Performance of convection-permitting hurricane initialization and prediction during 2008-2010 with ensemble data assimilation of inner-core airborne Doppler radar observations

Fuqing Zhang, Yonghui Weng, John F. Gamache, Frank D. Marks

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122 Scopus citations

Abstract

This study examines a hurricane prediction system that uses an ensemble Kalman filter (EnKF) to assimilate high-resolution airborne radar observations for convection-permitting hurricane initialization and forecasting. This system demonstrated very promising performance, especially on hurricane intensity forecasts, through experiments over all 61 applicable NOAA P-3 airborne Doppler missions during the 2008-2010 Atlantic hurricane seasons. The mean absolute intensity forecast errors initialized with the EnKF-analysis of the airborne Doppler observations at the 24-to 120-h lead forecast times were 20-40% lower than the National Hurricane Center's official forecasts issued at similar times. This prototype system was first implemented in real-time for Hurricane Ike (2008). It represents the first time that airborne Doppler radar observations were successfully assimilated in real-time into a hurricane prediction model. It also represents the first time that the convection-permitting ensemble analyses and forecasts for hurricanes were performed in real-time. Also unprecedented was the on-demand usage of more than 23,000 computer cluster processors simultaneously in real-time.

Original languageEnglish (US)
Article numberL15810
JournalGeophysical Research Letters
Volume38
Issue number15
DOIs
StatePublished - Aug 1 2011

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Earth and Planetary Sciences(all)

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