations. [ABSTRACT FROM AUTHOR]

ABSTRACT In this study, the spatio-temporal variability and trends of droughts across Bolivia between 1955 and 2012 were investigated using two climate drought indices: the Standardized Precipitation Index ( SPI), which is based on precipitation data, and the Standardized Precipitation Evapotranspiration Index ( SPEI), which is based on the difference between the precipitation and the reference evapotranspiration ( ETo). We found that the average drought conditions across the country showed a temporal behaviour mainly characterized by decadal variations. The spatial pattern of drought evolution showed marked differences between the Amazonian region and the Bolivian Altiplano. Both regions showed different drought periods, a lower frequency of drought variability in the Amazon region and trends towards drier conditions in the Altiplano, mainly due to a higher atmospheric water demand as a consequence of increased ETo. We also showed that inclusion of ETo, obtained from maximum and minimum temperature records, increased the spatial heterogeneity of the drought evolution in relation to the evolution observed when only precipitation droughts were considered. The SPEI, the calculation of which includes precipitation and ETo, indicated intensification in drought severity in the last years analysed relative to the pattern found when precipitation droughts alone were considered, and also indicated an increase in the magnitude and duration of drought events. The potential for increasing drought conditions under various climate change scenarios is discussed. [ABSTRACT FROM AUTHOR]

ABSTRACT The Standardized Precipitation Index ( SPI) has been widely used to monitor the drought status. In the estimation of SPI, an appropriate probability distribution function ( APDF) is required to fit precipitation series with different timescales, such as 3-month, 9-month and so on. Then the standard normal distribution function is used to transform the cumulative probability derived from APDF to calculate the SPI value. Obviously, the estimation accuracy of SPI particularly depends on the sample that influences the selection of PDF and parameter estimation. However, the size of the observed sample is usually small, and it cannot perfectly present the statistical property of the population, which usually causes the uncertainty on calculation of SPI and in turn results in the uncertainty of drought assessment. Due to the existence of gap between the estimated SPI and the true SPI, when one obtains the estimation of SPI, it is necessary to know the reliability or uncertainty of the estimated SPI. In this article, a new method based on the Bootstrap method was put forward to analyse the impact of sampling uncertainty on the estimation of SPI and drought assessment. Through repeating samples from the original sample, a large number of Bootstrap samples are constructed, and based on each Bootstrap sample, the corresponding estimation of SPI for the given event can be obtained. Therefore, the sampling distribution of SPI for the given event can also be derived, on which both the point estimation and interval estimation of SPI for the given precipitation event can be provided, and the overall assessment of a drought event could be achieved. The case study shows that, compared with the original SPI calculation method, the proposed method not only provides equivalent assessment results, but also has the capability to assess the impact of sampling uncertainty on the uncertainty of SPI calculation and drought assessment. [ABSTRACT FROM AUTHOR]

ABSTRACT Xinjiang is the largest arid inland region in China and its agricultural development plays an important role in the socio-economy of China. Drought is one of the major natural hazards in this region and has impacts on agriculture. In this study, spatiotemporal patterns of droughts are analysed based on monthly precipitation datasets from 52 meteorological stations covering the period of 1961-2008 using the Rotated Empirical Orthogonal Functions ( REOF) technique and also the Mann-Kendall trend test ( MK test). Results of the study indicate that: (1) a wetting tendency is observed in recent years, particularly in northern Xinjiang. Seasonally, the wetting tendency is found mainly in winter. The modes of REOF can be divided by the Tianshan mountain and the principal component ( PC) of the northern Xinjiang mode in winter has a significant increasing trend. (2) The area of drought-affected regions is decreasing in northwestern Xinjiang and along the northern side of Tianshan mountain. Seasonally, the area of drought-affected regions is significantly decreasing in winter. (3) The wetting tendency of Xinjiang may alleviate the drought influence. However, uneven spatial patterns of precipitation changes may enhance drought impacts. Besides, drought-related impacts can be greatly alleviated where irrigation conditions are favourable. [ABSTRACT FROM AUTHOR]

ABSTRACT In this study, wet and dry periods were analysed using the Standardized Precipitation Index ( SPI) on timescales of 1, 3, 6 and 12 months ( SPI1, SPI3, SPI6 and SPI12) at ten stations in Serbia during the period 1949-2011. The onset of severe wetness and drought during the period 1999-2001 was presented. The distributions of the monthly precipitation amounts for each station were modelled by a gamma distribution. The severity and duration of the wet and dry periods were calculated. The generalized Pareto distribution ( GPD) was applied to the SPI values for the timescales of 1 and 12 months during the period 1936-2011 in Belgrade. Furthermore, the severity and duration of the wet and dry periods for timescales of 1 and 12 months were analysed using the extreme value theory. Using the time series of the SPI, it was found that the frequency of droughts in the southern part of Serbia was higher than in the other parts of the country. The obtained results indicated that the GPD could be an appropriate distribution for SPI values less than −1 at the 1- and 12-month timescales, and for the severity of the wet and dry periods at the 1-month timescale. [ABSTRACT FROM AUTHOR]

ABSTRACT The implications of geographical factors (i.e. elevation, freshwater area, urbanization, and proximity to coast) and climatic factors (i.e. air temperature, wind speed, relative humidity, and solar radiation) with regard to drought trend were investigated by analyzing the monthly averaged daily climate data (i.e. precipitation, temperature, wind speed, relative humidity, and solar radiation) recorded from 1973 to 2006 at 53 climatological stations in South Korea. In addition, geographical characteristics were identified by GIS analysis and land cover data were analyzed for these 53 stations. Further, multivariate regression analyses were performed by setting the Standardized Precipitation Index ( SPI) trend as the dependent variable and the geographical and climatic factors as the independent variables. The results indicated that, overall, the droughts in South Korea are becoming more severe in spring for the short- and seasonal term; however, the droughts in all seasons are becoming less severe for the long term. The effects of geographical and climatic factors on drought trends are also closely related to seasonality and drought duration for short-, seasonal-, and medium-term droughts, but not for long-term droughts. Therefore, for efficient water resources management for drought preparedness, drought duration and seasonality should also be considered along with geographical and climatic characteristics of a region. [ABSTRACT FROM AUTHOR]

Assessing the risk, the severity and the likely evolution of droughts are key tasks for improving preparedness of regions prone to drought conditions, and mitigation of drought consequences. The access to real-time and high-quality climatic information is essential for this purpose. Different climatic databases are being developed and made available on real time by climatic research institutions, but their capability for quantifying droughts characteristics including severity, or spatio-temporal variability, is uncertain given their low spatial resolution. In this study, we assessed the capability of three databases with contrasted spatial resolution for measuring spatial and temporal variability of drought occurrence. The standardized precipitation index, calculated for each database, showed that the low resolution datasets allow an acceptable measurement of the magnitude, intensity and duration of droughts, while failing mostly in detecting the spatial patterns of the specific drought episodes. Moreover, the capability of the datasets for assessing the impacts of droughts on surface hydrology and tree growth was examined. Results confirmed the usefulness of the drought index for assessing drought impacts on water resources and forest ecosystems even when low resolution databases are used. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Under the aspect of future climate change, it is important for decision makers to know how drought conditions might change on the regional scale in order to map out adequate adaptation and mitigation strategies. Recent RCM simulations provided by the ENSEMBLES project are used to analyse changes in dry and wet conditions in Europe by the mid of the 21st century under the A1B emission scenario. Eight RCMs are selected to capture the uncertainties of the projected changes. An empirical statistical error correction approach is applied to modelled daily mean air temperature and precipitation amount to account for RCM errors, and commonly used drought indices-the Standardized Precipitation Index (SPI), the self calibrated Palmer Z-Index (scZI) and Palmer Drought Severity Index (scPDSI)-are calculated. Changes in the mean, in interannual variability, and in frequency, length, distance, magnitude, and area of dry and wet events are investigated. The statistical significance of the projected multi-model mean changes and the according uncertainties are analysed for nine European subregions. Furthermore, distributional changes of the dry and wet spell characteristics are assessed. Changes in the mean, and in dry and wet event characteristics show the most pronounced changes towards drier and wetter conditions in the southern- and northernmost European subregions, respectively. Here, the changes are highly significant and confident, while the projected changes are more dissonant for the other subregions. Severe changes in the extremes of event length, distance, magnitude, and area particularly arise in the southern- and northernmost European subregions. The projected changes in interannual variability are less significant and confident. However, significantly increasing interannual variability is projected in regions with pronounced changes in the mean towards wetter as well as towards drier conditions. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Located in northwest Baja California, Mexico, the Guadalupe River Basin is situated in a semiarid region where periods of drought pose serious economic, social and environmental concerns. The study area has highly variable climate, with mean annual precipitation ranging from less than 12 mm to over 750 mm a year across the basin, and with most of the annual precipitation occurring during the autumn and winter seasons. To quantify the frequency and severity of meteorological droughts at the local (watershed) scale, this study investigates seasonal and annual precipitation data from 34 sites in northwest Baja California. Along with the analysis of precipitation climatology and interannual variability, El Niño/Southern Oscillation (ENSO) and related Pacific Ocean sea surface temperature (SST) patterns are shown to be potential predictors of seasonal precipitation. Analysis of precipitation variability at seasonal and annual time scales is performed using the standardized precipitation index (SPI) methodology, and annual, seasonal, and ENSO-conditioned precipitation frequency analyses are executed using the regional L-moment algorithm. The SPI and regional rainfall drought frequency estimates developed in this study may be useful for monitoring meteorological droughts and could serve as critical components of a comprehensive drought management plan. Furthermore, the methods applied in this study may be transferred to other semi-arid locations to mitigate drought risk and, potentially, impacts of drier conditions in the 21st century. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The frequency and intensity of meteorological droughts over the Indo-Gangetic Region (IGR) of India pertaining to the rice crop during kharif season (June to July to October to November) and the wheat crop during the rabi season (November to December to March) were assessed using the standardized precipitation index (SPI). The monthly distribution of rainfall is more crucial than the cumulative seasonal rainfall on rice-wheat (RW) productivity. Consequently, an attempt was made to measure the effectiveness of using monthly SPI from June to September to assess drought on RW productivity over five major RW growing states of IGR in India. An attempt is also made to test the use of monthly SPI for the early kharif rice and rabi wheat forecasts for these states. The long-term (1906-2005) mean annual rainfall of IGR is 1099.1 mm with a standard deviation of 115.7 mm and a coefficient of variation of 10.5%. It was observed that the kharif rice productivity index and monthly SPI from June to September have a significant ( R2 = 0.44) multiple regression at 0.001 level over IGR. It was also observed that in the Indo-Gangetic Region, the wheat productivity index and monthly SPI (June to September) have an insignificant ( R2 = 0.21) multiple regression. It indicated that the monthly distribution of monsoon rainfall in terms of the SPI accounted for 44% yield variability in rice and 21% yield variability in wheat. Thus, these indices may be used for forecasting the productivity of the RW system over IGR states in India. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Extratropical and tropical influences on Tibetan Plateau severe and extreme dry and wet summer months are investigated focussing on the large-scale circulation and using results of the coupled climate model ECHAM5/MPI-OM. A pre-industrial control run and scenario runs for the 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) are considered. Tibetan Plateau precipitation in months of wetness and drought is related to atmospheric circulation anomalies in the North-Atlantic/European sector and to sea surface temperature anomalies in the Tropics. Drought on the Tibetan Plateau is associated with a pronounced wave train bridging Eurasia from the North Atlantic to Asia. Increased transient eddy activity in the North Atlantic storm track has a more south-west to north-east orientation. This supports a high pressure anomaly over the eastern North Atlantic and Scandinavia which excites a cross Eurasian wave train reducing the moisture inflow to the Tibetan Plateau from the Arabian Sea. A concurrent warming in the tropical Indian Ocean increases the low level monsoonal westerlies deviating the moisture transport from the Bay of Bengal towards the Indochinese Peninsula and the Philippines. Wetness on the Tibetan Plateau is dominated by a cooling in the tropical oceans, whereas atmospheric flow is predominantly zonal in the extratropics of North America and Europe. Thus, moisture inflow can reach the Tibetan Plateau via the Arabian Sea, the Bay of Bengal and the mid-latitude westerlies. Future scenarios show little change of atmospheric flow composites for wetness and dryness; the Tibetan Plateau droughts increase by 10% for an A1B-scenario, while extreme wet summer months are reduced by approximately 1%. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article focuses on a study about the relationship between precedent soil moisture anomalies and summer precipitation in the U.S. Great Plains. It states that Variable Infiltration Capacity (VIC)-simulated soil moisture and Standardized Precipitation Index (SPI) were used in the study. Findings show a correlation between spring soil moisture and summer SPI when Niño sea surface temperatures (SSTs) and summer SPIs are not correlated.

The article presents a study which examines various processes which affect the dryness and wetness of the Tibetan plateau's boreal summer variability. The ERA-40 reanalysis was used to observe the precipitation on the plateau and analyze how surface temperature and atmospheric circulation influenced drought and wetness experienced in the Tibetan plateau. The study indicates that upstream and downstream Tibetan plateau conditions manifest importance for developing south-eastern Asian rainfall.

The article presents a study that aims to assess the rainfall drought patterns in Great Britain. It mentions that the Mediterranean region has been observed as the high frequency in the occurrence of droughts as claimed by the European Commission. It notes that climatological droughts can be assessed through General Circulation Modes (GCM). It also states that perturbed-physics ensembles and multimodel ensembles are the two main approaches in addressing the uncertainty in the climatic droughts.

The article studies the characteristics of drought/pluvial regimes, such as intensity, duration and spatial coverage, in U.S. based on a high resolution precipitation dataset by examining the spatial and temporal characteristics of anomalous precipitation throughout the country. Two indexes, the Palmer drought severity index (PDSI) and the standard precipitation index (SPI) from 1895-2003 was constructed using parameter-elevation regression on independent slopes model (PRISM). Findings reveal that the largest yearly drought or pluvial events happen more frequently in central U.S. while extreme values occur more in western U.S.