Statistical and Applied Mathematical Sciences Institute
19 T. W. Alexander Drive
P.O. Box 14006
Research Triangle Park, NC 27709-4006
Tel: 919.685.9350 FAX: 919.685.9360
[email protected]

SAMSI course on 

"Data Assimilation Methods for the Ocean and Atmosphere"

Instructor:

Kayo Ide, Department of Atmospheric and Ocean Sciences - University of California, Los Angeles

Class Time:  Tuesdays, 4:30-7:00pm

Class Location:  NISS Building, Room 104 (directions)

Class begins January 18, 2005

University Listings

Duke                     STA 294.02

NC State               MA (ST) 810J.006

UNC                     MATH 261.001

COURSE DESCRIPTION

Data assimilation provides a way to combine the models and observations effectively for the estimation of the present state of the ocean and atmosphere. It also forms a basis for the forecast of the future and re-analysis of the past. Data assimilation is a subject that requires a balanced understanding of statistics and applied mathematics as well as the relevant geophysical systems. This course introduces the concepts of data assimilation derived in the context of estimation theory and covers a variety of methods for numerical weather prediction and ocean forecasting, such as optimal interpolation, Kalman-filtering and variational based methods. Advanced topics and the state-of-art data assimilation systems will also be discussed.

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