Journal of Meteorological Research

, Volume 33, Issue 2, pp 159–189 | Cite as

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

  • Youlong Xia
  • Zengchao HaoEmail author
  • Chunxiang Shi
  • Yaohui Li
  • Jesse Meng
  • Tongren Xu
  • Xinying Wu
  • Baoqing Zhang
Special Collection on Development and Applications of Regional and Global Land Data Assimilation Systems


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.

Key words

land data assimilation system (LDAS) regional and global LDASs in-situ observation satellite retrieval land surface model (LSM) 


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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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Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2019

Authors and Affiliations

  • Youlong Xia
    • 1
  • Zengchao Hao
    • 2
    Email author
  • Chunxiang Shi
    • 3
  • Yaohui Li
    • 4
  • Jesse Meng
    • 1
  • Tongren Xu
    • 5
  • Xinying Wu
    • 2
  • Baoqing Zhang
    • 6
  1. 1.I.M. Systems Group at Environmental Modeling Center (EMC)National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA)College ParkUSA
  2. 2.College of Water SciencesBeijing Normal UniversityBeijingChina
  3. 3.National Meteorological Information CenterChina Meteorological AdministrationBeijingChina
  4. 4.Institute of Arid MeteorologyChina Meteorological AdministrationLanzhouChina
  5. 5.State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical ScienceBeijing Normal UniversityBeijingChina
  6. 6.Key Laboratory of Western China’s Environmental Systems of Ministry of Education, College of Earth and Environmental SciencesLanzhou UniversityLanzhouChina

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