HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses
<p>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 exp...
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doaj-f29c3a0d5beb46ad8f929e6fa2453ec22021-01-22T12:44:38ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032021-01-011436537510.5194/gmd-14-365-2021HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analysesK. DorheimS. J. SmithB. Bond-Lamberty<p>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 CO<span class="inline-formula"><sub>2</sub></span> 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.</p>https://gmd.copernicus.org/articles/14/365/2021/gmd-14-365-2021.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
K. Dorheim S. J. Smith B. Bond-Lamberty |
spellingShingle |
K. Dorheim S. J. Smith B. Bond-Lamberty HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses Geoscientific Model Development |
author_facet |
K. Dorheim S. J. Smith B. Bond-Lamberty |
author_sort |
K. Dorheim |
title |
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses |
title_short |
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses |
title_full |
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses |
title_fullStr |
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses |
title_full_unstemmed |
HIRM v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses |
title_sort |
hirm v1.0: a hybrid impulse response model for climate modeling and uncertainty analyses |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2021-01-01 |
description |
<p>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 CO<span class="inline-formula"><sub>2</sub></span> 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.</p> |
url |
https://gmd.copernicus.org/articles/14/365/2021/gmd-14-365-2021.pdf |
work_keys_str_mv |
AT kdorheim hirmv10ahybridimpulseresponsemodelforclimatemodelinganduncertaintyanalyses AT sjsmith hirmv10ahybridimpulseresponsemodelforclimatemodelinganduncertaintyanalyses AT bbondlamberty hirmv10ahybridimpulseresponsemodelforclimatemodelinganduncertaintyanalyses |
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