An estimate of the state of the ocean, a deep dive into the Bayesian decision theory, and how enables us to fuse available data with prior knowledge, are some of the topics covered by this lecture series led by UCLA college scholar Michael Rescorla .

This is a three-session lecture organized by the EELISA Community “Protecting European Waters”

PROGRAM

Lecture 1: Ocean state estimation (2 hours). – June 2, 2022

Estimating the state of the ocean is vital for numerous scientific and commercial purposes. The ocean state estimation problem is quite difficult for several reasons, including the enormous dimensionality of the state space along with the relative paucity of data. I highlight some key challenges posed by the estimation problem and analyze how it pervasively impacts our dealings with the ocean.

Lecture 2: Bayes and the Ocean: Foundations (2 hours) – June 9, 2022

Bayesian decision theory, a mathematical framework for modeling reasoning and decision-making under uncertain conditions, is widely used to tackle the ocean state estimation problem. I elucidate foundational aspects of the Bayesian approach. I then argue for its normative and practical superiority to rival frameworks.

Lecture 3: Bayes and the Ocean: Applications (2 hours) – June 16, 2022

I survey how contemporary oceanography uses Bayesian decision theory to estimate the ocean state. I focus on the ensemble Kalman filter as an exemplary application of the Bayesian framework. I discuss how the Bayesian framework enables us to fuse available data with prior knowledge (e.g. prior knowledge of ocean dynamics). I argue that the Bayesian framework underwrites empirically and pragmatically fruitful probabilistic representations of the ocean.

WHEN

June 2, 9 and 16, 2022 @15:30 PM – 17:30 PM (CETS, UTC+2)

FORMAT

Online

FOR WHOM?

Masters and Ph.D. students, Academics, Researchers, educators

REGISTRATION DEADLINE

May 31st

REGISTER HERE