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A Global Multiscale SPEI Dataset under an Ensemble Approach

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  • Monia Santini

    (Division on Impacts on Agriculture, Forests and Ecosystem Services (IAFES), Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 01100 Viterbo, Italy)

  • Sergio Noce

    (Division on Impacts on Agriculture, Forests and Ecosystem Services (IAFES), Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 01100 Viterbo, Italy)

  • Marco Mancini

    (Division on Advanced Scientific Computing (ASC), Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 73100 Lecce, Italy)

  • Luca Caporaso

    (Division on Impacts on Agriculture, Forests and Ecosystem Services (IAFES), Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), 01100 Viterbo, Italy
    European Commission-Joint Research Centre (JRC), 21027 Ispra, Italy)

Abstract

A new multiscale Standardized Precipitation Evapotranspiration Index (SPEI) dataset is provided for a reference period (1960–1999) and two future time horizons (2040–2079) and (2060–2099). The historical forcing is based on combined climate observations and reanalysis (WATer and global CHange Forcing Dataset), and the future projections are fed by the Fast Track experiment of the Inter-Sectoral Impact Model Intercomparison Project under representative concentration pathways (RCPs) 4.5 and 8.5 and by an additional Earth system model (CMCC-CESM) forced by RCP 8.5. To calculate the potential evapotranspiration (PET) input to the SPEI, the Hargreaves–Samani and Thornthwaite equations were adopted. This ensemble considers uncertainty due to different climate models, development pathways, and input formulations. The SPEI is provided for accumulation periods of potential moisture deficit from 1 to 18 months starting in each month of the year, with a focus on the within-period variability, excluding long-term warming effects on PET. In addition to supporting drought analyses, this dataset is also useful for assessing wetter-than-normal conditions spanning one or more months. The SPEI was calculated using the SPEIbase package.

Suggested Citation

  • Monia Santini & Sergio Noce & Marco Mancini & Luca Caporaso, 2023. "A Global Multiscale SPEI Dataset under an Ensemble Approach," Data, MDPI, vol. 8(2), pages 1-14, February.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:2:p:36-:d:1058653
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    References listed on IDEAS

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    1. Yongxia Ding & Shouzhang Peng, 2020. "Spatiotemporal Trends and Attribution of Drought across China from 1901–2100," Sustainability, MDPI, vol. 12(2), pages 1-17, January.
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