HR: 11:45h
AN: A12D-06    [Abstracts]
TI: Representing Hurricanes with a Nested Global Forecast Model
AU: * Otte, M J
EM: otte@duke.edu
AF: Duke University, Department of Civil and Environmental Engineering, Box 90287, Durham, NC 27708-0287, United States
AU: Walko, R L
EM: robert.walko@duke.edu
AF: Duke University, Department of Civil and Environmental Engineering, Box 90287, Durham, NC 27708-0287, United States
AU: Avissar, R
EM: avissar@duke.edu
AB: A global forecast model is essential for predicting hurricane tracks beyond a period of ~2 days since global processes that may influence the longer-term storm tracks can be represented explicitly and there are no errors from the lateral boundary conditions that can propagate into the model domain and diminish the accuracy of the track forecasts. However, global models usually do not have enough horizontal and vertical resolution to produce meaningful hurricane intensity forecasts. Most current operational global forecast models represent the atmosphere horizontally using spherical harmonic basis functions with an equivalent resolution of ~40-50 km. The NOAA Science Advisory Board Hurricane Intensity Research Working Group recommends approximately 1-km-resolution hurricane forecasts in order to represent the important physical processes in the core region of hurricanes that are important to accurately predict hurricane intensity. Even with state-of-the-art computers, it will be many years before global forecasts with 1-km horizontal resolution are practical. To predict both hurricane tracks and intensity well, a nested global model is necessary. Large-scale processes are represented on a coarser, computationally-efficient grid while features such as hurricanes are represented on a high-resolution nest. The global model used in this study is the Ocean-Land-Atmosphere Model (OLAM) being developed at Duke University. OLAM is the global successor to the Regional Atmospheric Modeling System (RAMS), which originated at Colorado State University in 1986. OLAM uses the same physics parameterizations as RAMS, but it solves the governing equations by discretizing the atmosphere on an unstructured triangular finite-volume grid. The triangular grid uses the Arakawa-C staggering and is fully mass conservative. Since the triangular mesh is unstructured, the mesh can be refined to produce much higher horizontal resolution in areas of interest such as near hurricanes. Here, we examine hurricane track and intensity forecasting in a global nested model using a real-data case. Using a high-resolution nest in the vicinity of a hurricane, we examine how well the inner core hurricane structure can be resolved in order to produce meaningful intensity forecasts. We also determine if the better representation of hurricanes also leads to better longer-term hurricane track predictions.
DE: 3315 Data assimilation
DE: 3322 Land/atmosphere interactions (1218, 1631, 1843)
DE: 3339 Ocean/atmosphere interactions (0312, 4504)
DE: 3354 Precipitation (1854)
DE: 3374 Tropical meteorology
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting