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    Accuracy of Wind Fields Observed by a Bistatic Doppler Radar Network 

    Source: Journal of Atmospheric and Oceanic Technology:;2003:;volume( 020 ):;issue: 008:;page 1077
    Author(s): Satoh, Shinsuke; Wurman, Joshua
    Publisher: American Meteorological Society
    Abstract: The accuracy of wind vectors derived from bistatic dual-Doppler synthesis was investigated. The investigation was based on mathematical examinations and observation data analyses in both convective and stratiform cases. ...
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    Polarimetric Radar Observation of the Melting Layer in a Convective Rainfall System during the Rainy Season over the East China Sea 

    Source: Journal of Applied Meteorology and Climatology:;2010:;volume( 050 ):;issue: 002:;page 354
    Author(s): Shusse, Yukari; Takahashi, Nobuhiro; Nakagawa, Katsuhiro; Satoh, Shinsuke; Iguchi, Toshio
    Publisher: American Meteorological Society
    Abstract: During the rainy season over the East China Sea, convective rainfalls often show melting layer (ML) characteristics in polarimetric radar variables. In this research, the appearance ratio of the ML (the ratio of rainfall ...
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    Precipitation Nowcasting with Three-Dimensional Space–Time Extrapolation of Dense and Frequent Phased-Array Weather Radar Observations 

    Source: Weather and Forecasting:;2015:;volume( 031 ):;issue: 001:;page 329
    Author(s): Otsuka, Shigenori; Tuerhong, Gulanbaier; Kikuchi, Ryota; Kitano, Yoshikazu; Taniguchi, Yusuke; Ruiz, Juan Jose; Satoh, Shinsuke; Ushio, Tomoo; Miyoshi, Takemasa
    Publisher: American Meteorological Society
    Abstract: he phased-array weather radar (PAWR) is a new-generation weather radar that can make a 100-m-resolution three-dimensional (3D) volume scan every 30 s for 100 vertical levels, producing ~100 times more data than the ...
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    Nowcasting Multiparameter Phased-Array Weather Radar (MP-PAWR) Echoes of Localized Heavy Precipitation Using a 3D Recurrent Neural Network Trained with an Adversarial Technique 

    Source: Journal of Atmospheric and Oceanic Technology:;2023:;volume( 040 ):;issue: 007:;page 803
    Author(s): Baron, Philippe; Kawashima, Kohei; Kim, Dong-Kyun; Hanado, Hiroshi; Kawamura, Seiji; Maesaka, Takeshi; Nakagawa, Katsuhiro; Satoh, Shinsuke; Ushio, Tomoo
    Publisher: American Meteorological Society
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    “Big Data Assimilation” Revolutionizing Severe Weather Prediction 

    Source: Bulletin of the American Meteorological Society:;2016:;volume( 097 ):;issue: 008:;page 1347
    Author(s): Miyoshi, Takemasa; Kunii, Masaru; Ruiz, Juan; Lien, Guo-Yuan; Satoh, Shinsuke; Ushio, Tomoo; Bessho, Kotaro; Seko, Hiromu; Tomita, Hirofumi; Ishikawa, Yutaka
    Publisher: American Meteorological Society
    Abstract: udden local severe weather is a threat, and we explore what the highest-end supercomputing and sensing technologies can do to address this challenge. Here we show that using the Japanese flagship ?K? supercomputer, we can ...
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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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