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

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

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

Evolution of first-year and second-year snow properties on sea ice in the Weddell Sea during spring-summer transition

Observations of snow properties, superimposed ice, and atmospheric heat fluxes have been performed on first-year and second-year sea ice in the western Weddell Sea, Antarctica. Snow in this region is particular as it does usually survive summer ablation. Measurements were performed during Ice Station Polarstern (ISPOL), a 5-week drift station of the German icebreaker RV Polarstern. Net heat flux to the snowpack was 8 W m−2, causing only 0.1 to 0.2 m of thinning of both snow cover types, thinner first-year and thicker second-year snow. Snow thinning was dominated by compaction and evaporation, whereas melt was of minor importance and occurred only internally at or close to the surface. Characteristic differences between snow on first-year and second-year ice were found in snow thickness, temperature, and stratigraphy. Snow on second-year ice was thicker, colder, denser, and more layered than on first-year ice. Metamorphism and ablation, and thus mass balance, were similar between both regimes, because they depend more on surface heat fluxes and less on underground properties. Ice freeboard was mostly negative, but flooding occurred mainly on first-year ice. Snow and ice interface temperature did not reach the melting point during the observation period. Nevertheless, formation of discontinuous superimposed ice was observed. Color tracer experiments suggest considerable meltwater percolation within the snow, despite below-melting temperatures of lower layers. Strong meridional gradients of snow and sea-ice properties were found in this region. They suggest similar gradients in atmospheric and oceanographic conditions and implicate their importance for melt processes and the location of the summer ice edge

The microwave emissivity variability of snow covered first-year sea ice from late winter to early summer: a model study

Satellite observations of microwave brightness temperatures between 19 GHz and 85 GHz are the main data sources for operational sea-ice monitoring and retrieval of ice concentrations. However, microwave brightness temperatures depend on the emissivity of snow and ice, which is subject to pronounced seasonal variations and shows significant hemispheric contrasts. These mainly arise from differences in the rate and strength of snow metamorphism and melt. We here use the thermodynamic snow model SNTHERM forced by European Re-Analysis (ERA) interim data and the Microwave Emission Model of Layered Snowpacks (MEMLS), to calculate the sea-ice surface emissivity and to identify the contribution of regional patterns in atmospheric conditions to its variability in the Arctic and Antarctic. The computed emissivities reveal a pronounced seasonal cycle with large regional variability. The emissivity variability increases from winter to early summer and is more pronounced in the Antarctic. In the pre-melt period (January–May, July–November) the standard deviations in surface microwave emissivity due to diurnal, regional and inter-annual variability of atmospheric forcing reach up to Δε = 0.034, 0.043, and 0.097 for 19 GHz, 37 GHz and 85 GHz channels, respectively. Between 2000 and 2009, small but significant positive emissivity trends were observed in the Weddell Sea during November and December as well as in Fram Strait during February, potentially related to earlier melt onset in these regions. The obtained results contribute to a better understanding of the uncertainty and variability of sea-ice concentration and snow-depth retrievals in regions of high sea-ice concentrations

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

Ice production of polynyas in the Laptev Sea calculated from mesoscale NWP model simulations for the winters 2007/08 and 2008/09

The Laptev Sea area of the Siberian Arctic is known as being a highly productive area for the formation of new ice throughout the winter season. This area is characterized by flaw polynyas which occur at the edge of the fast ice surrounding the coastal zones during wintertime. Due to large turbulent atmospheric heat fluxes, polynyas are strong sea ice producers. However, estimates of sea ice production in the Laptev Sea polynyas are arguable since high resolution and high quality atmospheric data is not available for that area. Previous estimations of ice production rely on global reanalyses as atmospheric forcing, such as NCEP with about 280km horizontal resolution, which is too coarse to take polynyas into account. In our study, we use the limited area model COSMO with a prescribed sea ice coverage by daily AMSR-E satellite data. Runs with 15 and 5 km horizontal resolution (nested in global GME model data) are performed for the two winter periods (Nov-May) 2007/08 and 2008/09. The net energy loss of the polynya surface is used to determine ice production. COSMO is run in a forecast mode for overlapping daily 30h runs. We use a thermodynamic sea ice module for COSMO and varied the ice thickness in the polynya area from 0 to 10 cm. This allows for a new approach for estimating the ice production in the Laptev Sea polynyas. The total polynya ice production is calculated as 51.25 km3 in 2007/08 and 126.87 km3 in 2008/09 for the assumption of ice free polynyas. A coverage with 10 cm of thin ice reduces the ice production by about 30 %. An AMSR-E- and NCEP-based study gives a value of 46.37 km3 for 2007/08 and an average of 55.2 km3 for 1979-2008 with a maximum of 73.3 km3 in 2003/04 and a minimum 35.7 km3. Hence, interannual variability between the two COSMO-simulated years outnumbers the long-term mean interannual variability of satellite-based study with NCEP forcing. Our study leads to the conclusion that interannual variability is underestimated by previous studies, which are not able to take into account the interaction between the polynya and the overlying atmospheric boundary layer. In future, we will use ERA-Interim data as forcing data for COSMO to extend the modeled time range to 10 years

Monitoring of thin ice in the Laptev Sea Polynya

It is estimated that a considerable fraction of new ice formation on Arctic shelf areas takes place in the Laptev Sea polynyas. However, the different studies reveal strong discrepancies in ice production rates. For an accurate monitoring of surface heat loss and hence, ice production within polynyas it is important to know the thin ice distribution within the polynya. We use an established thin-ice algorithm with several modifications to retrieve the thin ice thickness distribution up to 50 cm based on MODIS ice surface temperatures and atmospheric data from model simulations. We verify the MODIS ice surface temperatures with a data set measured during a field campaign in the Laptev Sea. For the calculation of thin ice thicknesses we use NCEP reanalyses, GME analyses and COSMO simulations in comparison as different atmospheric forcing data. We find that from the several atmospheric variables the air temperature at 2 m has the greatest impact on the ice thickness calculation. At ice thicknesses above 20 cm the algorithm responds sensitively to errors in the atmospheric data. In regions of very thin ice the errors in the atmospheric data are masked due to larger temperature differences between surface and atmosphere. However, a reliable atmospheric data set is necessary for the calculation of accurate thin ice thicknesses