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    Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

    Source: Weather and Forecasting:;2018:;volume 033:;issue 006::page 1587
    Author:
    Shimada, Udai
    ,
    Owada, Hiromi
    ,
    Yamaguchi, Munehiko
    ,
    Iriguchi, Takeshi
    ,
    Sawada, Masahiro
    ,
    Aonashi, Kazumasa
    ,
    DeMaria, Mark
    ,
    Musgrave, Kate D.
    DOI: 10.1175/WAF-D-18-0021.1
    Publisher: American Meteorological Society
    Abstract: AbstractThe Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind speed (Vmax)]. To further improve the accuracy of the Japan Meteorological Agency version of SHIPS, five new predictors associated with TC rainfall and structural features were incorporated into the scheme. Four of the five predictors were primarily derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetry of rainfall distribution around a TC multiplied by ocean heat content (OHC), rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain multiplied by OHC. The fifth predictor is the Rossby number. Among these predictors, the axisymmetry multiplied by OHC had the greatest impact on intensity change, particularly, at forecast times up to 42 h. The forecast results up to 5 days showed that the mean absolute error (MAE) of the Pmin forecast in SHIPS with the new predictors was improved by over 6% in the first half of the forecast period. The MAE of the Vmax forecast was also improved by nearly 4%. Regarding the Pmin forecast, the improvement was greatest (up to 13%) for steady-state TCs, including those initialized as tropical depressions, with slight improvement (2%?5%) for intensifying TCs. Finally, a real-time forecast experiment utilizing the hourly near-real-time GSMaP product demonstrated the improvement of the SHIPS forecasts, confirming feasibility for operational use.
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      Further Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4261422
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    • Weather and Forecasting

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    contributor authorShimada, Udai
    contributor authorOwada, Hiromi
    contributor authorYamaguchi, Munehiko
    contributor authorIriguchi, Takeshi
    contributor authorSawada, Masahiro
    contributor authorAonashi, Kazumasa
    contributor authorDeMaria, Mark
    contributor authorMusgrave, Kate D.
    date accessioned2019-09-19T10:05:30Z
    date available2019-09-19T10:05:30Z
    date copyright8/22/2018 12:00:00 AM
    date issued2018
    identifier otherwaf-d-18-0021.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261422
    description abstractAbstractThe Statistical Hurricane Intensity Prediction Scheme (SHIPS) is a multiple regression model for forecasting tropical cyclone (TC) intensity [both central pressure (Pmin) and maximum wind speed (Vmax)]. To further improve the accuracy of the Japan Meteorological Agency version of SHIPS, five new predictors associated with TC rainfall and structural features were incorporated into the scheme. Four of the five predictors were primarily derived from the hourly Global Satellite Mapping of Precipitation (GSMaP) reanalysis product, which is a microwave satellite-derived rainfall dataset. The predictors include the axisymmetry of rainfall distribution around a TC multiplied by ocean heat content (OHC), rainfall areal coverage, the radius of maximum azimuthal mean rainfall, and total volumetric rain multiplied by OHC. The fifth predictor is the Rossby number. Among these predictors, the axisymmetry multiplied by OHC had the greatest impact on intensity change, particularly, at forecast times up to 42 h. The forecast results up to 5 days showed that the mean absolute error (MAE) of the Pmin forecast in SHIPS with the new predictors was improved by over 6% in the first half of the forecast period. The MAE of the Vmax forecast was also improved by nearly 4%. Regarding the Pmin forecast, the improvement was greatest (up to 13%) for steady-state TCs, including those initialized as tropical depressions, with slight improvement (2%?5%) for intensifying TCs. Finally, a real-time forecast experiment utilizing the hourly near-real-time GSMaP product demonstrated the improvement of the SHIPS forecasts, confirming feasibility for operational use.
    publisherAmerican Meteorological Society
    titleFurther Improvements to the Statistical Hurricane Intensity Prediction Scheme Using Tropical Cyclone Rainfall and Structural Features
    typeJournal Paper
    journal volume33
    journal issue6
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-18-0021.1
    journal fristpage1587
    journal lastpage1603
    treeWeather and Forecasting:;2018:;volume 033:;issue 006
    contenttypeFulltext
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