Physical parameterizations in computer models need to consider the unique structures of tropical cyclones. The study helps us understand turbulent mixing to advance how we account for it in our forecast model parameterizations to improve forecasts.
Tropical cyclones are fueled by the heat from the warm ocean below. This heat energy moves upward into the atmosphere due to mixing by turbulence, random and continuously changing wind over small distances (Fig. 1). Computer models predict the weather at regularly spaced locations, called grid points, that are usually between 1 and 50 km apart, but these distances are far too large to show the small turbulence. So, the models use what we call parameterizations that approximate what is happening with the small turbulent features. These parameterizations usually work the same way everywhere, although we know that turbulence is different in tropical cyclones than in other areas, and even within tropical cyclones themselves.
We ran the Weather Research and Forecasting (WRF) model many times with different turbulence parameterizations to understand how they impact forecasts. A total of 135 runs of five real hurricanes were conducted by varying the grid resolution (the distance between model grid points), turbulence parameterizations, and horizontal mixing length scales that represent the average size of the turbulent features.
You can read the study online at https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021MS002796. For more information, contact firstname.lastname@example.org.
The authors acknowledge the Department of Civil and Environmental Engineering at the University of Houston for support via startup funds. Jun Zhang was supported by NOAA Grant NA19OAR4590239 and ONR grant N00014-20-1-2071.
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