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. This study uses daily observations and modern reanalyses in order to evaluatereanalysis products over northern Eurasia regarding the spring snow albedofeedback (SAF) during the period from 2000 to 2013. We used thestate-of-the-art reanalyses from ERA-Interim/Land and the Modern-EraRetrospective Analysis for Research and Applications version 2 (MERRA-2) aswell as an experimental set-up of ERA-Interim/Land with prescribed shortgrass as land cover to enhance the comparability with the station data whileunderlining the caveats of comparing in situ observations with gridded data.Snow depth statistics derived from daily station data are well reproduced inall three reanalyses. However day-to-day albedo variability is notably higherat the stations than for any reanalysis product. The ERA-Interim grass set-upshows improved performance when representing albedo variability and generatescomparable estimates for the snow albedo in spring. We find that modernreanalyses show a physically consistent representation of SAF, with realisticspatial patterns and area-averaged sensitivity estimates. However,station-based SAF values are significantly higher than in the reanalyses,which is mostly driven by the stronger contrast between snow and snow-freealbedo. Switching to grass-only vegetation in ERA-Interim/Land increases theSAF values up to the level of station-based estimates. We found nosignificant trend in the examined 14-year time series of SAF, but interannualchanges of about 0.5 % K −1 in both station-based and reanalysisestimates were derived. This interannual variability is primarily dominatedby the variability in the snowmelt sensitivity, which is correctly capturedin reanalysis products. Although modern reanalyses perform well for snowvariables, efforts should be made to improve the representation of dynamicalbedo changes.

Spring snow albedo feedback over northern Eurasia: Comparing in situ measurements with reanalysis products