Uncertainties in wind inversion from scatterometer observations are contributed by system and geophysical noise. In practice, both can be quantified by the indicators applied in the quality control (QC) procedures during wind processing. In this research, the underlying principles of three reported indicators, MLE, SE and J oss , are discussed for CSCAT. In the observation scenes of this Ku-band scatterometer, one of the major reasons for geophysical noise are rain clouds, which are analyzed specifically with respect to those indicators. Finally, examples for super typhoon Lekima, followed by Krosa in 2019, are discussed. We confirm that the MLE and J oss indicators are relatively independent from each other, and show different features in rain screening. The combined application of them would result in a better result of rain labelling. Another conclusion derived from this research is that SE and J oss are similar indicators of spatial heterogeneity in scatterometer wind fields, but that the wind speed depression measured by Joss is a more unique indicator of rain than SE. This research contributes to improving the quality of wind retrieval from scatterometers.
Xingou Xu, Ad Stoffelen, Marcos Portabella, Wenming Lin, Xiaolong Dong
. A Comparison of Quality Indicators for Ku-Band Wind Scatterometry & for Typhoons Lekima and Krosa
Journal: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Year: 2021, doi: https://doi.org/10.1109/IGARSS47720.2021.9553678