Atmosphere Ocean Science Friday Seminar

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Probabilistic Subseasonal-to-Seasonal Prediction of Sea Level Using Uncertainty-Permitting Machine Learning

Speaker: Andrew Brettin, CAOS

Location: Warren Weaver Hall 1314

Date: Friday, April 7, 2023, 4 p.m.

Synopsis:

Due to the chaotic dynamics of the Earth’s climate system, predictions of sea level on subseasonal-to-seasonal timescales (15-60 days) is challenging and remains an active area of research. Recent studies have focused on identifying “forecasts of opportunity”— initial conditions in the climate state that permit longer time horizons of high predictability. In this talk I will describe and explore a uncertainty-permitting machine learning based approach for forecasting sea level and identifying initial conditions conducive to high predictability. An ANN is trained on daily fields from the CESM2 large ensemble (LENS2) project using a maximum-likelihood based training loss to forecast not only a point estimate for sea level, but also an uncertainty range. I’ll show some preliminary predictions, some metrics for assessing the model’s predictions, and discuss drivers of high dynamic sea level predictability on subseasonal-to-seasonal timescales.