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A Global Multiscale SPEI Dataset under an Ensemble Approach

Data, ISSN: 2306-5729, Vol: 8, Issue: 2
2023
  • 4
    Citations
  • 0
    Usage
  • 10
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    4
    • Citation Indexes
      3
    • Policy Citations
      1
      • Policy Citation
        1
  • Captures
    10
  • Mentions
    1
    • Blog Mentions
      1
      • Blog
        1

Most Recent Blog

Data, Vol. 8, Pages 36: A Global Multiscale SPEI Dataset under an Ensemble Approach

Data, Vol. 8, Pages 36: A Global Multiscale SPEI Dataset under an Ensemble Approach Data doi: 10.3390/data8020036 Authors: Monia Santini Sergio Noce Marco Mancini Luca

Article Description

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. Dataset:https://doi.org/10.25424/cmcc-mfd5-t060 (accessed on 3 February 2023). Dataset License: The dataset is made available under license CC-BY.

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