4.7 Article

Improved Rain Screening for Ku-Band Wind Scatterometry

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2019.2951726

关键词

Rain; Radar measurements; Maximum likelihood estimation; Spaceborne radar; Wind; Sea surface; False alarms; Ku-band wind scatterometry; probability of detection (POD); quality control (QC); rain; spatial characteristics

资金

  1. National Key Research and Development Program of China [2016YFC1401001]
  2. European Organization for the Exploitation of Metrological Satellites Ocean and Sea Ice Satellite Application Facility (EUMETSAT OSI SAF)

向作者/读者索取更多资源

Spaceborne scatterometers for ocean surface winds usually operate in Ku- or C-band. Rather strict quality control (QC) procedures are included in the Ku-band wind retrieval chain for labeling rain-contaminated observations. Existing QC factors represent the deviation of measurements from the wind geophysical model function (GMF) modeled measurement surface. Other QC indicators flag outliers by examining neighborhood consistency. In this article, spatial heterogeneity of rain is further exploited by a new indicator for Ku-band QC, namely, , the speed component of the observation cost function, , of the selected solution in the 2-D variational ambiguity removal (2-DVAR) step of the wind retrieval. First, the characteristics of 2-DVAR speeds in rainy condition are analyzed, and then, the ability of in quality labeling is proposed and verified by applying it to the Ku-band scatterometer on-board ScatSat. Its effectiveness for rain screening is confirmed with collocated references from the C-band scatterometer on-board the MetOp-B satellite, which are much less affected by rain. With reference to collocated rain rates from the Global Precipitation Mission (GPM), the more direct relations to rain and wind speed errors of the newly proposed QC indicator than existing QC indicators, including are illustrated by the analysis of its correlation with rain rates. In a novel approach, is applied to accept (unflag) more than 75 & x0025; of the data rejected by the widely applied maximum likelihood estimation (MLE) thresholds (i.e., correct false alarms) in the tropics. The promising results open a new opportunity for improving QC of rain in the Ku-band wind scatterometry benefitting scatterometer applications.

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