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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-157
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-157
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 09 Jul 2019

Development and technical paper | 09 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

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 Bin Cao et al.
  • Department of Geography and Environmental Studies, Carleton University, Ottawa, Canada

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA-5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for ten terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulation and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time-series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.

Bin Cao et al.
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Status: open (until 03 Sep 2019)
Status: open (until 03 Sep 2019)
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Bin Cao et al.
Model code and software

geocryology/globsim: GMDD Submission B. Cao, Xi. Quan, N. Brown, Ch. Molnar, Lu. Padilla, and S. Gruber https://doi.org/10.5281/zenodo.3237258

Bin Cao et al.
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Latest update: 20 Jul 2019
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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.
GlobSim is a tool for simulating land-surface processes and phenomena at point locations...
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