McEniry Building
Room 237

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fx: 704-687-5966

email: betherto

The demand for electricity is influenced by the weather. For example - on hot days people use their air conditioners more.  More accurate prediction of temperature will allow electric power companies to better serve their customers.  This work will focus on using the WRF model to more accurately predict surface temperatures in the Carolinas.

Thanks to Duke Energy for funding of this project.  Thanks also to collaborators Steve Leyton and Nick Keener

Thanks to Savannah River National Laboratory for funding of this project.  Thanks also to collaborator Robert Kurzeja

Eric Weinke
FREEZE PREDICTABILITY

When freezing conditions grip the southwest United States, the citrus crop is in jeopardy.  The more time there is to prepare, the better the outcome.  Eric is going to explore predictability of these freeze events.

Elliot Tardiff
METEOROLOGY IMPACTS ON NASCAR

The performance of race cars depends on many things, including the conditions of the atmosphere.  Elliot is going to look at the impacts of meteorology on NASCAR.

Chris Blanton
HURRICANE WILMA INTENSIFICATION

Hurricane Wilma underwent rapid intensification, from a Category 1 Hurricane to a Category 5 in less than 24-hours.  Why did this happen?  How important were vortex-rossby waves to the process?  Using WRF, Chris is investigating the intensification of Wilma.

Thanks to SIMVAC for funding of this project. 

Heavy rains can cause rivers to rise over their banks, and in the urban environment that is Charlotte, effects if impervious surfaces can amplify the pace of rising water.  In this project, we'll link up a precipitation model (WRF) with a river flood model to predict flash flooding in Charlotte.

Thanks to RENCI for funding of this project.  Thanks also to collaborator Ross Meentemeyer. 

HURRICANE EDUCATION

The 2005 Atlantic Season was the most active in recorded history.  Hurricane Katrina was the most damaging storm in U.S. History.  Hurricane Wilma was the most intense storm ever in the Atlantic.  These three topics will be the focus of educational modules built using the Integrated Data Viewer (IDV)

Thanks to Unidata for funding this research, and thanks to Jeff Weber, Bruce Muller and Pat Parrish (National Center for Atmospheric Research) and to Rich Cianflone for their contributions to this project.

PROABABILISTIC TROPICAL CYCLONE FORECASTING

When forecasting the track or intensity of tropical cyclones, it is beneficial to forecasters to have information regarding the uncertainty of model forecasts.  The SHIPS model can provide an intensity forecast for a tropical cyclone, and by altering parameters used in SHIPS (SST, wind shear, storm track), an ensemble of forecasts is generated.

Thanks to Mark Demaria (Cooperative Institute for Atmospheric Research) for contributions.

THE USE OF AIRS DATA IN PBL FORECASTS

The prediction of mesoscale convective complexes by numerical weather prediction models, such as WRF, is hindered by inadequate sampling of thermodynamic variables.  The AIRS sensor onboard the AQUA satellite can provide such data.  This project will work to incoroporate AQUA data into WRF forecasts, using and Ensemble Kalman Filter for data assimlation, to better predict the boundary layer VTMX