Debiasing Coarse-Scale Climate Models Using Statistically Consistent Neural Networks

Debiasing Coarse-Scale Climate Models Using Statistically Consistent Neural Networks

Kavli Institute for Theoretical Physics via YouTube Direct link

Statistics of reconstructed field

13 of 15

13 of 15

Statistics of reconstructed field

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Classroom Contents

Debiasing Coarse-Scale Climate Models Using Statistically Consistent Neural Networks

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

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