Articles | Volume 13, issue 4
Geosci. Model Dev., 13, 1827–1843, 2020
https://doi.org/10.5194/gmd-13-1827-2020
Geosci. Model Dev., 13, 1827–1843, 2020
https://doi.org/10.5194/gmd-13-1827-2020

Model description paper 06 Apr 2020

Model description paper | 06 Apr 2020

TIER version 1.0: an open-source Topographically InformEd Regression (TIER) model to estimate spatial meteorological fields

Andrew J. Newman and Martyn P. Clark

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Status: closed
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Andrew Newman on behalf of the Authors (19 Dec 2019)  Author's response    Manuscript
ED: Publish as is (12 Feb 2020) by Richard Neale
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Short summary
This paper introduces the Topographically InformEd Regression (TIER) model, which uses terrain attributes to turn observations of precipitation and temperature into spatial maps. TIER allows our understanding of complex atmospheric processes such as terrain-enhanced precipitation to be modeled in a very simple way. TIER lets users change the model so they can experiment with different ways of making maps. A key conclusion is that small changes in TIER will change the final map.