Showcasing MESMER‐X: Spatially Resolved Emulation of Annual Maximum Temperatures of Earth System Models. Issue 17 (30th August 2022)

• Record Type: Journal Article
• Authors: Quilcaille, Y.; Gudmundsson, L.; Beusch, L.; Hauser, M.; Seneviratne, S. I.
• Is Part Of: Geophysical research letters. Volume 49:Issue 17(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-30
• Subjects: climate extremes -- emulation -- modeling -- scenarios -- earth system -- climate change; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2022GL099012
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Emulators of Earth System Models (ESMs) are complementary to ESMs by providing climate information at lower computational costs. Thus far, the emulation of spatially resolved climate extremes has only received limited attention, even though extreme events are one of the most impactful aspects of climate change. Here, we propose a method for the emulation of local annual maximum temperatures, with a focus on reproducing essential statistical properties such as correlations in space and time. We test different emulator configurations and find that driving the emulations with global mean surface temperature offers an optimal compromise between model complexity and performance. We show that the emulations can mimic the temporal evolution and spatial patterns of the underlying climate model simulations and are able to reproduce their natural variability. The general design and the good performance for annual maximum temperatures suggest that the proposed methodology can be applied to other climate extremes. Plain Language Summary: Climate models are invaluable tools for studying climate change but take a very long time to run, even on modern supercomputers. Emulators of climate models are statistical tools that can be calibrated to mimic the behavior of complex climate models with a much lower computational demand. However, they are typically not designed to reproduce climate extremes, despite the fact that extreme climate events belong to the most impactful aspects of climate change. In this study, we propose a method for the emulation of annual maximum temperature in time and space. This method also reproduces the natural variability of climate models, even though it is driven only by global mean surface temperature. We show that the resulting emulations are very similar to the data created by climate models. In an example application, we use the emulator to examine the extreme temperatures for different climate scenarios. Key Points: We present a method for the emulation of spatially resolved annual maximum temperatures from Earth System Models The emulator reproduces statistical properties and correlations in space and time and can be extended to other extreme indicators The method exhibits good performance for annual maximum temperatures