the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Dec 2024
The impact of measurement precision on the resolvable resolution of ice core water isotope reconstructions
Abstract. Stable water isotopes in ice cores serve as a valuable proxy for the climate of the past hundreds of thousands of years. Over time, water isotope diffusion causes significant attenuation of the isotopic signal, exacerbated in deep ice due to extreme layer thinning and increased temperatures from geothermal heat flux. This damping affects higher frequencies to a greater extent, erasing information on the shortest timescales. It is possible to restore some of the attenuated variability through deconvolution, a method which reverses the effect of diffusion. However, since the measured isotopic signal always contains noise from the measurement process, deconvolution inevitably amplifies this measurement noise along with the isotopic signal. Thus the effectiveness of deconvolution depends on the precision of the measurements, with noisier data limiting the ability to restore otherwise resolvable frequencies. Here, we quantify the upper frequency limit introduced by the magnitude of the measurement noise analytically for different climate states, and offer a numerical example using the Beyond EPICA Oldest Ice Core (BE-OIC). We also demonstrate the qualitative significance of measurement noise on simulated Antarctic isotopic profiles. The general resolution improvement for firn or upper ice records is on the order of 1.5 times for a 10-fold reduction in measurement noise. Similarly, throughout the BE-OIC, we find the deconvolution of δ18O records with measurement error of 0.1 ‰ contributes a 1.5 times increase in the maximum resolvable frequency, which rises to a factor of 2 improvement after reducing the measurement noise to 0.01 ‰. While progress is continuously being made towards improving precision of stable isotope measurements, further improvements using longer integration times should be considered when analysing limited and precious deep ice in order to obtain the most faithful climate reconstructions possible.
-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
-
Preprint
(3073 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(3073 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-3650', Anonymous Referee #1, 30 Mar 2025
- AC1: 'Reply on RC1', Fyntan Shaw, 30 Jun 2025
-
RC2: 'Comment on egusphere-2024-3650', Anonymous Referee #2, 14 Apr 2025
Shaw et al report an analytical method to quantify the upper limit of recoverable frequency from diffused ice core isotopic records after deconvolution, with a particular focus on the effect of measurement noise. The authors suggest that the upper part can be analytically solved where white-noise dominates. Then the authors apply the numerical solutions to the Beyond EPICA Oldest Ice Core, for which climate reconstruction is still ongoing. Overall, the study provides valuable insights into the recovery of water isotope signals in deep ice cores, especially the usefulness of the Beyond EPICA Oldest Ice Core in reconstructing climate before the Mid-Pleistocene Transition. I have a few minor comments on the manuscript.
Although the authors provide two surrogate ice core record examples, it would be helpful to generalize how reducing the measurement noise improves the deconvolved depth profile. For instance, only two different diffusion lengths are discussed in the study. How would different diffusion lengths influence the results?
Please check the consistency of the mathematical expressions throughout the manuscript. For instance, Pn and Pn(f) are used interchangeably.
L86-87: it would be beneficial to provide evidence or justification for these choices?
Figure 3b: what is the purple curve?
The diffusion length stated at L184 appears to differ from that in the caption for Figure 7.
Figures 6 and 7: it is unclear how “the true, undiffused” records were obtained.
Citation: https://doi.org/10.5194/egusphere-2024-3650-RC2 - AC2: 'Reply on RC2', Fyntan Shaw, 30 Jun 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-3650', Anonymous Referee #1, 30 Mar 2025
This manuscript presents a well-structured and insightful study on the role of measurement precision in enhancing the resolvable resolution of ice core water isotope reconstructions, particularly focusing on the Beyond EPICA Oldest Ice Core (BE-OIC). The research is timely and addresses a critical gap in paleoclimate reconstructions by quantifying how measurement noise limits the recovery of high-frequency climate signals through deconvolution techniques. The analytical and numerical approaches are robust, and the results are clearly presented. The manuscript is suitable for publication after minor revisions.
The description of the Wiener deconvolution process and its application to ice core data is technically sound but could be more accessible. Figure 1 shows the conception of how reducing the measurement noise to recovery of higher frequencies. I think the legend of figure 1 should be explained in more details to aid readers unfamiliar with signal processing.
Line 69-73, the authors indicate that the post-depositional processes have a lesser effect on longer timescales. However, the diffusion process is one of the post-depositional processes. Here is a little confused. What kind of the post-depositional processes do you indicate?
The diffusion length profile (Fig. B1) is critical to the analysis but is only briefly mentioned. More details on its derivation, including sensitivity to parameters like geothermal heat flux, would strengthen the manuscript.
The authors should discuss the limitations of the deconvolution method. For example, briefly acknowledge any assumptions in the Wiener deconvolution method that might affect real-world applicability (e.g., linearity of diffusion, stationarity of noise) and discuss potential biases or uncertainties in the diffusion length profile (Appendix B) and how they might influence the results.
Citation: https://doi.org/10.5194/egusphere-2024-3650-RC1 - AC1: 'Reply on RC1', Fyntan Shaw, 30 Jun 2025
-
RC2: 'Comment on egusphere-2024-3650', Anonymous Referee #2, 14 Apr 2025
Shaw et al report an analytical method to quantify the upper limit of recoverable frequency from diffused ice core isotopic records after deconvolution, with a particular focus on the effect of measurement noise. The authors suggest that the upper part can be analytically solved where white-noise dominates. Then the authors apply the numerical solutions to the Beyond EPICA Oldest Ice Core, for which climate reconstruction is still ongoing. Overall, the study provides valuable insights into the recovery of water isotope signals in deep ice cores, especially the usefulness of the Beyond EPICA Oldest Ice Core in reconstructing climate before the Mid-Pleistocene Transition. I have a few minor comments on the manuscript.
Although the authors provide two surrogate ice core record examples, it would be helpful to generalize how reducing the measurement noise improves the deconvolved depth profile. For instance, only two different diffusion lengths are discussed in the study. How would different diffusion lengths influence the results?
Please check the consistency of the mathematical expressions throughout the manuscript. For instance, Pn and Pn(f) are used interchangeably.
L86-87: it would be beneficial to provide evidence or justification for these choices?
Figure 3b: what is the purple curve?
The diffusion length stated at L184 appears to differ from that in the caption for Figure 7.
Figures 6 and 7: it is unclear how “the true, undiffused” records were obtained.
Citation: https://doi.org/10.5194/egusphere-2024-3650-RC2 - AC2: 'Reply on RC2', Fyntan Shaw, 30 Jun 2025
Peer review completion
Journal article(s) based on this preprint
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 818 | 82 | 22 | 922 | 21 | 43 |
- HTML: 818
- PDF: 82
- XML: 22
- Total: 922
- BibTeX: 21
- EndNote: 43
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Thomas Münch
Vasileios Gkinis
Thomas Laepple
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(3073 KB) - Metadata XML
This manuscript presents a well-structured and insightful study on the role of measurement precision in enhancing the resolvable resolution of ice core water isotope reconstructions, particularly focusing on the Beyond EPICA Oldest Ice Core (BE-OIC). The research is timely and addresses a critical gap in paleoclimate reconstructions by quantifying how measurement noise limits the recovery of high-frequency climate signals through deconvolution techniques. The analytical and numerical approaches are robust, and the results are clearly presented. The manuscript is suitable for publication after minor revisions.
The description of the Wiener deconvolution process and its application to ice core data is technically sound but could be more accessible. Figure 1 shows the conception of how reducing the measurement noise to recovery of higher frequencies. I think the legend of figure 1 should be explained in more details to aid readers unfamiliar with signal processing.
Line 69-73, the authors indicate that the post-depositional processes have a lesser effect on longer timescales. However, the diffusion process is one of the post-depositional processes. Here is a little confused. What kind of the post-depositional processes do you indicate?
The diffusion length profile (Fig. B1) is critical to the analysis but is only briefly mentioned. More details on its derivation, including sensitivity to parameters like geothermal heat flux, would strengthen the manuscript.
The authors should discuss the limitations of the deconvolution method. For example, briefly acknowledge any assumptions in the Wiener deconvolution method that might affect real-world applicability (e.g., linearity of diffusion, stationarity of noise) and discuss potential biases or uncertainties in the diffusion length profile (Appendix B) and how they might influence the results.