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    Comparison of SST Diurnal Variation Models Over the Tropical Warm Pool Region

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    Zhang_et_al-2018-Journal_of_Ge ...
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    Author
    Zhang, Haifeng
    Beggs, Helen
    Merchant, Christopher J.
    Wang, Xiao Hua
    Majewski, Leon
    Kiss, Andrew E.
    Rodríguez, José
    Thorpe, Livia
    Gentemann, Chelle
    Brunke, Michael
    Affiliation
    Univ Arizona, Dept Hydrol & Atmospher Sci
    Issue Date
    2018-05
    
    Metadata
    Show full item record
    Publisher
    AMER GEOPHYSICAL UNION
    Citation
    Zhang, H., Beggs, H., Merchant, C. J., Wang, X. H., Majewski, L., Kiss, A. E., et al. (2018). Comparison of SST diurnal variation models over the Tropical Warm Pool region. Journal of Geophysical Research: Oceans, 123, 3467‐3488. https://doi.org/10.1029/2017JC013517
    Journal
    JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
    Rights
    © 2018. 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
    Four sea surface temperature (SST) diurnal variation (DV) models have been compared against Multifunctional Transport Satellite-1R (MTSAT-1R) SST measurements over the Tropical Warm Pool (TWP) region (90 degrees E-170 degrees E, 25 degrees S-15 degrees N) for 4 months from January to April 2010. The four models include one empirical model formulated by Chelle Gentemann (hereafter CG03), one physical model proposed by Zeng and Beljaars in 2005 (ZB05) and its updated version (ZB+T), and one air-sea coupled model (the Met Office Unified Model Global Coupled configuration 2, GC2) with ZB05 warm layer scheme added on top of the standard configuration. The sensitivity of the v3 MTSAT-1R data to the "true'' changes in SST is first investigated using drifting buoys and is estimated to be 0.60 +/- 0.05. This being significantly different from 1, the models are validated against MTSAT-1R data and the same data scaled by the inverse of the sensitivity (representing an estimate of the true variability). Results indicate that all models are able to capture the general DV patterns but with differing accuracies and features. Specifically, CG03 and ZB+T underestimate strong (> 2 K) DV events' amplitudes especially if we assume that sensitivity-scaled MTSAT-1R variability is most realistic. ZB05 can effectively capture the DV cycles under most DV and wind conditions, as well as the DV spatial distribution. GC2 tends to overestimate small-moderate (< 2 K) DV events but can reasonably predict large DV events. One to three hour lags in warming start and peak times are found in GC2.
    Note
    6 month embargo; published online: 23 April 2018
    ISSN
    21699275
    DOI
    10.1029/2017JC013517
    Version
    Final published version
    Sponsors
    China Scholarship Council; Australian Government; ARC Centre of Excellence for Climate System Science [CE110001028]
    Additional Links
    http://doi.wiley.com/10.1029/2017JC013517
    ae974a485f413a2113503eed53cd6c53
    10.1029/2017JC013517
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