A locally time-invariant metric for climate model ensemble predictions of extreme risk
This work addresses limitations in climate model ensemble weighting for high-impact extreme events, which is crucial for adaptation planning, though it appears incremental as it builds on existing evaluation methods.
The authors tackled the problem of evaluating climate model simulations for extreme events by introducing a locally time-invariant method, which they applied to predict extreme heat days in Nairobi and eight other cities, showing comparative results.
Adaptation-relevant predictions of climate change are often derived by combining climate model simulations in a multi-model ensemble. Model evaluation methods used in performance-based ensemble weighting schemes have limitations in the context of high-impact extreme events. We introduce a locally time-invariant method for evaluating climate model simulations with a focus on assessing the simulation of extremes. We explore the behaviour of the proposed method in predicting extreme heat days in Nairobi and provide comparative results for eight additional cities.