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The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system

Authors

  • Kenneth E. Mitchell,

    1. Environmental Modeling Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration–National Weather Service, Camp Springs, Maryland, USA
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  • Dag Lohmann,

    1. Environmental Modeling Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration–National Weather Service, Camp Springs, Maryland, USA
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  • Paul R. Houser,

    1. Hydrological Sciences Branch and Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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  • Eric F. Wood,

    1. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
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  • John C. Schaake,

    1. Office of Hydrologic Development, National Oceanic and Atmospheric Administration–National Weather Service, Silver Spring, Maryland, USA
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  • Alan Robock,

    1. Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey, USA
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  • Brian A. Cosgrove,

    1. Hydrological Sciences Branch and Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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  • Justin Sheffield,

    1. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
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  • Qingyun Duan,

    1. Office of Hydrologic Development, National Oceanic and Atmospheric Administration–National Weather Service, Silver Spring, Maryland, USA
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  • Lifeng Luo,

    1. Department of Environmental Sciences, Rutgers University, New Brunswick, New Jersey, USA
    2. Now at Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA.
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  • R. Wayne Higgins,

    1. Climate Prediction Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration–National Weather Service, Camp Springs, Maryland, USA
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  • Rachel T. Pinker,

    1. Department of Meteorology, University of Maryland, College Park, Maryland, USA
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  • J. Dan Tarpley,

    1. Office of Research and Applications, National Environmental Satellite Data and Information Service, Camp Springs, Maryland, USA
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  • Dennis P. Lettenmaier,

    1. Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, USA
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  • Curtis H. Marshall,

    1. Environmental Modeling Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration–National Weather Service, Camp Springs, Maryland, USA
    2. Now at Department of Atmospheric Sciences, Colorado State University, Fort Collins, Colorado, USA.
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  • Jared K. Entin,

    1. Hydrological Sciences Branch and Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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  • Ming Pan,

    1. Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
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  • Wei Shi,

    1. Climate Prediction Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration–National Weather Service, Camp Springs, Maryland, USA
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  • Victor Koren,

    1. Office of Hydrologic Development, National Oceanic and Atmospheric Administration–National Weather Service, Silver Spring, Maryland, USA
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  • Jesse Meng,

    1. Environmental Modeling Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration–National Weather Service, Camp Springs, Maryland, USA
    2. Hydrological Sciences Branch and Data Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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  • Bruce H. Ramsay,

    1. Office of Research and Applications, National Environmental Satellite Data and Information Service, Camp Springs, Maryland, USA
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  • Andrew A. Bailey

    1. Office of Research and Applications, National Environmental Satellite Data and Information Service, Camp Springs, Maryland, USA
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Abstract

[1] Results are presented from the multi-institution partnership to develop a real-time and retrospective North American Land Data Assimilation System (NLDAS). NLDAS consists of (1) four land models executing in parallel in uncoupled mode, (2) common hourly surface forcing, and (3) common streamflow routing: all using a 1/8° grid over the continental United States. The initiative is largely sponsored by the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP). As the overview for nine NLDAS papers, this paper describes and evaluates the 3-year NLDAS execution of 1 October 1996 to 30 September 1999, a period rich in observations for validation. The validation emphasizes (1) the land states, fluxes, and input forcing of four land models, (2) the application of new GCIP-sponsored products, and (3) a multiscale approach. The validation includes (1) mesoscale observing networks of land surface forcing, fluxes, and states, (2) regional snowpack measurements, (3) daily streamflow measurements, and (4) satellite-based retrievals of snow cover, land surface skin temperature (LST), and surface insolation. The results show substantial intermodel differences in surface evaporation and runoff (especially over nonsparse vegetation), soil moisture storage, snowpack, and LST. Owing to surprisingly large intermodel differences in aerodynamic conductance, intermodel differences in midday summer LST were unlike those expected from the intermodel differences in Bowen ratio. Last, anticipating future assimilation of LST, an NLDAS effort unique to this overview paper assesses geostationary-satellite-derived LST, determines the latter to be of good quality, and applies the latter to validate modeled LST.

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