Satellite Passive Microwave Sea-Ice Concentration Data Set Intercomparison
for Arctic Summer Conditions

We report on results of a systematic inter-comparison of 10 global sea-ice concentration (SIC) data products at 12.5 to 50.0 km grid resolution from satellite passive microwave (PMW) observations for the Arctic during summer. The products are compared against SIC and net ice-surface fraction (ISF) – SIC minus the per-grid cell melt-pond fraction (MPF) on sea ice – as derived from MODerate resolution Imaging Spectroradiometer (MODIS) satellite observations and observed from ice15 going vessels. Like in Kern et al. (2019), we group the 10 products based on the concept of the SIC retrieval used. Group I consists of products of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Ocean and Sea Ice Satellite Application Facility (OSI SAF) and European Space Agency (ESA) Climate Change Initiative (CCI) algorithms. Group II consists of products derived with the Comiso bootstrap algorithm and the National Oceanographic and Atmospheric Administration (NOAA) National Snow and Ice Data Center (NSIDC) SIC climate data record (CDR). Group 20 III consists of Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) and National Aeronautics and Space Administration (NASA) Team (NT) algorithm products and group IV consists of products of the enhanced NASA Team algorithm (NT2). We find wide-spread positive and negative differences between PMW and MODIS SIC with magnitudes frequently reaching up to 20-25 % for groups I and III and up to 30-35 % for groups II and IV. On a pan-Arctic scale these differences may cancel out: Arctic average SIC from Ggroup I products agrees with MODIS within 2-5 % accuracy during the 25 entire melt period from May through September. Group II and IV products over-estimate MODIS Arctic average SIC by 5-10 %. Out of group III, ASI is similar to group I products while NT SIC under-estimates MODIS Arctic average SIC by 5-10 %. These differences, when translated into the impact computing Arctic sea-ice area (SIA), match well with the differences in SIA between the four groups reported for the summer months by Kern et al. (2019). MODIS ISF is systematically overestimated by all products; NT provides the smallest (up to 25 %) over-estimations (up to 25 %), group II and IV products the 30 largest (up to 45 %) over-estimations (up to 45 %). The spatial distribution of the observed over-estimation of MODIS ISF agrees reasonably well with the spatial distribution of the MODIS MPF and we find a robust linear relationship between PMW SIC and MODIS ISF for group I and III products during peak melt, i.e. July and August. We discuss different cases taking into account the expected influence of ice-surface properties other than melt ponds, i.e. wet snow and coarse grained snow / refrozen surface, on brightness temperatures and their ratiosPMW observations used as input to the SIC retrieval algorithms. Based on 35 this discussion we identify the mismatch between the actually observed surface properties and those represented by the ice tie points as the most likely reason for i) the observed differences between PMW SIC and MODIS ISF and for ii) the often surprisingly small difference between PMW and MODIS SIC in areas of high melt-pond fraction. We conclude that all 10 SIC products are highly inaccurate during summer melt. We hypothesize that the un-known amount of melt-pond signatures likely included in the ice tie points plays an important role – particularly for groups I and II – and recommendsuggest to conduct 40 further research in this field.