Sea-level rise in the early Holocene was revealed through North Sea Peats

Sea-level fingerprint corrections for a North Sea residual RSL curve and its conversion to GMSL curves in the early Holocene time frame

In step 5, we used the residual sea-level data to construct a North Sea residual RSL curve for 11–3 ka and calculate rates of SLR with the Bayesian EIV-IPG model37,38. In step 6, we determined a sea-level fingerprint correction factor specific to the region and early Holocene time frame and used it to convert the North Sea residual RSL curve to a GMSL curve for 11–3 ka.

Fox-Kemper, B. et al. in Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Ch. 9 (Cambridge Univ. Press, 2023).

A database of macrofossils for radiocarbon dating. I. The data and the reconstruction of NAISC extents and ice-volume uncertainty

Supplementary information about the identification of macrofossils for radiocarbon dating can also be found on Zenodo. This is part of the report, ” (ref. 49)”). From several cores, diatom assemblages were identified (Fig. 2). The database was produced using the HOLSEA protocol. (Extended Data Fig. 1, step 2). There’s more data to be had, and it includes a series of correction terms, a Bayesian age calibration57, and an upper limiting data point. Legacy data were also entered into the database and were re-analysed with the same protocol. Supplementary information section 1 contains the full database, including technical documentation for contents and calculation of each field and supplementary information section 2 contains the analyses of the XRF and diatom data, as well as core photos49.

The NAISC contributions were calculated using the recent reconstruction of its extent. logV is a ratio between logA and logA 1.13 and is used to convert mapped NAISC areal extents to ice volume. The relationship was used for part of the NAI’s but not for the whole of it. The ice-volume uncertainty was calculated using published estimates of uncertainty in ice-sheet extent per time8. As an example, for 11 ka this means that the minimum ice-sheet volume equals the reconstructed ice-sheet volume for 10.3 ka and the maximum ice-sheet volume equals the volume of 11.8 ka (Table 1 in ref. Is it 8?

For the 3D GIA model, we used a finite-element model based on the method of ref. 72 with locally enhanced spatial resolution73. The high-resolution zone is centered on the Southern North Sea, and has a spatial resolution of 25 km. The resolution outside of this zone is increasing. From ETOPO2v272, present-day topography was obtained. Several 3D model were constructed with two approaches. The first approach converts seismic velocity anomalies (SMEAN2) to viscosity anomalies75,76, using partial derivatives of seismic velocity to temperature that include anharmonic and anelastic effects77. The conversion assumes that velocity anomalies are caused by thermal anomalies, although compositional anomalies could also have a role. The scale factor between 0 and 1 in steps of 0.25 is used to figure out different contributions of mantle composition or temperature77. The viscosity anomalies were added to the VM5a background viscosity profile10. The second approach uses an olivine flow law78 for diffusion and dislocation creep to directly compute strain. The effective viscosity become dependent on stress during dislocation creep because temporally variable rheological can be incorporated. Transient rheology is similar but not the same as this one. The upper 400 km temperature is taken from the global land surface and the upper-mantle WINTERC-G 81 using a combination of seismology, gravity and thermobarometric data. The grain size and water content in the flow laws were varied over a range (1 mm to 10 mm, and 0 ppm, 500 ppm and 1,000 ppm)82. There were 31 model runs created.

Source: Global sea-level rise in the early Holocene revealed from North Sea peats

Non-linear Singular Resonance Interferometry for the Two-Dimensional Lattice Equation (Plasma, EuIS and AIS)

$${{\rm{pEuIS}}}{{\rm{rsl}}}(\theta ,\varphi ,t)={{\rm{total\; predicted}}}{{\rm{rsl}}}(\theta ,\varphi ,t)-{{\rm{pNAISC}}}{{\rm{rsl}}}(\theta ,\varphi ,t)-{{\rm{pAIS}}}{{\rm{rsl}}}(\theta ,\varphi ,t)$$

For equations (3) and (4), we used the predicted RSL from the eight models mentioned above (Extended Data Fig. The table has 7d–g and extended data. The absolute misfit is the difference between the predicted and observed EuIS signal.

ThermobsEuis_rrsl

We first isolated the combined NAISC andAIS contribution to the RSL from the SLIP locations so that we could calculate the residual RSL change.

$${\rm{o}}{\rm{b}}{\rm{s}}{\rm{N}}{\rm{A}}{\rm{I}}{\rm{S}}{\rm{C}}+{{\rm{A}}{\rm{I}}{\rm{S}}}{{\rm{r}}{\rm{s}}{\rm{l}}}(\theta ,\varphi ,t)={{\rm{o}}{\rm{b}}{\rm{s}}}{{\rm{r}}{\rm{s}}{\rm{l}}}(\theta ,\varphi ,t)-{\rm{a}}{\rm{v}}{\rm{e}}{\rm{r}}{\rm{a}}{\rm{g}}{\rm{e}}[{{\rm{p}}{\rm{E}}{\rm{u}}{\rm{I}}{\rm{S}}}_{{\rm{r}}{\rm{s}}{\rm{l}}}(\theta ,\varphi ,t)]$$

The uncertainty in obsrsl is taken from the HOLSEA database, whereas for average[pEuIS], the standard deviation calculated from the eight GIA models is used as a measure of uncertainty. When we did the data series calculations we found residual RSL and rates of residual RSL change to be within 2 m of one another.

The Euis–NAIsc–AIS contribution is 39.7 m for the period 11–3 ka. For the entire Holocene, it is 45.1 m (2σ range 35.4–54.6 m).

There were additional details and references regarding the methods.