scholarly journals Spatial patterns of European droughts under a moderate emission scenario

2015 ◽  
Vol 12 (1) ◽  
pp. 179-186 ◽  
Author(s):  
J. Spinoni ◽  
G. Naumann ◽  
J. Vogt
Keyword(s):  
Spatial Patterns ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Mediterranean Area ◽  
Severe Drought ◽  
Monthly Precipitation ◽  
Precipitation Increase ◽  
The Standardized Precipitation Index ◽  
Near Future

Abstract. Meteorological drought is generally defined as a prolonged deficiency of precipitation and is considered one of the most relevant natural hazards as the related impacts can involve many different sectors. In this study, we investigated the spatial patterns of European droughts for the periods 1981–2010, 2041–2070, and 2071–2100, focusing on the projections under a moderate emissions scenario. To do that, we used the outputs of the KNMI-RACMO2 model, which belongs to the A1B family and whose spatial resolution is 0.25° × 0.25°. By means of monthly precipitation and potential evapotranspiration (PET), we computed the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at the 12-month accumulation scale. Thereafter, we separately obtained drought frequency, duration, severity, and intensity for the whole of Europe, excluding Iceland. According to both indicators, the spatial drought patterns are projected to follow what recently characterized Europe: southern Europe, who experienced many severe drought events in the last decades, is likely to be involved by longer, more frequent, severe, and intense droughts in the near future (2041–2070) and even more in the far future (2071–2100). This tendency is more evident using the SPEI, which also depends on temperature and consequently reflects the expected warming that will be highest for the Mediterranean area in Europe. On the other side, less severe and fewer drought events are likely to occur in northern Europe. This tendency is more evident using the SPI, because the precipitation increase is projected to outbalance the temperature (and PET) rise in particular in Scandinavia. Regarding the mid-latitudes, the SPEI-based analyses point at more frequent drought events, while the SPI-based ones point at less frequent events in these regions.

scholarly journals Assessing droughts using meteorological drought indices in Victoria, Australia

2014 ◽  
Vol 46 (3) ◽  
pp. 463-476 ◽  
Author(s):  
Siti Nazahiyah Rahmat ◽  
Niranjali Jayasuriya ◽  
Muhammed Bhuiyan
Keyword(s):  
Urban Communities ◽  
Potential Evapotranspiration ◽  
Climatic Variability ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Rural And Urban ◽  
The Standardized Precipitation Index

Droughts adversely impact rural and urban communities, industry, primary production and, thus, a country's economy. Drought monitoring is directed to detecting the onset, persistence and severity of the drought. In this study, meteorological drought indices such as the Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI) and deciles were assessed to investigate how well these indices reflect drought conditions in Victoria, Australia. The Theory of Runs was also used to identify the drought deficit. The study uses 55 years (1955–2010) of monthly precipitation and reference evapotranspiration data for five selected meteorological stations in Victoria, Australia. Results show that drought characterization using SPI and RDI provides a standardized classification of severity thus exhibiting advantages over deciles. As RDI considers both rainfall and potential evapotranspiration in calculations, it could be sensitive to climatic variability. For characterizing agricultural droughts, the application of the RDI is recommended. The use of the SPI was shown to be satisfactory for assessing and monitoring meteorological droughts. The SPI was also successful in detecting the onset and the end of historical droughts for the selected events.

scholarly journals Elucidating Diverse Drought Characteristics from Two Meteorological Drought Indices (SPI and SPEI) in China

2020 ◽  
Vol 21 (7) ◽  
pp. 1513-1530 ◽  
Author(s):  
Lingcheng Li ◽  
Dunxian She ◽  
Hui Zheng ◽  
Peirong Lin ◽  
Zong-Liang Yang
Keyword(s):  
Clustering Algorithm ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Three Dimensional ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Severity ◽  
Severe Drought ◽  
Small Areas ◽  
Drought Characteristics

AbstractThis study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.

scholarly journals Drought monitoring and prediction using SPI, SPEI, and random forest model in various climates of Iran

2021 ◽  
Author(s):  
Morteza Lotfirad ◽  
Hassan Esmaeili-Gisavandani ◽  
Arash Adib
Keyword(s):  
Random Forest ◽  
Correlation Coefficient ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Monthly Precipitation ◽  
Model Combination ◽  
The North ◽  
Drought Prediction ◽  
Lag Times ◽  
The Standardized Precipitation Index

Abstract The aim of this study is to select the best model (combination of different lag times) for predicting the standardized precipitation index (SPI) and the standardized precipitation and evapotranspiration index (SPEI) in next time. Monthly precipitation and temperature data from 1960 to 2019 were used. In temperate climates, such as the north of Iran, the correlation coefficient of SPI and SPEI was 0.94, 0.95, and 0.81 at the time scales of 3, 12, and 48 months, respectively. Besides, this correlation coefficient was 0.47, 0.35, and 0.44 in arid and hot climates, such as the southwest of Iran because potential evapotranspiration (PET) depends on temperature more than rainfall. Drought was predicted using the random forest (RF) model and applying 1–12 months lag times for next time. By increasing of time scale, the prediction accuracy of SPI and SPEI will improve. The ability of SPEI is more than SPI for drought prediction, because the overall accuracy (OA) of prediction will increase, and the errors (i.e., overestimate (OE) and underestimate (UE)) will reduce. It is recommended for future studies (1) using wavelet analysis for improving accuracy of predictions and (2) using the Penman–Monteith method if ground-based data are available.

scholarly journals Droughts and corruption

Public Choice ◽  
2020 ◽  
Author(s):  
Daniela Wenzel
Keyword(s):  
Public Sector ◽  
Natural Disasters ◽  
Good Governance ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Developed Countries ◽  
Severe Drought ◽  
Specific Analysis ◽  
Short And Long Term ◽  
The Standardized Precipitation Index

Abstract Natural disasters are challenges for good governance. That conclusion follows from recent research investigating the effects of natural disasters on one important force hostile to good governance: public sector corruption. However, a specific analysis of droughts is so far neglected in the still-young relevant strand of the literature. The present paper fills that gap by analyzing the short- and long-term influence of droughts on public sector corruption within a unified panel estimation approach for 120 countries during the period 1985–2013. Relying on a meteorological drought measure, the Standardized Precipitation Index, we show that more severe drought exposure is followed by more corruption. The effect holds for subsamples of developing and developed countries. The robustness of the results is supported by a variety of stability tests. Furthermore, we provide initial evidence on the transmission paths of drought-induced corruption, which differ depending on the countries’ level of development. Whereas droughts increase corruption risk in developing countries by triggering significantly larger aid inflows and less democratic accountability and transparency, corruption in developed countries rises as a consequence of governmental drought relief payments.

scholarly journals Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3366
Author(s):  
Mairon Ânderson Cordeiro Correa de Carvalho ◽  
Eduardo Morgan Uliana ◽  
Demetrius David da Silva ◽  
Uilson Ricardo Venâncio Aires ◽  
Camila Aparecida da Silva Martins ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Rain Gauge ◽  
Monthly Precipitation ◽  
Indirect Measurements ◽  
Study Region ◽  
Development Cycle ◽  
Historical Series ◽  
The Standardized Precipitation Index

Drought is a natural disaster that affects a country’s economy and food security. The monitoring of droughts assists in planning assertive actions to mitigate the resulting environmental and economic impacts. This work aimed to evaluate the performance of the standardized precipitation index (SPI) using rainfall data estimated by orbital remote sensing in the monitoring of meteorological drought in the Cerrado–Amazon transition region, Brazil. Historical series from 34 rain gauge stations, in addition to indirect measurements of monthly precipitation obtained by remote sensing using the products CHIRPS-2.0, PERSIANN-CDR, PERSIANN-CCS, PERSIANN, GPM-3IMERGMv6, and GPM-3IMERGDLv6, were used in this study. Drought events detected by SPI were related to a reduction in soybean production. The SPI calculated from the historical rain series estimated by remote sensing allowed monitoring droughts, enabling a high detailing of the spatial variability of droughts in the region, mainly during the soybean development cycle. Indirect precipitation measures associated with SPI that have adequate performance for detecting droughts in the study region were PERSIANN-CCS (January), CHIRPS-2.0 (February and November), and GPM-3IMERGMv6 (March, September, and December). The SPI and the use of precipitation data estimated by remote sensing are effective for characterizing and monitoring meteorological drought in the study region.

Evaluation of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA v7) in drought monitoring over southwest Iran

2020 ◽  
Vol 82 ◽  
pp. 55-73
Author(s):  
M Montazeri ◽  
MSK Kiany ◽  
SA Masoodian
Keyword(s):  
Standardized Precipitation Index ◽  
Tropical Rainfall Measuring Mission ◽  
Meteorological Drought ◽  
Drought Monitoring ◽  
Severe Drought ◽  
Study Region ◽  
Tropical Rainfall ◽  
Southwestern Iran ◽  
The Standardized Precipitation Index ◽  
Quantitative Precipitation Estimates

Characterizing the errors in satellite-based precipitation estimations for drought monitoring is of great importance, as these estimations provide both spatially and temporally complete records. The aim of this study was to evaluate satellite-based quantitative precipitation estimates to monitor meteorological drought in southwestern Iran. The reliability of the Tropical Rainfall Measuring Mission Version 7 products (3B42 and 3B43) in estimating the standardized precipitation index (SPI) was evaluated against a ground-based gridded precipitation dataset at 0.25° spatial resolution for 1998-2016. The analysis conducted for the SPI at various time scales revealed that both products (3B42 and 3B43) are capable of capturing the spatial and temporal behavior of drought events over the study region, with the best performance at SPI6. 3B43 is also more efficient in the identification of shorter severe drought events compared to 3B42. The findings suggest that both satellite products, particularly 3B43, are suitable to be used directly for SPI computation in the region for drought monitoring and early warning in terms of the accuracy and the spatial and temporal resolutions they provide.

scholarly journals Meteorological Drought Assessment in Sharjah, UAE Using Drought Indices

2022 ◽  
Vol 13 (1) ◽  
pp. 16-20
Author(s):  
Mhamd S. Oyounalsoud ◽  
◽  
Arwa Najah ◽  
Abdullah G. Yilmaz ◽  
Mohamed Abdallah ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Crop Production ◽  
Standardized Precipitation Index ◽  
Extended Period ◽  
Meteorological Drought ◽  
Distribution Functions ◽  
Drought Indices ◽  
Monthly Precipitation ◽  
Drought Assessment ◽  
The Standardized Precipitation Index

Drought is a natural disaster that significantly affects environmental and socio-economic conditions. It occurs when there is a period of below average precipitation in a region, and it results in water supply shortages affecting various sectors and life adversely. Droughts impact the ecosystems, crop production, and erode livelihoods. Monitoring drought is essential especially in the United Arab Emirates (UAE) due to the scarcity of rainfall for an extended period of time. In this study, drought is assessed in Sharjah UAE using monthly precipitation and average temperature data recorded for 35 years (1981-2015) at the Sharjah International Airport. The standardized precipitation Index (SPI), and the Reconnaissance Drought Index (RDI) are selected to predict future droughts in the region. SPI and RDI are fitted to the statistical distribution functions (gamma and lognormal) in an annual time scale and then, a trend analysis of index values is carried out using Mann-Kendal test. The correlation between SPI and RDI indices was found to be high where both showed high drought frequencies and a tendency to get drier over time, thus indicating the need of appropriate drought management and monitoring.

scholarly journals Baseline Probabilities for the Seasonal Prediction of Meteorological Drought

2012 ◽  
Vol 51 (7) ◽  
pp. 1222-1237 ◽  
Author(s):  
Bradfield Lyon ◽  
Michael A. Bell ◽  
Michael K. Tippett ◽  
Arun Kumar ◽  
Martin P. Hoerling ◽  
...  
Keyword(s):  
Seasonal Cycle ◽  
Serial Correlation ◽  
Climate Model ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Seasonal Prediction ◽  
Monthly Precipitation ◽  
Predictive Skill ◽  
Drought Indicators ◽  
The Standardized Precipitation Index

AbstractThe inherent persistence characteristics of various drought indicators are quantified to extract predictive information that can improve drought early warning. Predictive skill is evaluated as a function of the seasonal cycle for regions within North America. The study serves to establish a set of baseline probabilities for drought across multiple indicators amenable to direct comparison with drought indicator forecast probabilities obtained when incorporating dynamical climate model forecasts. The emphasis is on the standardized precipitation index (SPI), but the method can easily be applied to any other meteorological drought indicator, and some additional examples are provided. Monte Carlo resampling of observational data generates two sets of synthetic time series of monthly precipitation that include, and exclude, the annual cycle while removing serial correlation. For the case of no seasonality, the autocorrelation (AC) of the SPI (and seasonal precipitation percentiles, moving monthly averages of precipitation) decays linearly with increasing lag. It is shown that seasonality in the variance of accumulated precipitation serves to enhance or diminish the persistence characteristics (AC) of the SPI and related drought indicators, and the seasonal cycle can thereby provide an appreciable source of drought predictability at regional scales. The AC is used to obtain a parametric probability density function of the future state of the SPI that is based solely on its inherent persistence characteristics. In addition, a method is presented for determining the optimal persistence of the SPI for the case of no serial correlation in precipitation (again, the baseline case). The optimized, baseline probabilities are being incorporated into Internet-based tools for the display of current and forecast drought conditions in near–real time.

scholarly journals Assessment of Meteorological Drought in Korea under Climate Change

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Jaewon Kwak ◽  
Soojun Kim ◽  
Jaewon Jung ◽  
Vijay P. Singh ◽  
Dong Ryul Lee ◽  
...  
Keyword(s):  
Climate Change ◽  
Spatial Distribution ◽  
Climate Model ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Joint Probability ◽  
Meteorological Drought ◽  
Copula Method ◽  
The Standardized Precipitation Index ◽  
Near Future

Drought has become one of the most important elements for water resources planning and management in Korea. The objective of this study is to estimate the spatial distribution of drought and change in the drought characteristics over time due to climate change. For the spatial characterization of drought, the standardized precipitation index (SPI) is calculated from the 45 observatories in Korea and the spatial distribution is also estimated based on the joint probability analysis using the copula method. To analyze the effect of climate change, spatial distribution of drought in the future is analyzed using the SPI time series calculated from Representative Concentration Pathways (RCPs) scenarios and HADGEM3-RA regional climate model. The results show that the Youngsan River and the northwest of Nakdong River basins in Korea have nearly doubled drought amount compared to the present and are most vulnerable to drought in near future (2016 to 2039 years).

scholarly journals Developing Objective Operational Definitions for Monitoring Drought

2009 ◽  
Vol 48 (6) ◽  
pp. 1217-1229 ◽  
Author(s):  
Steven M. Quiring
Keyword(s):  
Water Conservation ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Decision Makers ◽  
Drought Severity ◽  
Specific Method ◽  
The Standardized Precipitation Index ◽  
Spatially Variant ◽  
Objective Methodology

Abstract Drought is a complex phenomenon that is difficult to accurately describe because its definition is both spatially variant and context dependent. Decision makers in local, state, and federal agencies commonly use operational drought definitions that are based on specific drought index thresholds to trigger water conservation measures and determine levels of drought assistance. Unfortunately, many state drought plans utilize operational drought definitions that are derived subjectively and therefore may not be appropriate for triggering drought responses. This paper presents an objective methodology for establishing operational drought definitions. The advantages of this methodology are demonstrated by calculating meteorological drought thresholds for the Palmer drought severity index, the standardized precipitation index, and percent of normal precipitation using both station and climate division data from Texas. Results indicate that using subjectively derived operational drought definitions may lead to over- or underestimating true drought severity. Therefore, it is more appropriate to use an objective location-specific method for defining operational drought thresholds.

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