Helicopter-borne sea ice thickness measurements during cruises ARK-XX/2 and ARK-XXII/2 (SPACE) in the Arctic Ocean

Helicopter-borne electromagnetic sea ice thickness measurements were performed over the Transpolar Drift in late summers of 2001, 2004, and 2007, continuing ground-based measurements since 1991. These show an ongoing reduction of modal and mean ice thicknesses in the region of the North Pole of up to 53 and 44%, respectively, since 2001. A buoy derived ice age model showed that the thinning was mainly due to a regime shift from predominantly multi- and second-year ice in earlier years to first-year ice in 2007, which had modal and mean summer thicknesses of 0.9 and 1.27 m. Measurements of second-year ice which still persisted at the North Pole in April 2007 indicate a reduction of late-summer second-year modal and mean ice thicknesses since 2001 of 20 and 25% to 1.65 and 1.81 m, respectively. The regime shift to younger and thinner ice could soon result in an ice free North Pole during summer.

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.

Age and chemical composition of apatites from five DSDP and ODP Sites in the Pacific, Atlantic and Indian Oceans

Since studies on deep-sea cores were carried out in the early 1990s it has been known that ambient temperature may have a marked affect on apatite fission track annealing. Due to sluggish annealing kinetics, this effect cannot be quantified by laboratory annealing experiments. The unknown amount of low-temperature annealing remains one of the main uncertainties for extracting thermal histories from fission track data, particularly for samples which experienced slow cooling in shallow crustal levels. To further elucidate these uncertainties, we studied volcanogenic sediments from five deep-sea drill cores, that were exposed to maximum temperatures between ~10° and 70°C over geological time scales of ~15-120 Ma. Mean track lengths (MTL) and etch pit diameters (Dpar) of all samples were measured, and the chemical composition of each grain analyzed for age and track length measurements was determined by electron microprobe analysis. Thermal histories of the sampled sites were independently reconstructed, based on vitrinite reflectance measurements and/or 1D numerical modelling. These reconstructions were used to test the most widely used annealing models for their ability to predict low-temperature annealing. Our results show that long-term exposure to temperatures below the temperature range of the nominal apatite fission track partial annealing zone results in track shortening ranging between 4 and 11%. Both chlorine content and Dpar values explain the downhole annealing patterns equally well. Low chlorine apatite from one drill core revealed a systematic relation between Si-content and Dpar value. The question whether Si-substitution in apatite has direct and systematic effects on annealing properties however, cannot be addressed by our data. For samples, which remained at temperatures <30°C, and which are low in chlorine, the Laslett et al. [Laslett G., Green P., Duddy I. and Gleadow A. (1987) Thermal annealing of fission tracks in apatite. Chem. Geol. 65, 1-13] annealing model predicts MTL up to 0.6 µm longer than those actually measured, whereas for apatites with intermediate to high chlorine content, which experienced temperatures >30°C, the predictions of the Laslett et al. (1987) model agree with the measured MTL data within error levels. With few exceptions, predictions by the Ketcham et al. [Ketcham R., Donelick R. and Carlson W. (1999) Variability of apatite fission-track annealing kinetics. III: Extrapolation to geological time scales. Am. Mineral. 84/9, 1235-1255] annealing model are consistent with the measured data for samples which remained at temperatures below ~30°C. For samples which experienced maximum temperatures between ~30 and 70°C, and which are rich in chlorine, the Ketcham et al. (1999) model overestimates track annealing.

234Th and particulate fluxes in the Kara Sea in October 1993

The mean residence time of 234Th associated with suspended matter in the Kara Sea was calculated from distributions of dissolved and suspended 234Th. Integral particulate fluxes at different levels were estimated for two stations. The flux increases only in the pycnocline; below it changes insignificantly. Two maxima of differential fluxes are noted in vertical profiles: in the surface layer where primary production is maximal, and in the interface layer where zooplankton realizing active transport of suspended matter is usually concentrated. Differential fluxes were determined at 10 stations; their space distribution is controlled by primary production, which depends usually on turbidity of river water in estuaries.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) and Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic (2004-2012)

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2007

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2008

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Physical and chemical oceanography in the Arctic Ocean

Data from sections across the Eurasian Basin of the Arctic Ocean occupied by the German Research Vessel Polarstern in 1987 and by the Swedish icebreaker Oden in 1991 are used to derive information on the freshwater balance of the Arctic Ocean halocline and on the sources of the deep waters of the Nansen, Amundsen and Makarov basins. Salinity, d18O and mass balances allow separation of the river-runoff and the sea-ice meltwater fractions contained in the Arctic halocline. This provides the basis for tracking the river-runoff signal from the shelf seas across the central Arctic Ocean to Fram Strait. The halocline has to be divided into at least three lateral regimes: the southern Nansen Basin with net sea-ice melting, the northern Nansen Basin and Amundsen Basin with net sea-ice formation and increasing river-runoff fractions, and the Canadian Basin with minimum sea-ice meltwater and maximum river-runoff fractions and water of Pacific origin. In the Canadian Basin, silicate is used as a tracer to identify Pacific water entering through Bering Strait and an attempt is made to quantify its influence on the halocline waters of the Canadian Basin. For this purpose literature data from the CESAR and LOREX ice camps are used. Based on mass balances and depending on the value of precipitation over the area of the Arctic Ocean the average mean residence time of the river-runoff fraction contained in the Arctic Ocean halocline is determined to be about 14 or 11 years. Water column inventories of river-runoff and sea-ice meltwater are calculated for a section just north of Fram Strait and implications for the ice export rate through Fram Strait are discussed. Salinity, tritium, 3He and the d18O ratio of halocline waters sampled during the 1987 Polarstern cruise to the Nansen Basin are used to estimate the mean residence time of the river-runoff component in the halocline and on the shelves of the Arctic Ocean. These estimates are done by comparing ages of the halocline waters based on a combination of tracers yielding different time information: the tritium 'vintage' age which records the time that has passed since the river-runoff entered the shelf and the tritium/3He age which reflects the time since the shelf waters left the shelf. The difference between the ages determined by these two methods is about 3 to 6 years. Correction for the initial tritium/3He age of the shelf waters (about 0.5 to 1.5 years) yields a mean residence time of the river-runoff on the shelves of about 3.5 ± 2 years. Comparison of the 18O/16O ratios of shelf water, Atlantic water and the deep waters of the Arctic Ocean indicate that the sources of the deep and bottom waters of the Eurasian Basin are located in the Barents and Kara seas.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2011

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.