The Impact of Aircraft Dropsonde and Satellite Wind Data on Numerical Simulations of Two Landfalling Tropical Storms during the Tropical Cloud Systems and Processes Experiment

Abstract

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.

The impact of microphysical schemes on hurricane intensity and track

“…The initial conditions were enhanced by incorporating satellite data through the WRF three-dimensional variational data assimilation (3DVAR) system. Please see Pu et al (2008) for more information on the data assimilation procedure. Thirty-hour model integrations were performed.…”

How Vertical Wind Shear Affects Tropical Cyclone Intensity Change: An Overview

“…Thus, large-eddy simulations (LES) will be primarily used to determine the eddy-diffusion coefficients necessary to properly parameterize these motions when using a grid spacing on the order of a kilometer. Going forward, increasing wind observations and the assimilation of these wind measurements into the models would improve model initial conditions in terms of the accurate representation of the wind shears and thus enhance the numerical model's ability to produce accurate TC intensity forecasts (e.g., Pu et al 2008). The future in the shearintensity area of research looks particularly dependent on increases in computing power, which will enable scientists to examine the above questions without as much of a reliance on parameterizations.…”

Improving Hurricane Intensity Forecasting through Data Assimilation: Environmental Conditions Versus the Vortex Initialization

“…A further study with Hurricane Cindy (2005) shows that the assimilation of the aforementioned wind data has a great impact on the quantitative precipitation forecast (QPF) during Cindy's evolution (Fig. 2), implying the significant effects of environmental wind shear on the mesoscale convective system associated with Cindy (See Pu et al, 2008 for details). Without data assimilation, the forecast shows unrealistically large amounts of rain after Cindy made landfall.…”