Multi-physics ensemble snow modelling in the western Himalaya

Pritchard, David M. W.; Forsythe, Nathan; O'Donnell, Greg; Fowler, Hayley J.; Rutter, Nick

doi:https://doi.org/10.5194/tc-14-1225-2020

Articles | Volume 14, issue 4

https://doi.org/10.5194/tc-14-1225-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-14-1225-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 4

Research article

|

14 Apr 2020

Research article |

| 14 Apr 2020

Multi-physics ensemble snow modelling in the western Himalaya

David M. W. Pritchard, Nathan Forsythe, Greg O'Donnell, Hayley J. Fowler, and Nick Rutter

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Final revised paper (published on 14 Apr 2020)
Supplement to the final revised paper
Preprint (discussion started on 10 Sep 2019)
Supplement to the preprint

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review', Matthieu Lafaysse, 14 Oct 2019
- AC1: 'Author response to RC1 and RC2', David Pritchard, 20 Jan 2020
RC2: 'Review', Anonymous Referee #2, 04 Dec 2019
- AC1: 'Author response to RC1 and RC2', David Pritchard, 20 Jan 2020

Peer-review completion

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

ED: Publish subject to minor revisions (review by editor) (14 Feb 2020) by Marie Dumont

AR by Svenja Lange on behalf of the Authors (06 Mar 2020) Author's response Manuscript

ED: Publish subject to technical corrections (10 Mar 2020) by Marie Dumont

Short summary

This study compares different snowpack model configurations applied in the western Himalaya. The results show how even sparse local observations can help to delineate climate input errors from model structure errors, which provides insights into model performance variation. The results also show how interactions between processes affect sensitivities to climate variability in different model configurations, with implications for model selection in climate change projections.