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    The Forecast Skill of Tropical Cyclone Genesis in Two Global Ensembles

    Source: Weather and Forecasting:;2022:;volume( 038 ):;issue: 001::page 83
    Author:
    Xiping Zhang
    ,
    Juan Fang
    ,
    Zifeng Yu
    DOI: 10.1175/WAF-D-22-0145.1
    Publisher: American Meteorological Society
    Abstract: Tropical cyclone (TC) genesis forecasts during 2018–20 from two operational global ensemble prediction systems (EPSs) are evaluated over three basins in this study. The two ensembles are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the MetOffice in the United Kingdom (UKMO-EPS). The three basins include the northwest Pacific, northeast Pacific, and the North Atlantic. It is found that the ensemble members in each EPS show a good level of agreement in forecast skill, but their forecasts are complementary. Probability of detection (POD) can be doubled by taking all the member forecasts in the EPS into account. Even if an ensemble member does not make a hit forecast, it may predict the presence of cyclonic vortices. Statistically, a hit forecast has more nearby disturbance forecasts in the ensemble than a false alarm. Based on the above analysis, we grouped the nearby forecasts at each model initialization time to define ensemble genesis forecasts, and verified these forecasts to represent the performance of the ensemble system. The PODs are found to be more than twice that of the individual ensemble members at most lead times, which is about 59% and 38% at the 5-day lead time in UKMO-EPS and ECMWF-EPS, respectively; while the success ratios are smaller compared with that of the ensemble members. In addition, predictability differs in different basins, and genesis events in the North Atlantic basin are the most difficult to forecast in EPS, and its POD at the 5-day lead time is only 46% and 23% in UKMO-EPS and ECMWF-EPS, respectively.
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      The Forecast Skill of Tropical Cyclone Genesis in Two Global Ensembles

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    contributor authorXiping Zhang
    contributor authorJuan Fang
    contributor authorZifeng Yu
    date accessioned2023-04-12T18:46:58Z
    date available2023-04-12T18:46:58Z
    date copyright2022/12/29
    date issued2022
    identifier otherWAF-D-22-0145.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290244
    description abstractTropical cyclone (TC) genesis forecasts during 2018–20 from two operational global ensemble prediction systems (EPSs) are evaluated over three basins in this study. The two ensembles are from the European Centre for Medium-Range Weather Forecasts (ECMWF-EPS) and the MetOffice in the United Kingdom (UKMO-EPS). The three basins include the northwest Pacific, northeast Pacific, and the North Atlantic. It is found that the ensemble members in each EPS show a good level of agreement in forecast skill, but their forecasts are complementary. Probability of detection (POD) can be doubled by taking all the member forecasts in the EPS into account. Even if an ensemble member does not make a hit forecast, it may predict the presence of cyclonic vortices. Statistically, a hit forecast has more nearby disturbance forecasts in the ensemble than a false alarm. Based on the above analysis, we grouped the nearby forecasts at each model initialization time to define ensemble genesis forecasts, and verified these forecasts to represent the performance of the ensemble system. The PODs are found to be more than twice that of the individual ensemble members at most lead times, which is about 59% and 38% at the 5-day lead time in UKMO-EPS and ECMWF-EPS, respectively; while the success ratios are smaller compared with that of the ensemble members. In addition, predictability differs in different basins, and genesis events in the North Atlantic basin are the most difficult to forecast in EPS, and its POD at the 5-day lead time is only 46% and 23% in UKMO-EPS and ECMWF-EPS, respectively.
    publisherAmerican Meteorological Society
    titleThe Forecast Skill of Tropical Cyclone Genesis in Two Global Ensembles
    typeJournal Paper
    journal volume38
    journal issue1
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-22-0145.1
    journal fristpage83
    journal lastpage97
    page83–97
    treeWeather and Forecasting:;2022:;volume( 038 ):;issue: 001
    contenttypeFulltext
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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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