Improvement of RapidScat and HSCAT wind quality control

Abstract

This paper reviews several wind quality-sensitive parameters derived from Ku-band scatterometer data. The objective is to assess their sensitivity to wind data quality in order to optimize the quality control (QC) for Ku-band scatterometers. The current scatterometer wind data processor uses the inversion residual or maximum likelihood estimator (MLE) value in QC. A large inconsistency between the measured backscatter set andthe geophysical model function (GMF) results in a largeMLE value, which indicates geophysical conditions other than those modeled by the wind GMF, such as rain,sea ice, highlocal wind variability,orconfused sea state.Therefore, the MLE value provides a good indication of the quality of the retrieved winds. Besides, an image processing technique, known as Singularity Analysis (SA), has been recently proposed as a complementaryQC tool to the current Advanced Scatterometer (ASCAT) MLE-based QC. In general, MLE is a proxy for sub- wind vector cell (WVC) wind variability, where large positive MLEs are usually found near (gust) fronts, squall lines, and convective systems. The SA-derived singularity exponent (SE) is based on spatial derivatives and therefore mostly represents the inter-WVC variability. By using a spatial filter approach similar to the SE derivation, one can also study the inter-WVC variability with the spatially-averaged MLE, which may further improve the wind quality control.

A comprehensive wind quality assessment is carried out forthe ongoing Ku-band rotating pencil-beam scatterometers, namely RapidSCAT installed on the International Space Station and HSCAT onboard the Chinese HY-2A satellite. Since ASCAT QC near rain (< 1%) has been investigated recently and the C-band ASCAT sensitivity to rain is limited as compared to that of Ku-band scatterometers, ASCAT winds can be used as reference for tuning the Ku-band QC. Moreover, thanks to the inclined orbit of RapidScat, a large amount of well collocated (in pace and time) ASCAT and RapidSCAT wind data can be used to fine tune the Ku-band scatterometer QC near rain.The RapidSCAT and HSCAT derived wind dataare further collocated with the European Centre for Medium-Range Weather Forecasts (ECMWF) winds, the Tropical Rainfall Measuring Mission’s Microwave Imager (TRMM TMI) rain data, in order to characterize and validate the proposed quality indicators. Moreover, buoy wind collocations are also used for validating the proposed QC algorithm. A set of MLE and SE thresholds are defined to optimize the QC effectiveness, i.e., to maximize poor-quality wind rejections (particularly contaminated by rain) while preserving fair-quality data