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. The Tibetan Plateau (TP) region, often referred to as the ThirdPole, is the world's highest plateau and exerts a considerable influence onregional and global climate. The state of the snowpack over the TP is amajor research focus due to its great impact on the headwaters of a dozenmajor Asian rivers. While many studies have attempted to validateatmospheric reanalyses over the TP area in terms of temperature orprecipitation, there have been – remarkably – no studies aimed atsystematically comparing the snow depth or snow cover in global reanalyseswith satellite and in situ data. Yet, snow in reanalyses provides criticalsurface information for forecast systems from the medium to sub-seasonaltimescales. Here, snow depth and snow cover from four recent global reanalysis products, namely the European Centre forMedium-Range Weather Forecasts (ECMWF) ERA5 and ERA-Interim reanalyses, theJapanese 55-year Reanalysis (JRA-55) and the NASA Modern-Era Retrospective analysisfor Research and Applications (MERRA-2), areinter-compared over the TP region. The reanalyses are evaluatedagainst a set of 33 in situ station observations, as well as against theInteractive Multisensor Snow and Ice Mapping System (IMS) snow cover anda satellite microwave snow depth dataset. The high temporal correlationcoefficient (0.78) between the IMS snow cover and the in situ observationsprovides confidence in the station data despite the relative paucity ofin situ measurement sites and the harsh operating conditions. While several reanalyses show a systematic overestimation of the snowdepth or snow cover, the reanalyses that assimilate local in situobservations or IMS snow cover are better capable of representing theshallow, transient snowpack over the TP region. The latter point is clearlydemonstrated by examining the family of reanalyses from the ECMWF, of whichonly the older ERA-Interim assimilated IMS snow cover at high altitudes,while ERA5 did not consider IMS snow cover for high altitudes. We furthertested the sensitivity of the ERA5-Land model in offline experiments,assessing the impact of blown snow sublimation, snow cover to snow depthconversion and, more importantly, excessive snowfall. These results suggestthat excessive snowfall might be the primary factor for the largeoverestimation of snow depth and cover in ERA5 reanalysis. Pending asolution for this common model precipitation bias over the Himalayas and the TP,future snow reanalyses that optimally combine the use of satellite snowcover and in situ snow depth observations in the assimilation and analysiscycles have the potential to improve medium-range to sub-seasonal forecastsfor water resources applications.

Evaluation of snow depth and snow cover over the Tibetan Plateau in global reanalyses using in situ and satellite remote sensing observations