Study on Water Level Prediction Using Observational Data from a Multi-Parameter Phased Array Weather Radar

Abstract

A dual-polarization, phased array weather radar, also known as the multi-parameter phased array weather radar (MP-PAWR), was developed by the Japanese Cross-ministerial Strategic Innovation Promotion (SIP) Program. Since this weather radar has been made into an active phased array, three-dimensional observation of weather phenomena can be realized at high speed by means of electrical scanning in the elevation direction and mechanical scanning in the azimuth direction. This is expected to shed light on hydrological processes in river basins, such as those of urban rivers, and improve prediction accuracy. In this study, river water levels in urban areas were estimated from vertically integrated liquid (VIL) Nowcast water content results, a meteorological forecasting method based on the three-dimensional observation MP-PAWR data, using a synthesized rational formula. A runoff analysis for urban basins was carried out using the rainfall forecast results based on MP-PAWR observational data. Since it is known that this formula can be used to deliver a rapid response time for runoff phenomena in the basin, it is possible to fully exploit the features of the MP-PAWR. This study shows how MP-PAWR is used in a series of hydrological processes. In this paper, we report the results of a basic study on water level predictions based on MP-PAWR observational data and also present future prospects for the use of this technology.