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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2020-33
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-33
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 27 Apr 2020

Submitted as: model description paper | 27 Apr 2020

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A revised version of this preprint is currently under review for the journal GMD.

HIRM v1.0: A hybrid impulse response model for climate modeling and uncertainty analyses

Kalyn Dorheim, Steven Smith, and Ben Bond-Lamberty Kalyn Dorheim et al.
  • Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD 20740, United States of America

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 allows it to capture the crucial nonlinear dynamics frequently encountered in going from greenhouse gas emissions to atmospheric concentration to radiative forcing to climate change. As a test, the HIRM framework was configured to emulate total temperature of the simple climate model Hector 2.0 under the four Representative Concentration Pathways and the temperature response of an abrupt four 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.

Kalyn Dorheim et al.

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Kalyn Dorheim et al.

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Code and Data for A hybrid impulse response model for climate modeling and uncertainty analyses K. Dorheim, S. J. Smith, and B. Bond-Lamberty https://doi.org/10.17605/OSF.IO/T3Q9Y

Model code and software

JGCRI/HIRM: Dorheim et al. 2020 submitted to GMD K. Dorheim, S. J. Smith, and B. Bond-Lamberty https://doi.org/10.5281/zenodo.3756122

Kalyn Dorheim et al.

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Latest update: 28 Sep 2020
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Short summary
Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. There are two types of simple climate models, idealized and processes based. In this paper we present a hybrid approach that combines the strength of both types of simple climate model into a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainty.
Simple climate models are frequently used in research and decision-making communities because of...
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