Abstract

Distinguishing weather radar ground clutter from weather echoes is an important part of radar data quality control. For example, radar echoes due to anomalous propagation (AP) can quickly appear on radar data displays and be mistaken for precipitation echoes. If filters are applied to all radar d... Show moreDistinguishing weather radar ground clutter from weather echoes is an important part of radar data quality control. For example, radar echoes due to anomalous propagation (AP) can quickly appear on radar data displays and be mistaken for precipitation echoes. If filters are applied to all radar data, ground clutter can be effectivel eliminated, however,zero velocity precipitation echoes will also be attenuated. Recently an automated ground clutter mitigation algorithm (CMD, Clutter Mitigation Decision) was developed and deployed on the network of NEXRADs. The algorithm identifies both NP (normal propagation) and AP clutter in real time so that clutter filters can be applied only to those data that are clutter contaminated. Important to this algorithm is the understanding and modeling of ground clutter. Even though CMD correctly distinguishes between weather and ground clutter echoes the vast majority of the time, there are anomalous misidentifications that do occur. This paper examines some of these anomalous data and shows how improvements to CMD can further enhance its performance. Data from NEXRADs as well as S-Pol, NCAR's S-band polarimetric radar, are used to illustrate the developed theory. Show less