Explainability, uncertainty & physics

Trustworthy Artificial Intelligence for Environmental Sciences: An Innovative Approach for Summer School

Amy McGovern, David John Gagne, Christopher D. Wirz, Imme Ebert‐Uphoff, Ann Bostrom, Yuhan Douglas Rao, Andrea Schumacher, Montgomery L. Flora, Randy J. Chase, Antonios Mamalakis, Marie C. McGraw, Ryan Lagerquist et al.

Bulletin of the American Meteorological Society · 14 April 2023 · NOAA (incl. GFDL, PSL, GSL, NCEP/EMC), NSF NCAR / UCAR, University of Washington, Colorado State University (incl. CIRA), University of Oklahoma (AI2ES)

Paper

In one sentence. Describes an AI2ES summer school teaching trustworthy and explainable AI for severe storms, tropical cyclones and space weather to 677 participants.

Labels

Topic

Explainability, uncertainty & physics, Benchmarks, datasets & evaluation

Type

Position or perspective paper

Method

Other

Data

Other

Status

Research

Identifiers

DOI:10.1175/bams-d-22-0225.1 OpenAlex:W4365508948

Added

2026-10-22

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