Computer models of the ocean and atmosphere are our primary tool for predicting future climate change - quantities important for society such as sea level rise, storm intensity and warming.  Because of computer limitations, these models cannot include all physical processes occurring in the ocean but must rather rely on observations to properly represent or "parameterize" their effects on the model.  Model predictions of sea level rise, for example, are sensitive to how the effects of ocean turbulence are represented.  Specifically, predictions of sea level rise 100 years from now vary by about 30 cm using different turbulence representations.  Intuitively, this can be easily understood since turbulence reduces temperature gradients or contrasts in the ocean by moving heat.  The more turbulence occurring, the more heat is taken up by the ocean and the greater the sea level rise owing in part to contraction.  The primary goal of this project has been to take the detailed observations of ocean turbulence (which is primarily due to breaking internal gravity waves, the subsurface analogue of the waves we see breaking on beaches) and to develop means of including them in the climate models.  The problem is complicated because waves break far from their sources.  Hence, we have broken then problem into "local" turbulence (due to flows over seafloor bumps) and "remote" turbulence (due to waves generated by those flows that travel to other regions before breaking down into turbulence).  Additionally, the wind creates "near-inertial" waves that also lead to turbulence.  These three effects have now been included in climate models and their importance demonstrated.  Future work will continue to refine these methods and representations for improved climate state predictions.

Last Modified: 06/30/2015
Modified by: Matthew H Alford