Impact of dropwindsonde data on the track forecasts of a tropical cyclone: An observing-systems simulation experiment study

Seon K. Park, Da Lin Zhang, Hyun Hee Kim

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this study, the model initial uncertainties associated with the track forecast of Hurricane Bonnie (1998) is examined through a series of observing-systems simulation experiments (OSSEs) with the Penn State University-National Center for Atmospheric Research mesoscale model (i.e., MM5). Analysis soundings with varying densities and configurations are used to mimic the inclusion of dropwindsonde data in the model initial conditions. Results show that increasing the soundings around the storm center improves the track forecasts. Enhanced observations in any quadrant of the storm would result in better track forecasts, but the forecast improvement is more pronounced when more soundings are added to a region of stronger winds. The results indicate that proper design of the dropwindsonde distribution and density is crucial to the improvement of the track forecasts of tropical cyclones.

Original languageEnglish
Pages (from-to)85-92
Number of pages8
JournalAsia-Pacific Journal of Atmospheric Sciences
Volume44
Issue number1
StatePublished - 2008

Keywords

  • Data assimilation
  • Data impact
  • Dropwindsonde
  • Tropical cyclone

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