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Linear Inverse Modeling

PI: James Scott
Institution: NOAA
Abstract:
Oceanic processes, including tropical and extratropical Rossby waves, seasonally dependent ocean mixing and fluctuations in the subtropical cell, and interactions with the atmosphere, result in variability that evolves over seasonal and longer time scales. Our knowledge of these processes, combined with advances in numerical and statistical models, have enabled skillful forecasts of some aspects of the Pacific climate system, primarily those associated with El Nino/Southern Oscillation (ENSO). However, the level of skill from statistical models can likely be improved, especially in the extratropics. Furthermore information from forecasts can be used to identify model errors and the processes that determine predictability. We plan to use statistical models trained on sea surface temperature (SST) data, ocean assimilation products and coupled general circulation model, experiments (CGCMs) to forecast upper ocean variables in the tropical and north Pacific Ocean on a seasonal basis for up to one year in the future.
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