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MCRN

Statistical Data Assimilation For Parameter Estimation In Costal Ocean Hydrodynamics Modeling

Coastal ocean models are used for a variety of applications, including modeling tides and hurricane storm surge. These models numerically solve the shallow water equations, which are derived by depth integrating the Navier-Stokes equations. The inherent uncertainties in coastal ocean models are a re…
  • Resource Presentations
MCRN

Correlated Observation Errors in Data Assimilation

Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information, and reduction in analysis accu…
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MCRN

Particle filters for geophysical applications

Avoiding degeneracy is a crucial challenge for particle filters. Results have shown that the number of particles scales exponentially with respect to the number of independent observations. In this talk I will review attempts to counteract this phenomenon by exploiting proposal densities. I will put…
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MCRN

Emulators in climate science. Uncertainty, sensitivity, calibration and more

An emulator or a surrogate is a statistical approximation of a complex numerical model. Emulators are fast to run and include a measure of their own uncertainty. This makes them suitable for a number of applications in climate science. Emulators were originally devised for uncertainty quantification…
  • Resource Presentations