The Assimilation of Radar Data for Weather Prediction

Abstract

Since the early years of radar meteorology, scientists have given a good deal of attention to the development of techniques for deducing the unobserved meteorological fields from Doppler radar observations. For example, Lhermitte and Atlas (1961) and Atlas (1964) described the velocity-azimuth display (VAD) method for determining a horizontally averaged wind profile from single-Doppler radial velocity observations. Lhermitte (1970) developed a method to derive the detailed horizontal wind field from dual-Doppler radial velocity observations. These early research activities were largely driven by the desire to understand the dynamical processes of convective systems in the atmosphere. In the late 1980s, however, scientists began to recognize that radar observations would also play an important role in future mesoscale and convective-scale data assimilation systems for short-term weather forecasting. This scientific vision was gained, in large part, as a result of the planned implementation of the Weather Surveillance Radar-1988 Doppler (WSR-88D) network in the United States and the rapid increase in computer power. With these increased resources, it appeared that running numerical weather prediction (NWP) models with resolutions that are able to resolve mesoscale and cloudscale features was within reach. On account of the considerable societal and economic impact of the operational storm-scale NWP and the scientific and technological advancement, Lilly (1990) argued that it was time for convective-storm research scientists to apply their knowledge and to show whether storm-scale NWP was a realistic goal. Since the WSR-88D network is the major observing system capable of sampling the four-dimensional structure of storm-scale flows, a key scientific and technical challenge is whether these observations can be used to initialize high-resolution storm prediction models.