Thursday, March 25

Large-Scale Implementation of Data Assimilation for the Ocean and Atmosphere - Part I of II

10:30 AM-12:30 PM
Room: Ballroom A

For Part II, see MS19.

Numerous physical problems do not fit into the classical paradigm of initial or boundary value problems. Instead, empirical data are available at different spatial positions at different times, and one seeks a solution that best fits the data and a mathematical model, in some optimal sense. One formulation of this idea is to generate a hindcast of past events; such a solution can be used to generate initial conditions for a forecast or to test a dynamical model as a formal hypothesis. Another technique is to incorporate data into a forecast as it proceeds. The speakers in this minisymposium will discuss the computational and physical issues involved in the implementation of such methods for large-scale modeling of the atmosphere and ocean.

Organizer: Robert L. Higdon
Oregon State University

10:30-10:55 NewSequential Data Assimilation for Nonlinear Dynamics
Geir Evensen, Nansen Environmental and Remote Sensing Center, Bergen, Norway
11:00-11:25 NewTowards A True Four-Dimensional Atmospheric Data Assimilation Algorithm: Application of a Cycling Representer Algorithm to a Simple Transport Problem
Liang Xu, U. S. Naval Research Laboratory
11:30-11:55 Data Assimilation for Large-Scale Coherent Structures
Kayo Ide, University of California, Los Angeles
12:00-12:25 Data Assimilation in Phase-Resolving Ocean Wave Models
James M. Kaihatu, U.S. Naval Research Laboratory, Stennis Space Center

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MMD, 1/19/99