Spatiotemporal characterization of meteorological drought: a global approach using the Drought Exceedance Probability Index (DEPI)

被引:3
|
作者
Limones, Natalia [1 ]
Vargas Molina, Jesus [1 ]
Paneque, Pilar [2 ]
机构
[1] Univ Seville, Seville 41004, Spain
[2] Pablo de Olavide Univ, Ctra Utrera Km 1, Seville 41013, Spain
关键词
Meteorological drought events; Drought duration; Drought intensity; Global assessment; Spatiotemporal patterns; RISK; CLIMATE;
D O I
10.3354/cr01703
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We present a global spatiotemporal characterization of meteorological droughts using historical precipitation data through the Drought Exceedance Probability Index (DEPI). The relationship between meteorological drought characteristics and monthly precipitation is explored at a global level. This study contributes to our understanding of the drought features observed in different areas of the planet, which can help predict the behavior of future droughts. The DEPI was applied to the Climate Research Unit global gridded high-resolution rainfall data set covering the period 1901-2019. Monthly drought index series were examined to extract the number of droughts experienced in each pixel (0.50 degrees x 0.50 degrees) of the globe, as well as their durations, intensities and severities. Results show agreement with other global drought characterization efforts, revealing areas with a greater drought occurrence. This paper demonstrates that regions with less seasonality and less intra- and inter-annual rainfall variability report fewer drought episodes. Duration and severity of droughts are also related to these rainfall features. The last part of the study describes the temporal distribution of droughts throughout the world. We conclude that regions with many events show stable, even distributions over time, but many pixels in the intertropical regions, the Middle East and smaller patches in Mongolia, China, Siberia and Canada currently show higher-intensity and longer-duration drought events than at the beginning of the twentieth century, while the opposite occurs in parts of Scandinavia, Russia, Argentina and Tanzania. The analysis demonstrates that DEPI is easy to use, is applicable to different climates and is effective in detecting the onset, end and intensity of droughts.
引用
收藏
页码:137 / 154
页数:18
相关论文
共 50 条
  • [1] A new index to assess meteorological drought: the Drought Exceedance Probability Index (DEPI)
    Limones, Natalia
    Fernanda Pita-Lopez, Maria
    Mariano Camarillo, Juan
    ATMOSFERA, 2022, 35 (01): : 67 - 88
  • [2] Testing of Drought Exceedance Probability Index (DEPI) for Turkey using PERSIANN data for 2000-2021 period
    Topcu, Emre
    ITALIAN JOURNAL OF AGROMETEOROLOGY-RIVISTA ITALIANA DI AGROMETEOROLOGIA, 2021, (02): : 15 - 28
  • [3] Spatiotemporal characterization of agricultural drought in the Sahel region using a composite drought index
    Abdourahamane, Zakari Seybou
    Garba, Issa
    Boukary, Aboubakr Gambo
    Mirzabaev, Alisher
    JOURNAL OF ARID ENVIRONMENTS, 2022, 204
  • [4] Nonparametric approach for bivariate drought characterization using palmer drought index
    Kim, TW
    Valdés, JB
    Yoo, C
    JOURNAL OF HYDROLOGIC ENGINEERING, 2006, 11 (02) : 134 - 143
  • [5] Spatiotemporal variability of meteorological drought in Romania using the standardized precipitation index (SPI)
    Cheval, Sorin
    Busuioc, Aristita
    Dumitrescu, Alexandru
    Birsan, Marius-Victor
    CLIMATE RESEARCH, 2014, 60 (03) : 235 - 248
  • [6] Spatiotemporal climate variability and meteorological drought characterization in Ethiopia
    Kourouma, Jean Moussa
    Eze, Emmanuel
    Kelem, Goitom
    Negash, Emnet
    Phiri, Darius
    Vinya, Royd
    Girma, Atkilt
    Zenebe, Amanuel
    GEOMATICS NATURAL HAZARDS & RISK, 2022, 13 (01) : 2049 - 2085
  • [7] Spatiotemporal analysis of meteorological drought variability in the Indian region using standardized precipitation index
    Kumar, M. Naresh
    Murthy, C. S.
    Sai, M. V. R. Sesha
    Roy, P. S.
    METEOROLOGICAL APPLICATIONS, 2012, 19 (02) : 256 - 264
  • [8] Multiscale spatiotemporal meteorological drought prediction: A deep learning approach
    Zhang, Jia-Li
    Huang, Xiao-Meng
    Sun, Yu-Ze
    ADVANCES IN CLIMATE CHANGE RESEARCH, 2024, 15 (02) : 211 - 221
  • [9] Spatiotemporal analysis of meteorological drought variability in a homogeneous region using standardized drought indices
    Niaz, Rizwan
    Almazah, Mohammed M. A.
    Al-Duais, Fuad S.
    Iqbal, Nouman
    Khan, Dost Muhammad
    Hussain, Ijaz
    GEOMATICS NATURAL HAZARDS & RISK, 2022, 13 (01) : 1457 - 1481
  • [10] Drought assessment and characterization using SPI, EDI and DEPI indices in northern Algeria
    Brahim Habibi
    Mohamed Meddi
    Topçu Emre
    Abdelkader Boucefiane
    Abedelwahab Rahmouni
    Natural Hazards, 2024, 120 : 5201 - 5231