Reproducing complex simulations of economic impacts of climatechange with lower-cost emulators

Abstract. In order to project climate-change impacts under a wide-range of scenarios or conduct on-line coupled simulations, the computational and implementation cost of economic impact calculations should be reduced. To do so, in this study, we developed various emulators that mimic simulation outputs, namely economic models coupled with bio/physical process-based impact models. Their performance was evaluated for multiple sectors and regions. Among the tested emulators, those composed of artificial neural networks, which can incorporate nonlinearities and interactions between variables, performed better particularly when finer input variables were available. Although simple functional forms were effective for approximating general tendencies, complex emulators are necessary if the focus is regional or sectoral heterogeneity. The developed emulators could be used to explore future scenarios related to climate-change policies, and the findings of this study could also help researchers design their own emulators under different situations.