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    Objective Reduction of Rain Gauge Network via Geostatistical Analysis of Uncertainty in Radar-Gauge Precipitation Estimation 

    Source: Journal of Hydrologic Engineering:;2015:;Volume ( 020 ):;issue: 004
    Author(s): Dong-Jun Seo; Ridwan Siddique; Peter Ahnert
    Publisher: American Society of Civil Engineers
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    Mean-Field Rainfall Bias Studies for WSR-88D 

    Source: Journal of Hydrologic Engineering:;1998:;Volume ( 003 ):;issue: 003
    Author(s): Emmanouil N. Anagnostou; Witold F. Krajewski; Dong-Jun Seo; Edward R. Johnson
    Publisher: American Society of Civil Engineers
    Abstract: Real-time radar-rainfall bias adjustment procedures for weather surveillance Doppler radar (WSR-88D) are investigated. Statistical analysis of the mean-field bias is performed on a 2-year record of WSR-88D observations ...
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    Independent Assessment of Incremental Complexity in NWS Multisensor Precipitation Estimator Algorithms 

    Source: Journal of Hydrologic Engineering:;2013:;Volume ( 018 ):;issue: 002
    Author(s): Emad Habib; Lingling Qin; Dong-Jun Seo; Grzegorz J. Ciach; Brian R. Nelson
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents a comprehensive intercomparison analysis of different radar-based multisensor precipitation products generated operationally by the National Weather Service (NWS) Multisensor Precipitation Estimator ...
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    Creation of Multisensor Precipitation Products from WSI NOWrad Reflectivity Data 

    Source: Journal of Hydrologic Engineering:;2017:;Volume ( 022 ):;issue: 005
    Author(s): Yu Zhang; David Kitzmiller; Dong-Jun Seo; Dongsoo Kim; Robert Cifelli
    Publisher: American Society of Civil Engineers
    Abstract: Radar and multisensor quantitative precipitation estimates (QPEs) have played a critical role in real-time hydrologic and weather predictions. The utility of this data set for hydrologic model calibration, however, is ...
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    Improving Probabilistic Quantitative Precipitation Forecasts Using Short Training Data through Artificial Neural Networks 

    Source: Journal of Hydrometeorology:;2022:;volume( 023 ):;issue: 009:;page 1365
    Author(s): Mohammadvaghef Ghazvinian; Yu Zhang; Thomas M. Hamill; Dong-Jun Seo; Nelun Fernando
    Publisher: American Meteorological Society
    Abstract: Conventional statistical postprocessing techniques offer limited ability to improve the skills of probabilistic guidance for heavy precipitation. This paper introduces two artificial neural network (ANN)-based, geographically ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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