ALBERT

Description: This is a compilation of all short-wave and long-wave radiation datasets from Reunion Island that were and are published in the frame of BSRN. New data will be added regularly. The data are subject to the data release guidelines of BSRN (https://bsrn.awi.de/data/conditions-of-data-release/).

Description: Upwelling systems are significant sources of atmospheric nitrous oxide (N₂O). The Benguela Upwelling System is one of the most productive regions worldwide and a temporally variable source of N₂O. Strong O₂ depletions above the shelf are favoring periodically OMZ formations. We aimed to assess underlying N₂O production and consumption processes on different temporal and spatial scales during austral winter in the Benguela Upwelling System, when O₂⁻deficiency in the water column is relatively low. The fieldwork took place during the cruise M157 (August 4ᵗʰ – September 16ᵗʰ 2019) onboard the R/V METEOR. This expedition included four close-coastal regions around Walvis Bay at 23°S, which presented the lowest O₂ concentrations near the seafloor and thus may provide hotspots of N₂O production. Seawater was collected in 10 L free-flow bottles by using a rosette system equipped with conductivity-temperature-depth (CTD) sensors (SBE 911plus, Seabird-electronics, USA).Seawater samples were collected from 10 L free-flow bottles bubble-free, filled into 200 mL serum bottles and immediately fixed with saturated mercury chloride (HgCl₂). Concentrations of dissolved N₂O were measured by a purge and trap system using a dynamic headspace (Sabbaghzadeh et al., 2021). The N₂O gas saturation (N₂Oₛₐₜ in %) was calculated from the concentration ratio between the seawater sample and seawater equilibrated with the atmosphere. ∆N₂O (N₂O saturation disequilibrium in nmol L⁻¹) was calculated as the difference between the measured N₂O concentration and the atmospheric equilibrium N₂O concentration using Bunsen solubility coefficient (Weiss and Price, 1980). AOU (apparent oxygen utilization in µmol L⁻¹) expresses the O₂ consumption by microbial respiration and was calculated as the difference between the equilibrated O₂ and observed O₂ concentration with the same physico-chemical properties (Weiss and Price, 1980).

Description: Upwelling systems are significant sources of atmospheric nitrous oxide (N₂O). The Benguela Upwelling System is one of the most productive regions worldwide and a temporally variable source of N₂O. Strong O₂ depletions above the shelf are favoring periodically OMZ formations. We aimed to assess underlying N₂O production and consumption processes on different temporal and spatial scales during austral winter in the Benguela Upwelling System, when O₂-deficiency in the water column is relatively low. The fieldwork took place during the cruise M157 (August 4ᵗʰ – September 16ᵗʰ 2019) onboard the R/V METEOR. This expedition included four close-coastal regions around Walvis Bay at 23°S, which presented the lowest O₂ concentrations near the seafloor and thus may provide hotspots of N₂O production. Seawater was collected in 10 L free-flow bottles by using a rosette system equipped with conductivity-temperature-depth (CTD) sensors (SBE 911plus, Seabird-electronics, USA). Concentrations of inorganic nutrients (PO₄³⁻, NH₄⁺, NO₃⁻, NO₂⁻, and SiO₂) were measured colorimetrically according to Grasshoff et al. (1999) by means of a continuous segmented flow analyzer (SEAL Analytical, QuAAtro39). To determine the water mass fractions along the sampling transects, vertical profiles were collected using a free-falling microstructure profiler (MSS90L, Sea & Sun Technology). Temperature, dissolved oxygen, and salinity were measured with a CTD system consisting of a SeaBird 911+ probe, mounted on a sampling rosette.

Description: Upwelling systems are significant sources of atmospheric nitrous oxide (N₂O). The Benguela Upwelling System is one of the most productive regions worldwide and a temporally variable source of N₂O. Strong O₂ depletions above the shelf are favoring periodically OMZ formations. We aimed to assess underlying N₂O production and consumption processes on different temporal and spatial scales during austral winter in the Benguela Upwelling System, when O₂-deficiency in the water column is relatively low. The fieldwork took place during the cruise M157 (August 4th – September 16th 2019) onboard the R/V METEOR. This expedition included four close-coastal regions around Walvis Bay at 23°S, which presented the lowest O₂ concentrations near the seafloor and thus may provide hotspots of N₂O production. Seawater was collected in 10 L free-flow bottles by using a rosette system equipped with conductivity-temperature-depth (CTD) sensors (SBE 911plus, Seabird-electronics, USA). Incubation experiments were performed using stable isotope ¹⁵N-tracers. Seawater samples for ¹⁵N-tracer incubations and natural abundance N₂O analysis were collected from 10 L free-flow bottles and filled bubble-free into 125 mL serum bottles. The samples for natural abundance N₂O analysis were immediately fixed with saturated HgCl₂ and stored in the dark. To perform the incubation, we added ¹⁵N-labeled NO₂-, NO₃⁻ and NH₄⁺ to estimate the in-situ N₂O production rates and associated reactions. To determine a single rate, the bottles were sacrificed after tracer addition, and within the time interval of 12 h, 24 h and 48 h by adding HgCl₂. Rates were calculated based on a linear regression over time. Total N₂O and natural abundance isotopologues of N₂O were analyzed by using an isotope ratio mass spectrometer (IRMS, Delta V Plus, Thermo Scientific). NO₂- production was additionally analyzed by transforming ¹⁵NO₂- to ¹⁵N₂O following the azide method after McIlvin & Altabet (2005) and the nitrogen isotope ratio of N₂O was measured by an IRMS. N₂ production was determined via an IRMS (Flash-EA-ConfloIV-DELTA V Advanced, Thermo Scientific) by injecting headspace from exetainers. The N₂O yield per nitrite produced and the N₂O yield during denitrification was calculated. Samples for natural abundance N₂O was sampled and measured in triplicates and is shown as an average with standard deviation (SD). In order to estimate the contribution of different N₂O producing pathways by major biological processes and the extent of N₂O reduction to N₂, the dual-isotope mapping approach was applied to natural abundance isotopologues of N₂O, which uses the relative position of background-subtracted N₂O samples in a δ¹⁵Nˢᴾ-N₂O vs. δ¹⁸O-N₂O diagram (Yu et al., 2020; Lewicka-Szczebak et al., 2020).

Description: Driven primarily by variations in the earth's axis wobble, tilt, and orbit eccentricity, our planet experienced massive glacial/interglacial reorganizations of climate and atmospheric CO2 concentrations during the Pleistocene (2.58 million years ago (Ma)–11.7 thousand years ago (ka)). Even after decades of research, the underlying climate response mechanisms to these astronomical forcings have not been fully understood. To further quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model version 1.2 (CESM1.2, ∼3.75∘ horizontal resolution), which covers the climatic history of the past 3 million years (3 Myr). In addition to the astronomical insolation changes, CESM1.2 is forced by estimates of CO2 and ice-sheet topography which were obtained from a simulation previously conducted with the CLIMBER-2 earth system model of intermediate complexity. Our 3 Ma simulation consists of 42 transient interglacial/glacial simulation chunks, which were partly run in parallel to save computing time. The chunks were subsequently merged, accounting for spin-up and overlap effects to yield a quasi-continuous trajectory. The computer model data were compared against a plethora of paleo-proxy data and large-scale climate reconstructions. For the period from the Mid-Pleistocene Transition (MPT, ∼1 Ma) to the late Pleistocene we find good agreement between simulated and reconstructed temperatures in terms of phase and amplitude (−5.7 ∘C temperature difference between Last Glacial Maximum and Holocene). For the earlier part (3–1 Ma), differences in orbital-scale variability occur between model simulation and the reconstructions, indicating potential biases in the applied CO2 forcing. Our model-proxy data comparison also extends to the westerlies, which show unexpectedly large variance on precessional timescales, and hydroclimate variables in major monsoon regions. Eccentricity-modulated precessional variability is also responsible for the simulated changes in the amplitude and flavors of the El Niño–Southern Oscillation. We further identify two major modes of planetary energy transport, which played a crucial role in Pleistocene climate variability: the first obliquity and CO2-driven mode is linked to changes in the Equator-to-pole temperature gradient; the second mode regulates the interhemispheric heat imbalance in unison with the eccentricity-modulated precession cycle. During the MPT, a pronounced qualitative shift occurs in the second mode of planetary energy transport: the post-MPT eccentricity-paced variability synchronizes with the CO2 forced signal. This synchronized feature is coherent with changes in global atmospheric and ocean circulations, which might contribute to an intensification of glacial cycle feedbacks and amplitudes. Comparison of this paleo-simulation with greenhouse warming simulations reveals that for an RCP8.5 greenhouse gas emission scenario, the projected global mean surface temperature changes over the next 7 decades would be comparable to the late Pleistocene glacial-interglacial range; but the anthropogenic warming rate will exceed any previous ones by a factor of ∼100.

Description: This data set is a higher-processing-level version of Geolocated sea-ice or snow surface elevation point clouds from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Jutila et al., 2022; doi:10.1594/PANGAEA.950509), where the surface elevation point cloud has been converted to freeboard using automatic open water detection scheme and projected onto a regular 0.5-meter grid. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The gridded data are stored in 30-second along-track segments in netCDF format. For the small scale grid flights, the data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. Open water points are identified to derive a freeboard estimate from the surface elevations. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate (grid pattern flights) or no freeboard (transects). The gridded 30-s segments include as data variables: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. In addition, list of detected open water points and an overview figure of each flight is provided.

Description: This data set provides high-resolution geolocated point clouds of sea-ice or snow surface elevation for mapping temporal and spatial evolution of sea-ice conditions such as freeboard, roughness, or the size and spatial distributions of surface features. The surface elevation data are referenced to the DTU21 mean sea surface height and are not corrected for sea-ice drift during acquisition. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (hdl:10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & hdl:10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The flights are both small scale, ~5x5 km grid patterns mainly over the central observatory, and large scale, few tens of km away from RV Polarstern, triangle patterns, or transects. The point cloud data are stored in 5-min along-track segments in a custom binary format, for which we provide a python-based parsing tool in awi-als-toolbox (https://github.com/awi-als-toolbox/awi-als-toolbox), together with corresponding metadata json and line-shot quicklook png files. The point cloud data includes as variables: surface elevation (referenced to DTU mean sea surface height), surface reflectance, and echo width. The degraded GPS altitude data 〉85°N may cause undulations in the along-track surface elevations, which are not corrected for in this data product.

Description: This data set is a higher-processing-level version of Gridded segments of sea-ice or snow surface elevation and freeboard from helicopter-borne laser scanner during the MOSAiC expedition, version 1 (Hutter et al., 2022; doi:10.1594/PANGAEA.950339), where the individual 30-second segments of the small scale grid flights have been combined into merged grids. The data were collected using a near-infrared, line-scanning Riegl VQ-580 airborne laser scanner (https://hdl.handle.net/10013/sensor.7ebb63c3-dc3b-4f0f-9ca5-f1c6e5462a31 & https://hdl.handle.net/10013/sensor.7a931b33-72ca-46d0-b623-156836ac9550) mounted in a helicopter along the MOSAiC drift from the north of the Laptev Sea, across the central Arctic Ocean, and towards the Fram Strait from September 2019 to October 2020. The merged data are stored in netCDF and geotiff format. The data are drift corrected using the position and heading data of RV Polarstern and elevation offset corrected using overlapping segments to overcome degraded GPS altitude data 〉85°N. For the flights with degraded GPS altitude quality, we provide only a freeboard estimate. The merged grids include all data variables of the gridded 30-s segments: surface elevation, freeboard (estimate), freeboard uncertainty, estimated sea surface height, surface reflectance, echo width, and number of points used in the interpolation. Also the calculated elevation offset correction term is provided for each flight as a csv file.

Description: pH values were obtained using a SBE18 pH sensor (Seabird) mounted on the remotely operated vehicle (ROV) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. The values were derived from the sensor voltages using the same calibration during the entire expedition.

Description: Nitrate and UV-absorbance spectra were measured by a SUNA V2 UV-spectrometer (Satlantic) mounted in the sensor skid of a remotely operated vehicle (ROV) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition between November 2019 and September 2020. Data use manufacturer calibration.