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    Improving Harvey Forecasts with Next-Generation Weather Satellites: Advanced Hurricane Analysis and Prediction with Assimilation of GOES-R All-Sky Radiances

    Source: Bulletin of the American Meteorological Society:;2019:;volume 100:;issue 007::page 1217
    Author:
    Zhang, Fuqing
    ,
    Minamide, Masashi
    ,
    Nystrom, Robert G.
    ,
    Chen, Xingchao
    ,
    Lin, Shian-Jian
    ,
    Harris, Lucas M.
    DOI: 10.1175/BAMS-D-18-0149.1
    Publisher: American Meteorological Society
    Abstract: AbstractHurricane Harvey brought catastrophic destruction and historical flooding to the Gulf Coast region in late August 2017. Guided by numerical weather prediction models, operational forecasters at NOAA provided outstanding forecasts of Harvey?s future path and potential for record flooding days in advance. These forecasts were valuable to the public and emergency managers in protecting lives and property. The current study shows the potential for further improving Harvey?s analysis and prediction through advanced ensemble assimilation of high-spatiotemporal all-sky infrared radiances from the newly launched, next-generation geostationary weather satellite, GOES-16. Although findings from this single-event study should be further evaluated, the results highlight the potential improvement in hurricane prediction that is possible via sustained investment in advanced observing systems, such as those from weather satellites, comprehensive data assimilation methodologies that can more effectively ingest existing and future observations, higher-resolution weather prediction models with more accurate numerics and physics, and high-performance computing facilities that can perform advanced analysis and forecasting in a timely manner.
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      Improving Harvey Forecasts with Next-Generation Weather Satellites: Advanced Hurricane Analysis and Prediction with Assimilation of GOES-R All-Sky Radiances

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4263742
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    • Bulletin of the American Meteorological Society

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    contributor authorZhang, Fuqing
    contributor authorMinamide, Masashi
    contributor authorNystrom, Robert G.
    contributor authorChen, Xingchao
    contributor authorLin, Shian-Jian
    contributor authorHarris, Lucas M.
    date accessioned2019-10-05T06:53:21Z
    date available2019-10-05T06:53:21Z
    date copyright2/6/2019 12:00:00 AM
    date issued2019
    identifier otherBAMS-D-18-0149.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263742
    description abstractAbstractHurricane Harvey brought catastrophic destruction and historical flooding to the Gulf Coast region in late August 2017. Guided by numerical weather prediction models, operational forecasters at NOAA provided outstanding forecasts of Harvey?s future path and potential for record flooding days in advance. These forecasts were valuable to the public and emergency managers in protecting lives and property. The current study shows the potential for further improving Harvey?s analysis and prediction through advanced ensemble assimilation of high-spatiotemporal all-sky infrared radiances from the newly launched, next-generation geostationary weather satellite, GOES-16. Although findings from this single-event study should be further evaluated, the results highlight the potential improvement in hurricane prediction that is possible via sustained investment in advanced observing systems, such as those from weather satellites, comprehensive data assimilation methodologies that can more effectively ingest existing and future observations, higher-resolution weather prediction models with more accurate numerics and physics, and high-performance computing facilities that can perform advanced analysis and forecasting in a timely manner.
    publisherAmerican Meteorological Society
    titleImproving Harvey Forecasts with Next-Generation Weather Satellites: Advanced Hurricane Analysis and Prediction with Assimilation of GOES-R All-Sky Radiances
    typeJournal Paper
    journal volume100
    journal issue7
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-D-18-0149.1
    journal fristpage1217
    journal lastpage1222
    treeBulletin of the American Meteorological Society:;2019:;volume 100:;issue 007
    contenttypeFulltext
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