Articles | Volume 11, issue 2
https://doi.org/10.5194/essd-11-865-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-11-865-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data
School of Geosciences, University of Edinburgh, Edinburgh, UK
Richard Essery
School of Geosciences, University of Edinburgh, Edinburgh, UK
Alan Barr
Global Institute for Water Security, University of Saskatchewan, Saskatoon, Canada
Climate Research Division, Environment and Climate Change Canada, Toronto, Canada
Paul Bartlett
Climate Research Division, Environment and Climate Change Canada, Toronto, Canada
Jeff Derry
Center for Snow and Avalanche Studies, Silverton, Colorado, USA
Marie Dumont
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, France
Charles Fierz
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Hyungjun Kim
Institute of Industrial Science, University of Tokyo, Tokyo, Japan
Anna Kontu
Finnish Meteorological Institute, Space and Earth Observation Centre, Sodankylä, Finland
Yves Lejeune
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre d'Etudes de la Neige, Grenoble, France
Danny Marks
Northwest Watershed Research Center, Agricultural Research Service, Boise, Idaho, USA
Masashi Niwano
Climate Research Department, Meteorological Research Institute, Tsukuba, Japan
Mark Raleigh
National Snow and Ice Data Center (NSIDC), University of Colorado Boulder, Boulder, Colorado, USA
Libo Wang
Climate Research Division, Environment and Climate Change Canada, Toronto, Canada
Nander Wever
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA
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Short summary
This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
This paper describes long-term meteorological and evaluation datasets from 10 reference sites...
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