A locally time-invariant metric for climate model ensemble predictions of extreme risk

• URL: http://arxiv.org/abs/2211.16367v3
• Date: Tue, 18 Apr 2023 16:48:12 GMT
• Title: A locally time-invariant metric for climate model ensemble predictions of extreme risk
• Authors: Mala Virdee, Markus Kaiser, Emily Shuckburgh, Carl Henrik Ek, Ieva Kazlauskaite
• Abstract summary: 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.
• Score: 8.347190888362194
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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