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Debiasing Coarse-Scale Climate Models Using Statistically consistent Neural Networks
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Debiasing Coarse-Scale Climate Models Using Statistically Consistent Neural Networks
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- 1 Intro
- 2 Debiasing Coarse-Scale Climate Models Using Statistically consistent Neural Networks
- 3 Catastrophe (CAT) modeling industry needs better models
- 4 Unresolved scales
- 5 Higher-resolution GCMs are not the solution
- 6 Overview of framework
- 7 Discrete representation of spatial scales
- 8 Properties of spherical wavelets
- 9 Climate datasets
- 10 Problem formulation
- 11 Cross-trained multi-model architecture
- 12 Strengths of the ML architecture
- 13 Statistics of reconstructed field
- 14 Conclusions
- 15 Statistics and physics-based loss functions
