Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data

• DOI: 10.5194/essd-11-865-2019
• Publication Date: 2019-06-17T10:31:48Z
• Authors: Cécile B. Ménard; Richard Essery; Alan Barr; Paul Bartlett; Jeff Derry; Marie Dumont; Charles Fierz; Hyungjun Kim; Anna Kontu; Yves Lejeune; Danny Marks; Masashi Niwano; Mark Raleigh; Libo Wang; Nander Wever
• Keywords: Forcing (mathematics); Albedo (alchemy); Reference data

Abstract. This paper describes in situ meteorological forcing and evaluation data, bias-corrected reanalysis for cold regions' modelling at 10 sites. The long-term datasets (one maritime, one arctic, three boreal, five mid-latitude alpine) are the reference sites chosen evaluating models participating Earth System Model-Snow Model Intercomparison Project. Periods covered by data vary between 7 20 years of hourly with (snow depth, snow water equivalent, albedo, soil temperature, surface temperature) available varying temporal intervals. Thirty-year (1980–2010) time series have been extracted from a global gridded meteorology dataset (Global Soil Wetness Project Phase 3) grid cells containing sites, interpolated to 1 h steps bias-corrected. Although correction was applied all it most important mountain hundreds metres higher than elevations which uncorrected air temperatures were too high snowfall amounts low. discussion considers importance sharing identification errors how publication these contributes good practice, consistency, reproducibility geosciences. Supplement provides information on instrumentation, an estimate percentages missing values, gap-filling methods each site. It is hoped that will be used as benchmarks future model development their ease use availability help developers quantify uncertainties reduce errors. published repository PANGAEA https://doi.pangaea.de/10.1594/PANGAEA.897575.