Abstract. The spatial and temporal dynamics of melt ponds and sea ice albedo contain information on the current state and the trend of the climate of the Arctic region. This publication presents a study on melt pond fraction (MPF) and sea ice albedo spatial and temporal dynamics obtained with the Melt Pond Detection (MPD) retrieval scheme for the Medium Resolution Imaging Spectrometer (MERIS) satellite data. This study compares sea ice albedo and MPF to surface air temperature reanalysis data, compares MPF retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS), and examines albedo and MPF trends. Weekly averages of MPF for 2007 and 2011 showed different MPF dynamics while summer sea ice minimum was similar for both years. The gridded MPF and albedo products compare well to independent reanalysis temperature data and show melt onset when the temperature gets above zero; however MPD shows an offset at low MPFs of about 10 % most probably due to unscreened high clouds. Weekly averaged trends show pronounced dynamics of both, MPF and albedo: a negative MPF trend in the East Siberian Sea and a positive MPF trend around the Queen Elizabeth Islands. The negative MPF trend appears due to a change of the absolute MPF value in its peak, whereas the positive MPF trend is created by the earlier melt onset, with the peak MPF values unchanged. The MPF dynamics in the East Siberian Sea could indicate a temporal change of ice type prevailing in the region, as opposed to the Queen Elizabeth Islands, where MPF dynamics react to an earlier seasonal onset of melt.
Abstract. The historic MERIS (Medium Resolution Imaging Spectrometer) sensor on board Envisat (Environmental Satellite, operation 2002–2012) provides valuable remote sensing data for the retrievals of summer sea ice in the Arctic. MERIS data together with the data of recently launched successor OLCI (Ocean and Land Colour Instrument) on board Sentinel 3A and 3B (2016 onwards) can be used to assess the long-term change of the Arctic summer sea ice. An important prerequisite to a high-quality remote sensing dataset is an accurate separation of cloudy and clear pixels to ensure lowest cloud contamination of the resulting product. The presence of 15 visible and near-infrared spectral channels of MERIS allows high-quality retrievals of sea ice albedo and melt pond fraction, but it makes cloud screening a challenge as snow, sea ice and clouds have similar optical features in the available spectral range of 412.5–900 nm. In this paper, we present a new cloud screening method MECOSI (MERIS Cloud Screening Over Sea Ice) for the retrievals of spectral albedo and melt pond fraction (MPF) from MERIS. The method utilizes all 15 MERIS channels, including the oxygen A absorption band. For the latter, a smile effect correction has been developed to ensure high-quality screening throughout the whole swath. A total of 3 years of reference cloud mask from AATSR (Advanced Along-Track Scanning Radiometer) (Istomina et al., 2010) have been used to train the Bayesian cloud screening for the available limited MERIS spectral range. Whiteness and brightness criteria as well as normalized difference thresholds have been used as well. The comparison of the developed cloud mask to the operational AATSR and MODIS (Moderate Resolution Imaging Spectroradiometer) cloud masks shows a considerable improvement in the detection of clouds over snow and sea ice, with about 10 % false clear detections during May–July and less than 5 % false clear detections in the rest of the melting season. This seasonal behavior is expected as the sea ice surface is generally brighter and more challenging for cloud detection in the beginning of the melting season. The effect of the improved cloud screening on the MPF–albedo datasets is demonstrated on both temporal and spatial scales. In the absence of cloud contamination, the time sequence of MPFs displays a greater range of values throughout the whole summer. The daily maps of the MPF now show spatially uniform values without cloud artifacts, which were clearly visible in the previous version of the dataset. The developed cloud screening routine can be applied to address cloud contamination in remote sensing data over sea ice. The resulting cloud mask for the MERIS operating time, as well as the improved MPF–albedo datasets for the Arctic region, is available at https://www.seaice.uni-bremen.de/start/ (Istomina et al., 2017).
The historic MERIS sensor onboard Envisat (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) provides valuable remote sensing data for the retrievals of the summer sea ice in the Arctic. MERIS data together with the data of recently launched successor OLCI onboard Sentinel 3A and 3B (2016 onwards) can be used to assess the long-term change of the Arctic summer sea ice. An important 10 prerequisite to a high-quality remote sensing dataset is an accurate separation of cloudy and clear pixels to ensure lowest cloud contamination of the resulting product. The presence of 15 VIS and NIR spectral channels of MERIS allow high quality retrievals of sea ice albedo and melt pond fraction, but make cloud screening a challenge as snow, sea ice and clouds have similar optical features in the available spectral range of 412.5 -900nm.In this paper, we present a new cloud screening method MECOSI (MERIS Cloud screening Over Sea Ice) for the retrievals 15 of spectral albedo and melt pond fraction (MPF) from MERIS. The method utilizes all 15 MERIS channels, including the oxygen A absorption band. For the latter, a smile effect correction has been developed to ensure high quality screening throughout the whole swath. Three years of reference cloud mask from AATSR (Istomina et al., 2010) have been used to train the Bayesian cloud screening for the available limited MERIS spectral range. Whiteness and brightness criteria as well as normalized difference thresholds have been used as well. 20The comparison of the developed cloud mask to the operational AATSR and MODIS cloud masks shows a considerable improvement in the detection of clouds over snow and sea ice, with about 10% false clear detections during May-July and less than 5% false clear detections in the rest of the melting season. This seasonal behaviour is expected as the sea ice surface is generally brighter and more challenging for cloud detection in the beginning of the melting season.The effect of the improved cloud screening on the MPF/albedo datasets is demonstrated on both temporal and spatial scales. 25In the absence of cloud contamination, the time sequence of MPFs displays a greater range of values throughout the whole summer. The daily maps of the MPF now show spatially uniform values without cloud artefacts, which were clearly visible in the previous version of the dataset.The resulting cloud mask for the MERIS operating time, as well as the improved MPF/albedo datasets are available as swath data and daily means on the ftp server of the University of Bremen https://seaice.uni-bremen.de/data/meris/gridded_cldscr/. 30
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