Comparison of WSR-88D derived rainfall estimates with gauge data in Lexington county, South Carolina

The deployment of the National Weather Service Weather Surveillance Radar-1988 Doppler (WSR-88D) has provided an improved tool for monitoring precipitation distribution. Because the WSR-88D can estimate rainfall at high spatial and temporal resolution, it has great potential for meteorological and hydrological modeling. Unfortunately, a number of factors introduce discrepancies between radar rainfall estimates and actual rainfall at the Earth's surface. In this paper, I compare rainfall estimates from the Columbia Airport National Weather Service WSR-88D with precipitation recorded by 62 standard rain gauges and 10 tipping gauges in Lexington County, South Carolina. The study included seven precipitation episodes that covered a variety of synoptic types such as convective storms, tropical systems, and stratiform events. Discrepancies between the gauge and radar were analyzed by storm event to determine what potential synoptic or inherent factors caused the differences.

The results of the Geographic Information System (GIS) and the SAS regression and ANOVA models were generally consistent in their analysis proving the radar underestimates precipitation independent of the storm type. When all the storms were combined, agreement between gauges and radar was weak, with the total for the gauges being 20.9 inches on average and that for the radar 8.1 inches on average, a difference of 61%. However, when the storms were considered individually, two storms had a radar-gauge difference of less than 5%. The degree of underestimation varied with storm intensity, duration and type. The radar’s performance was the weakest during the three stratiform storms. The underestimation of 75% of the gauge data was probably attributed to the light, widespread rain and small dropsize. Overall the convective events had the average highest percent accuracy with the radar estimating 96% of the gauge data. However, the radar estimation accuracy was not consistent. The factors during these convective systems which probably had the greatest effect on radar measurements were enhancement of reflectivity by hail and larger than average raindrops and diminution of estimation by small drops and downdrafts. The radars estimated precipitation during the passage of Tropical System Earl, September 3-4, 1998, ranged from 20% to 86% as compared to the gauges. The abundance of moisture associated with tropical maritime air makes it difficult for the radar to determine a representative reflectivity.

The results from this study indicate that the radar can not yet provide the spatial distribution of surface rainfall that is needed for many operational and research applications. Because of the great variability in the intensity and distribution of precipitation, more radar-gauge comparisons should be conducted covering a larger number of storms. Future research has been stimulated by these results which include analysis of the radar level II base reflectivity data to determine whether the error sources were caused by inaccurate reflectivity values, an incorrect Z-R conversion, or a combination of the two. Results from both studies will ultimately be coupled with efforts to eliminate the systematic biases of the radar and improve quantitative precipitation forecasts.