1. Ackerman, S. A., Frey, R. A., Strabala, K., Liu, Y., Gumley, L. E., Baum, B.,
and Menzel, P.: Discriminating clear-sky from clouds with MODIS – Algorithm
theoretical basis document, Tech. Rep., MODIS Cloud Mask Team and
Cooperative Institute for Meteorological Satellite Studies, University of
Wisconsin, Madison, USA, available at:
https://modis-atmos.gsfc.nasa.gov/sites/default/files/ModAtmo/MOD35_ATBD_Collection6_0.pdf (last access: 8 October 2020),
2010. a, b, c, d, e
2. AMAP: Snow, Water, Ice and Permafrost, Summary for Policy-makers, Tech. Rep., Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway, available at:
https://www.amap.no/documents/doc/Snow-Water-Ice-and-Permafrost.-Summary-for-Policy-makers/1532 (last access: 8 October 2020),
2017. a
3. Brodzik, M. J. and Stewart, J. S.: Near-Real-Time SSM/I-SSMIS EASE-Grid Daily Global Ice Concentration and Snow Extent, Version 5 [Data set], NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado, USA, https://doi.org/10.5067/3KB2JPLFPK3R, 2016. a
4. Brown, O. B. and Minnett, P. J.: MODIS Infrared Sea Surface Temperature
Algorithm Theoretical Basis Document Version 2.0, Tech. Rep., University of
Miami, Florida, USA, available at: https://modis.gsfc.nasa.gov/data/atbd/atbd_mod25.pdf (last access: 8 October 2020),
1999. a
5. Cavalieri, D. J. and Parkinson, C. L.: Arctic sea ice variability and trends, 1979–2010, The Cryosphere, 6, 881–889, https://doi.org/10.5194/tc-6-881-2012, 2012. a, b