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 Sequential Data Assimilation for Nonlinear Dynamics**- Geir Evensen, Nansen Environmental and Remote Sensing Center, Bergen, Norway
**11:00-11:25 Towards 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

*MMD, 1/19/99*