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For the first time ever, convection-resolving forecasts at 1 km grid spacing were produced in realtime in spring 2009 by the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The forecasts assimilated both radial velocity and reflectivity data from all operational WSR-88D radars within a domain covering most of the continental United States. In preparation for the realtime forecasts, 1 km forecast tests were carried out using a case from spring 2008 and the forecasts with and without assimilating radar data are compared with corresponding 4 km forecasts produced in realtime. Significant positive impact of radar data assimilation is found to last at least 24 hours. The 1 km grid produced a more accurate forecast of organized convection, especially in structure and intensity details. It successfully predicted an isolated severe-weather-producing storm nearly 24 hours into the forecast, which all ten members of the 4 km real time ensemble forecasts failed to predict. This case, together with all available forecasts from 2009 CAPS realtime forecasts, provides evidence of the value of both convection-resolving 1 km grid and radar data assimilation for severe weather prediction for up to 24 hours. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]