Designing Optimal Sampling Networks, Fixed and Adaptive for Ocean Forecast Modeling
Abstract
LONG TERM GOAL. The overall long term goal is to develop innovative, practical and efficient methodologies for the design of fixed and adaptive oceanic platforms, eulerian and lagrangian, such as fixed moorings, profiling moorings, gliders, drifters, AUVs. OBJECTIVES. The main objective is to develop this methodology for the Gulf of Maine/Georges Bank (GM/GB) region where an integrated model system has been developed at the University of Massachusetts at Dartmouth centered around the Finite- Volume Coastal Ocean circulation Model (FVCOM). APPROACH. The technical approach will be to test the available data assimilation packages, i.e. Reduced Rank Kalman Filter (RRKF); Ensemble Kalman Filter (EnKF); Ensemble Square Root Kalman Filter (EnSRF) and the Ensemble Transform Kalman Filter (ETKF) in the idealized test-cases outlined in the report. Successively, the filters will be adapted to FVCOM in the GM/GB configuration for coastal circulation prediction and adaptive sampling studies.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2007
- Accession Number
- ADA605552
Entities
People
- Paola Rizzoli
Organizations
- Massachusetts Institute of Technology