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    Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

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    jhm-d-19-0123.1.pdf
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    Author
    Cui, Wenjun
    Dong, Xiquan
    Xi, Baike
    Feng, Zhe
    Fan, Jiwen cc
    Affiliation
    Univ Arizona, Dept Hydrol & Atmospher Sci
    Issue Date
    2020-01-16
    Keywords
    Precipitation
    Mesoscale systems
    Radars
    Radar observations
    Satellite observations
    
    Metadata
    Show full item record
    Publisher
    AMER METEOROLOGICAL SOC
    Citation
    Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?: Journal of Hydrometeorology: Vol 21, No 1. (2020). Retrieved February 4, 2020, from Journal of Hydrometeorology website: https://journals.ametsoc.org/doi/10.1175/JHM-D-19-0123.1 ‌
    Journal
    JOURNAL OF HYDROMETEOROLOGY
    Rights
    Copyright © 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
    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
    Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs' rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs' precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.
    Note
    6 month embargo; published online: 16 January 2020
    ISSN
    1525-755X
    DOI
    10.1175/jhm-d-19-0123.1
    Version
    Final published version
    ae974a485f413a2113503eed53cd6c53
    10.1175/jhm-d-19-0123.1
    Scopus Count
    Collections
    UA Faculty Publications

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