Sea-Ice Wintertime Lead Frequencies and Regional Characteristics in the Arctic, 2003–2015

The presence of sea-ice leads represents a key feature of the Arctic sea ice cover. Leads promote the flux of sensible and latent heat from the ocean to the cold winter atmosphere and are thereby crucial for air-sea-ice-ocean interactions. We here apply a binary segmentation procedure to identify leads from MODIS thermal infrared imagery on a daily time scale. The method separates identified leads into two uncertainty categories, with the high uncertainty being attributed to artifacts that arise from warm signatures of unrecognized clouds. Based on the obtained lead detections, we compute quasi-daily pan-Arctic lead maps for the months of January to April, 2003–2015. Our results highlight the marginal ice zone in the Fram Strait and Barents Sea as the primary region for lead activity. The spatial distribution of the average pan-Arctic lead frequencies reveals, moreover, distinct patterns of predominant fracture zones in the Beaufort Sea and along the shelf-breaks, mainly in the Siberian sector of the Arctic Ocean as well as the well-known polynya and fast-ice locations. Additionally, a substantial inter-annual variability of lead occurrences in the Arctic is indicated

Pan-Arctic lead detection from MODIS thermal infrared imagery

Polynyas and leads are key elements of the wintertime Arctic sea-ice cover. They play a crucial role in surface heat loss, potential ice formation and consequently in the seasonal sea-ice budget. While polynyas are generally sufficiently large to be observed with passive microwave satellite sensors, the monitoring of narrow leads requires the use of data at a higher spatial resolution. We apply and evaluate different lead segmentation techniques based on sea-ice surface temperatures as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS). Daily lead composite maps indicate the presence of cloud artifacts that arise from ambiguities in the segmentation process and shortcomings in the MODIS cloud mask. A fuzzy cloud artifact filter is hence implemented to mitigate these effects and the associated potential misclassification of leads. The filter is adjusted with reference data from thermal infrared image sequences, and applied to daily MODIS data from January to April 2008. The daily lead product can be used to deduct the structure and dynamics of wintertime sea-ice leads and to assess seasonal divergence patterns of the Arctic Ocean

Kryosphäre – Gegenwart und Zukunft

Im globalen Klimasystem hat die Kryosphäre – mit ihren Komponenten Schnee, Meereis, See- und Flusseis, Eisschilde, Gebirgsgletscher und Permafrost einen großen Einfluss auf den Energiehaushalt der Erdoberfläche und auf die Wechselwirkungen an den Grenzflächen zwischen Landflächen, Ozeanen und der Atmosphäre. Dies beruht u.a. auf ihren besonderen physikalischen Eigenschaften (u.a. der Eis-Albedo-Rückkopplung) und ihrer großen Fläche. Für den globalen Wasserhaushalt sind die in der Kryosphäre gebundenen Wassermengen von erheblicher Bedeutung. Zahlreiche internationale Forschungsprogramme sind vor dem Hintergrund des globalen Klimawandels auf die Veränderungen und die zukünftige Entwicklung vor allem des arktischen Meereises und der Eisschilde fokussiert. Neben den in-situ Beobachtungen und Fernerkundungsmethoden ermöglichen numerische Modelle einen tieferen Einblick in die Prozesse und Wechselwirkungen der Kryosphäre. Zu den aktuellen Forschungsfeldern gehören vor allem die Identifikation von Wechselwirkungen zwischen der Kryosphäre und dem globalen Klimasystem, die polaren Ökosysteme und die Verbesserung von Vorhersagen zukünftiger Änderungen innerhalb der Kryosphäre

Thin ice thickness distribution and ice production in the Storfjorden Polynya for 2002/2003 - 2011/2012 using MODIS thermalinfrared imagery

Spatial and temporal characteristics of the Storfjorden polynya, which forms regularly in the proximity of the islands Spitsbergen, Barentsøya and Edgeøya in the Svalbard archipelago under the influence of strong north-easterly winds, have been investigated for the period 2002/2003 to 2011/2012 using thermal infrared satellite imagery. Thin ice thicknesses were calculated from MODIS ice surface temperatures, combined with ECMWF ERA-Interim reanalysis atmospheric data in an energy balance model. Based on calculated thin ice thicknesses, associated quantities like polynya area and total ice production were derived and compared to previous remote sensing and modelling studies. It appears that the sea ice in the Storfjorden area shows signs of a delayed fall freeze-up over the 10 year-period, with an increasing frequency of large polynya events until the end of December. Average ice production in the fjord is estimated with 19.9+-3.9 km3 and is therefore slightly lower compared to previously calculated values by other authors. Nevertheless it underlines the importance of this relatively small coastal polynya system considering its contribution to the cold halocline layer through salt release during ice formation processes. Application of a simple cloud coverage-correction scheme yielded reasonable adjustments for the polynya area and accumulated ice production, while some open questions originating from inherent cloud effects and the applied parametrizations in the polynya area retrieval have to be addressed in future studies

A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery

The presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and are sources for the formation of dense water which affects the ocean circulation. Atmospheric and ocean models strongly rely on observational data to describe the respective state of the sea ice since numerical models are not able to produce sea ice leads explicitly. For the Arctic, some lead datasets are available, but for the Antarctic, no such data yet exist. Our study presents a new algorithm with which leads are automatically identified in satellite thermal infrared images. A variety of lead metrics is used to distinguish between true leads and detection artefacts with the use of fuzzy logic. We evaluate the outputs and provide pixel-wise uncertainties. Our data yield daily sea ice lead maps at a resolution of 1 km2 for the winter months November– April 2002/03–2018/19 (Arctic) and April–September 2003–2019 (Antarctic), respectively. The long-term average of the lead frequency distributions show distinct features related to bathymetric structures in both hemisphere

Thin ice thickness distribution and ice production in the North Water and Laptev Sea polynya regions using MODIS thermal infrared imagery

We present investigations of Arctic polynya dynamics for the period 2002/2003 to 2011/2012. Thin ice thicknesses were calculated from MODIS ice surface temperatures, combined with ECMWF ERA-Interim reanalysis atmospheric data in an energy balance model. Regions of interest include the North Water Polynya, located between Ellesmere Island (Canada) and Greenland, and the Laptev Sea flaw polynyas. Based on calculated thin ice thicknesses, associated quantities like polynya area and total ice production were derived for all regarded regions and compared to recent studies using passive microwave remote sensing data. Calculated ice production reaches mean values of 223 km3 for the North Water Polynya and 79 km3 for the Laptev Sea. They underline the importance of the two coastal polynya systems in the context of the Arctic sea ice budget, although their individual contribution seems to be overestimated in other satellite-based studies. For both regions, obtained polynya areas and ice production clearly exceeded the corresponding values from passive microwave studies, despite a good agreement in the overall seasonal development. Possible reasons include a hidden effect of undetected clouds and the applied parametrizations in the polynya area retrieval. The application of a simple cloud coverage-correction scheme yielded reasonable adjustments for the polynya area and accumulated ice production, while open questions originating from inherent cloud effects have to be addressed in future studies. Noticeably, the sea ice cover in both regarded polynya regions shows signs of a delayed fall freeze-up over the 10 year-period

The observation of the thin-ice thickness distribution within the Laptev Sea polynya using MODIS data

Polynyas are of high research interest since these features are areas of extensive new ice formation. The calculation of accurate ice-production values requires the knowledge of polynya area and thin-ice thickness distribution. These two variables can be derived by remote sensing data. However, a cross-validation study of various remote sensing data sets indicates that the spatial resolution issue is essential for the retrieval of accurate thin-ice thickness distribution. Thus, high-resolution remote sensing data must be used. MODIS thermal-infrared data with a spatial resolution of 1 km × 1 km is appropriate for the retrieval of thin-ice thickness distribution within the polynya. The algorithm to derive thermal-infrared thin-ice thickness is improved to state-of-the-art parameterizations. The mean absolute error of thin-ice thickness is ±4.7 cm for ice below 20 cm of thickness. The thin-ice thickness maps lack full coverage due to the restriction of the algorithm to cloud-free and nighttime data. Therefore, a compositing method is applied to compute daily thin-ice thickness maps. These maps cover on average 70 % of the Laptev Sea polynya. In order to fill the remaining gaps a combined remote sensing – model approach is developed to provide a consistent time series of high-resolution thin-ice thickness maps. This data set is valuable for the retrieval of accurate ice production within polynyas