GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

Cao, Bin; Quan, Xiaojing; Brown, Nicholas; Stewart-Jones, Emilie; Gruber, Stephan

doi:https://doi.org/10.5194/gmd-12-4661-2019

Articles | Volume 12, issue 11

https://doi.org/10.5194/gmd-12-4661-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-12-4661-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 11

Development and technical paper

|

07 Nov 2019

Development and technical paper |

| 07 Nov 2019

GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

Bin Cao, Xiaojing Quan, Nicholas Brown, Emilie Stewart-Jones, and Stephan Gruber

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Final revised paper (published on 07 Nov 2019)
Preprint (discussion started on 09 Jul 2019)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Comments on “GlobSim (v1.0): Deriving meteorological time series for point locations from multiple global reanalyses”', Anonymous Referee #1, 03 Aug 2019
- SC2: 'Responses to RC1', Bin Cao, 28 Aug 2019
RC2: 'climate', Anonymous Referee #2, 05 Aug 2019
- SC1: '\textit{Interactive comment on} “GlobSim (v1.0): Deriving meteorological time series for point locations from multiple global reanalyses” \textit{by Bin Cao et al.}}', Bin Cao, 26 Aug 2019
AC1: 'Final response and revised manuscript with changes highlighted', Stephan Gruber, 12 Sep 2019

Peer-review completion

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

AR by Stephan Gruber on behalf of the Authors (12 Sep 2019) Author's response Manuscript

ED: Publish as is (24 Sep 2019) by David Lawrence

AR by Bin Cao on behalf of the Authors (28 Sep 2019) Manuscript

Short summary

GlobSim is a tool for simulating land-surface processes and phenomena at point locations globally, even where no site-specific meteorological observations exist. This is important because simulation can add insight to the analysis of observations or help in anticipating climate-change impacts and because site-specific simulation can help in model evaluation.