A Weibull approach for improving climate model projections of tropical cyclone wind-speed distributions

AMS Citation:
Tye, M. R., D. B. Stephenson, G. Holland, and R. Katz, 2014: A Weibull approach for improving climate model projections of tropical cyclone wind-speed distributions. Journal of Climate, 27, 6119-6133, doi:10.1175/JCLI-D-14-00121.1.
Date:2014-08-15
Resource Type:article
Title:A Weibull approach for improving climate model projections of tropical cyclone wind-speed distributions
Abstract: Reliable estimates of future changes in extreme weather phenomena, such as tropical cyclone maximum wind speeds, are critical for climate change impact assessments and the development of appropriate adaptation strategies. However, global and regional climate model outputs are often too coarse for direct use in these applications, with variables such as wind speed having truncated probability distributions compared to those of observations. This poses two problems: How can model-simulated variables best be adjusted to make them more realistic? And how can such adjustments be used to make more reliable predictions of future changes in their distribution? This study investigates North Atlantic tropical cyclone maximum wind speeds from observations (1950-2010) and regional climate model simulations (1995-2005 and 2045-55 at 12- and 36-km spatial resolutions). The wind speed distributions in these datasets are well represented by the Weibull distribution, albeit with different scale and shape parameters. A power-law transfer function is used to recalibrate the Weibull variables and obtain future projections of wind speeds. Two different strategies, bias correction and change factor, are tested by using 36-km model data to predict future 12-km model data (pseudo-observations). The strategies are also applied to the observations to obtain likely predictions of the future distributions of wind speeds. The strategies yield similar predictions of likely changes in the fraction of events within Saffir-Simpson categories—for example, an increase from 21% (1995–2005) to 27%–37% (2045–55) for category 3 or above events and an increase from 1.6% (1995-2005) to 2.8%-9.8% (2045-55) for category 5 events.
Peer Review:Refereed
Copyright Information:Copyright 2014 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.
OpenSky citable URL: ark:/85065/d76h4jc7
Publisher's Version: 10.1175/JCLI-D-14-00121.1
Author(s):
  • Mari Tye - NCAR/UCAR
  • David Stephenson
  • Gregory Holland - NCAR/UCAR
  • Richard Katz - NCAR/UCAR
  • Random Profile

    PROJ SCIENTIST II

    Recent & Upcoming Visitors