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Advances in understanding difficult cases of tropical cyclone track forecasts

  • Linus Magnusson
  • , James D. Doyle
  • , William A. Komaromi
  • , Ryan D. Torn
  • , Chi Kit Tang
  • , Johnny C.L. Chan
  • , Munehiko Yamaguchi
  • , Fuqing Zhang
  • European Centre for Medium-Range Weather Forecasts
  • Naval Research Laboratory
  • City University of Hong Kong
  • Japan Meteorological Agency
  • Pennsylvania State University

Research output: Contribution to journalReview articlepeer-review

24 Scopus citations

Abstract

Although tropical cyclone track forecast errors have substantially decreased in recent decades, there are still cases each season with large uncertainties in the forecasts and/or very large track errors. As such cases are challenging for forecasters, it is important to understand the mechanisms behind the low predictability. For this purpose the research community has developed a number of tools. These tools include ensemble and adjoint sensitivity models, ensemble perturbation experiments and nudging experiments. In this report we discuss definitions of difficult cases for tropical cyclone track forecasts, diagnostic techniques to understand sources of errors, lessons learnt in recent years and recommendations for future work.

Original languageEnglish
Pages (from-to)109-122
Number of pages14
JournalTropical Cyclone Research and Review
Volume8
Issue number3
DOIs
StatePublished - Sep 2019

Keywords

  • adjoint modelling
  • ensemble sensitivity
  • forecast busts
  • predictability
  • tropical cyclones

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