Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Computational Methods in Ice-sheet Modeling - Uncertainty Quantification and Optimization

Society for Industrial and Applied Mathematics via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore computational methods for ice-sheet modeling in this webinar from the SIAM Activity Group on Mathematics of Planet Earth. Delve into state-of-the-art techniques for calibrating Greenland and Antarctic ice sheet models through high-dimensional parameter inversion. Learn about the critical role of ice sheet mass loss in global sea level rise and the importance of accurate modeling for future projections. Discover how large-scale PDE-constrained optimization and Bayesian inference are applied to approximate parameter distributions efficiently. Examine a case study on the Humboldt Glacier in Greenland, focusing on how basal friction parameter uncertainties affect mass loss predictions. Gain insights into multi-fidelity methods that significantly reduce computational costs in estimating glacier mass change statistics. The webinar concludes with a Q&A session, offering further exploration of applied mathematics in environmental science, sustainability, and climate policy.

Syllabus

Introduction
Webinar
Q&A

Taught by

Society for Industrial and Applied Mathematics

Reviews

Start your review of Computational Methods in Ice-sheet Modeling - Uncertainty Quantification and Optimization

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.