The Advanced Regional Prediction System (ARPS), storm-scale numerical weather prediction and data assimilation

In this paper, we first describe the current status of the Advanced Regional Prediction System of the Center for Analysis and Prediction of Storms at the University of Oklahoma. A brief outline of future plans is also given. Two rather successful cases of explicit prediction of tornadic thunderstorms are then presented. In the first case, a series of supercell storms that produced a historical number of tornadoes was successfully predicted more than 8 hours in advance, to within tens of kilometers in space with initiation timing errors of less than 2 hours. The general behavior and evolution of the predicted thunderstorms agree very well with radar observations. In the second case, reflectivity and radial velocity observations from Doppler radars were assimilated into the model at 15-minute intervals. The ensuing forecast, covering a period of several hours, accurately reproduced the intensification and evolution of a tornadic supercell that in reality spawned two tornadoes over a major metropolitan area. These results make us optimistic that a model system such as the ARPS will be able to deterministically predict future severe convective events with significant lead time. The paper also includes a brief description of a new 3DVAR system developed in the ARPS framework. The goal is to combine several steps of Doppler radar retrieval with the analysis of other data types into a single 3-D variational framework and later to incorporate the ARPS adjoint to establish a true 4DVAR data assimilation system that is suitable for directly assimilating a wide variety of observations for flows ranging from synoptic down to the small nonhydrostatic scales.