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

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

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

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

Multi-Decadal Variability of Polynya Characteristics and Ice Production in the North Water Polynya by Means of Passive Microwave and Thermal Infrared Satellite Imagery

The North Water (NOW) Polynya is a regularly-forming area of open-water and thin-ice, located between northwestern Greenland and Ellesmere Island (Canada) at the northern tip of Baffin Bay. Due to its large spatial extent, it is of high importance for a variety of physical and biological processes, especially in wintertime. Here, we present a long-term remote sensing study for the winter seasons 1978/1979 to 2014/2015. Polynya characteristics are inferred from (1) sea ice concentrations and brightness temperatures from passive microwave satellite sensors (Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS)) and (2) thin-ice thickness distributions, which are calculated using MODIS ice-surface temperatures and European Center for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis data in a 1D thermodynamic energy-balance model. Daily ice production rates are retrieved for each winter season from 2002/2003 to 2014/2015, assuming that all heat loss at the ice surface is balanced by ice growth. Two different cloud-cover correction schemes are applied on daily polynya area and ice production values to account for cloud gaps in the MODIS composites. Our results indicate that the NOW polynya experienced significant seasonal changes over the last three decades considering the overall frequency of polynya occurrences, as well as their spatial extent. In the 1980s, there were prolonged periods of a more or less closed ice cover in northern Baffin Bay in winter. This changed towards an average opening on more than 85% of the days between November and March during the last decade. Noticeably, the sea ice cover in the NOW polynya region shows signs of a later-appearing fall freeze-up, starting in the late 1990s. Different methods to obtain daily polynya area using passive microwave AMSR-E/AMSR2 data and SSM/I-SSMIS data were applied. A comparison with MODIS data (thin-ice thickness ≤ 20 cm) shows that the wintertime polynya area estimates derived by MODIS are about 30 to 40% higher than those derived using the polynya signature simulation method (PSSM) with AMSR-E data. In turn, the difference in polynya area between PSSM and a sea ice concentration (SIC) threshold of 70% is fairly low (approximately 10%) when applied to AMSR-E data. For the coarse-resolution SSM/I-SSMIS data, this difference is much larger, particularly in November and December. Instead of a sea ice concentration threshold, the PSSM method should be used for SSM/I-SSMIS data. Depending on the type of cloud-cover correction, the calculated ice production based on MODIS data reaches an average value of 264.4 ± 65.1 km 3 to 275.7 ± 67.4 km 3 (2002/2003 to 2014/2015) and shows a high interannual variability. Our achieved long-term results underline the major importance of the NOW polynya considering its influence on Arctic ice production and associated atmosphere/ocean processes

Thin-ice dynamics and ice production in the Storfjorden polynya for winter-seasons 2002/2003–2013/2014 using MODIS thermal infrared 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 2013/2014 using thermal infrared satellite imagery. Thin-ice thicknesses were calculated from MODIS ice-surface temperatures, combined with ECMWF ERA-Interim atmospheric reanalysis 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 modeling studies. A basic coverage-correction scheme was applied to account for cloud-gaps in the daily composites. The sea ice in the Storfjorden area experiences a late fall freeze-up in several years over the 12 winter-period, with an increasing frequency of large polynya events until the end of December. During the regarded period, the mean polynya area is 4555.7 ± 1542.9 km2. The average ice production in the fjord is estimated with 28.3 ± 8.5 km3 per winter and therefore lower than in previous studies. Despite this comparatively short record of 12 winter-seasons, a significant positive trend of 20.2 km3 per decade could be detected, which contrasts earlier reports of a slightly negative trend in accumulated ice production prior to 2002. Derived estimates underline the importance of this relatively small coastal polynya system considering its contribution to the cold halocline layer through salt release during ice formation processes