Characterizing the Impacts of Turbulence Closures on Real Hurricane Forecasts: A Comprehensive Joint Assessment of Grid Resolution, Horizontal Turbulence Models, and Horizontal Mixing Length

Abstract

Hurricanes are highly complex geophysical flows that have caused billions of dollars in damage in recent years. Despite the significance of these extreme weather events, the turbulence mechanisms that derive the dynamics of hurricane flow systems are poorly understood and ineffectively parameterized in numerical weather prediction (NWP) models. The objective of this study is to bridge these knowledge gaps by assessing the accuracy and deficiencies of existing horizontal turbulence models in NWPs for hurricane forecasts. In particular, the Weather and Research Forecasting (WRF) Model is employed to conduct 135 simulations of five real hurricanes by varying the grid resolution, turbulence models, and horizontal mixing length values. Decreasing the default horizontal mixing length values both in low and high resolution WRF simulations significantly improves the wind intensity forecasts. This result indicates that the existing horizontal diffusion parameterizations are overly dissipative for hurricane flows, and thus, generate a weaker vortex compared to observations. These deficiencies are shown to stem from the horizontal mixing‐length parameterization in WRF that is prescribed as a function of grid size without considering the physics of the flows (e.g., rotation). The paper provides notable insights into the role of turbulent fluxes in simulated hurricane evolutions that can be useful to advance the turbulence parameterizations of NWP models for hurricane forecasts.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 01, 2022
Source ID
10.1029/2021ms002796

Entities

People

  • Jun Zhang
  • Mostafa Momen
  • Oussama Romdhani

Organizations

  • National Oceanic and Atmospheric Administration
  • Office of Naval Research
  • University of Houston
  • University of Miami

Tags

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers