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We combine consistently dated benthic carbon isotopic records distributed over the entire Atlantic Ocean with numerical simulations performed by a glacial configuration of the Norwegian Earth System Model with active ocean biogeochemistry, in order to interpret the observed Cibicides δ13C changes at the stadial-interstadial transition corresponding to the end of Heinrich Stadial 4 (HS4) in terms of ocean circulation and remineralization changes. We show that the marked increase in Cibicides δ13C observed at the end of HS4 between ~2000 and 4200 m in the Atlantic can be explained by changes in nutrient concentrations as simulated by the model in response to the halting of freshwater input in the high latitude glacial North Atlantic. Our model results show that this Cibicides δ13C signal is associated with changes in the ratio of southern-sourced (SSW) versus northern-sourced (NSW) water masses at the core sites, whereby SSW is replaced by NSW as a consequence of the resumption of deep water formation in the northern North Atlantic and Nordic Seas after the freshwater input is halted. Our results further suggest that the contribution of ocean circulation changes to this signal increases from ~40 % at 2000 m to ~80 % at 4000 m. Below ~4200 m, the model shows little ocean circulation change but an increase in remineralization across the transition marking the end of HS4. The simulated lower remineralization during stadials than interstadials is particularly pronounced in deep subantarctic sites, in agreement with the decrease in the export production of carbon to the deep Southern Ocean during stadials found in previous studies.

Increasing upwelling intensity and shoaling of the oxygen minimum zone (OMZ) is projected for Eastern Boundary Upwelling Systems (EBUSs) under ocean warming which may have severe consequences for mesopelagic food webs, trophic transfer, and fish production also in the Humboldt Current Upwelling System (HUS). To improve our mechanistic understanding, from February 23, 2017 until April 14, 2017 we performed a 50 days mesocosm experiment in the northern HUS (off Callao Bay, Peru) and monitored the zooplankton development prior to and following a simulated upwelling event through the addition of deeper water of two different OMZ-influenced subsurface waters to four of in total eight mesocosms. To elucidate plankton dynamics and trophic relationships, we followed the temporal development of the mesozooplankton community in relation to that of phytoplankton, analyzed the fatty acid composition and gut fluorescence of dominant copepods, and determined the stable isotope (SI) and elemental composition (C:N) of dominant zooplankton taxa. Zooplankton samples were collected from the mesocosms over the entire experiment duration using an Apstein net (17 cm diameter, 100 µm mesh) to determine abundance and taxonomic composition of the zooplankton community, and to analyze fatty acid composition, gut fluorescence and elemental composition of dominant zooplankton. Furthermore, abundance and biomass of zooplankton groups was estimated from scanned ZooScan images.

Particle size distribution data was collected during multiple cruises globally with several regularly intercalibrated Underwater Vision Profilers, Version 5 (UVP5; Picheral et al 2010). During the respective cruises, the UVP5 was mounted on the CTD-Rosette or as a standalone instrument and deployed in vertical mode. The UVP5 takes pictures of an illuminated watervolume of about 1 Liter every few milliseconds. Imaged items are counted, their size measured and abundance and biovolume of the particles is calculated. For different size bins, this information is summarized in the columns "Particle concentration" and "Particle biovolume". For further details please refer to Kiko et al. (in prep.) "A global marine particle size distribution dataset obtained with the Underwater Vision Profiler 5".

Rivers are major pathways of plastics from lands into the Ocean. However, there is still a huge lack of knowledge on how riverine litter, including macroplastics, is transferred into the Ocean. Quantitative measurements of macroplastic emissions in rivers even suggest that a small fraction (0.001 to 3%) of the Mismanaged Plastic Waste (MPW) generated within a river basin finally reach the sea. Instead, macroplastics may remain within the catchment and on coastlines because of complex transport dynamics that delay the transfer of plastic debris. In order to better understand those dynamics, we performed tracking of riverine litter over time. First, hundreds of date-prints items were collected on riverbanks in the Seine estuary. The distribution of their Use-By-Dates suggest that riverine litter may remain stored on riverbanks for decades. Second, we performed real time tracking of floating and sub-floating bottles using GPS-trackers. Between March 2018 and April 2019, 39 trajectories were recorded in the estuary under tidal influence and 11 trajectories upriver, covering a wide range of hydrometeorological conditions. Results show a succession of stranding/remobilization episodes in combination with alternating upstream and downstream transport in the estuary related to tides. In the end, tracked bottles systematically stranded somewhere, for hours to weeks, from one to several times on different sites. The overall picture shows that different hydrometeorological phenomena interact with various time scales ranging from hours/days (high/low tides) to weeks/months (spring/neap tides and highest tides) and years (seasonal river flow, vegetation and geomorphological aspects). Thus, the fate of plastic debris is highly unpredictable with a chaotic-like transfer of plastic debris into the Ocean. The residence time of these debris is much longer than the transit time of water. This offers the opportunity to collect them before they get fragmented and/or reach the Sea.

Eight overlapping sediment cores, representing an approximately 6.6 m–long composite sequence, were collected on March 24, 2013 from Lake Malaya Chabyda in Central Yakutia (exact coring location 61°57.509' 129°24.500'). Sampling was conducted during a German–Russian Expedition (“Yakutia 2013”) as a cooperation between the North Eastern Federal State University in Yakutsk (NEFU) and the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI). To penetrate ca. 1 m of lake ice cover, 250-mm-diameter holes were drilled using a hand-held Jiffy ice auger. Water depth was measured using an Echo sounder (HONDEX PS-7 LCD) and a calibrated rope for verification. 100 cm-long parallel cores were collected at 2 m water depth using a Russian peat corer and supported by an UWITEC gravity coring system. Cores were stored in waterproof sealed, transparent PVC plastic tubes in cool and dark conditions. After the field season, the cores were transported to Potsdam, Germany and stored at 4°C in the cold rooms at AWI. The cores did not experience any visible drying or surface oxidation during storage. High–resolution X–ray fluorescence (XRF) analyses were carried out with 10 mm resolution on the entire sequence using an Avaatech XRF core scanner at AWI (Bremerhaven, Germany) with a Rh X-ray tube at 10 kV (without filter, 12 s, 1.5 mA) and 30 kV (Pd-thick filer, 15 s, 1.2 mA). The sediment surface was cleaned, leveled, and covered with a 4µm ultralene foil to avoid sediment desiccation prior to XRF scanning. Individual element counts per second (CPS) were transformed using a centered log transformation (CLR) and element ratios were transformed using an additive log ratio (ALR) to account for compositional data effects and reduce effects from variations in sample density, water content, and grain size. Statistical analysis was completed using the Python programming language (Python Software Foundation, https://www.python.org/). XRF analysis of the sequence indicated 24 detectable elements and a subset of these were selected for analysis based on low element χ2 values. These selected elements include the major rock forming elements of Silicon (Si) (Chi2 1.4), Calcium (Ca) (Chi2 6.3), Titanium (Ti) (Chi2 1.3), Rubidium (Rb) (Chi2 0.6), Strontium (Sr) (Chi2 0.7), Zircon (Zr) (Chi2 0.6) and the redox sensitive, productivity indicating elements of Manganese (Mn) (Chi2 1.3), Iron (Fe) (Chi2 2.5), and Bromine (Br) (Chi2 0.8). All subsequent analyses took place after the extracted subsamples had been freeze–dried until completely dry (approximately 48 hours). Grain size analysis was conducted on 18 samples that were chosen to span the entire sequence at relatively regular intervals. The samples were first treated for five weeks with H2O2 (0.88 M) in order to isolate clastic material. After treatment, seven samples were eliminated from the analysis because the remaining inorganic sediment fraction was too low for detection by the laser grain size analyzer. The remaining samples were homogenized using an elution shaker for 24 h and then analyzed using a Malvern Mastersizer 3000 laser. Standard statistical parameters (mean, median, mode, sorting, skewness, and kurtosis) were determined using GRADISTAT 9.1. Total carbon (TC), total organic carbon (TOC), and total nitrogen (TN) analyses were completed after the freeze–dried subsamples were ground in a Pulverisette 5 (Fritsch) planetary mill at 3000 rpm for 7 minutes. TC and TN were measured in a carbon–nitrogen–sulphur analyzer (Vario EL III, Elementar). Five mg of sample material were encapsulated in tin (Sn) capsules together with 10 mg of tungsten–(VI)–oxide. The tungsten–(VI)–oxide ensures complete oxidation of the sample during the measurement process. Duplicate capsules were prepared and measured for each subsample. Blanks and calibration standards were placed every 15 samples to ensure analytical accuracy (< ± 0.1 wt%). Between each sample spatula was cleaned with KIMTECK fuzz-free tissues and isopropyl. Analysis of TOC began by removing the inorganic carbon fraction by placing each subsample in a warm hydrochloric acid solution (1.3 molar) for at least three hours and then transferring the sample to a drying oven. The TC measured for each subsample in the previous analysis was used to determine the amount of sample required for the TOC analysis. The appropriate amount of sample was weighted in a ceramic crucible and analyzed using the Vario Max C, Elementar. The TOC/TN ratio was converted to the TOC/TNatomic ratio by multiplying the TOC/TN ratio by 1.167 (atomic weight of carbon and nitrogen). Total inorganic carbon (TIC) analysis was completed using a Vario SoilTOC cube elemental analyzer after combustion at 400ºC (TOC) and 900ºC (TIC) (Elementar Corp., Germany). Calculation of δ13C was completed twice for a subset of samples using two different methodologies. The analysis completed at the AWI Potsdam ISOLAB Facility removed carbonate by treating the samples with hydrogen chloride (12 M HCl) for three hours at 97 °C, then adding purified water and decanting and washed three times. Once the chloride content was below 500 parts per million (ppm), the samples were filtered over a glass microfiber (Whatman Grade GF/B, nominal particle retention of 1.0 µm). The residual sample was dried overnight in a drying cabinet at 50°C. The dry samples were manually ground for homogenization and weighted into tin capsules and analyzed using a ThermoFisher Scientific Delta–V–Advantage gas mass spectrometer equipped with a FLASH elemental analyzer EA 2000 and a CONFLO IV gas mixing system. In this system, the sample is combusted at 1020°C in O2 atmosphere so that the OC is quantitatively transferred to CO2, after which the isotope ratio is determined relative to a laboratory standard of known isotopic composition. Capsules for control and calibration were run in between. The isotope composition is given in permil (‰) relative to Vienna Pee Dee Belemnite (VPDB). The analysis of a small subset of samples which took place at Laboratoire des sciences du climat et de l'environnement Isotopic Laboratory for methodological comparison underwent a slightly different treatment, as follows. The sediment underwent a soft leaching process to remove carbonate using pre-combusted glass beakers, HCl 0.6N at room temperature, ultra-pure water and drying at 50 C. The samples were then crushed in a pre-combusted glass mortar for homogenization prior to carbon content and δ13 C analysis. The handling and chemical procedures are common precautions employed with low-carbon-content sediments. Analysis was performed online using a continuous flow EA-IRMS coupling, that is, a Fisons Instrument NA 1500 Element Analyzer coupled to a ThermoFinigan Delta+XP Isotope-Ratio Mass Spectrometer. Two in-house standards (oxalic acid, δ13C =−19.3% and GCL, _13C =−26.7 %) were inserted every five samples. Each in-house standard was regularly checked against international standards. The measurements were at least triplicated for representativeness. The external reproducibility of the analysis was better than 0.1 %, typically 0.06 %. Extreme values were checked twice. Those samples for which the carbonate was leeched at the room temperature, with lower HCl concentration (0.6N), and without a filtration step (samples analyzed at Laboratoire des sciences du climat et de l'environnement Isotopic Laboratory) had δ13C values 0.1‰ to 1.0‰ (average 0.5‰) higher than the samples treated at the higher temperature (97.7 ºC). However, the plotted δ13C curve is nearly identical for the subset of samples which were subjected to both treatments. There is some heterogeneity in the amount of offset between the two treatment methods. This might be related to an asymmetrical distribution of hot acid-soluble organic compounds throughout the sediment core. A correction of ca. +0.5‰ was applied to the results of the high temperature treatment. These values were then combined with the low temperature results to provide a complete dataset for the whole core. The standard deviation (1σ) is generally better than δ13C = ±0.15‰.

The shallower oxygen-poor water masses of the ocean confine a majority of the microbial communities that can produce up to 90 % of oceanic N2. This effective N2-yielding section encloses a suspended small-particle layer, inferred from particle backscattering (bbp) measurements. It is thus hypothesized that this layer (hereafter, the bbp-layer) is linked to microbial communities involved in N2 yielding such as nitrate-reducing SAR11 as well as sulfur-oxidizing, anammox, and denitrifying bacteria – a hypothesis yet to be evaluated. Here, data collected by three BGC-Argo floats deployed in the Black Sea are used to investigate the origin of this bbp-layer. To this end, we evaluate how the key drivers of N2-yielding bacteria dynamics impact the vertical distribution of bbp and the thickness of the bbp-layer. In conjunction with published data on N2 excess, our results suggest that the bbp-layer is at least partially composed of the bacteria driving N2 yielding for three main reasons: (1) strong correlations are recorded between bbp and nitrate; (2) the top location of the bbp-layer is driven by the ventilation of oxygen-rich subsurface waters, while its thickness is modulated by the amount of nitrate available to produce N2; and (3) the maxima of both bbp and N2 excess coincide at the same isopycnals where bacteria involved in N2 yielding coexist. We thus advance that bbp and O2 can be exploited as a combined proxy to delineate the N2-yielding section of the Black Sea. This proxy can potentially contribute to refining delineation of the effective N2-yielding section of oxygen-deficient zones via data from the growing BGC-Argo float network.

As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.

We present the first high-resolution measurements of pollutant trace gases in the Asian summer monsoon upper troposphere and lowermost stratosphere (UTLS) from the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) during the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) campaign based in Kathmandu, Nepal, 2017. Measurements of peroxyacetyl nitrate (PAN), acetylene (C2H2), and formic acid (HCOOH) show strong local enhancements up to altitudes of 16 km. More than 500 pptv of PAN, more than 200 pptv of C2H2, and more than 200 pptv of HCOOH are observed. Air masses with increased volume mixing ratios of PAN and C2H2 at altitudes up to 18 km, reaching to the lowermost stratosphere, were present at these altitudes for more than 10 d, as indicated by trajectory analysis. A local minimum of HCOOH is correlated with a previously reported maximum of ammonia (NH3), which suggests different washout efficiencies of these species in the same air masses. A backward trajectory analysis based on the models Alfred Wegener InsTitute LAgrangian Chemistry/Transport System (ATLAS) and TRACZILLA, using advanced techniques for detection of convective events, and starting at geolocations of GLORIA measurements with enhanced pollution trace gas concentrations, has been performed. The analysis shows that convective events along trajectories leading to GLORIA measurements with enhanced pollutants are located close to regions where satellite measurements by the Ozone Monitoring Instrument (OMI) indicate enhanced tropospheric columns of nitrogen dioxide (NO2) in the days prior to the observation. A comparison to the global atmospheric models Copernicus Atmosphere Monitoring Service (CAMS) and ECHAM/MESSy Atmospheric Chemistry (EMAC) has been performed. It is shown that these models are able to reproduce large-scale structures of the pollution trace gas distributions for one part of the flight, while the other part of the flight reveals large discrepancies between models and measurement. These discrepancies possibly result from convective events that are not resolved or parameterized in the models, uncertainties in the emissions of source gases, and uncertainties in the rate constants of chemical reactions.

Upper suboxic water masses confine a majority of the microbial communities that can produce up to 90 % of oceanic N2. This effective N2-yielding section encloses a suspended small-particle layer, inferred from particle backscattering (bbp) measurements. It is thus hypothesized that this layer (hereafter, the bbp-layer) is linked to N2-yielding microbial communities such as anammox and denitrifying bacteria – a hypothesis yet to be evaluated. Here, data collected by three BGC-Argo floats deployed in the Black Sea are used to investigate the origin of this bbp-layer. To this end, we evaluate how key drivers of anammox-denitrifying bacteria dynamics impact on the vertical distribution of bbp and the thickness of the bbp-layer. In conjunction with published data on N2 excess, our results suggest that the bbp-layer is at least partially composed of anammox-denitrifying bacteria for three main reasons: (1) strong correlations are recorded between bbp and nitrate; (2) the top location of the bbp-layer is driven by the ventilation of oxygen-rich subsurface waters, while its thickness is modulated by the amount of nitrate available to produce N2; (3) the maxima of both bbp and N2 excess coincide at the same isopycnals where denitrifying-anammox bacteria coexist. We thus advance that bbp and O2 can be exploited as a combined proxy to delineate the N2-yielding section of the Black Sea. This proxy can potentially contribute to refining delineation of the effective N2-yielding section of oxygen-deficient zones via data from the growing BGC-Argo float network.

In the framework of the EU-FP7 BACCHUS (impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) project, an intensive field campaign was performed in Cyprus (March 2015). Remotely piloted aircraft system (RPAS), ground-based instruments, and remote-sensing observations were operating in parallel to provide an integrated characterization of aerosol–cloud interactions. Remotely piloted aircraft (RPA) were equipped with a five-hole probe, pyranometers, pressure, temperature and humidity sensors, and measured vertical wind at cloud base and cloud optical properties of a stratocumulus layer. Ground-based measurements of dry aerosol size distributions and cloud condensation nuclei spectra, and RPA observations of updraft and meteorological state parameters are used here to initialize an aerosol–cloud parcel model (ACPM) and compare the in situ observations of cloud optical properties measured by the RPA to those simulated in the ACPM. Two different cases are studied with the ACPM, including an adiabatic case and an entrainment case, in which the in-cloud temperature profile from RPA is taken into account. Adiabatic ACPM simulation yields cloud droplet number concentrations at cloud base (approximately 400 cm−3) that are similar to those derived from a Hoppel minimum analysis. Cloud optical properties have been inferred using the transmitted fraction of shortwave radiation profile measured by downwelling and upwelling pyranometers mounted on a RPA, and the observed transmitted fraction of solar radiation is then compared to simulations from the ACPM. ACPM simulations and RPA observations shows better agreement when associated with entrainment compared to that of an adiabatic case. The mean difference between observed and adiabatic profiles of transmitted fraction of solar radiation is 0.12, while this difference is only 0.03 between observed and entrainment profiles. A sensitivity calculation is then conducted to quantify the relative impacts of 2-fold changes in aerosol concentration, and updraft to highlight the importance of accounting for the impact of entrainment in deriving cloud optical properties, as well as the ability of RPAs to leverage ground-based observations for studying aerosol–cloud interactions.