Abstract
Abstract. Simple climate models (SCMs) are frequently used in research and decision-making communities because of their flexibility, tractability, and low computational cost. SCMs can be idealized, flexibly representing major climate dynamics as impulse response functions, or process-based, using explicit equations to model possibly nonlinear climate and Earth system dynamics. Each of these approaches has strengths and limitations. Here we present and test a hybrid impulse response modeling framework (HIRM) that combines the strengths of process-based SCMs in an idealized impulse response model, with HIRM's input derived from the output of a process-based model. This structure enables the model to capture some of the major nonlinear dynamics that occur in complex climate models as greenhouse gas emissions transform to atmospheric concentration to radiative forcing to climate change. As a test, the HIRM framework was configured to emulate the total temperature of the simple climate model Hector 2.0 under the four Representative Concentration Pathways and the temperature response of an abrupt 4 times CO2 concentration step. HIRM was able to reproduce near-term and long-term Hector global temperature with a high degree of fidelity. Additionally, we conducted two case studies to demonstrate potential applications for this hybrid model: examining the effect of aerosol forcing uncertainty on global temperature and incorporating more process-based representations of black carbon into a SCM. The open-source HIRM framework has a range of applications including complex climate model emulation, uncertainty analyses of radiative forcing, attribution studies, and climate model development.
Highlights
Climate models encompass a diverse collection of approaches to representing Earth system processes at various levels of complexity and resolution
In this paper we document and test hybrid impulse response modeling framework (HIRM), a framework that leverages the nonlinear dynamics of process-based Simplified Climate Models (SCMs) within a computationally efficient, highly idealized linear impulse response model
While other IRF-based models have incorporated nonlinear dynamics using a number of approaches (Hooss et al, 2001; Millar et al, 2017, ADD), HIRM is able to demonstrate nonlinear dynamics through its use of exogenous forcing inputs from Hector
Summary
Climate models encompass a diverse collection of approaches to representing Earth system processes at various levels of complexity and resolution. The most complex are the Earth System Models (ESMs): highly detailed representations of the physical, chemical, and biological processes governing the Earth system at high spatial and temporal resolution (Hurrell et al, 2013). These models are computationally expensive and can only be run for a limited number of scenarios. In this paper we document and demonstrate a highly idealized IRF-based framework This modeling framework is configured using output from a process-based model to capture nonlinear and complex climate dynamics, we refer to it as a hybrid impulse response modeling (HIRM) framework. We discuss the implications of these results and potential future uses of this framework
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