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

Conclusions

14 of 15

14 of 15

Conclusions

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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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