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Earth System Models (ESMs) are essential for understanding the dynamics of our climate system, but their computational costs make nuanced investigations of future climatic conditions difficult. Using statistical techniques, computationally efficient tools known as emulators, which mimic ESM simulations, can be built. Emulators allow to (i) project the regional climate change for a broad variety of emission scenarios and to (ii) thoroughly sample the uncertainty space associated with natural variability as well as structural model uncertainties. Both tasks would be computationally infeasible with actual ESMs. In this contribution, we introduce a probabilistic, bivariate ESM emulation framework that produces joint monthly spatial fields of temperature and precipitation for a given global mean temperature trajectory. This contribution adds to the existing modular MESMER framework developed by Beusch et al. (2020). The building blocks of the new emulator are: (i) A module for approximating the annual global mean temperature trajectory from ESM output. This module is adapted from the existing MESMER framework. (ii) A module capturing the deterministic local response of monthly temperature and precipitation to global mean temperature. The response function is assumed to be linear with coefficients fitted independently for each month, grid-cell and variable. (iii) A module capturing the residual variability, that follows a probabilistic, non-parametric approach to reproduce spatial and temporal variance, covariance and cross-covariance structures of both variables. The emulator is trained and tested on ESM ensembles generated during CMIP6. Near-term development steps include the quantification of inter-ESM differences through the trained parameters and the coupling of the emulator to the simple climate model MAGICC (Meinshausen et al., 2020) to explore the emission scenario space. Beusch, Lea, Lukas Gudmundsson, and Sonia I. Seneviratne. "Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land." Earth System Dynamics 11.1 (2020): 139-159.Meinshausen, Malte, et al. "The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500." Geoscientific Model Development 13.8 (2020): 3571-3605. |
