Research ArticleCLIMATOLOGY

Mid-Holocene Northern Hemisphere warming driven by Arctic amplification

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Science Advances  11 Dec 2019:
Vol. 5, no. 12, eaax8203
DOI: 10.1126/sciadv.aax8203
  • Fig. 1 Global and Arctic surface temperature simulated by 13 climate models.

    (A and C) The mid-Holocene surface temperature (TS) anomalies (differences between 6 ka and 0 k) of 13 different climate models, averaged (A) globally (90°S-90°N) and (C) in the NH extratropics (30°N-90°N). (B and D) Multimodel relationships between surface temperature anomalies (B) in the Arctic (70°N-90°N) versus the global average and (D) in the Arctic versus the NH extratropics. (E) The annual mean surface temperature anomalies averaged across the 13 models. (F) The zonal mean surface temperature anomalies as a function of latitude in all 13 models (black lines) and averaged across the 4 warmest (red line) and 4 coldest (blue line) models.

  • Fig. 2 Surface temperature and Arctic sea ice responses.

    (A and B) Zonally averaged, latitude-time Hovmöller plots of surface temperature anomalies in (A) the four warmest models and (B) the four coldest models. The abscissa is time (months) and the ordinate is latitude. Arctic sea ice concentration (SIC; %) anomalies in (C and D) the four warmest models and (E and F) the four coldest models, averaged in (C and E) July to November and (D and F) December to April.

  • Fig. 3 Disentangling the impacts of Arctic sea ice loss and insolation forcing.

    Surface temperature responses to mid-Holocene (A and D) Arctic sea ice loss, (B and E) insolation forcing, and (C and F) total forcing (sum of sea ice loss and insolation). (A to C) Zonally averaged, latitude-time Hovmöller plots of anomalous surface temperature and (D to F) the annual mean SST anomalies. In (A) to (C), the abscissa is time (months) and the ordinate is latitude.

  • Fig. 4 Evaluating the climate models against paleo-proxy data.

    (A) Relationship between mid-Holocene surface temperature anomalies in the sub-Arctic (60°N-80°N), averaged over the grid points at which paleo-proxy data are available (abscissa), and the entire NH extratropics (30°N-90°N) (ordinate). The green dots are from the 13 climate model simulations examined in this study, and the red dot is from the paleo-proxy data. The gray shading superposed on the red dot indicates a 95% confidence interval range for the paleo-proxy data, bootstrapped via Monte Carlo simulation. Sub-Arctic surface temperature anomalies (B) reconstructed from the paleo-proxy data and (C) simulated by the four warmest climate models over the grid points at which the paleo-proxy estimates are available.

  • Fig. 5 Validating against multiple paleo-proxy datasets.

    Relationship between surface temperature anomalies in the sub-Arctic (60°N-80°N), averaged over the grid points at which paleo-proxy data are available (abscissa), and the entire NH extratropics (30°N-90°N) (ordinate). Paleo-proxy data are from (A) Bartlein et al. (36), (B) Sundqvist et al. (37), (C) Marcott et al. (15), and (D) Marsicek et al. (16). The green dots are from the 13 climate model simulations examined in this study, and the red dots are from the paleo-proxy data. The gray shading superposed on the red dot indicates a 95% confidence interval range for the paleo-proxy data, bootstrapped via Monte Carlo simulation. (A) is identical to Fig. 4A.

  • Table 1 The spatial correlation coefficient of the annual mean temperature anomalies between paleo-proxy data (37) and the individual climate model.

    The spatial correlation coefficient of the annual mean temperature anomalies between paleo-proxy data (37) and the individual climate model.. The second and third columns indicate the correlation coefficient and statistical significance, respectively. Statistically significant values, higher than 95% (p < 0.05), are in boldface.

    Climate models (from
    the warmest to
    coldest)
    Correlation
    coefficient
    Statistical
    significance
    CNRM-CM5 (warm)0.1286%
    CESM1-CAM5 (warm)0.0546%
    MRI-CGCM3 (warm)0.1998%
    GISS-E2-R (warm)0.0862%
    IPSL-CM5A-LR
    (median)
    0.2098%
    GFDL-CM2.1 (median)0.1076%
    CSIRO-Mk3-6-0
    (median)
    0.2599.7%
    BCC-CSM-1 (median)0.1593%
    FGOALS-s2 (median)0.2499.6%
    MPI-ESM-P (cold)0.1795%
    NCAR-CCSM4 (cold)0.1998%
    MIROC-ESM (cold)−0.0972%
    FGOALS-g2 (cold)0.1489%
  • Table 2 Summary of the PMIP3 simulations and two additional climate model simulations conducted for the purpose of this study.

    The fourth and fifth columns indicate the averaging periods (years) for the preindustrial (0 ka) and the mid-Holocene (6 ka) simulations, respectively. References for these PMIP3 models can be found in (39).

    PMIP3 modelsAtmosphere resolutions
    (lat × lon lev)
    Ocean resolutions
    (lat × lon lev)
    0 ka (years)6 ka (years)
    BCC-CSM-1T42 L26360 × 232 L40500100
    NCAR-CCSM40.9° × 1.25° L26320 × 384 L601050300
    CNRM-CM5T127 L31362 × 292 L42850200
    CSIRO-Mk3-6-0T63 L18192 × 192 L31500100
    FGOALS-g22.81° × 2.81° L26360 × 196 L30700685
    FGOALS-s21.67° × 2.81° L26360 × 196 L30501100
    GISS-E2-R2.0° × 2.5° L40288 × 180 L321200100
    IPSL-CM5A-LR1.875° × 3.75° L39182 × 149 L311000500
    MIROC-ESM2.8° × 2.8° L80256 × 192 L44630100
    MPI-ESM-PT63 L47256 × 220 L401150100
    MRI-CGCM3TL159 L48364 × 368 L51500100
    Additional modelsAtmosphere resolutionsOcean resolutions0 ka (years)6 ka (years)
    CESM1-CAM50.9° × 1.25° L26gx1v6 L60250250
    GFDL-CM2.12.0° × 2.5° L24360 × 384 L50150150

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/5/12/eaax8203/DC1

    Fig. S1. Mid-Holocene insolation anomalies.

    Fig. S2. Surface temperature anomalies simulated by climate models.

    Fig. S3. Testing the impact of mid-Holocene tropical cooling using CM2.1.

    Fig. S4. Same as Fig. 2 except for the second and third warmest/coldest model composites.

    Fig. S5. Autumn-winter surface heat fluxes in the Arctic.

  • Supplementary Materials

    This PDF file includes:

    • Fig. S1. Mid-Holocene insolation anomalies.
    • Fig. S2. Surface temperature anomalies simulated by climate models.
    • Fig. S3. Testing the impact of mid-Holocene tropical cooling using CM2.1.
    • Fig. S4. Same as Fig. 2 except for the second and third warmest/coldest model composites.
    • Fig. S5. Autumn-winter surface heat fluxes in the Arctic.

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