Impact of satellite surface-wind data on weather prediction

Abstract

One of the important applications of satellite surface wind observations is to increase the accuracy of weather analyses and forecasts. The first satellite to measure surface wind over the oceans was Seasat in 1978. On board was a scatterometer, which measured radar backscatter from centimeter-scale capillary waves, from which surface wind speed and direction could be deduced. In more recent years, passive microwave remote sensing of the ocean surface has provided extensive observations of surface wind speed, and advanced scatterometers have been providing surface wind velocity data over the oceans. The initial impact of satellite surface wind data on weather analysis and forecasting was very small, but extensive research has been conducted since the early days of Seasat to improve the data accuracy and the utilization of these data in atmospheric models. Current satellite surface wind data are used to improve the detection of intense storms over the ocean, as well as to improve the overall representation of the wind field in numerical weather prediction models. As a result, these data are contributing to improved warnings for ships at sea and to improved global weather forecasts. Recent experiments conducted with data from the SeaWinds scatterometers aboard both Quikscat and ADEOS 2 indicate that increased coverage of scatterometer data can lead to even larger impacts than are routinely obtained now.