Diagnosing forecast errors in tropical cyclone motion

Thomas J. Galarneau, Christopher A. Davis

Research output: Contribution to journalArticlepeer-review

109 Scopus citations

Abstract

This paper reports on the development of a diagnostic approach that can be used to examine the sources of numerical model forecast error that contribute to degraded tropical cyclone (TC) motion forecasts. Tropical cyclone motion forecasts depend upon skillful prediction of the environment wind field, and by extension, the synoptic-scale weather systems nearby the TC. While previous research suggests that the deep-layer mean (DLM) steering flow typically approximates the actual TC motion, it is shown that the motion of even mature TCs can depart from the DLM steering flow. An optimal environmental steering flow is defined, which varies the vertical extent of the steering layer and the radius over which TC vorticity and divergence are removed. Errors in predicted TC motion are quantified using a diagnostic equation that accounts for not only differences in the synoptic-scale flow, but also differences in the depth and radius used to define the steering flow. Differences in the latter two parameters are interpreted in terms of errors in predicted TC structure or errors in proximate mesoscale flow features. Results from an analysis of 24-h forecasts from theAdvancedHurricane Weather Research and Forecasting Model during the 2008-10 NorthAtlantic TC seasons show that forecast motion errors are dominated by errors in the environment wind field. Contributions from other terms are occasionally large and are interpreted from a vorticity perspective. The utility of this new diagnostic equation is that it can be used to assess TC motion forecasts from any numerical modeling system.

Original languageEnglish
Pages (from-to)405-430
Number of pages26
JournalMonthly Weather Review
Volume141
Issue number2
DOIs
StatePublished - Feb 2013

Keywords

  • Forecast verification/skill
  • Hurricanes/typhoons
  • Numerical weather prediction/forecasting
  • Storm environments
  • Synoptic-scale processes
  • Tropical cyclones

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