Letter | Published:

Mid-latitude net precipitation decreased with Arctic warming during the Holocene

Naturevolume 568pages8387 (2019) | Download Citation

Abstract

The latitudinal temperature gradient between the Equator and the poles influences atmospheric stability, the strength of the jet stream and extratropical cyclones1,2,3. Recent global warming is weakening the annual surface gradient in the Northern Hemisphere by preferentially warming the high latitudes4; however, the implications of these changes for mid-latitude climate remain uncertain5,6. Here we show that a weaker latitudinal temperature gradient—that is, warming of the Arctic with respect to the Equator—during the early to middle part of the Holocene coincided with substantial decreases in mid-latitude net precipitation (precipitation minus evapotranspiration, at 30° N to 50° N). We quantify the evolution of the gradient and of mid-latitude moisture both in a new compilation of Holocene palaeoclimate records spanning from 10° S to 90° N and in an ensemble of mid-Holocene climate model simulations. The observed pattern is consistent with the hypothesis that a weaker temperature gradient led to weaker mid-latitude westerly flow, weaker cyclones and decreased net terrestrial mid-latitude precipitation. Currently, the northern high latitudes are warming at rates nearly double the global average4, decreasing the Equator-to-pole temperature gradient to values comparable with those in the early to middle Holocene. If the patterns observed during the Holocene hold for current anthropogenically forced warming, the weaker latitudinal temperature gradient will lead to considerable reductions in mid-latitude water resources.

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Data availability

All of the proxy and instrumental climate records that were analysed in this study are from published sources. Supplementary Tables 1 and 2 include the citations to the original publications for each of the Holocene-long temperature and hydroclimate proxy records, respectively. The proxy data and basic metadata for the time series compiled for this study from these sources are available at the World Data Service for Paleoclimatology hosted by NOAA (https://www.ncdc.noaa.gov/paleo/study/25890). The landing page includes links to digital versions of the primary results (time series) generated by this study, including the (1) Holocene temperature composites by latitude (Fig. 3a–e), (2) Northern Hemisphere LTG (Fig. 3f) and (3) mid-latitude net precipitation reconstruction (Fig. 3h). The proxy temperature records for the past 2,000 years were compiled by the PAGES2k Consortium16 and are available at: https://www.ncdc.noaa.gov/paleo-search/study/21171. The CRU instrumental data are available at http://www.cru.uea.ac.uk/. PMIP3 model output is available at https://esgf-node.llnl.gov/projects/esgf-llnl/.

Code availability

The MATLAB code (https://www.mathworks.com/products/matlab.html) used to create the figures in this article was modified from code developed by Emile-Geay et al.33, which is available at https://github.com/CommonClimate/PAGES2k_phase2 under a free BSD licence.

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Acknowledgements

Funding for this research was provided by the Science Foundation Arizona Bisgrove Scholar award (BP 0544-13), the National Science Foundation (AGS-1602105 and EAR-1347221), and the State of Arizona Technology and Research Initiative Fund administered by the Arizona Board of Regents. We acknowledge support by the USGS Climate and Land Use Program (any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the US government). H.G. is Research Director at the Fonds de la Recherche Scientifique–FNRS (Belgium). We thank D. Coumou and USGS reviewers M. Robinson and T. Cronin for comments on the manuscript. This work benefited from the new compilation of proxy temperature records for the past 2,000 years that was led by the Past Global Changes (PAGES) project, and from discussions with colleagues at PAGES-sponsored workshops. We thank all original data contributors who made their data available. We also thank the leaders of, and the many contributors to, the data compilations that were integrated in this study.

Reviewer information

Nature thanks Matthew Kirby, Fredrik Charpentier Ljungqvist and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

  1. School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA

    • Cody C. Routson
    • , Nicholas P. McKay
    • , Darrell S. Kaufman
    •  & Michael P. Erb
  2. Université Catholique de Louvain, Earth and Life Institute, Georges Lemaître Center for Earth and Climate Research, Louvain-la-Neuve, Belgium

    • Hugues Goosse
  3. Roy J. Shlemon Center for Quaternary Studies, Department of Geology and Geophysics, University of Wyoming, Laramie, WY, USA

    • Bryan N. Shuman
  4. Florence Bascom Geoscience Center, US Geological Survey, Reston, VA, USA

    • Jessica R. Rodysill
  5. Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA

    • Toby Ault

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Contributions

C.C.R. conceived and designed the study with contributions to the conceptual framework from N.P.M., H.G., D.S.K. and T.A. C.C.R. compiled the dataset with data contributions from J.R.R. and B.N.S. N.P.M. built the database framework. C.C.R. and B.N.S conducted the proxy analyses with input from N.P.M, D.S.K. and H.G. M.P.E. conducted the PMIP3 model analyses. C.C.R. and D.S.K. wrote the paper with input from the other authors.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Cody C. Routson.

Extended data figures and tables

  1. Extended Data Fig. 1 Holocene insolation forcing by latitude and time.

    a, b, Change in (a) annual and (b) seasonal (JJA) insolation during the past 12,000 years caused by the Earth’s orbital cycle. Values are anomalies relative to present. Data from output of MATLAB code of ref. 38, using the calendar days option and based on orbital parameters of ref. 14.

  2. Extended Data Fig. 2 Northern Hemisphere LTG at three temporal scales.

    ac, Changes in LTG slope over (a) the instrumental period (twentieth century), (b) the past two millennia, and (c) Holocene (black) compared with Holocene annual latitudinal insolation gradient (red), and past two millennia LTGs binned to the same resolution as the Holocene data (dark blue). Gradients were calculated using linear regression across five 20° latitudinal composites as illustrated in Extended Data Fig. 8. Twentieth-century LTGs were calculated from CRU TS4.01 data15, last two millennia LTGs rely on the PAGES 2k network16, and Holocene-long LTGs use the new dataset presented in this study. Shading represents the one- and two-standard deviation bootstrapped confidence intervals over 500 iterations. Age and proxy temperature uncertainties included in the Holocene error estimations (Methods) smooth the error envelope with respect to the last two millennia, for which there is less age uncertainty16. The Holocene latitudinal insolation gradient uses data from ref. 14. The historical trend in a towards weaker gradients (less negative slopes) characterizes recent Arctic amplification.

  3. Extended Data Fig. 3 Calibrated hydroclimate records with insolation gradient and ice sheet area.

    a, Northern Hemisphere annual mean latitudinal insolation gradient14 and Laurentide Ice Sheet (LIS) area18. b, Calibrated hydroclimate records (n = 15, blue) with a fitted regression model using the annual insolation gradient and the LIS area. Shading represents the 95% bootstrapped uncertainty estimates (see Methods). Fitted dashed line is a simple linear model and the solid line includes an autoregressive (ar1) term for the residuals to account for autocorrelation in the hydroclimate records. The fitted solid line indicates that the mean hydroclimate change represents an increase in net precipitation of 16.8 ± 7 mm per 0.01 W m−2 per degree of latitude decrease in the annual insolation gradient since 8 ka. Earlier amplification of the dryness in these records can probably be attributed to ice-sheet effects. c, Spatial distribution of calibrated hydroclimate records. The map was generated using code and associated data from ref. 30.

  4. Extended Data Fig. 4 Change in zonal-mean quantities for mid-Holocene (6 ka) minus preindustrial in a nine-model mean.

    Each panel is a Hovmöller figure showing zonal-mean climate anomalies by latitude (0° N to 90° N, y-axis) and calendar month (1–12, x-axis). a, The change in forcing is strongest in summer, and the insolation gradient change is weaker through much of the year. b, High-latitude warming anomalies dominate between June and December, with reductions in sea-ice extent likely to be causing the anomalous propagation of polar warmth into winter. c, The localized meridional temperature gradient anomalies (the derivative of temperature) shows weaker temperature gradients at 70° N between September and June. Negative values indicate a reduced temperature gradient. During summer (June through September) the temperature gradient anomaly is negative between 15° N and 50° N. d, Changes in 500 hPa geopotential height. e, Vertically integrated zonal winds show reduced jet-stream strength for much of the year. f, Vertically integrated omega (vertical motion, with positive values indicating anomalous downward motion). g, Precipitation minus evaporation anomalies show decreases in mid-latitude net precipitation through much of the year. h, Evaporation. i, Total precipitation shows decreases in mid-latitude rainfall through much of the year. Large increases in localized total precipitation correspond to a shift in the intertropical convergence zone and increased monsoon strength. j, Convective precipitation shows enhanced monsoon systems. k, Large-scale precipitation (including extratropical cyclones) decreases from January through October, with the largest reductions in August. Vertically integrated quantities (e,f) are ‘mass-weighted’: the quantities are integrated on pressure levels from the surface to the top of atmosphere and divided by the standard gravity, then multiplied by −1 to give more easily interpretable quantities.

  5. Extended Data Fig. 5 PMIP3 model ensemble mid-Holocene minus preindustrial annual anomalies by latitude.

    a, Insolation anomalies showing decreased annual insolation at the Equator and enhanced insolation at the high latitudes. b, Temperature anomalies corresponding to the change in insolation. The higher temperatures at high latitudes and lower temperatures at low latitudes reduced the LTG at 6 ka by 0.011 °C per degree of latitude, as calculated using the same procedures as for the proxy data. c, Changes in hydroclimate variables. Precipitation (blue), large-scale precipitation (dashed blue), evaporation (red) and precipitation minus evaporation (black). The model spread for precipitation minus evaporation is shown in the grey band. Large positive and negative precipitation anomalies between 0° N and 30° N correspond to changes in monsoon strength and in the position of the intertropical convergence zone, which do not have strong agreement between models. Decreases in moisture between 30° N and ~55° N are smaller but consistent between models.

  6. Extended Data Fig. 6 Palaeo-temperature time series aggregated at different scales.

    ae, All Holocene temperature records are adjusted to a mean of zero and subdivided by the latitudinal bands used to calculate the Northern Hemisphere LTG. To generate the temperature composites (Fig. 3a–e), median values were used to avoid the influence of the outliers visible here (some of the outliers extend beyond the y axis spanning 10 °C in ae). f, A Hovmöller plot illustrating the evolution of Holocene temperature anomalies from the temperature proxy network binned into 5° latitudinal bands. The colour map is in temperature anomaly units of °C with respect to the mean of 0 to 2,000 years bp. g, h, High-latitude (50° N to 90° N, g) and low-latitude (10° S to 30° N, h) temperature composites, with the number of contributing records in grey (200-year bins), and a y axis spanning 3 °C. Shading represents the 95% bootstrapped uncertainty estimate, which includes estimate of age and calibration uncertainties (Methods). The low-latitude composite was subtracted from the high-latitude composite as one of the three methods used to calculate the LTG shown in Fig. 3f.

  7. Extended Data Fig. 7 Temperature composites spanning the last two millennia.

    ae, The temperature composites represent five 20° latitudinal bands and were used to scale the Holocene composites shown in Fig. 3a–e. Time series are all displayed on the same scale, with each y-axis spanning 3 °C (left side). The number of contributing records to each composite are shown in grey (20-year bins) (right y-axis) (data from ref. 16). Shading denotes the bootstrapped sampling with replacement 95% confidence intervals.

  8. Extended Data Fig. 8 Calculating the LTG.

    a, Average Equator-to-pole Northern Hemisphere LTG (red line) for the twentieth-century, calculated using CRU TS4.01 temperature data15 averaged across five latitude bands (blue symbols), and fit to robust linear regression, weighted by the cosine of latitude. b, LTG calculated using the second alternative method in which individual Holocene proxy records are scaled by latitude. CRU TS4.0115 temperature plotted by latitude in dark red. All the individual years available in the CRU data are plotted as the resulting broad dark red line. The interpolated PAGES 2k network data16 used to scale the Holocene records are plotted in bright red, and mean temperatures for 100-year binned Holocene records are plotted as blue circles. The Holocene records were scaled by the period (500–1,500 bp) overlapping with the PAGES 2k dataset, which in turn was calibrated using the CRU TS4.01data.

  9. Extended Data Fig. 9 Standardized Holocene hydroclimate proxy records from the mid-latitudes (30° N to 50° N).

    a–e, Time-series composites subdivided by dominant proxy types, with the number of contributing records in grey (200-year bins). Shading represents the 95% bootstrapped uncertainty estimate. f, g, Time-series composites by region. Mid-latitude (30° N to 50° N) hydroclimate in (f) North America (180° W to 45° W) and (g) Eurasia (45° W to 180° E) land area. North America was driest in the earliest Holocene (10 ka), with a gradual wetting trend to the present day. The Asian–European hydroclimate records suggest that the driest conditions occurred during the early Holocene (10 ka to 8 ka). The Eurasian region had increasing net precipitation to about 6 ka, then decreasing net precipitation to about 4 ka, followed by increasing net precipitation to the present day. h, Individual hydroclimate records contributing to the mid-latitude (30° N to 50° N) composite (Fig. 3h), illustrating the variability among records across the mid-latitudes. All time series are standardized to have a mean of 0 and a standard deviation of 1 over the 0–10 ka interval. All y-axes are in standard deviation (SD) units.

  10. Extended Data Fig. 10 Proxy network sensitivity tests.

    ae, Scatterplots showing the relation between decadal mean temperature at the proxy locations versus the average of the entire 20° latitudinal zone using gridded instrumental CRU TS4.01 temperature observations15. In the instrumental dataset, the mean temperature at the proxy locations explain between 77% and 96% of the variance in the latitudinal bands. The spread in data represents the overall temperature trend over the twentieth century. f, Mid-Holocene minus preindustrial (MH − PI) temperature averaged for the proxy locations (y-axis) versus the latitudinal averages (x-axis) from 12 PMIP3 climate models (symbols) across five latitudinal bands (colours). The models suggest that the proxy network captures the same mid-Holocene temperature anomalies as the latitudinal averages. g, Using gridded CRU TS4.01 precipitation observations15 to test the representativeness of the hydroclimate proxy network and the influence of standardization on the magnitude and variability in the composite time series. The standardized (mean = 0; variance = ±1 s.d.) decadally averaged composite is shown for the entire latitudinal zone 30° N to 50° N (orange squares) and for the proxy locations (green diamonds), along with the latitudinal average in native units (purple circles). The standardized mean from the proxy locations closely tracks the variability of the standardized and native unit latitudinal averages. h, Testing the number of proxy records needed to characterize Holocene hydroclimate changes in the mid-latitudes. Proxy record composites with iteratively smaller sample sizes were correlated with the final mid-latitude composite. The solid and dashed lines show the strength of correlation (R and P values, respectively) between the mid-latitude hydroclimate composite based on the full dataset of 72 records and composites using a randomly selected subset of fewer records. The error envelope shows the 95% bootstrapped random sampling confidence intervals. Correlation with the final composite begins to plateau near 40 records, suggesting our sample size of 72 is sufficient to represent the region.

Supplementary information

  1. Supplementary Table 1 Northern Hemisphere (10°S-90°N) temperature proxy records used in this study, sorted from north to south

    Information includes site, location, elevation, proxy type, archive type, seasonality as inferred by the original authors, and bibliographic reference. Proxy data time series complied for this study are available at the World Data Service for Paleoclimatology at NOAA (https://www.ncdc.noaa.gov/paleo/study/25890).

  2. Supplementary Table 2 Mid-latitude (30°N-50°N) hydroclimate proxy records used in this study, sorted from north to south

    Information includes site, location, elevation, proxy type, archive type, seasonality as inferred by the original authors, and bibliographic reference. Proxy data time series complied for this study are available at the World Data Service for Paleoclimatology at NOAA (https://www.ncdc.noaa.gov/paleo/study/25890).

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