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Volume 19 Issue 6

Nov.  2002

Article Contents
Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2002 >  19(6): 1029-1044

The Impact of Dropsonde Data on Forecasts of Hurricane Debby by the Meteorological Office Unified Model

  • 1.

    United Kingdom Meteorological Office, Bracknell, U.K.,United Kingdom Meteorological Office, Bracknell, U.K.


doi: 10.1007/s00376-002-0062-4

  • The numerical product of hurricane tracks vastly depends on initial observation fields. However, the forecast error is very large because of lack of observational data, especially when hurricanes are over the sea.This paper shows that extra non-real-time data (dropsonde data) can improve hurricane track forecasts compared with real-time observational data, and that the wind and relative humidity components of the dropsonde data have the greatest impact on the track forecasts.
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    [8] Kanghui ZHOU, Jisong SUN, Yongguang ZHENG, Yutao ZHANG, 2022: Quantitative Precipitation Forecast Experiment Based on Basic NWP Variables Using Deep Learning, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 1472-1486.  doi: 10.1007/s00376-021-1207-7
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    [10] Daosheng XU, Jeremy Cheuk-Hin LEUNG, Banglin ZHANG, 2023: A Time Neighborhood Method for the Verification of Landfalling Typhoon Track Forecast, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 273-284.  doi: 10.1007/s00376-022-1398-6
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    [12] XU Yamei, WU Rongsheng, 2003: The Conservation of Helicity in Hurricane Andrew (1992) and the Formation of the Spiral Rainband, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 940-950.  doi: 10.1007/BF02915517
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    • Manuscript History

    Manuscript received: 10 November 2002
    Manuscript revised: 10 November 2002
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    The Impact of Dropsonde Data on Forecasts of Hurricane Debby by the Meteorological Office Unified Model

    • 1. United Kingdom Meteorological Office, Bracknell, U.K.,United Kingdom Meteorological Office, Bracknell, U.K.
    • Manuscript received: 2002-11-10
    • Manuscript revised: 2002-11-10

    Abstract: The numerical product of hurricane tracks vastly depends on initial observation fields. However, the forecast error is very large because of lack of observational data, especially when hurricanes are over the sea.This paper shows that extra non-real-time data (dropsonde data) can improve hurricane track forecasts compared with real-time observational data, and that the wind and relative humidity components of the dropsonde data have the greatest impact on the track forecasts.

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