III: Risk Management
17
Robustness đ§
Climate Risk Assessment and Management
Welcome đŻ
About this book
License
Contributing
Citing
Further Reading
Preface
I: Foundations
1
Climate science đ§
2
Probability and inference âď¸
3
Machine learning and nonparametric methods đ§
4
Correlation and dimensionality đ§
5
Model validation and comparison đ§
II: Hazard Assessment
6
Extreme value theory âď¸
7
Downscaling and Bias Correction đ§
8
Stochastic weather generators đ§
9
Physics-based models and calibration đ§
10
Optimal sampling methods đ§
11
Global sensitivity analysis đ§
III: Risk Management
12
Exposure and Vulnerability đ§
13
Cost-Benefit Analysis and Net Present Value đ§
14
Policy Search & Optimization đ§
15
Risk Transfer đ§
16
Deep Uncertainty and Model Structure đ§
17
Robustness đ§
18
Adaptive Planning and Flexibility đ§
19
Working with People: Values, Participation, and Communication đ§
Computational Case Studies
Overview
Understanding probability distributions âď¸
Inference Example: Flipping a Coin âď¸
Linear regression: three perspectives on the same problem âď¸
Extreme Value Theory Examples âď¸
Mosquito bites and beer consumption: simulation-based inference âď¸
References
Appendices
A
Software Setup âď¸
B
Julia Learning Resources âď¸
C
Large Language Models (âAIâ) âď¸
III: Risk Management
17
Robustness đ§
17
Robustness đ§
16
Deep Uncertainty and Model Structure đ§
18
Adaptive Planning and Flexibility đ§