Presenting Author: Dr. Linwood Jones
Due to the high surface winds and associated heavy precipitation, extreme wind events, such as tropical cyclones, present a daunting challenge to space-borne Ku-band scatterometer measurements of ocean vector winds. High rain rates attenuate the ocean surface backscatter due to surface winds and rain volume scattering increases the sigma-0 measured by the scatterometer. Thus, rain can either increase or decrease the observed backscattered power compared to ocean measurements without rain; and for both of these conditions, wind retrievals that ignore rain are significantly degraded. This paper describes recent developments of an improved ocean wind vector retrieval algorithm that uses both active and passive measurements from QuikSCAT to infer simultaneous wind vector and rain rate measurements. Ocean brightness temperature, determined passively, is used to model both the transmission and scattering effects of rain, which are used to correct the measured sigma-0 at 12.5 km resolution. Wind retrievals are performed using an improved geophysical model function (GMF) tuned with high speed surface wind measurements derived from NOAA hurricane hunter aircraft underflights. This algorithm results in significant improvements in wind vector measurements in hurricanes and other extreme wind events and better rain-flagging of severely rain contaminated areas than does NASAís standard wind vector product (L2B). The results from this algorithm, known as Q-Winds, are compared to an independent surface wind analysis derived from near-simultaneous NOAA aircraft flights through several hurricanes with multiple satellite passes. Airborne sensors, that include the Stepped Frequency Microwave Radiometer, GPS dropwindsondes and flight-level inertial navigation winds, are used by the NOAA Hurricane Research Divisionís H*Wind Analysis System to derive a reliable surface wind field. Comparisons are presented for H*Wind, Q-Winds and the SeaWinds Projects new L2B12.5 ocean vector winds products.
2019 International OVWST Meeting
May 29-31 in Portland, Maine, USA