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High resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset for Central Asia

Update Frequency: Not Planned
Latest Data Update: 2021-05-27
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2021-06-03
DOI Publication Date: 2022-02-28
Download Stats: last 12 months
Dataset Size: 50 Files | 51GB


This dataset contains high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought data for Central Asia. There are forty-eight different SPEI time scales and the available period is from 1981 - 2018, the data was produced using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation dataset and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation dataset. The SPEI-HR dataset, over time and space, correlates fairly well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) dataset. Furthermore, the SPEI-HR dataset, for 6-month timescale, displayed a good correlation of 0.66 with GLEAM root zone soil moisture and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS).

Citable as:  Pyarali, K.; Peng, J.; Disse, M.; Tuo, Y. (2022): High resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset for Central Asia. NERC EDS Centre for Environmental Data Analysis, 28 February 2022. doi:10.5285/feb1e0b5426d4f5c80f791909a3a2d37.
Abbreviation: Not defined
Keywords: SPEI, Central Asia, drought


Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data was prepared for a Masters Thesis at the Chair of Hydrology and River Basin Management and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.

Data Quality:
Data is as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)..
File Format:
Data are NetCDF formatted

Citations: 1

The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.

Pyarali, K., Peng, J., Disse, M., & Tuo, Y. (2022). Development and application of high resolution SPEI drought dataset for Central Asia. Scientific Data, 9(1).

Process overview

This dataset was generated by the computation detailed below.

Standardized Precipitation Evapotranspiration Index (SPEI)


The SPEI dataset was developed by first aligning and formatting the precipitation and potential evaporation dataset using Climate Data Operators (CDO). Then a water deficit dataset was produced by subtracting these two datasets. Later, using R programming languages SPEI package, created by Santiago Beguería and Sergio M. Vicente-Serrano, the SPEI values were estimated for forty-eight different timescales. Finally, the dataset was validated using Climate Research Unit’s dataset, soil moisture dataset and Normalized Difference Vegetation Index dataset.

Input Description


Output Description


Software Reference


  • units: -
  • long_name: Standardized Precipitation Evapotranspiration Index
  • var_id: spei
  • var_id: mask_array
  • long_name: time
  • var_id: time

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: lat
  • long_name: lat
  • units: degrees_east
  • standard_name: longitude
  • var_id: lon
  • long_name: lon
Temporal Range
Start time:
End time:
Geographic Extent