Journal
WEATHER AND FORECASTING
Volume 26, Issue 6, Pages 885-901Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/WAF-D-11-00001.1
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Funding
- NASA [1284085]
- ONR [N000140710186]
- NSF [ATM0758609]
- Div Atmospheric & Geospace Sciences
- Directorate For Geosciences [0758609] Funding Source: National Science Foundation
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In this study, a 72-h cloud-permitting numerical prediction of Hurricane Wilma (2005), covering its initial 18-h spinup, an 18-h rapid intensification (RI), and the subsequent 36-h weakening stage, is performed using the Weather Research Forecast Model (WRF) with the finest grid length of 1 km. The model prediction uses the initial and lateral boundary conditions, including the bogus vortex, that are identical to the Geophysical Fluid Dynamics Laboratory's then-operational data, except for the time-independent sea surface temperature field. Results show that the WRF prediction compares favorably in many aspects to the best-track analysis, as well as satellite and reconnaissance flight-level observations. In particular, the model predicts an RI rate of more than 4 hPa h(-1) for an 18-h period, with the minimum central pressure of less than 889 hPa. Of significance is that the model captures a sequence of important inner-core structural variations associated with Wilma's intensity changes, namely, from a partial eyewall open to the west prior to RI to a full eyewall at the onset of RI, rapid eyewall contraction during the initial spinup, the formation of double eyewalls with a wide moat area in between during the most intense stage, and the subsequent eyewall replacement leading to the weakening of Wilma. In addition, the model reproduces the boundary layer growth up to 750 hPa with an intense inversion layer above in the eye. Recognizing that a single case does not provide a rigorous test of the model predictability due to the stochastic nature of deep convection, results presented herein suggest that it is possible to improve forecasts of hurricane intensity and intensity changes, and especially RI, if the inner-core structural changes and storm size could be reasonably predicted in an operational setting using high-resolution cloud-permitting models with realistic initial conditions and model physical parameterizations.
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