Data Assimilation in Geosciences
Organized by Jeff Anderson (NCAR), Kayo Ide (CSCAMM, UMd), Eitan Tadmor (CSCAMM, UMd), Olivier Talagrand (ENS)http://www2.cscamm.umd.edu/programs/das13/
06/03/13 - 06/14/13
Center for Scientific Computation and Math. Modeling, University of Maryland, College Park
Data assimilation (DA) aims at determining and predicting the state of a dynamical system as accurately as possible by combining heterogeneous sources of information in an optimal way. The mathematical problem of DA is both fundamental in that it aims at the estimation of an unknown, true state and challenging as it does not naturally afford a clean solution. The mathematical methods of DA describe algorithms for combining observations of a dynamical system, a computational model that describes its evolution, and appropriate prior information. From its beginning in the 50s, numerical weather prediction lead the development of DA. It has now become an intensive field of research, with applications in oceanography and atmospheric chemistry, and extensions to other geophysical sciences.
This summer school targets primarily researchers at an early stage of their career with previous experience in data assimilation. It will focus on interdisciplinary exposure to advanced methods in data assimilation, while lectures by operational experts will provide an overview of current cutting-edge techniques in this field.