Award Abstract # 2228299
Unique Turbulence Dynamics in Hurricane Boundary Layers and Improving Their Parameterizations in Numerical Weather Prediction Models

NSF Org: AGS
Division of Atmospheric and Geospace Sciences
Recipient: UNIVERSITY OF HOUSTON SYSTEM
Initial Amendment Date: October 21, 2022
Latest Amendment Date: July 7, 2023
Award Number: 2228299
Award Instrument: Standard Grant
Program Manager: Nicholas Anderson
nanderso@nsf.gov
 (703)292-4715
AGS
 Division of Atmospheric and Geospace Sciences
GEO
 Directorate for Geosciences
Start Date: November 1, 2022
End Date: October 31, 2025 (Estimated)
Total Intended Award Amount: $458,238.00
Total Awarded Amount to Date: $508,227.00
Funds Obligated to Date: FY 2023 = $508,227.00
History of Investigator:
  • Mostafa Momen (Principal Investigator)
    mmomen@uh.edu
  • Jun Zhang (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Houston
4300 MARTIN LUTHER KING BLVD
HOUSTON
TX  US  77204-3067
(713)743-5773
Sponsor Congressional District: 18
Primary Place of Performance: University of Houston
4800 W CALHOUN ST STE 316
HOUSTON
TX  US  77004
Primary Place of Performance
Congressional District:
18
Unique Entity Identifier (UEI): QKWEF8XLMTT3
Parent UEI:
NSF Program(s): Physical & Dynamic Meteorology
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 152500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.050

ABSTRACT

Hurricanes have been the costliest natural disaster in US history thus far by causing billions of dollars in damage. Ocean warming and climate change can exacerbate tropical cyclone destruction by increasing the frequency and intensity of future major hurricanes. Only four recent hurricanes ? Katrina, Sandy, Maria, and Harvey ? resulted in more than $450B in damages and about 5,000 fatalities. Thus, it is imperative for the scientific community to better understand and forecast hurricane dynamics and its turbulent winds in order to effectively mitigate their economic ramifications. Although turbulence plays a significant role in hurricane evolution, it is neither thoroughly understood nor parameterized in hurricane flows. Given the remarkable impacts of future hurricanes on humans and the lack of a reliable turbulence scale model for such rotating flows, a high-fidelity hurricane model is now essential. This project aims to address this knowledge gap using a combination of numerical weather prediction (NWP) models and observations to thrust forward the understanding of hurricane turbulence, and to develop practical methodologies for improving hurricane forecasts in NWP models.

The research provides pathways to new frontiers in turbulence theory and modeling of hurricane flows. In particular, the driving hypothesis of the project is ?turbulence dynamics in hurricane boundary layers (HBLs) are significantly different from typical atmospheric boundary layers (ABLs) due to rotation in HBLs and their large Rossby number (centrifugal/Coriolis force); therefore, existing turbulence models in NWPs limit the accuracy of hurricane forecasts.? This hypothesis will be tested by answering these open research questions 1) How do hurricanes modulate the characteristic mixing length scales and turbulence dynamics in the HBL? and 2) How should the horizontal and vertical turbulent fluxes of an HBL be parameterized in NWPs compared to typical ABLs? To answer these questions, a unique combination of high-fidelity large-eddy simulations (LESs), NWPs, and observations will be employed. The preliminary results support the project?s central hypothesis by demonstrating remarkably different turbulence structures and energy spectra in HBLs when compared to typical ABLs, and substantial improvements in NWP?s hurricane forecasts when current turbulence models are altered. Hence, addressing the above questions will advance the field of physical and dynamic meteorology by elucidating the distinctive turbulence mechanisms in hurricanes compared to conventional much-studied ABLs. Other notable expected outcomes of the project include an extensive dataset of high-resolution LESs of HBLs, new physics-based turbulence closures with rotation correction that are specifically designed for real hurricanes, and a dataset of improved hurricane simulations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 14)
Aberson, Sim D and Zhang, Jun A and Zawislak, Jonathan and Sellwood, Kathryn and Rogers, Robert and Cione, Joseph J "The NCAR GPS Dropwindsonde and Its Impact on Hurricane Operations and Research" Bulletin of the American Meteorological Society , v.104 , 2023 https://doi.org/10.1175/BAMS-D-22-0119.1 Citation Details
Holbach, Heather M. and Bousquet, Olivier and Bucci, Lisa and Chang, Paul and Cione, Joe and Ditchek, Sarah and Doyle, Jim and Duvel, Jean-Philippe and Elston, Jack and Goni, Gustavo and Hon, Kai Kwong and Ito, Kosuke and Jelenak, Zorana and Lei, Xiaotu a "Recent advancements in aircraft and in situ observations of tropical cyclones" Tropical Cyclone Research and Review , v.12 , 2023 https://doi.org/10.1016/j.tcrr.2023.06.001 Citation Details
Khondaker, Md_Murad_Hossain and Momen, Mostafa "Improving Hurricane Intensity and Streamflow Forecasts in Coupled Hydrometeorological Simulations by Analyzing Precipitation and Boundary Layer Schemes" Journal of Hydrometeorology , v.25 , 2024 https://doi.org/10.1175/JHM-D-23-0153.1 Citation Details
Li, Meng and Zhang, Jun A. and Matak, Leo and Momen, Mostafa "The Impacts of Adjusting Momentum Roughness Length on Strong and Weak Hurricane Forecasts: A Comprehensive Analysis of Weather Simulations and Observations" Monthly Weather Review , v.151 , 2023 https://doi.org/10.1175/MWR-D-22-0191.1 Citation Details
Li, Xin and Pu, Zhaoxia and Zhang, Jun A and Zhang, Zhan "A modified vertical eddy diffusivity parameterization in the HWRF model based on large eddy simulations and its impact on the prediction of two landfalling hurricanes" Frontiers in Earth Science , v.11 , 2023 https://doi.org/10.3389/feart.2023.1320192 Citation Details
Matak, Leo and Momen, Mostafa "The Role of Vertical Diffusion Parameterizations in the Dynamics and Accuracy of Simulated Intensifying Hurricanes" Boundary-Layer Meteorology , v.188 , 2023 https://doi.org/10.1007/s10546-023-00818-w Citation Details
Ming, Jie and Zhang, Jun A. and Li, Xin and Pu, Zhaoxia and Momen, Mostafa "Observational Estimates of Turbulence Parameters in the Atmospheric Surface Layer of Landfalling Tropical Cyclones" Journal of Geophysical Research: Atmospheres , v.128 , 2023 https://doi.org/10.1029/2022JD037768 Citation Details
Rezaie, Milad and Momen, Mostafa "Characterizing turbulence structures in convective and neutral atmospheric boundary layers via Koopman mode decomposition and unsupervised clustering" Physics of Fluids , v.36 , 2024 https://doi.org/10.1063/5.0206387 Citation Details
Rogers, Robert F. and Zhang, Jun A. "Airborne Doppler Radar Observations of Tropical Cyclone Boundary Layer Kinematic Structure and Evolution During Landfall" Geophysical Research Letters , v.50 , 2023 https://doi.org/10.1029/2023GL105548 Citation Details
Romdhani, Oussama and Matak, Leo and Momen, Mostafa "Hurricane track trends and environmental flow patterns under surface temperature changes and roughness length variations" Weather and Climate Extremes , v.43 , 2024 https://doi.org/10.1016/j.wace.2024.100645 Citation Details
Sabet, Fateme and Yi, Young R. and Thomas, Leif and Momen, Mostafa "Characterizing mean and turbulent structures of hurricane winds via large-eddy simulations" , 2022 Citation Details
(Showing: 1 - 10 of 14)

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