A Module for Calibrating Impact Functions in the Climate Risk Modeling Platform CLIMADA

Abstract

Impact functions model the vulnerability of people and assets exposed to weather and climate hazards. Given probabilistic hazard event sets or weather forecasts, they enable the computation of associated risks or impacts, respectively. Because impact functions are difficult to determine on larger spatial and temporal scales of interest, they are often calibrated using hazard, exposure, and impact data from past events. We present a module for calibrating impact functions based on such data using established calibration techniques like Bayesian optimization. It is implemented as Python submodule climada.util.calibrate of the climate risk modeling platform CLIMADA (Aznar-Siguan et al., 2023), and fully integrates into its workflow.