Weather Radar Estimates of Rainfall Adjusted to Rain Gauge Measurements Using Neural Networks

Other than rain gauges which measure the rain rate R directly on the ground, the weather radar measures the reflectivity Z aloft and the rain rate has to be determined over a Z-R relationship. Besides the fact that the rain rate has to be calculated from the reflectivity many other sources of possible errors are inherent to the radar system. Worth mentioning are especially errors caused by the vertical profile of reflectivity (VPR). In this paper an approach is described to estimate ground rainfall using radar data based on a neural network technique. The results indicate that the relationship determined by the neural network model between VRP and rain rate measured on the ground, is also representative for sites nearby.