Submission information
Submission Number: 175
Submission ID: 3944
Submission UUID: 6694fe6d-02c6-4b60-9e45-0133328984cf
Submission URI: /form/project
Created: Mon, 08/21/2023 - 06:22
Completed: Mon, 08/21/2023 - 06:26
Changed: Mon, 07/08/2024 - 13:28
Remote IP address: 146.75.253.174
Submitted by: Gaurav Khanna
Language: English
Is draft: No
Webform: Project
| Project Title | Effects of wind-wave misalignment on air-sea momentum flux and drag coefficient |
|---|---|
| Program | CAREERS |
| Project Image | |
| Tags | oceanography (331) |
| Status | Complete |
| Project Leader | Tetsu Hara |
| tetsuhara@uri.edu | |
| Mobile Phone | |
| Work Phone | |
| Mentor(s) | Tetsu Hara |
| Student-facilitator(s) | Joshua Port |
| Mentee(s) | |
| Project Description | We conduct Large Eddy Simulation (LES) studies of turbulent wind over surface waves that propagate in different directions from wind direction. The results are used to better understand how misaligned waves modify the wind turbulence and resulting air-sea momentum flux. Recent observational studies show that the drag coefficient (air-sea momentum flux) is significantly reduced when dominant wind-forced surface waves are misaligned from the local wind. Misaligned waves are particularly common under tropical cyclones and/or in shallow water coastal regions. The results from this study will be used to develop a new parameterization of sea-state dependent drag coefficient (air-sea momentum flux) including the effect of misaligned surface waves. Such a parameterization is needed for various coupled atmospheric, wave, and ocean prediction models. In particular, tropical cyclone prediction models are expected to be significantly improved by including the newly developed parameterization. The student will obtain extensive experience working on an HPC cluster (command-line Linux, Fortran code compilation, SLURM job scheduler, optimal submission parameters etc.) and will also learn to use available visualization tools. The project will require access to a modest HPC system that provides ~1024 cores (128 cores x 8 nodes, 64 cores x 16 nodes, etc.) and a scratch filesystem. |
| Project Deliverables | |
| Project Deliverables | |
| Student Research Computing Facilitator Profile | |
| Mentee Research Computing Profile | |
| Student Facilitator Programming Skill Level | |
| Mentee Programming Skill Level | |
| Project Institution | University of Rhode Island -- Bay Campus |
| Project Address | |
| Anchor Institution | CR-University of Rhode Island |
| Preferred Start Date | |
| Start as soon as possible. | No |
| Project Urgency | Already behind3Start date is flexible |
| Expected Project Duration (in months) | 6 |
| Launch Presentation | |
| Launch Presentation Date | 02/14/2024 |
| Wrap Presentation | |
| Wrap Presentation Date | |
| Project Milestones |
|
| Github Contributions | |
| Planned Portal Contributions (if any) | |
| Planned Publications (if any) | |
| What will the student learn? | |
| What will the mentee learn? | |
| What will the Cyberteam program learn from this project? | |
| HPC resources needed to complete this project? | |
| Notes | |
| What is the impact on the development of the principal discipline(s) of the project? | Better constraining the drag coefficient under shoaling and wind-wave misalignment would be a useful contribution to the physics of air-sea interaction and could potentially improve modeling performance. We'll see how the results shake out! |
| What is the impact on other disciplines? | The results could have engineering impacts; for example, better constraining drag at the wave surface could improve estimates of wind speed at blade level for offshore wind farms. |
| Is there an impact physical resources that form infrastructure? | |
| Is there an impact on the development of human resources for research computing? | |
| Is there an impact on institutional resources that form infrastructure? | |
| Is there an impact on information resources that form infrastructure? | |
| Is there an impact on technology transfer? | |
| Is there an impact on society beyond science and technology? | In theory better constraining the drag coefficient of shoaling waves could improve things like storm surge model predictions, which of course would have economic and safety implications. |
| Lessons Learned | When using HPCs, I always find myself trying to balance willingness to experiment with not wanting to waste energy and computing resources. I think I'm in a much better place with that balance now. |
| Overall results | We've tested a number of different permutations of inputs for shoaling and non-shoaling waves which has taught us a lot about how best to sync up our simulations with laboratory observations. So, while there's a lot of work still to do, we've done a lot of the leg work to speed up future simulations while aligning results with observations. |