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Regional and Global Land Data Assimilation Systems: Innovations, Challenges, and Prospects

  • Special Collection on Development and Applications of Regional and Global Land Data Assimilation Systems
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Abstract

Since the North American and Global Land Data Assimilation Systems (NLDAS and GLDAS) were established in 2004, significant progress has been made in development of regional and global LDASs. National, regional, project-based, and global LDASs are widely developed across the world. This paper summarizes and overviews the development, current status, applications, challenges, and future prospects of these LDASs. We first introduce various regional and global LDASs including their development history and innovations, and then discuss the evaluation, validation, and applications (from numerical model prediction to water resources management) of these LDASs. More importantly, we document in detail some specific challenges that the LDASs are facing: quality of the in-situ observations, satellite retrievals, reanalysis data, surface meteorological forcing data, and soil and vegetation databases; land surface model physical process treatment and parameter calibration; land data assimilation difficulties; and spatial scale incompatibility problems. Finally, some prospects such as the use of land information system software, the unified global LDAS system with nesting concept and hyper-resolution, and uncertainty estimates for model structure, parameters, and forcing are discussed.

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Acknowledgment

The authors thank Eric Luebehusen of U.S. Department of Agriculture who helped us generate Fig. 5. We acknowledge Mary Hart for proofreading and editing our first draft, Holly Norton and Roshan Shrestha for the EMC internal review, and three anonymous reviewers for valuable comments.

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Authors and Affiliations

  1. I.M. Systems Group at Environmental Modeling Center (EMC), National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), College Park, MD, 20740, USA

    Youlong Xia & Jesse Meng

  2. College of Water Sciences, Beijing Normal University, Beijing, 100875, China

    Zengchao Hao & Xinying Wu

  3. National Meteorological Information Center, China Meteorological Administration, Beijing, 100081, China

    Chunxiang Shi

  4. Institute of Arid Meteorology, China Meteorological Administration, Lanzhou, 730020, China

    Yaohui Li

  5. State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China

    Tongren Xu

  6. Key Laboratory of Western China’s Environmental Systems of Ministry of Education, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China

    Baoqing Zhang

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  1. Youlong Xia
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  2. Zengchao Hao
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Correspondence to Zengchao Hao.

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Supported by the US Environmental Modeling Center (EMC) Land Surface Modeling Project (granted to Youlong Xia) and National Natural Science Foundation of China (51609111, granted to Baoqing Zhang).

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Xia, Y., Hao, Z., Shi, C. et al. Regional and Global Land Data Assimilation Systems: Innovations, Challenges, and Prospects. J Meteorol Res 33, 159–189 (2019). https://doi.org/10.1007/s13351-019-8172-4

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