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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" xml:lang="en" dtd-version="3.0" article-type="research-article"><?xmltex \bartext{Research article}?>
  <front>
    <journal-meta><journal-id journal-id-type="publisher">ACP</journal-id><journal-title-group>
    <journal-title>Atmospheric Chemistry and Physics</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1680-7324</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-22-8843-2022</article-id><title-group><article-title>Volcanic stratospheric injections up to 160 Tg(S) yield a Eurasian winter warming indistinguishable<?xmltex \hack{\break}?> from internal variability</article-title><alt-title>Negligible Eurasian winter warming for eruptions up to 160 Tg(S)​​​​​​​</alt-title>
      </title-group><?xmltex \runningtitle{Negligible Eurasian winter warming for eruptions up to 160\,Tg(S)​​​​​​​}?><?xmltex \runningauthor{K. DallaSanta and L. M. Polvani}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>DallaSanta</surname><given-names>Kevin</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff2 aff3 aff4">
          <name><surname>Polvani</surname><given-names>Lorenzo M.</given-names></name>
          <email>polvani@gmail.com</email>
        <ext-link>https://orcid.org/0000-0003-4775-8110</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>NASA Goddard Institute for Space Studies, New York, New York, USA​​​​​​​</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York, USA</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Department of Earth and Environmental Sciences, Columbia University, New York, New York, USA</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, USA</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Lorenzo M. Polvani (polvani@gmail.com)</corresp></author-notes><pub-date><day>8</day><month>July</month><year>2022</year></pub-date>
      
      <volume>22</volume>
      <issue>13</issue>
      <fpage>8843</fpage><lpage>8862</lpage>
      <history>
        <date date-type="received"><day>24</day><month>January</month><year>2022</year></date>
           <date date-type="rev-request"><day>3</day><month>February</month><year>2022</year></date>
           <date date-type="rev-recd"><day>1</day><month>June</month><year>2022</year></date>
           <date date-type="accepted"><day>2</day><month>June</month><year>2022</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2022 </copyright-statement>
        <copyright-year>2022</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d1e113">Early observational and modeling work suggested that low-latitude volcanic eruptions, comparable
to the one of Pinatubo in 1991 or Krakatau in 1883, cause substantial surface warming over the
northern continents at mid-latitudes in winter. The proposed mechanism consists of the
formation of an anomalously strong Equator-to-pole temperature gradient in the stratosphere due to
the presence of volcanic aerosols in the tropics, which are accompanied by an acceleration of the
stratospheric polar vortex, which then shifts the Northern Annular Mode into a positive phase,
resulting in warming surface temperatures over Eurasia.</p>

      <p id="d1e116">However, a large body of research in the past decade has shown that, for eruptions such as
Pinatubo or Krakatau, no such warming is seen in simulations with more recent climate models
which, in general, have much finer vertical and horizontal resolution than the early ones, and
which have separated the forced response from the internal variability by using large ensembles of
integrations. Since the proposed physical mechanism is sound, it is then possible that eruptions
comparable to those of Pinatubo or Krakatau are simply too weak, but even larger ones might indeed be
capable of causing Eurasian surface warming in winter.</p>

      <p id="d1e119">In this study, we explore this possibility using a state-of-the-art, stratosphere-resolving
climate model, forced with prescribed aerosols from the Easy Volcanic Aerosol protocol. We
consider eruptions with stratospheric sulfur injections of 5, 10, 20, 40, 80, and 160 Tg(S). With
20-member ensembles, we find that with injections of 20 Tg(S) or more – roughly twice the
amplitude of the Pinatubo and Krakatau eruptions – our model simulates a winter surface warming over
Eurasia, which is statistically significant with a <inline-formula><mml:math id="M1" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test given our 20-member ensembles.
However, the forced volcanic signal on Eurasian winter surface temperatures is very small, barely
exceeding the 1<inline-formula><mml:math id="M2" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> range of internal variability for the 160 Tg(S) injection case, and much
smaller for smaller eruptions. Most importantly, the number of eruptions needed to
establish statistical significance is considerably larger than the number of eruptions known to
have occurred in the past 2000 years.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e145">Large, low-latitude eruptions, such as the 1815 eruption of Mount Tambora in the Lesser Sunda
Islands, can inject considerable amounts of sulfate into the lower stratosphere. Since the
Brewer–Dobson circulation advects tracers upwards and polewards in the tropics <xref ref-type="bibr" rid="bib1.bibx28" id="paren.1"/>,
the volcanic aerosols from such eruptions have long residence times (from many months to years),
making them capable of impacting surface climate in a substantial way. That impact is primarily a
reduction in surface temperature, as the aerosols shield the surface from incoming solar radiation
and cause cooling. It is thus not immediately obvious how such large eruptions would produce any
surface <italic>warming</italic>.</p>
      <p id="d1e154">Nonetheless, a series of observational and modeling studies, starting in the early 1990s and
continuing to this day, have argued that low-latitude eruptions comparable to the one of Krakatau in
1883, or Pinatubo in 1991, do in fact cause surface warming over the Northern Hemisphere (NH)
continents in the winters following the eruption. This surprising result was first reported in
observational studies <xref ref-type="bibr" rid="bib1.bibx34 bib1.bibx35" id="paren.2"/> and initially supported by modeling studies
<xref ref-type="bibr" rid="bib1.bibx17 bib1.bibx20" id="paren.3"/>. However, those observational results suffered from serious
methodological flaws: to cite one example, the early claim of <xref ref-type="bibr" rid="bib1.bibx34" id="text.4"/> was based on a mere
12 eruptions, half of which did not actually occur in the tropics, averaged together irrespective of
amplitude, commingling first and second post-eruption winters. In addition, the early low-resolution
modeling results have not been replicated by the vast majority of later studies of those same
eruptions – roughly all the major events since pre-industrial times – with stratosphere-resolving
models at much higher horizontal and vertical resolution (e.g., <xref ref-type="bibr" rid="bib1.bibx38 bib1.bibx13 bib1.bibx5" id="altparen.5"/>).</p>
      <p id="d1e169">In spite of these later results, the idea that low-latitude eruptions might cause winter warming at
Northern Hemisphere high latitudes has remained compelling, mostly because the original claims were predicated
on a sound physical mechanism. As originally proposed by <xref ref-type="bibr" rid="bib1.bibx17" id="text.6"/> and <xref ref-type="bibr" rid="bib1.bibx21" id="text.7"/>,
that mechanism consists of three steps: (1) the sulfate aerosols of volcanic origin in the tropical
lower stratosphere absorb longwave radiation (LW) and cause anomalous warming in that region, and
(2) this yields an enhanced Equator-to-pole temperature gradient which results in an anomalously
strong stratospheric polar vortex during the winter months (via simple thermal wind balance) which,
in turn, (3) induces a more positive phase of the Northern Annular Mode (NAM) at tropospheric
mid-latitudes, accompanied by warmer Eurasian surface temperatures. We refer to this sequence of
events as the “stratospheric pathway” mechanism.</p>
      <p id="d1e178">Starting from the first link in the causality chain, it is widely documented that recent-generation
climate models are able to simulate tropical lower-stratospheric warming in response to low-latitude
volcanic eruptions. Figure 3 of <xref ref-type="bibr" rid="bib1.bibx13" id="text.8"/>, for instance, clearly shows that such
post-eruption warming (typically of several <inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) is simulated in models for all large eruptions
since 1870. Furthermore, as demonstrated by <xref ref-type="bibr" rid="bib1.bibx6" id="text.9"/>, those same models are able to
capture the weak acceleration of the polar vortex (typically of the order of a few meters per second) for the two
largest events, the 1883 Krakatau and the 1991 Pinatubo eruptions. Why, then, are those models
unable to produce a statistically significant forced post-eruption Eurasian surface winter warming?</p>
      <p id="d1e197">An answer to this conundrum was proposed by <xref ref-type="bibr" rid="bib1.bibx30" id="text.10"/> who, focusing specifically on the
1991 Pinatubo eruption alone to avoid averaging large and small eruptions together, analyzed three
large ensembles of model runs and showed that a polar vortex acceleration of a few meters per second is too small
to impact the tropospheric NAM in a statistically significant way. Simply put, the large natural
variability of the mid-latitude winter circulation completely overwhelms any forced signal coming
from the stratosphere for that eruption. This result was recently – and independently – confirmed
by <xref ref-type="bibr" rid="bib1.bibx1" id="text.11"/> with a much larger ensemble of runs of a stratosphere-resolving model (100
members). As in <xref ref-type="bibr" rid="bib1.bibx30" id="text.12"/>, that more recent study demonstrates that while a statistically
significant volcanically forced acceleration of the polar vortex can be detected (in a model) with a
sufficiently large ensemble of runs, for the 1991 Pinatubo eruption that forced acceleration is just
too small to cause a statistically significant shift in the winter North Atlantic Oscillation
(NAO) and, consequently, of Eurasian surface temperatures.</p>
      <p id="d1e209">One may argue that the 1991 Pinatubo eruption was peculiar in some way and may not be
representative of other eruptions. To address that question <xref ref-type="bibr" rid="bib1.bibx29" id="text.13"/> examined the other
large, low-latitude event of the industrial era: the 1883 eruption of Mount Krakatau. That event
not only falls within the instrumental period of many temperature reconstructions (so that we have a
robust estimate of the surface temperature anomalies), but literally hundreds of model simulations
of that eruption are available from the Coupled Model Intercomparison Project (CMIP). Examining
several temperature reconstructions, <xref ref-type="bibr" rid="bib1.bibx29" id="text.14"/> highlighted that the weak Eurasian surface
warming observed in the winter following that eruption falls well within the natural variability of
Eurasian surface temperatures. Furthermore, examining CMIP model output, they confirmed the absence of a
volcanically forced response in the surface temperatures at Northern Hemisphere mid-latitudes in the first
winter following the Krakatau eruption.</p>
      <p id="d1e218">At this point, then, one is inevitably led to ask: if Pinatubo and Krakatau are not large enough, how
large does an eruption need to be to cause winter surface warming at Northern Hemisphere mid-latitudes? At
the upper boundary, in a geoengineering context, it has recently been shown that large and <italic>sustained</italic> stratospheric sulfate injections do indeed produce winter warming over Eurasia
(<xref ref-type="bibr" rid="bib1.bibx22" id="altparen.15"/>, see their Fig. 8, bottom right panel), and this surface warming (which is
absent in the summer months) has been linked to stratosphere–troposphere dynamical coupling
affecting the NAO <xref ref-type="bibr" rid="bib1.bibx4" id="paren.16"/>. <xref ref-type="bibr" rid="bib1.bibx10" id="text.17"/> also found a robust impact of
sustained lower stratospheric tropical warming on the NAO, using an idealized model. While these
studies suggest that the stratospheric pathway to a winter Eurasian surface warming can indeed be
operative, the sulfate injection in <xref ref-type="bibr" rid="bib1.bibx22" id="text.18"/> is equivalent to several Pinatubo-size
eruptions each year, and sustained for many decades: such forcing is not comparable to any realistic
eruption. One would like to examine stratospheric injections typical to actual eruptions and,
starting from eruptions comparable to those of Pinatubo or Krakatau, methodically increase the amplitude of
the injection until a clear winter warming over Eurasia appears.</p>
      <p id="d1e236">A first step in that direction was recently taken by <xref ref-type="bibr" rid="bib1.bibx1" id="text.19"/>. Using a state-of-the-art
model they performed and analyzed large-ensembles of idealized low-latitude eruptions with
stratospheric sulfur injections ranging from 2.5 to 20 Tg(S), using the Easy Volcanic Aerosol (EVA)
protocol of <xref ref-type="bibr" rid="bib1.bibx43" id="text.20"/> to generate the aerosol distributions. They report that for
injections of 10 Tg(S) or larger, a statistically significant forced warming pattern is seen in
their model, at latitudes northward of 55<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N over a reduced set of longitudes (10–90<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E). While this is an interesting result, the actual value of the forced warming produced by a 10 Tg(S) eruption is at most 0.75 <inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C (depending on specific regions selected). Such a value, it is
important to note, is smaller than the natural year-to-year variability in surface temperature over
Eurasia, as computed by <xref ref-type="bibr" rid="bib1.bibx29" id="text.21"/> from three temperature datasets spanning the
1850-to-present period (see their Fig. 3; variability is computed therein over the region 40–70<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
0–150<inline-formula><mml:math id="M8" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E). Also, even for a 20 Tg(S) eruption, the largest amplitude explored in
<xref ref-type="bibr" rid="bib1.bibx1" id="text.22"/>, the largest Eurasian warming in their model is 1.5 <inline-formula><mml:math id="M9" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C, which falls within
the 2<inline-formula><mml:math id="M10" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> range of natural variability. Hence, while that study has demonstrated the existence
of a statistically significant warming signal in a model by using a sufficiently large ensemble and
a sufficiently large injection, the signal they report would hardly be exceptional: the winter
following a 20 Tg(S) eruption would not be distinguishable from many other anomalously warm
winters which are not preceded by a large, low-latitude eruption.</p>
      <p id="d1e313">In this paper, building on the findings of <xref ref-type="bibr" rid="bib1.bibx1" id="text.23"/>, we perform a similar exercise but
with a different goal. Rather than ask: <italic>How large does an eruption need to be to produce a statistically significant surface winter warming over Eurasia?</italic> We ask: <italic>How large does an eruption need to be to produce a forced winter warming over Eurasia that is substantially larger than the natural variability?</italic> The key idea is that one can always produce a statistically
significant result by enlarging the ensemble size, thus reducing the noise and capturing the
forced signal. But, in practice, what really matters is how large that forced signal is in
comparison with the unforced variability. As we will show, our findings indicate that eruptions as
large as 160 Tg(S) are unable to produce a forced winter Eurasian warming that exceeds natural
variability in a significant way.</p>
      <p id="d1e325">Our paper is structured as follows: in the next section we describe the model used, the protocol to
generate a progressively larger sequence of idealized volcanic aerosol forcings, the simulations
performed, and the analysis techniques employed herein. We specifically limit our study to
eruptions occurring during neutral phases of the El Niño Southern Oscillation (ENSO), to
characterize the volcanic impact without the (potentially) confounding influence of anomalous
conditions in the tropical Pacific. In Sect. 3 we examine the impact of our idealized volcanic
eruptions on the atmospheric circulation, in the stratosphere and in the troposphere, with
particular attention on the response of the NAM which underlies the surface warming. We turn our
attention to the latter in Sect. 4, and examine the Eurasian temperature response to our idealized
eruptions, comparing it with the one from Pinatubo and Krakatau in the same model. We conclude the paper
with a brief summary and a discussion of our model results in light of the observed eruptions of the
past 2500 years.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>The model</title>
      <p id="d1e343">All the simulations performed and analyzed here were carried out with the NASA Goddard Institute for
Space Studies (GISS) model E2.2-AP, a high-top model developed for research questions in which the
stratosphere plays an important role <xref ref-type="bibr" rid="bib1.bibx32 bib1.bibx27" id="paren.24"/>. The atmospheric component has 2<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
latitude–longitude horizontal resolution and 102 levels in the vertical, with a spontaneously
generated Quasi-Biennial Oscillation <xref ref-type="bibr" rid="bib1.bibx31" id="paren.25"/>, and improved stratospheric fidelity compared
with its low-top counterpart, model E2.1 <xref ref-type="bibr" rid="bib1.bibx27" id="paren.26"/>. For this study, we have configured the
model with coupled ocean, sea ice, and land components. However, the chemistry is non-interactive,
so that aerosols, ozone, and other trace gases (not including water vapor) are prescribed from
forcing files. While this makes our simulations not entirely physically consistent (as tracer gases
and aerosols are not transported by the model winds), it has the advantage that volcanic aerosols
can be prescribed precisely, rendering our findings highly reproducible. A similar strategy was
adopted by <xref ref-type="bibr" rid="bib1.bibx1" id="text.27"/>. We emphasize that the GISS model E2.2-AP was a contributing member
to the Sixth Coupled Model Intercomparison Project (CMIP6; <xref ref-type="bibr" rid="bib1.bibx15" id="altparen.28"/>), and therefore its
climate simulations have been carefully validated.</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>The volcanic forcing</title>
      <p id="d1e380">Volcanic aerosols in the GISS E2.2-AP simulations discussed below were prescribed from external
files created following the Easy Volcanic Aerosol protocol (<xref ref-type="bibr" rid="bib1.bibx43" id="altparen.29"/>), which has
also been adopted for the Volcanic Model Intercomparison Project (VolMIP; <xref ref-type="bibr" rid="bib1.bibx47" id="altparen.30"/>).
EVA generates spatiotemporally varying aerosol properties for a given eruption from a few input
parameters, and was calibrated using observations of the 1991 Pinatubo eruption and historical
reconstructions. The key advantage of using EVA is that it allows us to span a wide range of
eruption amplitudes with forcings that are reproducible across different climate models.</p>
      <p id="d1e389">EVA takes a handful of user-specified parameters as input, and then computes aerosol extinction
coefficients, the effective aerosol radius, the single scattering albedo, and the scattering
asymmetry factor as functions of time and latitude. In our model only the first two are used, while
the latter two are internally set <xref ref-type="bibr" rid="bib1.bibx18" id="paren.31"/>. With reference to Table 1 of
<xref ref-type="bibr" rid="bib1.bibx43" id="text.32"/>, the parameters for the eruptions simulated here are as follows:
<list list-type="bullet"><list-item>
      <p id="d1e400"><italic>Latitude</italic>: this is set to 0, as the stratospheric pathway requires large stratospheric
injections, and these are greatest for volcanoes near the Equator (for reference: Tambora is at
8<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, Krakatau at 6<inline-formula><mml:math id="M13" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S, and Pinatubo at 15<inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N).</p></list-item><list-item>
      <p id="d1e433"><italic>Month</italic>: we set this to June, as the 1991 Pinatubo eruption occurred around 15 June,
noting that the 1883 Krakatau eruption was in August, and the 1815 Tambora eruption was in April,
so that in all these cases a substantial tropical lower-stratospheric warming was present in the
late fall when the polar vortex starts to form.</p></list-item><list-item>
      <p id="d1e439"><italic>Hemispheric asymmetry</italic>: this is set to 1, for simplicity (we may explore asymmetric
eruptions in a later study but, as will become apparent later, there may not be a need to do so).</p></list-item><list-item>
      <p id="d1e445"><italic>Sulfur injection</italic>: this is the key parameter that controls the amplitude of the eruption,
and here we explore the values 5, 10, 20, 40, 80, and 160 Tg(S).</p></list-item></list>
It is important to note that, in the EVA framework, the 1991 Pinatubo eruption corresponds to a
sulfur injection of 9 Tg(S). These injections, therefore, span the approximate range from
<inline-formula><mml:math id="M15" display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">2</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math></inline-formula> to <inline-formula><mml:math id="M16" display="inline"><mml:mrow><mml:mn mathvariant="normal">16</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math></inline-formula> the Pinatubo value, in a simple doubling progression. The zonal
mean aerosol optical depth at 550 nm in the first 3 post-eruption years, and the zonal mean
extinction coefficient as a function of latitude and height in the first post-eruption winter, as
derived from EVA, are shown in Fig. <xref ref-type="fig" rid="Ch1.F1"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><?xmltex \def\figurename{Figure}?><label>Figure 1</label><caption><p id="d1e480">The EVA aerosols for eruptions used in this study. All eruptions are in June and at the
Equator, with injections of 5, 10, 20, 40, 80, and 160 Tg(S), from top to bottom. Left column:
zonally averaged, 550 nm aerosol optical depth (AOD) for the first 3 years of forcing. Right
column: zonally averaged, latitude–height distribution of extinction coefficients (Ext), averaged
over the first winter (December–January–February) following the June eruptions. Rows are labeled
by the mass (in Tg) of the sulfur injection.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f01.png"/>

        </fig>

      <p id="d1e490">We recognize that, since it was calibrated on the 1991 Pinatubo eruption, EVA's accuracy for large
injections is not easily validated – due to the dearth of observations and the large intermodel spread
(see, e.g., <xref ref-type="bibr" rid="bib1.bibx8" id="altparen.33"/>) – and could therefore be partially unrealistic. Nonetheless, the
EVA framework offers a simple, reproducible, and methodical way of exploring progressively larger
eruptions. Importantly, it also allows us to compare results with those of <xref ref-type="bibr" rid="bib1.bibx1" id="text.34"/>, who
also used EVA forcings such as ours, and who simulated eruptions with injection amplitudes of 2.5,
5, 10, and 20 Tg(S).</p>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>The model simulations</title>
      <p id="d1e507">Prior to simulating individual eruptions, we carry out a 230-year control integration with
pre-industrial forcings, including pre-industrial background aerosols as defined by the EVA. We discard
the first 30 years of that integration, as the model equilibrates (at least in the atmosphere) to
the EVA background aerosols which are different from the historical aerosols used for the
pre-industrial integrations performed for CMIP6. We then use the remaining 200 years to evaluate
the unforced interannual variability, and to select initial conditions for our idealized eruptions.</p>
      <p id="d1e510">Next, for each of the six injection amplitudes detailed above, we perform a set of 20 simulations,
each integrated for 10 years. The 20 members of each ensemble share identical forcings, and only
differ in their initial conditions. The 20 different initial conditions are chosen from the
200-year control. Specifically, to avoid confounding the response to the eruption with El Niño
Southern Oscillation, the initial conditions for all eruptions are selected to be on 1 June
of ENSO-neutral years, which we identify using the widely used Niño 3.4 index
<xref ref-type="bibr" rid="bib1.bibx44" id="paren.35"/>. Furthermore, all initial conditions are separated by at least a decade, to
ensure sample independence.</p>
      <p id="d1e516">While some studies have suggested that the winter warming signal is insensitive to the ENSO phase
(e.g., <xref ref-type="bibr" rid="bib1.bibx7 bib1.bibx40" id="altparen.36"/>), those suggestions have recently been questioned
<xref ref-type="bibr" rid="bib1.bibx9" id="paren.37"/>. In keeping with our overall approach to avoid unnecessary confusion, therefore,
we focus here solely on ENSO-neutral eruptions. We intend to investigate the role of different ENSO
initial conditions in a subsequent study.</p>
</sec>
<sec id="Ch1.S2.SS4">
  <label>2.4</label><title>The post-eruption anomalies</title>
      <p id="d1e533">Two ways for computing the post-eruption anomalies have been previously employed in the literature.
We will be using both in this study, as appropriate. We will also show that they yield similar
results. In both cases, we will focus uniquely on the December–January–February (DJF) mean in the first post-eruption winter. In fact, we will demonstrate that there is no good
reason to include the second post-eruption winter as suggested in some earlier studies
(e.g., <xref ref-type="bibr" rid="bib1.bibx34 bib1.bibx37" id="altparen.38"/>).</p>
      <p id="d1e539">First, the post-eruption anomalies can be defined as the paired difference from the pre-industrial
(PI) control integration beginning with the same initial conditions (e.g, as
in <xref ref-type="bibr" rid="bib1.bibx10" id="altparen.39"/>). This definition has the advantage of isolating the forced response from any
concurrent low-frequency variability (i.e., anything slower than the 6-month timescale from the June
eruption to the first DJF). Its disadvantage is that a companion “unperturbed” model integration
– i.e., one without the volcanic eruption – is needed. Hence, such anomalies cannot be evaluated
for reanalyses, or for temperature reconstructions, or for many existing model simulations
(including the CMIP output). We will refer to them as the “difference-from-control-run”
anomalies and designate them with the symbol <inline-formula><mml:math id="M17" display="inline"><mml:mi mathvariant="normal">Δ</mml:mi></mml:math></inline-formula>.</p>
      <p id="d1e552">Second, the post-eruption anomalies can be defined as the difference from the average of a specified
number of years prior to the eruption (typically 3 or 5 years, or more;
e.g., <xref ref-type="bibr" rid="bib1.bibx13" id="altparen.40"/>). We will refer to these as the “difference-from-reference-period”
anomalies, and designate them with the symbol <inline-formula><mml:math id="M18" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>. This definition, which has been widely
used in the literature, has the advantage of being equally applicable to model output and to reanalyses
or reconstructions; it is thus ideal for comparing model simulations to observations. While it
suffers from the possible interference of low-frequency natural variability, it can be validated by
varying the length of the pre-eruption reference period, to ensure that the results do not
significantly depend on that length, as was done by <xref ref-type="bibr" rid="bib1.bibx29" id="text.41"/>. To be consistent with that
paper, here we use the five winters prior to the June eruption as the reference period. We have
checked that our conclusions are unchanged when using only three prior winters as the reference
period.</p>
</sec>
<sec id="Ch1.S2.SS5">
  <label>2.5</label><title>The response and its significance</title>
      <p id="d1e581">In this study we define the “response” of a quantity <inline-formula><mml:math id="M19" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula> to an eruption with a given injection
amplitude as the ensemble mean of the anomalies in the first post-eruption winter, designated
<inline-formula><mml:math id="M20" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>. Since individual members are identically forced and only differ in their
initial conditions, averaging over the latter removes (to some extent, at least) the influence of
internal variability, leaving behind the forced response. This method, pioneered by
<xref ref-type="bibr" rid="bib1.bibx12" id="text.42"/>, is now widely used and should not be controversial. We emphasize, however, that
it is incorrect to average together eruptions with differing stratospheric injections, as that
confounds forced responses of different amplitudes.</p>
      <p id="d1e607">To assess the significance of the response we employ several approaches. First, we use a canonical
<inline-formula><mml:math id="M21" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test (e.g., <xref ref-type="bibr" rid="bib1.bibx45" id="altparen.43"/>, Sect. 6.6.6). Since each model run with an eruption is paired with
the corresponding time period in the PI control with same initial conditions but without the eruption, for any quantity
<inline-formula><mml:math id="M22" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula> of interest we compute <inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow></mml:math></inline-formula>, the difference between the run with the eruption and the
paired period in the control run. The <inline-formula><mml:math id="M24" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> statistic is then defined as
<inline-formula><mml:math id="M25" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>≡</mml:mo><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:msqrt><mml:mi>N</mml:mi></mml:msqrt><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>, where <inline-formula><mml:math id="M26" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> is the ensemble mean
of <inline-formula><mml:math id="M27" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M28" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> its standard deviation across the ensemble, and <inline-formula><mml:math id="M29" display="inline"><mml:mi>N</mml:mi></mml:math></inline-formula> is the size of the
ensemble. This statistic is compared against tabulated values for rejection of the null hypothesis
(i.e., <inline-formula><mml:math id="M30" display="inline"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0</mml:mn></mml:mrow></mml:math></inline-formula>) at 95 % confidence with <inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mi>N</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula> members.</p>
      <p id="d1e738">An important theme of this study is the relation between <inline-formula><mml:math id="M32" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>, <inline-formula><mml:math id="M33" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>, and <inline-formula><mml:math id="M34" display="inline"><mml:mi>N</mml:mi></mml:math></inline-formula>.
It is well appreciated that an arbitrarily small signal can be made statistically significant by
using a sufficiently large ensemble, scaling as <inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:mi>N</mml:mi><mml:mo>∼</mml:mo><mml:mo>(</mml:mo><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:msup><mml:mo>)</mml:mo><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. Therefore,
an alternative way to evaluate the importance of the response is to turn things around and ask
instead: given <inline-formula><mml:math id="M36" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> and <inline-formula><mml:math id="M37" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>, what is the smallest value of <inline-formula><mml:math id="M38" display="inline"><mml:mi>N</mml:mi></mml:math></inline-formula> for which
the null hypothesis can be rejected at the 95 % level? This is accomplished by solving
<inline-formula><mml:math id="M39" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>(</mml:mo><mml:mi>N</mml:mi><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:msqrt><mml:mi>N</mml:mi></mml:msqrt><mml:mo>=</mml:mo><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula> for <inline-formula><mml:math id="M40" display="inline"><mml:mi>N</mml:mi></mml:math></inline-formula>. The solution, denoted <inline-formula><mml:math id="M41" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>,
is obtained numerically using the values of <inline-formula><mml:math id="M42" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>(</mml:mo><mml:mi>N</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> for a 95 % confidence level. The quantity
<inline-formula><mml:math id="M43" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> offers a different perspective on the response: when <inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is very
large, we deduce that the response is tiny, since a huge ensemble is needed to establish whether it
is statistically significant.</p>
      <p id="d1e912">Even more naively, leaving aside any consideration of ensemble size, we will consider the simple
signal-to-noise ratio <inline-formula><mml:math id="M45" display="inline"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>. When this quantity is smaller than 1,
the signal is smaller than the noise: this fact speaks for itself. But there is an even more
important version of signal-to-noise that we also wish to consider. For any variable <inline-formula><mml:math id="M46" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula> of
interest, in our case Eurasian winter surface temperature, primarily, we compute from the long
pre-industrial control run the standard deviation of the quantity <inline-formula><mml:math id="M47" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mi>X</mml:mi></mml:mrow></mml:math></inline-formula>, i.e., the difference
between <inline-formula><mml:math id="M48" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula> in any winter and <inline-formula><mml:math id="M49" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula> averaged over the preceding five winters: this quantity represents
the internal – i.e., unforced – fluctuations of the variable <inline-formula><mml:math id="M50" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula>, and we refer to its standard
deviation as <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>. For <inline-formula><mml:math id="M52" display="inline"><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> computed as the ensemble mean over
post-eruption winters, therefore, the signal-to-noise ratio, <inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mi>X</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>,
tells us whether the response to the eruption exceeds the internal variability. As we will argue
below, this quantity is the one that ultimately matters when trying to determine whether the
response to an eruption of specific amplitude is of practical importance.</p>
</sec>
<sec id="Ch1.S2.SS6">
  <label>2.6</label><title>The Northern Annular Mode</title>
      <p id="d1e1034">Since the proposed stratospheric pathway mechanism involves the acceleration of the stratospheric
polar vortex and the accompanying poleward shift of the tropospheric mid-latitude jet due to
stratospheric–troposphere coupling, it is common to characterize the extratropical circulation
response as a positive phase of the Northern Annular Mode (NAM). This can be quantified from the
zonal mean zonal wind following <xref ref-type="bibr" rid="bib1.bibx10" id="text.44"/>, as we do here, or from the polar-cap
averaged geopotential, as described in <xref ref-type="bibr" rid="bib1.bibx3" id="text.45"/>. Both lead to very similar results.</p>
      <p id="d1e1043">Our NAM computation is as follows: we define the NAM for each vertical level using monthly zonal
mean zonal wind in the control run. Attention is restricted to winter (DJF) zonal wind
anomalies north of 30<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, obtained by subtracting the climatological mean. Then, the first
principal component (i.e., the time series) is obtained using the first eigenvector of the
latitude-weighted covariance matrix. Lastly, the principal component is regressed onto the
unweighted zonal wind anomalies to obtain the spatial pattern of the NAM. The associated eigenvalue
reflects the fraction of the month-to-month variance captured by the NAM. As we will show, the NAM
provides a useful framework for interpreting the signal-to-noise ratio.</p>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Response of the atmospheric temperature and circulation</title>
      <p id="d1e1064">Before discussing any Eurasian surface warming, we need to start by examining stratospheric
temperature and circulation responses, to determine whether the volcanic aerosols in the lower
tropical stratosphere are able to accelerate the polar vortex, with an accompanying positive phase
of the NAM in the first DJF following the eruptions. The difference-from-control-run response of
the atmospheric temperature <inline-formula><mml:math id="M55" display="inline"><mml:mi>T</mml:mi></mml:math></inline-formula>, as a function of latitude and height, for the first winter (DJF)
followed each eruption is shown in the left column of Fig. <xref ref-type="fig" rid="Ch1.F2"/>. It is very clear
that as the sulfur mass injection is increased from 5 to 160 Tg(S), the volcanic aerosols in the
tropical lower stratosphere cause a progressively larger warming response, which reaches into the
mid-latitudes for the larger amplitudes.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><?xmltex \def\figurename{Figure}?><label>Figure 2</label><caption><p id="d1e1078">Zonal mean response of the atmospheric temperature (<inline-formula><mml:math id="M56" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>T</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>, left column) and
zonal wind (<inline-formula><mml:math id="M57" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>, right column) in the first DJF following the June eruptions,
for injections of 5, 10, 20, 40, 80, and 160 Tg(S), from top to bottom. Gray shading indicates
the lack of a statistically significant response, from a <inline-formula><mml:math id="M58" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test at the 95 % confidence level.</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f02.png"/>

      </fig>

      <p id="d1e1120">As expected from thermal wind balance, a similar response is seen in the zonal mean zonal wind <inline-formula><mml:math id="M59" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>
(Fig. <xref ref-type="fig" rid="Ch1.F2"/>, right column), with a progressively stronger polar vortex acceleration
in the NH with stronger eruptions. Note that, in these idealized calculations, 20 Tg(S) are
required to obtain a statistically significant vortex acceleration. At 10 Tg(S), an amplitude
comparable to that of the 1991 Pinatubo eruption, 20 members are not sufficient to establish statistical
significance. However, with a larger ensemble, size significance can be established for a 10 Tg(S)
eruption, as documented originally by <xref ref-type="bibr" rid="bib1.bibx6" id="text.46"/>. In fact, <xref ref-type="bibr" rid="bib1.bibx1" id="text.47"/> report a
significant polar vortex acceleration for even smaller EVA injections, down to 5 Tg(S) in their
model, using 100-member ensembles. However, the very fact than 20 eruptions are not sufficient to
establish significance speaks to the fact that the signal is small for injections smaller than 10 Tg(S), even in the stratosphere.</p>
      <p id="d1e1139">But let us now turn to the tropospheric circulation. In the right column in Fig. <xref ref-type="fig" rid="Ch1.F2"/> one can see a clear dipole in the NH tropospheric mid-latitudes, which is
statistically significant for injections of 20 Tg(S) and above, in our model. This dipole, which is
most prominent over the North Atlantic (not shown), represents a poleward shift in the eddy-driven
jet. It is customary to quantify such jet shifts in terms of the NAM, also known as the Arctic
Oscillation, which has become a standard metric for stratosphere–troposphere coupling (e.g., see <xref ref-type="bibr" rid="bib1.bibx2" id="altparen.48"/>). To illustrate the NAM in our model, the zonal mean zonal winds associated
with 1 standard deviation of the NAM index are shown in Fig. <xref ref-type="fig" rid="Ch1.F3"/>a: notice how the
NAM regressed winds resemble the <inline-formula><mml:math id="M60" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow></mml:math></inline-formula> response in Fig. <xref ref-type="fig" rid="Ch1.F2"/>. This suggests
that the NAM is likely to be a key tool in understanding the wind response. It is also worth
emphasizing that the NAM explains a large fraction of unforced variability in <inline-formula><mml:math id="M61" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula>, as seen in Fig. <xref ref-type="fig" rid="Ch1.F3"/>b: over 50 % in the troposphere and over 75 % in the stratosphere.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><?xmltex \currentcnt{3}?><?xmltex \def\figurename{Figure}?><label>Figure 3</label><caption><p id="d1e1173"><bold>(a)</bold> Zonal mean zonal winds associated with 1 standard deviation of the Northern Annular
Mode (NAM) in our PI control run (see Sect. 2.6 for details). <bold>(b)</bold> Fraction of variance captured
by the NAM in the control run. <bold>(c)</bold> Projection of <inline-formula><mml:math id="M62" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow></mml:math></inline-formula> (Fig. <xref ref-type="fig" rid="Ch1.F2"/>, right)
onto the NAM, in units of the NAM standard deviation computed from the PI control run. <bold>(d)</bold>
Latitude-weighted correlation of <inline-formula><mml:math id="M63" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow></mml:math></inline-formula> and the NAM at each level. The legend in <bold>(d)</bold> also
applies to <bold>(c)</bold>: the colors indicate different injections. <bold>(e)</bold> Smallest ensemble size (<inline-formula><mml:math id="M64" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>)
necessary for the NAM response to be significant at the 95 % confidence level in the first-DJF
NAM. <bold>(f)</bold> As in <bold>(e)</bold>, but for the spatial pattern of <inline-formula><mml:math id="M65" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow></mml:math></inline-formula>.</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f03.png"/>

      </fig>

      <p id="d1e1253">To express the zonal wind response to the eruptions in NAM terms, we project <inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow></mml:math></inline-formula> onto the NAM
index, at each level, and plot this in units of the NAM standard deviation (<inline-formula><mml:math id="M67" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>) in Fig. <xref ref-type="fig" rid="Ch1.F3"/>c. Notice that the tropospheric response below 250 hPa is considerably
smaller than the stratospheric response: except for the two most extreme cases, the tropospheric
wind response is comparable to, or smaller than, the natural variability of the NAM, i.e., the
signal-to-noise ratio is less than one. If indeed the Eurasian surface temperature anomalies
following the eruption are driven by the stratospheric pathway mechanism via the NAM, they are also
unlikely to exceed natural variability, except possibly for the largest injections. This will be
carefully analyzed and discussed in the next section.</p>
      <p id="d1e1275">An alternative way of quantifying the zonal wind response in the context of natural variability is
to ask: how many ensemble members are required to establish statistical significance? The answer to
this is illustrated in Fig. <xref ref-type="fig" rid="Ch1.F3"/>e and f, where the <inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> values, computed as
detailed in Sect. <xref ref-type="sec" rid="Ch1.S2.SS5"/>, are shown for winter post-eruption NAM and <inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>u</mml:mi></mml:mrow></mml:math></inline-formula>,
respectively. For both quantities, for injections smaller than 20 Tg(S) more than 20 eruptions are
typically needed to establish a statistically significant response of the circulation in the
troposphere. Thus, an individual event, such as the 1991 Pinatubo eruption, would be unremarkable in
terms of its wind response: we remind the reader that, in fact, the polar vortex was anomalously <italic>weak</italic> – not strong – in winter 1991–1992, in spite of the volcanic aerosols present in the
tropical lower stratosphere (see <xref ref-type="bibr" rid="bib1.bibx30" id="altparen.49"/>, and the discussion therein). Furthermore,
assuming our idealized eruptions are representative of actual eruptions, even a 40 Tg(S) injection
– which is more than 30 % larger than the 1815 Tambora injection – would require between 5 and 10
eruptions before a statistically significant signal in the tropospheric circulation at mid-latitudes
could be ascertained. It is sobering to realize that there is only one eruption with a
stratospheric sulfur injection larger than 40 Tg(S) in the past 2000 years (Samalas, in 1257),
and possibly a second one if one reaches back to the past 2500 years (see Table 2
of <xref ref-type="bibr" rid="bib1.bibx41" id="altparen.50"/>).</p>
      <p id="d1e1313">Lastly, before turning to surface temperatures, we wish to briefly discuss the response of the
atmospheric circulation in the <italic>second</italic> winter after the eruption. There is some confusion on
this matter in the literature: earlier studies suggested the presence of a considerable response in
the second winter (e.g., <xref ref-type="bibr" rid="bib1.bibx35 bib1.bibx37 bib1.bibx16" id="altparen.51"/>), whereas later studies
have agreed that only the first winter should be considered (e.g., <xref ref-type="bibr" rid="bib1.bibx6 bib1.bibx46 bib1.bibx30" id="altparen.52"/>), since there is essentially no memory in the stratosphere to carry the
response 18 months after the eruptions, when the bulk of the aerosols are no longer in the
stratosphere. To provide further evidence in support of the more recent consensus, we show the time
series of the NAM response in our model for 3 whole years after the eruption, at three
different levels (10, 100, and 850 hPa) and for all stratospheric injections from 5 to 160 Tg(S).
As one can see in Fig. <xref ref-type="fig" rid="Ch1.F4"/>c, at 850 hPa there is no statistically
significant NAM response in the second winter after the eruption (except, possibly, for the very
largest injection mass) and thus no reason to expect a response in Eurasian surface temperatures,
to which we now turn our attention.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><?xmltex \currentcnt{4}?><?xmltex \def\figurename{Figure}?><label>Figure 4</label><caption><p id="d1e1330">Monthly evolution of the NAM response for 3 years after the June eruptions, with the
95 % confidence significance level indicated by the black horizontal line, at <bold>(a)</bold> 10 hPa, <bold>(b)</bold> 100 hPa, and <bold>(c)</bold> 850 hPa. The units on the ordinate are standard deviations of the NAM from the PI
control (<inline-formula><mml:math id="M70" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>). On the abscissa, the numbers 1, 2, and 3 designate the first, second, and
third January after the eruption.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f04.png"/>

      </fig>

</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Response of the winter surface temperature over Eurasia</title>
      <p id="d1e1363">The starting point of this discussion is the quantity <inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, the surface temperature anomaly,
computed using the difference-from-control-run method, in the first post-eruption winter. Its
ensemble mean <inline-formula><mml:math id="M72" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> , shown in the left column of Fig. <xref ref-type="fig" rid="Ch1.F5"/>,
represents the forced response caused by the eruption for each injection amplitude. It is readily
seen that for our idealized EVA eruptions, a statistically significant warming response starts to
emerge for 20 Tg(S) injections over parts of eastern Eurasia, and covers most of Eurasia for 40 Tg(S) and above. To quantify this more carefully over Eurasia, we start by considering the region
40–70<inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and 0–150<inline-formula><mml:math id="M74" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, for consistency<fn id="Ch1.Footn1"><p id="d1e1416">Due to an unfortunate typographical
oversight in both <xref ref-type="bibr" rid="bib1.bibx30" id="text.53"/> and <xref ref-type="bibr" rid="bib1.bibx29" id="text.54"/>, the Eurasian region in those studies
was stated to comprise the longitudes 0–150<inline-formula><mml:math id="M75" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, instead of the obvious 0–150<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E. We have
double-checked the code used in those studies and can confirm that the proper longitudes –
i.e., those to the east of the prime meridian – were used in the actual calculations; thus, the
results in those studies stand as reported. Unfortunately, <xref ref-type="bibr" rid="bib1.bibx1" id="text.55"/> also state
analyzing a Eurasian region covering longitudes 0–150<inline-formula><mml:math id="M77" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W in their Fig. 10.</p></fn> with previous
studies <xref ref-type="bibr" rid="bib1.bibx30 bib1.bibx29 bib1.bibx1" id="paren.56"/>. As seen in Table 1, the forced response
<inline-formula><mml:math id="M78" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> becomes statistically significant over that region only with an 80 Tg(S)
injection. However, a careful inspection of the red areas in the left column of
Fig. <xref ref-type="fig" rid="Ch1.F5"/> suggests that 40–70<inline-formula><mml:math id="M79" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N might not be the best choice of latitudes if
one is trying to capture the largest Eurasian warming.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><?xmltex \currentcnt{5}?><?xmltex \def\figurename{Figure}?><label>Figure 5</label><caption><p id="d1e1489">The surface temperature response <inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> (left) and the corresponding ensemble
standard deviation <inline-formula><mml:math id="M81" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> (right) for the first winter (DJF) following the eruptions. Rows show
increasing injection amplitudes, from 5 to 160 Tg(S), top to bottom, as labeled. Gray shading
indicates the lack of a statistically significant response at the 95 % confidence level using a
<inline-formula><mml:math id="M82" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test.</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f05.png"/>

      </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e1528">Statistics of surface temperature anomalies, averaged over Eurasia, in the first
post-eruption winter (DJF) following idealized low-latitude eruptions with injections from 5 to
160 Tg(S). Two averaging regions are considered: 40–70<inline-formula><mml:math id="M83" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 0–150<inline-formula><mml:math id="M84" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (as
in <xref ref-type="bibr" rid="bib1.bibx30 bib1.bibx29" id="altparen.57"/>) and 50–80<inline-formula><mml:math id="M85" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 0–150<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (as
in <xref ref-type="bibr" rid="bib1.bibx1" id="altparen.58"/>). For each averaging region, <inline-formula><mml:math id="M87" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> is the ensemble mean
anomaly (the response) computed using the difference-from-control-run method, <inline-formula><mml:math id="M88" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> the
corresponding standard deviation, and <inline-formula><mml:math id="M89" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> the minimum ensemble size needed to obtain
a response that is statistically significant at the 95 % confidence level. Injection amplitudes
for which <inline-formula><mml:math id="M90" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula> produce responses that are not statistically significant at that
level with 20-member ensembles; these insignificant responses are followed by an asterisk.
<inline-formula><mml:math id="M91" display="inline"><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> is the response computed using the difference-from-reference-period
method.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="8">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right" colsep="1"/>
     <oasis:colspec colnum="5" colname="col5" align="left"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:colspec colnum="8" colname="col8" align="left"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry rowsep="1" namest="col2" nameend="col4" align="center" colsep="1">40–70<inline-formula><mml:math id="M92" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 0–150<inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E </oasis:entry>
         <oasis:entry rowsep="1" namest="col5" nameend="col8" align="center">50–80<inline-formula><mml:math id="M94" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 0–150<inline-formula><mml:math id="M95" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E </oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Injection [Tg(S)]</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M96" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> [K]</oasis:entry>
         <oasis:entry colname="col3"><inline-formula><mml:math id="M97" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> [K]</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M98" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M99" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>[K]</oasis:entry>
         <oasis:entry colname="col6"><inline-formula><mml:math id="M100" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> [K]</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M101" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M102" display="inline"><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> [K]</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">5</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M103" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.43<inline-formula><mml:math id="M104" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">1.56</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M105" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M106" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.19<inline-formula><mml:math id="M107" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.12</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M108" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8"><inline-formula><mml:math id="M109" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.25<inline-formula><mml:math id="M110" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">10</oasis:entry>
         <oasis:entry colname="col2"><inline-formula><mml:math id="M111" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.17<inline-formula><mml:math id="M112" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">1.62</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M113" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.04<inline-formula><mml:math id="M114" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col6">2.64</oasis:entry>
         <oasis:entry colname="col7"><inline-formula><mml:math id="M115" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col8">0.02<inline-formula><mml:math id="M116" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">20</oasis:entry>
         <oasis:entry colname="col2">0.11<inline-formula><mml:math id="M117" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">1.75</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M118" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">0.83</oasis:entry>
         <oasis:entry colname="col6">2.16</oasis:entry>
         <oasis:entry colname="col7">16</oasis:entry>
         <oasis:entry colname="col8">0.78</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">40</oasis:entry>
         <oasis:entry colname="col2">0.39<inline-formula><mml:math id="M119" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">1.76</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M120" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">20</mml:mn></mml:mrow></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1.36</oasis:entry>
         <oasis:entry colname="col6">2.64</oasis:entry>
         <oasis:entry colname="col7">8</oasis:entry>
         <oasis:entry colname="col8">1.31</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">80</oasis:entry>
         <oasis:entry colname="col2">0.66</oasis:entry>
         <oasis:entry colname="col3">1.41</oasis:entry>
         <oasis:entry colname="col4">11</oasis:entry>
         <oasis:entry colname="col5">1.82</oasis:entry>
         <oasis:entry colname="col6">2.20</oasis:entry>
         <oasis:entry colname="col7">5</oasis:entry>
         <oasis:entry colname="col8">1.76</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">160</oasis:entry>
         <oasis:entry colname="col2">1.12</oasis:entry>
         <oasis:entry colname="col3">1.48</oasis:entry>
         <oasis:entry colname="col4">6</oasis:entry>
         <oasis:entry colname="col5">2.35</oasis:entry>
         <oasis:entry colname="col6">2.03</oasis:entry>
         <oasis:entry colname="col7">4</oasis:entry>
         <oasis:entry colname="col8">2.29</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p id="d1e2129">Therefore, following the suggestion in <xref ref-type="bibr" rid="bib1.bibx1" id="text.59"/>, we will focus on the more northerly
region 50–80<inline-formula><mml:math id="M121" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N over the same longitude range 0–150<inline-formula><mml:math id="M122" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, in order to maximize the
volcanically forced surface warming. We will refer to this as the “standard” Eurasian region. As
seen in Table 1, over that region the response becomes significant with only a 20 Tg(S) injection.
In fact, <xref ref-type="bibr" rid="bib1.bibx1" id="text.60"/> report that the response is significant even for a 10 Tg(S) injection
over that region. This is not at odds with our results, considering our smaller 20-member ensembles
compared with their 100-member ensembles. Although <inline-formula><mml:math id="M123" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> computed as per the method of
Sect. <xref ref-type="sec" rid="Ch1.S2.SS5"/> cannot be directly evaluated for small injections owing to the tiny value of
<inline-formula><mml:math id="M124" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>, which results in a near division by zero, we can estimate it via
extrapolation as follows: assuming the response to be approximately linear for the small
injections, and noting that <inline-formula><mml:math id="M125" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub><mml:mo>∝</mml:mo><mml:mo>(</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:msup><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>)</mml:mo><mml:mo>∝</mml:mo><mml:mo>(</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:msup><mml:mi>A</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>,
where <inline-formula><mml:math id="M126" display="inline"><mml:mi>A</mml:mi></mml:math></inline-formula> is the injection amplitude, a halving of the injection would require a 4-fold increase
in <inline-formula><mml:math id="M127" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>. Since <inline-formula><mml:math id="M128" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">16</mml:mn></mml:mrow></mml:math></inline-formula> for 20 Tg(S) in our model, we deduce a value of
<inline-formula><mml:math id="M129" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">64</mml:mn></mml:mrow></mml:math></inline-formula> for 10 Tg(S) and <inline-formula><mml:math id="M130" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mn mathvariant="normal">256</mml:mn></mml:mrow></mml:math></inline-formula> for 5 Tg(S). These numbers are
perfectly in line and thus confirm the findings of <xref ref-type="bibr" rid="bib1.bibx1" id="text.61"/> who, with 100-member
ensembles, found a significant warming for 10 Tg(S) but not for 5 Tg(S) injections.</p>
      <p id="d1e2304">Since a 10 Tg(S) injection is quite close to the one accompanying the 1991 Pinatubo and the 1883
Krakatau eruptions (each close to 9 Tg(S); see <xref ref-type="bibr" rid="bib1.bibx41" id="altparen.62"/>), one wonders why recent modeling
studies have found no statistically significant winter warming following those eruptions
<xref ref-type="bibr" rid="bib1.bibx5 bib1.bibx30 bib1.bibx29 bib1.bibx1" id="paren.63"/>. The answer rests in the fact that the EVA
aerosols are sufficiently different from the ones used in the standard CMIP5 and CMIP6 historical
simulations to generate a stronger response which, given a large enough ensemble, can yield
statistical significance for a 10 Tg(S) injection. We discuss this more in Appendix A and also
refer the reader to <xref ref-type="bibr" rid="bib1.bibx1" id="text.64"/> who also show that, even with a 100-member ensemble,
non-idealized aerosols yield no significant post-Pinatubo warming response in their model.</p>
      <p id="d1e2316">But let us focus on injections larger than Pinatubo and Krakatau, for which our model does show a
statistically significant Eurasian warming response. For the standard Eurasian region, our model
simulates a post-eruption winter warming of 0.83 <inline-formula><mml:math id="M131" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C for a 20 Tg(S) injection, and this warming
grows monotonically up to 2.35 <inline-formula><mml:math id="M132" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C at 160 Tg(S), as seen in Table 1. While these values may
appear considerable, we now argue that they are small in the context of internal variability. There
are several ways to show this.</p>
      <p id="d1e2337">First, we draw the reader's attention to the magnitude of the ensemble spread, as quantified by the
standard deviation <inline-formula><mml:math id="M133" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula>. This quantity is shown in the right column of
Fig. <xref ref-type="fig" rid="Ch1.F5"/>, and we emphasize that the colorbar for <inline-formula><mml:math id="M134" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> is identical to the
one for <inline-formula><mml:math id="M135" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>. Notice that over most of Eurasia, <inline-formula><mml:math id="M136" display="inline"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>&lt;</mml:mo><mml:mi mathvariant="italic">σ</mml:mi></mml:mrow></mml:math></inline-formula>
for both 20 and 40 Tg(S) injections. In fact, averaging over our standard Eurasian box, we see that
the signal-to-noise ratio <inline-formula><mml:math id="M137" display="inline"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> even for 80 Tg(S); and, even for the
very largest injection amplitude, 160 Tg(S), the Eurasian signal-to-noise ratio is a meager 1.16 –
a rather unimpressive value if one considers that a 160 Tg(S) injection is almost three times the
size of the the largest known volcanic injection of the past 2500 years
(Samalas, in 1257, with a 59 Tg(S) injection, as estimated by <xref ref-type="bibr" rid="bib1.bibx41" id="altparen.65"/>).</p>
      <p id="d1e2422">Second, to further appreciate how small the post-volcanic surface temperature response is in the
context of internal variability, we present in Fig. <xref ref-type="fig" rid="Ch1.F6"/> the warmest
(right column) and coldest (left column) simulation found in each 20-member ensemble, for all
injection amplitudes. Remarkably, even for a massive 160 Tg(S) injection, one can find an event with
temperatures that are anomalously <italic>cold</italic> over Eurasia in the first winter after the eruption.
In addition, we note that this can be captured with our relatively small 20-member ensemble.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><?xmltex \currentcnt{6}?><?xmltex \def\figurename{Figure}?><label>Figure 6</label><caption><p id="d1e2433">Coldest (left) and warmest (right) winter surface temperature anomalies over Eurasia in
each 20-member ensemble, from 5 to 160 Tg(S), top to bottom, as labeled. Note that the colorbar
covers twice the range as the one in Fig. <xref ref-type="fig" rid="Ch1.F5"/>, as the variability is larger
than the response, even for very large sulfur injections.</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f06.png"/>

      </fig>

      <p id="d1e2444">Third, and most importantly, we now quantitatively compare the forced post-eruption winter warming
to the unforced interannual variability, as done in <xref ref-type="bibr" rid="bib1.bibx29" id="text.66"/>. To do this, we start by
computing the response <inline-formula><mml:math id="M138" display="inline"><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>, where anomalies are computed using the five
pre-eruption winters as the reference period (see Sect. <xref ref-type="sec" rid="Ch1.S2.SS4"/>). As one can see from
Table 1, this quantity is very similar to the difference-from-control-run response
<inline-formula><mml:math id="M139" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>, over the entire range of amplitudes. This confirms that our findings are
robust. For the sake of completeness, box-and-whisker plots of <inline-formula><mml:math id="M140" display="inline"><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> averaged
over several different Eurasian regions are shown in Fig. <xref ref-type="fig" rid="Ch1.F7"/>, where the
EVA response can be directly compared to one from Pinatubo and Krakatau. The green bars, for the
region used in <xref ref-type="bibr" rid="bib1.bibx30" id="text.67"/>, indicate that an 80 Tg(S) injection is needed for significance.
But using the more northerly standard region, shown in the light blue bars, we see that 20 Tg(S)
suffices to capture a statistically significant warming, in agreement with the threshold value for
<inline-formula><mml:math id="M141" display="inline"><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7"><?xmltex \currentcnt{7}?><?xmltex \def\figurename{Figure}?><label>Figure 7</label><caption><p id="d1e2530">Eurasian surface temperature anomalies, computed using the difference-from-reference-period
method, for the first winter following the indicated eruptions for both, two historical
simulations and for the EVA. Colors indicate different averaging regions over Eurasia, as shown in
the legend. Boxes show the upper and lower quartiles, central bars the median, and whiskers the
ensemble maximum and minimum. Stars denote statistically significant responses at the 95 % confidence level.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f07.png"/>

      </fig>

      <p id="d1e2539">Next, in order to contrast these <inline-formula><mml:math id="M142" display="inline"><mml:mover accent="true"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover></mml:math></inline-formula> responses to interannual variability, we
compute the probability distribution function (PDF) of <inline-formula><mml:math id="M143" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="normal">Δ</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> in the pre-industrial control
run of our model, where no volcanic eruptions occur. This quantity represents the surface
temperature anomalies over the standard Eurasian region originating solely from internal
variability: it has a mean value of zero and, fitting a standard Gaussian to it, a standard
deviation <inline-formula><mml:math id="M144" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> of 1.78 <inline-formula><mml:math id="M145" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C. Finally, we superimpose onto this PDF the 20 simulated
eruptions for each injection amplitude, together with the ensemble mean representing the forced
response.</p>
      <p id="d1e2597">From those plots, seen in the left column of Fig. <xref ref-type="fig" rid="Ch1.F8"/>, it is clear
that nearly all individual post-eruption anomalies in our study fall well within the PDF of unforced
anomalies. In fact, the forced response (i.e., the ensemble mean) only exceeds the interannual
variability <inline-formula><mml:math id="M146" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> with a 160 Tg(S) injection; and, even in that case, the forced response
is only slightly larger than <inline-formula><mml:math id="M147" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, and nowhere close to <inline-formula><mml:math id="M148" display="inline"><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>. This means
that, even with a massive 160 Tg(S) volcanic injection, post-eruption anomalies in winter over
Eurasia would be largely indistinguishable from the large anomalies that occur even in the absence
of an eruption, as a consequence of the large internal variability of surface temperature at
mid-latitudes.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><?xmltex \currentcnt{8}?><?xmltex \def\figurename{Figure}?><label>Figure 8</label><caption><p id="d1e2640">Eurasian winter surface temperature anomalies (computed with the
difference-from-reference-period method), for each eruption (thin colored bars) and for the
ensemble mean (thick colored bar), from 5 to 160 Tg(S), top to bottom, as labeled. In each panel,
these are superimposed on the climatology (black) of the same quantity from the pre-industrial
control runs, quantified by a histogram and a Gaussian fit, and with dashed lines indicating the
1<inline-formula><mml:math id="M149" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> and 2<inline-formula><mml:math id="M150" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> ranges, as in <xref ref-type="bibr" rid="bib1.bibx29" id="text.68"/>. Left column: average temperature
over the region 50–80<inline-formula><mml:math id="M151" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and 0–150<inline-formula><mml:math id="M152" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E. Right column: average temperature over
the region 55–80<inline-formula><mml:math id="M153" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and 10–90<inline-formula><mml:math id="M154" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E.​​​​​​​</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f08.png"/>

        <p id="d1e2702">​​​​​​​</p>
      </fig>

      <p id="d1e2706">As a final check on the robustness of our conclusion, we have explored the narrower region
55–80<inline-formula><mml:math id="M155" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and 10–90<inline-formula><mml:math id="M156" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E reported by <xref ref-type="bibr" rid="bib1.bibx1" id="text.69"/> as the locus of the largest
post-eruption warming over Eurasia in their model. First, in our model we find that the forced
response over that region is not different from the one over the standard region, as seen in Fig. <xref ref-type="fig" rid="Ch1.F7"/> (contrast the light and dark blue bars). Second, and more
crucially: making the region narrower dramatically increases the interannual variability
<inline-formula><mml:math id="M157" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mi mathvariant="normal">IV</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, which goes from 1.78 to 2.96. This is seen in the right column of
Fig. <xref ref-type="fig" rid="Ch1.F8"/>, where the axis on the abscissa needs to be expanded by a
factor of two to encompass the entire PDF of unforced post-eruption surface temperature anomalies.
In fact, for this narrower region the forced response is smaller than the interannual variability
even for 160 Tg(S)​​​​​​​ injections. This further corroborates our conclusion.</p>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <label>5</label><title>Summary, discussion, and outlook</title>
      <p id="d1e2755">In a nutshell, we have explored the winter response to progressively larger, low-latitude eruptions
using a stratosphere-resolving climate model with idealized prescribed volcanic aerosols, and two
key results have emerged from our exploration. First, we have confirmed that with a sufficiently
large stratospheric injection and with a sufficiently large ensemble size, statistically significant
surface warming over Eurasia in the first post-eruption winter can be seen in a climate model, as
reported in <xref ref-type="bibr" rid="bib1.bibx1" id="text.70"/>. Second, and most importantly, we have shown that for injections up
to 160 Tg(S), the first post-eruption Eurasian winter warming forced by the volcanic aerosols is
sufficiently small as to be indistinguishable from internal variability. With these key findings in
mind, we are now ready to address several important issues, and also to place our results in the
context of earlier studies and of the observational record.</p>
      <p id="d1e2761">First, regarding the emergence of a statistically significant post-eruption Eurasian winter warming:
the threshold for this – for the idealized EVA aerosols – is 20 Tg(S) in our model, using
20-member ensembles. <xref ref-type="bibr" rid="bib1.bibx1" id="text.71"/> report the threshold to be at 10 Tg(S) using 100-member
ensembles, for the same EVA aerosols. The difference largely resides in the fact that our ensemble
size is considerably smaller but, in part, may also be due to model differences. From our model, we
estimate that over 64 eruptions are needed for a 10 Tg(S) injection to produce significant warming.
While <xref ref-type="bibr" rid="bib1.bibx1" id="text.72"/> do not report the values of <inline-formula><mml:math id="M158" display="inline"><mml:mrow><mml:msub><mml:mi>N</mml:mi><mml:mi mathvariant="normal">min</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>, the mere fact that more than 60
events are needed speaks to how small the forced volcanic warming signal actually is in these
models.</p>
      <p id="d1e2781"><?xmltex \hack{\newpage}?>In fact, over the past 2500 years, there are only 33 eruptions with stratospheric
injections estimated to be in excess of 10 Tg(S), according to the latest compilation by
<xref ref-type="bibr" rid="bib1.bibx42" id="text.73"/>. Thus, assuming that EVA aerosols are representative of typical eruptions (which
may not be the case; see below), and assuming that current-generation models are not lacking in
significant aspects relevant to this problem, it is currently impossible to observationally validate
this modeling evidence of a weak post-eruption winter warming over Eurasia given the limited
eruption record. Focusing on larger eruptions would improve the signal-to-noise ratio, but that
effort is similarly futile: for a 40 Tg(S) injection, our model suggests that eight events are needed to
establish statistical significance, but only two such events are known to have occurred in the past
2500 years. One could look further back in time, but temperature reconstructions become even more
problematic given that we are seeking a winter signal, and most tree-ring-based reconstructions are
based largely on summer data (when trees actually grow).</p>
      <p id="d1e2788">Second, it must be kept in mind that the results in Table 1 apply only to the EVA aerosols, and some
evidence suggests that these idealized aerosols at 10 Tg(S) produce more warming than the aerosols
used for Pinatubo in the CMIP5 and CMIP6 model runs. For instance, <xref ref-type="bibr" rid="bib1.bibx1" id="text.74"/> found no
statistically significant warming – even with 100 members – for Pinatubo when forced with an
earlier aerosol reconstruction <xref ref-type="bibr" rid="bib1.bibx39" id="paren.75"/>, although their model shows significant
warming with EVA aerosols at 10 Tg(S). <xref ref-type="bibr" rid="bib1.bibx30" id="text.76"/> found no significant warming for Pinatubo with a
50-member ensemble of the CanESM2 model forced with CMIP5 volcanic aerosols, and <xref ref-type="bibr" rid="bib1.bibx29" id="text.77"/>
found no surface warming for Krakatau with the 100-member Grand Ensemble <xref ref-type="bibr" rid="bib1.bibx24" id="paren.78"/>. Also,
Figs. 3 and 7 of <xref ref-type="bibr" rid="bib1.bibx43" id="text.79"/> indicate that the optical depth of EVA aerosols for a 9 Tg(S)
injection is considerably larger than the one produced for Pinatubo by the Chemistry-Climate Model
Initiative (CCMI; <xref ref-type="bibr" rid="bib1.bibx14" id="altparen.80"/>), which formed the basis for the CMIP6 forcing. It is
possible, therefore, that the EVA aerosol forcing might be unrealistically large and thus overly
favorable to cause Eurasian winter warming, further underscoring our key conclusion.</p>
      <p id="d1e2814">Third, the reader may wonder if and how our findings might be altered if the eruptions coincided
with El Niño or La Niña events. The extant literature is confounding: one study has claimed
that El Niño is necessary to produce winter warming over Eurasia <xref ref-type="bibr" rid="bib1.bibx9" id="paren.81"/>, but two
earlier studies have reported that the winter warming signal is insensitive to the ENSO phase
<xref ref-type="bibr" rid="bib1.bibx7 bib1.bibx40" id="paren.82"/>. Similarly, while some modeling studies have claimed that
volcanic eruptions cause El Niño (e.g., <xref ref-type="bibr" rid="bib1.bibx19" id="altparen.83"/>), others have argued that there is
little evidence to support that claim (e.g., <xref ref-type="bibr" rid="bib1.bibx11" id="altparen.84"/>; note: one of the referees of this paper
insisted that we also cite his own critical views of that study, which can be found in <xref ref-type="bibr" rid="bib1.bibx33" id="altparen.85"/>). The very existence of such contradictory claims in the peer-reviewed literature is
a strong indication of a very small signal, at best. In fact, preliminary results from our
model show no significant ENSO impacts on winter warming in the Northern Hemisphere, and we plan to
report on that in a future paper.</p>
      <p id="d1e2832">Fourth, we wish to emphasize that modeled winter surface warming reported here, and in
<xref ref-type="bibr" rid="bib1.bibx1" id="text.86"/>, does not validate the early modeling studies that claimed a forced winter
warming following the Pinatubo eruption, but actually demonstrates how that warming was spuriously
generated by those studies' inadequacies. Just to cite one example: <xref ref-type="bibr" rid="bib1.bibx36" id="text.87"/>, with an
early GISS ModelE version at 4<inline-formula><mml:math id="M159" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M160" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 5<inline-formula><mml:math id="M161" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> horizontal resolution and with a mere 20 vertical
levels, running with <italic>prescribed SST</italic>, reported a statistically significant winter warming over
Eurasia after Pinatubo with a 5-member ensemble. This contrasts with the model used here, with over
100 vertical levels and finer horizontal resolution, which shows no forced Eurasian winter warming
from Pinatubo aerosols, nor from the stronger EVA aerosols with 10 Tg(S) injection with a much
larger ensemble. One might rebut that 10 years from now we will have even better models and that
the conclusions reached here may again be revised. We agree that such a possibility is very real.</p>
      <p id="d1e2870">In fact, there is little doubt that, beyond model resolution, several aspects of our simulations are ready
for improvement. Perhaps the most unrealistic aspect of the modeling setup employed here – which
is common to nearly every study on the question of Eurasian post-eruption winter warming – is the
fact that our volcanic aerosols are prescribed from an external file and thus inconsistent with the
atmospheric circulation and composition. However, we note the existence of major uncertainties in
interactive aerosol modeling, which the VolMIP community has labeled “drastic” <xref ref-type="bibr" rid="bib1.bibx8" id="paren.88"/>.
Also, whether the dependency of the aerosol optical depth on injection mass as parameterized in the EVA
is truly representative of large eruptions remains an unanswered question, owing to the lack of
observations. In any event, what emerges from our study, which independently confirms the findings
of <xref ref-type="bibr" rid="bib1.bibx1" id="text.89"/>, is that the early claims of robust Eurasian winter warming for eruptions such
as Pinatubo – and even smaller ones, such as the 1982 El Chichón or the 1962 Agung eruptions –
simply cannot be reproduced with current-generation climate models: they have consistently failed
to show any warming for such historical eruptions, because the signal-to-noise ratio is simply too
small.</p>
      <p id="d1e2879">Fifth, and most importantly, our simulations clearly demonstrate that the signal-to-noise ratio is
not only small for eruptions with sulfur injections comparable to those of Pinatubo and Krakatau, roughly 10 Tg(S): the signal-to-noise ratio remains small all the way up to 160 Tg(S). Even with that gigantic
forcing, we have found that only 3 out of 20 members produce winter warming anomalies that exceed
the 2<inline-formula><mml:math id="M162" display="inline"><mml:mi mathvariant="italic">σ</mml:mi></mml:math></inline-formula> range of the unforced variability in the control run (see the bottom left panel of
Fig. <xref ref-type="fig" rid="Ch1.F8"/>). In addition, if one nonetheless wanted to establish a
statistically significant warming signal over Eurasia for 160 Tg(S) eruptions, at least four such
events would be needed (see Table 1). Yet, not a single such eruption has occurred in the past
2500 years <xref ref-type="bibr" rid="bib1.bibx41" id="paren.90"/>.</p>
      <p id="d1e2894">An alternative way to appreciate how the post-eruption response is overwhelmed by the internal
variability is the following: let us look again at the 80 Tg(S) case, which is considerably larger
than the 1257 Samalas eruption, the largest of the past 2500 years. For such an eruption
<inline-formula><mml:math id="M163" display="inline"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:msub><mml:mi>T</mml:mi><mml:mi mathvariant="normal">s</mml:mi></mml:msub></mml:mrow><mml:mo mathvariant="normal">‾</mml:mo></mml:mover><mml:mi mathvariant="normal">​</mml:mi><mml:mi mathvariant="normal">​</mml:mi><mml:mi mathvariant="normal">​</mml:mi><mml:mi mathvariant="normal">​</mml:mi><mml:mi mathvariant="normal">​</mml:mi><mml:mi mathvariant="normal">​</mml:mi><mml:mi mathvariant="normal">​</mml:mi><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1.8</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M164" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C over Eurasia (see Table 1), and this is very close to 1 standard deviation of the interannual variability, as seen in Fig. <xref ref-type="fig" rid="Ch1.F8"/> (left column, second to last panel). So, using the
68–95–99.7​​​​​​​ rule for a standard Gaussian, we deduce that 16 % of the time, the winter anomalies <italic>in the absence</italic> of an eruption, are larger than the mean anomaly following an 80 Tg(S) eruption in
our model. This means that over a period of 2500 years we expect 400 winters with an anomalous warming
larger than the mean post-eruption warming. This is what we mean when we say that the post-eruption
warming – even for eruptions larger than any of the ones known to have occurred over the last 2500 years – would be unremarkable and indistinguishable from internal variability.</p>
      <p id="d1e2946">Finally, we remind the reader that the new evidence we have presented here for the possible
existence of post-eruption Eurasian winter warming comes from climate <italic>models</italic>. The
observational evidence, at this point, is what is clearly lacking, especially when one considers
that the models are telling us that many events are needed to separate the forced response from
internal variability. As already noted, most of the early observational studies reached
unsubstantiated conclusions, and the evidence for a winter warming provided by the most recent, and
most comprehensive, observational study <xref ref-type="bibr" rid="bib1.bibx16" id="paren.91"/> is also questionable. First, only 15
eruptions were examined in that study, of which only a handful are larger than Pinatubo or Krakatau.
Second, their conclusions were reached by averaging together large and small eruptions, which
confounds signal and noise. Third, and most importantly, the largest warming signal was found to
occur in the <italic>second</italic> post-eruption winter, a fact that we find difficult to believe given the
evidence presented above (see Fig. <xref ref-type="fig" rid="Ch1.F4"/>). Fourth, that study was
conducted with a single temperature reconstruction <xref ref-type="bibr" rid="bib1.bibx23" id="paren.92"/> and, to date, it has not
been independently confirmed with a different reconstruction. Since the models are now in good
agreement in showing that the Eurasian warming signal – if it exists at all – is very small at
best, more work is needed on the observational side to provide at least some plausible evidence (if
not a statistically convincing demonstration) that the post-eruption winter surface warming is not a
mere modeling artifact.</p>
</sec>

      
      </body>
    <back><app-group>

<app id="App1.Ch1.S1">
  <?xmltex \currentcnt{A}?><label>Appendix A</label><title>Contrasting the idealized EVA eruptions with Pinatubo and Krakatau</title>
      <p id="d1e2974">To evaluate the realism of eruptions simulated with the idealized EVA aerosols, we compare them with
the two largest low-latitude eruptions found in the “historical” runs that were performed with our
same model configuration as part of the CMIP6 <xref ref-type="bibr" rid="bib1.bibx25" id="paren.93"/>: the 1991 Pinatubo and the 1883
Krakatau eruptions. Both of these eruptions are estimated to have resulted in approximately 9 Tg(S)
injections, so we contrast them with the 10 Tg(S) case. It is important to keep in mind that the
historical integrations, of which a small ensemble of six were performed independently from this study
and submitted to CMIP6, also include all other climate forcings over the period 1850–2016, not
simply the volcanic aerosols.</p>
      <p id="d1e2980">First, as shown in Fig. <xref ref-type="fig" rid="App1.Ch1.S1.F9"/>, the EVA aerosols show some clear differences
to the ones prescribed by CMIP6 for Pinatubo and Krakatau, which were built as historical
reconstructions. Second, in Fig. <xref ref-type="fig" rid="App1.Ch1.S1.F10"/> we show the atmospheric wind and
temperature response, computed with the difference-from-reference-period method. One can see that the
tropical temperature anomalies are much broader in the meridional direction for Pinatubo and
Krakatau than for the EVA, owing to a more global spread of aerosols in the CMIP6 prescription than in
the EVA. This results in a weakened meridional temperature gradient and thus a weaker vortex
acceleration compared with the EVA at 10 Tg(S), although the significance is very weak, even in the
stratosphere, for all these eruptions, and it is actually non-existent in the troposphere. In any case, the
impression here is that the EVA aerosols appear more favorable to stratospheric vortex acceleration
due to their stronger meridional temperature gradient.</p>
      <p id="d1e2987">Third, at the surface, none of these aerosol forcings cause a statistically significant response, as
shown in Fig. <xref ref-type="fig" rid="App1.Ch1.S1.F11"/>. If anything, the historical forcings seem to
produce a little surface warming, although it is more centered over the pole than Eurasia and thus
unlikely to be tied to the NAM. In any case, nothing here is significant, so there is little to
discuss. One could argue that our ensemble sizes of 6 are too small, but <xref ref-type="bibr" rid="bib1.bibx1" id="text.94"/> show
that in their model too, with a much larger 100-member ensemble, the historical Pinatubo aerosols
produce no statistically significant Eurasian winter surface warming, and the same was shown for
Krakatau by <xref ref-type="bibr" rid="bib1.bibx29" id="text.95"/>, also with a 100-member ensemble.</p>

      <?xmltex \floatpos{h!}?><fig id="App1.Ch1.S1.F9"><?xmltex \currentcnt{A1}?><?xmltex \def\figurename{Figure}?><label>Figure A1</label><caption><p id="d1e3001">As in Fig. <xref ref-type="fig" rid="Ch1.F1"/>, but for the CMIP6 volcanic aerosol prescription
<xref ref-type="bibr" rid="bib1.bibx25" id="paren.96"/>, for Pinatubo <bold>(a, b)</bold> and Krakatau <bold>(c, d)</bold>. For comparison, the EVA
10 Tg(S) aerosols are shown in <bold>(e)</bold> and <bold>(f)</bold>.</p></caption>
        <?xmltex \hack{\hsize\textwidth}?>
        <?xmltex \igopts{width=312.980315pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f09.png"/>

      </fig>

<?xmltex \hack{\clearpage}?><?xmltex \floatpos{h!}?><fig id="App1.Ch1.S1.F10"><?xmltex \currentcnt{A2}?><?xmltex \def\figurename{Figure}?><label>Figure A2</label><caption><p id="d1e3033">As in Fig. <xref ref-type="fig" rid="Ch1.F2"/>, but using the difference-from-reference-period method,
for Krakatau <bold>(a, b)</bold>, Pinatubo <bold>(c, d)</bold>, and EVA aerosols at 10 Tg(S) <bold>(e, f)</bold>, with the ensemble size in
parentheses in <bold>(a)</bold>, <bold>(c)</bold>, and <bold>(e)</bold>​​​​​​​.</p></caption>
        <?xmltex \hack{\hsize\textwidth}?>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f10.png"/>

      </fig>

      <?xmltex \floatpos{h!}?><fig id="App1.Ch1.S1.F11"><?xmltex \currentcnt{A3}?><?xmltex \def\figurename{Figure}?><label>Figure A3</label><caption><p id="d1e3067">As in Fig. <xref ref-type="fig" rid="Ch1.F5"/>, but using the difference-from-reference-period method,
for Krakatau <bold>(a, b)</bold>, Pinatubo <bold>(c, d)</bold>, and EVA aerosols at 10 Tg(S) <bold>(e, f)</bold>, with the ensemble size in
parentheses in <bold>(a)</bold>, <bold>(c)</bold>, and <bold>(e)</bold>.</p></caption>
        <?xmltex \hack{\hsize\textwidth}?>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/22/8843/2022/acp-22-8843-2022-f11.png"/>

      </fig>

<?xmltex \hack{\clearpage}?>
</app>
  </app-group><notes notes-type="codedataavailability"><title>Code and data availability</title>

      <p id="d1e3105">The historical simulations for CMIP6 are available on the Earth System Grid
Federation (<ext-link xlink:href="https://doi.org/10.22033/ESGF/CMIP6.7129" ext-link-type="DOI">10.22033/ESGF/CMIP6.7129</ext-link>, <xref ref-type="bibr" rid="bib1.bibx26" id="altparen.97"/>). The EVA simulations are stored on NASA servers, and the
authors will gladly make them available upon request, together with our EVA namelists. ModelE
source code is available at <uri>https://www.giss.nasa.gov/tools/modelE/</uri> <xref ref-type="bibr" rid="bib1.bibx27 bib1.bibx32" id="paren.98"/>. The EVA protocol files are available at <ext-link xlink:href="https://doi.org/10.5194/gmd-9-4049-2016-supplement" ext-link-type="DOI">10.5194/gmd-9-4049-2016-supplement</ext-link> <xref ref-type="bibr" rid="bib1.bibx43" id="paren.99"/>.</p>
  </notes><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3130">The authors designed the study together. KD performed the model integrations,
analyzed the output, and sketched an early draft of the manuscript. LMP contributed the majority
of the writing, and both authors carefully reviewed and approved the final version of the paper.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3136">The contact author has declared that neither they nor their co-author has any competing interests.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d1e3142">Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3148">Kevin DallaSanta acknowledges support from the NASA Postdoctoral Program at the Goddard Institute for Space
Studies, and computational resources supporting this work were provided by the NASA High-End
Computing (HEC) Program through the NASA Center for Climate Simulation (NCCS) at Goddard Space
Flight Center. Lorenzo M. Polvani is supported by an award from the U.S. National Science Foundation
to Columbia University. The authors are grateful to Clara Orbe and Kostas Tsigaridis for useful
conversations, and to Zachary McGraw for a careful reading of the manuscript prior to submission
and for an insightful suggestion.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3153">This research has been supported by the National Science Foundation, Directorate for Geosciences (grant no. 1914569), and the National Aeronautics and Space Administration, Goddard Institute for Space Studies (grant no. NNH15CO48B).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3159">This paper was edited by Farahnaz Khosrawi and reviewed by Alan Robock and one anonymous referee.</p>
  </notes><ref-list>
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