the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Aug 2025
Multidecadal behavior of the North Atlantic Oscillation during the last millennium
Abstract. The North Atlantic Oscillation (NAO) is a major source of atmospheric variability in the Northern Hemisphere, affecting temperature, precipitation, and storm tracks across North America and Eurasia. Understanding NAO variability on multidecadal to centennial timescales requires paleo-reconstructions, but previously published reconstructions disagree on the magnitude of low-frequency NAO variability over the last millennium. Paleoclimate proxies for the oxygen and hydrogen isotope composition of meteoric waters have thus far been under-utilized in published NAO reconstructions. Here, we present a new reconstruction of the NAO over the last millennium using the Iso2k database, a collection of globally distributed water isotope-based paleoclimate proxy records. In contrast to recent NAO reconstructions, we find significant multidecadal to centennial scale variability. Critically, however, the strength of the low-frequency signal has not been consistent throughout the last millennium. Isotope-enabled model simulations did not reproduce the low-frequency signal in the NAO reconstructions and thus it may be necessary to account for low-frequency variability when projecting the impacts of the NAO on temperature and precipitation under future climate scenarios.
- Preprint
(2314 KB) - Metadata XML
-
Supplement
(1914 KB) - BibTeX
- EndNote
Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-4121', Anonymous Referee #1, 24 Sep 2025
-
RC2: 'Reviewer on egusphere-2025-4121', Jesper Sjolte, 10 Oct 2025
Review Flaim et al. CP
The study of Flaim et al. seeks to reconstruct the NAO over the past millennium using water stable isotopes from geological archives. Using a regression-based method including randomization to test dependency on proxy data, the authors produce an ensemble reconstruction. Flaim et al. then correlate the ensemble reconstruction to other reconstructions and examine the dependency of different types of proxy data. The main science question is focused on the multidecal-centennial variance of the NAO reconstruction, which is found not to be reproduced by a millennium-length isotope enabled simulation.
General comments
Having worked for many years on the topic of climate and atmospheric circulation reconstructions using records of water stable isotope records, I welcome new research in this area. With that said I don’t think the premises and treatment of previous work is entirely correct in the study by Flaim et al. Also, I have concerns about some of the proxy records incorporated used in the study due to large uncertainties in the age-scales, which appears not to be taken into account by the authors. Furthermore, the seasonality in proxy data has been researched extensively, but it is not explained how this plays a role in this study. Finally, the study of the multidecal-centennial NAO signal is limited to the NAO record of Flaim et al. and one model run, while I would have expected a comparison with published NAO reconstructions. In summary, I think the study by Flaim et al. needs extensive reworking to be publishable.
My advice is to develop the section on the multidecal-centennial NAO signal and the dependency on choice of proxy records, combined with a comparison with published NAO records and an extended discussion on where the multidecal-centennial signal comes from in proxy-based NAO reconstructions.
Below I provide the details of my main concerns with this study. I do not provide detailed comments on the text.
Age uncertainties:
- I consider the time scale of speleothems, ice cores from Svalbard and Alpine sites too uncertain to be directly incorporated in this type of reconstruction without taking into account age-scale uncertainties. For example, the Svalbard age-depth scale is based on a flow model with a few volcanic horizons for reference (Isaksson et al., 2001). This should inflate the uncertainty envelope back in time considerably.
- For Greenland ice core time-scale pre ~1200 CE an error in time scale has been uncovered after publication and therefore in the inclusion in iso2K database. See e.g., Adolphi & Muscheler (2015). The options are to correct the raw ice data with new dating or shorten reconstruction (I too the latter approach in my work).
Seasonality:
- Proxy data: what is the seasonality of the proxydata used in the reconstruction?
- It appears that all proxydata are assigned to calendar year? (L155). I think it doesn’t make sense to use the approach of Putman & Bowen for proxy data.
- See publication on seasonality, circulation patterns and climate variability: Vinther et al. (2010) and Sjolte et al. (2020).
- The use of the calendar year for Greenland ice core data causes loss of signal.
Impact of changing number of records trough time:
- Type of proxies partly investigated (Fig S5) but not the influence of varying the number of proxy records. What is the performance of the reconstruction using only spanning the full timeframe? This would indicate what the skill is in the earlier part of the reconstruction.
- How does Figure 3 look like for the period prior to the validation period?
Multi-decadal to centennial variability:
- The authors discuss the multi-decadal to centennial variability of other NAO reconstructions, but there is no comparison of different NAO reconstructions. Since you make use of wavelet analysis, cross-wavelet power and wavelet coherence would be appropriate.
- If the focus is multi-decadal to centennial variability the time window for the validation is very short, and I supposed done on annual data with no filtering?
- How does Figure 3 look like for the period prior to the validation period using a decadal filter (e.g., a Gauss filter)?
- It is well-known that models underestimate multi-decadal to centennial variability, in particularly on regional scales (Laepple et al., 2023). Instead of just repeating this, you could investigate where the model underestimates the isotope variability by extracting all the proxy sites from the model output and comparing to the spectrum of the isotope records.
Reference to previous work on the topic and claim that isotope records are underutilized: L12-13 and L102-104:
- I think this claim is not correct. Even if we disregard my own work on the topic this ignores the use of ice core isotope records in previous work by Cook et al. (2002), Ortega et al. (2015), Michel et al. (2020) etc. some also referred to by the Flaim et al.
- I think part of the perceived underutilization could come from some records not being used, as people (myself included) refrain from using these records due to large dating uncertainties (see point on age uncertainties above).
- My work on this topic can be found in (Sjolte et al., 2011, 2018, 2020, 2023, 2025; Tao et al., 2023). I hope you will find this relevant for your study. My reconstructions are available for download. Follow links in publications.
References
Elisabeth Isaksson, Mark Hermanson, Sheila Hicks, Makoto Igarashi, Kokichi Kamiyama, John Moore, Hideaki Motoyama, Derek Muir, Veijo Pohjola, Rein Vaikmäe, Roderik S.W van de Wal, Okitsugu Watanabe, Ice cores from Svalbard––useful archives of past climate and pollution history, Physics and Chemistry of the Earth, Parts A/B/C, Volume 28, Issues 28–32, 2003, Pages 1217-1228, ISSN 1474-7065, https://doi.org/10.1016/j.pce.2003.08.053.(https://www.sciencedirect.com/science/article/pii/S147470650300202X)
Laepple, T., Ziegler, E., Weitzel, N. et al. Regional but not global temperature variability underestimated by climate models at supradecadal timescales. Nat. Geosci. 16, 958–966 (2023). https://doi.org/10.1038/s41561-023-01299-9
Sjolte, J., G. Hoffmann, S. J. Johnsen, B. M. Vinther, V. Masson‐Delmotte, and C. Sturm, Modeling the water isotopes in Greenland precipitation 1959–2001 with the meso‐scale model REMO‐iso, J. Geophys. Res., 116, D18105, doi:10.1029/2010JD015287 2011.
Sjolte, J., Sturm, C., Adolphi, F., Vinther, B. M., Werner, M., Lohmann, G., and Muscheler, R.: Solar and volcanic forcing of North Atlantic climate inferred from a process-based reconstruction, Clim. Past, 14, 1179-1194, https://doi.org/10.5194/cp-14-1179-2018, 2018.
Sjolte, J., Adolphi, F., Vinther, B. M., Muscheler, R., Sturm, C., Werner, M., and Lohmann, G.: Seasonal reconstructions coupling ice core data and an isotope-enabled climate model – methodological implications of seasonality, climate modes and selection of proxy data, Clim. Past, 16, 1737–1758, https://doi.org/10.5194/cp-16-1737-2020, 2020.
Sjolte, J., Tao, Q., & Muscheler, R. (2023). Updated gridded reconstruction of sea level pressure, temperature, and precipitation during winter in the North Atlantic region covering 1241-1970 CE [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8328301
Sjolte, J. and Tao, Q.: Climate field reconstructions for the North Atlantic region of annual, seasonal and monthly resolution spanning CE 1241–1970, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-2911, 2025.
Tao, Q. , Sjolte, J. , & Muscheler, R. (2023). Persistent model biases in the spatial variability of winter North Atlantic atmospheric circulation. Geophysical Research Letters, 50, e2023GL105231. https://doi.org/10.1029/2023GL105231
Vinther, B.M., Jones, P.D., Briffa, K.R., Clausen, H.B., Andersen, K.K., Dahl-Jensen, D. and Johnsen, S.J., 2010: Climatic signals in multiple highly resolved stable isotope records from Greenland, Quaternary Science Reviews 29: 522-538.
Citation: https://doi.org/10.5194/egusphere-2025-4121-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 1,581 | 64 | 14 | 1,659 | 23 | 30 | 21 |
- HTML: 1,581
- PDF: 64
- XML: 14
- Total: 1,659
- Supplement: 23
- BibTeX: 30
- EndNote: 21
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
This paper seeks to tackle the debate about how the NAO varies at different timescales over the past millennium using a large network of water isotope records. The use of water isotope records for this purpose is new and this paper deserves to be published after due consideration of the issues I bring up.
I think the problem with the debate about high vs. low-frequency variability in the NAO is in part a matter of definition. If we restrict ourselves to the original definition of the NAO by Hurrell, van Loon, Jones, and others, the NAO is simply an atmospheric pressure difference index in the North Atlantic, with little inter-decadal or longer variability indicated as far back as 1824 in CRU instrumental pressure data and back to 1781 in a high-quality extension of the NAO index by Phil Jones. This is clearly indicated by their “flat” (no slope) power spectra shown in Fig. 5b of the Cook et al. (2019) paper. Thus, it should come as no surprise that the Cook et al. (2019) winter NAO index reconstruction, after due consideration taken to match the overall slope of the instrumental data power spectra, should have a “flat” power spectrum as well, as opposed to the substantial “redness” in some other NAO reconstructions (e.g. Ortega et al., 2015).
For this reason, I argue that the NAO reconstruction being presented in this paper (and in Ortega as well), with its substantially greater decadal-to-centennial variability, is not a reconstruction of the NAO atmospheric pressure index itself, but a reconstruction that includes NAO impacts from long-range, persistent, effects on atmospheric circulation and regional climate. The authors know this because it is explicitly stated by them on lines 64-66 of the paper (“Water isotopes provide information about the NAO on broader spatial and temporal scales … because they integrate on basin-wide to hemispheric scales …”). See also lines 79-81. As such, what is presented here is distinctly different from the reconstruction of the NAO index itself. This difference in definition was also reflected in the title of the Hurrell and van Loon (1997) NAO paper “Decadal variations in climate ASSOCIATED with the North Atlantic Oscillation” [my emphasis added]. So the water isotopes are clearly telling us something useful about NAO variability and its impacts over the NH, but the reconstruction from them ought not be considered an unbiased expression of the NAO alone.
Considerable discussion is made about the somewhat intermittent multi-decadal variability indicated in the wavelet spectra. While there is little doubt that this could reflect true variations in the strength of natural forcing at these timescales, no mention is made of the likelihood that the dating of some of the annual water isotope records is very likely to degrade back in time. (Certainly for speleothems, which are never precisely dated, and should only be expected to reflect lower frequency variability.) This is known to be a problem with ice core records in general and these make up the bulk of the longer records used in the NAO reconstruction (see Figs. 1 and 2b). The result will almost certainly be a loss of high-frequency signal and a relative increase of lower-frequency power in the composite reconstruction as the dating errors accumulate and the composite consequently smooths back in time. This is actually suggested in Fig. 2a by the visible reduction in the amplitude of variability before 1700 CE. I also note that the wavelet spectrum of the NAO reconstruction based on glacier ice only (Fig. S5a) shows an almost total loss of power a periods <5 years before 1790 whereas the reconstruction based on better dated wood cellulose records maintain it better. This could reflect a gradual loss of dating fidelity back in time in the ice cores. This said, in no way I am suggesting that the loss of precise dating invalidates the usefulness of the reconstruction at lower frequencies, but it should be acknowledged as another likely contributor to the changing pattern of variability seen in the wavelet spectra.
Given these concerns, in order to recommend publication I would need the authors to: