Precipitation Variability, Representativeness of Surface Disdrometers and Radar Calibration

Improvements are needed in the methodology for measuring precipitation in order to make progress in properly representing the hydrologic cycle in numerical models. In order to achieve this goal, it is necessary to have reliable local measurements of precipitation to validate satellite retrievals and model predictions. The disdrometer has become an important tool for precipitation research since the DSD is a central parameter that can be used to determine other precipitation parameters such as reflectivity, rain rate and liquid water content. Accordingly, the disdrometer can provide a time history of reflectivity and other precipitation parameters locally at a fixed location on the surface. The disdrometer measurements can be used for calibration of radar profilers or scanning radars. However, since precipitation is highly variable in space and time the extent to which the disdrometer measurements are representative over a larger domain is unknown. This paper summarizes recent progress aimed at determining typical representativeness error of disdrometer measurements utilizing radar precipitation profiler observations that allow us to compare with disdrometer measurements in the vertical. We utilize observations taken during the TRMM ground validation field campaigns and more recently at Wallops Island using low-powered precipitation profilers to provide a quantitative measure of the representativeness of the disdrometer.