Mathematical Advancement in Geophysical Data Assimilation (08w5096)


(Université de Québec à Montréal)

(University of Maryland College Park)

(University of North Carolina at Chapel Hill)

Keith Thompson (Dalhousie University)


The most routinely performed implementation of geophysical data
assimilation (DA) is numerical weather prediction. The daily
weather forecast is state-of-the-art science performed on a
supercomputer using up-to-date DA technology. The current state
of the atmosphere is estimated optimally by fusing the relevant
atmospheric observations over the preceding few hours of a DA cycle
into an output computed by a large atmospheric model as a forecast.
The resulting analysis of the current state is then used as a new
initial condition to start a forecast for the next assimilation cycle.

The issue of fusing data into models arises in all scientific
areas that enjoy a profusion of data. We now have a tremendous
opportunity to bring the relevant scientific areas together in a
focused effort aimed at developing new approaches, understanding
the underlying issues and testing the implementation of new schemes.
This workshop aims to advance DA further beyond the current
state-of-the-art by engaging the mathematical community in the
fascinating challenges presented by the need for ever-improving

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the US National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnologí­a (CONACYT).