Real-Time Calibration of Radar Precipitation Estimates

Abstract

One of the main concerns with precipitation measurements is that gage networks are almost always too sparse to provide an adequate spatial coverage of storm-scale precipitation. Gage measurements are representative only at the measurement site and are biased underestimates of the actual precipitation, mainly as a result of the effect of wind on the gage. Consequently, storm-scale, real-time assessments using only gage-measured precipitation are frequently inadequate. With the advent of the WSR-88D (formerly NEXRAD) weather radars, precipitation estimates at higher spatial resolutions (4 km by 4 km) are now available in real time. These radars use the reflectivity of S-band (10 cm) microwaves to provide an estimate of precipitation. Unfortunately, reflectivity is a function of the surface area of the raindrops and not their volume. As a result of this and other sources of error, radar precipitation estimates using fixed reflectivity-to-rainfall relationships are subject to substantial biases. To provide better high-resolution precipitation estimates, a gage-radar precipitation compositing procedure has been developed to enhance real-time precipitation assessments. Radar estimates provide the spatial ‘footprint’ of the storm while gage data are used to enhance accuracy. This procedure calibrates each radar separately (since biases usually vary by radar), provides a composite mosaic of multiple radars for regions that lie under more than one radar umbrella, and determines an estimate of the uncertainty of the calibration.