Statistical Problems in Ocean Modeling and Prediction
UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES CENTER FOR APPLIED MATHEMATICAL SCIENCES
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My project addresses statistical and stochastic problems in the following fields Lagrangian prediction and Lagrangian data assimilation 1, estimating transport and mixing parameters from tracer observations 2, and ocean model validation 3. The long range scientific goals of this study comprise determining limits of predictability for Lagrangian motion in semi-enclosed seas and littoral zones on time scales of days and weeks, estimating mixing and transport parameters in the upper ocean to improve performance of numerical models , and constructing statistical tests for model validation based on realistic confidence intervals for estimated mean fields and appropriate quantitative misfit measures.
- Physical and Dynamic Oceanography
- Statistics and Probability