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    Why Do Global Reanalyses and Land Data Assimilation Products Underestimate Snow Water Equivalent?

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    jhm-d-16-0056.pdf
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    Author
    Broxton, Patrick D.
    Zeng, Xubin
    Dawson, Nicholas
    Affiliation
    Univ Arizona, Dept Hydrol & Atmospher Sci
    Issue Date
    2016-11
    
    Metadata
    Show full item record
    Publisher
    AMER METEOROLOGICAL SOC
    Citation
    Why Do Global Reanalyses and Land Data Assimilation Products Underestimate Snow Water Equivalent? 2016, 17 (11):2743 Journal of Hydrometeorology
    Journal
    Journal of Hydrometeorology
    Rights
    © 2016 American Meteorological Society.
    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
    There is a large uncertainty of snow water equivalent (SWE) in reanalyses and the Global Land Data Assimilation System (GLDAS), but the primary reason for this uncertainty remains unclear. Here several reanalysis products and GLDAS with different land models are evaluated and the primary reason for their deficiencies are identified using two high-resolution SWE datasets, including the Snow Data Assimilation System product and a new dataset for SWE and snowfall for the conterminous United States (CONUS) that is based on PRISM precipitation and temperature data and constrained with thousands of point snow observations of snowfall and snow thickness. The reanalyses and GLDAS products substantially underestimate SWE in the CONUS compared to the high-resolution SWE data. This occurs irrespective of biases in atmospheric forcing information or differences in model resolution. Furthermore, reanalysis and GLDAS products that predict more snow ablation at near-freezing temperatures have larger underestimates of SWE. Since many of the products do not assimilate information about SWE and snow thickness, this indicates a problem with the implementation of land models and pinpoints the need to improve the treatment of snow ablation in these systems, especially at near-freezing temperatures.
    Note
    Published Online: 7 November 2016; 6 Month Embargo.
    ISSN
    1525-755X
    1525-7541
    DOI
    10.1175/JHM-D-16-0056.1
    Version
    Final published version
    Sponsors
    NASA [NNX14AM02G]; NOAA [NA13NES4400003]; NSF [AGS-0944101]
    Additional Links
    http://journals.ametsoc.org/doi/10.1175/JHM-D-16-0056.1
    ae974a485f413a2113503eed53cd6c53
    10.1175/JHM-D-16-0056.1
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