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Quantifying Snow Albedo Radiative Forcing and Its Feedback during 2003–2016

Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
University of Chinese Academy of Sciences, Beijing 100049, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China
Nansen Environmental and Remote Sensing Center, N-5006 Bergen, Norway
Laboratory for Remote Sensing and Geoinformatics, Department of Geological Sciences, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA
Jiangsu Center of Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Author to whom correspondence should be addressed.
Academic Editors: Yuei-An Liou, Jean-Pierre Barriot, Chung-Ru Ho, Yuriy Kuleshov, Chyi-Tyi Lee, Richard Müller and Prasad S. Thenkabail
Remote Sens. 2017, 9(9), 883;
Received: 26 June 2017 / Revised: 10 August 2017 / Accepted: 22 August 2017 / Published: 25 August 2017
(This article belongs to the Special Issue Earth Observations for Addressing Global Challenges)
PDF [1858 KB, uploaded 30 August 2017]


Snow albedo feedback is one of the most crucial feedback processes that control equilibrium climate sensitivity, which is a central parameter for better prediction of future climate change. However, persistent large discrepancies and uncertainties are found in snow albedo feedback estimations. Remotely sensed snow cover products, atmospheric reanalysis data and radiative kernel data are used in this study to quantify snow albedo radiative forcing and its feedback on both hemispheric and global scales during 2003–2016. The strongest snow albedo radiative forcing is located north of 30°N, apart from Antarctica. In general, it has large monthly variation and peaks in spring. Snow albedo feedback is estimated to be 0.18 ± 0.08 W∙m−2∙°C−1 and 0.04 ± 0.02 W∙m−2∙°C−1 on hemispheric and global scales, respectively. Compared to previous studies, this paper focuses specifically on quantifying snow albedo feedback and demonstrates three improvements: (1) used high spatial and temporal resolution satellite-based snow cover data to determine the areas of snow albedo radiative forcing and feedback; (2) provided detailed information for model parameterization by using the results from (1), together with accurate description of snow cover change and constrained snow albedo and snow-free albedo data; and (3) effectively reduced the uncertainty of snow albedo feedback and increased its confidence level through the block bootstrap test. Our results of snow albedo feedback agreed well with other partially observation-based studies and indicate that the 25 Coupled Model Intercomparison Project Phase 5 (CMIP5) models might have overestimated the snow albedo feedback, largely due to the overestimation of surface albedo change between snow-covered and snow-free surface in these models. View Full-Text
Keywords: snow albedo radiative forcing; snow albedo feedback; radiative kernel; remote sensing snow albedo radiative forcing; snow albedo feedback; radiative kernel; remote sensing

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Xiao, L.; Che, T.; Chen, L.; Xie, H.; Dai, L. Quantifying Snow Albedo Radiative Forcing and Its Feedback during 2003–2016. Remote Sens. 2017, 9, 883.

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