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No evidence for globally coherent warm and cold periods over the preindustrial Common Era

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Abstract and Figures

Earth’s climate history is often understood by breaking it down into constituent climatic epochs¹. Over the Common Era (the past 2,000 years) these epochs, such as the Little Ice Age2–4, have been characterized as having occurred at the same time across extensive spatial scales⁵. Although the rapid global warming seen in observations over the past 150 years does show nearly global coherence⁶, the spatiotemporal coherence of climate epochs earlier in the Common Era has yet to be robustly tested. Here we use global palaeoclimate reconstructions for the past 2,000 years, and find no evidence for preindustrial globally coherent cold and warm epochs. In particular, we find that the coldest epoch of the last millennium—the putative Little Ice Age—is most likely to have experienced the coldest temperatures during the fifteenth century in the central and eastern Pacific Ocean, during the seventeenth century in northwestern Europe and southeastern North America, and during the mid-nineteenth century over most of the remaining regions. Furthermore, the spatial coherence that does exist over the preindustrial Common Era is consistent with the spatial coherence of stochastic climatic variability. This lack of spatiotemporal coherence indicates that preindustrial forcing was not sufficient to produce globally synchronous extreme temperatures at multidecadal and centennial timescales. By contrast, we find that the warmest period of the past two millennia occurred during the twentieth century for more than 98 per cent of the globe. This provides strong evidence that anthropogenic global warming is not only unparalleled in terms of absolute temperatures⁵, but also unprecedented in spatial consistency within the context of the past 2,000 years.
Reconstruction skill and methods agreement in years 1 ad and 1000 ad a, Density of CRPS_RE values in PCR reconstructions based on: the full proxy network (dark yellow, the same as the PCR boxplot in Extended Data Fig. 9); proxy records extending at least to 1000 ad (green); and the records covering the full Common Era (blue). Numbers besides the curves indicate the percentage of grid cells with positive values. b, c, Maps showing the spatial distribution of CRPS_RE for the years 1000 ad (b) and 1 ad (c). Proxy locations are indicated with grey circles. d–f, As for a–c but for the CRPS_CE. g–i, As for a–c but for the RMSE. j–l, As for a–c but for the correlation coefficient. In general the spatial patterns between the time periods we analysed remain similar over time, but with areas of lower skill naturally extending backwards in time (see also the red line in Fig. 1). The largest decrease in skill generally occurs in the first millennium ad. m–o, Average correlation of ensemble median reconstructions accross all methods over the periods 1900–1999 ad (m), 1000–1099 ad (n) and 1–99 ad (o). More than 99% of correlations are positive in all three periods. Respectively 97%, 76% and 73% of correlations in the twentieth, eleventh and first centuries ad are above 0.28, which is the average α = 0.05 significance level given the autocorrelation in the reconstructions. In all periods the method agreement is larger in the Northern Hemisphere, particularly in the North Pacific and European domains, than in the Southern Hemisphere. Lowest agreement is found over tropical South America and Africa and over the Southern Ocean, the same areas that also exhibit the largest errors in the reconstructions.
… 
Unscreened proxy network a–e, As for Fig. 3 but using the full unscreened PAGES 2k temperature proxy database. Note that the methods used herein do not incorporate low-frequency records (with resolutions of less than 1 year); therefore, only 559 of the 692 records from the PAGES 2k database were used to generate this figure. Colours in maps indicate the century with the largest ensemble-based probability of containing the warmest (a–c) and coldest (d, e) 51-year period within each climatic epoch (see Methods). f, As for Fig. 4, but using the full unscreened PAGES 2k temperature proxy database. The figure shows the fraction of Earth’s surface (y axis) that simultaneously experienced the warmest (top panels) or coldest (bottom panels) multidecadal period (51 years) during each of five different epochs (see Methods). Each solid circle represents an ensemble member, plotted according to the year in which the largest area experienced peak warm/cold conditions. Horizontal grey shading represents the distribution from the same analysis based on multivariate AR1 noise fields, with darker shading indicating a higher probability. Boxplots on the right show area fractions integrated over time. The centre line is the median; the ends of the boxes represent the interquartile range; and whiskers represent the 90% range. Bold text in panel f represents epochs with reconstructed area fractions that are significantly larger than from the noise fields (Mann–Whitney U-test; α = 0.05). Recall that we searched for CWP maxima within the full 2,000-year reconstruction period. Unlike in Fig. 4, which used the screened proxy matrix, in this figure the period of largest warming within the 2,000-year range falls in the second century ad for one single CCA ensemble member, thus overlapping with the search windows of the RWP period. Therefore, circles representing the CWP have a black border to distinguish them from other epochs.
… 
101-year maxima and minima a–e, As for Fig. 3, but for 101-year instead of 51-year periods. Colours in maps indicate the century that has the largest ensemble-based probability of containing the warmest (a–c) and coldest (d, e) 51-year period within each climatic epoch (see Methods). f, As for Fig. 4, but for 101-year periods. The figure shows the fraction of Earth’s surface (y axis) that simultaneously experienced the warmest (top panels) or coldest (bottom panels) multidecadal period (51 years) during each of five different epochs (see Methods). Each solid circle represents an ensemble member, plotted according to the year in which the largest area experienced peak warm/cold conditions. Horizontal grey shading represents the distributions from the same analysis based on multivariate noise fields from an AR1 analysis, with darker colours indicating higher probabilities. Boxplots on the right show area fractions integrated over time. The centre line is the median; the ends of the boxes represent the interquartile range; and whiskers represent the 90% range. Bold text represents epochs with reconstructed area fractions significantly higher than those from the noise fields (Mann–Whitney U-test; α = 0.05). Recall that we searched for CWP maxima within the full 2,000-year reconstruction period. Unlike the 51-year maxima displayed in Fig. 4, some of the 101-year maxima within this 2,000-year range fall within the pre-1350 period, thus overlapping with the search windows of the RWP and MCA periods. Therefore, circles representing the CWP have a black border to distinguish them from other epochs.
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LETTER https://doi.org/10.1038/s41586-019-1401-2
No evidence for globally coherent warm and cold
periods over the preindustrial Common Era
Raphael Neukom1*, Nathan Steiger2, Juan José Gómez-Navarro3, Jianghao Wang4 & Johannes P. Werner5
Earth’s climate history is often understood by breaking it down
into constituent climatic epochs1. Over the Common Era (the
past 2,000 years) these epochs, such as the Little Ice Age2–4, have
been characterized as having occurred at the same time across
extensive spatial scales
5
. Although the rapid global warming seen
in observations over the past 150 years does show nearly global
coherence6, the spatiotemporal coherence of climate epochs
earlier in the Common Era has yet to be robustly tested. Here we
use global palaeoclimate reconstructions for the past 2,000 years,
and find no evidence for preindustrial globally coherent cold and
warm epochs. In particular, we find that the coldest epoch of the
last millennium—the putative Little Ice Age—is most likely to have
experienced the coldest temperatures during the fifteenth century
in the central and eastern Pacific Ocean, during the seventeenth
century in northwestern Europe and southeastern North America,
and during the mid-nineteenth century over most of the remaining
regions. Furthermore, the spatial coherence that does exist over the
preindustrial Common Era is consistent with the spatial coherence of
stochastic climatic variability. This lack of spatiotemporal coherence
indicates that preindustrial forcing was not sufficient to produce
globally synchronous extreme temperatures at multidecadal and
centennial timescales. By contrast, we find that the warmest period
of the past two millennia occurred during the twentieth century for
more than 98 per cent of the globe. This provides strong evidence
that anthropogenic global warming is not only unparalleled in
terms of absolute temperatures5, but also unprecedented in spatial
consistency within the context of the past 2,000 years.
The study of past climate provides an essential baseline from which
to understand and contextualize changes in the contemporary climate.
Since the formative period of modern Earth sciences in the 1800s, the
complex history of Earths climate has been conceptualized through
the construction of distinct climatic periods or epochs1–7. Several
terms for climatic epochs within the past 2,000 years have come into
wide use. Most prominent among these is the ‘Little Ice Age’ (LIA),
a term that was originally created to broadly describe glacier growth
in the Sierra Nevada mountains during the late Holocene (the past
few thousand years)2; later, the LIA was used to describe inferred late
Holocene glacial advances in many locations, particularly the European
Alps3,4. Over the past few decades, this term has been widely used
in palaeoclimatology and historical climatology to indicate a nearly
global, centuries-long cold climate state that occurred between roughly
1300 and 1850 (refs 5,8). This period is often contrasted with
the Mediaeval Warm Period, also known as the Mediaeval Climate
Anomaly (MCA)
8–10
, which is commonly associated with warm tem-
peraturesin 800–1200. The first millennium of the Common Era
has also been subdivided into the ‘Dark Ages Cold Period’ (DACP)
11,12
,
or ‘Late Antique Little Ice Age’ (LALIA)
13
, which occurred within about
400–800, and lastly the ‘Roman Warm Period’ (RWP)
12,14
, which
covers the first few centuries of the Common Era. We note that for all of
these epochs, no consensus exists about their precise temporal extent.
Each of these climatic epochs has its origin in pieces of palaeocli
-
matic evidence from the extratropical Northern Hemisphere, particu-
larly Europe and North America4,9–12. Climate-epoch narratives were
constructed to explain the early palaeoclimatic evidence, and later-de-
veloped time series from across the globe were situated within these
narrative frameworks. This process probably created the expectation
that Common Era climate epochs are global-scale phenomena. Loosely
defined epochs based on a few dozen specific proxies were hard to
falsify given the inherent noise of natural proxies, with, for example,
nearly all annually resolved proxies that cover the Common Era having
a signal-to-noise ratio of less than 1, and usually less than 0.5 (ref. 15).
Yet the association of a relatively small number of palaeoclimate proxy
records with global-scale phenomena did not come without contro-
versy and the discovery of proxy time series that did not match the
standard climate-epoch narratives4,10,16. Studies that have attempted
to assess the spatial coherence of Common Era climate epochs have
used relatively few proxy records (for example, 14 proxy time series17),
or only continentally averaged temperature reconstructions18, or only
one or two reconstruction methods8,12—a choice that has been shown
to limit the reliability of the assessment of temperature patterns19.
Here we test the hypothesis that there were globally coherent climate
epochs over the Common Era by using a collection of probabilistic,
global temperature reconstructions for the period 1–2000, derived
from a set of six different ensemble field reconstruction methodol-
ogies (seeMethods; wenote that we use ‘coherence’ here in its gen-
eral, non-signal-processing sense). The reconstructions are based on
techniques that vary widely in their assumptions and approaches to
the reconstruction problem. They span a broad range of complexity,
from basic proxy composites at the one end, to advanced statistical
techniques at the other that incorporate physical constraints and forc-
ing information from climate-model simulations. All methods use
the same set of input data, namely the annual records from the recent
PAGES 2k global temperature-sensitive proxy collection
20
(see Fig.1
and Methods). This multimethod, probabilistic framework allows us to
robustly assess the spatiotemporal homogeneity of climatic variability
over the Common Era.
At the original annual resolution, the reconstruction ensemble mean
shows no clear indication of a long period of years with globally con-
sistent below-average temperatures relative to the mean for 1–2000
(Fig.2a); the area fraction of warmth and cold shows high interannual
variability. Of the years before 1850, 97% had at least 10% of the globe
experiencing above-average temperatures, and 10% of the globe expe-
riencing below-average temperatures. It is only if the reconstructed
time series are smoothed over multidecadal timescales (seeMethods),
and if global area is shown in aggregate, that the classical picture of a
loosely defined LIA and MCA appears (Fig.2b and Extended Data
Fig.1). Yet the analysis in Fig.2 does not include information from
individual ensemble members (Extended Data Fig.1); nor does it indi-
cate spatial patterns of coherence, or provide a precise evaluation of the
climate-epochs hypothesis.
1Oeschger Centre for Climate Change Research and Institute of Geography, University of Bern, Bern, Switzerland. 2Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA.
3Department of Physics, University of Murcia, Murcia, Spain. 4The MathWorks Inc, Natick, USA. 5Bjerknes Center for Climate Research, Bergen, Norway. *e-mail: neukom@giub.unibe.ch
550 | NATURE | VOL 571 | 25 JULY 2019
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