Sea surface salinity (SSS) is the least constrained major variable of the past (paleo) ocean but is fundamental in controlling the density of seawater and thus large-scale ocean circulation. The hydrogen isotopic composition (δD) of non-exchangeable hydrogen of algal lipids, specifically alkenones, has been proposed as a promising new proxy for paleo SSS. The δD of surface seawater is correlated with SSS, and laboratory culture studies have shown the δD of algal growth water to be reflected in the δD of alkenones. However, a large-scale field study testing the validity of this proxy is still lacking. Here we present the δD of open-ocean Atlantic and Pacific surface waters and coincident δD of alkenones sampled by underway filtration. Two transects of approximately 100° latitude in the Atlantic Ocean and more than 50° latitude in the Western Pacific sample much of the range of open ocean salinities and seawater δD, and thus allow probing the relationship between δD of seawater and alkenones. Overall, the open ocean δD alkenone data correlate significantly with SSS, and also agree remarkably well with δD water vs δD alkenone regressions developed from culture studies. Subtle deviations from these regressions are discussed in the context of physiological factors as recorded in the carbon isotopic composition of alkenones. In a best-case scenario, the data presented here suggest that SSS variations as low as 1.2 can be reconstructed from alkenone δD.
Alkenone core top data (UK'37, UK'38ME, UK'38ET, UE'36OME, K38ME/K37, K37/K38) from 168 samples that span a geographic region from from 76.75°N -76.5°S and 178.8E-179.6W. Data were collected for calibration of alkenone indices to sea surface temperature. Also included are alkenone data (UK'37, UK'38ME, and SST estimates) from 12 early Pliocene age samples from ODP sites 1143 and 806, which were collected to constrain the behavior of UK'38ME relative to UK'37 at warmer than modern ocean SSTs. Data were collected via gas chromatography-flame ionization detection Agilent 214 7890N Series instrument with splitless injection and Restek Rtx-200 ms (105 m x 250 µm x 0.25 x 215 µm) poly(triflouropropylmethylsiloxane) stationary phase semi-polar column.
Im Rahmen des Projektes CAHOL soll aufbauend auf unseren vorherigen Ergebnissen und in enger Kooperation mit unseren Partnern das Holozäne Klima Zentralasiens rekonstruiert werden. Am MPI wird dazu das Leitprofil des Chatyr Kul - Sees in SE-Kirgisistan bearbeitet. Abrupte Klimaänderungen ('Tipping-Points') an denen rasche Änderungen von Temperaturen, Niederschlägen und Niederschlagsquellen aufgetreten sind, sollen mittels organisch-geochemischer Biomarker der Seesedimente und deren Isotopenverhältnissen unter Anwendung neuer statistischer Verfahren identifiziert werden. Im Vergleich mit regionalen Rekords werden lokale von regionalen Signalen differenziert und gehen final zusammen mit Indikationen weiterer Analysen in Klimasimulationen ein. Ziel der Untersuchungen ist das Auftreten früher Warnsignale und das Passieren von Schwellwerten ('thresholds') im Vorlauf identifizierter Tipping-Points zu identifizieren. Final soll ein neues Verständnis der Zusammenhänge hemisphärischer und globaler Faktoren auf das Klima Zentralasiens während des gesamten Holozäns erreicht werden. Am hochaufgelöste laminierte Klimaarchiv des 'Chatyr Kul - See' werden Alkenone und GDGT's als Temperaturproxies und Wasserstoff und Kohlenstoffisotope an terrestrischen und aquatischen Biomarkern zur Rekonstruktion des Wasserkreislaufs untersucht. Hierzu werden an identifizierten Kippunkten hochauflösende Analysen eingesetzt, um die zeitliche Abfolge von Ereignissen zu fassen und ein mechanistisches Verständnis der Abläufe zu erhalten. Basieren auf der sehr guten Datenlage aus dem abgeschlossenen TIP Projekt für Wasserstoffisotope vom Tibetischen Plateau und den marinen Ergebnissen aus WP2 und 3 sowie den bereits publizierten Arbeiten aus anderen Klimaarchiven soll der räumliche Zusammenhang der Ergebnisse gefasst werden. Hierzu sollen vor allem multivariate statistische Verfahren (Ordinationsverfahren, Distanzmatrizen, Autokorrelationen und Crosskorrelationen) eingesetzt werden.
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.
Here we compiled stable carbon isotope data from 23 ODP sites in the Atlantic and Pacific, binned by marine isotope stage.Stable carbon isotope data were binned and averaged according to the marine isotope age assignments in the LR04 and the reported ages of the samples from each site. Only Cibicidoides wuellerstorfi values were used, although sometimes measured species was not reported for each sample by the original publication. Please note that some sites have data originating from multiple publications. Calculated values for whole basin δ13C of dissolved inorganic carbon, calculated Δδ13C, and associated uncertainties from the values compiled in MPWP_benthic_isotope_data_compilation. Benthic δ13C data from all sites below 2000 meters water depth were binned by marine isotope stage as defined by the age bounds provided with the LR04 stack. Because of our focus on specific MIS events, sedimentary records with low-resolution age models were excluded. All data are derived from Cibicidoides wuellerstorfi. In datasets composed of isotope measurements of two or more benthic foraminifera species (e.g., ODP 883), only C. wuellerstorfi δ13C data were used. The mean of the binned data across the entire isotope stage from each site was then used to calculate a mean deep Pacific and mean deep Atlantic δ13CDIC estimate for all 11 marine isotope stages in the MPWP, assuming a 1:1 relationship between C. wuellerstorfi δ13C and δ13CDIC. All sites were weighed equally.
Late Pliocene (~2.6-3.4 million years ago) multiproxy paleoceanographic datasets from Ocean Drilling Program subpolar North Pacific Leg 145 sites 883 (51.12°N, 167.46°E, 2384 m water depth) and 887 (54.22°N, 148.27°W, 3631.2 m water depth). Composite splice for site 883 was created by visual correlation of the shipboard gamma ray attenuation and porosity evaluator (GRAPE) wet bulk density (WBD) measurements between 883B and 883C starting at core 9H and ending at 18H. An astronomically tuned age model for site 883 was developed by correlation of benthic foraminiferal δ18O (3.0–3.385 Ma) to the δ18O probabilistic stack and the 883 GRAPE WBD composite (2.841–3.0 Ma & 3.385–3.465 Ma) to the nearby astronomically-tuned ODP 882 carbonate weight percent record. Benthic foraminiferal stable oxygen and carbon isotope ratios were quantified with a Finnigan Mat 252 with Carbonate Kiel III autosampler. Alkenone concentrations and the UK'37 sea surface temperature index were determined by an Agilent Technologies 6890 gas chromatograph flame ionization detector (GC-FID), with an Agilent Technologies DB-1 column (60 m, 0.32 mm diameter, 0.10 mm film thickness). Calcium carbonate content was determined by acidification of bulk sediment samples with 2M hydrogen sulfide and quantification of the resulting gaseous carbon with a UIC Coulometrics CO2 Coulometer. A composite section was developed for ODP 887 by correlation of shipboard gamma ray attenuation and porosity evalvuator (GRAPE) wet bulk density between 887A and 887C. An improved age model was developed by correlation of the GRAPE composite to that of ODP 883. Stable carbon isotope data were compiled for each marine isotope stage of the mid-Piacenzian warm period from 23 IODP/ODP/DSDP core sites. These data were then binned by marine isotope stage, averaged, and grouped by ocean basin.
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