Antarctic ice shelf melting and its impact on the global sea ice-ocean system

Earth s ice shelves are mainly located in Antarctica. They cover about 44% of the Antarctic coastline and are a salient feature of the continent. Antarctic ice shelf melting (AISM) removes heat from and inputs freshwater into the adjacent Southern Ocean. Although playing an important role in the global climate, AISM is one of the most important components currently absent in the IPCC climate model. In this study, AISM is introduced into a global sea ice-ocean climate model ORCA2-LIM, following the approach of Beckmann and Goosse (2003; BG03) for the thermodynamic interaction between the ice shelf and ocean. This forms the model ORCA2-LIM-ISP (ISP: ice shelf parameterization), in which not only all the major Antarctic ice shelves but also a number of minor ice shelves are included. Using these two models, ORCA2-LIM and ORCA2-LIM-ISP, the impact of addition of AISM and increasing AISM have been investigated. Using the ORCA2-LIM model, numerical experiments are performed to investigate the sensitivity of the polar sea ice cover and the Antarctic Circumpolar Current (ACC) transport through Drake Passage (DP) to the variations of three sea ice parameters, namely the thickness of newly formed ice in leads (h0), the compressive strength of ice (P*), and the turning angle in the oceanic boundary layer beneath sea ice (θ). It is found that the magnitudes of h0 and P* have little impact on the seasonal sea ice extent, but lead to large changes in the seasonal sea ice volume. The variation in turning angle has little impact on the sea ice extent and volume in the Arctic but tends to reduce them in the Antarctica when ignored. The magnitude of P* has the least impact on the DP transport, while the other two parameters have much larger influences. Numerical results from ORCA2-LIM and ORCA2-LIM-ISP are analyzed to investigate how the inclusion of AISM affects the representation of the Southern Ocean hydrography. Comparisons with data from the World Ocean Circulation Experiment (WOCE) show that the addition of AISM significantly improves the simulated hydrography. It not only warms and freshens the originally too cold and too saline bottom water (AABW), but also warms and enriches the salinity of the originally too cold and too fresh warm deep water (WDW). Addition of AISM also improves the simulated stratification. The close agreement between the simulation with AISM and the observations suggests that the applied parameterization is an adequate way to include the effect of AISM in a global sea ice-ocean climate model. We also investigate the models capability to represent the sea ice-ocean system in the North Atlantic Ocean and the Arctic regions. Our study shows both models (with and without AISM) can successfully reproduce the main features of the sea ice-ocean system. However, both tend to overestimate the ice flux through the Nares Strait, produce a lower temperature and salinity in the Hudson Bay, Baffin Bay and Davis Strait, and miss the deep convection in the Labrador Sea. These deficiencies are mainly attributed to the artificial enlargement of the Nares Strait in the model. In this study, the impact of increasing AISM on the global sea ice-ocean system is thoroughly investigated. This provides a first idea regarding changes induced by increasing AISM. It is shown that the impact of increasing AISM is global and most significant in the Southern Ocean. There, increasing AISM tends to freshen the surface water, to warm the intermediate and deep waters, and to freshen and warm the bottom water. In addition, increasing AISM also leads to changes in the mixed layer depths (MLD) in the deep convection sites in the Southern Ocean, deepening in the Antarctic continental shelf while shoaling in the ACC region. Furthermore, increasing AISM influences the current system in the Southern Ocean. It tends to weaken the ACC, and strengthen the Antarctic coastal current (ACoC) as well as the Weddell Gyre and the Ross Gyre. In addition to the ocean system, increasing AISM also has a notable impact on the Antarctic sea ice cover. Due to the cooling of seawater, sea ice concentration and thickness generally become higher. In austral winter, noticeable increases in sea ice concentration mainly take place near the ice edge. In regards with sea ice thickness, large increases are mainly found along the coast of the Weddell Sea, the Bellingshausen and Amundsen Seas, and the Ross Sea. The overall thickening of sea ice leads to a larger volume of sea ice in Antarctica. In the North Atlantic, increasing AISM leads to remarkable changes in temperature, salinity and density. The water generally becomes warmer, more saline and denser. The most significant warming occurs in the subsurface layer. In contrast, the maximum salinity increase is found at the surface. In addition, the MLD becomes larger along the Greenland-Scotland-Iceland ridge. Global teleconnections due to AISM are studied. The AISM signal is transported with the surface current: the additional freshwater from AISM tends to enhance the northward spreading of the surface water. As a result, more warm and saline water is transported from the tropical region to the North Atlantic Ocean, resulting in warming and salt enrichment there. It would take about 30 40 years to establish a systematic noticeable change in temperature, salinity and MLD in the North Atlantic Ocean according to this study. The changes in hydrography due to increasing AISM are compared with observations. Consistency suggests that increasing AISM is highly likely a major contributor to the recent observed changes in the Southern Ocean. In addition, the AISM might contribute to the salinity contrast between the North Atlantic and North Pacific, which is important for the global thermohaline circulation.

Intermingling and seasonal migrations of Greenland halibut (Reinhardtius hippoglossoides) populations determined from tagging studies

A total of 7244 Greenland halibut (Reinhardtius hippoglossoides, Walbaum) were tagged in Greenland waters between 1986 and 1998 to increase information on stock delineations, to clarify migration routes, and to describe the seasonal movements of fjord populations. At present 517 recaptured Greenland halibut have been recorded. For Greenland halibut released in Davis Strait, Baffin Bay, and the fjords of southwestern and eastern Greenland, a substantial portion of recovered fish demonstrated migratory behavior, up to 2500 km, primarily to Denmark Strait between Greenland and Iceland. The recaptured fish provided evidence of intermingling between the population in Denmark Strait and the populations in Davis Strait and the southwest Greenland fjords. These observations support those of other studies that indicate that Greenland halibut inhabiting Davis Strait and the fjords of southwestern and eastern Greenland originate in the spawning grounds west of Iceland. The high mobility of offshore Greenland halibut within Baffin Bay and Davis Strait suggests that Greenland halibut migrate extensively between feeding and spawning areas. Greenland halibut in the fjords of northwestern Greenland appear to be resident in behavior and do not intermingle with offshore or more southerly inshore populations. A seasonal pattern in the recovery of these fish indicates that Greenland halibut aggregate in the inner part of fjords during the second half of the year (when inshore waters are not covered with ice).

Daily polynya area and ice production in the North Water polynya region

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.

Carbon chemistry of ODP Leg 105 sites

The quantity and quality of organic carbon of Eocene to Holocene sediments from ODP Sites 645, 646, and 647 were investigated to reconstruct depositional environments. Results were based on organic-carbon and nitrogen determinations, Rock-Eval pyrolysis, and kerogen microscopy. The sediments at Site 645 in Baffin Bay are characterized by relatively high organic-carbon values, most of which range from 0.5% to almost 3%, with maximum values in the middle Miocene. Distinct maxima of organic-carbon accumulation rates occur between 18 and 12.5 Ma and between 3.4 and 0 Ma. At Sites 646 and 647 in the Labrador Sea, organic-carbon contents vary between 0.1% and 0.75%. Cyclic 'Milankovitch-type' changes in organic-carbon deposition imply climate-controlled mechanisms that cause these fluctuations. The composition of organic matter at Site 645 is dominated by terrigenous components throughout the entire sediment sequence. An increased content of marine organic carbon was recorded only in the late-middle Miocene. At Sites 646 and 647, the origin of the organic matter most probably is marine. Oceanic paleoproductivity values were estimated, based on the amount of marine organic carbon. During most of the Neogene time interval at Site 645, productivity was low, i.e., similar or less than that measured in Baffin Bay today. Higher values of up to 150 (200) gC/m**2/y may have occurred only in the Miocene. At Sites 646 and 647, mean paleoproductivity values vary between 90 and 170 gC/m**2/y; i.e., these are also similar to those measured in the Labrador Sea today. Lower values of 40 to 70 gC/m**2/y were estimated for the early Eocene and (middle) Miocene.