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    Performance of the Navy’s Tropical Cyclone Prediction Model in the Western North Pacific Basin during 1996

    Source: Weather and Forecasting:;1999:;volume( 014 ):;issue: 003::page 297
    Author:
    Rennick, M. A.
    DOI: 10.1175/1520-0434(1999)014<0297:POTNST>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: The U.S. Navy?s operational implementation of the hurricane prediction system developed at the National Oceanographic and Atmospheric Administration?s Geophysical Fluid Dynamics Laboratory is described, and the performance of the model during the 1996 western North Pacific tropical cyclone season is analyzed. The model was highly reliable in terms of maintaining and tracking tropical cyclones, maintaining 96%, 93%, and 93% of all tropical storms and typhoons at 24-, 48-, and 72-h forecast periods. Subsequent model improvements raised these percentages to 96%, 93%, and 100%. Overall track errors were 176, 316, and 466 km for the same periods. Errors for tropical storms and typhoons were 75?150 km smaller than those for tropical depressions. The difference generally grew with forecast length. Large track errors were generally associated with a sheared environment, spurious interactions with elevated terrain, or poorly timed recurvature. On average, the model slightly underforecast intensity, but intense systems were significantly underforecast due to the inability of the model to resolve the eyewall. For the entire season, tropical cyclone track errors are very similar to those of the navy?s global model, Navy Operational Global Atmospheric Prediction System. However, significant differences are found in individual forecasts. Further study is required to identify environmental features that lead to systematic differences in model performance.
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      Performance of the Navy’s Tropical Cyclone Prediction Model in the Western North Pacific Basin during 1996

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    contributor authorRennick, M. A.
    date accessioned2017-06-09T14:57:12Z
    date available2017-06-09T14:57:12Z
    date copyright1999/06/01
    date issued1999
    identifier issn0882-8156
    identifier otherams-3041.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4167746
    description abstractThe U.S. Navy?s operational implementation of the hurricane prediction system developed at the National Oceanographic and Atmospheric Administration?s Geophysical Fluid Dynamics Laboratory is described, and the performance of the model during the 1996 western North Pacific tropical cyclone season is analyzed. The model was highly reliable in terms of maintaining and tracking tropical cyclones, maintaining 96%, 93%, and 93% of all tropical storms and typhoons at 24-, 48-, and 72-h forecast periods. Subsequent model improvements raised these percentages to 96%, 93%, and 100%. Overall track errors were 176, 316, and 466 km for the same periods. Errors for tropical storms and typhoons were 75?150 km smaller than those for tropical depressions. The difference generally grew with forecast length. Large track errors were generally associated with a sheared environment, spurious interactions with elevated terrain, or poorly timed recurvature. On average, the model slightly underforecast intensity, but intense systems were significantly underforecast due to the inability of the model to resolve the eyewall. For the entire season, tropical cyclone track errors are very similar to those of the navy?s global model, Navy Operational Global Atmospheric Prediction System. However, significant differences are found in individual forecasts. Further study is required to identify environmental features that lead to systematic differences in model performance.
    publisherAmerican Meteorological Society
    titlePerformance of the Navy’s Tropical Cyclone Prediction Model in the Western North Pacific Basin during 1996
    typeJournal Paper
    journal volume14
    journal issue3
    journal titleWeather and Forecasting
    identifier doi10.1175/1520-0434(1999)014<0297:POTNST>2.0.CO;2
    journal fristpage297
    journal lastpage305
    treeWeather and Forecasting:;1999:;volume( 014 ):;issue: 003
    contenttypeFulltext
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