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    A novel Machine Learning-based gap-filling of fine-resolution remotely sensed snow cover fraction data by combining downscaling and regression 

    Source: Journal of Hydrometeorology:;2021:;volume( ):;issue:
    Author(s): Yatheendradas, Soni;Kumar, Sujay
    Publisher: American Meteorological Society
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    Satellite Precipitation Characterization, Error Modeling, and Error Correction Using Censored Shifted Gamma Distributions 

    Source: Journal of Hydrometeorology:;2017:;Volume( 018 ):;issue: 010:;page 2801
    Author(s): Wright, Daniel B.;Kirschbaum, Dalia B.;Yatheendradas, Soni
    Publisher: American Meteorological Society
    Abstract: AbstractSatellite multisensor precipitation products (SMPPs) have a variety of potential uses but suffer from relatively poor accuracy due to systematic biases and random errors in precipitation occurrence and magnitude. ...
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    Parameter Sensitivity of the Noah-MP Land Surface Model with Dynamic Vegetation 

    Source: Journal of Hydrometeorology:;2018:;volume 019:;issue 005:;page 815
    Author(s): Arsenault, Kristi R.; Nearing, Grey S.; Wang, Shugong; Yatheendradas, Soni; Peters-Lidard, Christa D.
    Publisher: American Meteorological Society
    Abstract: Abstract The Noah land surface model with multiple parameterization options (Noah-MP) includes a routine for the dynamic simulation of vegetation carbon assimilation and soil carbon decomposition processes. To use remote ...
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    Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor 

    Source: Journal of Hydrometeorology:;2023:;volume( 024 ):;issue: 009:;page 1457
    Author(s): Yatheendradas, Soni; Mocko, David M.; Peters-Lidard, Christa; Kumar, Sujay
    Publisher: American Meteorological Society
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    Calculating Crop Water Requirement Satisfaction in the West Africa Sahel with Remotely Sensed Soil Moisture 

    Source: Journal of Hydrometeorology:;2015:;Volume( 016 ):;issue: 001:;page 295
    Author(s): McNally, Amy; Husak, Gregory J.; Brown, Molly; Carroll, Mark; Funk, Chris; Yatheendradas, Soni; Arsenault, Kristi; Peters-Lidard, Christa; Verdin, James P.
    Publisher: American Meteorological Society
    Abstract: he Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this ...
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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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