Day 4

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Paper title Fitness of satellite and reanalysis products to monitor the snow-albedo feedback
  1. Ruben Urraca European Commission - Joint Research Centre (JRC) Speaker
  2. Nadine Gobron EC-JRC
Form of presentation Poster
  • A5. Climate
    • A5.02 The role of Earth Observation in climate services
Abstract text An accurate monitoring of the snow-albedo feedback is essential for understanding the effects of climate change in snow-covered regions. The IPCC’s Sixth Assessment Report (AR6) established that a surface albedo feedback in the range of +0.35 [0.10 to 0.60] Wm-2C-1 is very likely [1]. The main component of this feedback is the so-called snow/ice-albedo feedback, which until AR5 was analyzed independently. AR6 included as well temperature-induced albedo changes over snow-free surfaces. Snow/ice-albedo feedback has been generally monitored with global climate models (GCMs). The increasing availability of satellite observations provides new opportunities to reduce the uncertainty in the snow-albedo feedback estimates, and also to improve its understanding by separating the contribution of ice and snow, and within snow, by separating the contribution of snow cover retreat and snow metamorphosis [2]. Indeed, observations are being increasingly used either to constrain GCMs [1], or to estimate the snow albedo feedback directly from multi-decadal observations [3].

Two types of observational products are currently being used: satellite-based products and global reanalyses. However, both face stability challenges that need to be quantified to understand the uncertainty of the snow-albedo feedback estimates obtained. Satellite products concatenate different sensors (e.g., C3S albedo) or different versions of the same sensor (e.g., AVHRR, VGT), which can introduce discontinuities during the transition periods. For each sensor, orbital drifts and instrument degradation are also a problem. Additional instabilities are added by the retrieval algorithm and the snow mask used. Besides, the uncertainty of albedo retrievals increases over snow due to the highly anisotropic reflectance of snow and the generally low solar angles during snow albedo retrievals.

Stability issues in reanalysis are related to the addition of new observations (satellite or ground) into the data assimilation system. Reanalyses face a trade-off between accuracy and stability that depends on the weight they give to new observations. NWP initialization applications require more accurate estimations that are obtained by weighting more recent observations, which generally introduces temporal instabilities in the long-term. By contrast, climate applications prefer stability over accuracy. Therefore, instabilities of different degrees can be present in reanalysis products based on the approach undertaken.

Our goal is to evaluate if the existing satellite and reanalysis products are fit for monitoring the snow-albedo feedback. The satellite products evaluated are MCD43C3 v6.1 (2000-present), CLARA-A2.1 (1982-present), GLAS-AVHRR v4 (1982-present), and C3S v2 (1982-present). The reanalyses evaluated are ERA5 (1950-present), ERA5-Land (1950-present), MERRA-2 (1982-present), and JRA-55 (1958-present). First, we evaluate if snow albedo values and trends from the different products are consistent globally. Then, we quantify how instabilities and incostinencies in multi-decadal albedo datasets propagate to the snow-albedo feedback estimates. For that, we generate an independent estimate of the snow-albedo feedback from each product using a common radiative kernel [4]. Our final aim is to determine whether the existing products area accurate and stable enough, and to identify aspects that can be improved to reduce the uncertainty of snow-albedo feedback estimates.


[1] IPCC, Climate Change 2021: The Physical Science Basis Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte V, Zhai P, Pirani AS, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds.)]. Cambridge University Press. In Press.]
[2] Wegmann M, Dutra E, Jacobi HW, Zolina O. Spring snow albedo feedback over northern Eurasia: Comparing in situ measurements with reanalysis products. The Cryosphere 12, 1887-1898, 2018
[3] Xiao L, Che T, Chen L, Xie H, Dai L. Quantifying snow albedo radiative forcing and its feedback during 2003–2016. Remote Sensing 9, 883, 2017
[4] Pithan F, Mauritsen T. Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nature Geoscience 7, 181-184, 2014.