Abstract

Monitoring snow cover extent is now feasible using Earth Observation (EO) data together with reanalysis products (derived from earth system model and data assimilation) to infer climate change impacts. Temporal stability is essential but can be altered by the combination of multiple satellite sensors and their degradation, or by the assimilation of new observations at a certain period in the case of reanalysis. This study evaluates the stability of some longest satellite and reanalysis products (ERA5, 1950–2020, ERA5-Land, 1981–2020, and NOAA CDR, 1966–2020) by using 470 ground stations as reference data (1950–2020). Temporal stability is assessed with the time series of the annual bias in snow depth and snow cover duration of the products at the different stations. Results show that the assimilation of new observations in ERA5 improved significantly its accuracy during the recent years (2005–2020) but introduced three negative step discontinuities starting in 1980, 1992, 2004. By contrast, ERA5-Land is more stable due to the lack of data assimilation, but at expense of worsening its accuracy despite having a finer spatial resolution. In the NOAA CDR, the increasing number of satellite data used introduces a positive trend since 1990–1995 that leads to artificial recovery of snow cover in fall and winter. The magnitude of most of these artificial trends/discontinuities is larger than actual snow cover trends and Global Climate Observing System (GCOS) stability requirements. The stability challenge of reanalysis products is linked to the assimilation of new observations to improve their accuracy or extend their temporal coverage. The study also updates snow trends (1950–2020) over local sites in the North Hemisphere (NH) corroborating the retreat of snow cover, driven mainly by an earlier melt and recently by a later snow onset. In warmer regions such as Europe, snow cover decrease is aggravated by a decreasing snow depth due to less snowfall, while in drier regions such as Russia snow cover retreats despite the increasing snow depth observed.

Highlights

  • Ground snow cover plays a very important role in the climate system due to its high albedo, thermal insulation and contribution to soil moisture and runoff, has been defined as an essential climate variable (ECV) by the Global Climate Observing System (GCOS)(GCOS, 2016)

  • The goal of this study is to evaluate the temporal stability of ERA5, ERA5-Land and National Oceanic and Atmospheric Administration (NOAA) Climate Data Records (CDRs), which are some of the 70 snow products with the longest temporal coverage

  • This study evaluates the temporal stability of ERA5 (1950-2020), ERA5-Land (1981-2020) and NOAA CDR (1968-2020) for analyzing snow trends

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Summary

Introduction

Ground snow cover plays a very important role in the climate system due to its high albedo, thermal insulation and contribution to soil moisture and runoff, has been defined as an essential climate variable (ECV) by the Global Climate Observing System (GCOS)(GCOS, 2016). Global reanalyses appear as an increasingly appealing option for climate studies due to their long-term global coverage of multiple atmospheric, land and ocean variables They provide estimations of most snow parameters such as snowfall, snowmelt, 55 snow mass and snow cover. The latest generation of global reanalysis includes ERA5 (1950-present) from the Copernicus Climate Change Service (C3S) (Albergel et al, 2018), MERRA-2 (1980-present) from NASA (Gelaro et al, 2017) and JRA55 (1953-present) from the Japanese Meteorological Agency (JMA)(Kobayashi et al, 2015) They mainly differ in their spatial resolution, the complexity of their snow schemes (Krinner et al, 2018), and the amount and type of observations assimilated. Global reanalyses are generally available since the start of the satellite era or before, 65 but the amount and type of data assimilated changes temporally (Mudryk et al, 2015) All these issues can introduce artificial trends or discontinuities in long-term satellite and reanalyses products. The study updates the 75 trends in SD, SCD, and NH SCE during the last 70 years

Snow products
ERA5-Land
NOAA CDR
In-situ snow measurements In situ snow daily observations were obtained from the
Spatial representativeness of in-situ snow observations
Validation of snow products
Validation metrics
Analysis of snow cover trends in the Northern Hemisphere
Spatial representativeness of in-situ snow measurements
ERA5 step-wise discontinuities
Conclusions
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