Real-time forecasts of five landfalling Atlantic hurricanes during 2005 using the Advanced Research Weather Research and Forecasting (WRF) (ARW) Model at grid spacings of 12 and 4 km revealed performance generally competitive with, and occasionally superior to, other operational forecasts for storm position and intensity. Recurring errors include 1) excessive intensification prior to landfall, 2) insufficient momentum exchange with the surface, and 3) inability to capture rapid intensification when observed. To address these errors several augmentations of the basic community model have been designed and tested as part of what is termed the Advanced Hurricane WRF (AHW) model. Based on sensitivity simulations of Katrina, the inner-core structure, particularly the size of the eye, was found to be sensitive to model resolution and surface momentum exchange. The forecast of rapid intensification and the structure of convective bands in Katrina were not significantly improved until the grid spacing approached 1 km. Coupling the atmospheric model to a columnar, mixed layer ocean model eliminated much of the erroneous intensification of Katrina prior to landfall noted in the real-time forecast.

A novel methodology is introduced for processing and presenting polarimetric data collected by weather surveillance radars. It involves azimuthal averaging of radar reflectivity Z, differential reflectivity ZDR, cross-correlation coefficient ρhv, and differential phase ΦDP at high antenna elevation, and presenting resulting quasi-vertical profiles (QVPs) in a height-versus-time format. Multiple examples of QVPs retrieved from the data collected by S-, C-, and X-band dual-polarization radars at elevations ranging from 6.4° to 28° illustrate advantages of the QVP technique. The benefits include an ability to examine the temporal evolution of microphysical processes governing precipitation production and to compare polarimetric data obtained from the scanning surveillance weather radars with observations made by vertically looking remote sensors, such as wind profilers, lidars, radiometers, cloud radars, and radars operating on spaceborne and airborne platforms. Continuous monitoring of the melting layer and the layer of dendritic growth with high vertical resolution, and the possible opportunity to discriminate between the processes of snow aggregation and riming, constitute other potential benefits of the suggested methodology.

Valley cold pools (VCPs), which are trapped, cold layers of air at the bottoms of basins or valleys, pose a significant problem for forecasters because they can lead to several forms of difficult-to-forecast and hazardous weather such as fog, freezing rain, or poor air quality. Numerical models have historically failed to routinely provide accurate guidance on the formation and demise of VCPs, making the forecast problem more challenging. In some case studies of persistent wintertime VCPs, there is a connection between the movement of upper-level waves and the timing of VCP formation and decay. Herein, a 3-yr climatology of persistent wintertime VCPs for five valleys and basins in the western United States is performed to see how often VCP formation and decay coincides with synoptic-scale (;200-2000 km) wave motions. Valley cold pools are found to form most frequently as an upper-level ridge approaches the western United States and in response to strong midlevel warming. The VCPs usually last as long as the ridge is over the area and usually only end when a trough, and its associated midlevel cooling, move over the western United States. In fact, VCP strength appears to be almost entirely dictated by midlevel temperature changes, which suggests large-scale forcing is dominant for this type of VCP most of the time.