An improved wind quality control for the China-France Oceanography Satellite (CFOSAT) scatterometer

Quality control (QC) is an essential procedure in scatterometer wind retrieval, which is used to distinguish good-quality data from poor-quality wind vector cells (WVCs) for the sake of wind applications. The current wind processor of the China-France Oceanography Satellite (CFOSAT) scatterometer (CSCAT) adopts a maximum likelihood estimator (MLE)-based QC method to filter WVCs affected by geophysical noise, such as rainfall and wind variability. As the first Ku-band rotating fan-beam scatterometer, CSCAT can acquire up to 16 observations over a single WVC, giving abundant information with diverse incidence/azimuth angles, as such its MLE statistical characteristics may be different from the previous scatterometers. In this study, several QC indicators, including MLE, its spatially averaged value (MLE_m), and the singularity exponents (SE), are analyzed using the collocated Global Precipitation Mission rainfall data as well as buoy data, to compare their sensitivity to rainfall and wind quality. The results show that wind error characteristics of CSCAT under different QC methods are similar to those of other Ku-band scatterometers, i.e., SE is more suitable than other parameters for the wind QC at outer-swath and nadir regions, while MLE_m is the best QC indicator for the sweet region WVCs. Specifically, SE is much more favorable than others at high wind speeds. By combining different indicators, an improved QC method is developed for CSCAT. The validation with the collocated buoy data shows that it accepts more WVCs, and in turn, improves the quality control of CSCAT wind data.