An advanced research version of the Weather Research and Forecasting (ARW) Model is used to simulate the early rapid intensification of Hurricane Emily (2005) using grids nested to high resolution (3 km). A series of numerical simulations is conducted to examine the sensitivity of the simulation to available cloud microphysical (CM) and planetary boundary layer (PBL) parameterization schemes. Results indicate that the numerical simulations of the early rapid intensification of Hurricane Emily are very sensitive to the choice of CM and PBL schemes in the ARW model. Specifically, with different CM schemes, the simulated minimum central sea level pressure (MSLP) varies by up to 29 hPa, and the use of various PBL schemes has resulted in differences in the simulated MSLP of up to 19 hPa during the 30-h forecast period. Physical processes associated with the above sensitivities are investigated. It is found that the magnitude of the environmental vertical wind shear is not well correlated with simulated hurricane intensities. In contrast, the eyewall convective heating distributions and the latent heat flux and high equivalent potential temperature ( e ) feeding from the ocean surface are directly associated with the simulated intensities. Consistent with recognized facts, higher latent heat release in stronger eyewall convection, stronger surface energy, and high e air feeding from the ocean surface into the hurricane eyewall are evident in the more enhanced convection and intense storms. The sensitivity studies in this paper also indicate that the contributions from the CM and PBL processes can only partially explain the slow intensification in the ARW simulations. Simulation at 1-km grid resolution shows a slight improvement in Emily's intensity forecast, implying that the higher resolution is somewhat helpful, but still not enough to cause the model to reproduce the real intensity of the hurricane.

Accurate forecasting of a hurricane's intensity changes near its landfall is of great importance in making an effective hurricane warning. This study uses airborne Doppler radar data collected during the NASA Tropical Cloud Systems and Processes (TCSP) field experiment in July 2005 to examine the impact of airborne radar observations on the short-range numerical simulation of hurricane track and intensity changes. A series of numerical experiments is conducted for Hurricane Dennis (2005) to study its intensity changes near a landfall. Both radar reflectivity and radial velocity-derived wind fields are assimilated into the Weather Research and Forecasting (WRF) model with its three-dimensional variational data assimilation (3DVAR) system. Numerical results indicate that the radar data assimilation has greatly improved the simulated structure and intensity changes of Hurricane Dennis. Specifically, the assimilation of radar reflectivity data shows a notable influence on the thermal and hydrometeor structures of the initial vortex and the precipitation structure in the subsequent forecasts, although its impact on the intensity and track forecasts is relatively small. In contrast, assimilation of radar wind data results in moderate improvement in the storm-track forecast and significant improvement in the intensity and precipitation forecasts of Hurricane Dennis. The hurricane landfall, intensification, and weakening during the simulation period are well captured by assimilating both radar reflectivity and wind data.

Dropwindsonde, Geostationary Operational Environmental Satellite-11 (GOES-11) rapid-scan atmospheric motion vectors, and NASA Quick Scatterometer (QuikSCAT) near-surface wind data collected during NASA's Tropical Cloud Systems and Processes (TCSP) field experiment in July 2005 were assimilated into an advanced research version of the Weather Research and Forecasting (WRF) model using its three-dimensional variational data assimilation (3DVAR) system. The impacts of the mesoscale data assimilation on WRF numerical simulation of Tropical Storms Cindy and Gert (2005) near landfall are examined. Sensitivity of the forecasts to the assimilation of each single data type is investigated. Specifically, different 3DVAR strategies with different analysis update cycles and resolutions are compared in order to identify the better methodology for assimilating the data from research aircraft and satellite for tropical cyclone study.The results presented herein indicate the following. 1) Assimilation of dropwindsonde and satellite wind data into the WRF model improves the forecasts of the two tropical storms up to the landfall time. The QuikSCAT wind information is very important for improving the storm track forecast, whereas the dropwindsonde and GOES-11 wind data are also necessary for improved forecasts of intensity and precipitation. 2) Data assimilation also improves the quantitative precipitation forecasts (QPFs) near landfall of the tropical storms. 3) A 1-h rapid-update analysis cycle at high resolution (9 km) provides more accurate tropical cyclone forecasts than a regular 6-h analysis cycle at coarse (27 km) resolution. The high-resolution rapidly updated 3DVAR analysis cycle might be a practical way to assimilate the data collected from tropical cyclone field experiments.

A series of numerical experiments are conducted to examine the sensitivity of the numerical simulation of Hurricane Emily's (2005) early rapid intensification to the cumulus parameterization schemes in the advanced research version of Weather Research and Forecasting (WRF) model at di¤erent horizontal resolutions. Results indicate that the numerical simulations are very sensitive to the choices of cumulus schemes at 9 km grid spacings. Specifically, with di¤erent cumulus schemes, the simulated minimum central sea level pressure (SLP) varies by 41 hPa during the 54 h forecast period. In contrast, only about 10 hPa di¤erence is produced in minimum central SLP by varying planetary boundary layer (PBL) parameterization schemes in the same simulation period. Physical and dynamic mechanisms associated with this sensitivity are investigated. It is found that the intensity of the simulated storm depends highly on the magnitude and structure of surface latent heat flux and convective heating rate over the storm eyewall. The use of cumulus schemes is helpful for the model to reproduce those favorable conditions that cause the storm deepening. However, at 3 km resolution, the cumulus schemes do not result in any notable di¤erence in the storm intensity and track forecasts. Only a slight di¤erence is found in the simulated storm precipitation structure. Compared with cumulus schemes, the PBL schemes have significant impacts on Emily's intensity forecast at 3 km resolution; the minimum central SLP varies by 37 hPa with the use of a di¤erent PBL scheme in the WRF model.

Lightning initiation (LI) events over Florida and Oklahoma are examined and statistically compared to understand the behavior of observed radar and infrared satellite interest fields (IFs) in the 75-min time frame surrounding LI. Lightning initiation is defined as the time of the first lightning, of any kind, generated in a cumulonimbus cloud. Geostationary Operational Environmental Satellite (GOES) infrared IFs, contoured frequency by altitude diagrams (CFADs) of radar reflectivity, and model sounding data, analyzed in concert, show the mean characteristics over time for 36 and 23 LI events over Florida and Oklahoma, respectively. CFADs indicate that radar echoes formed 60 min before Florida LI, yet Oklahoma storms exhibited a ~30-min delayed development. Large ice volumes in Florida developed from the freezing of lofted liquid hydrometeors formed by long-lived (~45 min) warm rain processes, which are mostly absent in Oklahoma. However, ice volumes developed abruptly in Oklahoma storms despite missing a significant warm rain component. GOES fields were significantly different before 30 min prior to LI between the two locations. Compared to Florida storms, lower precipitable water (PW), higher convective available potential energy, and higher 3.9-μm reflectance in Oklahoma, suggest stronger and drier updrafts producing a greater abundance of small ice particles. Somewhat larger 15-min 10.7-μm cooling rates in Oklahoma confirm stronger updrafts, while clouds in the 60–30-min pre-LI period show more IF variability (e.g., in the 6.5–10.7-μm difference). Florida storms (high PW, slower growth) offer more lead time for LI predictability, compared to Oklahoma storms (low PW, explosive growth), with defined anvils being obvious at the time of LI.