Application of Satellite Imagery for Surface Rain Rate Estimation, Technical Summary

摘要

Rainfall events can directly affect the surface transportation infrastructure and disrupt routine operations. Extended periods of light to moderate rain can saturate the topsoil, leading to excessive runoff , inundation, and roadway damage. More intense events can cause widespread flooding that may ultimately increase flows in waterways, thereby impacting bridges and overpasses immediately from floating debris and, in the longer term, through potential scouring around supporting structures. Of course, highway safety during rain is a primary concern. Traditionally, characteristics of rainfall events have been derived from rain gage data and radar observations. However, the number of official rain gage stations is relatively small, and their wide spatial distribution may not accurately represent a particular location of interest. Radar rain estimates are well accepted, but anomalous atmospheric propagation and the earths curvature can introduce errors over distance. More recently, infrared (IR) cloud top temperatures (CTTs) as observed by satellite are being employed to estimate a surface rain rate. A primary advantage of this method is the excellent spatial and temporal resolution of the imagery that is typically available in near real time. The Geostationary Operational Environmental Satellite (GOES) system provides IR imagery at 15- to 30-minute intervals with a resolution of 4 x 4 kilometers, or about 2.5 x 2.5 miles. Since the late 1970s, many algorithms and calibration techniques for relating CTT to surface rain rate have been developed and tested. The most current methods in use by the U.S. federal government rely not only on GOES data, but also numerical model data, microwave rain rates, and other corrective factors to produce rain estimates. An earlier method, the Automated Satellite Rainfall Rate Estimation technique, or Auto-Estimator, developed by Vincente et al. provided a formulation to directly estimate rain rate from IR CTT alone as one part of its computational process. The purpose of this brief study was to determine the applicability of this basic Vincente formulation for operational use in Louisiana. This was be accomplished by comparing the rain rates computed from GOES IR CTTs to actual rain gage measurements under a variety of synoptic weather situations.