Abstract
Abstract. We report on results of an intercomparison 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 >350 images acquired in the visible–near-infrared frequency range by the joint National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) Landsat sensor during the 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 intercomparison results across the entire SIC range instead of focusing on overall mean differences and to take into 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 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 underestimation 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.
Highlights
We carry on the evaluation of sea-ice concentration (SIC) products derived from satellite passive microwave (PMW) observations
We present and discuss results obtained in the Northern Hemisphere and Southern Hemisphere
We preferred to not merge the results of Landsat-5 and Landsat-8 in the Northern Hemisphere because with that we have a relatively natural discrimination between cases dominated by first-year ice (Landsat-5) and cases dominated by mixed firstyear–multiyear ice or multiyear ice (Landsat-8)
Summary
We carry on the evaluation of sea-ice concentration (SIC) products derived from satellite passive microwave (PMW) observations. In Kern et al (2019), we presented an evaluation of 10 PMW SIC products at 0 % and 100 % SIC and with respect to sea-ice observations along ship tracks. Kern et al (2019) presented results of an evaluation of PMW SIC against a multi-annual set of standardized manual visual ship-based observations of the ice conditions. These observations are, of limited accuracy and of limited representativity because the average accuracy is between 5 % and 10 %, and observations mostly represent sea-ice conditions where it is possible to navigate. The averaging resulted in a reduction in the number of valid data pairs from approximately 15 000 to less than 800, i.e., about 400 per hemisphere
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