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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

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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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
JournalTropical Cyclone Research and Review
Volume8
Issue number3
DOIs
Publication statusPublished - Sept 2019

Research Keywords

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

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

RGC Funding Information

  • RGC-funded

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