Joshua BrinksISciences, LLC 


  • Standardized anomalies allow for temporal and spatial climatic comparisons.
  • Historic data to 1901.
  • R package available to generate a user dataset.
  • Coarse resolution.
  • Data quality subject to model input quality and goodness of distribution fit.

The standardized precipitation evapotranspiration index (SPEI) is a recent entry into the vast landscape of drought indices. Introduced in 2010 by Vicente-Serrano, SPEI sought to improve upon established drought indices such as the Palmer drought severity index (PDSI) and the standardized precipitation index (SPI) by introducing a multi-scalar model utilizing reference evapotranspiration.1 This framework permits a wide array of applications and comparisons across wide spatial and temporal extents. For more detailed comparisons of SPEI with additional drought indices or using alternative model parameterizations see Tirivarombo (2018),2 Potopova (2015),3 Begueria (2014),4 and Hayes (1999).5

Although anomaly based drought indices provide a platform to analyze drought severity across large temporal ranges and a variety of biomes, they are not without their drawbacks. Foremost, drought indices are dependent on the quality of data used for their inputs. At the minimum, this includes precipitation data, however, SPEI also requires temperature data to calculate the evaporative demand. When employed across large spatial extents precipitation and temperature data may be irregularly distributed, recorded with varying levels of precision and accuracy, or be subject to additional underlying biases. SPEI is also sensitive to the method for calculating evapotranspiration. For a more thorough discussion of SPEI outputs as a function of actual or reference evapotranspiration see Begueria (2014).4 Lastly, drought indices require long base periods of reference data in order to accurately assess the severity of the drought and accurately fit the theoretical distribution of anomalies. Ideally, models are calculated using at least 50 years of data.

Figure 1: Standardized precipitation evapotranspiration index for 2015 with a 4 year integration period.

Figure 1: Standardized precipitation evapotranspiration index for 2015 with a 4 year integration period.

Despite its relative immaturity in comparison to long established indices like SPI (1993) and PDSI (1965), SPEI has been widely adopted in the academic and practitioner communities. SPEI has recently been featured in examinations of the impacts of drought on cereal crops in China,6 agricultural drought risks in the Czech Republic,3 grassland and livestock management,7 and characterizing future drought under increasing climactic stress in India.8 SPEI routinely performs well in hindcast comparisons with other popular drought indices, however, the development team has responded to user feedback and peer reviewed critiques by further adjusting distribution parameter fitting, performing a thorough examination of evapotranspiration methods, introducing an R package for custom user dataset creation,9 and introduced a real-time monitoring system.4


Vicente-Serrano, S. M., Beguería, S. & López-Moreno, J. I. A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate 23, 1696–1718 (2009).
Tirivarombo, S., Osupile, D. & Eliasson, P. Drought monitoring and analysis: Standardised Precipitation Evapotranspiration Index ( SPEI) and Standardised Precipitation Index ( SPI). Physics and Chemistry of the Earth, Parts A/B/C 106, 1–10 (2018).
Potopová, V., Štěpánek, P., Možný, M., Türkott, L. & Soukup, J. Performance of the standardised precipitation evapotranspiration index at various lags for agricultural drought risk assessment in the Czech Republic. Agricultural and Forest Meteorology 202, 26–38 (2015).
Beguería, S., Vicente-Serrano, S. M., Reig, F. & Latorre, B. Standardized precipitation evapotranspiration index ( SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology 34, 3001–3023 (2014).
Hayes, M. J., Svoboda, Mark. D., Wiihite, D. A. & Vanyarkho, O. V. Monitoring the 1996 Drought Using the Standardized Precipitation Index. Bulletin of the American Meteorological Society 80, 429–438 (1999).
Chen, T., Xia, G., Liu, T., Chen, W. & Chi, D. Assessment of Drought Impact on Main Cereal Crops Using a Standardized Precipitation Evapotranspiration Index in Liaoning Province, China. Sustainability 8, 1069 (2016).
Starks, P. J. et al. Assessment of the Standardized Precipitation and Evaporation Index ( SPEI) as a Potential Management Tool for Grasslands. Agronomy 9, 235 (2019).
Bisht, D. S., Sridhar, V. R., Mishra, A., Chatterjee, C. & Raghuwanshi, N. S. Characterization of future drought conditions in India using Standardized Precipitation Evapotranspiration Index. AGU Fall Meeting Abstracts 51, (2018).
Beguería, S. & Vicente-Serrano, S. M. SPEI: Calculation of the Standardised Precipitation- Evapotranspiration Index. (2017).

Citation Information:

  • Title: The Standardized Precipitation Evapotranspiration Index (SPEI)
  • Edition: Version 2.5
  • Publication Date: 2017
  • Data Form: raster
  • Publisher: Spanish National Research Council
  • Online Host:
  • DANTE Citekey: Vicente-Serrano2009

Dataset Contact Information:

Sergio M. Vicente-Serrano, Instituto Pirenaico de Ecología, Zaragoza, Spain 
Santiago Beguería, Estación Experimental de Aula Dei, Zaragoza, Spain 
Juan I. López-Moreno, Instituto Pirenaico de Ecología, Zaragoza, Spain 

Use Constraints:

Open Databse License (ODbL) v1.0


Drought is a major cause of agricultural, economic and environmental damage. Drought effects are apparent after a long period with a shortage of precipitation, making it very difficult to determine their onset, extent and end. Thus, it is hard to objectively quantify the characteristics of drought episodes in terms of their intensity, magnitude, duration and spatial extent. Much effort has been devoted to developing techniques for drought analysis and monitoring. Among these, the definition of quantitative indices is the most widespread approach, but subjectivity in the definition of drought has made it very difficult to establish a unique and universal drought index. Most studies related to drought analysis and monitoring systems have been conducted using either i) the Palmer Drought Severity Index (PDSI), based on a soil water balance equation, or ii) the Standardised Precipitation Index (SPI), based on a precipitation probabilistic approach.

Additional Metadata

Spatial Information:

Bounding Coordinates:

  • West Bounding Coordinate: -179.75
  • East Bounding Coordinate: 179.75
  • North Bounding Coordinate: 89.75
  • South Bounding Coordinate: -89.75

Spatial Reference Information:

  • Coordinate System: Longitude / Latitude
  • Resolution: 0.5
  • Units: decimal degrees
  • Geodetic Model: WGS84

Time Period Information:

  • Beginning Date: 1901
  • Ending Date: 2015
  • Resolution: monthly

Add new comment

Plain text

  • Allowed HTML tags: <a href hreflang> <em> <strong> <cite> <blockquote cite> <code> <ul type> <ol start type> <li> <dl> <dt> <dd>