• Login
    View Item 
    •   DSpace Home
    • AMS
    • Weather and Forecasting
    • View Item
    •   DSpace Home
    • AMS
    • Weather and Forecasting
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Understanding Biases in Tropical Cyclone Intensity Forecast Error

    Thumbnail
    View/Open
    waf-d-17-0106.1.pdf (1.232Mb)
    Date
    2017
    Author
    Na, Wei
    McBride, John L.
    Zhang, Xing-Hai
    Duan, Yi-Hong
    Metadata
    Show full item record
    Abstract
    AbstractThe characteristics of 24-h official forecast errors (OFEs) of tropical cyclone (TC) intensity are analyzed over the North Atlantic, east Pacific, and western North Pacific. The OFE is demonstrated to be strongly anticorrelated with TC intensity change with correlation coefficients of ?0.77, ?0.77, and ?0.68 for the three basins, respectively. The 24-h intensity change in the official forecast closely follows a Gaussian distribution with a standard deviation only ? of that in nature, suggesting the current official forecasts estimate fewer cases of large intensity change. The intensifying systems tend to produce negative errors (underforecast), while weakening systems have consistent positive errors (overforecast). This asymmetrical bias is larger for extreme intensity change, including rapid intensification (RI) and rapid weakening (RW). To understand this behavior, the errors are analyzed in a simple objective model, the trend-persistence model (TPM). The TPM exhibits the same error-intensity change correlation. In the TPM, the error can be understood as it is exactly inversely proportional to the finite difference form of the concavity or second derivative of the intensity?time curve. The occurrence of large negative (positive) errors indicates the intensity?time curve is concave upward (downward) in nature during the TC?s rapid intensification (weakening) process. Thus, the fundamental feature of the OFE distribution is related to the shape of the intensity?time curve, governed by TC dynamics. All forecast systems have difficulty forecasting an accelerating rate of change, or a large second derivative of the intensity?time curve. TPM may also be useful as a baseline in evaluating the skill of official forecasts. According to this baseline, official forecasts are more skillful in RW than in RI.
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4261374
    Collections
    • Weather and Forecasting

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV