Over recent millennia, orbital forcing has continually reduced summer insolation in the Northern Hemisphere⁵. Peak insolation changes in Northern Hemisphere high latitudes, at ~65° N between June–August (JJA), have been identified as the prime forcing of climate variability over the past million years¹. Together with long-term CO₂ variability resulting from biogeochemical feedbacks of the marine and terrestrial ecosystems¹⁴, these insolation cycles have initiated the interplay between glacial and interglacial periods¹⁵.

State-of-the-art coupled general circulation model (CGCM) simulations and high-resolution climate reconstructions rarely extend beyond the past few hundred years, limiting possibilities to evaluate low-frequency temperature fluctuations beyond broad assessments (and debate) of the Medieval Warm Period and Little Ice Age⁴. In fact, most high-resolution temperature reconstructions¹⁶ including tree-ring width (TRW) records, the most widespread and important late-Holocene climate proxy¹⁷, have never even been compared with orbital forcing. However, limitations related to the necessary removal of biological noise and the questioned ability of TRW records to reliably track recent (and past) warm episodes¹⁸ may not make this proxy suitable to investigate the role of orbital forcing on climate. Indeed an evaluation of long-term temperature reconstructions, even over the past 7,000 years from across northern Eurasia, demonstrates that TRW-based records fail to show orbital signatures found in low-resolution proxy archives and climate model simulations (Supplementary Fig. S1). These discrepancies not only reveal that dendrochronological records are limited in preserving millennial scale variance, but also suggest that hemispheric reconstructions, integrating these data, might underestimate natural climate variability.

We here address these issues by developing a 2,000-year summer temperature reconstruction based on 587 high-precision maximum latewood density (MXD) series from northern Scandinavia (Fig. 1). The record was developed over three years using living and subfossil pine (Pinus sylvestris) trees from 14 lakes and 3 lakeshore sites >65° N (Methods), making it not only longer but also much better replicated than any existing MXD time series (for example, the widely cited Tornetraesk record contains 65 series¹⁹). We carried out a number of tests to the MXD network and noted the robustness of the long-term trends, but also the importance of including living trees from the lakeshore to form a seamless transition to the subfossil material preserved in the lakes (Methods). Calibration/verification with instrumental data is temporally robust and no evidence for divergence²⁰ was noted. The final reconstruction (N-scan) was calibrated against regional JJA temperature (r_1876–2006 = 0.77) and spans the 138 BC–AD 2006 period.

N-scan shows a succession of warm and cold episodes including peak warmth during Roman and Medieval times alternating with severe cool conditions centred in the fourth and fourteenth centuries (Fig. 2). AD 21–50 (+1.05 °C, with respect to the 1951–1980 mean) was the warmest reconstructed 30-year period, ~2 °C warmer than the coldest AD 1451–1480 period (−1.19 °C) and still ~0.5 °C warmer than maximum twentieth-century warmth recorded AD 1921–1950 (+0.52 °C). Twentieth-century Scandinavian warming is relatively small compared with most other Northern Hemisphere high-latitude regions⁴.

Superimposed on this interannual to multicentennial variability, N-scan reveals a long-term cooling trend of −0.31 °C per 1,000 years (±0.03 °C) over the 138 BC–AD 1900 period (the dashed red curve in Fig. 2) in line with evidence from low-resolution Holocene proxies^{2, 3}. The cooling trend, representing a −0.34 °C temperature difference between the first and second millennium AD (−0.36 °C excluding the twentieth century from the second millennium mean), is however not preserved in the TRW data from the same temperature-sensitive trees (Fig. 3). Similarly, no evidence for a long-term cooling trend is observed in a previous Fennoscandian TRW-based temperature reconstruction spanning the past 2,000 years²¹. Such a trend was found in only low-resolution lake sediment and ice-core data of a circum-Arctic proxy network⁶. The high-latitude TRW data included in ref. 6 also suggested no sign of a long-term cooling trend, demonstrating that variance at this lowest frequency is absent in existing tree-ring time series and thus most of the large-scale reconstructions produced so far¹⁶. Removal of the tree-ring data from the Arctic-wide network⁶ results in an increased cooling trend substantially larger than the −0.21 °C per 1,000 years estimated using all proxy archives (Fig. 3c). Other reconstructions (besides the records shown here) that would be long enough and contain a clear and calibrated temperature signal to assess orbital signatures in tree-ring data are not available from the Northern Hemisphere at present.

As suggested previously^{2, 6}, we propose that the millennial scale cooling trend retained in N-scan is forced by JJA insolation changes of ~ −6 W m⁻² over the past 2,000 years⁵, as other potential forcings, including volcanic eruptions, land use and greenhouse gas changes, are either too small or free of long-term trends⁴. We tested this theory by analysing the two CGCMs that were run over several millennia (ECHO-G and ECHAM5–MPIOM; refs 7, 8), and compared the modelled temperature trends with and without orbital forcing (Methods). The CGCMs revealed similar JJA temperature patterns including a long-term cooling trend over the past two millennia centred in Northern Hemisphere high latitudes (Supplementary Fig. S12). The cooling trends are stronger in the ECHO-G model (−0.19 °C per 1,000 years for the 60°–70° N latitudinal band) compared with the ECHAM5–MPIOM model (−0.10 °C per 1,000 years), but diminish in both CGCMs towards lower latitudes. A smaller trend in orbital forcing and reduced albedo-driven feedbacks from high-latitude terrestrial snow and sea-ice cover contribute to this latitudinal gradient (Supplementary Fig. S13; ref. 22). Both models reveal stronger cooling over the continents in comparison with the oceans and indicate trends of −0.17 °C (ECHO-G) and −0.10 °C (ECHAM5–MPIOM) per 1,000 years in the grid boxes closest to northern Scandinavia. Whereas the absolute values from the simulations might not be as reliable as the empirically derived estimates reported here (> −0.3° per 1,000 years in northern Scandinavia and the Arctic zone), the long-term CGCM runs are valuable for the spatial assessment of orbital signatures.

The missing millennial scale trends in existing TRW records as well as the increased cooling trend after removal of this proxy type from the Arctic-wide estimates⁶ both suggest that the widely cited hemispheric reconstructions^{9, 10, 11, 12, 13, 14} underestimate pre-instrumental temperatures to some extent. This hypothesis seems to be important as most of the annually resolved, large-scale records are solely composed of or dominated (on longer timescales) by TRW data¹⁶, and their spatial domain encompasses the Northern Hemisphere extratropics including northern boreal and Arctic environments. Inclusion of tree-ring data that lack millennial scale cooling trends, as revealed here (Fig. 3 and Supplementary Fig. S1), thus probably causes an underestimation of historic temperatures. In line with the course and magnitude of the underlying orbital forcing (Supplementary Fig. S13), this underestimation ought to build up back in time, for example from the Medieval back to Roman times. Impacts on large-scale reconstructions from the omitted long-term trend in tree-ring data should, however, diminish towards lower Northern Hemisphere latitudes, as the forcing and radiative feedbacks^{5, 22} decrease towards equatorial regions.

Further calculation of these effects based on the missing cooling trends in TRW data and the spatial CGCM temperature patterns is, however, not yet possible, as the existing large-scale reconstructions include changing regional proxies, represent varying fractions of Northern Hemisphere (full Northern Hemisphere, Northern Hemisphere extratropics, Northern Hemisphere high latitudes), and are composed and calibrated using an array of methods¹⁶. The implications of missing orbital signatures in tree-ring records are generally related to the overall variance of temperature variations retained in the large-scale reconstructions (Supplementary Fig. S14). Whereas most of these time series show a similar course of long-term temperature change—including warmth during Medieval times, cold during the Little Ice Age and subsequent warming—the magnitude of reconstructed temperatures differs considerably among the hemispheric records^{16, 23}. Some records show decadal scale variations of the order of ~ 0.4 °C over the past millennium¹², whereas others indicate temperature variability up to 1.0 °C over the same period⁹. As a consequence, any adjustment for the omitted millennial scale temperature trends in dendrochronological records would have stronger implications, if the calibrated amplitude of past temperature variations was indeed small, say <0.5 °C, but would be less significant if the high-variance reconstructions turn out to be correct. The missing orbital signature in tree-ring records is also less significant to reconstructions containing variance increases (owing to reduced proxy coverage) back in time^{9, 13}. These results reinforce the need to better constrain the pre-instrumental temperature variance structure¹⁰ and amplitude²³.

Whereas our results on orbitally forced climate trends in a 2,000-year MXD chronology seem to be in line with coarse-resolution Holocene proxies^{2, 3} and are supported by CGCM evidence^{7, 8}, little attention has been paid to the lack of these trends in long-term tree-ring records and implications thereof. The JJA temperature reconstruction presented here closes this gap, a finding that largely stems from the exceptionally strong and temporally stable climate signal, and the unprecedented length and replication of the new N-scan MXD chronology. The ability of MXD data to retain millennial scale temperature trends seems to result from a number of properties, including a reduced age trend²⁴ and biological persistence²⁵ resulting in less distortion of retained trends through regional curve standardization²⁶ (RCS), the ability of tree populations to develop cell walls of continuously changing thickness over millennia and the non-plastic response of the termination of cell-wall lignification with respect to the integrated heat over the high and late summer seasons²⁷. It is the combination of these properties that seems to enable the retention of a millennial scale trend in the MXD record and the lack of this lowest frequency variance in existing TRW records. These findings together with the trends revealed in long-term CGCM runs suggest that large-scale summer temperatures were some tenths of a degree Celsius warmer during Roman times than previously thought.

It has been demonstrated⁴ that prominent, but shorter term climatic episodes, including the Medieval Warm Period and subsequent Little Ice Age, were influenced by solar output and (grouped) volcanic activity changes, and that the extent of warmth during medieval times varies considerably in space. Regression-based calculations over only the past millennium (including the twentieth century) are thus problematic as they effectively provide estimates of these forcings that typically act on shorter timescales. Accurate estimation of orbitally forced temperature signals in high-resolution proxy records therefore requires time series that extend beyond the Medieval Warm Period and preferably reach the past 2,000 years or longer⁶.

Further uncertainty on estimating the effect of missing orbital signatures on hemispheric reconstructions is related to the spatial patterns of JJA orbital forcing and associated CGCM temperature trends. First, the simulated temperature trends, indicating substantial weakening of insolation signals towards the tropics, can at present be assessed in only two CGCMs (refs 7, 8). More long-term runs with GCMs to validate these hemispheric patterns are required. Whereas the large-scale patterns of temperature trends seem rather similar among the CGCMs, the magnitude of orbitally forced trends varies considerably among the simulations. Additional uncertainty stems from the weight of tree-ring data and varying seasonality of reconstructed temperatures in the large-scale compilations. Although some of the reconstructions are solely composed of tree-ring data, others include a multitude of proxies (including precipitation-sensitive time series) and may even include non-summer temperature signals. Some of these issues are difficult to tackle, as the weighting of individual proxies in several large-scale reconstructions is poorly quantified. The results presented here, however, indicate that a thorough assessment of the impact of potentially omitted orbital signatures is required as most large-scale temperature reconstructions include long-term tree-ring data from high-latitude environments. Further well-replicated MXD-based reconstructions are needed to better constrain the orbital forcing of millennial scale temperature trends and estimate the consequences to the ongoing evaluation of recent warming in a long-term context.

Tree-ring data and spatial coherence.

We collected core samples from living P. sylvestris trees growing at lakeshore and inland (that is ten or more metres distance from lakes) microsites, and disc samples from submerged logs in northern Finland and Sweden (Supplementary Table S1 and Fig. S2). MXD data were derived from high-resolution density profiles using X-ray radiographic techniques²⁸ (Fig. 1). Within and between-site coherence of the northern Scandinavian MXD network has been assessed using a total of nine data sets from living trees—of which three (Ket, Kir, Tor) are additionally subdivided into lakeshore and inland subsets—and 14 data sets from subfossil lake material. We calculated Pearson correlation coefficients among living-tree chronologies over the 1812–1978 common period (r_MXD = 0.72, r_TRW = 0.58; Supplementary Table S2 and Fig. S3), and over varying periods of overlap (AD 700–1600) between subfossil MXD chronologies (r_MXD = 0.71; Supplementary Table S3 and Fig. S4) to estimate data homogeneity throughout space and time. To ensure signal homogeneity, we considered MXD data from only lakeshore sites together with the subfossil material discovered from the lakes for the final reconstruction (N-scan). The record integrates 587 high-resolution P. sylvestris MXD measurement series.

Chronology development and assessment.

Various combinations of living-tree and subfossil MXD data were produced to assess the sensitivity of the long-term N-scan record to detrending methodology and microsite conditions. Application of negative exponential and RCS detrending techniques revealed substantial changes in retained low-frequency variance and sensitivity of twentieth-century trends to density differences between living-tree sites ranging from ~0.002 to 0.010 g cm⁻³ over the first 200 years of tree growth (Supplementary Fig. S5). Sensitivity of increased (decreased) twentieth-century chronology levels was assessed using MXD data from only lakeshore (inland) microsites in long-term RCS runs (Supplementary Fig. S6). N-scan characteristics were detailed by calculating 95% bootstrap confidence ranges, chronology age and replication curves, and interseries correlation and expressed population signal statistics (Supplementary Fig. S7). We analysed the RCS detrended N-scan data by classifying the measurement series into age classes ranging from 1–10 years to 201–210 years and calculating 100-year spline filters for each of these classes (Supplementary Fig. S8). This procedure provided insights into the coherence of long-term trends retained in (typically noisier) juvenile and (typically less replicated) adult tree-ring data. N-scan trend behaviour was additionally assessed by analysing the persistence of low-frequency variability in tree-ring parameters, indicating that only the MXD data preserved substantial variance on millennial timescales (Supplementary Fig. S9).

Proxy calibration and JJA temperature reconstruction.

The MXD climate signal was assessed using Pearson correlation coefficients between the lakeshore subsets Ket-L (r = 0.74), Kir-L (r = 0.75) and Tor-L (r = 0.74) and mean JJA temperatures recorded at the global historical climatology network stations Haparanda, Karasjok and Sodankyla over the 1876–2006 common period. Running correlations were applied to analyse the temporal characteristics of the signal revealing reduced coherence among the station records as well as between the station and proxy data centred in the 1910s (Supplementary Fig. S10). The long-term N-scan record integrating lakeshore and subfossil MXD data correlates at 0.77 (r² = 0.59) with regional JJA temperatures. We transferred this record into a JJA temperature reconstruction using ordinary least square regression with MXD as the independent variable. This approach provides conservative estimates—owing to the reduction of variability caused by unexplained variance²⁹—of pre-instrumental climate variability and derived long-term trends. Split-period calibration/verification statistics³⁰ with early and late r² (0.-57–0.61), reduction of error (0.57–0.59), coefficient of efficiency (0.50–0.54) and full period Durbin–Watson (1.75) statistics were applied to validate the reconstruction. N-scan confidence intervals were calculated considering the standard error (±2 × root mean square error) derived from verification against instrumental JJA temperatures over the early 1876–1941 period and a bootstrap confidence range derived from resampling the MXD data 1,000 times with replacement. A total of 2,000 MXD chronologies derived from randomly drawn subsets of the N-scan record were developed to test the influence of reduced sample replication, typical to earlier periods of the long-term reconstruction, on the calibration results. These tests revealed that the transfer model remains robust (r > 0.70) down to a replication of ten MXD measurement series (Supplementary Fig. S11). Extreme cool and warm summers (decades and centuries) since 138 BC are expressed as deviations from the 1951 to 1980 mean (Supplementary Table S4) and millennial scale JJA temperature trends estimated by calculating a linear ordinary least square regression over the 138 BC–AD 1900 period (Fig. 2). The robustness of the regression slope (−0.31 °C per 1,000 years) was tested by reducing the length of the regression period stepwise at both ends by 100 years to derive a 95% confidence range (±0.03 °C) of the millennial scale trend.

CGCM Holocene simulations.

Spatial patterns of JJA surface air temperatures derived from multimillennial ECHO-G (ref. 7) and ECHAM5–MPIOM (ref. 8) CGCM runs forced with and without long-term insolation changes were analysed to estimate low-frequency temperature trends throughout the Northern Hemisphere extratropics (Supplementary Fig. S12). ECHO-G is one of the coupled atmosphere–ocean models considered in the Intergovernmental Panel on Climate Change Fourth Assessment Report and was ranked among the best five models in simulating the mean patterns of surface atmospheric circulation and precipitation⁴. It integrates the atmospheric ECHAM4 model with a horizontal resolution of 3.75 × 3.75 degrees and 19 vertical levels, and the oceanic HOPE model with a horizontal resolution ranging from about 2.8 × 2.8 to 0.5 × 0.5 degrees towards the Equator and 20 vertical levels including a thermodynamic sea-ice model. To avoid artificial climate drift in the very long (7,000 years) climate simulations used here, a flux adjustment was applied to the atmosphere–ocean coupling. The second transient Holocene simulation⁸ consists of the spectral atmosphere model ECHAM5 run at truncation T31, corresponding to a horizontal resolution of a 3.75 × 3.75 longitude–latitude grid, with 19 vertical hybrid sigma pressure levels and the highest level at 10 hPa. It integrates the land-surface model JSBACH including a dynamic vegetation module, has been coupled to the ocean GCM MPIOM run with 40 vertical levels (30 levels within the top 2,000 m) and includes a zero-layer dynamic-thermodynamic sea-ice model with viscous-plastic rheology. No flux correction has been applied to this CGCM.

1. Milankovitch, M. Kanon der Erdbestrahlung und seine Anwendung auf das Eiszeitenproblem. (Königlich Serbische Akademie, 1941).
   • Show context
2. Wanner, H. et al. Mid- to late Holocene climate change: An overview. Quat. Sci. Rev. 27, 1791–1828 (2008).
   • ADS
   • Article
   • Show context
3. Mayewski, P. A. et al. Holocene climate variability. Quat. Res. 62, 243–255 (2004).
   • ISI
   • Article
   • Show context
4. IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) (Cambridge Univ. Press, 2007).
   • Show context
5. Berger, A. & Loutre, M. F. Insolation values for the climate of the last 10 million years. Quat. Sci. Rev. 10, 297–317 (1991).
   • ADS
   • ISI
   • Article
   • Show context
6. Kaufman, D. S. et al. Recent warming reverses long-term Arctic cooling. Science 325, 1236–1339 (2009).
   • CAS
   • ADS
   • ISI
   • PubMed
   • Article
   • Show context
7. Zorita, E., Gonzlez-Rouco, F., von Storch, H., Montavez, J. P. & Valero, F. Natural and anthropogenic modes of surface temperature variations in the last thousand years. Geophys. Res. Lett. 32, L08707 (2005).
   • Article
   • Show context
8. Fischer, N. & Jungclaus, J. H. Evolution of the seasonal temperature cycle in a transient Holocene simulation: Orbital forcing and sea-ice. Clim. Past 7, 1139–1148 (2011).
   • Article
   • Show context
9. Esper, J., Cook, E. & Schweingruber, F. Low-frequency signals in long tree-ring chronologies for reconstructing past temperature variability. Science 295, 2250–2253 (2002).
   • CAS
   • ADS
   • ISI
   • PubMed
   • Article
   • Show context
10. Frank, D., Esper, J. & Cook, E. R. Adjustment for proxy number and coherence in a large-scale temperature reconstruction. Geophys. Res. Lett. 34, L16709 (2007).
    • ADS
    • Article
    • Show context
11. Hegerl, G. C. et al. Detection of human influence on a new, validated 1500-year temperature reconstruction. J. Clim. 20, 650–666 (2007).
    • ISI
    • Article
    • Show context
12. Mann, M. E., Bradley, R. S. & Hughes, M. K. Northern hemisphere temperatures during the past millennium: Inferences, uncertainties, and limitations. Geophys. Res. Lett. 26, 759–762 (1999).
    • ADS
    • ISI
    • Article
    • Show context
13. Mann, M. E. et al. Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proc. Natl Acad. Sci. USA 105, 13252–13257 (2008).
    • ADS
    • PubMed
    • Article
    • Show context
14. Frank, D. C. et al. Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate. Nature 463, 527–530 (2010).
    • CAS
    • ADS
    • PubMed
    • Article
    • Show context
15. Laepple, T., Werner, M. & Lohmann, G. Synchronicity of Antarctic temperatures and local solar insolation on orbital timescales. Nature 471, 91–94 (2011).
    • CAS
    • ADS
    • ISI
    • PubMed
    • Article
    • Show context
16. Frank, D., Esper, J., Zorita, E. & Wilson, R. A noodle, hockey stick, and spaghetti plate: A perspective on high-resolution paleoclimatology. Wiley Interdiscipl. Rev. Clim. Change 1, http://dx.doi.org/10.1002/wcc.53(2010).
    • Show context
17. Esper, J., Frank, D. C. & Wilson, R. J. S. Climate reconstructions: Low frequency ambition and high frequency ratification. Eos 85, 113, 130 (2004).
    • Show context
18. Cook, E. R., Briffa, K. R., Meko, D. M., Graybill, D. A. & Funkhouser, G. The ‘segment length curse’ in long tree-ring chronology development for palaeoclimatic studies. Holocene 5, 229–237 (1995).
    • ISI
    • Article
    • Show context
19. Schweingruber, F. H., Bartholin, T., Schär, E. & Briffa, K. R. Radiodensitometric-dendroclimatological conifer chronologies from Lapland (Scandinavia) and the Alps (Switzerland). Boreas 17, 559–566 (1988).
    • Article
    • Show context
20. Esper, J. et al. Trends and uncertainties in Siberian indicators of 20th century warming. Glob. Change Biol. 16, 386–398 (2010).
    • Article
    • Show context
21. Briffa, K. R. et al. Trends in recent temperature and radial tree growth spanning 2000 years across northwest Eurasia. Philos. Trans. R. Soc. B 363, 2269–2282 (2008).
    • Article
    • Show context
22. Kerwin, M. W. et al. The role of oceanic forcing in mid-Holocene northern hemisphere climatic change. Paleoceanography 14, 200–210 (1999).
    • ADS
    • Article
    • Show context
23. Esper, J. et al. Climate: Past ranges and future changes. Quat. Sci. Rev. 24, 2164–2166 (2005).
    • ADS
    • Article
    • Show context
24. Frank, D. & Esper, J. Characterization and climate response patterns of a high-elevation, multi-species tree-ring network for the European Alps. Dendrochronologia 22, 107–121 (2005).
    • Article
    • Show context
25. Frank, D., Büntgen, U., Böhm, R., Maugeri, M. & Esper, J. Warmer early instrumental measurements versus colder reconstructed temperatures: Shooting at a moving target. Quat. Sci. Rev. 26, 3298–3310 (2007).
    • ADS
    • Article
    • Show context
26. Esper, J., Cook, P. J., Krusic, K., Peters, F. H. & Schweingruber, Tests of the RCS method for preserving low-frequency variability in long tree-ring chronologies. Tree-Ring Res. 59, 81–98 (2003).
    • Show context
27. Moser, L. et al. Timing and duration of European larch growing season along an altitudinal gradient in the Swiss Alps. Tree Physiol. 30, 285–233 (2010).
    • PubMed
    • Article
    • Show context
28. Schweingruber, F. H., Fritts, H. C., Bräker, O. U., Drew, L. G. & Schaer, E. The X-ray technique as applied to dendroclimatology. Tree-Ring Bull. 38, 61 (1978).
    • Show context
29. Lee, T., Zwiers, F. & Tsao, M. Evaluation of proxy-based millennial reconstruction methods. Clim. Dynam. 31, 263–281 (2008).
    • ADS
    • Article
    • Show context
30. Cook, E. R., Briffa, K. & Jones, P. D. Spatial regression methods in dendroclimatology: A review and comparison of techniques. Int. J. Climatol. 14, 379–402 (1994).
    • ISI
    • Article
    • Show context

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We thank D. S. Kaufman for comments and H. Grudd for help with fieldwork. Supported by the Mainz Geocycles Research Centre and Palaeoweather Group, the European Union projects Carbo-Extreme (226701), CIRCE (36961) and ACQWA (212250), the Swiss National Science Foundation project INTEGRAL (121859), the German Science Foundation project PRIME (LU1608/1-1) and the Eva Mayr-Stihl Foundation.