Event Detail

Event Type: 
Applied Mathematics and Computation Seminar
Friday, April 9, 2010 - 05:00
Gilkey 113

Speaker Info

College of Oceanic and Atmospheric Sciences, OSU

Projections of future climate change are uncertain. How do we quantify this uncertainty? Are there strategies to reduce the uncertainty? These are the fundamental questions I'd like to explore. I'll argue that, at present, the uncertainty is not well quantified and that one way to reduce the uncertainty involves developing a method to evaluate models using observations. As an example I use simulations with a model of intermediate complexity focusing on quantifying ocean diapycnal (vertical) mixing through a comparison with observations of various spatially resolved ocean tracer observations. A Bayesian approach is applied to calculate probability density functions for the diapycnal diffusivity. Issues that came up during this exercise are spatial aggregation of data, spatial auto-correlation and parameter interactions.