In recent years, demand has increased for high-resolution accurate forecasts of convective weather. NCAR’s WRF-ARW model has played a critical role in real-time demonstrations of explicit convective forecasts showing skill in convective forecast guidance out to 36 hours. However, NWP models require further refinement to enable accurate forecasts of the timing and location of high-impact weather in the first 0-12 hours. Accurate specification of the initial state down to the convective scale through assimilation of high-resolution observations such as Doppler radar and densely spaced surface observations is one of the keys to markedly improve NWP forecasts of high-impact weather events.

Four WRF-ARW based data assimilation techniques have been developed in the past few years at NCAR: observation nudging, 3-D variational assimilation (3DVAR), 4-D variational assimilation (4DVAR), and ensemble Kalman filter (EnKF). The nudging and 3DVAR are targeted for real-time implementation and the other two are used currently for case studies. Recently, a retrospective study was conducted using one-week IHOP data to evaluate the capabilities and limitations of these data assimilation systems and define future directions for further development. The focus of this presentation will be on WRF 3DVAR and 4DVAR techniques. 3DVAR radial velocity data assimilation for the one-week IHOP period was evaluated through a number of sensitivity experiments varying cycling configurations. The statistical results of these experiments will be presented. The preliminary WRF 4DVAR system was evaluated through an IHOP case study assimilating radar radial velocity data. The results were compared with the 3DVAR system especially in terms of their sensitivities with respect to background error statistics. Preliminary diagnostic analysis of key convective processes, such as low-level convergence, wind shear, cold pool, and CAPE and CIN, were conducted to gain some understanding on the causes of forecast success and failure. Results from these studies indicate that radar radial velocity data assimilation has a positive impact on the forecasting of convective weather, but the impact is sensitive to detailed system configurations. Further development of WRF variational system to assimilate radar reflectivity is needed and underway.