Online Drought Indicators and Indices

Global Land Data Assimilation System (GLDAS)

 

Index name: Global Land Data Assimilation System (GLDAS).

Ease of use: Green.

Origins: Rodell led the work, which involved scientists from NASA and NOAA in the United States.

Characteristics: Uses a system of surface and remotely sensed data along with land surface models and data assimilation techniques to provide data on terrestrial conditions. Output includes soil moisture characteristics, which are a good drought indicator.

Input parameters: Land surface models, surface-based meteorological observations, vegetation classifications and satellite data.

Applications: Useful for determining river and streamflow projections as well as runoff components based on current conditions; ideal for monitoring droughts that have multiple impacts.

Strengths: As it is global in nature and available at a high resolution, it can represent most areas. Useful for monitoring developing drought in areas that are data poor.

Weaknesses: The grid size is not sufficiently fine for island nations. Only areas that lack near-real-time surface observations are represented by the data assimilation process.

Resources: The methodology and inputs are well described in the literature. Output is available online at the National Center for Atmospheric Research (NCAR) webpage on NLDAS: North American Land Data Assimilation System; the NASA webpage on LDAS Land Data Assimilation Systems and the Goddard Earth Sciences Data and Information Services Center (GES DISC) data collection of GLDAS.

References:
Mitchell, K., D. Lohman, P. Houser, E. Wood, J. Schaake, A. Robock, B. Cosgrove, J. Sheffield, Q. Duan, L. Luo, R. Higgins, R. Pinker, J. Tarpley, D. Lettenmaier, C. Marshall, J. Entin, M. Pan, W. Shi, V. Koren, J. Meng, B. Ramsay and A. Bailey, 2004: The multi-institution North American Land Data Assimilation System (NLDAS): utilizing multiple GCIP products and partners in a continental distributed hydrological modelling system. Journal of Geophysical Research, 109:D07S90. DOI: 10.1029/2003JD003823.

Rodell, M., P. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosogrove, J. Radakovich, M. Bosilovich, J. Entin, J. Walker, D. Lohmann and D. Toll, 2004: The Global Land Data Assimilation System. Bulletin of the American Meteorological Society, 85(3): 381–394. DOI: 10.1175/BAMS-85-3-381.

Xia, Y., K. Mitchell, M. Ek, J. Sheffield, B. Cosgrove, E. Wood, L. Luo, C. Alonge, H. Wei, J. Meng, B. Livneh, D. Lettenmaier, V. Koren, Q. Duan, K. Mo, Y. Fan and D. Mocko, 2012: Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. Journal of Geophysical Research, 117: D03109. DOI: 10.1029/2011JD016048.

2 Comments
  1. adugnaw nega
    March 4, 2021 Reply

    how can we get soil moisture and evapotranspiration without using programing

    1. Katrin Ehlert
      March 23, 2021 Reply

      Dear Adugnaw Nega

      Thank you for your question. The GLDAS project combines a multitude of ground and space-based observations in order to create global datasets on key parameters (including soil moisture and evapotranspiration) and fluxes through different models. Datasets can be obtained through the GLDAS/GES DISC online portal (e.g. https://disc.gsfc.nasa.gov/datasets?keywords=GLDAS) and extensive documentation is available online (see references above).

      Best regards
      IDMP TSU

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