Radiolarians of DSDP Site 136-842 and Hole 136-843C

Deep-sea cores recovered at Sites 842 and 843 on Leg 136 of the Ocean Drilling Program have yielded assemblages of Quaternary, Eocene, and Cretaceous radiolarians from the Hawaiian Arch region of the northern equatorial Pacific Ocean. Reddish-brown clays from Hole 842A (0-9.6 mbsf), Hole 842B (0-6.3 mbsf), and Hole 843C (0-4.2 mbsf) contain abundant and diverse assemblages of Quaternary radiolarians consisting of more than 80 species typical of the equatorial Pacific region. Quaternary radiolarians at these sites are assignable to the Quaternary Collosphaera tuberosa Interval Zone and Amphirhopalum ypsilon Interval Zone. The boundary between these zones cannot be determined precisely because of the rarity of zonal markers below surface sediments. Correlations have been made between radiolarian occurrences and magnetostratigraphic events elsewhere in the Pacific Ocean, but similar correlations are difficult at Sites 842 and 843 because of poor subsurface preservation. Chert samples collected from intervals in Cores 842B-10X and 842C-1W have yielded radiolarian ages of lower Cenomanian to Santonian and lower Cenomanian, respectively. Radiolarian assemblages in volcanic sand layers in Sections 6 and 7 of Core 842A-1H (7.5-9.6 mbsf) contain lower and middle Eocene radiolarians admixed with abundant Quaternary faunas. Reworked Eocene radiolarians appear to be restricted to thin layers of volcanic sands within the cores, suggesting deposition by turbidity currents.

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.

Granulometry of two sediment cores from Maxwell Bay, South Shetland Islands, West Antarctica

The climate evolution of the South Shetland Islands during the last c. 2000 years is inferred from the multiproxy analyses of a long (928 cm) sediment core retrieved from Maxwell Bay off King George Island. The vertical sediment flux at the core location is controlled by summer melting processes that cause sediment-laden meltwater plumes to form. These leave a characteristic signature in the sediments of NE Maxwell Bay. We use this signature to distinguish summer and winter-dominated periods. During the Medieval Warm Period, sediments are generally finer which indicates summer-type conditions. In contrast, during the Little Ice Age (LIA) sediments are generally coarser and are indicative of winter-dominated conditions. Comparison with Northern and Southern Hemisphere, Antarctic, and global temperature reconstructions reveals that the mean grain-size curve from Maxwell Bay closely resembles the curve of the global temperature reconstruction. We show that the medieval warming occurred earlier in the Southern than in the Northern Hemisphere, which might indicate that the warming was driven by processes occurring in the south. The beginning of the LIA appears to be almost synchronous in both hemispheres. The warming after the LIA closely resembles the Northern Hemisphere record which might indicate this phase of cooling was driven by processes occurring in the north. Although the recent rapid regional warming is clearly visible, the Maxwell Bay record does not show the dominance of summer-type sediments until the 1970s. Continued warming in this area will likely affect the marine ecosystem through meltwater induced turbidity of the surface waters as well as an extension of the vegetation period due to the predicted decrease of sea ice in this area.

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.

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.