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UPCLIV Workshop - Plenary Discussion
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"Understanding and attributing historical climate variations and extremes"
A1 - What are the main hurdles in understanding and attributing historical climate variations, including extremes?
No responses yet for this question.
A2 - What steps can be taken to overcome these hurdles and model limitations?
No responses yet for this question.
A3 - Which climate model errors or limitations are most relevant in causing inconsistencies between observed and simulated changes and variations?
No responses yet for this question.
A4 - How can improvements in high-resolution regional climate modeling
enhance our ability to accurately represent local extremes and
hydroclimatic variability?
No responses yet for this question.
"Forecast evaluation (extremes, anomalies, trends, windows of opportunity)"
B1 - Which recent progress in forecast evaluation do you find most exciting? Why?
No responses yet for this question.
B2 - Do you think AI/ML can help with forecast evaluation? How?
No responses yet for this question.
B3 - How can we assess forecasts of extremes? What’s required? Which extremes are most appropriate?
No responses yet for this question.
B4 - To what extent do our evaluation efforts meet user needs?
No responses yet for this question.
B5 - What improvements in observational networks or reanalysis products are
most needed to better capture the onset and evolution of climate
extremes?
No responses yet for this question.
“New methods in prediction (modelling, initialization, AI/ML, post-processing)”
C1 - What are the most promising new methods for advancing annual to multidecadal climate prediction?
No responses yet for this question.
C2 - How can we prioritize different new methods (AI/ML, process constraints, improved model physics, initialization, resolution, etc.)?
No responses yet for this question.
C3 - Can we, and should we, develop a unified evaluation framework for such diverse prediction methods ?
No responses yet for this question.
C4 - Do you expect any significant breakthroughs in predictive skill from AI-based predictions? In which forecast horizon?
No responses yet for this question.
C5 - How can hybrid approaches that combine physical climate models and AI
improve the robustness and interpretability of future climate
predictions?
No responses yet for this question.
“Mechanisms underlying predictability and their representation in forecast systems”
D1 - What do you consider to be the most effective strategy for overcoming the current limitations in representing the key mechanisms underpinning climate predictability?
No responses yet for this question.
D3 - Could models with higher resolution simulate more realistically the physical processes that are key to skillful predictions? If applicable, please provide a brief argument.
No responses yet for this question.
D4 - What do you think that may be the dominant cause of the signal-to-noise (S2N) problem?
No responses yet for this question.
D5 - Are current state-of-the-art predictions close to the predictability limit?
No responses yet for this question.
D6 - How can hybrid AI–physics approaches help identify and correct systematic biases that currently limit climate prediction skill?
No responses yet for this question.
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