Prediction of near-inertial wave generation and propagation

Abstract

Surface winds globally impart a large and uncertain amount of power (i.e., 0.35-1.4 TW) to inertial oscillations in the mixed layer. These currents are energetic and frequently exceed 10 cm/s. Where they converge and diverge they pump the base of the mixed layer, generating near-inertial internal waves (NIWs). Horizontally-variable wind, the beta effect, and mesoscale variability all produce divergences in mixed-layer currents, but their relative contributions to NIW generation are unknown. Once generated, NIWs propagate downward and laterally, but little is known about their interactions with other waves or mesoscale features. As a result, little is known about where NIWs dissipate, or how they mix the ocean .This research aims to better predict the generation and propagation of NIWs. The specific objectives are to (1) develop and test methods to separate forced and freely-propagating near- inertial motions in realistic simulations and observations, (2) use simplified global numerical simulations to estimate the geography of wind work, mixed-layer currents, NIW generation and NIW propagation, (3) quantify the effects of horizontally-variable wind stress, the beta effect, mesoscale flows on NIW generation, and (4) assess the accuracy of models that predict near-inertial surface currents and NIWs, and identify the dominant sources of uncertainty in each model. The methods will incorporate both theory and numerical modeling. First, a method of separating forced and freely propagating near-inertial motions in the upper ocean will be developed and tested. Using this method, NIW generation will be quantified in semi-analytical and idealized fully-nonlinear numerical models. Next, a 1/100 degree horizontal resolution coupled-mode shallow water (CSW) model with realistic winds, stratification, and topography will simulate basin-scale NIWs. This model will include linearized interactions with mesoscale currents and realistic mixed-layer submodels. Lastly, several prediction models will be analyzed to quantify sources of uncertainty in near-inertial currents and shear.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 04, 2018
Source ID
N000141812800

Entities

People

  • Samuel Kelly

Organizations

  • Office of Naval Research
  • Regents of the University of Minnesota
  • United States Navy

Tags

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computational Modeling and Simulation
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers