ALBERT

Description: We here report measured densities from a combination of records from the EastGRIP ice-core site. The data come from a trench and two ice cores: the shallow EGRIP-S6 core and the deep main core of the project. Based on these data, we parametrize the density as a function of depth, allowing us to provide a standard transfer function between true depth and ice-equivalent depth which is consistent with the EGRIP density measurements. EGRIP density data are only available to 117 m depth, at which depth the density is about 900 kg/m^3 and the difference between true depth and ice-equivalent depth is about 22 m. The density and overburden profiles have been extended below this depth and all the way to 1200 m in order to provide a convenient, continuous and (mostly) smooth transfer function between true depth and ice-equivalent depth. See PDF file provided under 'Documentation' for full description of data and parametrization.

Description: The Indian Summer Monsoon (ISM) with its rainfall is the lifeline for people living on the Indian subcontinent today and possibly was the driver of the rise and fall of early agricultural societies in the past. Intensity and position of the ISM have shifted in response to orbitally forced thermal land-ocean contrasts. At the northwestern monsoon margins, interactions between the subtropical westerly jet (STWJ) and the ISM constitute a tipping element in the Earth's climate system, because their non-linear interaction may be a first-order influence on rainfall. We reconstructed marine sea surface temperature (SST), supply of terrestrial material and vegetation changes from a very well-dated sediment core from the northern Arabian Sea to reconstruct the STWJ-ISM interaction. The Holocene record (from 11,000 years) shows a distinct, but gradual, southward displacement of the ISM in the Early to Mid-Holocene, increasingly punctuated by phases of intensified STWJ events that are coeval with interruptions of North Atlantic overturning circulation (Bond events). Effects of the non-linear interactions culminate between 4.6-3 ka BP, marking a climatic transition period during which the ISM shifted southwards and the influence of SWTJ became prominent. The lithogenic input shows an up to 4-fold increase after this time period signaling the strengthened influence of agricultural activities of the Indus civilization with enhanced erosion of soils amplifying the impact of Bond events and adding to the marine sedimentation rates adjacent to the continent.

Description: The data sets contains the age model as well as bulk organic and n-alkane data of sediment core GeoTü SL167 to reconstruct changes of the oxygen minimum zone strength for the late Quaternary. The age model is based on 14C AMS measurements of planktonic foraminifera and is calibrated with the BACON v. 2.5.6 software for R (Blauuw & Christen, 2011) and a marine reservoir age of ΔR = 93 ± 61 years. The ΔR is based on the weighted mean of two regional marine reservoir corrections (Muscat) by Southon et al. (2002) using the marine calibration database (Reimer and Reimer, 2001, http://calib.org/marine/). Total organic carbon and nitrogen measurements were carried out with an Euro EA3000 elemental analyser and δ15N measurements with a Thermo Scientific Flash EA1112 coupled to a Finnigan MAT 252 IRMS. Total organic carbon mass accumulation rates (TOC MAR) based on calculation using the organic carbon content and total mass accumulation rates. A description of the calculation of the total mass accumulations rates is given in Burdanowitz et al 2021. The measurements of n-alkanes were carried out using Thermo Scientific Trace 1310 GC-FID and Thermo Scientific DSQ II (GC-MS). Gravity core GeoTü SL167, was retrieved at station no. 960 during R.V. METEOR cruise M74/1b in 2007 (Bohrmann et al., 2010) from the northwestern Arabian Sea off Oman, at 22°37.2'N, 59°41.5'E, 774 m water depth, core recovery 7.39 m. The sediment core was retrieved for the reconstruction of circulation and productivity changes in the eastern Mediterranean Sea during the late Quaternary with particular focus on changes in the Indian monsoon system.

Description: Core MD95-2042 alkenone and GDGT data: This dataset provides the following information for core MD95-2042: depth, age, summed OH-GDGT, iGDGT, and di-unsaturated and tri-unsaturated C37 alkenone concentrations, OH-GDGT-based, iGDGT-based, and alkenone-based paleothermometric indices, GDGT-2/GDGT-3 ratio, and biomarker-based sea surface temperature (SST) and 0‐ to 200‐m sea temperature (subT; gamma function probability distribution for target temperatures with a = 4.5 and b = 15) estimates. Sediment samples were taken every 5 cm from core MD95-2042 and homogenized before lipid extraction. The lipid extracts were splitted into two fractions: one for alkenone analysis by gas chromatography coupled to a flame ionization detector, and the other for GDGT analysis by high-performance liquid chromatography coupled to mass spectrometry. All GDGT analyses were done in duplicate. The 1σ analytical uncertainties from 37 replicate analyses of the core catcher sample from core MD95-2042 are 0.007 (0.4 °C) for RI-OH, 0.008 (0.2 °C) for RI-OH′, 0.003 (0.2 °C) for TEX86, 0.238 for GDGT-2/GDGT-3, and 0.010 (0.26 °C) for UK′37. RI-OH′-SST estimates are from the following global calibration: SST = (RI-OH′ + 0.029)/0.0422 (Fietz et al., 2020). RI-OH-SST estimates are from the following global calibration: SST = (RI-OH − 1.11)/0.018 (Lü et al., 2015). TEX86H-SST estimates are from the following regional paleocalibration: SST = 68.4 × TEX86H + 33.0 (Darfeuil et al., 2016). UK′37-SST estimates are from the following global calibration: SST = 29.876 × UK′37 − 1.334 (Conte et al., 2006). Bayesian calibrations were also used for TEX86-SST and TEX86-subT estimates (BAYSPAR; Tierney & Tingley, 2014, 2015) and for UK′37-SST estimates (BAYSPLINE; Tierney & Tingley, 2018). Alkenone data covering the 160–70 and 70–0 ka BP periods are from Davtian et al. (2021) and Darfeuil et al. (2016), respectively. GDGT data covering the 160–45 ka BP period are from Davtian et al. (2021). The age model of core MD95-2042 for the 160–43 and 43–0 ka BP periods was obtained by tuning to Chinese speleothems (Cheng et al., 2016) and by recalibrating existing 14C ages with the Marine20 calibration curve (Heaton et al., 2020), respectively. MIS, Marine Isotope Stage; GDGT, glycerol dialkyl glycerol tetraether; and N/A, not available. Greenland atmospheric temperature record: This dataset consists in a composite Greenland atmospheric temperature record, which was built with the following records: the GISP2 atmospheric temperature record by Kobashi et al. (2017) for the 10–0 ka BP period, the NGRIP atmospheric temperature record by Kindler et al. (2014) for the 120–10 ka BP period, and the NEEM atmospheric temperature record by NEEM community members (2013) for the 129–120 ka BP period. The NEEM temperature anomalies obtained by NEEM community members (2013) were shifted by –31 °C to obtain absolute air temperatures. The employed age model is the one of Davtian and Bard (2023) for Greenland and Antarctic ice-core records. Antarctic δ18Oice and atmospheric temperature stacks: This dataset consists in two stacks of three Antarctic records (EDC, EDML, and WD), one for δ18Oice and the other for atmospheric temperature: both stacks are provided with their stacking uncertainties. To build the Antarctic δ18Oice stack, the Antarctic δ18Oice records were resampled every 10 years before centering to zero means and normalization to unit standard deviations over the 140–0 ka BP period (68–0 ka BP for WD). To optimize the continuity between the portions with and without the WD ice core, the Antarctic δ18Oice records were centered to zero means over the 68–67 ka BP period. The resulting Antarctic δ18Oice records were then averaged and stacking uncertainties were calculated as the pooled standard deviation of the stacked Antarctic δ18Oice records divided by the square root of the number of stacked Antarctic δ18Oice records. The final Antarctic δ18Oice stack, expressed in ‰, has the same standard deviation as the δ18Oice record from EDML over the 140–0 ka BP period, and has a zero mean over the 1–0 ka BP. The Antarctic atmospheric temperature stack was built like the Antarctic δ18Oice stack, except that the Antarctic δ18Oice records were corrected for seawater δ18Oice variations before conversion into atmospheric temperature. The employed age model is the one of Davtian and Bard (2023) for Greenland and Antarctic ice-core records.

Description: The Universität Hamburg is part of the environmental studies in the INDEX (Indian Ocean Exploration) program, which was established by the BGR (Federal Institute for Geosciences and Natural Resources), Hanover. The INDEX license area is located in the oligotrophic subtropical gyre of the South Indian Ocean. Sinking particulate matter samples were collected by sediment trap mooring 12-01 to measure vertical particle flux quantitatively and qualitatively. Mooring 12-01 was deployed during cruise SO259 (RV Sonne) and recovered during cruise PE446 (RV Pelagia).

Description: These data include salinity and oxygen isotope measurements of water samples collected from coastal sites along the Gulf of Maine between 2003 and 2015. In particular, a suite of samples were collected along the coast of Maine, east of Penobscot Bay, on a monthly basis between April 2014 and March 2015. These data also include several freshwater samples collected from the Kennebec and Penobscot Rivers on a semi-monthly basis in 2014 and 2015. For the water samples with sample IDs starting with DSW, JSW, NSW, or OSW: The water samples were collected by hand from shore or boat using French square glass bottles with phenolic polycone lined caps. Salinity was measured using a Oakton SALT 6+ handheld salinity meter. Oxygen isotopes were measured using a Picarro L2130-i Isotopic Liquid Water Analyzer with an attached autosampler. Water samples with sample IDs starting with ASW were collected from shore. Samples with sample IDs starting with DMC 2010 were collected at the flowing seawater laboratory at the Darling Marine Center. Samples with sample IDs starting with Summer 2011 were collected from a boat. For these last 3 sample types (ASW, DMC 2010, Summer 2011): Salinity was measured with YSI Professional Plus salinity meter and oxygen isotopes were measured using a Picarro L1102-i Isotopic Liquid Water Analyzer with an attached autosampler. Data from Owen et al., 2008 and Wanamaker et al. (2006, 2007) was collected from the flowing seawater laboratory at the Darling marine center. Salinity was measured using a YSI model 85 oxygen, conductivity, salinity, and temperature system and oxygen isotopes were measured using a dual-inlet VG/Micromass SIRA (CO2–H2O equilibration method at 30 °C for 12 h).