iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://pubmed.ncbi.nlm.nih.gov/31372180
Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era - PubMed Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Jun 12;12(8):643-649.
doi: 10.1038/s41561-019-0400-0. Epub 2019 Jul 24.

Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era

Affiliations

Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era

PAGES 2k Consortium et al. Nat Geosci. .

Abstract

Multi-decadal surface temperature changes may be forced by natural as well as anthropogenic factors, or arise unforced from the climate system. Distinguishing these factors is essential for estimating sensitivity to multiple climatic forcings and the amplitude of the unforced variability. Here we present 2,000-year-long global mean temperature reconstructions using seven different statistical methods that draw from a global collection of temperature-sensitive paleoclimate records. Our reconstructions display synchronous multi-decadal temperature fluctuations, which are coherent with one another and with fully forced CMIP5 millennial model simulations across the Common Era. The most significant attribution of pre-industrial (1300-1800 CE) variability at multi-decadal timescales is to volcanic aerosol forcing. Reconstructions and simulations qualitatively agree on the amplitude of the unforced global mean multi-decadal temperature variability, thereby increasing confidence in future projections of climate change on these timescales. The largest warming trends at timescales of 20 years and longer occur during the second half of the 20th century, highlighting the unusual character of the warming in recent decades.

PubMed Disclaimer

Conflict of interest statement

Competing Interests The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. Global mean surface temperature history over the Common Era.
a, Colored lines: 30-year low-pass filtered ensemble medians for the individual reconstruction methods. Gray shading: quantiles of all reconstruction ensemble members from all seven methods; the 2.5th and 97.5th percentiles are indicated with black dotted lines. Black: instrumental data [25] 1850–2017. b, Same as (a) but for 30- to 200-year bandpass filtered ensemble; instrumental data not shown.
Figure 2
Figure 2. Multi-decadal temperature variability in reconstructions and models and volcanic forcing over the past millennium.
Colored lines: Ensemble median reconstruction from the different methods, 30- to 200-year bandpass filtered. Gray shading: model simulation percentiles. Green: volcanic forcing [59].
Figure 3
Figure 3. Pre-industrial forcing response and magnitude of unforced MDV.
a Multi-decadal detection and attribution scaling factors over 1300–1800 CE for the CESM1-CAM5 model based on differently forced runs. Gray box-whisker plot: D&A experiment using fully forced runs. Golden, green and blue box-whisker plots: multivariate experiment combining runs with solar forcing only, volcanic forcing only and GHG forcing only. Circles represent the individual reconstruction methods (median). b Estimates of unforced natural variability based on the D&A regression residuals of the full-forcing experiment (gray), the standard deviation in pre-industrial control simulations (black) and reconstruction and model standard deviation during the period of low external forcing variability 850-1100 (brown; details see Methods). Boxes represent the interquartile range, whiskers the 90% range. Black points represent the individual model simulations.
Figure 4
Figure 4. Multi-decadal temperature trends over the Common Era.
a, 51-year trends in reconstructions (black, ensemble percentiles shaded) and instrumental data [25] (blue dashed), with temperature response to volcanic forcing [59] based on a Energy Balance Model (green, see Methods). For the trends, the years on the horizontal axis represent the end-year of the 51-year trends. Horizontal lines denote pre-industrial 97.5th percentiles in reconstructions (black), models (red dashed) and pre-industrial control runs (red dotted), including all ensemble members and years. b, Ensemble probability of largest trend occurring after 1850 CE as a function of trend length. Black: reconstructions; orange: reconstructions using noise-proxies; brown: random numbers.

Similar articles

Cited by

References

    1. Masson-Delmotte V, et al. Information from Paleoclimate Archives. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; 2013. pp. 383–464.
    1. Abram NJ, et al. Early onset of industrial-era warming across the oceans and continents. Nature. 2016;536:411–418. - PubMed
    1. Hegerl GC, Stefan Brönnimann, Andrew Schurer, Tim Cowan. The early 20th century warming: Anomalies, causes, and consequences. Wiley Interdisciplinary Reviews: Climate Change. 2018;9:e522. - PMC - PubMed
    1. Medhaug I, Stolpe MB, Fischer EM, Knutti R. Reconciling controversies about the ‘global warming hiatus’. Nature. 2017;545:41–47. - PubMed
    1. Deser C, Phillips A. An overview of decadal-scale sea surface temperature variability in the observational record. PAGES Magazine. 2017;25:2–6.