Satellite Passive Microwave Sea-Ice Concentration Data Set Inter-comparison using Landsat data

• Main Authors: Kern, Stefan, Lavergne, Thomas, Pedersen, Leif Toudal, Tonboe, Rasmus Tage, Bell, Louisa, Meyer, Maybritt, Zeigermann, Luise Marie
• Format: Text
• Language: English
• Published: 2021
• Subjects: Sea ice
• Online Access: https://doi.org/10.5194/tc-2021-258; https://tc.copernicus.org/preprints/tc-2021-258/

We report on results of an 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 this we use SIC estimated from > 300 images acquired in the visible / near-infrared frequency range by joint the National Aeronautics and Space Administration (NASA)/United States Geological Survey (USGS) Landsat sensor during years 2003–2011 and 2013–2015. Conditions covered are late winter / early spring in the Northern Hemisphere and from late winter through fall freeze-up in the Southern Hemisphere. Among the products investigated are the four 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: SICCI-2 and OSI-450. We stress the importance to consider inter-comparison results across the entire SIC range instead of focusing on overall mean differences, and to take in account known biases in PMW SIC products, e.g. for thin ice. We find superior linear agreement between PMW SIC and Landsat SIC for the 25 km and the 50 km SICCI-2 products in both hemispheres. We discuss quantitatively various uncertainty sources of the evaluation carried out. First, depending on the number of mixed ocean-ice Landsat pixels classified erroneously as ice only, our Landsat SIC is found to be biased high. This applies to some of our Southern Hemisphere data, promotes an overly large fraction of Landsat SIC under-estimation by PMW SIC products, and renders PMW SIC products overestimating Landsat SIC particularly problematic. Secondly, our main results are based on SIC data truncated to the range 0 % to 100 %. We demonstrate using non-truncated SIC values, where possible, can considerably improve linear agreement between PMW and Landsat SIC. Thirdly, we investigate the impact of filters often used to clean up the final products from spurious SIC over open water due to weather effects and along coastlines due to land spillover. Benefiting from the possibility to switch on or off certain filters in the SICCI-2 and OSI-450 products we quantify the impact land spillover filtering can have on evaluation results as shown in this paper.