This event is part of Confronting Global Climate Change View Details

Climate Model Evaluation and Uncertainty

Description

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Climate models are important tools for understanding past, current and future global climate variability, yet they exhibit key uncertainties that limit their applicability to fine scale analysis and future projections.  Some key sources of uncertainty include coarse grid resolution, inadequate representation of relevant physics and interactions, overfitting from downscaling and bias-correction, lack of observations to calibrate and evaluate models, uncertain model parameters, different model structures, and so on. In addition, coupled climate models are computationally expensive and thus difficult to use for uncertainty analysis, while reduced complexity models are fast and flexible but are highly parameterized and lack physics. These computational tradeoffs pose major challenges for evaluating/comparing model results, constructing reliable projections, and quantifying relevant uncertainties. The workshop will bring together researchers from multi-disciplinary fields to highlight new math/stat methods for climate model evaluation and uncertainty quantification across spatial and temporal scales, and to advance our understanding about the physical processes leading to model errors, biases, and uncertainty. 

This workshop will include a poster session. The form for submitting a poster proposal will be available below after registration.

Organizers

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B L
Bo Li University of Illinois at Urbana-Champaign
C P
Cristi Proistosescu University of Illinois at Urbana-Champaign
R S
Ryan Sriver University of Illinois at Urbana-Champaign

Speakers

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P C
Peter Craigmile Ohio State University
N D
Noah Diffenbaugh Stanford University
D H
Dorit Hammerling Colorado School of Mines
T H
Trevor Harris Texas A&M University
P H
Patrick Heimbach University of Texas at Austin
M K
Matthias Katzfuss Texas A&M University
L M
Linda Mearns UCAR
D N
Douglas Nychka Colorado School of Mines
S S
Steve Sain Jupiter Intelligence
G S
Gavin Schmidt NASA
T S
Tapio Schneider Caltech
C S
Chris Smith University of Leeds
C W
Chris Wikle University of Missouri

Poster Session

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The posters that have been submitted for the poster session are available on the poster session page.

Schedule

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Monday, September 19, 2022
9:25-9:30 CDT
Welcome Remarks
9:30-10:30 CDT
Ensemble Consistency Testing for the Community Earth System Model

Speaker: Dorit Hammerling (Colorado School of Mines)

10:30-11:00 CDT
Break
11:00-12:00 CDT
Non-Gaussian Emulation of Climate Models via Scalable Bayesian Transport Maps

Speaker: Matthias Katzfuss (Texas A&M University, College Station)

12:00-13:30 CDT
Lunch
13:30-14:30 CDT
Uncertainties in Regional Climate Modeling

Speaker: Linda Mearns (UCAR)

Tuesday, September 20, 2022
9:30-10:30 CDT
Downscaling for climate risk analytics

Speaker: Steve Sain (Jupiter Intelligence)

10:30-11:00 CDT
Break
11:00-12:00 CDT
Using data-driven predictions to constrain climate model uncertainty in the time remaining until critical global warming thresholds are reached

Speaker: Noah Diffenbaugh (Stanford University)

12:00-13:30 CDT
Lunch
13:30-15:00 CDT
Poster Session + Social Hour
Wednesday, September 21, 2022
9:30-10:30 CDT
Assessing derived variables and coherent structures in model simulations

Speaker: Doug Nychka (Colorado School of Mines)

10:30-11:00 CDT
Break
11:00-12:00 CDT
AI-Accelerated Climate Science and Prediction

Speaker: Tapio Schneider (Caltech)

12:00-13:30 CDT
Lunch
13:30-14:30 CDT
A combined estimate of global temperature time series and a comparison to climate models

Speaker: Peter F. Craigmile (The Ohio State University)

Thursday, September 22, 2022
9:30-10:30 CDT
Some structural issues in coupled climate model comparisons and evaluations

Speaker: Gavin Schmidt (NASA Goddard Institute for Space Studies)

10:30-11:00 CDT
Break
11:00-12:00 CDT
Learning from data through the lens of (ocean) models, surrogates, and their derivatives

Speaker: Patrick Heimbach (University of Texas, Austin)

12:00-13:30 CDT
Lunch
13:30-14:30 CDT
Reduced complexity climate models: status, applications and opportunities

Speaker: Chris Smith (University of Leeds)

Friday, September 23, 2022
9:30-10:30 CDT
Multi-model Ensemble Analysis with Neural Network Gaussian Processes

Speaker: Trevor Harris (University of Illinois at Urbana-Champaign)

10:30-11:00 CDT
Break
11:00-12:00 CDT
Data-Driven Discovery of Geophysical Dynamics with Uncertainty Quantification

Speaker: Chris Wikle (University of Missouri)


Videos

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Uncertainties in Regional Climate Modeling

Linda Mearns
September 19, 2022

Downscaling for climate risk analytics

Steve Sain
September 20, 2022

Using data-driven predictions to constrain climate model uncertainty in the time remaining until critical global warming thresholds are reached

Noah Diffenbaugh
September 20, 2022

Assessing derived variables and coherent structures in model simulations

Doug Nychka
September 21, 2022

AI-Accelerated Climate Science and Prediction

Tapio Schneider
September 21, 2022

A combined estimate of global temperature time series and a comparison to climate models

Peter F. Craigmile
September 21, 2022

Some structural issues in coupled climate model comparisons and evaluations

Gavin Schmidt
September 22, 2022

Learning from data through the lens of (ocean) models, surrogates, and their derivatives

Patrick Heimbach
September 22, 2022

Reduced complexity climate models: status, applications and opportunities

Chris Smith
September 22, 2022

Multi-model Ensemble Analysis with Neural Network Gaussian Processes

Trevor Harris
September 23, 2022

Data-Driven Discovery of Geophysical Dynamics with Uncertainty Quantification

Chris Wikle
September 23, 2022