Development and Stakeholder-informed Evaluation of Global Climate Temperature Response Functions

Abstract

Modern climate models allow for accurate simulation over a range of future climate scenarios. However, there exists a significant gap in terms of speed, accuracy, and overall intuitiveness between the stateof-the-art and more generally accessible tools, especially in tools used for climate education. Climate emulators provide a potential closure for this gap, and a significant body of work has shown their efficacy in providing a relatively lightweight method to reproduce the results of full-scale Earth System Models. In this thesis, I demonstrate a novel methodology for climate emulation based on the response of the climate system to effective radiative forcing (ERF). While previous work has demonstrated the efficacy of impulse response functions as a tool for climate emulation, critically, these methods are largely nongeneralizable to new scenarios and are inaccessible to more general audiences. To remedy this, we present a general framework for integrating stakeholder analysis into the model development process to ensure all key stakeholder needs are identified and met at each step of development. This framework is then applied in the context of climate emulator development, showcasing how this integrated stakeholder analysis is able to increase emulator salience, credibility, and legitimacy for our target audience. We present results from an application to near-surface air temperature based on ERF and temperature data taken from experiments in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). We evaluate the emulator using additional experiments taken from the CMIP6 archive, including the Shared Socioeconomic Pathways (SSPs), demonstrating accurate emulation of global mean and spatially resolved temperature change with respect to the outputs of the CMIP6 ensemble. Global absolute error in predicted temperature averages 0.25◦C with a bias ranging from-0.14 to-0.04◦C. In addition, the comprehensive stakeholder analysis performed as a part of the development process affords the emulator ease of use and interpretability in its outputs while meeting all key stakeholder requirements. While it is unable to capture state-dependent climate feedbacks, such as the non-linear effects of Arctic sea ice melt in high-warming scenarios, our results show that the emulator is generalizable to any scenario independent of the specific forcings present.