Biomarker indices and concentrations and biomarker-based temperature estimates from the Iberian Margin core MD95-2042, composite atmospheric temperature record from Greenland, and stacks of delta 18Oice and atmospheric temperature records from three Antarctic sites
<p>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 C<sub>37</sub> 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 TEX<sub>86</sub>, 0.238 for GDGT-2/GDGT-3, and 0.010 (0.26 °C) for U<sup>K′</sup><sub>37</sub>. 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). TEX<sub>86</sub><sup>H</sup>-SST estimates are from the following regional paleocalibration: SST = 68.4 × TEX<sub>86</sub><sup>H</sup> + 33.0 (Darfeuil et al., 2016). U<sup>K′</sup><sub>37</sub>-SST estimates are from the following global calibration: SST = 29.876 × U<sup>K′</sup><sub>37</sub> − 1.334 (Conte et al., 2006). Bayesian calibrations were also used for TEX<sub>86</sub>-SST and TEX<sub>86</sub>-subT estimates (BAYSPAR; Tierney & Tingley, 2014, 2015) and for U<sup>K′</sup><sub>37</sub>-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 <sup>14</sup>C 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.</p> <p>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.</p> <p>Antarctic δ<sup>18</sup>O<sub>ice</sub> and atmospheric temperature stacks: This dataset consists in two stacks of three Antarctic records (EDC, EDML, and WD), one for δ<sup>18</sup>O<sub>ice</sub> and the other for atmospheric temperature: both stacks are provided with their stacking uncertainties. To build the Antarctic δ<sup>18</sup>O<sub>ice</sub> stack, the Antarctic δ<sup>18</sup>O<sub>ice</sub> 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 δ<sup>18</sup>O<sub>ice</sub> records were centered to zero means over the 68–67 ka BP period. The resulting Antarctic δ<sup>18</sup>O<sub>ice</sub> records were then averaged and stacking uncertainties were calculated as the pooled standard deviation of the stacked Antarctic δ<sup>18</sup>O<sub>ice</sub> records divided by the square root of the number of stacked Antarctic δ<sup>18</sup>O<sub>ice</sub> records. The final Antarctic δ<sup>18</sup>O<sub>ice</sub> stack, expressed in ‰, has the same standard deviation as the δ<sup>18</sup>O<sub>ice</sub> 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 δ<sup>18</sup>O<sub>ice</sub> stack, except that the Antarctic δ<sup>18</sup>O<sub>ice</sub> records were corrected for seawater δ<sup>18</sup>O<sub>ice</sub> 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.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0