*It is very important to accurately characterize the three-dimensional distribution of water vapor in the atmosphere for the understanding and prediction of mesoscale and storm-scale weather, especially with regard to quantitative precipitation forecasting (Emanuel et al. 1995). Skills in these predictions have been improved rather slowly owing to the high spatial and temporal variability of wa...

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 ...

Abstract. This paper presents a three-dimensional variational (3DVAR) data assimilation (DA) system for aerosol optical properties, including thickness (AOT) retrievals and lidar-based profiles, developed the Model Simulating Aerosol Interactions Chemistry (MOSAIC) within Weather Research Forecasting model coupled to (WRF-Chem) model. For computational efficiency, 32 variables in MOSAIC_4bin sc...

Accurate specification of hurricane inner-core structure is critical to predicting the evolution a hurricane. However, observations over inner cores are generally lacking. Previous studies have emphasized Tail Doppler radar (TDR) data assimilation improve representation. Recently, wind lidar (DWL) has been used as an observing system sample and environmental conditions. The NOAA P3 Hurricane Hu...

A dual-resolution, hybrid, three-dimensional ensemble-variational (3DEnVAR) data assimilation method combining static and ensemble background error covariances is used to assimilate radar data, pseudo-water vapor observations improve short-term severe weather forecasts with the Weather Research Forecast (WRF) model. The higher-resolution deterministic forecast lower-resolution members have 3 9 ...