High-resolution Global Multi-Index Drought (GMID) dataset, 1980-2024
https://doi.org/10.5285/f5ce92b0-03e8-4719-82ff-c62e6ebe927b
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Here, we present the Global Multi-Index Drought (GMID) dataset, which includes some of the most used and widely recommended standardised drought indices: the Standardized Precipitation Index (SPI), the Evaporative Drought Demand Index (EDDI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Evapotranspiration Deficit Index (SEDI), and the Standardized Vapor Pressure Deficit Index (SVPDI). This dataset is available on a global scale covering 1-12, 18, 24, 48-month time scales for the period 1980 to 2024, with high spatial (0.1 degrees) and temporal (weekly and monthly) resolution. GMID was generated using different meteorological input datasets, including: Multi-Source Weighted-Ensemble Precipitation (MSWEP) v2.8 (https://www.gloh2o.org/mswep/), Global Land Evaporation Amsterdam Model (GLEAM) v4.2a (https://www.gleam.eu/), and Multi-Source Weather (MSWX) vMSWX-Past (https://www.gloh2o.org/mswx/).
The GMID dataset is provided weekly and monthly, including two versions of the five drought indices: one generated using the "reference" approach (i.e., based on the probability distribution typically recommended in the literature for calculating these drought indices), and another using the "best-fit" approach (i.e., based on the probability distributions that provide better normalised resulting series for each case). GMID represents a comprehensive and robust global long-term dataset for drought (and flash drought) assessment, which will be further updated annually as input data become available.
The GMID dataset is provided weekly and monthly, including two versions of the five drought indices: one generated using the "reference" approach (i.e., based on the probability distribution typically recommended in the literature for calculating these drought indices), and another using the "best-fit" approach (i.e., based on the probability distributions that provide better normalised resulting series for each case). GMID represents a comprehensive and robust global long-term dataset for drought (and flash drought) assessment, which will be further updated annually as input data become available.
Publication date: 2026-03-31
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Format
NetCDF
Spatial information
Study area
Spatial representation type
Raster
Spatial reference system
WGS 84
Spatial resolution
11000 metres
Temporal information
Temporal extent
1980-01-01 to 2024-12-31
Temporal resolution
Weekly, Monthly
Provenance & quality
The drought indices were obtained by the standardization of different meteorological variables: precipitation, potential evapotranspiration, climatic water balance, evapotranspiration deficit and vapor pressure deficit.
Two different methods ("reference" and "best-fit" approach) were employed to standardize the variables. Reference version of the indices was calculated the probability distribution recommended by previous studies that explored the suitability of different probability distributions to calculate each drought index. By contrast, Best-fit version of the indices was calculated based on the probability distributions that provide better normalised resulting series for each case according to Shapiro-Wilks test.
Two different methods ("reference" and "best-fit" approach) were employed to standardize the variables. Reference version of the indices was calculated the probability distribution recommended by previous studies that explored the suitability of different probability distributions to calculate each drought index. By contrast, Best-fit version of the indices was calculated based on the probability distributions that provide better normalised resulting series for each case according to Shapiro-Wilks test.
Licensing and constraints
This dataset is available under the terms of the Open Government Licence 
Cite this dataset as:
Noguera, I.; Bulut, B.; Chevuturi, A.; Barker, L.J.; Hannaford, J. (2026). High-resolution Global Multi-Index Drought (GMID) dataset, 1980-2024. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/f5ce92b0-03e8-4719-82ff-c62e6ebe927b
Supplemental information
Wang, X., Alharbi, R. S., Baez-Villanueva, O. M., Green, A., McCabe, M. F., Wada, Y., Van Dijk, A. I. J. M., Abid, M. A., & Beck, H. E., (2025). Saudi Rainfall (SaRa): Hourly 0.1° Gridded Rainfall (1979-Present) for Saudi Arabia via Machine Learning Fusion of Satellite and Model Data. Hydrology and Earth System Sciences 29, 4983-5003.
Miralles, D.G., Bonte, O., Koppa, A., Baez-Villanueva, O.M., Tronquo, E., Zhong, F., Beck, H.E., Hulsman, P., Dorigo, W.A., Verhoest, N.E.C., Haghdoost, S., GLEAM4: global land evaporation and soil moisture dataset at 0.1° resolution from 1980 to near present, Scientific Data, 12, 416, 2025
Beck, H. E., van Dijk, A. I. J. M., Larraondo, P. R., McVicar, T. R., Pan, M., Dutra, E., and Miralles, D. G., MSWX: global 3‑hourly 0.1° bias-corrected meteorological data including near real-time updates and forecast ensembles. Bulletin of the American Meteorological Society 103, E710-E732.
Correspondence/contact details
Authors
https://orcid.org/0000-0002-0696-9504 Other contacts
Publisher
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Rights holder
UK Centre for Ecology & Hydrology
enquiries@ceh.ac.uk
Additional metadata
Keywords
Agriculture , Climate and climate change , drought , Environmental risk , Evaporative Drought Demand Index (EDDI) , flash drought , Hydrology , multiscalar , standardized drought indices , Standardized Evapotranspiration Deficit Index (SEDI) , Standardized Precipitation Evapotranspiration Index (SPEI) , Standardized Precipitation Index (SPI) , Standardized Vapor Pressure Deficit Index (SVPDI)
Funding
Natural Environment Research Council Award: NE/X006247/1