A global gridded dataset of GRACE drought severity index for 2002-14: Comparison with PDSI and SPEI and a case study of the Australia millennium drought

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Abstract

A new monthly global drought severity index (DSI) dataset developed from satellite-observed time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE) is presented. The GRACE-DSI record spans from 2002 to 2014 and will be extended with the ongoing GRACE and scheduled GRACE Follow-On missions. The GRACE-DSI captures major global drought events during the past decade and shows overall favorable spatiotemporal agreement with other commonly used drought metrics, including the Palmer drought severity index (PDSI) and the standardized precipitation evapotranspiration index (SPEI). The assets of the GRACE-DSI are 1) that it is based solely on satellite gravimetric observations and thus provides globally consistent drought monitoring, particularly where sparse ground observations (especially precipitation) constrain the use of traditional model-based monitoring methods; 2) that it has a large footprint (~350 km), so it is suitable for assessing regional- and global-scale drought; and 3) that it is sensitive to the overall terrestrial water storage component of the hydrologic cycle and therefore complements existing drought monitoring datasets by providing information about groundwater storage changes, which affect soil moisture recharge and drought recovery. In Australia, it is demonstrated that combining GRACE-DSI with other satellite environmental datasets improves the characterization of the 2000s "Millennium Drought" at shallow surface and subsurface soil layers. Contrasting vegetation greenness response to surface and underground water supply changes between western and eastern Australia is found, which might indicate that these regions have different relative plant rooting depths.

Original languageEnglish
Pages (from-to)2117-2129
Number of pages13
JournalJournal of Hydrometeorology
Volume18
Issue number8
DOIs
StatePublished - Aug 1 2017

Funding

Acknowledgments. This work was performed at the University of California, Irvine. Meng Zhao is supported by NASA Earth and Space Science Fellowship (NNX16AO64H), and all remaining authors are supported by NASA Grant NNX16AN05G and the Gordon and Betty Moore Foundation (GBMF3269). The GRACE-DSI and ancillary datasets analyzed in this paper will be freely available on the Velicogna’s research group website at the University of California, Irvine. We thank two anonymous reviewers and editor Dr. Christa Peters-Lidard for their careful reviews. This work was performed at the University of California, Irvine. Meng Zhao is supported by NASA Earth and Space Science Fellowship (NNX16AO64H), and all remaining authors are supported by NASA Grant NNX16AN05G and the Gordon and Betty Moore Foundation (GBMF3269). The GRACE-DSI and ancillary datasets analyzed in this paper will be freely available on the Velicogna's research group website at the University of California, Irvine. We thank two anonymous reviewers and editor Dr. Christa Peters-Lidard for their careful reviews.

FundersFunder number
National Aeronautics and Space AdministrationNNX16AN05G, NNX16AO64H
GBMF3269
University of California at Irvine

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 15 - Life on Land
      SDG 15 Life on Land

    Keywords

    • Drought
    • Hydrometeorology
    • Remote sensing

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