Satellite rainfall estimates for global flood monitoring and prediction

摘要

Flooding continues to exact a significant economic and humanitarian toll worldwide. Rainfall estimates from satellite data represent an important source of information for monitoring and predicting these events, particularly in regions where radar data are unavailable and the rain gauge network is unsuitable for smaller-scale applications. This paper will present several real-time satellite-based rainfall estimation and forecasting techniques that are in use at NOAA/NESDIS that take advantage of the global coverage offered by both the geostationary and polar-orbiting satellite constellations. One is the Hydro-Estimator rainfall algorithm, which produces 4- to 5-km resolution estimates of rainfall at sub-hourly time scales from geostationary infrared data. Another is the Tropical Rainfall Potential (TRaP) algorithm, which produces 24-hour forecasts of rainfall from landfalling tropical cyclones based on extrapolation of current microwave-estimated rain rates along the predicted storm track. Examples of these and other techniques will be presented, along with future advances that are anticipated as new instruments become available on upcoming satellite missions.