Observational Estimates of Turbulence Parameters in the Atmospheric Surface Layer of Landfalling Tropical Cyclones
Jie Ming
Key Laboratory for Mesoscale Severe Weather/MOE and School of Atmospheric Science, Nanjing University, Nanjing, China
Joint Center for Atmospheric Radar Research of Centre of Modern Analysis, Nanjing University (CMA/NJU), Beijing, China
China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an New Area, China
Lianyungang Institute of High-Tech Research, Nanjing University, Lianyungang, China
Contribution: Methodology, Formal analysis, Writing - original draft, Writing - review & editing
Search for more papers by this authorCorresponding Author
Jun A. Zhang
Hurricane Research Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanographic and Atmospheric Administration, Miami, FL, USA
Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
Correspondence to:
J. A. Zhang and M. Momen,
Contribution: Methodology, Conceptualization, Writing - original draft, Writing - review & editing, Funding acquisition
Search for more papers by this authorXin Li
Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA
Contribution: Formal analysis, Data curation, Writing - review & editing
Search for more papers by this authorZhaoxia Pu
Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA
Contribution: Methodology, Writing - original draft, Writing - review & editing, Funding acquisition
Search for more papers by this authorCorresponding Author
Mostafa Momen
Department of Civil and Environmental Engineering, University of Houston, Houston, TX, USA
Correspondence to:
J. A. Zhang and M. Momen,
Contribution: Conceptualization, Investigation, Writing - review & editing
Search for more papers by this authorJie Ming
Key Laboratory for Mesoscale Severe Weather/MOE and School of Atmospheric Science, Nanjing University, Nanjing, China
Joint Center for Atmospheric Radar Research of Centre of Modern Analysis, Nanjing University (CMA/NJU), Beijing, China
China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory, Xiong'an New Area, China
Lianyungang Institute of High-Tech Research, Nanjing University, Lianyungang, China
Contribution: Methodology, Formal analysis, Writing - original draft, Writing - review & editing
Search for more papers by this authorCorresponding Author
Jun A. Zhang
Hurricane Research Division, Atlantic Oceanographic and Meteorological Laboratory, National Oceanographic and Atmospheric Administration, Miami, FL, USA
Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
Correspondence to:
J. A. Zhang and M. Momen,
Contribution: Methodology, Conceptualization, Writing - original draft, Writing - review & editing, Funding acquisition
Search for more papers by this authorXin Li
Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA
Contribution: Formal analysis, Data curation, Writing - review & editing
Search for more papers by this authorZhaoxia Pu
Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA
Contribution: Methodology, Writing - original draft, Writing - review & editing, Funding acquisition
Search for more papers by this authorCorresponding Author
Mostafa Momen
Department of Civil and Environmental Engineering, University of Houston, Houston, TX, USA
Correspondence to:
J. A. Zhang and M. Momen,
Contribution: Conceptualization, Investigation, Writing - review & editing
Search for more papers by this authorAbstract
This study analyzes observations collected by multilevel towers to estimate turbulence parameters in the atmospheric surface layer of two landfalling tropical cyclones (TCs). The momentum flux, turbulent kinetic energy (TKE) and dissipation rate increase with the wind speed independent of surface types. However, the momentum flux and TKE are much larger over land than over the coastal ocean at a given wind speed range. The vertical eddy diffusivity is directly estimated using the momentum flux and strain rate, which more quickly increases with the wind speed over a rougher surface. Comparisons of the eddy diffusivity estimated using the direct flux method and that using the friction velocity and height show good agreement. On the other hand, the traditional TKE method overestimates the eddy diffusivity compared to the direct flux method. The scaling coefficients in the TKE method are derived for the two different surface types to better match with the vertical eddy diffusivity based on the direct flux method. Some guidance to improve vertical diffusion parameterizations for TC landfall forecasts in weather simulations are also provided.
Key Points
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The relationship between the vertical eddy diffusivity and wind speed is different over different underlying surface types
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The vertical eddy diffusivity estimated using the flux and strain rate is comparable to that using the friction velocity and height
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The scaling coefficient for estimating the vertical eddy diffusivity using turbulent kinetic energy varies with surface roughness length
Plain Language Summary
Improved understanding of small-scale processes near the surface is important for advancement of tropical cyclone intensity prediction. Observational data collected by multilevel towers are analyzed to study the turbulent mixing process and structure in the atmospheric surface layer of two landfalling storms. Turbulence parameters such momentum flux, turbulent kinetic energy (TKE) and dissipation rate are estimated, which shows a wind speed independence regardless of surface types. The magnitudes of the momentum flux and TKE are much larger over land than over the ocean at a given wind speed range. The turbulent mixing strength measured by the vertical eddy diffusivity are estimated and compared using three different methods. The scaling coefficient in the eddy diffusivity parameterization is derived based on observations. This newly derived coefficient would potentially lead to improved tropical cyclone forecasts when used in numerical models.
Open Research
Data Availability Statement
The observed data used in this paper are available on https://box.nju.edu.cn/d/dcbefdd2bcd24446b350/ with a password of datajgr for downloading the data. The hurricane field experiment data can be accessed through https://www.aoml.noaa.gov/hrd/data_sub/hurr.html. Access to other public datasets used in this study is described in Ming and Zhang (2018) that can be obtained from https://doi.org/10.1029/2017JD028076.
Supporting Information
| Filename | Description |
|---|---|
| 2022JD037768-sup-0001-Supporting Information SI-S01.docx742 KB | Supporting Information S1 |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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