Theory and Practice of Data Assimilation in Ocean Modeling
Abstract
The long range goal of this project is to combine computational models with observational data to form the best picture of the ocean as an evolving system, and use that picture to understand the physical influences which govern the ocean's behavior. Oceanic observations are sparse and models are limited in accuracy, but taken together, one can form a quantitative description of the state of the ocean that is superior to any based on either models or data alone. Along with the goal of analysis and prediction, we seek reliable estimates of the errors in our results. We expect our results to have implications beyond data assimilation. In particular, we hope this research will lead to enhanced understanding of the implications of nonlinearity and randomness for predictability of the ocean and atmosphere. To this end, we include among our long term goals the assessment of sensitivity of models to errors in initial and boundary conditions. The principal objective of this project is the development, implementation and validation of practical data assimilation methods for synoptic ocean models. By "data assimilation" we mean the construction of a composite estimate of the state of the ocean based on a combination of observed data with computational model output. Since data assimilation methods which give the most and best information are highly resource intensive, and often not practical for use with detailed models, we are particularly interested in the price paid in terms of accuracy and confidence for using economical but suboptimal data assimilation methods. Optimized methods require accurate knowledge of the statistics of the errors in the model and the data. It is therefore an objective to understand in detail the sensitivity of the data assimilation scheme to the details of the defining error estimates.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1998
- Accession Number
- ADA541576
Entities
People
- Robert N. Miller
Organizations
- Oregon State University