Abstract:

Surface wind speeds retrieved from airborne stepped frequency microwave radiometer (SFMR) brightness temperature measurements are important for estimating hurricane intensity. The SFMR performance is highly reliable at hurricane force wind speeds, but accuracy is found to degrade at weaker wind speeds, particularly in heavy precipitation. Specifically, a significant over-estimation of surface wind speeds is found in these conditions, suggesting inaccurate accounting for the impact of rain on the measured microwave brightness temperature. In this study, the wind speed bias is quantified over a broad range of operationally-computed wind speeds and rain rates, based on a large sample of co-located SFMR wind retrievals and Global Positioning System dropwindsonde surface-adjusted wind speeds. The retrieval bias is addressed by developing a new SFMR C-band microwave absorption—rain rate (κ-R) relationship from National Oceanic and Atmospheric Administration WP-3D aircraft tail Doppler radar reflectivity and in situ Droplet Measurement Technologies Precipitation Imaging Probe measurements to more accurately model precipitation impacts. Absorption is found to be a factor of two weaker than is estimated by the currently-operational algorithm. With this new κ-R relationship, surface wind retrieval bias is significantly reduced in the presence of rain at wind speeds weaker than hurricane force. At wind speeds greater than hurricane force where little bias exists, no significant change is found. Furthermore, maximum rain rates computed using the revised algorithm are around 50% greater than operational measurements, which is more consistent with maximum reflectivity-estimated rain rates in hurricanes.