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    Hybrid Ensemble–Variational Filter: A Spatially and Temporally Varying Adaptive Algorithm to Estimate Relative Weighting 

    Source: Monthly Weather Review:;2021:;volume( 149 ):;issue: 001:;page 65
    Author(s): El Gharamti, Mohamad
    Publisher: American Meteorological Society
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    Enhanced Adaptive Inflation Algorithm for Ensemble Filters 

    Source: Monthly Weather Review:;2018:;volume 146:;issue 002:;page 623
    Author(s): El Gharamti, Mohamad
    Publisher: American Meteorological Society
    Abstract: AbstractSpatially and temporally varying adaptive inflation algorithms have been developed to combat the loss of variance during the forecast due to various model and sampling errors. The adaptive Bayesian scheme of Anderson ...
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    A One-Step-Ahead Ensemble Kalman Smoothing Approach Toward Estimating the Tropical Cyclone Surface-Exchange Coefficients 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 003
    Author(s): Nystrom, Robert G.; Snyder, Chris; El Gharamti, Mohamad
    Publisher: American Meteorological Society
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    A One-Step-Ahead Ensemble Kalman Smoothing Approach Toward Estimating the Tropical Cyclone Surface-Exchange Coefficients 

    Source: Monthly Weather Review:;2023:;volume( 151 ):;issue: 003:;page 625
    Author(s): Nystrom, Robert G.; Snyder, Chris; El Gharamti, Mohamad
    Publisher: American Meteorological Society
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    Comparing Adaptive Prior and Posterior Inflation for Ensemble Filters Using an Atmospheric General Circulation Model 

    Source: Monthly Weather Review:;2019:;volume 147:;issue 007:;page 2535
    Author(s): El Gharamti, Mohamad; Raeder, Kevin; Anderson, Jeffrey; Wang, Xuguang
    Publisher: American Meteorological Society
    Abstract: AbstractSampling errors and model errors are major drawbacks from which ensemble Kalman filters suffer. Sampling errors arise because of the use of a limited ensemble size, while model errors are deficiencies in the dynamics ...
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    Towards an End-to-End Analysis and Prediction System for Weather, Climate, and Marine Applications in the Red Sea 

    Source: Bulletin of the American Meteorological Society:;2020:;volume( ):;issue: -:;page 1
    Author(s): Hoteit, Ibrahim;Abualnaja, Yasser;Afzal, Shehzad;Ait-El-Fquih, Boujemaa;Akylas, Triantaphyllos;Antony, Charls;Dawson, Clint;Asfahani, Khaled;Brewin, Robert J.;Cavaleri, Luigi;Cerovecki, Ivana;Cornuelle, Bruce;Desamsetti, Srinivas;Attada, Raju;Dasari, Hari;Sanchez-Garrido, Jose;Genevier, Lily;El Gharamti, Mohamad;Gittings, John A.;Gokul, Elamurugu;Gopalakrishnan, Ganesh;Guo, Daquan;Hadri, Bilel;Hadwiger, Markus;Hammoud, Mohammed Abed;Hendershott, Myrl;Hittawe, Mohamad;Karumuri, Ashok;Knio, Omar;Köhl, Armin;Kortas, Samuel;Krokos, George;Kunchala, Ravi;Issa, Leila;Lakkis, Issam;Langodan, Sabique;Lermusiaux, Pierre;Luong, Thang;Ma, Jingyi;Le Maitre, Olivier;Mazloff, Matthew;El Mohtar, Samah;Papadopoulos, Vassilis P.;Platt, Trevor;Pratt, Larry;Raboudi, Naila;Racault, Marie-Fanny;Raitsos, Dionysios E.;Razak, Shanas;Sanikommu, Sivareddy;Sathyendranath, Shubha;Sofianos, Sarantis;Subramanian, Aneesh;Sun, Rui;Titi, Edriss;Toye, Habib;Triantafyllou, George;Tsiaras, Kostas;Vasou, Panagiotis;Viswanadhapalli, Yesubabu;Wang, Yixin;Yao, Fengchao;Zhan, Peng;Zodiatis, George
    Publisher: American Meteorological Society
    Abstract: An integrated, high resolution, data-driven regional modeling system has been recently developed for the Red Sea region and is being used for research and various environmental applications.The Red Sea, home to the ...
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    DSpace software copyright © 2002-2015  DuraSpace
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