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    A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States

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    Ma_et_al-2017-Journal_of_Geoph ...
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    Author
    Ma, Ning cc
    Niu, Guo-Yue
    Xia, Youlong
    Cai, Xitian cc
    Zhang, Yinsheng
    Ma, Yaoming
    Fang, Yuanhao cc
    Affiliation
    Univ Arizona, Dept Hydrol & Atmospher Sci
    Issue Date
    2017-11-27
    Keywords
    land surface model
    gross primary productivity
    energy fluxes
    snow cover fraction
    Noah-MP
    HUC2 region
    
    Metadata
    Show full item record
    Publisher
    AMER GEOPHYSICAL UNION
    Citation
    A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States 2017, 122 (22):12,245 Journal of Geophysical Research: Atmospheres
    Journal
    Journal of Geophysical Research: Atmospheres
    Rights
    ©2017. American Geophysical Union. All Rights Reserved.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating R-n but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.
    Note
    6 month embargo; published online: 24 November 2017
    ISSN
    2169897X
    DOI
    10.1002/2017JD027597
    Version
    Final published version
    Sponsors
    National Key Research and Development Program of China [2017YFA0603101]; China Postdoctoral Science Foundation [2017LH032, 2017M620069]; National Natural Science Foundation of China [41661144025, 41430748]; NASA MAP Program [80NSSC17K0352]; University of Arizona Germinating Research Program Success: Faculty Seed Grants
    Additional Links
    http://doi.wiley.com/10.1002/2017JD027597
    ae974a485f413a2113503eed53cd6c53
    10.1002/2017JD027597
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