<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing with OASIS Tables v3.0 20080202//EN" "journalpub-oasis3.dtd">
<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" dtd-version="3.0">
  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">ESD</journal-id>
<journal-title-group>
<journal-title>Earth System Dynamics</journal-title>
<abbrev-journal-title abbrev-type="publisher">ESD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Dynam.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2190-4987</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/esd-7-371-2016</article-id><title-group><article-title>Atmospheric rivers moisture sources from a Lagrangian perspective</article-title>
      </title-group><?xmltex \runningtitle{Atmospheric rivers moisture sources from a Lagrangian perspective}?><?xmltex \runningauthor{A.~M.~Ramos et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Ramos</surname><given-names>Alexandre M.</given-names></name>
          <email>amramos@fc.ul.pt</email>
        <ext-link>https://orcid.org/0000-0003-3129-7233</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Nieto</surname><given-names>Raquel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Tomé</surname><given-names>Ricardo</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Gimeno</surname><given-names>Luis</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Trigo</surname><given-names>Ricardo M.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4183-9852</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff3">
          <name><surname>Liberato</surname><given-names>Margarida L. R.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-6677-9366</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Lavers</surname><given-names>David A.</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Lisbon, Portugal</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>EPhysLab (Environmental Physics Laboratory), Facultade de Ciencias, Universidade de Vigo, Ourense, Spain</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Escola de Ciências e Tecnologia, Universidade de Trás-os-Montes e Alto Douro, Vila Real, Portugal</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Alexandre M. Ramos (amramos@fc.ul.pt)</corresp></author-notes><pub-date><day>22</day><month>April</month><year>2016</year></pub-date>
      
      <volume>7</volume>
      <issue>2</issue>
      <fpage>371</fpage><lpage>384</lpage>
      <history>
        <date date-type="received"><day>2</day><month>December</month><year>2015</year></date>
           <date date-type="rev-request"><day>17</day><month>December</month><year>2015</year></date>
           <date date-type="rev-recd"><day>17</day><month>March</month><year>2016</year></date>
           <date date-type="accepted"><day>12</day><month>April</month><year>2016</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://esd.copernicus.org/articles/.html">This article is available from https://esd.copernicus.org/articles/.html</self-uri>
<self-uri xlink:href="https://esd.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://esd.copernicus.org/articles/.pdf</self-uri>


      <abstract>
    <p>An automated atmospheric river (AR) detection algorithm is used for the
North Atlantic Ocean basin, allowing the identification of the major ARs
affecting western European coasts between 1979 and 2012 over the winter
half-year (October to March). The entire western coast of Europe was divided
into five domains, namely the Iberian Peninsula (9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W,
36–43.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N), France (4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 43.75–50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N),
UK (4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N), southern Scandinavia and the Netherlands
(5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N), and northern Scandinavia (5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 59–70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N).
Following the identification of the main ARs that made landfall in western
Europe, a Lagrangian analysis was then applied in order to identify the main
areas where the moisture uptake was anomalous and contributed to the ARs
reaching each domain. The Lagrangian data set used was obtained from the
FLEXPART (FLEXible PARTicle dispersion) model global simulation from 1979 to 2012 and was forced by
ERA-Interim reanalysis on a 1<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitude–longitude grid.</p>
    <p>The results show that, in general, for all regions considered, the major
climatological areas for the anomalous moisture uptake extend along the
subtropical North Atlantic, from the Florida Peninsula (northward of
20<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) to each sink region, with the nearest coast to each
sink region always appearing as a local maximum. In addition, during AR
events the Atlantic subtropical source is reinforced and displaced, with a
slight northward movement of the sources found when the sink region is
positioned at higher latitudes. In conclusion, the results confirm not only the
anomalous advection of moisture linked to ARs from subtropical ocean areas
but also the existence of a tropical source, together with midlatitude
anomaly sources at some locations closer to AR landfalls.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Atmospheric rivers (ARs) are relatively narrow (on average
<inline-formula><mml:math display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 500 km) pathways of water vapour (WV) transport that can extend for
thousands of kilometres, contain large amounts of WV, and are often
accompanied by strong winds (Zhu and Newell, 1998; Ralph et al., 2004).
According to several authors (Ralph et al., 2004, 2005), their properties
include a concentrated band of enhanced WV in the lower troposphere and a
pre-cold frontal low-level jet (LLJ) due to the temperature gradient across
the cold front (Neiman et al., 2008; Ralph et al., 2004, 2005).</p>
      <p>The attribution of the terms “atmospheric river” or “tropospheric river” and
their genesis has caused some debate in the scientific community. Recently, some
agreement has been achieved (Dettinger et al., 2015) regarding the
relationships between ARs, warm conveyor belts (WCBs), and tropical moisture
exports (TMEs). The term WCB refers to the zone of dynamically uplifted heat
and vapour transport close to a midlatitude cyclone. This vapour is often
transported to the WCB by an AR, and the result of the uplift is heavy
rainfall that generally marks the downwind end of an AR, provided that the
AR has not experienced orographic uplift (upslope flow), accompanied by
rainout over mountains earlier on its approach to the WCB. TMEs are zones of
intense vapour transport out of the tropics, vapour that is frequently
conducted by ARs towards cyclones and WCBs. TMEs can provide important
vapour sources for ARs, but most ARs also incorporate midlatitude sources
and convergences of vapour along their paths (Dettinger et al., 2015;
Sodemann and Stohl, 2013). In addition, the role of ARs in explosive
cyclogenesis over the North Atlantic Ocean has been shown for three
extra-tropical cyclones (Klaus, Gong, and Stephanie), all of which had major
socio-economic impacts in parts of Europe (Ferreira et al., 2016).</p>
      <p>The importance of ARs in extreme precipitation events and floods has been
analysed in detail for the west coast of the USA (particularly for
California) over the last decade (e.g. Dettinger et al., 2011; Neiman et
al., 2008; Ralph et al., 2004, 2013).</p>
      <p>For Europe, Lavers and Villarini (2013) showed that ARs are responsible for
many annual maximum precipitation days in western Europe, with the
relationship being stronger along the western European seaboard, and with
some areas having up to 8 of their top-10 annual maxima related to ARs.
It was also shown that 40–80 % of winter floods in the UK are associated
with persistent ARs and that these ARs are critical in explaining the
10 largest winter flood events in a range of British rivers basins since
1970 (Lavers et al., 2011, 2012). For the Iberian Peninsula,
Ramos et al. (2015) showed that ARs play an overwhelming role in most
extreme precipitation days, decreasing in importance for less extreme
precipitation days. Moreover, over the North Atlantic Ocean and for the
island of Madeira, in particular, the association between extreme
precipitation and ARs has also been established (Couto et al., 2012, 2015).</p>
      <p>In addition, the importance of ARs in a few particular cases of extreme
precipitation in Europe has also been analysed in some detail. Liberato et
al. (2012) discussed an extreme precipitation event associated with an AR
occurring in the city of Lisbon, Portugal, in November 1983, which produced
flash flooding, urban inundations, and landslides, causing considerable
damage to infrastructure and human fatalities. On the Norwegian southwest
coast, an extreme precipitation event occurred in September 2005 and was
also shown to be directly linked with an AR (Stohl et al., 2008). More
recently, Trigo et al. (2014) considered the record precipitation and flood
event in the Iberia Peninsula of December 1876 and highlighted the
importance of ARs in this historical event.</p>
      <p>The association between ARs and modes of low-frequency variability has
already been addressed, with the Scandinavian pattern having a negative
correlation with the occurrence of ARs in Britain (Lavers et al., 2012),
while it is the North Atlantic Oscillation that controls their occurrence to
a certain extent in the rest of Europe (Lavers and Villarini, 2013). In
addition, Ramos et al. (2015) showed that for the particular case of the
Iberian Peninsula the Eastern Atlantic pattern also plays a major role in
explaining the annual variability of ARs.</p>
      <p>The increasing attention to the topic of ARs is confirmed by the publication
of two recent reviews, with Ralph and Dettinger (2011) emphasizing the
multiple studies of ARs striking the western coast of the USA, while Gimeno
et al. (2014) focused on the structure, methods of detection, impacts, and
dynamics of ARs.</p>
      <p>Bao et al. (2006) suggested that the moisture present in ARs has two main
origins, namely local moisture convergence along the front of extra-tropical
cyclones and direct poleward transport of tropical moisture, suggesting
that they play an important role in the water cycle, especially in
transporting moisture from the tropics to the mid- and high latitudes. In
this context Dacre et al. (2015) analysed selected cases of the transport of
water vapour within a climatology of wintertime North Atlantic
extra-tropical cyclone. In this particular study, the possibility was
discussed that ARs are formed by the cold front that sweeps up water vapour
in the warm sector as it catches up with the warm front. This causes a
narrow band of high water vapour content to form ahead of the cold front at
the base of the warm conveyor belt airflow. Thus, according to Dacre et al. (2015),
water vapour in the warm sector of the cyclone, rather than
long-distance transport of water vapour from the subtropics, is responsible
for the generation of ARs. According to Dettinger et al. (2015) it seems
that a combination of the two points of view are valid because TMEs can
provide important vapour sources for ARs, but most ARs also incorporate
midlatitude sources and convergences of vapour along their paths.</p>
      <p>To the best of our knowledge studies dealing with moisture sources from a
Lagrangian point of view along the paths of ARs are scarce and have only
been developed for selected case studies. For instance, Moore et al. (2012)
used Lagrangian trajectories associated with heavy flooding rainfall in
Nashville (USA) to analyse whether these were connected with AR events,
while Ryoo et at. (2015) analysed the transport pathways of water vapour
associated with AR events that made landfall along the west coast of the USA
between 1997 and 2010. In addition, Rutz et al. (2015) analysed the
evolution of ARs over western North America using trajectories released at
950 and 700 hPa within ARs along the Pacific coast. In this case a forward
mode was used to study the inland penetration of ARs.</p>
      <p>For Europe, Stohl et al. (2008) investigated the remote sources of water
vapour forming precipitation in Norway and their link with ARs over a 5-year
period. Liberato et al. (2012) showed that the evaporative sources for
precipitation falling over the Lisbon area, in Portugal, on the heaviest
precipitation event occurring there during the twentieth century were
distributed over large sectors of the tropical–subtropical North Atlantic
Ocean and included a significant contribution from the (sub)tropics.
Moreover, Sodemann and Stohl (2013) analysed the origins of moisture and
meridional transport in ARs and their association with multiple cyclones in
December 2006. Finally, Knippertz and Wernli (2010) presented a Lagrangian
climatology of tropical moisture exports to the northern hemispheric
extra-tropics by analysing forward trajectories leaving a box between
0 and 20<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N for 1979–2001.</p>
      <p>These researchers based their results on the use of Lagrangian models, which
allow studying the evolution of moisture in the atmosphere along a number of
trajectories. The use of Lagrangian models such as FLEXPART (FLEXible PARTicle dispersion model; Stohl et al.,
1998) can help us to assess the main sources of moisture and its transport
within ARs. This Lagrangian model allows us to follow the moisture that
reaches a specific region, more specifically making it possible to track
changes in the specific humidity along the trajectories over time. By
knowing the specific humidity (<inline-formula><mml:math display="inline"><mml:mi>q</mml:mi></mml:math></inline-formula>) at every time step, it is possible to identify
those particles that lose moisture through precipitation (<inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>) or receive it
through evaporation (<inline-formula><mml:math display="inline"><mml:mi>e</mml:mi></mml:math></inline-formula>). FLEXPART can “transport” these particles
backwards or forwards in time using a 3-D wind field. The record of
evaporation minus precipitation (<inline-formula><mml:math display="inline"><mml:mi>e</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>) provides information on the sources
(when evaporation exceeds precipitation) and sinks (when precipitation
exceeds evaporation) of moisture.</p>
      <p>The Lagrangian methodology of identifying moisture sources based on FLEXPART
has been extensively used over the past decade both for regional
(e.g. Nieto et al., 2007) and global studies (Gimeno et al., 2010a). The
comprehensive review by Gimeno et al. (2012) provides details of the
uncertainty and significance of this Lagrangian approach, as well as a
comparison with other methods of estimating moisture sources, and the
original paper by Stohl and James (2004) provides further information on the
FLEXPART model. Here we are mainly interested in analysing the backward
trajectories that arrive in the various regions along the Atlantic coast of
Europe where ARs make landfall. The objectives of this work are (1) to
identify the ARs affecting the western European coast between 1979 and 2012
during the winter half-year (ONDJFM) and (2) to provide a comprehensive
analysis of the areas where the AR moisture uptake is anomalous over the
same period for the ARs that reach the different European domains. The added
value of the manuscript is mainly twofold: (a) firstly the current study is
the first to analyse those areas where the moisture uptake is anomalous for
the ARs that reach the European coast from a climatological perspective;
(b) secondly we have made refinements to the AR tracking method introduced by
Lavers et al. (2012). In the present version, we use three reference meridians
rather than a single fixed one for the whole of western Europe to have a
higher accuracy on landfall times and locations (see Sect. 2.1). This is of
the utmost importance for analysing the anomaly for the moisture uptake for
the ARs based on the use of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>), because just a few degrees of difference
in the reference meridian longitude may translate into an erroneous
detection for any anomalous moisture sources.</p>
      <p>The work is organized as follows: we present the data sets and the different
methodologies in Sect. 2, while in Sect. 3 we analyse ARs that reach landfall
in Europe. The detection of those areas where the moisture uptake is
anomalous for ARs that reach Europe is analysed in Sect. 4. Finally, our
conclusions are presented in Sect. 5.</p>
</sec>
<sec id="Ch1.S2">
  <title>Methods and data sets</title>
<sec id="Ch1.S2.SS1">
  <title>Atmospheric river detection</title>
      <p>The detection of ARs can be achieved by adopting two very different
approaches, namely (a) using integrated column water vapour (IWV)
(e.g. Ralph et al., 2004; Ralph and Dettinger, 2011) and (b) based on vertically
integrated horizontal water vapour transport (IVT) (e.g. Zhu and Newell,
1998; Lavers et al., 2012; Ramos et al., 2015). The choice of either of
these two approaches is perfectly valid and will depend on the purpose and
location of the study.</p>
      <p>In this case we have used the ERA-Interim reanalysis (Dee et al., 2011) with
a 0.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitude–longitude grid resolution, spanning from
1979 to 2012 for the winter half-year (October to March, ONDJFM) for the
detection of ARs. The variables used at 6 h time steps were the specific
humidity, as well as zonal and meridional winds at the 1000, 925, 850, 700,
600, 500, 400, and 300 hPa levels, given that most of the moisture transport
is accounted for in these levels.</p>
      <p>The AR detection scheme employed (Lavers et al., 2012; Ramos et al., 2015)
depends entirely on the IVT and was computed between the 1000 and the 300 hPa levels (Eq. 1):

                <disp-formula id="Ch1.E1" content-type="numbered"><mml:math display="block"><mml:mrow><mml:mtext>IVT</mml:mtext><mml:mo>=</mml:mo><mml:msqrt><mml:mrow><mml:msup><mml:mfenced close=")" open="("><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mn mathvariant="normal">1</mml:mn><mml:mi>g</mml:mi></mml:mfrac></mml:mstyle><mml:munderover><mml:mo movablelimits="false">∫</mml:mo><mml:mrow><mml:mn>1000</mml:mn><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mtext>hPa</mml:mtext></mml:mrow><mml:mrow><mml:mn>300</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mtext>hPa</mml:mtext></mml:mrow></mml:munderover><mml:mi>q</mml:mi><mml:mi>u</mml:mi><mml:mi>d</mml:mi><mml:mi>p</mml:mi></mml:mfenced><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>+</mml:mo><mml:msup><mml:mfenced open="(" close=")"><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mn mathvariant="normal">1</mml:mn><mml:mi>g</mml:mi></mml:mfrac></mml:mstyle><mml:munderover><mml:mo movablelimits="false">∫</mml:mo><mml:mrow><mml:mn>1000</mml:mn><mml:mspace linebreak="nobreak" width="0.125em"/><mml:mtext>hPa</mml:mtext></mml:mrow><mml:mrow><mml:mn>300</mml:mn><mml:mspace width="0.125em" linebreak="nobreak"/><mml:mtext>hPa</mml:mtext></mml:mrow></mml:munderover><mml:mi>q</mml:mi><mml:mi>v</mml:mi><mml:mi>d</mml:mi><mml:mi>p</mml:mi></mml:mfenced><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:msqrt><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>

          where <inline-formula><mml:math display="inline"><mml:mi>q</mml:mi></mml:math></inline-formula> is the specific humidity, <inline-formula><mml:math display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> and <inline-formula><mml:math display="inline"><mml:mi>v</mml:mi></mml:math></inline-formula> are the zonal and meridional layer
averaged wind respectively, and <italic>dp</italic> is the pressure difference between two
adjacent levels. <inline-formula><mml:math display="inline"><mml:mi>g</mml:mi></mml:math></inline-formula> denotes the acceleration due to gravity.</p>
      <p>The identification of ARs is similar to that performed by Lavers and
Villarini (2013) for Europe and Ramos et al. (2015) for the Iberian
Peninsula, and it considers only one reference meridian for the computation of
the ARs. In this case we have used three distinct reference meridians
(Fig. 1) located at 9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W (meridian 1, just west of both the
Iberian Peninsula and Ireland), 4.50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W (meridian 2, located
west of the UK and France), and 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (meridian 3, west of
Scandinavia). Each different reference meridian (Fig. 1) was further divided
into 10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitudinal sections between 35 and 75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N for the 9.75 and
4.50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W reference meridians, and between 50 and 70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N for the 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E reference
meridian, to allow for differences in IVT depending on latitude.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><caption><p><bold>(a)</bold> Location of the three different reference meridians and sectors
in Europe used for the computation of the atmospheric rivers. <bold>(b)</bold> The
newly defined atmospheric river landfall domains: Iberian Peninsula (red), France
(blue), UK (green), southern Scandinavia and the Netherlands (yellow), and
northern Scandinavia (purple).</p></caption>
          <?xmltex \igopts{width=170.716535pt}?><graphic xlink:href="https://esd.copernicus.org/articles/7/371/2016/esd-7-371-2016-f01.png"/>

        </fig>

      <p><?xmltex \hack{\newpage}?>The value for the highest IVT and its respective latitude (IVT threshold)
for each meridian was computed as follows: we extracted the maximum IVT at
12:00 UTC each day for the entire period between 35 and
75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (for the 9.75 and 4.50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W meridians) and between 50 and 70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (for
the 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E meridian) and sorted these into
10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitude bins. Following the approach adopted in Lavers
et al. (2013), the threshold chosen for each bin corresponds to the
85th percentile of the maximum IVT values included in that bin. The
derived thresholds for the different reference meridians and sectors are
summarized in Table 1.</p>
      <p>After having computed the different thresholds for each reference meridian, the
following detection scheme was applied for each sector:
<list list-type="custom"><list-item><label>a.</label><p>At each 6 h time step of the data set (each day has four time steps) between
1979 and 2012 over the winter half-year, we compared the IVT values at the
grid points for each reference meridian and extracted the maximum IVT value
and its location.</p></list-item><list-item><label>b.</label><p>Where the maximum IVT exceeded the local IVT threshold (which depends on
both longitude and latitude and was computed for each meridian reference bin;
Table 1), this particular grid point was highlighted. We then performed a
west/east search to identify the maximum IVT at each longitude and tracked
the location for the grid points where the local IVT threshold was exceeded.
However, ARs have to extend for at least 1500 km; therefore a minimum length
threshold was also imposed. In this case, it corresponded to 30 contiguous
longitude points (30 <inline-formula><mml:math display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 0.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 22.25–1600 km,
considering that at 50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N the length of a degree of longitude is
<inline-formula><mml:math display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 71 km). Provided that this condition was fulfilled for a particular
time step, we considered it to be an AR time step.</p></list-item><list-item><label>c.</label><p>Because we applied the same procedure to all time steps, we obtained all the
AR time steps identified for the different reference meridians, but only
persistent AR events were retained. For a persistent AR event to occur
(Lavers and Villarini, 2013; Ramos et al., 2015), a temporal criterion was
applied in that (1) it required a persistence of at least 18h (three
continuous time steps), and (2) to be independent, two persistent ARs were
considered distinct only when they were separated by more than 1 day (four
time steps). A spatial criterion was also applied: a movement of not more
than 4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> latitude to the north or south of the initial IVT maximum in a 18 h period.</p></list-item></list></p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1"><caption><p>The vertically integrated horizontal water vapour transport (IVT)
threshold and the number of persistent atmospheric rivers detected for each
different reference meridian.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="center"/>
     <oasis:colspec colnum="3" colname="col3" align="center"/>
     <oasis:colspec colnum="4" colname="col4" align="center"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Sector</oasis:entry>  
         <oasis:entry colname="col3">IVT</oasis:entry>  
         <oasis:entry colname="col4">Number</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3">threshold</oasis:entry>  
         <oasis:entry colname="col4">of ARs</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3">(kg m<inline-formula><mml:math 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 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>)</oasis:entry>  
         <oasis:entry colname="col4"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">Reference meridian 1</oasis:entry>  
         <oasis:entry colname="col2">35–45<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">621.7048</oasis:entry>  
         <oasis:entry colname="col4">79</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">(9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W)</oasis:entry>  
         <oasis:entry colname="col2">45–55<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">691.5456</oasis:entry>  
         <oasis:entry colname="col4">87</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">55–65<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">614.4121</oasis:entry>  
         <oasis:entry colname="col4">70</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">65–75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">453.4208</oasis:entry>  
         <oasis:entry colname="col4">35</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Reference meridian 2</oasis:entry>  
         <oasis:entry colname="col2">35–45<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">527.9475</oasis:entry>  
         <oasis:entry colname="col4">113</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">(4.50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W)</oasis:entry>  
         <oasis:entry colname="col2">45–55<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">637.2342</oasis:entry>  
         <oasis:entry colname="col4">94</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">55–65<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">544.0915</oasis:entry>  
         <oasis:entry colname="col4">98</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">65–75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">439.4734</oasis:entry>  
         <oasis:entry colname="col4">46</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Reference meridian 3</oasis:entry>  
         <oasis:entry colname="col2">50–60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">524.1678</oasis:entry>  
         <oasis:entry colname="col4">100</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">(5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E)</oasis:entry>  
         <oasis:entry colname="col2">60–70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>  
         <oasis:entry colname="col3">468.0643</oasis:entry>  
         <oasis:entry colname="col4">80</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>The number of persistent ARs identified for each reference meridian is
summarized in Table 1 (last column) and will be discussed in Sect. 3. Given
that we are particularly interested in those ARs that have impacts over land,
we reorganized the previously computed ARs (Fig. 1 and Table 1) into the
following five new domains shown in Fig. 1 using different-coloured solid lines
and identified as (1) <italic>Iberian Peninsula</italic> (red; 9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W,
36–43.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N); (2) <italic>France</italic> (blue; 4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 43.75–50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N);
(3) <italic>UK</italic> (green; 4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N); (4) <italic>southern Scandinavia and the Netherlands</italic>
(yellow; 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and (5) <italic>northern Scandinavia</italic>
(purple; 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 59–70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N). This allows us to use contiguous domains from 36 to
70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, with domains (3) and (4) only differing in terms of the
meridional reference while maintaining the same latitudinal division. This
new division will be very helpful in Sect. 4, where the study of the
anomalous moisture uptake for ARs will be analysed in greater detail, given
that the specific location at which the ARs make landfall is of the utmost importance.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Lagrangian moisture quantification</title>
      <p>The method developed by Stohl and James (2004) allows us to track the
atmospheric moisture along Lagrangian trajectories of air parcels in the
atmosphere using the FLEXPART v9.0 Lagrangian model. This model simulates
the movement of approximately 2.0 million atmospheric parcels every 3 h.
Our global simulation was forced using ERA-Interim reanalysis data (Dee
et al., 2011) from 1979 to 2012. At each initial time this Lagrangian model
distributes the air parcels (also namely particles) homogeneously to cover
the largest possible volume, always taking the distribution of mass in the
atmosphere into account. The FLEXPART model imposes a condition on the mass,
which must be constant. The mass takes into account the volume and the
density of the air. We use 61 levels in the atmosphere, from 1000 to 0.1 hPa,
so the volume of the air parcel varies in accordance with the level
concerned: a volume is thus smaller near the surface and larger higher up
because the air density is greater near the surface and lower at high
altitudes. These particles are then moved using the reanalysis wind field,
and in addition turbulence and convection parametrizations are taken in
account, always maintaining the consistency of the atmospheric mass
distribution (Stohl et al., 1998, 2005). The meteorological
properties of the air parcels, such as specific humidity or temperature
among many others, are retained in the outputs of the FLEXPART model, taking
into account the ERA-Interim reanalysis input.</p>
      <p>The changes in specific humidity (d<inline-formula><mml:math display="inline"><mml:mi>q</mml:mi></mml:math></inline-formula>) of a particle (with mass <inline-formula><mml:math display="inline"><mml:mi>m</mml:mi></mml:math></inline-formula>) over
time (d<inline-formula><mml:math display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>) during its trajectory can be expressed as (Eq. 2)

                <disp-formula id="Ch1.E2" content-type="numbered"><mml:math display="block"><mml:mrow><mml:mi>e</mml:mi><mml:mo>-</mml:mo><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mi>m</mml:mi><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:mtext>d</mml:mtext><mml:mi>q</mml:mi></mml:mrow><mml:mrow><mml:mtext>d</mml:mtext><mml:mi>t</mml:mi></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>

          where (<inline-formula><mml:math display="inline"><mml:mi>e</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>) can be inferred as the freshwater flux in the parcel (the
difference between evaporation and precipitation).</p>
      <p>The moisture changes (<inline-formula><mml:math display="inline"><mml:mi>e</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula>) of all the particles in the atmospheric column over
a specified area (<inline-formula><mml:math display="inline"><mml:mi>A</mml:mi></mml:math></inline-formula>) yield the surface freshwater flux (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>), where <inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> is the
evaporation rate per unit area and <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> is the precipitation rate per unit area (Eq. 3):

                <disp-formula id="Ch1.E3" content-type="numbered"><mml:math display="block"><mml:mrow><mml:mi>E</mml:mi><mml:mo>-</mml:mo><mml:mi>P</mml:mi><mml:mo>≈</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mrow><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>k</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow><mml:mi>K</mml:mi></mml:munderover><mml:mo>(</mml:mo><mml:mi>e</mml:mi><mml:mo>-</mml:mo><mml:mi>p</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mi>A</mml:mi></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:math></disp-formula>

          where <inline-formula><mml:math display="inline"><mml:mi>K</mml:mi></mml:math></inline-formula> is the total number of particles in the atmospheric column. Each
particle is tracked backwards for a transport time of 10 days, this being
the average residence time of water vapour in the atmosphere (Numaguti, 1999).</p>
      <p><?xmltex \hack{\newpage}?>The different areas where the ARs make landfall are discussed in Sect. 3,
while the selection of each European domain where the particles are selected
for the backward trajectory (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) analyses will be discussed in Sect. 4.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2"><caption><p>The newly defined atmospheric river landfall domains and the corresponding
number of atmospheric rivers and the respective number of time steps.</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="center"/>
     <oasis:colspec colnum="3" colname="col3" align="center"/>
     <oasis:thead>
       <oasis:row>

         <oasis:entry colname="col1">AR domains</oasis:entry>

         <oasis:entry colname="col2">Number</oasis:entry>

         <oasis:entry colname="col3">Number of</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col2">of ARs</oasis:entry>

         <oasis:entry colname="col3">AR time</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col2"/>

         <oasis:entry colname="col3">steps</oasis:entry>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry colname="col1">(1) Iberian Peninsula</oasis:entry>

         <oasis:entry rowsep="1" colname="col2" morerows="1">21</oasis:entry>

         <oasis:entry rowsep="1" colname="col3" morerows="1">117</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1">9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 36–43.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(2) France</oasis:entry>

         <oasis:entry rowsep="1" colname="col2" morerows="1">140</oasis:entry>

         <oasis:entry rowsep="1" colname="col3" morerows="1">665</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1">4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 43.75–50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(3) UK</oasis:entry>

         <oasis:entry rowsep="1" colname="col2" morerows="1">74</oasis:entry>

         <oasis:entry rowsep="1" colname="col3" morerows="1">343</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1">4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(4) Southern Scandinavia</oasis:entry>

         <oasis:entry rowsep="1" colname="col2" morerows="2">90</oasis:entry>

         <oasis:entry rowsep="1" colname="col3" morerows="2">423</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">and the Netherlands</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1">5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(5) Northern Scandinavia</oasis:entry>

         <oasis:entry colname="col2" morerows="1">83</oasis:entry>

         <oasis:entry colname="col3" morerows="1">317</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 59–70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Landfall of atmospheric rivers in Europe</title>
      <p>The number of ARs for each domain is summarized in Table 1. There were
271 ARs for reference meridian 1, with a maximum of 87 ARs in the
45–55<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N sector; for reference meridian 2
the total number is 351, with a maximum of 98 ARs observed at latitudes
between 55 and 65<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N. In the case of
reference meridian 3 and given that the ARs come from the Atlantic region,
we divided the reference meridian into two sectors (50 to 60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and 60 to 70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N),
with the maximum number of ARs being recorded in the 50–60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N sectors (100 ARs). The IVT threshold has a maximum
around 45 and 55<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N for the reference
meridians, in good agreement with the results obtained by Lavers and
Villarini (2013) near 10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W. In addition, this maximum is
also confirmed by the analysis of the seasonal IVT mean fields, where a
maximum is present between 45 and 55<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (not shown).</p>
      <p>The number of ARs and the corresponding AR time steps for each new domain
are shown in Table 2 and will be analysed in detail in Sect. 4. This varies
from 21 ARs (117 time steps) in the Iberian Peninsula domain up to 140 ARs
(665 time steps) in the France domain.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p>The median position (coloured line) and the respective 90th and
10th percentiles (dashed lines) of the atmospheric river path along
the North Atlantic Ocean before arriving in each studied domain: <bold>(a)</bold> Iberian
Peninsula (red), <bold>(b)</bold> France (blue) and the UK (green), and <bold>(c)</bold> southern Scandinavia
and the Netherlands (yellow) and northern Scandinavia (purple).</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://esd.copernicus.org/articles/7/371/2016/esd-7-371-2016-f02.png"/>

      </fig>

      <p>This assessment of ARs for the different reference meridians confirms the
findings of Lavers and Villarini (2013) that the ARs also strike regions of
Europe other than the Iberian Peninsula (Ramos et al., 2015) or the UK
(Lavers et al., 2011). In this regard, we are confident that the use of
three different meridians of control (9.75 and 4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) provides a more precise
and robust assessment of all the ARs that make landfall in Europe.</p>
      <p>While it can be argued that the overall frequency of ARs is rather low, in
fact we are particularly interested in analysing tracking and the anomalous
moisture sources for the most intense ARs, i.e. those ARs that are often
associated with extreme precipitation events. It has been shown that a large
proportion of the most intense precipitation events (and of course their
associated floods) in western Europe are objectively associated with the
occurrence of ARs, both in the UK (Lavers et al., 2013) and in the Iberian
Peninsula (Ramos et al., 2015). In particular, Lavers and Villarini (2013)
showed in their Fig. 3 the number of top-10 annual maximum events related to
ARs. It is immediately striking that some areas of the Iberian Peninsula,
France, the UK, and Norway have up to 6 out of 10 top annual maxima associated
with ARs. In addition, Ramos et al. (2015) for the Iberian Peninsula showed
that ARs play an overwhelming role in the most extreme precipitation days,
but these decrease in importance for less extreme precipitation days.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><caption><p><bold>(a)</bold> The moisture sources (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0) computed for 10 days
for an AR making landfall in the Iberian Peninsula on 14 December 1981 at
00:00 UTC. <bold>(b)</bold> The vertically integrated horizontal water vapour transport (IVT)
field for 14 December 1981 at 00:00 UTC and the location of the IVT maxima
(black line). The moisture sources detected in <bold>(a)</bold> are also plotted
using red contours.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://esd.copernicus.org/articles/7/371/2016/esd-7-371-2016-f03.png"/>

      </fig>

      <p>The refinements made to the detection scheme for ARs (in the use of three
reference meridians regrouped into five sub-domains in terms of their
geographical relevance), as introduced by Lavers et al. (2012), were intended
to improve AR detection and allow us to obtain more precise locations for AR
landfalls. To analyse whether these refinements actually improve AR
detection, the number of top-10 annual maxima precipitation events (for the
extended winter months, i.e. ONDJFM) related to ARs was computed. To this
end, the annual maxima were computed for each calendar year (only for the
extended winter months) from 1979 to 2012 at each grid point (E-OBS, at
0.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> resolution; Haylock et al., 2008). The results
obtained (Fig. S1 in the Supplement) show that there is an improvement
in the relationship between ARs and annual maxima for France, Belgium,
Germany, and the Scandinavian countries compared to the results of Lavers and
Villarini (2013) in their Fig. 3.</p>
      <p>In order to track the path of the ARs, we computed the maximum longitudinal
IVT for each AR, in order to obtain a preliminary estimate of the position
of the ARs in the North Atlantic Ocean. For each new domain, we computed the
median, 90th percentile, and 10th percentile of the maximum IVT positions of
the different ARs along their first-guess trajectories, and the results are
presented in Fig. 2. The use of the 90th and 10th percentiles
allows us to visualize the spread of the positions of the vast majority of
the ARs throughout the North Atlantic basin associated with each domain.</p>
      <p>Regarding the Iberian Peninsula (Fig. 2a), the median position of the ARs is
mainly zonal, with a small WSW component, while their spatial dispersion is
quite high, particularly as we move away from the landfall area. This WSW
component is in line with the results obtained by Ramos et al. (2015), where
a positive anomaly of sea level pressure is found to the south of Portugal
when the ARs make landfall in the Iberian Peninsula.</p>
      <p>In the cases of France and the UK (Fig. 2b), the paths and dispersions are
similar with respect to the median path of the ARs, especially on the
eastern North Atlantic. The main differences are closer to the two domains,
namely (1) a more zonal path associated with the France domain, while for
the UK its path near the reference meridian is clearly more SW–NE oriented,
and (2) the dispersion of the AR paths is higher for the UK domain than for
the France domain, particularly to the west of 40<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W. The
results for the UK confirm those obtained by Lavers et al. (2011), although
here we have used the full climatology, whereas Lavers et al. (2011) only
analysed the AR paths for selected cases. Concerning the last two domains
(Fig. 2c), the results are very similar to those obtained for the France and
UK domains; i.e. most ARs show a strong SW–NE orientation, particularly to
the east of 40<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W for those ARs that arrive in the northern
Scandinavian domain. In addition, the dispersion of the paths in these two
domains is relatively high compared with the other three domains.</p>
      <p>These five new domains (Fig. 1) are those that will be used in the
computation of the moisture transport for the ARs that make landfall over
the western coasts of the European domains analysed.</p>
</sec>
<sec id="Ch1.S4">
  <title>Atmospheric rivers and anomalous moisture uptake</title>
      <p>The use of the IVT is an effective
Eulerian approach for studying the temporal variability of moisture flows
for specific locations around the globe and is therefore widely used in the
identification of ARs. However, this Eulerian perspective is not suitable
for finding sources of moisture, and of course it is impossible to use it
to compute where the uptake of moisture to the AR is, given that the method is
not able to follow any specific “particle” transported by the ARs. To
illustrate the difference between the use of the IVT and the information
that can be extracted from FLEXPART, we provide in Fig. 3 an example of a
particular AR that occurred on 14 December 1981 at 00:00 UTC, which reached the
Iberian Peninsula. Figure 3a shows the sources of moisture (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0
computed for 10 days back in time (reddish colours). Three areas clearly
emerge as sources: one located to the west of the Iberian Peninsula near the
coast, and two larger ones located in the central and western Atlantic. In
Fig. 3b we show the IVT field for the same day and the maximum edge of the
IVT denoted by a black line and used in this study to detect ARs, together
with a red contour delimiting the sources of moisture in Fig. 3a. It can
clearly be seen that the moisture sources and the IVT maximum are not
coincident. When we analyse either the IVT maximum or the IVT field, we only
reveal a snapshot of the integrated horizontal flux transport for that
specific time step, not the path of the air masses. This indicates
neither where the moisture comes from nor where the moisture uptake is
anomalous during the previous days of the AR, which is one of the objectives
of this analysis.</p>
      <p>The use of Lagrangian models such as FLEXPART allows us to study air parcels
as they move through space and time, i.e. their trajectory, and also allows
us to characterize accurately the history of the air parcels (e.g. their
specific humidity) that arrive at a specific site. The use of Lagrangian
models was shown to be a worthwhile and important tool for analysing the
moisture sources in a case study of ARs in Norway (Stohl et al., 2008) and
in Portugal (Liberato et al., 2012). In the latter case the methodology has
been applied over different accumulated periods (for 1 to 3, 3 to 5, and 5 to
10 days), also allowing for the identification of the relative importance of the several
moisture sources' contribution over time. Our use of FLEXPART simulations and
the computation of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) is intended to help us locate the origin of the
anomalous moisture uptake associated with ARs reaching the Atlantic European
coast for all the systems detected and from a climatological point of view.
It is important to note that an AR transports a large amount of moisture
that often reaches a continental area. This moisture must necessarily be
available for transport in the atmosphere. Therefore, it must be evaporated
and accumulated in certain areas during the days prior to the intense track
of the AR. The existence of an intense flux is important but not sufficient,
in that an intense anomalous quantity of moisture must be available for the
AR to occur. Therefore, in this research we detect (for the 10 days prior to
the AR reaching landfall) where the moisture uptake to the atmosphere is anomalous.</p>
      <p>The backward trajectory analyses were performed for air particles residing
over the area 5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> to the west of the AR detection meridian
reference (Table 3): e.g. for the Iberian Peninsula region it included
particles located inside a rectangle (covering an area between
9.75 and 4.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W and from 36 to 43.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and tracked backwards for
10 days at 6 h intervals (a total of 40 time steps).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3"><caption><p>(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) backward trajectories regions where the computation is made
for all the air parcels inside it.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="2">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1">ARs domains</oasis:entry>

         <oasis:entry colname="col2">Longitude and latitude limits</oasis:entry>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry colname="col1">(1) Iberian Peninsula</oasis:entry>

         <oasis:entry colname="col2">9.75–4.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 36–43.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(2) France</oasis:entry>

         <oasis:entry colname="col2">4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 43.75–50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(3) UK</oasis:entry>

         <oasis:entry colname="col2">4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–0.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(4) Southern Scandinavia</oasis:entry>

         <oasis:entry colname="col2" morerows="1">5.25–10.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">and the Netherlands</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(5) Northern Scandinavia</oasis:entry>

         <oasis:entry colname="col2">5.25–10.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 59–70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N</oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>We computed the uptake of moisture for all individual ARs at all time steps,
retaining only positive values of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) every 6 h during the 10-day back
trajectories (40 time steps). For instance, there are 117 cases for the
Iberian Peninsula, so we computed 117 fields of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0, and the
same for the other domains. To check whether these areas (where the ARs take
on moisture) differ from the climatology, we computed for each AR the
anomaly between (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 of the ARs and the “climatology” for the
corresponding AR dates. The climatology at this point corresponded to the
same (Julian) time step but for all 33 years of the study (retaining again
only the positive values of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) for each 6 h time step). For the example
given in Fig. 3, if an AR existed on 14 December 1981 at 00:00 UTC, we computed the
anomaly between (a) (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0) on 14 December 1981 at 00:00 UTC and
(b) (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 for all time steps of 14 December 00:00 UTC, in other words,
(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 for the corresponding day for the 33 years of the entire
period. We then computed the anomaly for this particular case (14 December 1981
00:00 UTC) using the difference between (b) and (a). The climatology and the
anomaly for each domain, denoted by (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>Cli</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 and
(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 in Fig. 4, correspond to the mean values for all
the respective ARs. A representation of the fields of
(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>Cli</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 and (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 for all the five
regions studied is provided in Fig. 4 (left panel and right panel,
respectively). Moreover, the anomalous moisture of the sources is only shown
for the areas that are statistically significant at the 90 % level,
applying a Student <inline-formula><mml:math display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test to the (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 for all the ARs and the
climatology (Table 4). In general, for all regions the major anomalous
uptake of moisture (hereafter AUM) extends along the subtropical north
Atlantic (from the Tropic of Cancer to 35<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N according to the
definition of the American Meteorological Society), from the Gulf Stream
Current, just off the Florida Peninsula (to the north of 20<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N),
to each sink region, being further to the south (clearly subtropical) in
the western basin of the North Atlantic Ocean and reaching extra-tropical
latitudes on the eastern basin coast. Moreover, the nearest coast to each
sink region always appears as a local maximum of AUM (e.g. see the southern
Iberian Peninsula coast or the Bay of Biscay in France). The Norwegian Sea
acts as a more important AUM because the region analysed is located at
higher latitudes and is a maximum for the northern Scandinavia region.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T4"><caption><p>90th percentile for the anomaly values of the (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0
field [(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>] for each studied domain and longitude (in mm day<inline-formula><mml:math 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>).</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.92}[.92]?><oasis:tgroup cols="6">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="center"/>
     <oasis:colspec colnum="3" colname="col3" align="center"/>
     <oasis:colspec colnum="4" colname="col4" align="center"/>
     <oasis:colspec colnum="5" colname="col5" align="center"/>
     <oasis:colspec colnum="6" colname="col6" align="center"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Iberian</oasis:entry>  
         <oasis:entry colname="col3">France</oasis:entry>  
         <oasis:entry colname="col4">UK</oasis:entry>  
         <oasis:entry colname="col5">Southern</oasis:entry>  
         <oasis:entry colname="col6">Northern</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Peninsula</oasis:entry>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">Scandinavia</oasis:entry>  
         <oasis:entry colname="col6">Scandinavia</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">and the</oasis:entry>  
         <oasis:entry colname="col6"/>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4"/>  
         <oasis:entry colname="col5">Netherlands</oasis:entry>  
         <oasis:entry colname="col6"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col2">0.45</oasis:entry>  
         <oasis:entry colname="col3">0.40</oasis:entry>  
         <oasis:entry colname="col4">0.50</oasis:entry>  
         <oasis:entry colname="col5">0.55</oasis:entry>  
         <oasis:entry colname="col6">0.41</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">20<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col2">0.77</oasis:entry>  
         <oasis:entry colname="col3">0.56</oasis:entry>  
         <oasis:entry colname="col4">0.69</oasis:entry>  
         <oasis:entry colname="col5">0.73</oasis:entry>  
         <oasis:entry colname="col6">0.53</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">30<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col2">0.82</oasis:entry>  
         <oasis:entry colname="col3">0.69</oasis:entry>  
         <oasis:entry colname="col4">0.90</oasis:entry>  
         <oasis:entry colname="col5">0.86</oasis:entry>  
         <oasis:entry colname="col6">0.63</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">40<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col2">0.99</oasis:entry>  
         <oasis:entry colname="col3">0.85</oasis:entry>  
         <oasis:entry colname="col4">0.93</oasis:entry>  
         <oasis:entry colname="col5">0.90</oasis:entry>  
         <oasis:entry colname="col6">0.62</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col2">0.98</oasis:entry>  
         <oasis:entry colname="col3">0.81</oasis:entry>  
         <oasis:entry colname="col4">0.83</oasis:entry>  
         <oasis:entry colname="col5">0.80</oasis:entry>  
         <oasis:entry colname="col6">0.56</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col2">1.06</oasis:entry>  
         <oasis:entry colname="col3">0.79</oasis:entry>  
         <oasis:entry colname="col4">0.64</oasis:entry>  
         <oasis:entry colname="col5">0.71</oasis:entry>  
         <oasis:entry colname="col6">0.52</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <p>The distribution of the particle density used to compute the AUM (using a
5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> by 5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid cell) for each domain was also
computed. Figure S2 shows how many times a
parcel (in percentage terms) contributes to the (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0
field. In addition, one must be aware that the areas of maximum density of
the parcels may (or may not) correspond to areas of maximum anomalies and
vice versa, because a grid cell can contribute many times, but its AUM contribution
could be less than that of others with a lower AUM density.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F4" specific-use="star"><caption><p>For each studied sink domain (Iberian Peninsula, France, UK,
southern Scandinavia and the Netherlands, and northern Scandinavia) for
wintertime from 1979 to 2012. Left panels: mean value of the (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0
field [(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>Cli</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>], backward integrated over a 10-day
period. Right panels: (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 anomaly field for AR days
[(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>]. Units in mm day<inline-formula><mml:math 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>. Regarding the anomaly fields, only the
results that are statistically significant at the 90 % level are shown.
The Tropic of Cancer parallel (23.43<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and the 35<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N parallel are also shown.</p></caption>
        <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://esd.copernicus.org/articles/7/371/2016/esd-7-371-2016-f04.png"/>

      </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p>Longitudinal cross section of the anomaly values of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0
field [(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>] for each studied domain: Iberian
Peninsula (red line), France (blue), UK (green), southern Scandinavia and
the Netherlands (yellow), and northern Scandinavia (purple). The bold line
shows those values over the 90th percentile of each series (values
shown in Table 4). Units in mm day<inline-formula><mml:math 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>. The Tropic of Cancer parallel
(23.43<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and the 35<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N parallel are also shown.</p></caption>
        <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://esd.copernicus.org/articles/7/371/2016/esd-7-371-2016-f05.png"/>

      </fig>

      <p>The importance of the North Atlantic Ocean as a source of moisture for some
regions of Europe has already been noted in previous studies. In a complete
moisture source catalogue for important climate regions, Castillo et al. (2014)
showed that for southern Europe (including our Iberian Peninsula and
France domains) and northern Europe (UK, southern Scandinavia and the
Netherlands, and northern Scandinavia) the dominant source of moisture is
the North Atlantic, with a strong signal over the Norwegian Sea when
northern continental areas were analysed. Studies focused on specific
regions also found similar results, for instance Gimeno et al. (2010b) and
Drumond et al. (2011) for the Iberian Peninsula, or studies of European
regions at higher latitudes (Nieto et al., 2007; Sodemann et al., 2008)
revealed the importance of the Atlantic source. Interestingly, in almost all
these studies the authors pointed to the effects of ARs as the major
moisture transport mechanism from the subtropical Atlantic. In this work,
the key novelty is that we show those regions where the moisture uptake is
anomalous and significant when an AR occurs.</p>
      <p>We are particularly interested in understanding which regions with higher
AUM (depicted in Fig. 4, left panel) are reinforced during ARs associated
with each of the five different domains. These reinforced sectors are
identified in yellowish and reddish colours in maps of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> (Fig. 4,
right panel). Overall, the largest anomalies are detected in the middle of
the North Atlantic, between 20 and 40<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, with a slight northward movement when the sink region is positioned at
higher latitudes. These results confirm that part of the excess of moisture
transported by ARs vs. the climatology comes from tropical latitudes (south
of the Tropic of Cancer, 23.43<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N), but the bulk of the
additional amount provided by the ARs is obtained from subtropical ocean
areas (i.e. those between the Tropic of Cancer and 35<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N).
The most notable anomaly is detected for the Iberian Peninsula, followed by
the southern Scandinavia and the Netherlands domain, and the lowest is for the
northern Scandinavia domain. Each domain shows differences in values of
(<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mrow><mml:mi>P</mml:mi><mml:msub><mml:mo>)</mml:mo><mml:mtext>An</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 in both latitude and longitude. To understand
these patterns better, we quantified the anomaly values every
10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> between 70 and 5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and between 10 and 60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W.</p>
      <p>Figure 5 shows the different latitudinal sections for all the studied regions
in which values over the 90th percentile of the anomaly (Table 4) are
highlighted using a bold line. We refer to these values to compare the five
domains of study. In general, there is a longitudinal southern shift of the
anomaly, which is a common feature for all the regions. So for instance, for
northern Scandinavia (purple line) the anomalous uptake of moisture at
10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W occurs mostly between 60 and 48<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, while
at 60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W it occurs predominantly between
40 and 30<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N; whereas for the Iberian Peninsula (IP, red line)
at 10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W the anomalous uptake occurs mainly in a band
between 43 and 33<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, and at 60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W it is
particularly intense between 36 and 21<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N. The Iberian Peninsula
shows the highest values of AUM for all the latitudes and is the region
where the anomalous moisture uptake occurs furthest south, with local maxima
partially over tropical areas. Because the region is positioned more to the
north, the tropical AUM tends to be lower, but the subtropical source still
dominates, particularly at central and western longitudes.
Figure S3 is included to complement the information
given in Fig. 5, albeit showing the same results for each individual domain.</p>
      <p>To understand more about the effect of ARs over the European domains, we
checked whether those areas with significant AUM contribute to a significant
increase in precipitation. Because FLEXPART can be run in forward mode, we
looked for the sinks for those air parcels (particles) that leave a
particular area, using the AUM regions (those in Fig. 3, right panel) to
compute the precipitation (as <inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0) over each target domain. We
computed (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0 values for the climatological period
((<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0)<inline-formula><mml:math display="inline"><mml:msub><mml:mi/><mml:mtext>Clim</mml:mtext></mml:msub></mml:math></inline-formula>) and only for the AR days
((<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0)<inline-formula><mml:math display="inline"><mml:msub><mml:mi/><mml:mtext>AR</mml:mtext></mml:msub></mml:math></inline-formula>). The results show that the AUM areas associated with ARs support
sufficient moisture to increase the precipitation (Table 5). The ratio
between the climatology and the AR values provides evidence of an increase
ranging from 1.26 times as much precipitation in the UK to 3 times more in
the Iberian Peninsula.</p>
      <p>It is important to place these results in the light of recent works dealing
with the origin of moisture in ARs. Sodemann and Stohl (2013) showed that in
December 2006 several ARs reached from the subtropics to high latitudes,
inducing precipitation over western Scandinavia. The sources and transport
of water vapour in the North Atlantic storm track during that month were
examined, and they reveal that the ARs were composed of a sequence of
meridional excursions of water vapour. Different moisture sources were
found: (1) in cyclone cores, the rapid turnover of water vapour by
evaporation and condensation was identified, leading to a rapid
assimilation of water from the underlying ocean surface; (2) in the regions
of long-range transport, water vapour tracers from the southern edges of the
midlatitudes and subtropics dominated over local contributions. Our results
generalize for all the domains previous findings of Liberato et al. (2012)
obtained for a case study for Portugal, confirming the presence of extended
source areas that support anomalous moisture uptake (tropical and
subtropical) for all the domains, with the highest anomalies being found for
the Iberian Peninsula and the UK. Because ARs are always dynamically coupled
to cyclones, Sodemann and Stohl (2013) also analyse in their study the
change in moisture composition in the vicinity of the cyclone responsible
for the intense events over western Scandinavia. This fact may be better
corroborated in future work by using the long database of ARs for all
European coastal domains. In any case, our results also suggest
contributions from nearby sources of anomalous moisture uptake associated
with the ARs. According to Sodemann and Stohl (2013), this may be due to the
rapid turnover of water vapour by evaporation and condensation, leading to
the rapid assimilation of water from the underlying ocean surface near the
cyclone cores.</p>
      <p>We acknowledge the scepticism of some authors regarding the far-reaching
origin of moisture considered to contribute to the ARs. Dacre et al. (2015)
considered a selected number of cases of water vapour transport associated
with North Atlantic extra-tropical cyclones in winter. The authors inferred
that AR moisture originates mostly from the water vapour in the cyclone's
warm sector, and not that much from the long-distance transport of water
vapour from the subtropics. Our long-term (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) <inline-formula><mml:math display="inline"><mml:mo>&gt;</mml:mo></mml:math></inline-formula> 0 analysis shows
that for the ARs that make landfall on the western European coast the anomalous
moisture linked with the ARs comes mainly from subtropical areas and, to a
lesser extent, from midlatitudes. In addition, a small anomalous moisture
uptake has also been found in the tropical zone. Garaboa-Paz et al. (2015),
using Lagrangian coherent structures (LCSs), showed for two AR case studies
that the passive advection of water vapour in the AR from tropical latitudes is possible.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T5"><caption><p>The contribution of the different moisture sources to the
precipitation derived from FLEXPART, computed as <inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0
(<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>), over the five analysed domains for the climatological period
(<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX Clim</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>) and for the AR days (<inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX AR</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>). The ratio between the
two is also shown.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.88}[.88]?><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="center"/>
     <oasis:colspec colnum="3" colname="col3" align="center"/>
     <oasis:colspec colnum="4" colname="col4" align="center"/>
     <oasis:thead>
       <oasis:row>

         <oasis:entry colname="col1">Domain</oasis:entry>

         <oasis:entry colname="col2"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX Clim</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col3"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX AR</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX AR</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula>/</oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col2">(mm day<inline-formula><mml:math 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>)</oasis:entry>

         <oasis:entry colname="col3">(mm day<inline-formula><mml:math 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>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math display="inline"><mml:mrow><mml:msub><mml:mi>P</mml:mi><mml:mtext>FLEX Clim</mml:mtext></mml:msub></mml:mrow></mml:math></inline-formula></oasis:entry>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry colname="col1">(1) Iberian Peninsula</oasis:entry>

         <oasis:entry colname="col2">255.85</oasis:entry>

         <oasis:entry colname="col3">788.14</oasis:entry>

         <oasis:entry colname="col4">3.07</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(2) France</oasis:entry>

         <oasis:entry colname="col2">360.94</oasis:entry>

         <oasis:entry colname="col3">779.01</oasis:entry>

         <oasis:entry colname="col4">2.16</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(3) UK</oasis:entry>

         <oasis:entry colname="col2">561.61</oasis:entry>

         <oasis:entry colname="col3">709.86</oasis:entry>

         <oasis:entry colname="col4">1.26</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(4) Southern Scandinavia</oasis:entry>

         <oasis:entry colname="col2" morerows="1">616.42</oasis:entry>

         <oasis:entry colname="col3" morerows="1">829.89</oasis:entry>

         <oasis:entry colname="col4" morerows="1">1.34</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">and the Netherlands</oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1">(5) Northern Scandinavia</oasis:entry>

         <oasis:entry colname="col2">601.35</oasis:entry>

         <oasis:entry colname="col3">871.06</oasis:entry>

         <oasis:entry colname="col4">1.44</oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusions</title>
      <p>We have described our innovative study related to the anomalous uptake of
moisture for ARs that reach different western European domains in the winter
half-year (ONDJFM). To achieve this goal, we used an objective AR detection
scheme (Lavers et al., 2012; Ramos et al., 2015) that depends entirely on
the IVT. In order
to ensure that the AR detection is performed as close to the coast as
possible, this analysis was applied to three different reference meridians
(9.75 and 4.50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) divided into 10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> sectors between
35 and 75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N. The use of three different reference meridians
represents a refinement to the approach of Lavers and Villarini (2013), who
only used the 10<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W meridian reference. Because we are
mostly interested in those ARs that make landfall in western Europe and over
land, we regrouped the previously computed ARs (Fig. 1 and Table 1) into the
following 5 new domains (Fig. 1): (1) Iberian Peninsula
(9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 36–43.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N); (2) France (4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 43.75–50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N);
(3) the UK (4.5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N); (4) southern Scandinavia and the Netherlands
(5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 50–59<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and (5) northern Scandinavia
(5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 59–70<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N).</p>
      <p>The number of ARs found shows a latitudinal dependence, with the highest
values being recorded for the three meridional references
9.75<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, 4.50<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W, and 5.25<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E are 45–55<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N,
35–45<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, and 50–60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, respectively. We then considered only those ARs that made landfall in
western Europe over land into the new domains, where the French (140 ARs)
and southern Scandinavia and the Netherlands (90 ARs) domains showed the
highest values, while the Iberian Peninsula (21) domain recorded the lowest value.</p>
      <p>The Lagrangian perspective of this work can help provide additional input
regarding the effective moisture sources associated with most of the ARs
that reach Europe. To achieve this objective, we detected those areas where
the moisture uptake to the atmosphere occurs in an anomalous way. The
computation of positive values of (<inline-formula><mml:math display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> <inline-formula><mml:math display="inline"><mml:mi>P</mml:mi></mml:math></inline-formula>) every 6 h for each AR for
10 days of transport was undertaken, taking into account the air particles
residing over the area 5<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W of the AR detection meridian reference
mentioned above and shown in Table 3. This amount was computed for all the
ARs that reached a continental domain and was compared with the climatology.
We have therefore shown in this paper the anomalous uptake of moisture areas for the ARs.</p>
      <p>The near-surface wind speed and the near-surface atmospheric specific
humidity, together with the SST, are bound to play a major role in the
process of moisture uptake over the oceans (Gimeno et al., 2012). Therefore,
despite not analysing the role of sea surface temperature (SST) in the present study, we can
nevertheless speculate on the possibility of positive anomalies of SST influencing the interannual variably of the ARs. Future studies
of the SST variability and its influence over the ARs should be considered
in order to understand this relationship better.</p>
      <p>The most important results obtained can be summarized as follows:
<list list-type="bullet"><list-item><p>In general, for all the regions, the major AUM areas extend along the
subtropical North Atlantic, from the Florida Peninsula (north of
20<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) to each sink region. However, the midlatitude also
plays an important role, with the coastal area nearest to each sink region
always appearing as a local maximum of AUM.</p></list-item><list-item><p>The Atlantic subtropical AUM source is reinforced during ARs where the major
uptake anomalies are detected in the middle of the North Atlantic,
between 20 and 40<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, with a slight
northward movement when the sink region is positioned at higher latitudes.</p></list-item><list-item><p>The most notable anomaly of moisture uptake is detected for the Iberian
Peninsula, followed by the southern Scandinavia and the Netherlands domains,
with the lowest being for the northern Scandinavia domain.</p></list-item></list></p>
      <p>To conclude, we have shown that the main anomalous uptake of moisture areas
associated with the ARs that strike western European coast are located over
subtropical latitudes. For the southern domains one must be also be aware of
the presence of a tropical AUM area. Near the continental sink areas,
extra-tropical areas with anomalous uptake of moisture are also apparent,
confirming the local transport produced by the nearby ocean.</p><?xmltex \hack{\newpage}?>
</sec>

      
      </body>
    <back><app-group>
        <supplementary-material position="anchor"><p><bold>The Supplement related to this article is available online at <inline-supplementary-material xlink:href="http://dx.doi.org/10.5194/esd-7-371-2016-supplement" xlink:title="pdf">doi:10.5194/esd-7-371-2016-supplement</inline-supplementary-material>.</bold><?xmltex \hack{\vspace*{-6mm}}?></p></supplementary-material>
        </app-group><ack><title>Acknowledgements</title><p>Alexandre M. Ramos was supported through a postdoctoral grant (SFRH/BPD/84328/2012)
from the Fundação para a Ciência e a
Tecnologia (FCT, Portuguese Science Foundation). This work also was
partially supported by FEDER funds through the COMPETE (Programa Operacional
Factores de Competitividade) programme and by national funds through the FCT
project STORMEx FCOMP-01-0124-FEDER-019524
(PTDC/AAC-CLI/121339/2010). Raquel Nieto acknowledges funding by the Spanish
MINECO within project TRAMO and the Galician Regional Government (Xunta)
within project THIS, both co-funded by FEDER. <?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: K. Thonicke</p></ack><ref-list>
    <title>References</title>

      <ref id="bib1.bib1"><label>1</label><mixed-citation>
Bao, J-W., Michelson, S. A., Neiman, P. J., Ralph, F. M., and Wilczak, J.
M.: Interpretation of enhanced integrated water vapor bands associated with
extratropical cyclones: Their formation and connection to tropical moisture,
Mon. Weather Rev., 134, 1063–1080, 2006.</mixed-citation></ref>
      <ref id="bib1.bib2"><label>2</label><mixed-citation>Castillo, R., Nieto R., Drumond, A., and Gimeno, L.: Estimating the temporal
domain when the discount of the net evaporation term affects the resulting
net precipitation pattern in the moisture budget using a 3-D Lagrangian
approach, PLoS ONE, 9, e99046, <ext-link xlink:href="http://dx.doi.org/10.1371/journal.pone.0099046" ext-link-type="DOI">10.1371/journal.pone.0099046</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib3"><label>3</label><mixed-citation>Couto, F. T., Salgado, R., and Costa, M. J.: Analysis of intense rainfall events
on Madeira Island during the 2009/2010 winter, Nat. Hazards Earth Syst. Sci.,
12, 2225–2240, <ext-link xlink:href="http://dx.doi.org/10.5194/nhess-12-2225-2012" ext-link-type="DOI">10.5194/nhess-12-2225-2012</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib4"><label>4</label><mixed-citation>Couto, F. T., Salgado, R., Costa, M. J., and Prior, V.: Precipitation in the
Madeira Is- land over a 10-year period and the meridional water vapour
transport during the winter seasons, Int. J. Climatol., 35, 3748–3759,
<ext-link xlink:href="http://dx.doi.org/10.1002/joc.4243" ext-link-type="DOI">10.1002/joc.4243</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib5"><label>5</label><mixed-citation>Dacre, H., Clark, P., Martinez-Alvarado, O., Stringer, M., and Lavers, D.:
How do atmospheric rivers form?, B. Am. Meteorol. Soc., 96, 1243–1255,
<ext-link xlink:href="http://dx.doi.org/10.1175/BAMS-D-14-00031.1" ext-link-type="DOI">10.1175/BAMS-D-14-00031.1</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib6"><label>6</label><mixed-citation>
Dee, D. P., Uppala, S. M., Simmons, A. J., et al.: The ERA-Interim reanalysis: configuration
and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc.,
137, 553–597, 2011.</mixed-citation></ref>
      <ref id="bib1.bib7"><label>7</label><mixed-citation>
Dettinger, M., Ralph, F. M., Das, T., Neiman, P. J., and Cayan, D. R.:
Atmospheric Rivers, Floods and the Water Resources of California, Water, 3, 445–478, 2011.</mixed-citation></ref>
      <ref id="bib1.bib8"><label>8</label><mixed-citation>Dettinger, M., Ralph, F. M., and Lavers, D.: Setting the stage for a global
science of atmospheric rivers, Eos, 96, <ext-link xlink:href="http://dx.doi.org/10.1029/2015EO038675" ext-link-type="DOI">10.1029/2015EO038675</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib9"><label>9</label><mixed-citation>Drumond, A., Gimeno, L., and Nieto, R.: On the contribution of the Tropical
Western Hemisphere Warm Pool source of moisture to the northern hemisphere
precipitation through a lagrangian approach, J. Geophys. Res., 116, D00Q04,
<ext-link xlink:href="http://dx.doi.org/10.1029/2010JD015397" ext-link-type="DOI">10.1029/2010JD015397</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib10"><label>10</label><mixed-citation>Ferreira, J. A., Liberato, M. L. R., and Ramos, A. M.: On the relationship between
atmospheric water vapour transport and extra-tropical cyclones development,
Phys. Chem. Earth, <ext-link xlink:href="http://dx.doi.org/10.1016/j.pce.2016.01.001" ext-link-type="DOI">10.1016/j.pce.2016.01.001</ext-link>, in press, 2016.</mixed-citation></ref>
      <ref id="bib1.bib11"><label>11</label><mixed-citation>Garaboa-Paz, D., Eiras-Barca, J., Huhn, F., and Pérez-Muñuzuri, V.:
Lagrangian coherent structures along atmospheric rivers, Chaos, 25, 063105,
<ext-link xlink:href="http://dx.doi.org/10.1063/1.4919768" ext-link-type="DOI">10.1063/1.4919768</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib12"><label>12</label><mixed-citation>Gimeno, L., Drumond, A., Nieto, R., Trigo, R. M., and Stohl, A.: On the origin
of continental precipitation, Geophys. Res. Lett., 37, L13804, <ext-link xlink:href="http://dx.doi.org/10.1029/2010GL043712" ext-link-type="DOI">10.1029/2010GL043712</ext-link>, 2010a.</mixed-citation></ref>
      <ref id="bib1.bib13"><label>13</label><mixed-citation>Gimeno, L., Nieto, R., Trigo, R. M., Vicente, S., and Lopez-Moreno, J. I.:
Where does the Iberian Peninsula moisture come from? An answer based on a
Largrangian approach, J. Hydrometeorol., 11, 421–436, <ext-link xlink:href="http://dx.doi.org/10.1175/2009JHM1182.1" ext-link-type="DOI">10.1175/2009JHM1182.1</ext-link>, 2010b.</mixed-citation></ref>
      <ref id="bib1.bib14"><label>14</label><mixed-citation>Gimeno, L., Stohl, A., Trigo, R. M., Domínguez, F., Yoshimura, K., Yu,
L., Drumond, A., Durán-Quesada, A. M., and Nieto, R.: Oceanic and Terrestrial
Sources of Continental Precipitation, Rev. Geophys., 50, RG4003, <ext-link xlink:href="http://dx.doi.org/10.1029/2012RG000389" ext-link-type="DOI">10.1029/2012RG000389</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib15"><label>15</label><mixed-citation>Gimeno, L., Nieto, R., Vázquez, M., and Lavers, D. A.: Atmospheric
rivers: a mini-review, Front. Earth Sci., 2, <ext-link xlink:href="http://dx.doi.org/10.3389/feart.2014.00002" ext-link-type="DOI">10.3389/feart.2014.00002</ext-link>, 2014.</mixed-citation></ref>
      <ref id="bib1.bib16"><label>16</label><mixed-citation>Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D.,
and New, M.: A European daily high-resolution gridded data set of surface
temperature and precipitation for 1950–2006, J. Geophys. Res., 113, D20119,
<ext-link xlink:href="http://dx.doi.org/10.1029/2008JD010201" ext-link-type="DOI">10.1029/2008JD010201</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bib17"><label>17</label><mixed-citation>
Knippertz, P. and Wernli, H.: A Lagrangian Climatology of Tropical Moisture
Exports to the Northern Hemispheric Extratropics, J. Climate, 23, 987–1003, 2010.</mixed-citation></ref>
      <ref id="bib1.bib18"><label>18</label><mixed-citation>
Lavers, D. A. and Villarini, G.: The nexus between atmospheric rivers and
extreme precipitation across Europe, Geophys. Res. Lett., 40, 3259–3264, 2013.</mixed-citation></ref>
      <ref id="bib1.bib19"><label>19</label><mixed-citation>Lavers, D. A., Allan, R. P., Wood, E. F., Villarini, G., Brayshaw, D. J., and
Wade, A. J.: Winter floods in Britain are connected to atmospheric
rivers, Geophys. Res. Lett., 38, L23803, <ext-link xlink:href="http://dx.doi.org/10.1029/2011GL049783" ext-link-type="DOI">10.1029/2011GL049783</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bib20"><label>20</label><mixed-citation>Lavers, D. A., Villarini, G., Allan, R. P., Wood, E. F., and Wade, A. J.:
The detection of atmospheric rivers in atmospheric reanalyses and their
links to British winter floods and the large-scale climatic circulation, J.
Geophys. Res., 117, D20106, <ext-link xlink:href="http://dx.doi.org/10.1029/2012JD018027" ext-link-type="DOI">10.1029/2012JD018027</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib21"><label>21</label><mixed-citation>Liberato, M. L. R., Ramos, A. M., Trigo, R. M., Trigo, I. F.,
Durán-Quesada, A. M., Nieto, R., and Gimeno, L.: Moisture Sources and
Large-Scale Dynamics Associated With a Flash Flood Event, in: Lagrangian
Modeling of the Atmosphere, edited by: Lin, J., Brunner, D., Gerbig, C., Stohl,
A., Luhar, A., and Webley, P., American Geophysical Union, Washington, D.C., <ext-link xlink:href="http://dx.doi.org/10.1029/2012GM001244" ext-link-type="DOI">10.1029/2012GM001244</ext-link>, 2012.</mixed-citation></ref>
      <ref id="bib1.bib22"><label>22</label><mixed-citation>
Moore, B. J., Neiman, P. J., Ralph, F. M., and Barthold, F. E.: Physical
processes associated with heavy flooding rainfall in Nashville, Tennessee,
and vicinity during 1–2 May 2010: The role of an atmospheric river and
mesoscale convective systems, Mon. Weather Rev., 140, 358–378, 2012.</mixed-citation></ref>
      <ref id="bib1.bib23"><label>23</label><mixed-citation>
Neiman, P. J., Ralph, F. M., Wick, G. A., Lundquist, J. D., and Dettinger,
M. D.: Meteorological characteristics and overland precipitation impacts of
atmospheric rivers affecting the West Coast of North America based on eight
years of SSM/I satellite observations, J. Hydrometeorol., 9, 22–47, 2008.</mixed-citation></ref>
      <ref id="bib1.bib24"><label>24</label><mixed-citation>Nieto, R., Gimeno, L., Gallego, D., and Trigo, R. M.: Identification of major
sources of moisture and precipitation over Iceland, Meteorol. Zeit., 16, 37–44, 2007.
 </mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib25"><label>25</label><mixed-citation>
Numaguti, A.: Origin and recycling processes of precipitating water over the
Eurasian continent: Experiments using an atmospheric general circulation
model, J. Geophys. Res., 104, 1957–1972, 1999.</mixed-citation></ref>
      <ref id="bib1.bib26"><label>26</label><mixed-citation>
Ralph, F. M. and Dettinger, M. D.: Storms, floods, and the science of
atmospheric rivers, Eos Trans. AGU, 92, 265, 2011.</mixed-citation></ref>
      <ref id="bib1.bib27"><label>27</label><mixed-citation>
Ralph, F. M., Neiman, P. J., and Wick, G. A.: Satellite and CALJET aircraft
observations of atmospheric rivers over the eastern North Pacific Ocean
during the winter of 1997/98, Mon. Weather Rev., 132, 1721–1745, 2004.</mixed-citation></ref>
      <ref id="bib1.bib28"><label>28</label><mixed-citation>Ralph, F. M., Neiman, P. J., and Rotunno, R.: Dropsonde Observations in Low-Level
Jets Over the Northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean
Vertical-Profile and Atmospheric-River Characteristics, Mon. Weather Rev.,
133, 889–910, <ext-link xlink:href="http://dx.doi.org/10.1175/MWR2896.1" ext-link-type="DOI">10.1175/MWR2896.1</ext-link>, 2005.</mixed-citation></ref>
      <ref id="bib1.bib29"><label>29</label><mixed-citation>
Ralph, F. M., Coleman, T., Neiman, P. J., Zamora, R. J., Dettinger, M. D.:
Observed Impacts of Duration and Seasonality of Atmospheric-River Landfalls
on Soil Moisture and Runoff in Coastal Northern California, J. Hydrometeorol.,
14, 443–459, 2013.</mixed-citation></ref>
      <ref id="bib1.bib30"><label>30</label><mixed-citation>Ramos, A. M., Trigo, R. M., Liberato, M. L. R., and Tome, R.: Daily
precipitation extreme events in the Iberian Peninsula and its association
with Atmospheric Rivers, J. Hydrometeorol., 16, 579–597, <ext-link xlink:href="http://dx.doi.org/10.1175/JHM-D-14-0103.1" ext-link-type="DOI">10.1175/JHM-D-14-0103.1</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib31"><label>31</label><mixed-citation>
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: The Inland Penetration of
Atmospheric Rivers over Western North America: A Lagrangian Analysis, Mon.
Weather Rev., 143, 1924–1944, 2015.</mixed-citation></ref>
      <ref id="bib1.bib32"><label>32</label><mixed-citation>Ryoo, J.-M., Waliser, D. E., Waugh, D. W., Wong, S., Fetzer, E. J., and Fung,
I.: Classification of atmospheric river events on the U.S. West Coast using a
trajectory model, J. Geophys. Res.-Atmos., 120, 3007–3028, <ext-link xlink:href="http://dx.doi.org/10.1002/2014JD022023" ext-link-type="DOI">10.1002/2014JD022023</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bib33"><label>33</label><mixed-citation>
Sodemann, H. and Stohl, A.: Moisture Origin and Meridional Transport in
Atmospheric Rivers and Their Association with Multiple Cyclones, Mon. Weather
Rev., 141, 2850–2868, 2013.</mixed-citation></ref>
      <ref id="bib1.bib34"><label>34</label><mixed-citation>Sodemann, H., Schwierz, C., and Wernli, H.: Interannual variability of
Greenland winter precipitation sources: Lagrangian moisture diagnostic and
North Atlantic Oscillation influence, J. Geophys. Res., 113, D03107,
<ext-link xlink:href="http://dx.doi.org/10.1029/2007JD008503" ext-link-type="DOI">10.1029/2007JD008503</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bib35"><label>35</label><mixed-citation>
Stohl, A. and James, P. A.: Lagrangian Analysis of the atmospheric branch
of the global water cycle. Part I: Method description, validation, and
demonstration for the August 2002 flooding in Central Europe, J. Hydrometeorol.,
5, 656–678, 2004.</mixed-citation></ref>
      <ref id="bib1.bib36"><label>36</label><mixed-citation>
Stohl, A., Hittenberger, M., and Wotawa, G.: Validation of the Lagrangian
particle dispersion model FLEXPART against large-scale tracer experiment
data, Atmos. Environ., 32, 4245–4264, 1998.</mixed-citation></ref>
      <ref id="bib1.bib37"><label>37</label><mixed-citation>Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note:
The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem.
Phys., 5, 2461–2474, <ext-link xlink:href="http://dx.doi.org/10.5194/acp-5-2461-2005" ext-link-type="DOI">10.5194/acp-5-2461-2005</ext-link>, 2005.</mixed-citation></ref>
      <ref id="bib1.bib38"><label>38</label><mixed-citation>Stohl, A., Forster, C., and Sodemann, C.: Remote sources of water vapor
forming precipitation on the Norwegian west coast at 60<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N: A tale
of hurricanes and an atmospheric river, J. Geophys. Res., 113, D05102,
<ext-link xlink:href="http://dx.doi.org/10.1029/2007JD009006" ext-link-type="DOI">10.1029/2007JD009006</ext-link>, 2008.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib39"><label>39</label><mixed-citation>Trigo, R. M., Varino, F., Ramos, A. M., Valente, M. A., Zêzere, J. L.,
Vaquero, J. M., Gouveia, C. M., and Russo, A.: The record precipitation and
flood event in Iberia in December 1876: description and synoptic analysis,
Front. Earth Sci., 2, <ext-link xlink:href="http://dx.doi.org/10.3389/feart.2014.00003" ext-link-type="DOI">10.3389/feart.2014.00003</ext-link>, 2014.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bib40"><label>40</label><mixed-citation>
Zhu, Y. and Newell, R. E.: A proposed algorithm for moisture fluxes from
atmospheric rivers, Mon. Weather Rev., 126, 725–735, 1998.</mixed-citation></ref>

  </ref-list><app-group content-type="float"><app><title/>

    </app></app-group></back>
    <!--<article-title-html>Atmospheric rivers moisture sources from a Lagrangian perspective</article-title-html>
<abstract-html><p class="p">An automated atmospheric river (AR) detection algorithm is used for the
North Atlantic Ocean basin, allowing the identification of the major ARs
affecting western European coasts between 1979 and 2012 over the winter
half-year (October to March). The entire western coast of Europe was divided
into five domains, namely the Iberian Peninsula (9.75° W,
36–43.75° N), France (4.5° W, 43.75–50° N),
UK (4.5° W, 50–59° N), southern Scandinavia and the Netherlands
(5.25° E, 50–59° N), and northern Scandinavia (5.25° E, 59–70° N).
Following the identification of the main ARs that made landfall in western
Europe, a Lagrangian analysis was then applied in order to identify the main
areas where the moisture uptake was anomalous and contributed to the ARs
reaching each domain. The Lagrangian data set used was obtained from the
FLEXPART (FLEXible PARTicle dispersion) model global simulation from 1979 to 2012 and was forced by
ERA-Interim reanalysis on a 1° latitude–longitude grid.</p><p class="p">The results show that, in general, for all regions considered, the major
climatological areas for the anomalous moisture uptake extend along the
subtropical North Atlantic, from the Florida Peninsula (northward of
20° N) to each sink region, with the nearest coast to each
sink region always appearing as a local maximum. In addition, during AR
events the Atlantic subtropical source is reinforced and displaced, with a
slight northward movement of the sources found when the sink region is
positioned at higher latitudes. In conclusion, the results confirm not only the
anomalous advection of moisture linked to ARs from subtropical ocean areas
but also the existence of a tropical source, together with midlatitude
anomaly sources at some locations closer to AR landfalls.</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Bao, J-W., Michelson, S. A., Neiman, P. J., Ralph, F. M., and Wilczak, J.
M.: Interpretation of enhanced integrated water vapor bands associated with
extratropical cyclones: Their formation and connection to tropical moisture,
Mon. Weather Rev., 134, 1063–1080, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Castillo, R., Nieto R., Drumond, A., and Gimeno, L.: Estimating the temporal
domain when the discount of the net evaporation term affects the resulting
net precipitation pattern in the moisture budget using a 3-D Lagrangian
approach, PLoS ONE, 9, e99046, <a href="http://dx.doi.org/10.1371/journal.pone.0099046" target="_blank">doi:10.1371/journal.pone.0099046</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Couto, F. T., Salgado, R., and Costa, M. J.: Analysis of intense rainfall events
on Madeira Island during the 2009/2010 winter, Nat. Hazards Earth Syst. Sci.,
12, 2225–2240, <a href="http://dx.doi.org/10.5194/nhess-12-2225-2012" target="_blank">doi:10.5194/nhess-12-2225-2012</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
Couto, F. T., Salgado, R., Costa, M. J., and Prior, V.: Precipitation in the
Madeira Is- land over a 10-year period and the meridional water vapour
transport during the winter seasons, Int. J. Climatol., 35, 3748–3759,
<a href="http://dx.doi.org/10.1002/joc.4243" target="_blank">doi:10.1002/joc.4243</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Dacre, H., Clark, P., Martinez-Alvarado, O., Stringer, M., and Lavers, D.:
How do atmospheric rivers form?, B. Am. Meteorol. Soc., 96, 1243–1255,
<a href="http://dx.doi.org/10.1175/BAMS-D-14-00031.1" target="_blank">doi:10.1175/BAMS-D-14-00031.1</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
Dee, D. P., Uppala, S. M., Simmons, A. J., et al.: The ERA-Interim reanalysis: configuration
and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc.,
137, 553–597, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>7</label><mixed-citation>
Dettinger, M., Ralph, F. M., Das, T., Neiman, P. J., and Cayan, D. R.:
Atmospheric Rivers, Floods and the Water Resources of California, Water, 3, 445–478, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>8</label><mixed-citation>
Dettinger, M., Ralph, F. M., and Lavers, D.: Setting the stage for a global
science of atmospheric rivers, Eos, 96, <a href="http://dx.doi.org/10.1029/2015EO038675" target="_blank">doi:10.1029/2015EO038675</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>9</label><mixed-citation>
Drumond, A., Gimeno, L., and Nieto, R.: On the contribution of the Tropical
Western Hemisphere Warm Pool source of moisture to the northern hemisphere
precipitation through a lagrangian approach, J. Geophys. Res., 116, D00Q04,
<a href="http://dx.doi.org/10.1029/2010JD015397" target="_blank">doi:10.1029/2010JD015397</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>10</label><mixed-citation>
Ferreira, J. A., Liberato, M. L. R., and Ramos, A. M.: On the relationship between
atmospheric water vapour transport and extra-tropical cyclones development,
Phys. Chem. Earth, <a href="http://dx.doi.org/10.1016/j.pce.2016.01.001" target="_blank">doi:10.1016/j.pce.2016.01.001</a>, in press, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>11</label><mixed-citation>
Garaboa-Paz, D., Eiras-Barca, J., Huhn, F., and Pérez-Muñuzuri, V.:
Lagrangian coherent structures along atmospheric rivers, Chaos, 25, 063105,
<a href="http://dx.doi.org/10.1063/1.4919768" target="_blank">doi:10.1063/1.4919768</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>12</label><mixed-citation>
Gimeno, L., Drumond, A., Nieto, R., Trigo, R. M., and Stohl, A.: On the origin
of continental precipitation, Geophys. Res. Lett., 37, L13804, <a href="http://dx.doi.org/10.1029/2010GL043712" target="_blank">doi:10.1029/2010GL043712</a>, 2010a.
</mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>13</label><mixed-citation>
Gimeno, L., Nieto, R., Trigo, R. M., Vicente, S., and Lopez-Moreno, J. I.:
Where does the Iberian Peninsula moisture come from? An answer based on a
Largrangian approach, J. Hydrometeorol., 11, 421–436, <a href="http://dx.doi.org/10.1175/2009JHM1182.1" target="_blank">doi:10.1175/2009JHM1182.1</a>, 2010b.
</mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>14</label><mixed-citation>
Gimeno, L., Stohl, A., Trigo, R. M., Domínguez, F., Yoshimura, K., Yu,
L., Drumond, A., Durán-Quesada, A. M., and Nieto, R.: Oceanic and Terrestrial
Sources of Continental Precipitation, Rev. Geophys., 50, RG4003, <a href="http://dx.doi.org/10.1029/2012RG000389" target="_blank">doi:10.1029/2012RG000389</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>15</label><mixed-citation>
Gimeno, L., Nieto, R., Vázquez, M., and Lavers, D. A.: Atmospheric
rivers: a mini-review, Front. Earth Sci., 2, <a href="http://dx.doi.org/10.3389/feart.2014.00002" target="_blank">doi:10.3389/feart.2014.00002</a>, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>16</label><mixed-citation>
Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D.,
and New, M.: A European daily high-resolution gridded data set of surface
temperature and precipitation for 1950–2006, J. Geophys. Res., 113, D20119,
<a href="http://dx.doi.org/10.1029/2008JD010201" target="_blank">doi:10.1029/2008JD010201</a>, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>17</label><mixed-citation>
Knippertz, P. and Wernli, H.: A Lagrangian Climatology of Tropical Moisture
Exports to the Northern Hemispheric Extratropics, J. Climate, 23, 987–1003, 2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>18</label><mixed-citation>
Lavers, D. A. and Villarini, G.: The nexus between atmospheric rivers and
extreme precipitation across Europe, Geophys. Res. Lett., 40, 3259–3264, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>19</label><mixed-citation>
Lavers, D. A., Allan, R. P., Wood, E. F., Villarini, G., Brayshaw, D. J., and
Wade, A. J.: Winter floods in Britain are connected to atmospheric
rivers, Geophys. Res. Lett., 38, L23803, <a href="http://dx.doi.org/10.1029/2011GL049783" target="_blank">doi:10.1029/2011GL049783</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>20</label><mixed-citation>
Lavers, D. A., Villarini, G., Allan, R. P., Wood, E. F., and Wade, A. J.:
The detection of atmospheric rivers in atmospheric reanalyses and their
links to British winter floods and the large-scale climatic circulation, J.
Geophys. Res., 117, D20106, <a href="http://dx.doi.org/10.1029/2012JD018027" target="_blank">doi:10.1029/2012JD018027</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>21</label><mixed-citation>
Liberato, M. L. R., Ramos, A. M., Trigo, R. M., Trigo, I. F.,
Durán-Quesada, A. M., Nieto, R., and Gimeno, L.: Moisture Sources and
Large-Scale Dynamics Associated With a Flash Flood Event, in: Lagrangian
Modeling of the Atmosphere, edited by: Lin, J., Brunner, D., Gerbig, C., Stohl,
A., Luhar, A., and Webley, P., American Geophysical Union, Washington, D.C., <a href="http://dx.doi.org/10.1029/2012GM001244" target="_blank">doi:10.1029/2012GM001244</a>, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>22</label><mixed-citation>
Moore, B. J., Neiman, P. J., Ralph, F. M., and Barthold, F. E.: Physical
processes associated with heavy flooding rainfall in Nashville, Tennessee,
and vicinity during 1–2 May 2010: The role of an atmospheric river and
mesoscale convective systems, Mon. Weather Rev., 140, 358–378, 2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>23</label><mixed-citation>
Neiman, P. J., Ralph, F. M., Wick, G. A., Lundquist, J. D., and Dettinger,
M. D.: Meteorological characteristics and overland precipitation impacts of
atmospheric rivers affecting the West Coast of North America based on eight
years of SSM/I satellite observations, J. Hydrometeorol., 9, 22–47, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>24</label><mixed-citation>
Nieto, R., Gimeno, L., Gallego, D., and Trigo, R. M.: Identification of major
sources of moisture and precipitation over Iceland, Meteorol. Zeit., 16, 37–44, 2007.

</mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>25</label><mixed-citation>
Numaguti, A.: Origin and recycling processes of precipitating water over the
Eurasian continent: Experiments using an atmospheric general circulation
model, J. Geophys. Res., 104, 1957–1972, 1999.
</mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>26</label><mixed-citation>
Ralph, F. M. and Dettinger, M. D.: Storms, floods, and the science of
atmospheric rivers, Eos Trans. AGU, 92, 265, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>27</label><mixed-citation>
Ralph, F. M., Neiman, P. J., and Wick, G. A.: Satellite and CALJET aircraft
observations of atmospheric rivers over the eastern North Pacific Ocean
during the winter of 1997/98, Mon. Weather Rev., 132, 1721–1745, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>28</label><mixed-citation>
Ralph, F. M., Neiman, P. J., and Rotunno, R.: Dropsonde Observations in Low-Level
Jets Over the Northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean
Vertical-Profile and Atmospheric-River Characteristics, Mon. Weather Rev.,
133, 889–910, <a href="http://dx.doi.org/10.1175/MWR2896.1" target="_blank">doi:10.1175/MWR2896.1</a>, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>29</label><mixed-citation>
Ralph, F. M., Coleman, T., Neiman, P. J., Zamora, R. J., Dettinger, M. D.:
Observed Impacts of Duration and Seasonality of Atmospheric-River Landfalls
on Soil Moisture and Runoff in Coastal Northern California, J. Hydrometeorol.,
14, 443–459, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>30</label><mixed-citation>
Ramos, A. M., Trigo, R. M., Liberato, M. L. R., and Tome, R.: Daily
precipitation extreme events in the Iberian Peninsula and its association
with Atmospheric Rivers, J. Hydrometeorol., 16, 579–597, <a href="http://dx.doi.org/10.1175/JHM-D-14-0103.1" target="_blank">doi:10.1175/JHM-D-14-0103.1</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>31</label><mixed-citation>
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: The Inland Penetration of
Atmospheric Rivers over Western North America: A Lagrangian Analysis, Mon.
Weather Rev., 143, 1924–1944, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>32</label><mixed-citation>
Ryoo, J.-M., Waliser, D. E., Waugh, D. W., Wong, S., Fetzer, E. J., and Fung,
I.: Classification of atmospheric river events on the U.S. West Coast using a
trajectory model, J. Geophys. Res.-Atmos., 120, 3007–3028, <a href="http://dx.doi.org/10.1002/2014JD022023" target="_blank">doi:10.1002/2014JD022023</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>33</label><mixed-citation>
Sodemann, H. and Stohl, A.: Moisture Origin and Meridional Transport in
Atmospheric Rivers and Their Association with Multiple Cyclones, Mon. Weather
Rev., 141, 2850–2868, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib34"><label>34</label><mixed-citation>
Sodemann, H., Schwierz, C., and Wernli, H.: Interannual variability of
Greenland winter precipitation sources: Lagrangian moisture diagnostic and
North Atlantic Oscillation influence, J. Geophys. Res., 113, D03107,
<a href="http://dx.doi.org/10.1029/2007JD008503" target="_blank">doi:10.1029/2007JD008503</a>, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>35</label><mixed-citation>
Stohl, A. and James, P. A.: Lagrangian Analysis of the atmospheric branch
of the global water cycle. Part I: Method description, validation, and
demonstration for the August 2002 flooding in Central Europe, J. Hydrometeorol.,
5, 656–678, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>36</label><mixed-citation>
Stohl, A., Hittenberger, M., and Wotawa, G.: Validation of the Lagrangian
particle dispersion model FLEXPART against large-scale tracer experiment
data, Atmos. Environ., 32, 4245–4264, 1998.
</mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>37</label><mixed-citation>
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note:
The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem.
Phys., 5, 2461–2474, <a href="http://dx.doi.org/10.5194/acp-5-2461-2005" target="_blank">doi:10.5194/acp-5-2461-2005</a>, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>38</label><mixed-citation>
Stohl, A., Forster, C., and Sodemann, C.: Remote sources of water vapor
forming precipitation on the Norwegian west coast at 60° N: A tale
of hurricanes and an atmospheric river, J. Geophys. Res., 113, D05102,
<a href="http://dx.doi.org/10.1029/2007JD009006" target="_blank">doi:10.1029/2007JD009006</a>, 2008.

</mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>39</label><mixed-citation>
Trigo, R. M., Varino, F., Ramos, A. M., Valente, M. A., Zêzere, J. L.,
Vaquero, J. M., Gouveia, C. M., and Russo, A.: The record precipitation and
flood event in Iberia in December 1876: description and synoptic analysis,
Front. Earth Sci., 2, <a href="http://dx.doi.org/10.3389/feart.2014.00003" target="_blank">doi:10.3389/feart.2014.00003</a>, 2014.

</mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>40</label><mixed-citation>
Zhu, Y. and Newell, R. E.: A proposed algorithm for moisture fluxes from
atmospheric rivers, Mon. Weather Rev., 126, 725–735, 1998.
</mixed-citation></ref-html>--></article>
