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Reconciling divergent trends and millennial variations in Holocene temperatures

Abstract

Cooling during most of the past two millennia has been widely recognized1,2 and has been inferred to be the dominant global temperature trend of the past 11,700 years (the Holocene epoch)3. However, long-term cooling has been difficult to reconcile with global forcing4, and climate models consistently simulate long-term warming4. The divergence between simulations and reconstructions emerges primarily for northern mid-latitudes, for which pronounced cooling has been inferred from marine and coastal records using multiple approaches3. Here we show that temperatures reconstructed from sub-fossil pollen from 642 sites across North America and Europe closely match simulations, and that long-term warming, not cooling, defined the Holocene until around 2,000 years ago. The reconstructions indicate that evidence of long-term cooling was limited to North Atlantic records. Early Holocene temperatures on the continents were more than two degrees Celsius below those of the past two millennia, consistent with the simulated effects of remnant ice sheets in the climate model Community Climate System Model 3 (CCSM3)5. CCSM3 simulates increases in ‘growing degree days’—a measure of the accumulated warmth above five degrees Celsius per year—of more than 300 kelvin days over the Holocene, consistent with inferences from the pollen data. It also simulates a decrease in mean summer temperatures of more than two degrees Celsius, which correlates with reconstructed marine trends and highlights the potential importance of the different subseasonal sensitivities of the records. Despite the differing trends, pollen- and marine-based reconstructions are correlated at millennial-to-centennial scales, probably in response to ice-sheet and meltwater dynamics, and to stochastic dynamics similar to the temperature variations produced by CCSM3. Although our results depend on a single source of palaeoclimatic data (pollen) and a single climate-model simulation, they reinforce the notion that climate models can adequately simulate climates for periods other than the present-day. They also demonstrate that amplified warming in recent decades increased temperatures above the mean of any century during the past 11,000 years.

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Figure 1: Comparison of North Atlantic and global marine-margin temperature reconstructions with our pollen-inferred mean annual temperature reconstruction for North America and Europe.
Figure 2: Reconstructed and simulated annual and seasonal temperature changes in North America, Europe and the northern marine margins during the Holocene.
Figure 3: The geographic extent of the reconstructed temperature trends during the Holocene.
Figure 4: Simulated and reconstructed departures from long-term temperature trends, including forced and unforced variations on centennial scales.

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References

  1. Mann, M. E. et al. Global signatures and dynamical origins of the Little Ice Age and Medieval Climate Anomaly. Science 326, 1256–1260 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  2. PAGES 2k Consortium. Continental-scale temperature variability during the past two millennia. Nat. Geosci. 6, 339–346 (2013)

  3. Marcott, S. A., Shakun, J. D., Clark, P. U. & Mix, A. C. A reconstruction of regional and global temperature for the past 11,300 years. Science 339, 1198–1201 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  4. Liu, Z. et al. The Holocene temperature conundrum. Proc. Natl Acad. Sci. USA 111, E3501–E3505 (2014)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  5. Liu, Z. et al. Transient simulation of last deglaciation with a new mechanism for Bølling–Allerød warming. Science 325, 310–314 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  6. Sachs, J. P. Cooling of Northwest Atlantic slope waters during the Holocene. Geophys. Res. Lett. 34, L03609 (2007)

    Article  ADS  Google Scholar 

  7. Viau, A. E., Gajewski, K., Sawada, M. C. & Fines, P. Millennial-scale temperature variations in North America during the Holocene. J. Geophys. Res. 111, D09102 (2006)

    Article  ADS  Google Scholar 

  8. Mauri, A., Davis, B. A. S., Collins, P. M. & Kaplan, J. O. The climate of Europe during the Holocene: a gridded pollen-based reconstruction and its multi-proxy evaluation. Quat. Sci. Rev. 112, 109–127 (2015)

    Article  ADS  Google Scholar 

  9. Bartlein, P. J. et al. Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis. Clim. Dyn. 37, 775–802 (2011)

    Article  Google Scholar 

  10. Hansen, J., Ruedy, R., Sato, M. & Lo, K. Global surface temperature change. Rev. Geophys. 48, RG4004 (2010)

    Article  ADS  Google Scholar 

  11. Renssen, H. et al. The spatial and temporal complexity of the Holocene thermal maximum. Nat. Geosci. 2, 411–414 (2009)

    Article  ADS  CAS  Google Scholar 

  12. Berger, A. & Loutre, M. F. Insolation values for the climate of the last 10 million years. Quat. Sci. Rev. 10, 297–317 (1991)

    Article  ADS  Google Scholar 

  13. Prentice, I. C. et al. A global biome model based on plant physiology and dominance, soil properties and climate. J. Biogeogr. 19, 117–134 (1992)

    Article  Google Scholar 

  14. Lorenz, S. J., Kim, J.-H., Rimbu, N., Schneider, R. R. & Lohmann, G. Orbitally driven insolation forcing on Holocene climate trends: evidence from alkenone data and climate modeling. Paleoceanography 21, PA1002 (2006)

    Article  ADS  Google Scholar 

  15. Samartin, S. et al. Warm Mediterranean mid-Holocene summers inferred from fossil midge assemblages. Nat. Geosci. 10, 207–212 (2017)

    Article  ADS  CAS  Google Scholar 

  16. Shuman, B. N. & Marsicek, J. The structure of Holocene climate change in mid-latitude North America. Quat. Sci. Rev. 141, 38–51 (2016)

    Article  ADS  Google Scholar 

  17. Webb, T. Is vegetation in equilibrium with climate? How to interpret late-Quaternary pollen data. Plant Ecol. 67, 75–91 (1986)

    Article  Google Scholar 

  18. deMenocal, P. et al. Abrupt onset and termination of the African Humid Period: rapid climate responses to gradual insolation forcing. Quat. Sci. Rev. 19, 347–361 (2000)

    Article  ADS  Google Scholar 

  19. Muschitiello, F., Zhang, Q., Sundqvist, H. S., Davies, F. J. & Renssen, H. Arctic climate response to the termination of the African Humid Period. Quat. Sci. Rev. 125, 91–97 (2015)

    Article  ADS  Google Scholar 

  20. Walker, M. J. C. et al. Formal subdivision of the Holocene Series/Epoch: a discussion paper by a Working Group of INTIMATE (integration of ice-core, marine and terrestrial records) and the Subcommission on Quaternary Stratigraphy (International Commission on Stratigraphy). J. Quat. Sci. 27, 649–659 (2012)

    Article  Google Scholar 

  21. Schurer, A. P., Mann, M. E., Hawkins, E., Tett, S. F. B. & Hegerl, G. C. Importance of the pre-industrial baseline for likelihood of exceeding Paris goals. Nat. Clim. Change 7, 563–567 (2017)

    Article  ADS  Google Scholar 

  22. Fyfe, R. M. et al. The European Pollen Database: past efforts and current activities. Veg. Hist. Archaeobot. 18, 417–424 (2009)

    Article  Google Scholar 

  23. Goring, S. et al. neotoma: a programmatic interface to the Neotoma Paleoecological Database. Open Quat. 1, https://doi.org/10.5334/oq.ab (2015)

  24. Williams, J. W., Shuman, B., Webb, T., Bartlein, P. J. & Leduc, P. L. Late Quaternary vegetation dynamics in North America: scaling from taxa to biomes. Ecol. Monogr. 74, 309–334 (2004)

    Article  Google Scholar 

  25. Grimm, E. C., Maher, L. J., Jr & Nelson, D. M. The magnitude of error in conventional bulk-sediment radiocarbon dates from central North America. Quat. Res. 72, 301–308 (2009)

    Article  CAS  Google Scholar 

  26. Blois, J. L., Williams, J. W., Grimm, E. C., Jackson, S. T. & Graham, R. W. A methodological framework for assessing and reducing temporal uncertainty in paleovegetation mapping from late-Quaternary pollen records. Quat. Sci. Rev. 30, 1926–1939 (2011)

    Article  ADS  Google Scholar 

  27. Lotter, A. F. et al. Younger Dryas and Allerød summer temperatures at Gerzensee (Switzerland) inferred from fossil pollen and cladoceran assemblages. Palaeogeogr. Palaeoclimatol. Palaeoecol. 159, 349–361 (2000)

    Article  Google Scholar 

  28. Marsicek, J. P., Shuman, B., Brewer, S., Foster, D. R. & Oswald, W. W. Moisture and temperature changes associated with the mid-Holocene Tsuga decline in the northeastern United States. Quat. Sci. Rev. 80, 129–142 (2013)

    Article  ADS  Google Scholar 

  29. Williams, J. W. & Shuman, B. Obtaining accurate and precise environmental reconstructions from the modern analog technique and North American surface pollen dataset. Quat. Sci. Rev. 27, 669–687 (2008)

    Article  ADS  Google Scholar 

  30. Whitmore, J. et al. An updated modern pollen-climate-vegetation dataset for North America. Quat. Sci. Rev. 24, 1828–1848 (2005)

    Article  ADS  Google Scholar 

  31. Overpeck, J. T., Webb, T., III & Prentice, I. C. Quantitative interpretation of fossil pollen spectra: dissimilarity coefficients and the method of modern analogs. Quat. Res. 23, 87–108 (1985)

    Article  Google Scholar 

  32. Davis, B. A. S. et al. The European Modern Pollen Database (EMPD) project. Veg. Hist. Archaeobot. 22, 521–530 (2013)

    Article  Google Scholar 

  33. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005)

    Article  Google Scholar 

  34. New, M., Lister, D., Hulme, M. & Makin, I. A high-resolution data set of surface climate over global land areas. Clim. Res. 21, 1–25 (2002)

    Article  Google Scholar 

  35. Cheddadi, R., Yu, G., Guiot, J., Harrison, S. P. & Prentice, I. C. The climate of Europe 6000 years ago. Clim. Dyn. 13, 1–9 (1996)

    Article  Google Scholar 

  36. Telford, R. & Trachsel, M. palaeoSig: significance tests for palaeoenvironmental reconstructions, R package version 1.1-3 (2015)

  37. Juggins, S. rioja: analysis of quaternary science data, R package version 0.9-15 (2016)

  38. Jackson, S. T. & Williams, J. W. Modern analogs in Quaternary paleoecology: here today, gone yesterday, gone tomorrow? Annu. Rev. Earth Planet. Sci. 32, 495–537 (2004)

    Article  ADS  CAS  Google Scholar 

  39. Telford, R. J. & Birks, H. J. B. A novel method for assessing the statistical significance of quantitative reconstructions inferred from biotic assemblages. Quat. Sci. Rev. 30, 1272–1278 (2011)

    Article  ADS  Google Scholar 

  40. Marlon, J. R. et al. Climate and human influences on global biomass burning over the past two millennia. Nat. Geosci. 1, 697–702 (2008)

    Article  ADS  CAS  Google Scholar 

  41. Cleveland, W. S. Robust locally weighted regression and smoothing scatterplots. J. Am. Stat. Assoc. 74, 829–836 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  42. Torrence, C. & Compo, G. P. A practical guide to wavelet analysis. Bull. Am. Meteorol. Soc. 79, 61–78 (1998)

    Article  ADS  Google Scholar 

  43. Gouhier, T. C., Grinstead, A. & Simko, V. biwavelet: conduct univariate and bivariate wavelet analyses, R package version 0.20.10 (2016)

  44. He, F. Simulating Transient Climate Evolution of the Last Deglaciation with CCSM3. PhD Thesis, Univ. Wisconsin-Madison (2011)

  45. Joussaume, S. & Braconnot, P. Sensitivity of paleoclimate simulation results to season definitions. J. Geophys. Res. Atmos. 102, 1943–1956 (1997)

    Article  ADS  Google Scholar 

  46. Kutzbach, J. E. & Gallimore, R. G. Sensitivity of a coupled atmosphere/mixed layer ocean model to changes in orbital forcing at 9000 years B.P. J. Geophys. Res. 93, 803–821 (1988)

    Article  ADS  Google Scholar 

  47. Bartlein, P. J. & Shafer, S. L. The impact of the “calendar effect” and pseudo-daily interpolation algorithms on paleoclimatic data-model comparisons. In AGU Fall Meeting Abstracts abstr. PP31C-2296 (American Geophysical Union, 2016)

  48. Timm, O., Timmermann, A., Abe-Ouchi, A., Saito, F. & Segawa, T. On the definition of seasons in paleoclimate simulations with orbital forcing. Paleoceanography 23, PA2221 (2008)

    Article  ADS  Google Scholar 

  49. Pollard, D. & Reusch, D. B. A calendar conversion method for monthly mean paleoclimate model output with orbital forcing. J. Geophys. Res. Atmos. 107, 4615 (2002)

    Article  ADS  Google Scholar 

  50. Chen, G.-S., Kutzbach, J. E., Gallimore, R. & Liu, Z. Calendar effect on phase study in paleoclimate transient simulation with orbital forcing. Clim. Dyn. 37, 1949–1960 (2011)

    Article  Google Scholar 

  51. Epstein, E. S. On obtaining daily climatological values from monthly means. J. Clim. 4, 365–368 (1991)

    Article  ADS  Google Scholar 

  52. Harrison, S. P. et al. Intercomparison of simulated global vegetation distributions in response to 6 kyr BP orbital forcing. J. Clim. 11, 2721–2742 (1998)

    Article  ADS  Google Scholar 

  53. Argus, D. F., Peltier, W. R., Drummond, R. & Moore, A. W. The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based on GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories. Geophys. J. Int. 198, 537–563 (2014)

    Article  ADS  Google Scholar 

  54. Peltier, W. R., Argus, D. F. & Drummond, R. Space geodesy constrains ice age terminal deglaciation: the global ICE-6G_C (VM5a) model. J. Geophys. Res. Solid Earth 120, 450–487 (2015)

    Article  ADS  Google Scholar 

  55. Cleveland, W. S. & Devlin, S. J. Locally weighted regression: an approach to regression analysis by local fitting. J. Am. Stat. Assoc. 83, 596–610 (1988)

    Article  MATH  Google Scholar 

Download references

Acknowledgements

We thank T. Webb, S. Marcott, J. Shinker, T. Minckley, B. McElroy and E. Currano for comments. Data were obtained from the Neotoma and European Pollen Databases, and we acknowledge the work of the data contributors and the Neotoma and European Pollen Database communities. TraCE-21ka was made possible by the DOE INCITE computing programme, and supported by NCAR, the NSF P2C2 programme, and the DOE Abrupt Change and EaSM programmes. Funding was provided by Wyoming NASA Space Grant (#NNX10AO95H) and EPA STAR (FP-91763201-0) to J.M., and NSF support to B.N.S. (DEB-1146297), S.B. (EAR-1003848) and P.J.B. (ATM-06202409). S.L.S. was supported by the US Geological Survey Climate Research and Development Program.

Author information

Authors and Affiliations

Authors

Contributions

J.M. and B.N.S. oversaw and contributed to all aspects of the research and, with S.B., designed the project. P.J.B. and S.L.S. contributed analyses of the CCSM3 climate model simulation. J.M. and B.N.S. carried out the analyses and wrote the first version of the paper, and J.M., B.N.S., P.J.B. and S.L.S. contributed to the final version.

Corresponding author

Correspondence to Jeremiah Marsicek.

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The authors declare no competing financial interests.

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Reviewer Information Nature thanks M. Haran and the other anonymous reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Figure 1 Time series of calendar-adjusted CCSM3-simulated continental and marine AnnTs and pollen-inferred reconstructions of AnnT highlight different long-term trends from the synthesis of marine and coastal temperature reconstructions.

a, Simulated AnnT anomalies are shown for land (black line with solid red smooth lines) and the oceans (black line with solid blue smooth lines), along with the simulated boreal summer (JJA) air-temperature anomalies for ocean grid cells (dashed blue) over the past 11,000 years. Smooth red and blue solid lines indicate the long-term trends in the simulation (6,500-yr loess fits) for comparison with additional millennial-scale variability (captured by 2,500-yr loess fits (thin solid lines) and GAMMs that account for temporal autocorrelation (thick solid lines)). b, Same as a, but for the pollen-inferred (red) and marine synthesis (blue) temperature reconstructions. The histograms in the insets show simulated random correlations of simulated or reconstructed AnnT over land with 1,000 random series with the same autoregressive characteristics as the de-trended ocean simulation in Fig. 4a and the de-trended marine reconstruction in Fig. 4b. The thick vertical line represents the correlations between the time series and the thin vertical lines represent the 95% range of the random correlations. All anomalies are relative to the mean of ad 1450–1950. Cal yr before 1950 ce, calibrated years before 1950 of the Common Era.

Extended Data Figure 2 Flow chart for data acquisition, data analyses and data products.

Data files and R code used in the reconstruction process can be found at https://www.ncdc.noaa.gov/paleo/study/22992.

Extended Data Figure 3 Site maps indicating the location of all and significant pollen-inferred temperature reconstructions.

ac, Maps showing the locations of significant reconstructions (coloured symbols) of AnnT (a), GDD5 (b) and MTCO (c). Grey symbols indicate additional (not significant) pollen records. Circles with a black outline indicate sites with data within the 0.5–0?kyr bp base period used in calculating temperature anomalies.

Extended Data Figure 4 Number of pollen sample and age control points over the Holocene.

Number of pollen samples (lightly shaded bars) and dates (dark-shaded bars) remaining after the extraction of significant records.

Extended Data Figure 5 Comparison of the mean of the gridded, significance-screened reconstructions of AnnT with mean reconstructions based on gridding or simply averaging (stacking) all AnnT reconstructions without screening.

The AnnT reconstructions for all sites include even the records (grey symbols in Extended Data Fig. 3a) that were not significantly different from random variables, and were produced either by averaging (black line) or first gridding the reconstructions (blue line). These mean time series compare with the mean of the gridded significant reconstructions (coloured symbols in Extended Data Fig. 3a), which we also use in Figs 1 and 2 (dark red line with uncertainty band). The dark red line represents the median of the 100 individual iterations of the mean in which 50% of grid cells were randomly removed with replacement before the mean was calculated. The underlying red uncertainty band denotes the 2.5%–97.5% quantiles of the 100 individual iterations with noise (based on the RMSE of AnnT) added to each grid cell per century before calculating the mean. All anomalies are relative to the mean of ad 1450–1950.

Extended Data Figure 6 Time series of mean reconstructed temperatures, based on gridding the significant site-level reconstructions, show long-term warming and millennial-scale changes.

ac, AnnT (a), GDD5 (b) and MTCO (c) anomalies reconstructed from 415–453 fossil pollen sites across North America and Europe. Light red lines indicate 100 individual iterations of the reconstruction of each variable reconstruction over the past 11?kyr bp in which 50% of grid cells were randomly removed with replacement, and the dark red lines represent the median of those iterations. The underlying red uncertainty bands denote the 2.5%–97.5% range of 100 additional iterations that degraded the reconstructions for each gridded cell by adding random noise to each time step based on the RMSE of the modern calibration (see Methods). All anomalies are relative to the mean of ad 1450–1950.

Extended Data Figure 7 Diagnosing millennial-scale variability from North American and European pollen-inferred AnnTs.

a, AnnT anomalies for North America (black line with red smooth lines) and Europe (black line with blue smooth lines) over the past 11?kyr bp. Smooth blue and red dashed lines indicate a 6,500-yr loess fit. Solid blue and red lines indicate a 2,500-yr loess fit (thin lines) and a GAMM fit (thick lines) to the North American and European temperature reconstructions after accounting for temporally autocorrelated residuals. b, Histograms show correlations of the de-trended North American (red) and European (blue) AnnT reconstructions with 1,000 randomly simulated time series with the same autoregressive characteristics as the de-trended reconstructions (thin lines in d). Vertical black lines indicate the correlation between the two de-trended reconstructions (r?=?0.75). c, Difference between the 6,500-yr loess fits to the North American and European reconstructions. d, Difference between the European and North American means (thin lines) and GAMMs (bold lines) after de-trending by subtracting the 6,500-yr loess fits. e, Same as in d, but removing a 2,500-yr loess fit. The grey bar indicates departures of one standard deviation from zero. All anomalies are relative to the mean of ad 1450–1950.

Extended Data Figure 8 Wavelet analysis highlights coherent millennial-scale variability.

ac, Wavelet decomposition of the marine synthesis (a), the North American AnnT reconstruction (b) and the European AnnT reconstruction (c); the colour scale represents the power spectrum (darker colours represent more power). df, Cross-wavelet significance is also shown for North America versus the marine synthesis (d), Europe versus the marine synthesis (e) and North America versus Europe (f); the colour scale indicates whether there is a significant relationship between the cross-wavelets of the datasets (red, no significant relationship; yellow, significant relationship at the 0.9 significance level). The period, in years, is shown on the y axes.

Extended Data Table 1 Modern calibration experiment results for AnnT
Extended Data Table 2 Sites used in marine synthesis

Supplementary information

Supplementary Table 1

Taxa used in pollen-based climate reconstructions. Table comprising the specific taxa used in the pollen-based climate reconstructions for North America and Europe. (XLSX 11 kb)

Supplementary Table 2

Significant sites and sites used in modern analog technique analysis. Site table containing all of the details for sites deemed significant by our analysis, and the sites used in our analyses. These include the latitude, longitude, elevation, significance values for each variable for each site, the number of samples the site contains throughout the last 11,000 years, and the age model assigned to the core data. (XLS 185 kb)

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Marsicek, J., Shuman, B., Bartlein, P. et al. Reconciling divergent trends and millennial variations in Holocene temperatures. Nature 554, 92–96 (2018). https://doi.org/10.1038/nature25464

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