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<p>Drought, characterized by below-average water supply, profoundly affects regional water resources and various ecosystem services. The Palmer Drought Severity Index (PDSI) is a widely used metric for drought monitoring and climate change assessments but suffers from inherent climatic inconsistencies and lacks comprehensive and reliable estimates under changing climate conditions. Here we develop a monthly multi-model and multi-scenario dataset of self-calibrated PDSI for the period 1850–2094, derived from 11 climate model outputs within the Coupled Model Intercomparison Project 6 (PDSI_CMIP6). The traditional two-layer bucket model in PDSI is replaced with direct hydrological outputs from CMIP6 models, ensuring alignment with CMIP6 projections. The PDSI estimates are validated against soil moisture simulations through correlation and regression analysis. Application of the dataset reveals pronounced spatial heterogeneity in long-term drought trends across continents, with limited global-mean change but notable regional intensification under climate change. This dataset provides uncertainty-constrained quantifications of terrestrial moisture conditions in a changing climate, faithfully reflecting CMIP6-projected hydrological changes.</p>

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PDSI_CMIP6: an ensemble CMIP6-projected self-calibrated Palmer drought severity index dataset

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月16日

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  • Jinghua Xiong,
  • Yuting Yang

摘要

Drought, characterized by below-average water supply, profoundly affects regional water resources and various ecosystem services. The Palmer Drought Severity Index (PDSI) is a widely used metric for drought monitoring and climate change assessments but suffers from inherent climatic inconsistencies and lacks comprehensive and reliable estimates under changing climate conditions. Here we develop a monthly multi-model and multi-scenario dataset of self-calibrated PDSI for the period 1850–2094, derived from 11 climate model outputs within the Coupled Model Intercomparison Project 6 (PDSI_CMIP6). The traditional two-layer bucket model in PDSI is replaced with direct hydrological outputs from CMIP6 models, ensuring alignment with CMIP6 projections. The PDSI estimates are validated against soil moisture simulations through correlation and regression analysis. Application of the dataset reveals pronounced spatial heterogeneity in long-term drought trends across continents, with limited global-mean change but notable regional intensification under climate change. This dataset provides uncertainty-constrained quantifications of terrestrial moisture conditions in a changing climate, faithfully reflecting CMIP6-projected hydrological changes.