Solar radiation over and under sea ice and photographic quantification of Ice algal aggregates during the POLARSTERN cruise ARK-XXVII/3 (IceArc) in summer 2012

The ice cover of the Arctic Ocean has been changing dramatically in the last decades and the consequences for the sea-ice associated ecosystem remain difficult to assess. Algal aggregates underneath sea ice have been described sporadically but the frequency and distribution of their occurrence is not well quantified. We used upward looking images obtained by a remotely operated vehicle (ROV) to derive estimates of ice algal aggregate biomass and to investigate their spatial distribution. During the IceArc expedition (ARK-XXVII/3) of RV Polarstern in late summer 2012, different types of algal aggregates were observed floating underneath various ice types in the Central Arctic basins. Our results show that the floe scale distribution of algal aggregates in late summer is very patchy and determined by the topography of the ice underside, with aggregates collecting in dome shaped structures and at the edges of pressure ridges. The buoyancy of the aggregates was also evident from analysis of the aggregate size distribution. Different approaches used to estimate aggregate biomass yield a wide range of results. This highlights that special care must be taken when upscaling observations and comparing results from surveys conducted using different methods or on different spatial scales.

Solar irradiance over and under seasonal land-fast sea ice off Barrow, Alaska, in 2010

The amount of solar radiation transmitted through Arctic sea ice is determined by the thickness and physical properties of snow and sea ice. Light transmittance is highly variable in space and time since thickness and physical properties of snow and sea ice are highly heterogeneous on variable time and length scales. We present field measurements of under-ice irradiance along transects under undeformed land-fast sea ice at Barrow, Alaska (March, May, and June 2010). The measurements were performed with a spectral radiometer mounted on a floating under-ice sled. The objective was to quantify the spatial variability of light transmittance through snow and sea ice, and to compare this variability along its seasonal evolution. Along with optical measurements, snow depth, sea ice thickness, and freeboard were recorded, and ice cores were analyzed for chlorophyll a and particulate matter. Our results show that snow cover variability prior to onset of snow melt causes as much relative spatial variability of light transmittance as the contrast of ponded and white ice during summer. Both before and after melt onset, measured transmittances fell in a range from one third to three times the mean value. In addition, we found a twentyfold increase of light transmittance as a result of partial snowmelt, showing the seasonal evolution of transmittance through sea ice far exceeds the spatial variability. However, prior melt onset, light transmittance was time invariant and differences in under-ice irradiance were directly related to the spatial variability of the snow cover.

(Table 2) Organic residue at DSDP Hole 76-534A

The kind, sedimentation rate, and diagenesis of organic particles delivered to the North Atlantic seafloor during the Middle Jurassic-Early Cretaceous were responsible for the presence of carbonaceous sediments in Hole 534A. Organic-rich black clays formed from the rapid supply of organic matter; this organic matter was composed of either abundant, well-preserved, and poorly sorted particles of land plants deposited in clays and silty clays within terrigenous turbiditic sequences (tracheal facies) or abundant amorphous debris (xenomorphic facies) generated through the digestive tracts of marine zooplankton and sedimented as fecal pellets. Evidence for the fecal-pellet origin of xenomorphic debris is illustrated. Black clays were also produced in sediments containing less organic matter as a result of the black color of carbonized particles composing all or most of the residues (micrinitic facies). Slowly sedimented hematitic Aptian clays contain very little carbonized, organic debris that survived diagenetic oxidation. In the red calcareous clay sequence of the Late Jurassic, larger amounts of this oxidized debris turned several clay layers black or blackish red. Carbonized debris also dominates the residues recovered in interbedded black and green Albian clays. Carbonization of organic matter in these sediments either turned them black or provided the diagenetic environment for reduced iron. Carbonized debris is also appreciable in burrow-mottled black-green Kimmeridgian clay. The study of Hole 534A organic matter indicates that during the middle Callovian there was a rapid supply of terrigenous organic matter, followed by a late Callovian episode of rapidly supplied xenomorphic debris deposited as fecal pellets. The Late Jurassic-Berriasian was a time of slower sedimentation of organic matter, primarily of a marine dinoflagellate flora in a poorly preserved xenomorphic facies variously affected by diagenetic oxidation. Several intervals of carbonized tracheal tissue in the Oxfordian and Kimmeridgian suggest episodes of oxidized terrigenous matter. The same sequence of Callovian organic events is evident in much of the Early Cretaceous

Particulate and phytoplankton absorption during POLARSTERN cruises ANT-XXVI/3 and ANT-XXVIII/3

The euphotic depth (Zeu) is a key parameter in modelling primary production (PP) using satellite ocean colour. However, evaluations of satellite Zeu products are scarce. The objective of this paper is to investigate existing approaches and sensors to estimate Zeu from satellite and to evaluate how different Zeu products might affect the estimation of PP in the Southern Ocean (SO). Euphotic depth was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Zeu-Chla) and (ii) inherent optical properties (Zeu-IOP). They were compared with in situ measurements of Zeu from different regions of the SO. Both approaches and sensors are robust to retrieve Zeu, although the best results were obtained using the IOP approach and SeaWiFS data, with an average percentage of error (E) of 25.43% and mean absolute error (MAE) of 0.10 m (log scale). Nevertheless, differences in the spatial distribution of Zeu-Chla and Zeu-IOP for both sensors were found as large as 30% over specific regions. These differences were also observed in PP. On average, PP based on Zeu-Chla was 8% higher than PP based on Zeu-IOP, but it was up to 30% higher south of 60°S. Satellite phytoplankton absorption coefficients (aph) derived by the Quasi-Analytical Algorithm at different wavelengths were also validated and the results showed that MODIS aph are generally more robust than SeaWiFS. Thus, MODIS aph should be preferred in PP models based on aph in the SO. Further, we reinforce the importance of investigating the spatial differences between satellite products, which might not be detected by the validation with in situ measurements due to the insufficient amount and uneven distribution of the data.

Accumulation rates for western Dronning Maud Land from firn cores and snow pits

As a result of intensive field activities carried out by several nations over the past 15 years, a set of accumulation measurements for western Dronning Maud Land, Antarctica, was collected, based on firn-core drilling and snow-pit sampling. This new information was supplemented by earlier data taken from the literature, resulting in 111 accumulation values. Using Geographical Information Systems software, a first region-wide mean annual snow-accumulation field was derived. In order to define suitable interpolation criteria, the accumulation records were analyzed with respect to their spatial autocorrelation and statistical properties. The resulting accumulation pattern resembles well known characteristics such as a relatively wet coastal area with a sharp transition to the dry interior, but also reveals complex topographic effects. Furthermore, this work identifies new high-return shallow drilling sites by uncovering areas of insufficient sampling density.