Numerical test of a simple approach for using TOMS total ozone data in hurricane environment

Abstract

AbstractUsing a regime‐dependent linear regression model that maps TOMS observed total column ozone (O3) into model mean vertically‐integrated potential vorticity (MPV): O3 = α × MPV + β, where the regression constants α and β are evaluated separately for data in regions strongly and weakly influenced by deep convection/southerly advection, respectively, TOMS ozone data can readily be incorporated into a hurricane forecast model. Case‐studies of several hurricanes are conducted applying such a simple regime‐dependent linear regression model to TOMS ozone data assimilation. Improvements in the track prediction are shown. A detailed analysis of how TOMS total ozone affects the track prediction is conducted for Hurricane Erin (2001). A significant improvement in the track prediction for Hurricane Erin (2001) using TOMS ozone occurred at about 20 hours into the model forecast, when the control forecast experiences a sudden increase of track error. It is found that such an improvement in the track prediction of Hurricane Erin is mainly due to differences in the steering flows of the two forecast experiments, resulting from the presence of an upstream middle‐latitude ozone trough and a downstream low‐latitude ozone trough. An examination of the time evolution of these two troughs in both forecast experiments indicates that both troughs became stronger and moved closer to Hurricane Erin with time in the forecast experiment with the assimilation of TOMS ozone data than did those in the control forecast. Copyright © 2008 Royal Meteorological Society