Coordinated Autonomous Platform Observations to Evaluate Ocean Surface Boundary Layer Models
Abstract
This work puts forth a model-observation comparison study to evaluate the robustness of ocean surface boundary layer (OSBL) turbulence parameterizations used routinely in regional and global numerical simulations. Parameterizations of OSBL turbulence are paramount to accurate numerical representation of upper ocean processes and air-sea interactions by operational forecast models, with implications for weather prediction (Seo et al. 2014; Orenstein et al. 2022) and understanding acoustic transmission pathways (Colosi and Rudnick 2020). Despite decades of theory and modeling work aimed at understanding OSBL dynamics, large biases still exist between simulated and observed upper ocean fields.The work proposed here will apply and expand the method developed by Johnson et al. 2022 toevaluate models against coordinated observations of the OSBL collected using multiple autonomous platforms. The method focuses on finite time model simulations to reveal when models most disagree and identify which dynamics the models fail to simulate accurately.First, the method will be modified for observations, using data collected previously by a fleet of autonomous assets during the ONRLangmuir cell (LC) DRI. Next, this information will be used to guide an autonomous asset focused OSBL experiment in the Arabian Seain conjunction with the upcoming ASTraL DRI. This experiment will deploy an APL-UW Lagrangian float (or mixed layer float , MLF) and two APL-UW SGX gliders to obtain highly resolved mean and turbulent quantities of the OSBL. The combined datasets would offer an unprecedented comprehensive set of metrics under a range of surface forcing and ocean state conditions to evaluate model performance.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 24, 2023
- Source ID
- N000142312691
Entities
People
- Leah Johnson
Organizations
- Office of Naval Research
- United States Navy
- University of Washington