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

Cécile B Ménard,Marie Dumont,Paul Bartlett,Richard Essery,Hyungjun Kim,Danny Marks,Masashi Niwano,Mark Raleigh,Jeff Derry,Nander Wever,Libo Wang,Charles Fierz,Yves Lejeune,Alan Barr,Anna Kontu

doi:10.5194/essd-11-865-2019

Abstract

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

Highlights

In the past decade, several long-term datasets aimed at providing high-quality continuous meteorological and evaluation data for cold regions modelling have been published (Table 1)
Earth system models (ESMs)-SnowMIP is closely aligned with the Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP; van den Hurk et al, 2016), which is a contribution to the Coupled Model Intercomparison Project Phase 6 (CMIP6), including global offline land model experiments with meteorological forcing data provided by the Global Soil Wetness Project Phase 3 (GSWP3; Kim, 2017)
Successive IPCC reports have noted that Earth system models (ESMs) often underestimate soil temperatures at high latitudes (Randall et al, 2007; Flato et al, 2013; Koven et al, 2013), having implications on assessing the permafrost carbon feedback, i.e. the amplification of surface warming from carbon emissions released by thawing permafrost

Summary

Introduction

Several long-term datasets aimed at providing high-quality continuous meteorological and evaluation data for cold regions modelling have been published (Table 1). The importance of such datasets is twofold. We describe 10 long-term datasets (Table 1) from reference sites chosen to force and to evaluate models participating in the Earth System Model-Snow Model Intercomparison Project (ESM-SnowMIP) (Krinner et al, 2018), an international coordinated modelling effort that investigates snow schemes. ESM-SnowMIP is closely aligned with the Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP; van den Hurk et al, 2016), which is a contribution to the Coupled Model Intercomparison Project Phase 6 (CMIP6), including global offline land model experiments with meteorological forcing data provided by the Global Soil Wetness Project Phase 3 (GSWP3; Kim, 2017). Previous iterations of SnowMIP have provided 19 site years of data from four sites in SnowMIP1 (Essery and Etchevers, 2004) and 9 site years of data from five sites in SnowMIP2 (Essery et al, 2009; Rutter et al, 2009); ESMSnowMIP totals 136 site years of in situ data from 10 sites and 300 site years derived from GSWP3

Results

Discussion

Conclusion