Spurious weather radar echo identification and removal using multisource temperature information

Abstract

A simple and pragmatic method utilising the difference between analysed near-surface and Meteosat IR temperatures (Δ T) is presented and applied with the aim of identifying and removing non-precipitation echoes in weather radar composite imagery. Despite inherent deficiencies in these multisource data, such as lower spatial and temporal resolutions relative to the radar data, Δ T is demonstrated to efficiently identify efficiently those areas void of potentially precipitating clouds, and to remove radar echoes in them. A set of 243 manually analysed composites from the summer of 2000 was used to evaluate the method. False alarm rates (FAR), percent correct (PC) and Hanssen-Kuipers skill (HKS) scores were calculated from standard contingency tables for five echo classes: weak, strong, land, sea, and all. FAR was lowered in all classes, PC was generally raised by a few percent to be over 95%, while HKS either remained unchanged or was slightly lowered through the application of Δ T. These results indicate that Δ T successfully removes a significant amount of non-precipitation, sometimes at the expense of a small amount of true precipitation. This penalty is larger over sea, which indicates that the method may need to be tuned differently for land and sea environments. This method may act as a foundation on which improvements to radar data quality control can be made with the introduction of new and improved satellite instrumentation such as that found on board the Meteosat Second Generation platform. However, this type of method should remain complementary to improved signal processing and radar data analysis techniques.