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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">
  <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-18-4403-2018</article-id><title-group><article-title>Spatio-temporal variations of nitric acid total columns from 9 years of IASI measurements – a driver study</article-title><alt-title>Spatio-temporal variations of HNO<inline-formula><mml:math id="M1" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns</alt-title>
      </title-group><?xmltex \runningtitle{Spatio-temporal variations of HNO${}_{3}$ total columns}?><?xmltex \runningauthor{G. Ronsmans et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Ronsmans</surname><given-names>Gaétane</given-names></name>
          <email>gronsman@ulb.ac.be</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Wespes</surname><given-names>Catherine</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Hurtmans</surname><given-names>Daniel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Clerbaux</surname><given-names>Cathy</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Coheur</surname><given-names>Pierre-François</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Université Libre de Bruxelles (ULB), Faculté des Sciences, Chimie Quantique et Photophysique, Brussels, Belgium</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>LATMOS/IPSL, UPMC Univ. Paris 06 Sorbonne Universités, UVSQ, CNRS, Paris, France</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Gaétane Ronsmans (gronsman@ulb.ac.be)</corresp></author-notes><pub-date><day>3</day><month>April</month><year>2018</year></pub-date>
      
      <volume>18</volume>
      <issue>7</issue>
      <fpage>4403</fpage><lpage>4423</lpage>
      <history>
        <date date-type="received"><day>7</day><month>November</month><year>2017</year></date>
           <date date-type="rev-request"><day>27</day><month>November</month><year>2017</year></date>
           <date date-type="rev-recd"><day>27</day><month>February</month><year>2018</year></date>
           <date date-type="accepted"><day>1</day><month>March</month><year>2018</year></date>
      </history>
      <permissions>
        
        
      <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/18/4403/2018/acp-18-4403-2018.html">This article is available from https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018.html</self-uri><self-uri xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018.pdf</self-uri>
      <abstract>
    <p id="d1e132">This study aims to understand the spatial and temporal variability of
HNO<inline-formula><mml:math id="M2" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns in terms of explanatory variables. To achieve this,
multiple linear regressions are used to fit satellite-derived time series of
HNO<inline-formula><mml:math id="M3" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> daily averaged total columns. First, an analysis of the IASI 9-year
time series (2008–2016) is conducted based on various equivalent latitude
bands. The strong and systematic denitrification of the southern polar
stratosphere is observed very clearly. It is also possible to distinguish,
within the polar vortex, three regions which are differently affected by the
denitrification. Three exceptional denitrification episodes in 2011, 2014 and
2016 are also observed in the Northern Hemisphere, due to unusually low
arctic temperatures. The time series are then fitted by multivariate
regressions to identify what variables are responsible for HNO<inline-formula><mml:math id="M4" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
variability in global distributions and time series, and to quantify their
respective influence. Out of an ensemble of proxies (annual cycle, solar
flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and
Antarctic oscillations and volume of polar stratospheric clouds), only the
those defined as significant (<inline-formula><mml:math id="M5" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M6" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.05) by a selection algorithm
are retained for each equivalent latitude band. Overall, the regression gives
a good representation of HNO<inline-formula><mml:math id="M7" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability, with especially good results at
high latitudes (60–80 % of the observed variability explained by the
model). The regressions show the dominance of annual variability in all
latitudinal bands, which is related to specific chemistry and dynamics
depending on the latitudes. We find that the polar stratospheric clouds
(PSCs) also have a major influence in the polar regions, and that their
inclusion in the model improves the correlation coefficients and the
residuals. However, there is still a relatively large portion of HNO<inline-formula><mml:math id="M8" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
variability that remains unexplained by the model, especially in the
intertropical regions, where factors not included in the regression model
(such as vegetation fires or lightning) may be at play.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <?pagebreak page4404?><p id="d1e202">Nitric acid (HNO<inline-formula><mml:math id="M9" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) is known to influence ozone (O<inline-formula><mml:math id="M10" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) concentrations in
the polar regions, due to its role as a NO<inline-formula><mml:math id="M11" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula>
(<inline-formula><mml:math id="M12" display="inline"><mml:mo lspace="0mm">≡</mml:mo></mml:math></inline-formula> NO <inline-formula><mml:math id="M13" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> NO<inline-formula><mml:math id="M14" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) reservoir and its ability to form polar
stratospheric clouds (PSCs) inside the vortex
<xref ref-type="bibr" rid="bib1.bibx82 bib1.bibx91 bib1.bibx65" id="paren.1"><named-content content-type="pre">e.g.</named-content></xref>. In the stratosphere, HNO<inline-formula><mml:math id="M15" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
forms from the reaction between OH and NO<inline-formula><mml:math id="M16" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (produced by the reaction
N<inline-formula><mml:math id="M17" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O <inline-formula><mml:math id="M18" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> O<inline-formula><mml:math id="M19" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msup></mml:math></inline-formula>D) and is destroyed by reaction with OH or
photodissociation,
both of these reactions being slow
during daytime and virtually non-existent at night-time
<xref ref-type="bibr" rid="bib1.bibx56 bib1.bibx73" id="paren.2"/>. This leads to photochemical lifetimes
between 1 and 3 months up to 30 km altitude and around 10 days at higher
altitudes <xref ref-type="bibr" rid="bib1.bibx1" id="paren.3"/>, inducing similar general transport pathways for
O<inline-formula><mml:math id="M20" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and NO<inline-formula><mml:math id="M21" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> (the sum of all reactive nitrogen species – including
HNO<inline-formula><mml:math id="M22" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) <xref ref-type="bibr" rid="bib1.bibx14" id="paren.4"/>. During the polar winter, with the arrival of
low temperatures, PSCs, composed of HNO<inline-formula><mml:math id="M23" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, sulphuric acid (H<inline-formula><mml:math id="M24" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>SO<inline-formula><mml:math id="M25" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula>) and
water ice (H<inline-formula><mml:math id="M26" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O), form within the vortex
<xref ref-type="bibr" rid="bib1.bibx95 bib1.bibx96" id="paren.5"><named-content content-type="pre">e.g.</named-content></xref>. They act as sites for heterogeneous
reactions, turning inactive forms of chlorine and bromine into active
radicals, and leading to the depletion of O<inline-formula><mml:math id="M27" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the polar regions
<xref ref-type="bibr" rid="bib1.bibx82 bib1.bibx98 bib1.bibx21 bib1.bibx99" id="paren.6"><named-content content-type="pre">e.g.</named-content></xref>. Furthermore, the
formation of these PSCs, particularly the nitric acid trihydrates (NAT),
leads to the denitrification of the stratosphere (condensation of HNO<inline-formula><mml:math id="M28" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
followed by sedimentation towards the lower stratosphere), which prevents
ClONO<inline-formula><mml:math id="M29" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> from reforming <xref ref-type="bibr" rid="bib1.bibx18 bib1.bibx82 bib1.bibx70" id="paren.7"><named-content content-type="pre">e.g.</named-content></xref>
and further enhances the depletion of ozone.</p>
      <p id="d1e421">HNO<inline-formula><mml:math id="M30" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> has been measured by a variety of instruments over the last few
decades, of which the MLS (on the UARS, then the Aura satellite) provided the
most complete data set. MLS measurements began in 1991 and allowed for the
extensive analyses of seasonal and interannual variability, as well as the
vertical distribution of HNO<inline-formula><mml:math id="M31" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
<xref ref-type="bibr" rid="bib1.bibx72 bib1.bibx73" id="paren.8"/>,
however with a coarse horizontal resolution. Other
instruments have also measured HNO<inline-formula><mml:math id="M32" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the atmosphere, such as MIPAS
(ENVISAT, <xref ref-type="bibr" rid="bib1.bibx63" id="altparen.9"/>), ACE-FTS (SCISAT, <xref ref-type="bibr" rid="bib1.bibx97" id="altparen.10"/>) and
SMR<fn id="Ch1.Footn1"><p id="d1e461">in the order of the instruments cited above: Microwave Limb
Sounder (MLS), Michelson Interferometer for Passive Atmospheric Sounding
(MIPAS), Atmospheric Chemistry Experiment-Fourier Transform Spectrometer
(ACE-FTS), Sub-Millimetre Radiometer (SMR)</p></fn> (Odin, <xref ref-type="bibr" rid="bib1.bibx91" id="altparen.11"/>),
although few of these data have been used for geophysical analyses in terms
of chemical and physical processes influencing HNO<inline-formula><mml:math id="M33" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, mostly due to the
limited horizontal sampling of these instruments.</p>
      <p id="d1e477">O<inline-formula><mml:math id="M34" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in comparison has been extensively analysed, and numerous studies
have been conducted to provide a better understanding of the factors
influencing stratospheric O<inline-formula><mml:math id="M35" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> depletion processes and to assess the
efficiency of international treaties put in place to reduce its
extent (e.g.
<xref ref-type="bibr" rid="bib1.bibx42 bib1.bibx82 bib1.bibx59 bib1.bibx48 bib1.bibx36 bib1.bibx102" id="altparen.12"/>).
Most recent studies have used multivariate regression analyses in order to
identify and quantify the main contributors to O<inline-formula><mml:math id="M36" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> spatial and seasonal
variations. The variables included in such regression models depend on the
atmospheric layer investigated (troposphere or stratosphere) and most often
include the solar cycle, the quasi-biennial oscillation (QBO), the aerosol
loading and the equivalent effective stratospheric chlorine (EESC) (e.g.
<xref ref-type="bibr" rid="bib1.bibx105 bib1.bibx80 bib1.bibx11" id="altparen.13"/>). They also often include
climate-related proxies for specific dynamical patterns such as El Niño–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) or the
Antarctic Oscillation (AAO) <xref ref-type="bibr" rid="bib1.bibx15 bib1.bibx68" id="paren.14"/>. In various
multivariate regression studies, an iterative selection procedure is used to
isolate the relevant variables for the concerned species
<xref ref-type="bibr" rid="bib1.bibx84 bib1.bibx47 bib1.bibx36 bib1.bibx102 bib1.bibx103" id="paren.15"/>.</p>
      <p id="d1e520">Despite the fact that it is one of the main species influencing stratospheric
O<inline-formula><mml:math id="M37" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, HNO<inline-formula><mml:math id="M38" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> has been studied much less in terms of explanatory variables,
in part because of the lack of global, consistent and sustained measurements.
Identifying the factors driving its spatial and temporal variability could consequently
help to characterize its behaviour in stratospheric chemistry, and hence
its interactions with O<inline-formula><mml:math id="M39" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>.</p>
      <p id="d1e551">The Infrared Atmospheric Sounding Interferometer (IASI) on-board the Metop
satellites has been, and still is, providing global measurements of the
HNO<inline-formula><mml:math id="M40" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total column, which are used here to investigate HNO<inline-formula><mml:math id="M41" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> spatial and
temporal variability. The data set used (Sect. <xref ref-type="sec" rid="Ch1.S2"/>) consists of a
time series of HNO<inline-formula><mml:math id="M42" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns retrieved from IASI/Metop A measurements over
the period 2008–2016; measurements were taken twice daily and with global
coverage. This unprecedented spatial and temporal sampling of the high
latitudes allows for an in-depth monitoring of the atmospheric state, in
particular during the polar winter <xref ref-type="bibr" rid="bib1.bibx101 bib1.bibx70" id="paren.16"/>. We make
use of equivalent latitudes in order to isolate polar air masses with
specific polar vortex characteristics, and therefore better understand the
role of HNO<inline-formula><mml:math id="M43" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in polar chemistry, with regard to geophysical features such
as the extent of the polar vortex and polar temperatures
(Sect. <xref ref-type="sec" rid="Ch1.S3"/>). We next apply multivariate regressions to the
IASI-derived HNO<inline-formula><mml:math id="M44" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> time series to statistically characterize their global
distributions and seasonal variability at different latitudes for the first
time. The global coverage and the sampling of observations also allow for the
retrieval of global patterns of the main HNO<inline-formula><mml:math id="M45" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> drivers (Sect. <xref ref-type="sec" rid="Ch1.S4"/>).</p>
</sec>
<sec id="Ch1.S2">
  <?xmltex \opttitle{IASI HNO${}_{3}$ data}?><title>IASI HNO<inline-formula><mml:math id="M46" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> data</title>
      <p id="d1e634">The HNO<inline-formula><mml:math id="M47" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns used here were retrieved from measurements taken by the
IASI instrument on-board the Metop A satellite. IASI measures the upwelling
infrared radiation from the Earth's surface and the atmosphere in the
645–2760 cm<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> spectral range at nadir and off-nadir along a broad
swath (2200 km). The level 1C data set used for the retrieval consists of
measurements taken twice daily (at 09:30 and 21:00, equatorial crossing
time) at a 0.5 cm<inline-formula><mml:math id="M49" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> apodized spectral resolution and with a low
radiometric noise (0.2 K in the HNO<inline-formula><mml:math id="M50" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> atmospheric window)
<xref ref-type="bibr" rid="bib1.bibx7 bib1.bibx23" id="paren.17"/>. The ground field of view of the instrument
consists of four elliptical pixels (2 by 2) yielding a horizontal footprint
(single pixel) that varies from 113 km<inline-formula><mml:math id="M51" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> (12 km diameter) at nadir to
400 km<inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> at the end of the swath.</p>
      <p id="d1e701">To retrieve HNO<inline-formula><mml:math id="M53" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> atmospheric concentrations, we use the level 1C
measurements available in near real-time at Université Libre de Bruxelles
(ULB) and retrieved by the Fast Optimal Retrievals on Layers for IASI (FORLI)
software, which uses the optimal estimation method <xref ref-type="bibr" rid="bib1.bibx69" id="paren.18"/>. A
complete description of the FORLI method can be found in <xref ref-type="bibr" rid="bib1.bibx29" id="normal.19"/>
and a summary of the retrieval parameters specific to HNO<inline-formula><mml:math id="M54" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in
<xref ref-type="bibr" rid="bib1.bibx70" id="normal.20"/>. The retrieval initially yields HNO<inline-formula><mml:math id="M55" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> vertical profiles
on 41 levels (from 0 to 40 km altitude) but with limited vertical
sensitivity. The characterization of the retrieved profiles conducted by
<xref ref-type="bibr" rid="bib1.bibx70" id="text.21"/> showed that the degrees of freedom for signal (DOFS)
range from 0.9 to 1.2 at all latitudes. Because of this lack of vertical
sensitivity, the HNO<inline-formula><mml:math id="M56" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total column is the most representative quantity for
the IASI measurements and is exploited here for the investigation of HNO<inline-formula><mml:math id="M57" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
time<?pagebreak page4405?> evolution. It is important to note, however, as thoroughly discussed
in <xref ref-type="bibr" rid="bib1.bibx70" id="text.22"/>, that the information on the HNO<inline-formula><mml:math id="M58" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> profile comes
mostly from the lower stratosphere (15–20 km) and the profile is therefore
mainly indicative of stratospheric abundance. In order to compute the total column, the retrieved vertical
profiles are integrated over the whole altitudinal range. Our previous study
showed that the resulting total columns yield a mean error of 10 % and a
low bias (10.5 %) when compared to ground-based FTIR measurements
<xref ref-type="bibr" rid="bib1.bibx70" id="paren.23"/>. The data set used spans from January 2008 to December
2016 with daily median HNO<inline-formula><mml:math id="M59" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns averaged on a <inline-formula><mml:math id="M60" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">2.5</mml:mn><mml:mo>∘</mml:mo></mml:msup><mml:mo>×</mml:mo><mml:msup><mml:mn mathvariant="normal">2.5</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> grid, for which both day and night measurements were used. Based
on cloud information from the EUMETSAT operational processing, the
cloud-contaminated scenes are filtered out, i.e. all scenes with a fractional
cloud cover higher than 25 % are not taken into account. It should be
noted that there was an abnormally small amount of IASI L2 data distributed
by EUMETSAT between 14 September and 2 December 2010 <xref ref-type="bibr" rid="bib1.bibx93" id="paren.24"/>,
and that these data have been removed from the figures and analyses in this
particular paper. For the purpose of this study the data are divided into
several time series according to equivalent latitudes
(sometimes referred to as
“eqlat”), which allow one to consider dynamically consistent regions of the
atmosphere throughout the globe and better preserve the sharp gradients
across the edge of the polar vortex. The potential vorticity data are daily
fields obtained from ECMWF ERA Interim reanalyses, taken at the potential
temperature of 530 K. Following the analysis of the potential vorticity
contours, we consider five equivalent latitude bands in each hemisphere
(30–40, 40–55, 55–65, 65–70, 70–90<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>), plus the intertropical
band (30<inline-formula><mml:math id="M62" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N–30<inline-formula><mml:math id="M63" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S), with the corresponding potential
vorticity contours, in units of 10<inline-formula><mml:math id="M64" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> K m<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> kg<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> s<inline-formula><mml:math id="M67" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>,
being 2.5 (<inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">30</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>), 3 (<inline-formula><mml:math id="M69" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">40</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>), 5 (<inline-formula><mml:math id="M70" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">55</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>), 8 (<inline-formula><mml:math id="M71" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">65</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>)
and 10 (<inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">70</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>) (Fig. <xref ref-type="fig" rid="Ch1.F1"/>).</p>
</sec>
<sec id="Ch1.S3">
  <?xmltex \opttitle{HNO${}_{3}$ time series}?><title>HNO<inline-formula><mml:math id="M73" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> time series</title>
      <p id="d1e955">The HNO<inline-formula><mml:math id="M74" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> time series for the mid to high latitudes are displayed in
Fig. <xref ref-type="fig" rid="Ch1.F2"/> for the years 2008–2016. Total columns are
represented for both north (green) and south (blue curves) hemispheres, for
equivalent latitudes bands 40–55, 55–65, 65–70 and 70–90<inline-formula><mml:math id="M75" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>. Also
highlighted by shaded areas are the periods during which the northern and
southern polar temperatures, taken at 50 hPa (light green and light
blue for the 70–90 eqlat band, N
and S respectively, and purple
for the 65–70<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band), were equal to or below the polar
stratospheric clouds formation threshold (195 K, based on ECMWF
temperatures). It should be noted that while this temperature is a widely
accepted approximation for the formation threshold for NAT (type I), its
actual value can differ depending on the local conditions
<xref ref-type="bibr" rid="bib1.bibx46 bib1.bibx12 bib1.bibx28" id="paren.25"/>. Also, other forms of PSCs, particularly
type II PSCs (ice clouds), form at a lower temperature of 188 K,
corresponding to the frost point of water, or 2–3 K below the frost point
(e.g. <xref ref-type="bibr" rid="bib1.bibx89 bib1.bibx62 bib1.bibx85 bib1.bibx13" id="altparen.26"/>).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><caption><p id="d1e996">Example of equivalent latitude contours for <inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">70</mml:mn></mml:mrow></mml:math></inline-formula> (blue), <inline-formula><mml:math id="M78" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">65</mml:mn></mml:mrow></mml:math></inline-formula>
(light blue), <inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">55</mml:mn></mml:mrow></mml:math></inline-formula> (red) and <inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">40</mml:mn></mml:mrow></mml:math></inline-formula> (green) equivalent latitudes. The
background colours are HNO<inline-formula><mml:math id="M81" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns (daily mean for 21 July 2011, in
molec cm<inline-formula><mml:math id="M82" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>).
</p></caption>
        <?xmltex \igopts{width=213.395669pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f01.pdf"/>

      </fig>

      <p id="d1e1067">As a general rule, we find larger concentrations in the Northern Hemisphere,
for the entire latitudinal range shown here (40–90 eqlat). The hemispheric
difference in HNO<inline-formula><mml:math id="M83" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> maximum concentrations can be partly attributed to the
hemispheric asymmetry of the Brewer–Dobson circulation associated with the
many topographical features in the Northern Hemisphere compared to the
Southern Hemisphere. As a result, the Northern Hemisphere has a more intense
planetary wave activity, which strengthens the deep branch of the
Brewer–Dobson circulation. This also has a direct effect on the latitudinal
mixing processes, which usually extend into the Arctic polar region, but less so
into the Antarctic due to a stronger polar vortex
<xref ref-type="bibr" rid="bib1.bibx58 bib1.bibx5" id="paren.27"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p id="d1e1085"><bold>(a–d)</bold> HNO<inline-formula><mml:math id="M84" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns time series for the years
2008–2016, for equivalent latitude bands 70–90, 65–70, 55–65 and 40–55,
north (green) and south (blue). Vertical shaded areas are the periods during
which the average temperatures are below <inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mtext>NAT</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> in the north (green)
and south (blue) 70–90<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> band, and in the south (purple)
65–70<inline-formula><mml:math id="M87" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> band. Note that the large period without data in 2010 is when
there was a low amount of data distributed by EUMETSAT (see
Sect. <xref ref-type="sec" rid="Ch1.S2"/>). <bold>(e)</bold> Daily average temperatures time series
(in K) taken at the altitude of 50 hPa for the equivalent latitude bands
70–90<inline-formula><mml:math id="M88" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (green) and South (blue) and 65–70<inline-formula><mml:math id="M89" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S (purple).
The horizontal black line represents <inline-formula><mml:math id="M90" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mtext>NAT</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>, i.e. the 195 K line.</p></caption>
        <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f02.png"/>

      </fig>

      <p id="d1e1169">Beyond hemispheric asymmetry, we also find that HNO<inline-formula><mml:math id="M91" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns are generally
larger at higher latitudes, with total column maxima between
3.0 <inline-formula><mml:math id="M92" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M93" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> and 3.7 <inline-formula><mml:math id="M94" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M95" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M96" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in
the equivalent latitudes bands 70–90, 65–70 and 55–65<inline-formula><mml:math id="M97" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, and lower
at around 2.2 <inline-formula><mml:math id="M98" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M99" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M100" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in the 40–55<inline-formula><mml:math id="M101" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
band, especially for the Southern Hemisphere. This latitudinal gradient of
HNO<inline-formula><mml:math id="M102" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> has been previously documented (e.g.
<xref ref-type="bibr" rid="bib1.bibx73 bib1.bibx91 bib1.bibx101 bib1.bibx70" id="altparen.28"/>) and can mainly be
explained by the larger amounts of NO<inline-formula><mml:math id="M103" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> at high latitudes due to a larger
age of air and the NO<inline-formula><mml:math id="M104" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> partitioning favouring HNO<inline-formula><mml:math id="M105" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>. An interesting
feature observable in Fig. <xref ref-type="fig" rid="Ch1.F2"/> is the different behaviour of
the three highest latitude regions with regard to the polar<?pagebreak page4406?> stratospheric
cloud formation threshold in the Southern Hemisphere. The denitrification
process that occurs with the condensation and sedimentation of PSCs (see e.g.
<xref ref-type="bibr" rid="bib1.bibx101 bib1.bibx52" id="altparen.29"/> and <xref ref-type="bibr" rid="bib1.bibx70" id="altparen.30"/> for further
details) is obvious in the 70–90<inline-formula><mml:math id="M106" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S region (blue curve in
Fig. <xref ref-type="fig" rid="Ch1.F2"/>a), with a systematic and strong decrease in HNO<inline-formula><mml:math id="M107" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
total columns (from 3.3 <inline-formula><mml:math id="M108" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M109" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> to
1.5 <inline-formula><mml:math id="M110" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M111" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M112" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) starting within 12 to 25 days
after the stratospheric temperature reaches the threshold of 195 K (start of
the blue shaded areas). The loss of HNO<inline-formula><mml:math id="M113" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> therefore usually starts around
the beginning of June in the Antarctic and the concentrations reach their
minimum value within one month. They stay low at
1.4 <inline-formula><mml:math id="M114" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M115" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M116" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> until mid-November (with a slight
gradual increase to 1.7 <inline-formula><mml:math id="M117" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M118" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M119" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> quite often
seen during the two following months), and start to increase again during
January, i.e. between 2.5 and 3 months after the polar stratospheric
temperatures are back above the NAT formation threshold. The same pattern can
be observed in the 65–70<inline-formula><mml:math id="M120" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S equivalent latitude region. However, a
delay of approximately 1 month exists for the start of the steepest decrease
in HNO<inline-formula><mml:math id="M121" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns, which appears to be more gradual than in the
70–90<inline-formula><mml:math id="M122" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S regions (3 months to reach minimum values, starting in
July). The minimum and plateau column values are thus reached by the end of
September; they remain higher than at the highest latitudes, with values
staying at around 1.7 <inline-formula><mml:math id="M123" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M124" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M125" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The delayed and
less severe loss of HNO<inline-formula><mml:math id="M126" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the 65–70<inline-formula><mml:math id="M127" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S band confirms that the
denitrification process spreads from the centre of the polar vortex, where
the lowest temperatures are reached first
<xref ref-type="bibr" rid="bib1.bibx56 bib1.bibx73 bib1.bibx41" id="paren.31"/>. This spreading from the centre
also leads to slightly higher concentrations for the maxima in the
65–70<inline-formula><mml:math id="M128" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band (mean of maxima of 3.26 <inline-formula><mml:math id="M129" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M130" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula>
versus 3.11 <inline-formula><mml:math id="M131" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M132" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M133" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in the 70–90<inline-formula><mml:math id="M134" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S
eqlat band). The delayed decrease in HNO<inline-formula><mml:math id="M135" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the outer parts of the vortex
(i.e. in the 65–70<inline-formula><mml:math id="M136" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band) can thus be attributed to the
later appearance of PSCs in this region (see Fig. <xref ref-type="fig" rid="Ch1.F2"/>b purple
shaded areas). By the end of December, when the vortex has started breaking
down (e.g. <xref ref-type="bibr" rid="bib1.bibx77 bib1.bibx51 bib1.bibx58" id="altparen.32"/>), the total
columns in both eqlat bands become homogenized and reach the same range of
values (1.7 <inline-formula><mml:math id="M137" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M138" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M139" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p id="d1e1647">Zonally averaged daily HNO<inline-formula><mml:math id="M140" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns distribution over
2008–2016, expressed in molec cm<inline-formula><mml:math id="M141" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The lines represent potential
vorticity contours at a potential temperature of 530 K (5 (black), 8 (cyan)
and 10 (blue) <inline-formula><mml:math id="M142" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M143" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> K m<inline-formula><mml:math id="M144" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> kg<inline-formula><mml:math id="M145" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> s<inline-formula><mml:math id="M146" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) which
correspond to the equivalent latitudes contours illustrated in
Fig. <xref ref-type="fig" rid="Ch1.F1"/>.</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f03.png"/>

      </fig>

      <p id="d1e1732">If the decrease is slower at 65–70 eqlat, this is not the case for the
recovery, with the build-up of concentrations starting roughly at the same
time as for the 70–90<inline-formula><mml:math id="M147" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band,<?pagebreak page4407?> hence resulting in a shorter
period of denitrified atmosphere in the 65–70<inline-formula><mml:math id="M148" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S band. These
results agree well with previous studies by <xref ref-type="bibr" rid="bib1.bibx56" id="text.33"/> and
<xref ref-type="bibr" rid="bib1.bibx73" id="text.34"/> for earlier years. However, the recovery of the HNO<inline-formula><mml:math id="M149" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
total columns is very slow compared to other species, namely O<inline-formula><mml:math id="M150" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, for which
concentrations return to usual values within 2 months (i.e. in December)
after PSCs have disappeared. In fact, the HNO<inline-formula><mml:math id="M151" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns stay low until well
after the September equinox and are only subject to a slow increase starting
2 months later (in early December) with concentrations back to
pre-denitrification levels by May. While more persistent local temperature
minima staying below 195 K could explain part of this late recovery, we
hypothesize that it is mainly due to a combination of two factors: (1) the
significant sedimentation of PSCs towards the lower atmosphere during the
winter, such that few PSCs remain available to release HNO<inline-formula><mml:math id="M152" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> under warmer
temperatures <xref ref-type="bibr" rid="bib1.bibx46 bib1.bibx33 bib1.bibx32" id="paren.35"/>; and (2) the effective
photolysis of HNO<inline-formula><mml:math id="M153" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and NO<inline-formula><mml:math id="M154" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in spring and summer under prolonged
sunlight conditions, mainly at the highest latitudes, which respectively
increase the HNO<inline-formula><mml:math id="M155" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> sink and reduce the chemical source (because NO<inline-formula><mml:math id="M156" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
cannot react with NO<inline-formula><mml:math id="M157" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> to produce N<inline-formula><mml:math id="M158" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O<inline-formula><mml:math id="M159" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">5</mml:mn></mml:msub></mml:math></inline-formula>,
<xref ref-type="bibr" rid="bib1.bibx82 bib1.bibx30 bib1.bibx56" id="altparen.36"/>). The increase observed in
March, at the start of the winter, can in turn be explained by a reduction in
the number of hours of sunlight (implying less photodissociation), as well as
by diabatic descent, which brings HNO<inline-formula><mml:math id="M160" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>-rich air to lower altitudes.</p>
      <p id="d1e1876">It is worth noting that the two regions previously mentioned (inner and outer
vortex) have been observed to behave differently; the inner vortex
(70–90<inline-formula><mml:math id="M161" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) undergoes strong internal mixing whereas the outer
vortex (65–70<inline-formula><mml:math id="M162" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S), isolated from the vortex core, experiences
little mixing of air. This, combined with a cooling of the stratosphere, could
lead to increased PSC formation and further ozone depletion
<xref ref-type="bibr" rid="bib1.bibx43 bib1.bibx71" id="paren.37"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p id="d1e1903">For northern <bold>(a)</bold> and southern <bold>(b)</bold> 70–90
equivalent latitude bands: HNO<inline-formula><mml:math id="M163" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns time series for the years
2008 to 2016 in molec cm<inline-formula><mml:math id="M164" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. Note that the <inline-formula><mml:math id="M165" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> axis limits differ
between the two plots. </p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f04.pdf"/>

      </fig>

      <p id="d1e1946">Regarding the HNO<inline-formula><mml:math id="M166" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns in the 55–65<inline-formula><mml:math id="M167" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band, which
comprises the vortex rim, or “collar” <xref ref-type="bibr" rid="bib1.bibx89" id="paren.38"/>, it is evident from
Fig. <xref ref-type="fig" rid="Ch1.F2"/>c that they are not affected by denitrification,
which is in agreement with previous observations (e.g.
<xref ref-type="bibr" rid="bib1.bibx72 bib1.bibx101 bib1.bibx70" id="altparen.39"/>). In fact, we show that columns
in this particular band keep increasing when temperatures at higher latitudes
start decreasing, to reach maximum values of about
3.4 <inline-formula><mml:math id="M168" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M169" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M170" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in June–July; this is due to a
change in NO<inline-formula><mml:math id="M171" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> partitioning towards HNO<inline-formula><mml:math id="M172" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, which is in turn due to less
sunlight in this period compared to summer. Also inducing increased
concentrations during the winter at high latitudes is the diabatic descent
occurring inside the vortex when temperatures decrease. This downward motion
of air enriches the lower stratosphere with HNO<inline-formula><mml:math id="M173" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> coming from higher
altitude <xref ref-type="bibr" rid="bib1.bibx50 bib1.bibx72" id="paren.40"/>, yielding higher column values which
are, in this eqlat band, not affected by denitrification. The slow decrease
in HNO<inline-formula><mml:math id="M174" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> starting in August and leading to minimum values in January is
related to the combined effect of increased photodissociation and mixing with
the denitrified polar air masses which are no longer confined to the polar
regions. Finally, as previously mentioned, the 40–55<inline-formula><mml:math id="M175" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band
records lower column values throughout the year (generally below
2 <inline-formula><mml:math id="M176" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M177" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M178" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and a much less pronounced seasonal
cycle.</p>
      <?pagebreak page4408?><p id="d1e2081">High latitudes in the Northern Hemisphere do not usually experience
denitrification, mostly because the temperatures, while frequently showing
local minima below 195 K, rarely reach the PSC formation threshold over
broad areas and for long time spans (see Fig. <xref ref-type="fig" rid="Ch1.F2"/> for average
temperatures, light green vertical areas). A few years stand out, however,
with exceptionally low stratospheric temperatures. This is especially the
case of the 2011 <xref ref-type="bibr" rid="bib1.bibx52" id="paren.41"/>, 2016 and, to some extent, 2014 Arctic
winters. During these three winters, temperatures dropped below the 195 K
threshold over a broader area and stayed low for a longer period than usual. Lower concentrations of
HNO<inline-formula><mml:math id="M179" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> were recorded as a consequence, especially in the northernmost
equivalent latitude band (see Fig. <xref ref-type="fig" rid="Ch1.F2"/>). The winter
2016 recorded exceptionally low temperatures
in particular, which led to large denitrification and significant ozone
depletion <xref ref-type="bibr" rid="bib1.bibx49 bib1.bibx53" id="paren.42"/>. The denitrification that occurred
in the northern polar regions affected a smaller area than is generally
observed in the Southern
Hemisphere; the columns in the 65–70<inline-formula><mml:math id="M180" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N eqlat band in particular do
not show a significant decrease.</p>
      <p id="d1e2113">Figure <xref ref-type="fig" rid="Ch1.F3"/>, which consists of the time series of the zonally
averaged distribution of HNO<inline-formula><mml:math id="M181" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> retrieved total columns, illustrates all of
these features particularly well: it highlights the low and constant columns
between <inline-formula><mml:math id="M182" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">40</mml:mn></mml:mrow></mml:math></inline-formula> and 40 degrees of latitude, the marked annual cycle at mid to
high latitudes and the systematic and occasional (2011, 2014, 2016) loss
of HNO<inline-formula><mml:math id="M183" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> during denitrification periods in the high latitudes of the
Southern and Northern hemispheres respectively, which are highlighted by the
iso-contours of potential vorticity at
<inline-formula><mml:math id="M184" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>10 <inline-formula><mml:math id="M185" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M186" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> K m<inline-formula><mml:math id="M187" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> kg<inline-formula><mml:math id="M188" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> s<inline-formula><mml:math id="M189" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (dark blue).</p>
      <p id="d1e2206">In order to give further insights into the interannual variability of HNO<inline-formula><mml:math id="M190" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
in polar regions, Fig. <xref ref-type="fig" rid="Ch1.F4"/> shows the seasonal cycle for each
individual year from 2008 to 2016 for eqlat 70–90 in the northern (Fig. 4a)
and the southern (Fig. 4b) hemispheres. July and August of 2010 stand out in
the Antarctic, with high and variable columns recorded by IASI. This is a
consequence of a mid-winter (mid-July) minor sudden stratospheric warming
(SSW) event, which induced a downward motion of air masses and modified the
chemical composition of the atmosphere between 10 and 50 hPa until at least
September <xref ref-type="bibr" rid="bib1.bibx10 bib1.bibx35" id="paren.43"/>. The principal effect of this
sudden stratospheric warming was to reduce the formation of PSCs (which
stayed well below the 1979–2012 average <xref ref-type="bibr" rid="bib1.bibx104" id="altparen.44"/>) and hence reduce
denitrification. This is shown by an initial drop in HNO<inline-formula><mml:math id="M191" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns in June,
as is usually observed in other years but then by an increase in HNO<inline-formula><mml:math id="M192" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
columns when the SSW occurs. These results confirm those previously obtained
by the Aura MLS during that particular winter and reported in the World
Meteorological Organization (WMO) Ozone Assessment of 2014 (see Fig. 6-3 in
<xref ref-type="bibr" rid="bib1.bibx104" id="altparen.45"/>). Apart from these peculiarities for the year 2010, all
years seem to coincide quite well in terms of seasonality in the Southern
Hemisphere (bottom panel, Fig. 4). The timing of the HNO<inline-formula><mml:math id="M193" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> steep decrease
in particular is consistent from one year to another.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p id="d1e2261">Proxies used for the regressions and their source.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="3">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Proxy</oasis:entry>
         <oasis:entry colname="col2">Description</oasis:entry>
         <oasis:entry colname="col3">Source</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">SF</oasis:entry>
         <oasis:entry colname="col2">Solar flux at 10.7 cm</oasis:entry>
         <oasis:entry colname="col3">NOAA National Center for Environmental Information</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">(<uri>https://www.ngdc.noaa.gov/stp/solar/flux.html</uri>)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">QBO</oasis:entry>
         <oasis:entry colname="col2">Quasi-biennial oscillation</oasis:entry>
         <oasis:entry colname="col3">Free University of Berlin</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">index at 10 and 30 hPa</oasis:entry>
         <oasis:entry colname="col3">(<uri>http://www.geo.fu-berlin.de/en/met/ag/strat/produkte/qbo/index.html</uri>)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MEI</oasis:entry>
         <oasis:entry colname="col2">Multivariate ENSO Index</oasis:entry>
         <oasis:entry colname="col3">NOAA Earth System Research Laboratory</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">(<uri>http://www.esrl.noaa.gov/psd/data/climateindices/</uri>)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">VPSC</oasis:entry>
         <oasis:entry colname="col2">Volume of nitric acid trihydrates</oasis:entry>
         <oasis:entry colname="col3">Ingo Wohltmann at AWI</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">formed in the stratosphere</oasis:entry>
         <oasis:entry colname="col3">(personal communication, 2017)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AO &amp; AAO</oasis:entry>
         <oasis:entry colname="col2">Arctic &amp; Antarctic</oasis:entry>
         <oasis:entry colname="col3">NOAA Earth System Research Laboratory</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">oscillation indices</oasis:entry>
         <oasis:entry colname="col3">(<uri>http://www.esrl.noaa.gov/psd/data/climateindices/</uri>)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <?pagebreak page4409?><p id="d1e2419">The Northern Hemisphere high latitudes (top panel, Fig. 4) show more interannual variability than in
the south, especially during the winter because of the unusual
denitrification periods observed in 2011 (purple), 2014 (blue) and 2016
(black) in January (concentrations as low as
2.2 <inline-formula><mml:math id="M194" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M195" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M196" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in 2016). In contrast to the
winter, the summer columns are more uniform from one year to another with
values around 2.1 <inline-formula><mml:math id="M197" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M198" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> to
2.8 <inline-formula><mml:math id="M199" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M200" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M201" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>.</p>
</sec>
<sec id="Ch1.S4">
  <title>Fitting the observations with a regression model</title>
<sec id="Ch1.S4.SS1">
  <title>Multi-variable linear regression</title>
      <p id="d1e2506">In order to identify the processes responsible for the HNO<inline-formula><mml:math id="M202" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability
observed in the IASI measurements, we use a multivariate linear regression
model featuring various dynamical and chemical processes known to affect
HNO<inline-formula><mml:math id="M203" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> distributions. We strictly follow the methodology used by <xref ref-type="bibr" rid="bib1.bibx102" id="text.46"/> for
investigating O<inline-formula><mml:math id="M204" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability; in particular, we use daily median HNO<inline-formula><mml:math id="M205" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
total columns. These are fitted with the following model:

                <disp-formula specific-use="align" content-type="numbered"><mml:math id="M206" display="block"><mml:mtable displaystyle="true"><mml:mlabeledtr id="Ch1.E1"><mml:mtd/><mml:mtd><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><mml:msub><mml:mtext>HNO</mml:mtext><mml:mn mathvariant="normal">3</mml:mn></mml:msub><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mo>=</mml:mo></mml:mrow></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mtext>cst</mml:mtext><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>+</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msub><mml:mi>y</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>⋅</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mtext>trend</mml:mtext><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>+</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mfenced close="" open="["><mml:mrow><mml:msub><mml:mi>a</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>⋅</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mi>cos⁡</mml:mi><mml:mo>(</mml:mo><mml:mi mathvariant="italic">ω</mml:mi><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>+</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msub><mml:mi>b</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:mfenced></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mtr><mml:mtd><mml:mstyle class="stylechange" displaystyle="true"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><mml:mfenced open="" close="]"><mml:mrow><mml:mo>⋅</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi>sin⁡</mml:mi><mml:mo>(</mml:mo><mml:mi mathvariant="italic">ω</mml:mi><mml:mi>t</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mfenced><mml:mo>+</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow><mml:mi>m</mml:mi></mml:munderover><mml:mfenced close="]" open="["><mml:mrow><mml:msub><mml:mi>y</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mo>⋅</mml:mo><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msub><mml:mi>Y</mml:mi><mml:mrow><mml:mtext>Norm</mml:mtext><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mfenced><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mo>+</mml:mo><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mi mathvariant="italic">ϵ</mml:mi><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>

            where <inline-formula><mml:math id="M207" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> is the day in the time series, cst is a constant term, the
<inline-formula><mml:math id="M208" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> terms are the regression coefficients for each variable, <inline-formula><mml:math id="M209" display="inline"><mml:mrow><mml:mi mathvariant="italic">ω</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2</mml:mn><mml:mi mathvariant="italic">π</mml:mi><mml:mo>/</mml:mo><mml:mn mathvariant="normal">365.25</mml:mn></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M210" display="inline"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mrow><mml:mtext>Norm</mml:mtext><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> refers to the chosen explanatory
variables <inline-formula><mml:math id="M211" display="inline"><mml:mi>Y</mml:mi></mml:math></inline-formula>, which are normalized over the period of IASI observations
(2008–2016) following
            <disp-formula id="Ch1.E2" content-type="numbered"><mml:math id="M212" display="block"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mrow><mml:mtext>Norm</mml:mtext><mml:mo>,</mml:mo><mml:mi>i</mml:mi></mml:mrow></mml:msub><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mo>=</mml:mo><mml:mn mathvariant="normal">2</mml:mn><mml:mo>(</mml:mo><mml:mi>Y</mml:mi><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mo>-</mml:mo><mml:msub><mml:mi>Y</mml:mi><mml:mtext>median</mml:mtext></mml:msub><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:mo>(</mml:mo><mml:msub><mml:mi>Y</mml:mi><mml:mtext>max</mml:mtext></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>Y</mml:mi><mml:mtext>min</mml:mtext></mml:msub><mml:mo>)</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          with <inline-formula><mml:math id="M213" display="inline"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mtext>max</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M214" display="inline"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mtext>min</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> being the maximum and minimum
values of the variable time series (before subtraction of the median,
<inline-formula><mml:math id="M215" display="inline"><mml:mrow><mml:msub><mml:mi>Y</mml:mi><mml:mtext>median</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>). The terms <inline-formula><mml:math id="M216" display="inline"><mml:mrow><mml:msub><mml:mi>a</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M217" display="inline"><mml:mrow><mml:msub><mml:mi>b</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> in Eq. (1) are the
coefficients accounting for the annual variability in the atmosphere. They
represent mainly the seasonality
of the solar insolation and of the meridional Brewer–Dobson circulation,
which is a slow stratospheric circulation redistributing the tropical air
masses to extra-tropical regions
<xref ref-type="bibr" rid="bib1.bibx58 bib1.bibx5 bib1.bibx39" id="paren.47"/>.</p>
      <p id="d1e2895">The regression coefficients are estimated by the least squares method. The
standard error (<inline-formula><mml:math id="M218" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mtext>e</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>) of each proxy is calculated based on the
regression coefficients and is corrected in order to take the autocorrelation
uncertainty into account <xref ref-type="bibr" rid="bib1.bibx36 bib1.bibx102" id="paren.48"/>:
            <disp-formula id="Ch1.E3" content-type="numbered"><mml:math id="M219" display="block"><mml:mrow><mml:msubsup><mml:mi mathvariant="italic">σ</mml:mi><mml:mtext>e</mml:mtext><mml:mn mathvariant="normal">2</mml:mn></mml:msubsup><mml:mo>=</mml:mo><mml:mo>(</mml:mo><mml:msup><mml:mi mathvariant="bold">Y</mml:mi><mml:mtext>T</mml:mtext></mml:msup><mml:mi mathvariant="bold">Y</mml:mi><mml:msup><mml:mo>)</mml:mo><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup><mml:mo>⋅</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:mo>∑</mml:mo><mml:mo>[</mml:mo><mml:mi mathvariant="bold-italic">H</mml:mi><mml:mi mathvariant="bold-italic">N</mml:mi><mml:msub><mml:mi mathvariant="bold-italic">O</mml:mi><mml:mn mathvariant="bold">3</mml:mn></mml:msub><mml:mo>-</mml:mo><mml:mi mathvariant="bold">Y</mml:mi><mml:mi mathvariant="bold-italic">y</mml:mi><mml:msup><mml:mo>]</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow><mml:mrow><mml:mi>n</mml:mi><mml:mo>-</mml:mo><mml:mi>m</mml:mi></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>⋅</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>+</mml:mo><mml:mi mathvariant="italic">φ</mml:mi></mml:mrow><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>-</mml:mo><mml:mi mathvariant="italic">φ</mml:mi></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>
          where <inline-formula><mml:math id="M220" display="inline"><mml:mi mathvariant="bold">Y</mml:mi></mml:math></inline-formula> is the matrix of explanatory variables of size <inline-formula><mml:math id="M221" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>×</mml:mo><mml:mi>m</mml:mi></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M222" display="inline"><mml:mi>n</mml:mi></mml:math></inline-formula> is the number of daily measurements and <inline-formula><mml:math id="M223" display="inline"><mml:mi>m</mml:mi></mml:math></inline-formula> the number of fitted
parameters. <inline-formula><mml:math id="M224" display="inline"><mml:mrow><mml:mi mathvariant="bold-italic">H</mml:mi><mml:mi mathvariant="bold-italic">N</mml:mi><mml:msub><mml:mi mathvariant="bold-italic">O</mml:mi><mml:mn mathvariant="bold">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> is the nitric acid column, <inline-formula><mml:math id="M225" display="inline"><mml:mi mathvariant="bold-italic">y</mml:mi></mml:math></inline-formula> the vector
of regression coefficients and <inline-formula><mml:math id="M226" display="inline"><mml:mi mathvariant="italic">φ</mml:mi></mml:math></inline-formula> is lag-1 autocorrelation of the
residuals.</p>
</sec>
<sec id="Ch1.S4.SS2">
  <title>Iterative selection of explanatory variables</title>
      <p id="d1e3069">The choice of variables included in the model is made using an iterative
elimination procedure; all variables are tested based on their importance for
the regression <xref ref-type="bibr" rid="bib1.bibx48" id="paren.49"/>. At each iteration, the variable with the
largest <inline-formula><mml:math id="M227" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value (and outside the confidence interval of 95 %) is
removed, until only the variables relevant for the regression remain,
i.e. variables with a <inline-formula><mml:math id="M228" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value smaller than 0.05. This selection algorithm is
applied on each band of equivalent latitude (or grid cell, for the global
distributions shown below) and thus yields a different combination of
variables, depending on the equivalent latitude region considered.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p id="d1e3091">Normalized proxies over the IASI observations period (2008–2016).
<bold>(a)</bold> Solar flux (yellow), QBO at 10 hPa (green) and QBO at 30 hPa
(orange). <bold>(b)</bold> Antarctic Oscillation (light blue), Arctic Oscillation
(dark blue) and Multivariate ENSO Index (MEI, pink). <bold>(c)</bold> VPSC proxy
in the Northern Hemisphere (light grey) and in the Southern Hemisphere (dark
grey).</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f05.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS3">
  <title>Variables used for the regression</title>
      <p id="d1e3115">Given the strong relationship between the O<inline-formula><mml:math id="M229" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and HNO<inline-formula><mml:math id="M230" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> chemistry and
variability <xref ref-type="bibr" rid="bib1.bibx82 bib1.bibx60 bib1.bibx74 bib1.bibx65" id="paren.50"/> and the
novelty of applying such a regression study in an HNO<inline-formula><mml:math id="M231" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> dataset, we
consider the major and well known drivers of total O<inline-formula><mml:math id="M232" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
variability here, namely a linear trend, harmonic terms for the annual
variability and geophysical proxies for the solar cycle, the QBO, the ENSO
phenomenon and the Arctic (AO) and Antarctic oscillations (AAO) for the
Northern and Southern hemispheres, respectively. Considering the short length
of the time series, however, the linear trend did not yield any significant
result and, recalling that the aim of the paper is not to derive long term
trends, this aspect will not be discussed further. In addition, a proxy for
the volume of polar<?pagebreak page4410?> stratospheric clouds is included to account for the
effect of the strong denitrification process during the polar night (cf.
Sect. <xref ref-type="sec" rid="Ch1.S3"/>). All the proxies are shown in Fig. <xref ref-type="fig" rid="Ch1.F5"/> and
described in more details hereafter. The source for each proxy is also
provided in Table <xref ref-type="table" rid="Ch1.T1"/>.</p>
<sec id="Ch1.S4.SS3.SSS1">
  <title>Solar flux (SF)</title>
      <p id="d1e3169">As a proxy for the solar activity we use the 10.7 cm solar flux
(<inline-formula><mml:math id="M233" display="inline"><mml:mrow><mml:msub><mml:mi>F</mml:mi><mml:mn mathvariant="normal">10.7</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>), which is a radio flux that varies daily and correlates to the
number of sunspots on the solar disk
<xref ref-type="bibr" rid="bib1.bibx9 bib1.bibx87 bib1.bibx86" id="paren.51"/>. The data set used here is the
adjusted flux that takes the changing earth–sun distance into account. The
solar cycle directly influences the partitioning between NO<inline-formula><mml:math id="M234" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> (produced by
the N<inline-formula><mml:math id="M235" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O <inline-formula><mml:math id="M236" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> O<inline-formula><mml:math id="M237" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msup></mml:math></inline-formula>D reaction) and HNO<inline-formula><mml:math id="M238" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> through the quantity of
sunlight available, and has been known to affect the dynamics and to
influence the O<inline-formula><mml:math id="M239" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> response in the lower stratosphere
<xref ref-type="bibr" rid="bib1.bibx25 bib1.bibx38 bib1.bibx26 bib1.bibx2" id="paren.52"><named-content content-type="pre">e.g.</named-content></xref>.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><caption><p id="d1e3247">Set of variables retained by the selection algorithm for each
equivalent latitude band. </p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.95}[.95]?><oasis:tgroup cols="11">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="left"/>
     <oasis:colspec colnum="6" colname="col6" align="left"/>
     <oasis:colspec colnum="7" colname="col7" align="left"/>
     <oasis:colspec colnum="8" colname="col8" align="left"/>
     <oasis:colspec colnum="9" colname="col9" align="left"/>
     <oasis:colspec colnum="10" colname="col10" align="left"/>
     <oasis:colspec colnum="11" colname="col11" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">70–90<inline-formula><mml:math id="M240" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col2">65–70<inline-formula><mml:math id="M241" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col3">55–65<inline-formula><mml:math id="M242" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col4">40–55<inline-formula><mml:math id="M243" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col5">30–40<inline-formula><mml:math id="M244" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S</oasis:entry>
         <oasis:entry colname="col6">30<inline-formula><mml:math id="M245" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S–30<inline-formula><mml:math id="M246" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>
         <oasis:entry colname="col7">30–40<inline-formula><mml:math id="M247" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>
         <oasis:entry colname="col8">40–55<inline-formula><mml:math id="M248" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>
         <oasis:entry colname="col9">55–65<inline-formula><mml:math id="M249" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>
         <oasis:entry colname="col10">65–70<inline-formula><mml:math id="M250" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>
         <oasis:entry colname="col11">70–90<inline-formula><mml:math id="M251" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">SF</oasis:entry>
         <oasis:entry colname="col3">SF</oasis:entry>
         <oasis:entry colname="col4">SF</oasis:entry>
         <oasis:entry colname="col5">SF</oasis:entry>
         <oasis:entry colname="col6">SF</oasis:entry>
         <oasis:entry colname="col7">SF</oasis:entry>
         <oasis:entry colname="col8">SF</oasis:entry>
         <oasis:entry colname="col9">SF</oasis:entry>
         <oasis:entry colname="col10">SF</oasis:entry>
         <oasis:entry colname="col11"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">QBO10</oasis:entry>
         <oasis:entry colname="col2">QBO10</oasis:entry>
         <oasis:entry colname="col3">QBO10</oasis:entry>
         <oasis:entry colname="col4">QBO10</oasis:entry>
         <oasis:entry colname="col5">QBO10</oasis:entry>
         <oasis:entry colname="col6">QBO10</oasis:entry>
         <oasis:entry colname="col7">QBO10</oasis:entry>
         <oasis:entry colname="col8">QBO10</oasis:entry>
         <oasis:entry colname="col9">QBO10</oasis:entry>
         <oasis:entry colname="col10">QBO10</oasis:entry>
         <oasis:entry colname="col11">QBO10</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">QBO30</oasis:entry>
         <oasis:entry colname="col4">QBO30</oasis:entry>
         <oasis:entry colname="col5">QBO30</oasis:entry>
         <oasis:entry colname="col6">QBO30</oasis:entry>
         <oasis:entry colname="col7">QBO30</oasis:entry>
         <oasis:entry colname="col8">QBO30</oasis:entry>
         <oasis:entry colname="col9">QBO30</oasis:entry>
         <oasis:entry colname="col10">QBO30</oasis:entry>
         <oasis:entry colname="col11">QBO30</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">COS1</oasis:entry>
         <oasis:entry colname="col2">COS1</oasis:entry>
         <oasis:entry colname="col3">COS1</oasis:entry>
         <oasis:entry colname="col4">COS1</oasis:entry>
         <oasis:entry colname="col5">COS1</oasis:entry>
         <oasis:entry colname="col6">COS1</oasis:entry>
         <oasis:entry colname="col7">COS1</oasis:entry>
         <oasis:entry colname="col8">COS1</oasis:entry>
         <oasis:entry colname="col9">COS1</oasis:entry>
         <oasis:entry colname="col10">COS1</oasis:entry>
         <oasis:entry colname="col11">COS1</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SIN1</oasis:entry>
         <oasis:entry colname="col2">SIN1</oasis:entry>
         <oasis:entry colname="col3">SIN1</oasis:entry>
         <oasis:entry colname="col4">SIN1</oasis:entry>
         <oasis:entry colname="col5">SIN1</oasis:entry>
         <oasis:entry colname="col6">SIN1</oasis:entry>
         <oasis:entry colname="col7">SIN1</oasis:entry>
         <oasis:entry colname="col8">SIN1</oasis:entry>
         <oasis:entry colname="col9">SIN1</oasis:entry>
         <oasis:entry colname="col10">SIN1</oasis:entry>
         <oasis:entry colname="col11">SIN1</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MEI</oasis:entry>
         <oasis:entry colname="col2">MEI</oasis:entry>
         <oasis:entry colname="col3">MEI</oasis:entry>
         <oasis:entry colname="col4">MEI</oasis:entry>
         <oasis:entry colname="col5">MEI</oasis:entry>
         <oasis:entry colname="col6">MEI</oasis:entry>
         <oasis:entry colname="col7">MEI</oasis:entry>
         <oasis:entry colname="col8">MEI</oasis:entry>
         <oasis:entry colname="col9">MEI</oasis:entry>
         <oasis:entry colname="col10"/>
         <oasis:entry colname="col11"/>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">VPSC</oasis:entry>
         <oasis:entry colname="col2">VPSC</oasis:entry>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6"/>
         <oasis:entry colname="col7"/>
         <oasis:entry colname="col8"/>
         <oasis:entry colname="col9"/>
         <oasis:entry colname="col10">VPSC</oasis:entry>
         <oasis:entry colname="col11">VPSC</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">AAO</oasis:entry>
         <oasis:entry colname="col3">AAO</oasis:entry>
         <oasis:entry colname="col4">AAO</oasis:entry>
         <oasis:entry colname="col5">AAO</oasis:entry>
         <oasis:entry colname="col6">AO/AAO</oasis:entry>
         <oasis:entry colname="col7">AO</oasis:entry>
         <oasis:entry colname="col8">AO</oasis:entry>
         <oasis:entry colname="col9">AO</oasis:entry>
         <oasis:entry colname="col10"/>
         <oasis:entry colname="col11">AO</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S4.SS3.SSS2">
  <title>Quasi-biennial oscillation (QBO)</title>
      <p id="d1e3718">The QBO is one of the main process regulating the dynamics of the tropical
atmosphere <xref ref-type="bibr" rid="bib1.bibx3 bib1.bibx80" id="paren.53"><named-content content-type="pre">e.g.</named-content></xref>. It is driven by vertically
propagating gravity waves, which lead to an oscillation between stratospheric
winds blowing from the east (easterlies) and west (westerlies), occurring over a mean
period of about 28–29 months
<xref ref-type="bibr" rid="bib1.bibx22 bib1.bibx76" id="paren.54"><named-content content-type="pre">e.g.</named-content></xref>.
The effect of the QBO on the distribution of chemical species is significant, especially
in equatorial regions where both a direct effect due to the changing winds
and an indirect effect via its influence on the Brewer–Dobson circulation,
affect, for example, the distribution of ozone
<xref ref-type="bibr" rid="bib1.bibx44 bib1.bibx58 bib1.bibx15 bib1.bibx36" id="paren.55"><named-content content-type="pre">e.g.</named-content></xref>. Two monthly
time series of QBO at two different pressure levels (30 and 10 hPa) from
ground-based measurements in Singapore were considered in the present
study, in order to take the differences in phase and shape of
the QBO signal in the upper and lower stratosphere into account.</p>
</sec>
<sec id="Ch1.S4.SS3.SSS3">
  <title>Multivariate ENSO Index (MEI)</title>
      <p id="d1e3742">The Multivariate ENSO Index is a metric that quantifies the strength of the
El Niño–Southern Oscillation; it is computed based on the measurement of
six variables over the tropical Pacific: sea-level pressure, zonal and
meridional winds, sea surface temperature, surface air temperature, and
cloudiness fraction
<xref ref-type="bibr" rid="bib1.bibx107 bib1.bibx108" id="paren.56"/>. The ENSO phenomenon, even
though it is a tropospheric process (mainly sea surface temperature
contrasts), also affects stratospheric circulation. Previous studies have
shown the impact of El Niño/La Niña oscillation on stratospheric
transport processes and the generation of Rossby waves, which in turn modulate
the strength of the polar vortex
<xref ref-type="bibr" rid="bib1.bibx90 bib1.bibx61 bib1.bibx17" id="paren.57"><named-content content-type="pre">e.g.</named-content></xref> and affect O<inline-formula><mml:math id="M252" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
in the stratosphere <xref ref-type="bibr" rid="bib1.bibx67 bib1.bibx45 bib1.bibx66" id="paren.58"><named-content content-type="pre">e.g.</named-content></xref>.</p>
</sec>
<sec id="Ch1.S4.SS3.SSS4">
  <title>Arctic Oscillation and Antarctic Oscillation</title>
      <?pagebreak page4411?><p id="d1e3774">The AO and AAO are included in the regression in order to represent the
atmospheric variability observed in the Northern and Southern hemispheres,
respectively <xref ref-type="bibr" rid="bib1.bibx19 bib1.bibx37 bib1.bibx88" id="paren.59"/>. They are constructed
from the daily geopotential height anomalies in the 20–90<inline-formula><mml:math id="M253" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> region,
at 1000 mb (for the Northern Hemisphere) and 700 mb (for the Southern
Hemisphere). Each index (AO or
AAO) is considered only in the hemisphere it is related to, while both
indices are included for equatorial latitudes. The impact of these
oscillations on O<inline-formula><mml:math id="M254" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> distributions has been demonstrated in several studies
<xref ref-type="bibr" rid="bib1.bibx68 bib1.bibx102" id="paren.60"><named-content content-type="pre">e.g.</named-content></xref>. We may expect a similar influence on
the HNO<inline-formula><mml:math id="M255" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> distributions, particularly because, even though they are
tropospheric features, their phase and intensity affect the atmospheric
circulation, and in particular the Brewer–Dobson Circulation, up to the
stratosphere <xref ref-type="bibr" rid="bib1.bibx57 bib1.bibx6" id="paren.61"/>.</p>
</sec>
<sec id="Ch1.S4.SS3.SSS5">
  <title>Volume of polar stratospheric clouds (VPSC)</title>
      <p id="d1e3822">The very low temperatures recorded during the winter in the polar
stratosphere inside the vortex lead to the formation of PSCs, which are
composed of nitric acid di- or trihydrates (NAD or NAT), supercooled ternary
HNO<inline-formula><mml:math id="M256" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M257" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> H<inline-formula><mml:math id="M258" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>SO<inline-formula><mml:math id="M259" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M260" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> H<inline-formula><mml:math id="M261" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O solutions (STS) or water ice
(H<inline-formula><mml:math id="M262" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O) <xref ref-type="bibr" rid="bib1.bibx98 bib1.bibx12" id="paren.62"><named-content content-type="pre">e.g.</named-content></xref>. Here, we consider only the NAT
particles (HNO<inline-formula><mml:math id="M263" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M264" display="inline"><mml:mo>⋅</mml:mo></mml:math></inline-formula> (H<inline-formula><mml:math id="M265" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O)<inline-formula><mml:math id="M266" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) for the PSCs, which are
ubiquitous (and often mixed with STS)
<xref ref-type="bibr" rid="bib1.bibx95 bib1.bibx64 bib1.bibx41" id="paren.63"/>. The other forms of PSCs are expected
to influence the variability in gas-phase HNO<inline-formula><mml:math id="M267" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> to a much lesser extent
<xref ref-type="bibr" rid="bib1.bibx96" id="paren.64"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p id="d1e3942">IASI HNO<inline-formula><mml:math id="M268" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns (red dots) for each of the equivalent latitude
bands and the associated fitted model (black curves). The residuals are in
blue, and the horizontal black line represents the zero residual line. For
each equivalent latitude band, the correlation coefficient (<inline-formula><mml:math id="M269" display="inline"><mml:mi>R</mml:mi></mml:math></inline-formula>) between the
observations and the model fit is given in the top left corner, and the root
mean square error (RMSE) in the top right corner. </p></caption>
            <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f06.png"/>

          </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p id="d1e3969">For north <bold>(a, c, e)</bold> and south <bold>(b, d, f)</bold> equivalent
latitude bands 70–90<inline-formula><mml:math id="M270" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>: <bold>(a, b)</bold> total columns (in
10<inline-formula><mml:math id="M271" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M272" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) of IASI observations (red) and the regression
fit without the VPSC proxy (black), for a subset of the time series, zooming
on denitrification periods. The correlation coefficients between the fit and
the IASI data (<inline-formula><mml:math id="M273" display="inline"><mml:mi>R</mml:mi></mml:math></inline-formula>) are displayed, as well as the root mean square error
(RMSE). <bold>(c, d)</bold> Same as top panels but for the fit with the VPSC
proxy. <bold>(e, f)</bold> Normalized VPSC proxy. Note the different time and
value ranges between the two hemispheres. </p></caption>
            <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f07.pdf"/>

          </fig>

      <p id="d1e4032">The proxy we use here for the NAT is the volume of air below <inline-formula><mml:math id="M274" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mtext>NAT</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>
(195 K), which depends on nitric acid concentrations, water vapour and
pressure <xref ref-type="bibr" rid="bib1.bibx20 bib1.bibx105" id="paren.65"/>. The temperatures needed to compute
the quantity are based on ERA-Interim reanalyses, and the HNO<inline-formula><mml:math id="M275" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and
H<inline-formula><mml:math id="M276" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O profiles are taken north and south of 70<inline-formula><mml:math id="M277" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> from an MLS
climatology. The proxy is calculated with a supersaturation of HNO<inline-formula><mml:math id="M278" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> over
NAT of 10, roughly corresponding to 3 K supercooling
<xref ref-type="bibr" rid="bib1.bibx28 bib1.bibx41 bib1.bibx106" id="paren.66"/>. It should be noted that this
proxy was not included in the regression outside of the polar regions. Inside
the polar regions (eqlat bands 70–90 north and south), it was included and
subject to the selection algorithm.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Finally,
for the sake of completeness, proxies accounting for the potential vorticity
(PV) and for the Eliassen–Palm flux (EPflux) were also tested in order to
take more precise patterns of the stratospheric dynamics and the
Brewer–Dobson circulation into account. Various levels for the QBO were also
tested. However, none of these proxies lead to a significant improvement of
the residuals or the correlation coefficients, and their signal is therefore
embedded here in the harmonic terms. For these reasons, they will not be
discussed further.</p>
</sec>
</sec>
<sec id="Ch1.S4.SS4">
  <title>Results</title>
      <p id="d1e4099">The results are presented in two ways: latitudinally averaged time series (eqlat bands) are used to analyse the
performances of the fit in terms of correlation coefficients and residuals,
with a focus on polar regions; the performance of the model is then analysed
in terms of global distributions (with the regression applied to every
<inline-formula><mml:math id="M279" display="inline"><mml:mrow><mml:mn mathvariant="normal">2.5</mml:mn><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup><mml:mo>×</mml:mo><mml:mn mathvariant="normal">2.5</mml:mn><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> grid cell) and the spatial distribution of
the fitted proxies is detailed.</p>
<sec id="Ch1.S4.SS4.SSS1">
  <?xmltex \opttitle{HNO${}_{3}$ fits for equivalent latitude bands}?><title>HNO<inline-formula><mml:math id="M280" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> fits for equivalent latitude bands</title>
      <p id="d1e4137">For each eqlat band, the variables retained by the selection procedure (see
Sect. <xref ref-type="sec" rid="Ch1.S4.SS2"/>) are listed in Table <xref ref-type="table" rid="Ch1.T2"/>. Most variables
are retained everywhere, except for the solar flux which is rejected in the
polar latitudes (70–90<inline-formula><mml:math id="M281" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and S). The QBO30 is also excluded in the
southern polar regions (65–90<inline-formula><mml:math id="M282" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) and the MEI in the northern polar
regions (65–90<inline-formula><mml:math id="M283" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N). Finally, the AO and AAO are excluded in the
65–70<inline-formula><mml:math id="M284" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and in the 70–90<inline-formula><mml:math id="M285" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S bands, respectively.</p>
      <?pagebreak page4412?><p id="d1e4190">The results from the multivariate regression are presented in Fig. <xref ref-type="fig" rid="Ch1.F6"/>
for each band of equivalent latitude. The model reproduces the measurements
well, with correlation coefficients between 0.81 (in the 30–40<inline-formula><mml:math id="M286" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N
eqlat band) and 0.94 (in the 70–90<inline-formula><mml:math id="M287" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat bands). Most major
features (seasonal and interannual variabilities) are reproduced by the
regression model. The residuals range between 1.74 <inline-formula><mml:math id="M288" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M289" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">10</mml:mn></mml:msup></mml:math></inline-formula> and
9.44 <inline-formula><mml:math id="M290" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M291" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M292" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, with better results for the
30<inline-formula><mml:math id="M293" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N–30<inline-formula><mml:math id="M294" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S equivalent latitude band (Root Mean Square
Error (RMSE) of 2.39 <inline-formula><mml:math id="M295" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M296" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">14</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M297" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) and worse fits
for the 65–70<inline-formula><mml:math id="M298" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S band (RMSE of
2.41 <inline-formula><mml:math id="M299" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M300" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M301" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). Following the comparison
between the fits and the observational data, some features can be
highlighted:</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><caption><p id="d1e4344"><bold>(a)</bold> Regression coefficients (<inline-formula><mml:math id="M302" display="inline"><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) and their standard
error (<inline-formula><mml:math id="M303" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="italic">σ</mml:mi><mml:mtext>e</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>, error bars, calculated by Eq. <xref ref-type="disp-formula" rid="Ch1.E3"/>) for the
selected variables in each equivalent latitude band (each data point is
located in the middle of its corresponding eqlat band).
<bold>(b, c)</bold> Fitted signal of the proxies in the eqlat bands 70–90
north <bold>(b)</bold> and south <bold>(c)</bold> for the variables selected. They
are calculated as [<inline-formula><mml:math id="M304" display="inline"><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>i</mml:mi></mml:msub><mml:mo>⋅</mml:mo><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>] with <inline-formula><mml:math id="M305" display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> the normalized
proxy and <inline-formula><mml:math id="M306" display="inline"><mml:mrow><mml:msub><mml:mi>x</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> the regression coefficient calculated by the regression
model. </p></caption>
            <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f08.pdf"/>

          </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9"><caption><p id="d1e4432"><bold>(a)</bold> Fraction (%) of the HNO<inline-formula><mml:math id="M307" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability in the IASI
observations explained by the regression model, and calculated as
<inline-formula><mml:math id="M308" display="inline"><mml:mrow><mml:mfenced close="]" open="["><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mo>(</mml:mo><mml:msubsup><mml:mtext>HNO</mml:mtext><mml:mn mathvariant="normal">3</mml:mn><mml:mtext>fit</mml:mtext></mml:msubsup><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi><mml:mo>(</mml:mo><mml:msubsup><mml:mtext>HNO</mml:mtext><mml:mn mathvariant="normal">3</mml:mn><mml:mtext>IASI</mml:mtext></mml:msubsup><mml:mo>)</mml:mo><mml:mo>×</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:mfenced></mml:mrow></mml:math></inline-formula>. <bold>(b)</bold> Root Mean Square Error (RMSE) calculated for
each grid cell as
<inline-formula><mml:math id="M309" display="inline"><mml:mrow><mml:mfenced open="[" close="]"><mml:msqrt><mml:mstyle displaystyle="false"><mml:mfrac style="text"><mml:mrow><mml:mo>∑</mml:mo><mml:mo>(</mml:mo><mml:mtext>fit</mml:mtext><mml:mo>-</mml:mo><mml:mtext>IASI</mml:mtext><mml:msup><mml:mo>)</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow><mml:mi>n</mml:mi></mml:mfrac></mml:mstyle></mml:msqrt></mml:mfenced></mml:mrow></mml:math></inline-formula> and expressed
in %.</p></caption>
            <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f09.png"/>

          </fig>

      <p id="d1e4523"><list list-type="bullet">
              <list-item>

      <p id="d1e4528">The high daily variability recorded in the data during the winter for both
polar regions is not captured very well by the regression fit. Indeed, we
find that the residuals are largest in this period, especially in the
Southern Hemisphere during the denitrification period of each year (from June
until September approximately), mostly because of the high variability of the
vortex itself. We
find an average standard deviation
of 1.44 <inline-formula><mml:math id="M310" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M311" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M312" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (average of the standard
deviation during the denitrification periods over the 9 years of
observation), as opposed to a mean standard deviation of
8.30 <inline-formula><mml:math id="M313" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M314" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M315" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for the periods between the
denitrification seasons. In the Northern Hemisphere, the day-to-day
variability is largest during winter as well, due to the vortex building up,
and this causes larger residuals for
the corresponding months (see December through March of each year, top left
panel of Fig. <xref ref-type="fig" rid="Ch1.F6"/>, with an average standard deviation of
7.97 <inline-formula><mml:math id="M316" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M317" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M318" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> compared to
7.26 <inline-formula><mml:math id="M319" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M320" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M321" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> for other months). It is
important to stress that these larger residuals are obtained in the polar
regions despite the fact that a VPSC proxy was used. In Fig. <xref ref-type="fig" rid="Ch1.F7"/> we
show, however, that the regression model performs worse in polar regions if
the proxy is neglected, as also discussed below.</p>
              </list-item>
              <list-item>

      <p id="d1e4652">Even though the high variability during the denitrification periods is
not exactly reproduced, the amplitude of the decrease in HNO<inline-formula><mml:math id="M322" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> occurring in
the southern polar<?pagebreak page4413?> region is captured accurately by the regression model.
Figure <xref ref-type="fig" rid="Ch1.F7"/> shows a zoomed in area of Fig. <xref ref-type="fig" rid="Ch1.F6"/> to better
highlight the model performance during the denitrification periods; the
regression was tested without (top panels) and with (middle panels) the VPSC
proxy, for the 70–90<inline-formula><mml:math id="M323" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (left panels) and the 70–90<inline-formula><mml:math id="M324" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S
(right panels) eqlat bands. The steep slope observed at the start of the low
temperatures is captured by the model when the proxy for the VPSC is included
(Fig. <xref ref-type="fig" rid="Ch1.F7"/>) and the correlation coefficients are improved for both
hemispheres (from 0.83 to 0.86 in the 70–90<inline-formula><mml:math id="M325" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and from 0.84 to
0.94 in the 70–90<inline-formula><mml:math id="M326" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band). In the 65–70<inline-formula><mml:math id="M327" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat
band however, as previously described in Sect. <xref ref-type="sec" rid="Ch1.S3"/>, the HNO<inline-formula><mml:math id="M328" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
columns continue to increase after the formation of PSCs has started in the
70–90<inline-formula><mml:math id="M329" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band. This translates to a lag between the
observations in the 65–70<inline-formula><mml:math id="M330" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band and the fit, in which the
drop of HNO<inline-formula><mml:math id="M331" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> concentrations occurs earlier than in the IASI observations.
This is explained by the fact that the VPSC proxy is based on temperatures
and composition
poleward of 70<inline-formula><mml:math id="M332" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>. It induces a lower correlation
coefficient (0.87) and higher RMSE
(2.41 <inline-formula><mml:math id="M333" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M334" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M335" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>). A proxy adapted to this eqlat
band should be used in further studies in order to represent the conditions
in this particular region of the vortex.</p>
              </list-item>
              <list-item>

      <p id="d1e4796">The high maxima seen in the IASI time series, mostly from mid-April through to
the end of May in the Southern Hemisphere, and from mid-December through
early February in the Northern Hemisphere, are not that well reproduced by
the regression model. In fact, the model fails to capture the highest columns
during the winters of each hemisphere. In the same way, a few pronounced lows
recorded by IASI, especially those in the<?pagebreak page4414?> Northern polar regions (mid-June to
early October 2014 and 2016, for instance) are not captured by the model.</p>
              </list-item>
            </list></p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F10" specific-use="star"><caption><p id="d1e4803">Time evolution of IASI HNO<inline-formula><mml:math id="M336" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> (red) and GOME-2 NO<inline-formula><mml:math id="M337" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (green) from
2008 to 2015 for Africa south of the Equator (5–20<inline-formula><mml:math id="M338" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S,
10–40<inline-formula><mml:math id="M339" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E). Both HNO<inline-formula><mml:math id="M340" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and NO<inline-formula><mml:math id="M341" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> columns are expressed in
molec cm<inline-formula><mml:math id="M342" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The NO<inline-formula><mml:math id="M343" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> data are tropospheric columns <xref ref-type="bibr" rid="bib1.bibx92" id="paren.67"/>
and are obtained from <uri>ftp://atmos.caf.dlr.de/</uri>. Note that the ranges
differ between the two <inline-formula><mml:math id="M344" display="inline"><mml:mi>y</mml:mi></mml:math></inline-formula> axes. </p></caption>
            <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f10.pdf"/>

          </fig>

      <?pagebreak page4415?><p id="d1e4901">Figure <xref ref-type="fig" rid="Ch1.F8"/> shows the regression coefficients of each
variable in each equivalent latitude band (top panel). The two bottom panels
show the signal of the fitted proxies, calculated by multiplying the proxy by
its regression coefficient. Only the variables retained by the selection
algorithm are shown and discussed. From Fig. <xref ref-type="fig" rid="Ch1.F8"/>a, it can
be seen that all proxies are significant, with errors smaller than the
coefficients for all eqlat bands. It is clear that annual variability is
predominant at all latitudes. From the two bottom panels, we also see the
large influence of the VPSC in the regression for the polar regions. Their
signal is, as expected, larger in the Southern Hemisphere where it reaches
<inline-formula><mml:math id="M345" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1.3</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M346" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M347" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M348" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>, which can be compared to
maximum values of around <inline-formula><mml:math id="M349" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.4</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M350" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M351" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M352" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> in the
Northern Hemisphere. A noteworthy difference is found for the year 2016 where
the VPSC signal reached <inline-formula><mml:math id="M353" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">0.7</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M354" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M355" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">16</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M356" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> during
the exceptionally cold Arctic winter. While the PSCs have significantly
affected HNO<inline-formula><mml:math id="M357" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> distributions in the winters of 2011, 2014 and 2016 in the
Arctic, their influence during other years may contribute to the high
variability recorded in the observations (see first highlighted feature
above). Other proxies show relatively large signals and their global
distribution will be discussed further in Sect. <xref ref-type="sec" rid="Ch1.S4.SS4.SSS3"/>.<?xmltex \hack{\newpage}?></p>
</sec>
<sec id="Ch1.S4.SS4.SSS2">
  <?xmltex \opttitle{Global model assessment with regard to the HNO${}_{3}$ variability}?><title>Global model assessment with regard to the HNO<inline-formula><mml:math id="M358" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability</title>
      <p id="d1e5052">To assess the model's ability to reproduce the measurements,
Fig. <xref ref-type="fig" rid="Ch1.F9"/>a shows the percentage of the HNO<inline-formula><mml:math id="M359" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability seen
by IASI that is explained by the regression model. The fraction is calculated
as the difference between the standard deviation of the fit and the
observations <inline-formula><mml:math id="M360" display="inline"><mml:mrow><mml:mfenced open="[" close="]"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mo>(</mml:mo><mml:msubsup><mml:mtext>HNO</mml:mtext><mml:mn mathvariant="normal">3</mml:mn><mml:mtext>fit</mml:mtext></mml:msubsup><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mo>)</mml:mo><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi><mml:mo>(</mml:mo><mml:msubsup><mml:mtext>HNO</mml:mtext><mml:mn mathvariant="normal">3</mml:mn><mml:mtext>IASI</mml:mtext></mml:msubsup><mml:mo>(</mml:mo><mml:mi>t</mml:mi><mml:mo>)</mml:mo><mml:mo>)</mml:mo><mml:mo>×</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:mfenced></mml:mrow></mml:math></inline-formula> and is expressed as a
percentage. We find that much of the observed variability can be explained by
the model in the Southern Hemisphere (generally between 50 and 80 %). The
southern mid-latitudes and the polar regions are particularly well modelled
(70–80 %), except in Antarctica above the ice shelves. The Northern
Hemisphere HNO<inline-formula><mml:math id="M361" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability is reasonably well explained by the model,
particularly above 40<inline-formula><mml:math id="M362" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> of latitude, with percentages ranging between
50 and 80 %, although some continental areas (Northern part of inner
Eurasia above Kazakhstan and the West Siberian plains) stand out with
percentages below 40 %. The region with the largest unexplained fraction
of variability is the intertropical band extending as far as 40<inline-formula><mml:math id="M363" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
north. There, the fraction of HNO<inline-formula><mml:math id="M364" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability explained by the model
reaches values as low as 20 %. These regions of low explained variability
coincide quite well with the regions where high lightning activity is found,
which produces large amounts of NO<inline-formula><mml:math id="M365" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> in the troposphere
<xref ref-type="bibr" rid="bib1.bibx40 bib1.bibx75 bib1.bibx8" id="paren.68"/>. While the IASI instrument is
usually not sensitive to tropospheric HNO<inline-formula><mml:math id="M366" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, it was found that large
amounts of tropospheric HNO<inline-formula><mml:math id="M367" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the tropics could be detected. This is
mainly owing to the lower contribution of the stratosphere in this region,
and because the NO<inline-formula><mml:math id="M368" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> produced by lightning is released in the high
troposphere, where IASI has still reasonable sensitivity. This could
consequently explain why the model is missing some of the variability
recorded in the observational data. Another cause for the discrepancies
between the observations and the model could be unaccounted sinks of HNO<inline-formula><mml:math id="M369" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>,
such as deposition in the liquid or solid phase and scavenging by rain. It
should be noted that a small area of high explained variability is observed
in Africa, just south of the Equator. The variability in this region is
unexpectedly high in the IASI time series (Fig. <xref ref-type="fig" rid="Ch1.F10"/>) and we suggest
that it could be influenced by biomass burning emissions of NO<inline-formula><mml:math id="M370" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, and
subsequent oxidation to HNO<inline-formula><mml:math id="M371" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> with a delay of about 2 months
(Fig. <xref ref-type="fig" rid="Ch1.F10"/>) <xref ref-type="bibr" rid="bib1.bibx78 bib1.bibx4 bib1.bibx79" id="paren.69"/>. Indeed, the
large vegetation fires in Africa every year around July emit the largest
amounts of NO<inline-formula><mml:math id="M372" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> (compared to large fires in South America, Australia and
southeast Asia). Their
influence translates to an over-representation of the annual term (up to
<inline-formula><mml:math id="M373" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M374" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M375" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M376" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) in the fitted model (although
not clearly visible in Fig. <xref ref-type="fig" rid="Ch1.F11"/> because of the colour scale
chosen). This larger contribution of the annual variability thus yields a
better agreement between the observations and the model in the tropical band.
However, some of the interannual variability is missing due to the
above-mentioned fires.</p>
      <p id="d1e5281">Fig. <xref ref-type="fig" rid="Ch1.F9"/>b depicts the global distribution
of the RMSE of the regression expressed as a percentage. The errors are small
everywhere (between 10 and 20 %) except in the Southern Hemisphere above
Antarctica, and particularly above the ice shelves (mainly the Ross and Ronne
ice shelves). We also find higher values above large desert areas (the
Sahara, the Arabian, the Turkistan and the Australian deserts) as well as off
the west coasts of South Africa and South America where persistent low clouds
occur. Regions of low clouds or those characterized by emissivity features
that are sharp (e.g. deserts) or seasonally varying (e.g. ice shelves) are
known to cause problems for the retrieval of HNO<inline-formula><mml:math id="M377" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> using the IASI spectra
<xref ref-type="bibr" rid="bib1.bibx29 bib1.bibx70" id="paren.70"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F11" specific-use="star"><caption><p id="d1e5300">Global distributions (<inline-formula><mml:math id="M378" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">2.5</mml:mn><mml:mo>∘</mml:mo></mml:msup><mml:mo>×</mml:mo><mml:msup><mml:mn mathvariant="normal">2.5</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> grid) of the
regression coefficients expressed in 10<inline-formula><mml:math id="M379" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M380" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. The gray
crosses are the cells where the proxy is not significant when accounting for
autocorrelation (see Eq. <xref ref-type="disp-formula" rid="Ch1.E3"/>). The white cells are where the proxy was
not retained and the black cells represent a coefficient of 0. Note the
different scales. The <inline-formula><mml:math id="M381" display="inline"><mml:mi>x</mml:mi></mml:math></inline-formula> axes are latitudes.</p></caption>
            <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/18/4403/2018/acp-18-4403-2018-f11.png"/>

          </fig>

</sec>
<sec id="Ch1.S4.SS4.SSS3">
  <title>Global patterns of fitted parameters</title>
      <?pagebreak page4416?><p id="d1e5363">Figure <xref ref-type="fig" rid="Ch1.F11"/> shows the global distributions of the regression
coefficients obtained after the multivariate regression, expressed in
molec cm<inline-formula><mml:math id="M382" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. All the variables are shown, with the areas where the proxy
was not retained left blank. The contribution of each proxy to the HNO<inline-formula><mml:math id="M383" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
variability was also calculated for each grid cell as <inline-formula><mml:math id="M384" display="inline"><mml:mrow><mml:mfenced open="[" close="]"><mml:mrow><mml:mi mathvariant="italic">σ</mml:mi><mml:mfenced open="(" close=")"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:mfenced><mml:mo>/</mml:mo><mml:mi mathvariant="italic">σ</mml:mi><mml:mfenced open="(" close=")"><mml:mrow><mml:msubsup><mml:mtext>HNO</mml:mtext><mml:mn mathvariant="normal">3</mml:mn><mml:mtext>IASI</mml:mtext></mml:msubsup></mml:mrow></mml:mfenced><mml:mo>×</mml:mo><mml:mn mathvariant="normal">100</mml:mn></mml:mrow></mml:mfenced></mml:mrow></mml:math></inline-formula> with <inline-formula><mml:math id="M385" display="inline"><mml:mrow><mml:msub><mml:mi>X</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> referring to each of the <inline-formula><mml:math id="M386" display="inline"><mml:mi>i</mml:mi></mml:math></inline-formula> explanatory variables
<inline-formula><mml:math id="M387" display="inline"><mml:mi>X</mml:mi></mml:math></inline-formula>, and expressed as a percentage. Note that, although the distributions of the
contribution of each proxy are not shown as a figure, the calculated
percentage values are used in the following discussion (next 3 subsections)
to quantify the influence of the fitted parameters.</p>
</sec>
<sec id="Ch1.S4.SS4.SSSx1" specific-use="unnumbered">
  <title>The annual cycle</title>
      <p id="d1e5456">The annual cycle, represented by the terms <inline-formula><mml:math id="M388" display="inline"><mml:mrow><mml:msub><mml:mi>a</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M389" display="inline"><mml:mrow><mml:msub><mml:mi>b</mml:mi><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, shows
large regression coefficients (Fig. <xref ref-type="fig" rid="Ch1.F11"/>) and holds the
largest part of the variability globally (up to 70 % in the northern and
southern mid to high latitudes), as was previously evidenced in
Fig. <xref ref-type="fig" rid="Ch1.F8"/>a. While the Brewer–Dobson circulation,
which is embedded in these harmonic terms, influences the
HNO<inline-formula><mml:math id="M390" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability to some extent (through its influence on the conversion of N<inline-formula><mml:math id="M391" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O to
NO<inline-formula><mml:math id="M392" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> in the tropics and through the transport of NO<inline-formula><mml:math id="M393" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula>-rich air masses
towards the polar regions and subsequent transformation into HNO<inline-formula><mml:math id="M394" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>), the
impact of the seasonality of the solar insolation is also likely to
largely influence the annual seasonality, especially in the mid- to high
latitudes. The increasing columns recorded during the winter in both polar
regions can be explained by the combination of three processes: first, at low
temperatures, HNO<inline-formula><mml:math id="M395" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> is formed by heterogeneous reactions between N<inline-formula><mml:math id="M396" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O<inline-formula><mml:math id="M397" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">5</mml:mn></mml:msub></mml:math></inline-formula>
and H<inline-formula><mml:math id="M398" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O<inline-formula><mml:math id="M399" display="inline"><mml:msub><mml:mi/><mml:mtext>aerosol</mml:mtext></mml:msub></mml:math></inline-formula> and between ClONO<inline-formula><mml:math id="M400" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> and H<inline-formula><mml:math id="M401" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>O<inline-formula><mml:math id="M402" display="inline"><mml:msub><mml:mi/><mml:mtext>aerosol</mml:mtext></mml:msub></mml:math></inline-formula>
or HCl<inline-formula><mml:math id="M403" display="inline"><mml:msub><mml:mi/><mml:mtext>aerosol</mml:mtext></mml:msub></mml:math></inline-formula>, which add to the main source gas-phase reaction
OH <inline-formula><mml:math id="M404" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> NO<inline-formula><mml:math id="M405" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> <inline-formula><mml:math id="M406" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> M <inline-formula><mml:math id="M407" display="inline"><mml:mo>→</mml:mo></mml:math></inline-formula> HNO<inline-formula><mml:math id="M408" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>; second, while the source
reactions of HNO<inline-formula><mml:math id="M409" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> are still active, the loss reactions (HNO<inline-formula><mml:math id="M410" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> photolysis
and its reaction with OH) are significantly slowed down during the winter
<xref ref-type="bibr" rid="bib1.bibx1 bib1.bibx56 bib1.bibx73" id="paren.71"/>; and third, as is mentioned in
Sect. <xref ref-type="sec" rid="Ch1.S3"/>, with the decrease of temperatures in the polar
stratosphere, the winds inside the polar vortex gain intensity and induce a
strong diabatic downward motion of air with little latitudinal mixing across
the vortex boundary. This descending air from the upper stratosphere enriches
the lower stratosphere in HNO<inline-formula><mml:math id="M411" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
<xref ref-type="bibr" rid="bib1.bibx77 bib1.bibx50 bib1.bibx72" id="paren.72"/>.</p>
</sec>
<?pagebreak page4417?><sec id="Ch1.S4.SS4.SSSx2" specific-use="unnumbered">
  <title>The solar cycle, MEI, AO/AAO and QBO</title>
      <p id="d1e5695">The solar flux, ENSO index and Arctic and Antarctic Oscillation
(Fig. <xref ref-type="fig" rid="Ch1.F11"/>) all have a similar influence in terms of magnitude
(between <inline-formula><mml:math id="M412" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2.5</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M413" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M414" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> and
2.5 <inline-formula><mml:math id="M415" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M416" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M417" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>), although with different spatial
patterns. The influence of the solar flux is positive in the northern polar
latitudes and in the tropical and southern mid-latitudes. It is close to zero
or negative elsewhere. While previous studies showed a positive signal
globally in the low stratosphere for the response of O<inline-formula><mml:math id="M418" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> to the solar cycle
<xref ref-type="bibr" rid="bib1.bibx25 bib1.bibx83" id="paren.73"/>, our results for the mid to high northern
latitudes suggest opposite behaviour (negative signal) for HNO<inline-formula><mml:math id="M419" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>. However,
the positive contribution of the solar cycle on the HNO<inline-formula><mml:math id="M420" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variation in the
tropical and southern mid-latitude stratosphere is in line with the O<inline-formula><mml:math id="M421" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
response previously reported
<xref ref-type="bibr" rid="bib1.bibx83 bib1.bibx55 bib1.bibx15 bib1.bibx54" id="paren.74"/>. Note also that
the strong negative signal observed above the ice shelves of western
Antarctica is most probably due to the drawback of using a
constant emissivity for ocean surfaces for all seasons (e.g. even when the ocean becomes
frozen). For this reason, the regression coefficients in this area will not
be discussed further.</p>
      <p id="d1e5798">The MEI shows a negative signal above the northern polar regions and in the
eastern parts of the Pacific and Atlantic oceans (especially west of South Africa). A positive signal is observed above Australia and above the southern
polar regions. Overall, the MEI influence is quite small, which is not
surprising considering that it affects mostly the tropospheric circulation,
where IASI is less sensitive. Its signature is nonetheless visible and
significant in the eastern Pacific, where it contributes to up to <inline-formula><mml:math id="M422" display="inline"><mml:mrow><mml:mn mathvariant="normal">30</mml:mn><mml:mi mathvariant="italic">%</mml:mi></mml:mrow></mml:math></inline-formula> of
the HNO<inline-formula><mml:math id="M423" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability, and in the mid-latitudes of the Northern Hemisphere.
The east–west gradient is in good agreement with chemical and dynamical
effects of El Niño on O<inline-formula><mml:math id="M424" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, and with previous studies that showed the same
patterns for the influence of the MEI on O<inline-formula><mml:math id="M425" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>
<xref ref-type="bibr" rid="bib1.bibx27 bib1.bibx68 bib1.bibx103" id="paren.75"/>.</p>
      <p id="d1e5841">The Arctic Oscillation (AO) signal is stronger, especially above the Atlantic
Ocean, with a positive signal above eastern Canada and Greenland and between
the north of eastern Africa and Florida. Except for those two regions, the AO
contributes at mid to high latitudes of the Northern Hemisphere with a
negative signal, which contributes 10–20 % to the HNO<inline-formula><mml:math id="M426" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability.
The corresponding proxy for the Southern Hemisphere (AAO) is also
significant, with a strong positive signal above the vortex rim and a
negative signal above Antarctica. These results are in agreement with
previous studies that showed that, for O<inline-formula><mml:math id="M427" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>, both the Arctic and Antarctic
oscillations (also called “annular modes”) are leading modes of variation
in the extratropical atmosphere
<xref ref-type="bibr" rid="bib1.bibx100 bib1.bibx15 bib1.bibx11 bib1.bibx103" id="paren.76"/>. Both the AO and the AAO
strongly influence the circulation up to the lower stratosphere and
represent, particularly in the Southern Hemisphere, fluctuations in the
strength of the polar vortex
<xref ref-type="bibr" rid="bib1.bibx88 bib1.bibx31 bib1.bibx94" id="paren.77"/>. This further shows the similarity in
the behaviour of O<inline-formula><mml:math id="M428" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> and HNO<inline-formula><mml:math id="M429" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>.</p>
      <p id="d1e5887">The QBO has a generally small influence on the distributions with, however,
some contribution (up to 30 %) in the equatorial band as expected
<xref ref-type="bibr" rid="bib1.bibx3 bib1.bibx81" id="paren.78"/>. As previously mentioned, several tests were performed (not shown here) with the QBO taken at other atmospheric pressure levels
(namely 20 and 50 hPa), and similar results were
obtained. Even though the QBO is a tropical phenomenon, its effects extend as
far as the polar latitudes, through the modulation of the planetary Rossby
waves <xref ref-type="bibr" rid="bib1.bibx24 bib1.bibx3" id="paren.79"><named-content content-type="pre">e.g.</named-content></xref>. Because there are more
topographical features in the Northern Hemisphere than in the Southern
Hemisphere, these waves have a larger amplitude and can influence the Arctic
stratospheric temperatures and hence the vortex formation. While the exact
mechanism for the extratropical influence of the QBO is not exactly
understood <xref ref-type="bibr" rid="bib1.bibx16 bib1.bibx81" id="paren.80"/>, it seems the large positive and
negative signals observed in the northern high latitudes in
Fig. <xref ref-type="fig" rid="Ch1.F11"/> can indeed be attributed to the modulation of the
Rossby waves by the oscillation in the meridional circulation. This was also
observed for O<inline-formula><mml:math id="M430" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in studies such as <xref ref-type="bibr" rid="bib1.bibx103" id="text.81"/>.</p>
</sec>
<sec id="Ch1.S4.SS4.SSSx3" specific-use="unnumbered">
  <title>VPSC</title>
      <p id="d1e5922">The annual cycle, which is the dominant factor for HNO<inline-formula><mml:math id="M431" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability at all
latitudes, leading to the build-up of concentrations during the winter, is
interrupted in the southern polar regions, particularly in the
70–90<inline-formula><mml:math id="M432" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S eqlat band (see also Fig. <xref ref-type="fig" rid="Ch1.F8"/>), by the
condensation and subsequent sedimentation of PSCs. The VPSC proxy, reflecting
the volume of air below <inline-formula><mml:math id="M433" display="inline"><mml:mrow><mml:msub><mml:mi>T</mml:mi><mml:mtext>NAT</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>, has a strong inverse correlation with
HNO<inline-formula><mml:math id="M434" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns, which decrease (negative values) with increasing VPSC
<xref ref-type="bibr" rid="bib1.bibx98 bib1.bibx46 bib1.bibx34" id="paren.82"><named-content content-type="pre">e.g.</named-content></xref>. The signal of the VPSC proxy is thus,
as expected, negative everywhere (in the polar regions considered), with
values around <inline-formula><mml:math id="M435" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">6</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M436" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10<inline-formula><mml:math id="M437" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">15</mml:mn></mml:msup></mml:math></inline-formula> molec cm<inline-formula><mml:math id="M438" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>. When looking at
their contribution, we find that the PSCs account for a larger part of the
HNO<inline-formula><mml:math id="M439" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability (40–60 %) in the Southern Hemisphere, where the
influence of denitrification is indeed expected to be more important,
compared to the Northern Hemisphere (maxima of 40 %), as discussed in
Sect. <xref ref-type="sec" rid="Ch1.S3"/> with the analysis of Fig. <xref ref-type="fig" rid="Ch1.F2"/>. The small
areas with a positive signal appear to be non significant (see grey crosses).</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusions</title>
      <p id="d1e6032">Time series of HNO<inline-formula><mml:math id="M440" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns retrieved from IASI/Metop between 2008
and 2016 have been presented and analysed in terms of seasonal cycle and
global variability. The analysis was conducted in terms of<?pagebreak page4418?> equivalent
latitudes (here calculated on the basis of potential vorticity) and focused
mainly on high latitude regions. We have shown that the IASI instrument
captures the broad patterns of the seasonal cycles at all latitudes but also
year-to-year specific behaviours. The systematic denitrification process
occurring every winter–spring in the Southern Hemisphere shows up
unambiguously in the time evolutions and the use of equivalent latitudes
enables one to isolate the regions affected based on the dominating stratospheric
dynamical regimes. Three distinct zones within the polar regions were separated in
particular: (1) the inner polar region (70–90<inline-formula><mml:math id="M441" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S), where
the denitrification starts earliest and where the HNO<inline-formula><mml:math id="M442" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns reach
their lowest values for the longest period; (2) the outer part of the polar
vortex (65–70<inline-formula><mml:math id="M443" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S), where the HNO<inline-formula><mml:math id="M444" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> columns drop occurs 1 month
later and the minimum concentrations do not reach such low levels; (3) the
polar vortex edges (55–65<inline-formula><mml:math id="M445" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S), where the columns follow a more
normal annual cycle, with maxima around July, forming a collar of high
columns around the denitrified vortex. The IASI-derived HNO<inline-formula><mml:math id="M446" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> distributions
also reflect the denitrification periods in the Northern Hemisphere, during
the exceptionally cold winters of 2011, 2014 and 2016.</p>
      <p id="d1e6099">The HNO<inline-formula><mml:math id="M447" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> time series were successfully fitted with multivariate
regressions in order to identify the various factors responsible for the
variability in the observations. To the best of our knowledge, this is the
first time that such regression models have been applied to HNO<inline-formula><mml:math id="M448" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> time
evolution. A specific set of explanatory variables was retained for each
equivalent latitude band following an iterative procedure, according to the
influence of each of these variables in the regression. The regression model
allowed good representation of the IASI observations in most cases
(correlation coefficients between 0.81 and 0.94). However, the variability
recorded in the tropics could not be reproduced that well, with only about 20
to 40 % correctly accounted for. The regression for other parts of the
globe yielded better results, especially in the southern polar regions, where
a high percentage (60–80 %) of the observed variability is reproduced by
the regression. Generally, it was found that the annual cycle is the factor
responsible for the largest part of the variability, showing a hemispheric
pattern. The Brewer–Dobson circulation, and also the solar insolation
seasonality, which are embedded in the harmonic terms, seem to be the main
drivers of variability; the
Brewer–Dobson circulation carries NO<inline-formula><mml:math id="M449" display="inline"><mml:msub><mml:mi/><mml:mi>y</mml:mi></mml:msub></mml:math></inline-formula> towards the poles and both
processes bring HNO<inline-formula><mml:math id="M450" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> concentrations to their maxima during the local
winter when production is enhanced and destruction inhibited. We also
interestingly show that polar stratospheric clouds are the second most
important driver of the variability of HNO<inline-formula><mml:math id="M451" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> in the southern polar
latitudes (65–90<inline-formula><mml:math id="M452" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S). The influence of PSCs is, as expected, less
marked in the Northern Hemisphere, but accounting for PSCs still
significantly improves the model-to-observation agreement especially during
the colder northern winters (<inline-formula><mml:math id="M453" display="inline"><mml:mi>R</mml:mi></mml:math></inline-formula> from 0.83 to 0.86). While we feel that the
VPSC proxy used here for the PSCs (including only the NAT) is generally good,
it is not excluded that adding other forms of PSCs would further improve the
model. In any case, the present work shows the potential of using IASI
measurements to study the polar denitrification processes in depth.</p>
      <p id="d1e6164">In the mid- and tropical latitudes, the annual cycle is still
prominent, but the relative influence of the QBO increases. Most of the weak
seasonality revealed by IASI in the tropical regions is explained by the
annual cycle (as well as a potential contribution of African fires and
lightning as additional NO<inline-formula><mml:math id="M454" display="inline"><mml:msub><mml:mi/><mml:mi>x</mml:mi></mml:msub></mml:math></inline-formula> sources), the QBO and the MEI.</p>
      <p id="d1e6176">More generally, this study shows that the IASI data allow a good analysis and
understanding of the HNO<inline-formula><mml:math id="M455" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability in the atmosphere. The measurements
are made with exceptional spatial and temporal sampling, which allows a
detailed analysis of the polar regions throughout the entire year. The amount
of data allows for a thorough monitoring of the processes regulating the
HNO<inline-formula><mml:math id="M456" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> variability, such as denitrification processes in the southern
polar regions, or seasonal variability in tropical regions. The IASI
HNO<inline-formula><mml:math id="M457" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> time series will soon be extended with the launch of Metop C in
September 2018, which should further improve the regression model. As shown
here by the still significant residuals at some periods and locations, other
factors could also probably be included to acquire a full and coherent
representation of the HNO<inline-formula><mml:math id="M458" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> total columns variability.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability">

      <p id="d1e6219">The IASI L2 data are available upon request to the
corresponding author.</p>
  </notes><notes notes-type="competinginterests">

      <p id="d1e6225">The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e6231">IASI was developed and built under the responsibility of the “Centre
National d'Etudes Spatiales” (CNES, France). It is flown on board the Metop
satellites as part of the EUMETSAT Polar System. The research was funded by
the F.R.S.-FNRS, the Belgian State Federal Office for Scientific, Technical
and Cultural Affairs (Prodex arrangement 4000111403 IASI.FLOW) and EUMETSAT
through the Satellite Application Facility on Atmospheric Composition
Monitoring (ACSAF). The authors would like to thank Ingo Wohltmann for the
VPSC proxy and for useful discussions. Gaétane Ronsmans is grateful to
the “Fonds pour la Formation à la Recherche dans l'Industrie et dans
l'Agriculture” of Belgium for a PhD grant (Boursier FRIA). Cathy Clerbaux is
grateful to CNES for financial support.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited
by: Jianzhong Ma<?xmltex \hack{\newline}?> Reviewed by: Michelle Santee and one
anonymous referee</p></ack><ref-list>
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<abstract-html><p>This study aims to understand the spatial and temporal variability of
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