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

Dorheim, Kalyn; Smith, Steven J.; Bond-Lamberty, Ben

doi:https://doi.org/10.5194/gmd-14-365-2021

Articles | Volume 14, issue 1

https://doi.org/10.5194/gmd-14-365-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-14-365-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 1

Model description paper

|

22 Jan 2021

Model description paper |

| 22 Jan 2021

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

Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty

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Final revised paper (published on 22 Jan 2021)
Preprint (discussion started on 27 Apr 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of Dorheim et al.', Ben Kravitz, 01 May 2020
- AC1: 'Response to RC1', Kalyn Dorheim, 02 Sep 2020
RC2: 'Review comment on gmd-2020-33', Kuno Strassmann, 29 May 2020
- AC2: 'Response to RC2', Kalyn Dorheim, 02 Sep 2020
RC3: 'Review of HIRM v1.0', Anonymous Referee #3, 01 Jul 2020
- AC3: 'Response to RC3', Kalyn Dorheim, 02 Sep 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Svenja Lange on behalf of the Authors (04 Nov 2020) Author's response

ED: Referee Nomination & Report Request started (05 Nov 2020) by Juan Antonio Añel

RR by Ben Kravitz (05 Nov 2020)

RR by Anonymous Referee #3 (23 Nov 2020)

ED: Publish subject to technical corrections (26 Nov 2020) by Juan Antonio Añel

AR by Kalyn Dorheim on behalf of the Authors (01 Dec 2020) Author's response Manuscript

Short summary

Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.