Data Assimilation & Prediction

High-dimensional multi-scale applications

High-Dimensional Multi-Scale Applications: The inevitable “curse of dimensionality” in data assimilation: The rapid growth in the number of earth observing systems, computational power, and data storage capabilities allows for the use of more complex numerical models and increases the potential of assimilating far more observations that previously possible. However, these benefits can also be a handicap as the give rise to the so-called “course of dimensionality,” in other words, the difficulty of dealing with large-dimensional problems. Our group develops techniques to account for complex interactions between multiple spatiotemporal scales and limitations introduced by dealing with high-dimensional dynamical/observation systems.

Relevant Publications


Zupanski, M., 2016: Reduced rank static error covariance for high-dimensional applications. Int. J. Numer. Meth. Fluids, 83, 245–262. doi: 10.1002/fld.4264. [Link]