Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring
Abstract
48 págs., 25 figs. Available online 21 December 2013. The definitive version is available at: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0088
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From The 2024 report of the Lancet Countdown on health and climate change: facing record-breaking threats from delayed action (2024) · cites this paper as [105]
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“The SPEI was calculated using the R package SPEI (Beguería et al. 2014), assuming a loglogistic probability distribution, and calibrated based on the period 1961-2020 (for ERA-20C and 20CRv3 using all available years in this period).”
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“The SPEI is a multi-scalar drought index that captures atmospheric water deficits by considering the difference between precipitation and PET.”
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The first global multi-timescale daily SPEI dataset from 1982 to 2021
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“…drought management is usually performed on a local to national scale, there are different drought monitoring systems available on a global scale, allowing to assess general dry or humid conditions over large areas (Beguería et al., 2014; Hao et al., 2014; Turco et al., 2020; Wood et al., 2015).”
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“The optimal PDF of SPEI is still controversial, and the same distribution function performs differently in different regions (Beguería et al., 2014; Stagge et al., 2013; VicenteSerrano & Beguería, 2015).”
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“SPI determines meteorological drought based on precipitation, whereas the SPEI incorporates the Potential Evapotranspiration (PET) parameter, which makes the calculation more complex (Beguería et al., 2014).”
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“The Spanish National Research Council (Consejo Superior de Investigaciones Científicas, CSIC) services a global SPEI product via their operational drought monitoring system and a corresponding drought database (see https://spei.csic.es 32,44,49 ).”
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“…is widely used to define meteorological drought, and the procedure to calculate the index involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution (Beguería et al., 2014; Vicente-Serrano et al., 2010).”
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“We used an ensemble of five long-term remote-sensing-based GPP products (Methods) and regressed GPP against drought indices, such as the Palmer drought severity index (PDSI) 16 and the standardized precipitation–evapotranspiration index (SPEI) 17 .”
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“Standardized Precipitation Evapotranspiration Index values that highlight extreme wet and dry events (that is, the difference between precipitation and potential evapotranspiration adjusted using a three-parameter log logistic distribution) were determined for the period 2000–2020 53 .”
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“The incorporation of both precipitation and evapotranspiration in the SPEI enables a more precise representation of alterations in the water balance of the climate (Vicente-Serrano et al. 2010 , 2012; Beguería et al. 2014 ).”
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“SPEI: the Standardized Precipitation Evapotranspiration Index (Vicente-Serrano et al.”
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“Albeit the larger the value of SPEI, the greater the rainfall in the area, excessive rainfall may cause floods.”
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“Furthermore, its outcomes are similar to the standard FAOPenman–Monteith equation (Beguería et al. 2014; Droogers and Allen 2002; Hargreaves and Allen 2003).”
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“2011), whereas SPEI computes a simplified water balance between precipitation and potential evapotranspiration (PET) (Vicente-Serrano et al. 2010; Beguería et al. 2014).”
BackgroundMethodInfluentialDrought Disasters in China from 1991 to 2018: Analysis of Spatiotemporal Trends and Characteristics
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Spatiotemporal Variations in Drought and Vegetation Response in Inner Mongolia from 1982 to 2019
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“The calculation process is as follows [40,41].”
A Conditional Model of Local Income Shock and Civil Conflict
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“In order to maintain a mean SPI of zero for the specified time and location (with half of the precipitation totals falling below the median and half above it), the long-term precipitation data is adjusted to a probability distribution and then transformed into a normal distribution [61].”
MethodExploring Climate Change Effects on Drought Patterns in Bangladesh Using Bias-Corrected CMIP6 GCMs
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Human-induced climate change increased 2021–2022 drought severity in horn of Africa
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“Several studies (Beguería et al., 2014; Dai, 2011; Sheffield et al., 2012; Van Der Schrier et al., 2011) have compared and evaluated the effect of using different PET equations in the calculation of drought indices.”
Gribbe, S., Enderle, L., Weigel, R. F. B., Hertel, D., Leuschner, C., & Muffler, L. (2024) · Forest Ecology and Management · doi:10.1016/j.foreco.2024.122022 · Cited by 36 · see citing works
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Global disparities in rural and urban population exposure to compound drought and heatwave events
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“We selected the SPEI in order to describe the hydric conditions of each growing season because our study was concentrated on the impact of drought (Beguería et al., 2014).”
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“This included calibrating models to recognize normal power flow fluctuations and distinguish them from potential cyber threats [29].”
BackgroundLuna, D. A., Pottier, J., & Picon‐Cochard, C. (2022) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2023.109325 · Cited by 30 · see citing works
Legacy effects in radial tree growth are rarely significant after accounting for biological memory
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“Here we computed the evapotranspiration using the Penman– Monteith equation 54 as recommended in a previous study 55 .”
Islam, M. R., Jönsson, A., Bergkvist, J., Lagergren, F., Lindeskog, M., Mölder, M., Scholze, M., & Kljun, N. (2024) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2024.109959 · Cited by 31
- Authors
- Beguería, S., Vicente-Serrano, S. M., Reig, F., & Latorre, B.
- Affiliations
- Estación Experimental de Aula Dei, Consejo Superior de Investigaciones Científicas (EEAD-CSIC); Zaragoza Spain
- Consejo Superior de Investigaciones Científicas (ES)
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2013-12-21
- Volume
- 34
- Issue
- 10
- Pages
- 3001-3023
- ISSN
- 0899-8418 (ISSN-L)
- OpenAlex
- W2165772416
- Cited by
- 2,128
- References
- 0
- Citations by year
- 2026: 300 · 2025: 284 · 2024: 290 · 2023: 246 · 2022: 252 · 2021: 195 · 2020: 174 · 2019: 135 · 2018: 104 · 2017: 61 · 2016: 48 · 2015: 32 · 2014: 5
- FWCI
- 21.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Climatology (publishedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
- Funders
- European Commission (LIFE MEDACC)
- Spanish Commission of Science and Technology (CGL2011-27574-CO2-02)
- Spanish Commission of Science and Technology and FEDER (CGL2011-24185, CGL2011-27536)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Hydrology and Drought Analysis
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
- Keywords
- Standardized Precipitation Evapotranspiration Index, drought monitoring, evapotranspiration modeling, parameter fitting, drought indices, climate data tools
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