Interannual and decadal variability of sea ice drift, concentration and thickness in the Weddell Sea

Sea ice concentrations in the Weddell Sea are subject to regional climate variability. The magnitude and origin of local trends in the sea ice coverage were studied using the bootstrap algorithm sea ice concentration data from the NSIDC for 1979-2006. The impact of atmospheric forcing such as air temperature, wind speed, sea level pressure and cloud coverage, gained from NCEP/NCAR reanalysis, was assessed by analyzing correlation coefficients between the respective atmospheric component and the sea ice concentrations. In addition, the variability of sea ice drift was analyzed using the Polar Pathfinder sea ice motion vectors, and the correlation with sea ice concentration was tested after an assessment of the product s uncertainties. The connection to the variability of sea ice thicknesses was derived by model simulations from the Finite Element Sea ice-Ocean Model (FESOM). It was found that sea ice concentrations increased in the eastern and decreased in the western Weddell Sea, predominantly in the marginal sea ice zone. There, and in coastal regions, temperatures are strongly negatively correlated to sea ice concentrations, whereas in the central Weddell Sea, mostly a positive correlation was assessed, especially during winter. From analyses of the wind field it was found that the prevailing westerlies at the Antarctic Peninsula frequently show a shift towards the south. The enhanced southward winds are expected to bring warmer air into the western and central Weddell Sea and are further expected to redistribute the sea ice from the west into the central and eastern regions. This would increase the sea ice concentrations in the central Weddell Sea due to enhanced compactness, although temperatures are increasing. The correlation between sea ice concentrations and sea ice drift is only robust for the central Weddell Sea, where both parameters are mainly anti-correlated. Hence, strong sea ice drift is connected to lower sea ice concentrations and vice versa. This finding is consistent with the connection to the wind fields, since stronger northerly winds would reduce the north-eastward drift of sea ice in this region and enhance the sea ice concentrations. From model simulations with FESOM it was found that sea ice thicknesses predominantly show the same tendencies for changes as the simulated sea ice concentrations, which are basically decreasing in the central Weddell Sea and increasing in the eastern Weddell Sea. The overall changes in sea ice thickness and concentration result in an increase of the total sea ice volume by 1 % per decade in the simulations. A sensitivity study with a free drift model, forced by 10-m wind speeds and ocean currents from FESOM showed that the trends in the modelled sea ice drift are driven by the atmospheric fields, since ocean currents show barely any trends. Further it was revealed that sea ice drift velocities in the model are overestimated, especially in the zonal direction. Nevertheless, despite the overestimation, the mean sea ice export rate of 22 x 10^3 m^3/s is only about half of the export rates found in previous studies, which is certainly an effect of underestimated sea ice thicknesses in the western Weddell Sea

The sialic acid binding activity of the S protein facilitates infection by porcine transmissible gastroenteritis coronavirus

<p>Abstract</p> <p>Background</p> <p>Transmissible gastroenteritis virus (TGEV) has a sialic acid binding activity that is believed to be important for enteropathogenicity, but that has so far appeared to be dispensable for infection of cultured cells. The aims of this study were to determine the effect of sialic acid binding for the infection of cultured cells under unfavorable conditions, and comparison of TGEV strains and mutants, as well as the avian coronavirus IBV concerning their dependence on the sialic acid binding activity.</p> <p>Methods</p> <p>The infectivity of different viruses was analyzed by a plaque assay after adsorption times of 5, 20, and 60 min. Prior to infection, cultured cells were either treated with neuraminidase to deplete sialic acids from the cell surface, or mock-treated. In a second approach, pre-treatment of the virus with porcine intestinal mucin was performed, followed by the plaque assay after a 5 min adsorption time. A student's t-test was used to verify the significance of the results.</p> <p>Results</p> <p>Desialylation of cells only had a minor effect on the infection by TGEV strain Purdue 46 when an adsorption period of 60 min was allowed for initiation of infection. However, when the adsorption time was reduced to 5 min the infectivity on desialylated cells decreased by more than 60%. A TGEV PUR46 mutant (HAD3) deficient in sialic acid binding showed a 77% lower titer than the parental virus after a 5 min adsorption time. After an adsorption time of 60 min the titer of HAD3 was 58% lower than that of TGEV PUR46. Another TGEV strain, TGEV Miller, and IBV Beaudette showed a reduction in infectivity after neuraminidase treatment of the cultured cells irrespective of the virion adsorption time.</p> <p>Conclusions</p> <p>Our results suggest that the sialic acid binding activity facilitates the infection by TGEV under unfavorable environmental conditions. The dependence on the sialic acid binding activity for an efficient infection differs in the analyzed TGEV strains.</p

Snow Depth on Arctic and Antarctic Sea Ice Derived from Snow Buoys

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local effects, weather events, and potential influences of dynamic sea ice processes on snow accumulation

Snow depth on Antarctic sea ice from autonomous measurements

The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences

A comparison of satellite-derived sea-ice motion with drifting-buoy data in the Weddell Sea, Antarctica

AbstractWe compare a satellite-derived sea-ice motion dataset obtained from the US National Snow and Ice Data Center with daily ice drift by drifting buoys between 1989 and 2005. the satellite data were derived from daily composites of passive-microwave satellite measurements by means of a cross-correlation method and were supplemented with data from visible and thermal channels of the Advanced Very High Resolution Radiometer. Seasonal and interannual variations of the agreement between the two datasets are discussed. In addition, regional differences in the agreement and correlation coefficients of buoy- and satellite-derived drift components are analyzed. Results show that the overall drift regime can be well described by satellite-derived drift data but 71% of the retrieved drift velocities are lower than those observed by buoys. Nevertheless, correlation coefficients, r, between the two datasets are 0.587 for the zonal and 0.613 for the meridional drift component. the correlation coefficients between monthly averages of buoy- and satellite-derived zonal and meridional drift components are on average 25.7% and 16.4% lower in summer (October–February) than in winter (March–September), with the exception of January. In January, correlation coefficients are about 62.6% (zonal) and 66.5% (meridional) lower than in winter. Furthermore, deviations between zonal buoy- and satellite-derived drift are 80% larger in the second half than in the first half of the year. the observed yearly and regional averaged agreement between the two datasets depends strongly on the season when buoy data were collected and on the number of coincident buoy and satellite data, which was often very low.</jats:p

On the qualification of available sea ice freeboard data for the validation of remote sensing observations

The significant loss of Arctic sea ice during the last decades shows the sensitivity of the sea ice system to changes in the global climate. To distinguish between natural variability and the impact of global warming, an understanding of processes and feedbacks is necessary and for that, consistent and comprehensive measurements of the most important sea ice properties are required. While sea ice concentration is observed routinely year-round since the beginning of the satellite era, strategies to investigate the sea ice thickness distribution, crucially needed for an investigation of ice mass changes, has only recently been developed. To contribute to the interpretation of the remotely sensed sea ice thickness products, which are mainly based on freeboard determination from altimeter measurements, available airborne sea ice thickness and freeboard data have been collected within the Sea Ice Downstream Services for Arctic and Antarctic Users and Stakeholders (SIDARUS) EU-Project, and have been analyzed with respect to their usability for validation of the large scale satellite products. Thus, statistical parameters like the variability of freeboards within the common footprint areas of satellites have been analyzed from measurements made during the PAMARCMIP 2011 campaign to determine the differences between point measurements and areal averages. Also, impacts on the deviated sea ice thicknesses have been studied by means of a cross validation of freeboard-based sea ice thicknesses with airborne thickness measurements with electromagnetic induction sounding. Finally, since during the PAMARCMIP campaign few flights were performed in conjunction with CryoSat-2 overpasses, the airborne-based freeboards can finally be used for a comparison with satellite-derived data

Interannuelle und dekadische Variabilität von Drift, Konzentration und Dicke des Meereises im Weddellmeer

Sea ice concentrations in the Weddell Sea are subject to regional climate variability. The magnitude and origin of local trends in the sea ice coverage were studied using the bootstrap algorithm sea ice concentration data from the NSIDC for 1979-2006. The impact of atmospheric forcing such as air temperature, wind speed, sea level pressure and cloud coverage, gained from NCEP/NCAR reanalysis, was assessed by analyzing correlation coefficients between the respective atmospheric component and the sea ice concentrations. In addition, the variability of sea ice drift was analyzed using the Polar Pathfinder sea ice motion vectors, and the correlation with sea ice concentration was tested after an assessment of the product s uncertainties. The connection to the variability of sea ice thicknesses was derived by model simulations from the Finite Element Sea ice-Ocean Model (FESOM). It was found that sea ice concentrations increased in the eastern and decreased in the western Weddell Sea, predominantly in the marginal sea ice zone. There, and in coastal regions, temperatures are strongly negatively correlated to sea ice concentrations, whereas in the central Weddell Sea, mostly a positive correlation was assessed, especially during winter. From analyses of the wind field it was found that the prevailing westerlies at the Antarctic Peninsula frequently show a shift towards the south. The enhanced southward winds are expected to bring warmer air into the western and central Weddell Sea and are further expected to redistribute the sea ice from the west into the central and eastern regions. This would increase the sea ice concentrations in the central Weddell Sea due to enhanced compactness, although temperatures are increasing. The correlation between sea ice concentrations and sea ice drift is only robust for the central Weddell Sea, where both parameters are mainly anti-correlated. Hence, strong sea ice drift is connected to lower sea ice concentrations and vice versa. This finding is consistent with the connection to the wind fields, since stronger northerly winds would reduce the north-eastward drift of sea ice in this region and enhance the sea ice concentrations. From model simulations with FESOM it was found that sea ice thicknesses predominantly show the same tendencies for changes as the simulated sea ice concentrations, which are basically decreasing in the central Weddell Sea and increasing in the eastern Weddell Sea. The overall changes in sea ice thickness and concentration result in an increase of the total sea ice volume by 1 % per decade in the simulations. A sensitivity study with a free drift model, forced by 10-m wind speeds and ocean currents from FESOM showed that the trends in the modelled sea ice drift are driven by the atmospheric fields, since ocean currents show barely any trends. Further it was revealed that sea ice drift velocities in the model are overestimated, especially in the zonal direction. Nevertheless, despite the overestimation, the mean sea ice export rate of 22 x 10^3 m^3/s is only about half of the export rates found in previous studies, which is certainly an effect of underestimated sea ice thicknesses in the western Weddell Sea