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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:oasis="http://docs.oasis-open.org/ns/oasis-exchange/table" 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-8-1247-2017</article-id><title-group><article-title>Evaluation of the moisture sources in two extreme landfalling atmospheric river events using<?xmltex \hack{\break}?> an Eulerian WRF tracers tool</article-title>
      </title-group><?xmltex \runningtitle{Moisture sources in ARs using WRF tracers}?><?xmltex \runningauthor{J. Eiras-Barca et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Eiras-Barca</surname><given-names>Jorge</given-names></name>
          <email>jorge.eiras@usc.es</email><email>jorge.eiras.b@gmail.com</email>
        <ext-link>https://orcid.org/0000-0003-4401-5944</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Dominguez</surname><given-names>Francina</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Hu</surname><given-names>Huancui</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Garaboa-Paz</surname><given-names>Daniel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Miguez-Macho</surname><given-names>Gonzalo</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4259-7883</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Non-Linear Physics Group, Universidade de Santiago de Compostela, Galicia, Spain</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana–Champaign, IL, USA</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Jorge Eiras-Barca (jorge.eiras@usc.es, jorge.eiras.b@gmail.com)</corresp></author-notes><pub-date><day>22</day><month>December</month><year>2017</year></pub-date>
      
      <volume>8</volume>
      <issue>4</issue>
      <fpage>1247</fpage><lpage>1261</lpage>
      <history>
        <date date-type="received"><day>16</day><month>June</month><year>2017</year></date>
           <date date-type="rev-request"><day>27</day><month>June</month><year>2017</year></date>
           <date date-type="rev-recd"><day>23</day><month>October</month><year>2017</year></date>
           <date date-type="accepted"><day>31</day><month>October</month><year>2017</year></date>
      </history>
      <permissions>
        
        
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017.html">This article is available from https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017.html</self-uri><self-uri xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017.pdf">The full text article is available as a PDF file from https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017.pdf</self-uri>
      <abstract>
    <p id="d1e123">A new 3-D tracer tool is coupled to the WRF model to analyze the origin of
the moisture in two extreme atmospheric river (AR) events: the so-called
“Great Coastal Gale of 2007” in the
Pacific Ocean and the “Great Storm of
1987” in the North Atlantic. Results show that
between 80 and 90 % of moisture advected by the ARs, and a high
percentage of the total precipitation produced by the systems have a
tropical origin. The tropical contribution to precipitation is in general
above 50 % and largely exceeds this value in the most affected areas.
Local convergence transport is responsible for the remaining moisture and
precipitation. The ratio of tropical moisture to total moisture is maximized
as the cold front arrives on land. Vertical cross sections of the moisture
content suggest that the maximum in tropical humidity does not necessarily
coincide with the low-level jet (LLJ) of the extratropical cyclone. Instead,
the amount of tropical humidity is maximized in the lowest atmospheric level
in southern latitudes and can be located above, below or ahead of the LLJ
in northern latitudes in both analyzed cases.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

      <?xmltex \hack{\allowdisplaybreaks}?>
<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p id="d1e135">Atmospheric rivers (hereafter, ARs) are long and narrow structures in the
lower troposphere that carry large amounts of water vapor <xref ref-type="bibr" rid="bib1.bibx72" id="paren.1"/>.
<xref ref-type="bibr" rid="bib1.bibx22" id="text.2"/> have estimated that ARs have a median length of about
3600 km, a median length <inline-formula><mml:math id="M1" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> width ratio of about 7 and a mean integrated vapor
transport (IVT) of 370 kg m<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> s<inline-formula><mml:math id="M3" 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>. ARs are associated with the
pre-cold frontal region and the warm conveyor belt (WCB) of extratropical
cyclones <xref ref-type="bibr" rid="bib1.bibx20" id="paren.3"/>. The maximum moisture flux often occurs within
the low-level jet (LLJ) located at around 1 km height along the cold frontal
boundary, and for this reason ARs and the LLJ are sometimes identified with each
other <xref ref-type="bibr" rid="bib1.bibx14" id="paren.4"/>. However, to account for most of the high
IVT and moisture content defining an AR, usually a wider region encompassing
the layers below 2.5 km ahead of the cold front must be considered
<xref ref-type="bibr" rid="bib1.bibx56 bib1.bibx57" id="paren.5"/>. On occasion, the relationship between ARs and
cyclones has been shown to be complex, with documented cases in which multiple
cyclones are associated with a single AR <xref ref-type="bibr" rid="bib1.bibx69" id="paren.6"/>.</p>
      <p id="d1e188">ARs supply moisture to the WCB of the cyclones and are therefore considered
as one of the potential precursors of extreme precipitation, particularly
when landfall occurs <xref ref-type="bibr" rid="bib1.bibx20" id="paren.7"><named-content content-type="pre">e.g.,</named-content></xref>. The relationship between ARs
and flood events has been extensively analyzed for the US West
Coast region
<xref ref-type="bibr" rid="bib1.bibx24 bib1.bibx57 bib1.bibx58 bib1.bibx56 bib1.bibx59 bib1.bibx3 bib1.bibx51 bib1.bibx52 bib1.bibx40 bib1.bibx13 bib1.bibx15 bib1.bibx70 bib1.bibx71 bib1.bibx63 bib1.bibx32" id="paren.8"><named-content content-type="pre">e.g.,</named-content></xref>,
Europe
<xref ref-type="bibr" rid="bib1.bibx37 bib1.bibx38 bib1.bibx39 bib1.bibx35 bib1.bibx36 bib1.bibx60 bib1.bibx61 bib1.bibx19 bib1.bibx5" id="paren.9"/>
and other regions worldwide <xref ref-type="bibr" rid="bib1.bibx42 bib1.bibx49" id="paren.10"><named-content content-type="pre">e.g.,</named-content></xref>. It is
important to better understand the physical mechanisms leading to extreme
flooding associated with ARs, considering their impacts on human and natural
systems and the mounting evidence that ARs are projected to become more
frequent and intense in the future
<xref ref-type="bibr" rid="bib1.bibx13 bib1.bibx39 bib1.bibx54" id="paren.11"><named-content content-type="pre">e.g.,</named-content></xref>.</p>
      <p id="d1e214">Between three and five ARs can be found per hemisphere at any given time
<xref ref-type="bibr" rid="bib1.bibx72" id="paren.12"/>, accounting for approximately 84 % of the meridional
IVT for the Northern Hemisphere and about 88 % in the Southern Hemisphere
<xref ref-type="bibr" rid="bib1.bibx22" id="paren.13"/>. Since these structures can transport an amount of
precipitable water equivalent to several times the discharge of the
Mississippi River <xref ref-type="bibr" rid="bib1.bibx55" id="paren.14"/>, ARs have been identified as a primary
feature of the global water cycle.</p>
      <p id="d1e226">There are several proposed methods of AR detection, most of which are based
on thresholds of integrated water vapor (IWV) and/or IVT, shape criteria,
and from satellite or reanalysis data
<xref ref-type="bibr" rid="bib1.bibx56 bib1.bibx3 bib1.bibx37 bib1.bibx38 bib1.bibx13 bib1.bibx50 bib1.bibx60 bib1.bibx19 bib1.bibx5" id="paren.15"><named-content content-type="pre">e.g.,</named-content></xref>.
<xref ref-type="bibr" rid="bib1.bibx22" id="text.16"/> developed a global detection method using filters of
intensity, direction, geometry and coherence of the structures. More
recently, <xref ref-type="bibr" rid="bib1.bibx19" id="text.17"/> proposed a combined IVT and IWV
variable-threshold detection algorithm, which operates both in summer and
winter months. These objective detection criteria have shown that AR
structures of IWV and IVT can extend from the tropics into midlatitudes;
however, they do not provide information about the source and sink regions of
AR water vapor.</p>
      <p id="d1e241">Tropical moisture exports have been identified as a primary source of
moisture for ARs in Europe and the US West Coast
<xref ref-type="bibr" rid="bib1.bibx14" id="paren.18"/>. AR structures link remote sources of moisture from
the tropics to midlatitudes through long corridors of advection
<xref ref-type="bibr" rid="bib1.bibx33 bib1.bibx69 bib1.bibx34 bib1.bibx65 bib1.bibx60" id="paren.19"><named-content content-type="pre">e.g.,</named-content></xref>.
These studies have primarily used backward Lagrangian tools to evaluate the
source–sink regions. However, moisture from midlatitudes (local sources) has
also been identified as an important source of water vapor convergence in AR
events <xref ref-type="bibr" rid="bib1.bibx14" id="paren.20"/>. <xref ref-type="bibr" rid="bib1.bibx61" id="text.21"/> used the FLEXible PARTicle
dispersion model (FLEXPART) to show that both tropical and local
sources of moisture are present in AR landfall events for different European
latitudes.</p>
      <p id="d1e258">Some authors argue that local sources are primarily responsible for the high
water vapor content within the AR core
<xref ref-type="bibr" rid="bib1.bibx3 bib1.bibx10 bib1.bibx12" id="paren.22"/>. By calculating the water vapor budget
of 200 extratropical cyclones, <xref ref-type="bibr" rid="bib1.bibx12" id="text.23"/> conclude that tropical
moisture reaching the extratropics only contributes to mid-level moisture,
above the boundary layer. Following this perspective, ARs can be thought of
as the footprints left behind the cyclone pathway, and not as a conduit for
meridional transport of water vapor and latent heat. One possible explanation
for the lack of agreement may be the sensitivity to the physics and
parametrization schemes used in the latter analysis <xref ref-type="bibr" rid="bib1.bibx5" id="paren.24"/>. The
current understanding is that tropical moisture exports can provide a
significant amount of moisture to ARs. Most of them also incorporate
midlatitude sources of vapor along their path <xref ref-type="bibr" rid="bib1.bibx14" id="paren.25"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p id="d1e275">Integrated vapor transport (IVT, vectors, kg m<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> s<inline-formula><mml:math id="M5" 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>),
sea level pressure (isobars, hPa) and integrated water vapor (IWV,
background, kg m<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula>) fields for both the Great Coastal Gale of
2007 <bold>(a–d)</bold> and the Great Storm of 1987 <bold>(e–h)</bold> events
throughout a 4-day time frame. Source: ERA-Interim.</p></caption>
        <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f01.jpg"/>

      </fig>

      <p id="d1e326">Considering that there is still an important discussion related to the origin
of moisture in ARs, in this paper, we use a new forward moisture tracer
tool coupled to the Weather Research and Forecast (WRF) model
<xref ref-type="bibr" rid="bib1.bibx47 bib1.bibx16 bib1.bibx30" id="paren.26"/> to evaluate the
moisture sources of two particularly extreme AR case studies, as well as the
transport mechanism of this humidity. The selected cases were associated
with extreme precipitation and flooding that led to significant socioeconomic
impacts. The first selected AR developed over the Pacific Ocean and affected
the western coast of North America, whereas the second AR developed over the
Atlantic Ocean and impacted the western coast of the Iberian Peninsula. The
tracer tool allows us to track the tropical moisture associated with these
two events and evaluate the relative contribution of this tropical moisture
to total moisture and precipitation. In addition, the WRF tracer tool also
provides information about the vertical distribution of tropical moisture, as
well as the position of the maximum of moisture with regard to the LLJ.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p id="d1e334">WRF output total precipitation for the Great Coastal
Gale of 2007 <bold>(a)</bold> and the Great Storm of 1987 <bold>(c)</bold> against observations
from LIVNEH <bold>(b)</bold> and IBERIA02 <bold>(d)</bold> for the same 24 h
period.</p></caption>
        <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f02.png"/>

      </fig>

</sec>
<sec id="Ch1.S2">
  <title>Data and methods</title>
<sec id="Ch1.S2.SS1">
  <title>Data</title>
      <p id="d1e366">Both events were very intense in terms of IVT and IWV and are well detected
by different methods <xref ref-type="bibr" rid="bib1.bibx22 bib1.bibx19 bib1.bibx5" id="paren.27"/>. The first
AR occurred on December 2007, affecting mostly the Pacific Northwest region
of the United States (Fig. <xref ref-type="fig" rid="Ch1.F1"/>a–d). Locally known as the
“Great Coastal Gale of 2007”, this event primarily impacted the western
state of Washington, and the associated flooding resulted in approximately
USD 680 million direct losses from three severely impacted counties in the
state <xref ref-type="bibr" rid="bib1.bibx2 bib1.bibx17" id="paren.28"/> and 11 fatalities <xref ref-type="bibr" rid="bib1.bibx53" id="paren.29"/>.
Formed from the remnants of the two typhoons Hagibis and Mitag, the event produced hurricane force winds <xref ref-type="bibr" rid="bib1.bibx11" id="paren.30"/>. The rapid and explosive
development of the cyclone (the central pressure fell more than <inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mn mathvariant="normal">24</mml:mn><mml:mo>⋅</mml:mo><mml:mi>sin⁡</mml:mi><mml:mi mathvariant="italic">φ</mml:mi><mml:mo>/</mml:mo><mml:mi>sin⁡</mml:mi></mml:mrow></mml:math></inline-formula> (60<inline-formula><mml:math id="M8" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) hPa in 24 h, where <inline-formula><mml:math id="M9" display="inline"><mml:mi mathvariant="italic">φ</mml:mi></mml:math></inline-formula> is the given
latitude) is shown in Figs. <xref ref-type="fig" rid="Ch1.F1"/>a–d and
<xref ref-type="fig" rid="App1.Ch1.F1"/> in Appendix A. The selected AR case was the third and most intense of a series of
three storms and led to extreme precipitation <xref ref-type="bibr" rid="bib1.bibx53" id="paren.31"/>. The
landfalling event and the resulting precipitation is shown in
Figs. <xref ref-type="fig" rid="Ch1.F1"/>d and <xref ref-type="fig" rid="Ch1.F2"/>d, respectively.</p>
      <p id="d1e430">The episode developed from the merging of a cold front, already undergoing wave
development, and a faster moving low pressure system catching up from behind.
Both systems originated from typhoons and already had a high water vapor
content. The interaction between the two resulted in an instant occlusion-like
mechanism that led to the rapid deepening of the combined cyclone over the
Pacific.</p>
      <p id="d1e433">Figure <xref ref-type="fig" rid="Ch1.F1"/>h shows the explosive cyclogenesis for the European
event. In this case, there is also a complex development process, with the
interaction between the remnants of a tropical system with high water vapor
content and a wave on the long frontal boundary across the North Atlantic as
a
precursor of the explosive cyclogenesis occurring northwest of the Iberian
Peninsula (see Fig. A2 in Appendix A).</p>
      <p id="d1e438">The water vapor signature of the second case, which developed during October 1987,
extended from the western tropical Atlantic Ocean to the Iberian
Peninsula and British Isles. This event is the well-known “Great Storm of
1987”, with reported losses of millions of pounds and 18 fatalities over the
British Isles <xref ref-type="bibr" rid="bib1.bibx9" id="paren.32"><named-content content-type="pre">e.g.,</named-content></xref>. For this case, <xref ref-type="bibr" rid="bib1.bibx67" id="text.33"/>
showed that two-thirds of the central pressure falling could be ascribed to
latent heat release, which suggests that the AR played a key role in the fast
deepening of the cyclone (35 hPa of pressure drop in 24 h)
(Fig. <xref ref-type="fig" rid="Ch1.F1"/>f–h). Figure A1 in Appendix A shows how the
cooperative linkage between a trough in the tropopause and low-level
baroclinicity contributed to the rapid growth of the system as well
<xref ref-type="bibr" rid="bib1.bibx27" id="paren.34"/>. The resulting precipitation (Fig. <xref ref-type="fig" rid="Ch1.F2"/>b)
was reported at above 100 mm throughout the Spanish region of Galicia, shown in
Fig. <xref ref-type="fig" rid="Ch1.F2"/>b.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>The Eulerian tracer tool</title>
      <p id="d1e465">The Eulerian tracer model is based on coupling a moisture tagging technique
with the WRF meteorological model. The strategy
consists in replicating the prognostic equations for the different
moisture species with equations for moisture tracers. A moisture tracer in
this context is defined as moisture originating from a predetermined source.
The set of equations for tracers is solved coupled to the model's governing
equations, meaning that tracers undergo turbulent diffusion with the same
eddy diffusivities as their full moisture counterparts, and that convection
and microphysics processes for tracers mimic those for full moisture, with
the assumption that phase changes among the different tracer species occur in
amounts proportional to the tracer fraction in the species undergoing the
change. The tracer tool running coupled to the model can separate moisture
from different sources with a very small error (less than 1 % in
traceability). Thus, the tracer tool is very accurate in the model world,
while the uncertainty in the real word is due to the WRF model error. A more
in-depth description of the Eulerian tracer tool and validation results can
be found in <xref ref-type="bibr" rid="bib1.bibx30" id="text.35"/>.</p>
      <p id="d1e471">The Eulerian tracer tool operates as follows: a wide region in the domain
covering the tropical latitudes is set up as a three-dimensional tracer mask.
All the water vapor in this three-dimensional volume (including the water
vapor evaporated and advected into the mask region) is tracked in space and
time. Notably, while previous moisture tracer configurations in WRF
focused on tracking water that evaporated from a two-dimensional region at
the surface <xref ref-type="bibr" rid="bib1.bibx16 bib1.bibx1" id="paren.36"><named-content content-type="pre">e.g.,</named-content></xref>, in this study all
the moisture in a three-dimensional volume (including the water vapor
evaporated and advected into the masked region) is tracked in space and time.
For details, see <xref ref-type="bibr" rid="bib1.bibx30" id="text.37"/>. Figure <xref ref-type="fig" rid="Ch1.F3"/> shows
the masks labeled in red for the Pacific (panel a) and Atlantic (panel b)
simulations. Once the simulation starts, the model tracks the humidity
originating from within the mask at any time, and the quantity of this
moisture is known in relation to the total moisture content at each point of
the domain, throughout the entire simulation. Similar to the rest of the
moisture, the “tagged” water vapor can change phase, and the fraction of
the condensed phase to the total condensate is also reported in the model
output.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p id="d1e486">Domains of the WRF simulation (blue) for the Great Coastal
Gale of 2007 <bold>(a)</bold> and the Great Storm of 1987 <bold>(b)</bold>. Areas highlighted
in red correspond to the masked region where the moisture is initially
labeled as tracer.</p></caption>
          <?xmltex \igopts{width=298.753937pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f03.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><caption><p id="d1e504">Absolute value of IVT in kilograms per meter per second for the Pacific
event from WRF <bold>(a)</bold> and MERRA <bold>(b)</bold> as well as for the
Atlantic event from WRF <bold>(c)</bold> and MERRA <bold>(d)</bold>.</p></caption>
          <?xmltex \igopts{width=384.112205pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f04.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p id="d1e527"><bold>(a)</bold> Total water vapor mixing ratio in grams per kilogram at
3 December 2007 12:00 UTC for the Pacific domain. <bold>(b)</bold> Tracers water
vapor mixing ratio in grams per kilogram at the same time and domain.
<bold>(c)</bold> Vertical cross sections of <bold>(a)</bold>. <bold>(d)</bold> Vertical
cross sections of <bold>(b)</bold>.</p></caption>
          <?xmltex \igopts{width=384.112205pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f05.png"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS3">
  <title>WRF simulations setup</title>
      <p id="d1e559">We use WRF 3.4.1 to simulate
these two events. For the Pacific case, the WRF horizontal resolution is
15 km and the vertical column is divided into 40 levels. For the Atlantic
simulation, grid spacing is 20 km in the horizontal and there are 50
vertical levels. Both simulations cover a period of 10 days, from
26 November 2007 in the Pacific case and from 8 October 1987 in the Atlantic
simulation. The moisture tracer tool is implemented in the Yonssei
University (YSU) planetary boundary layer parameterization
<xref ref-type="bibr" rid="bib1.bibx26 bib1.bibx66 bib1.bibx28 bib1.bibx29" id="paren.38"/>, the Kain–Fritsch convection scheme
<xref ref-type="bibr" rid="bib1.bibx31" id="paren.39"/> and the WRF Single-Moment 6-Class Microphysics Scheme
(WSM6) <xref ref-type="bibr" rid="bib1.bibx25" id="paren.40"/>, which are the parametrizations employed in the
simulations. In addition, the Rapid Radiative Transfer Model (RRTM)
<xref ref-type="bibr" rid="bib1.bibx48" id="paren.41"/> and Dudhia <xref ref-type="bibr" rid="bib1.bibx18" id="paren.42"/> schemes were used for long-wave and shortwave radiation, respectively. Spectral nudging of waves above
the boundary layer, longer than 1000 km, with a relaxation timescale of 1 h, is applied to avoid distortion of the large-scale circulation within
the regional model domain due to the interaction between the model's solution
and the lateral boundary conditions
<xref ref-type="bibr" rid="bib1.bibx45 bib1.bibx46" id="paren.43"/>. Further descriptions about WRF can
be found in <xref ref-type="bibr" rid="bib1.bibx68" id="text.44"/> or <xref ref-type="bibr" rid="bib1.bibx44" id="text.45"/>. Finally, considering that the
ECMWF reanalysis (ERA-Interim) has been shown to be a reliable tool in the
analysis of ARs <xref ref-type="bibr" rid="bib1.bibx64" id="paren.46"/>, the dataset provides lateral boundary and
initial conditions for the runs.</p>
      <p id="d1e590">Since spectral nudging has been used in the simulations, the large-scale
circulation in the model closely follows ERA-Interim and no further
validation is required <xref ref-type="bibr" rid="bib1.bibx21" id="paren.47"/>. Water vapor is not nudged to
ensure the mass conservation needed for the traceability of humidity from
different sources. Given that the subject of this study is moisture transport
and precipitation, we focus validations on these two variables.</p>
      <p id="d1e596">Finally, the integrated column of water vapor, and the integrated column
of water vapor tracers (<inline-formula><mml:math id="M10" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">IWV</mml:mi><mml:mi mathvariant="normal">TR</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>) can both be calculated
from the WRF simulations using Eqs. (2) and (3), respectively, where <inline-formula><mml:math id="M11" display="inline"><mml:mi>q</mml:mi></mml:math></inline-formula> is
the specific humidity, <inline-formula><mml:math id="M12" display="inline"><mml:mi>g</mml:mi></mml:math></inline-formula> is gravity, <inline-formula><mml:math id="M13" display="inline"><mml:mi>u</mml:mi></mml:math></inline-formula> and <inline-formula><mml:math id="M14" display="inline"><mml:mi>v</mml:mi></mml:math></inline-formula> represent the wind
fields, sfc is the land surface, and <inline-formula><mml:math id="M15" display="inline"><mml:mi>l</mml:mi></mml:math></inline-formula> is the highest model level, well
above the tropopause. The conversion between specific humidity (<inline-formula><mml:math id="M16" display="inline"><mml:mi>q</mml:mi></mml:math></inline-formula>) and
mixing ratio (<inline-formula><mml:math id="M17" display="inline"><mml:mi>w</mml:mi></mml:math></inline-formula>) has been performed using Eq. (4).

                <disp-formula specific-use="align" content-type="numbered"><mml:math id="M18" display="block"><mml:mtable displaystyle="true"><mml:mlabeledtr id="Ch1.E1"><mml:mtd/><mml:mtd><mml:mstyle displaystyle="true" class="stylechange"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mi mathvariant="normal">IVT</mml:mi><mml:mo>=</mml:mo><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:mtext>sfc</mml:mtext><mml:mi>l</mml:mi></mml:munderover><mml:mi>q</mml:mi><mml:mi mathvariant="bold-italic">u</mml:mi><mml:mtext>d</mml:mtext><mml:mi>p</mml:mi></mml:mfenced></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E2"><mml:mtd/><mml:mtd><mml:mstyle displaystyle="true" class="stylechange"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mi mathvariant="normal">IWV</mml:mi><mml:mo>=</mml:mo><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:mtext>sfc</mml:mtext><mml:mi>l</mml:mi></mml:munderover><mml:mi>q</mml:mi><mml:mtext>d</mml:mtext><mml:mi>p</mml:mi></mml:mrow></mml:mtd></mml:mlabeledtr></mml:mtable></mml:math></disp-formula></p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p id="d1e730">Same as Fig. <xref ref-type="fig" rid="Ch1.F5"/> but for the European domain in the
Great Storm of 1987 (15 October 1987 at 12:00 UTC).</p></caption>
          <?xmltex \igopts{width=355.659449pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f06.png"/>

        </fig>

<?xmltex \hack{\newpage}?>
      <p id="d1e744"><?xmltex \hack{\vspace*{-4mm}}?>

                <disp-formula specific-use="align" content-type="numbered"><mml:math id="M19" display="block"><mml:mtable displaystyle="true"><mml:mlabeledtr id="Ch1.E3"><mml:mtd/><mml:mtd><mml:mstyle class="stylechange" displaystyle="true"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><mml:msub><mml:mi mathvariant="normal">IWV</mml:mi><mml:mtext>TR</mml:mtext></mml:msub><mml:mo>=</mml:mo><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:mtext>sfc</mml:mtext><mml:mi>l</mml:mi></mml:munderover><mml:msub><mml:mi>q</mml:mi><mml:mtext>TR</mml:mtext></mml:msub><mml:mtext>d</mml:mtext><mml:mi>p</mml:mi></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E4"><mml:mtd/><mml:mtd><mml:mstyle class="stylechange" displaystyle="true"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><mml:mi>q</mml:mi><mml:mo>=</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mi>w</mml:mi><mml:mrow><mml:mi>w</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo><mml:mspace width="0.25em" linebreak="nobreak"/><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mtext>with</mml:mtext><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mspace linebreak="nobreak" width="0.25em"/><mml:mi>w</mml:mi><mml:mo>≪</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>⇒</mml:mo><mml:mi>q</mml:mi><mml:mo>≈</mml:mo><mml:mi>w</mml:mi></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mlabeledtr id="Ch1.E5"><mml:mtd/><mml:mtd><mml:mstyle displaystyle="true" class="stylechange"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mi mathvariant="bold-italic">u</mml:mi><mml:mo>=</mml:mo><mml:mo>(</mml:mo><mml:mi>u</mml:mi><mml:mo>,</mml:mo><mml:mi>v</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mtd></mml:mlabeledtr></mml:mtable></mml:math></disp-formula></p>
</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results and discussion</title>
      <p id="d1e862">Figure <xref ref-type="fig" rid="Ch1.F2"/> shows the comparison between WRF-simulated and
observed precipitation. Observations are from the <xref ref-type="bibr" rid="bib1.bibx41" id="text.48"/> dataset
for the Pacific simulation and from the Iberia02 precipitation dataset in the
case of the Atlantic simulation. The latter dataset is a combination of
Spain02 <xref ref-type="bibr" rid="bib1.bibx23" id="paren.49"/> and Portugal02 <xref ref-type="bibr" rid="bib1.bibx4" id="paren.50"/>, both of
which include a high density of good-quality stations <xref ref-type="bibr" rid="bib1.bibx23" id="paren.51"/>.
Further comparison of the simulations with observations, against IWV (IVT, Eq. 1) from NASA's Modern-Era Retrospective Analysis for
Research and Applications (MERRA) <xref ref-type="bibr" rid="bib1.bibx62" id="paren.52"/> is provided in
Fig. <xref ref-type="fig" rid="Ch1.F4"/>.</p>
      <p id="d1e885">Whereas the simulated IVT field is realistic when compared to observations,
WRF tends to overestimate precipitation. The overestimation is particularly
high in the mountains of Oregon and Washington for the 2007 event. However,
despite the fact that precipitation is arguably the most difficult
variable to simulate in a numerical model
<xref ref-type="bibr" rid="bib1.bibx43 bib1.bibx6" id="paren.53"><named-content content-type="pre">e.g.,</named-content></xref>, the spatial pattern of precipitation
is realistically represented.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p id="d1e895"><bold>(a)</bold> Ratio of tagged water vapor to total water vapor for
the Pacific event. <bold>(b)</bold> Same as <bold>(a)</bold> but for precipitation.
Panels <bold>(c, d)</bold> are equivalent to <bold>(a, b)</bold>, respectively, but for the
Atlantic event.</p></caption>
        <?xmltex \igopts{width=355.659449pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f07.png"/>

      </fig>

      <p id="d1e918">Figure <xref ref-type="fig" rid="Ch1.F5"/> shows the three-dimensional distribution of water
vapor mixing ratio (panel a), and tracer water vapor mixing ratio (panel b)
for the event in the Pacific that made landfall along the US West Coast.
While the former accounts for the total amount of moisture, the latter shows
only the moisture originating from tropical latitudes, labeled with the 3-D
mask depicted in Fig. <xref ref-type="fig" rid="Ch1.F3"/>. The simulation was started 8 days
before the time shown in Fig. <xref ref-type="fig" rid="Ch1.F5"/>. Panels (c) and (d) show a
snapshot of the water vapor mixing ratio and the tracer water vapor mixing
ratio in the form of a series of cross-section slices that allow the
visualization of the vertical distribution of moisture. The images suggest
that the vast majority of the moisture contained in the pre-frontal region
has its origin in the tropical regions. This is especially true at lower
latitudes. The maximum content of tropical moisture remains mostly in the
lower levels. The high moisture values behind the front and at the leading
edge of the AR structure, where the WCB is located, are not related to
tropical advection and are thus generated by convergence of moisture from
local sources occurring along the frontal region. Slightly different
conclusions are obtained for the Atlantic case study shown in
Fig. <xref ref-type="fig" rid="Ch1.F6"/>. For the sake of simplicity, only the eastern
longitudes of the domain of simulation are shown. Even though the tropical
moisture still remains in the lowest levels of the troposphere, its
contribution to the total is less significant than for the Pacific case
study. The reason is shown in Fig. <xref ref-type="fig" rid="Ch1.F1"/>e–h, indicating that most
of the connection of the WCB with tropical regions is through a much longer
path, due to the blocking position of the Azores High.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><caption><p id="d1e934">Transversal cross sections along the central axis of the atmospheric
river at latitudes 42.0 (transversal cross section P1), 37.4 (transversal
cross section P2) and 30.6 (transversal cross section P3). The plots show the
tracers' water vapor mixing ratio in grams per kilogram together with the wind
module in meters per second. The estimated position of the LLJ is shown
in the figures as well.</p></caption>
        <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f08.png"/>

      </fig>

      <p id="d1e943">Figure <xref ref-type="fig" rid="Ch1.F7"/>a shows the percentage of IWV that comes from the
tropics (<inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">IWV</mml:mi><mml:mtext>TR</mml:mtext></mml:msub><mml:mo>/</mml:mo><mml:mi mathvariant="normal">IWV</mml:mi></mml:mrow></mml:math></inline-formula>) for the Pacific event. In a
region extending from the tropics to the coast of
Washington state,
tropical moisture accounts for about 80–90 % of the precipitable water
and locally exceeding this contribution. These high percentages extend inland
along the northwestern US coastal regions. Likewise, Fig. <xref ref-type="fig" rid="Ch1.F7"/>b
shows the 24 h accumulated percentage of precipitation that is composed of
condensed tropical water vapor (<inline-formula><mml:math id="M21" display="inline"><mml:mrow><mml:msub><mml:mi mathvariant="normal">Prec</mml:mi><mml:mtext>TR</mml:mtext></mml:msub><mml:mo>/</mml:mo><mml:mi mathvariant="normal">Prec</mml:mi></mml:mrow></mml:math></inline-formula>).
For clarity, we only plot the region where precipitation exceeded
3 mm day<inline-formula><mml:math id="M22" 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> <xref ref-type="bibr" rid="bib1.bibx7" id="paren.54"/>. Precipitation of tropical origin
accounts for 70 to 90 % of total precipitation from northern California
to southern Oregon, and the ratio decreases at higher latitudes.
Interestingly, tropical moisture is funneled by local topography, and it
contributes to about 70 to 80 % of precipitation west of the Cascade
Range. In the Atlantic case, we also see a clear plume where tropical water
vapor accounts for more than 80 % of precipitable water; however, the
percentage decreases to around 70 % close to the center of the system
and just before arriving on the Iberian coast (Fig. <xref ref-type="fig" rid="Ch1.F7"/>c–d).
In this case, cyclogenesis occurs just off the coast of Galicia, on the
northwestern tip of the Iberian Peninsula, and thus the enhanced convergence
of the existent local moisture feeds the AR and is involved in the heavy
precipitation, which consequently is only between 60 and 80 % of tropical
origin. The high ratios observed in mountainous ranges such as the Pyrenees
and the Rockies, far ahead of the cold front and the AR associated with the
systems, are very likely due to the slantwise lift of tropical moisture in
mid-levels along the warm frontal boundary.</p>
      <p id="d1e998">Figure <xref ref-type="fig" rid="Ch1.F8"/> plots a range of transversal cross sections showing
the vertical distribution of the tracer water vapor mixing ratio through the
central axis of the AR, as well as wind speed. From these results, there is
evidence that the maximum of tropical moisture does not necessarily coincide
with the LLJ, which is the maximum in wind speed at lower
levels. More precisely, at the root of the AR, at subtropical latitudes
(Fig. <xref ref-type="fig" rid="Ch1.F8"/>d), most of the tropical moisture remains close to
the surface and below the LLJ, which can be identified at a height of
1 km. As the central axis of the LLJ goes upward with latitude, tropical
moisture tends to ascend in the vertical column, but the maximum of moisture
can be located in front of or behind the LLJ, as well as remaining near the
surface levels. In the leading part of the AR, the interaction of the
humidity with the topography of the Pacific coast of North America makes the
situation more difficult to analyze. Very likely, the complex formation
process of the cyclone, from the interaction of two preexistent frontal
systems, loaded with tropical moisture, adds complication to the
thermodynamic structure and moisture distribution of the resulting front.
Notwithstanding, this AR event is a particularly well defined case from the
perspective of vertically integrated quantities such as IVT and IWV.</p>
      <p id="d1e1005">An analogous plot for the Atlantic case is presented in Appendix A (Fig. A2).
The results are similar to the Pacific case, with no clear one-to-one
connection between the LLJ and the maximum in tropical humidity. We note that
no general conclusion can be obtained from particular case studies, but
these results suggest that the perception that ARs are clearly associated
with the LLJ of extratropical cyclones should be reviewed.</p>
      <p id="d1e1008">Figure <xref ref-type="fig" rid="Ch1.F9"/>a shows the area-averaged total precipitation
(black circles) and the ratio between tracer precipitation and total
precipitation (red crosses) throughout the region highlighted in
Fig. <xref ref-type="fig" rid="Ch1.F9"/>b for the Pacific event. As expected, the plot
shows that the maximum in tropical precipitation is observed during the
landfall of the cold front and the AR, which closely coincides with the
maximum in total precipitation. The secondary maximum in the total
precipitation observed 1 day before the landfall of the AR event is due to
the landfall of the warm front associated with the cyclone (see Fig. A3). The
convergence of local moisture would be the dynamical source for precipitation
in the warm front.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><caption><p id="d1e1018">Evolution over time of the tropical precipitation (red crosses)
and total precipitation (black circles) during the Pacific
event <bold>(a)</bold>. Data represent the spatial integration of both variables
through the region highlighted in red in <bold>(b)</bold>.</p></caption>
        <?xmltex \igopts{width=355.659449pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f09.png"/>

      </fig>

</sec>
<sec id="Ch1.S4" sec-type="conclusions">
  <title>Conclusions</title>
      <p id="d1e1040">A new 3-D Eulerian forward water vapor tracer tool implemented in the WRF
model has been used to analyze two important AR events. The first event
developed over the Pacific Ocean and corresponds to the Great Coastal Gale of
2007 on the US Pacific West Coast, which resulted in an estimated
USD 678 million in direct economic damages <xref ref-type="bibr" rid="bib1.bibx17" id="paren.55"/>. The
Atlantic event corresponds to an atmospheric river event in October 1987
that resulted in record winds of 100 km h<inline-formula><mml:math id="M23" 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> and daily precipitation of
over 100 mm day<inline-formula><mml:math id="M24" 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> in Galicia (in the northwest of Spain) and
Portugal. In an effort to understand the origin of moisture for these two AR
events, we use 3-D water vapor tracers to quantify the percentage of total
precipitable water and precipitation that originates from the tropics.</p>
      <p id="d1e1070">Results show that most of the moisture within and surrounding the two
atmospheric rivers had its origin in the tropical regions that we labeled
with the 3-D tracer mask. Consequently, most of the precipitation that fell
during these two events was composed of condensed tropical water vapor. The
Pacific event shows a more intense connection with tropical regions than the
Atlantic case. As a result, the percentage of tropical precipitation for this
event over North America is higher and peaks around 85 %. Nevertheless,
for the Atlantic event, still more than 60 % of the resulting
precipitation is of tropical origin.</p>
      <p id="d1e1073">The two selected case studies have been chosen due to the associated
severity of flooding and socioeconomic damages. Both correspond to a strong
AR feeding the system of a very intense extratropical storm. The conclusions
drawn from these two AR events are thus not necessarily representative of the
bulk of Pacific or Atlantic AR events. However, the results highlight the
importance of tropical moisture for the two case studies. We also find
evidence that convergence of local moisture also contributes to total
precipitable water, especially in the post-frontal region, the leading edge
of the AR and in the far northern latitudes where the tropical link has
weakened. It is well known that in a mature system, when baroclinic
structures are well differentiated, the stored water vapor tends to be
constant (e.g., <xref ref-type="bibr" rid="bib1.bibx8" id="altparen.56"/>), and since the fate of tropical
moisture is to precipitate, local convergence should keep the balance by
lateral inflow.</p>
      <p id="d1e1079">Based on these results, we hypothesize that the highest amounts of
precipitable water can only be attained in a system in which a clear tropical
source of moisture is sustained until landfall. Strong ARs with a direct
link to tropical latitudes should be expected to result in more precipitation
than those with local convergence as a primary feeding mechanism. It is our
aim for the future to extend this work by including more cases.</p>
      <p id="d1e1083"><?xmltex \hack{\newpage}?>Finally, our findings suggest that the maximum of tropical moisture does not
necessarily coincide with the LLJ of either extratropical cyclone analyzed.
Instead, this maximum is located near surface levels at lower latitudes to
gradually ascend in northern latitudes, but still remaining below 2 km,
mostly within the boundary layer, in contrast with findings in other studies
<xref ref-type="bibr" rid="bib1.bibx12" id="paren.57"/>. The maximum of tropical moisture may be situated below and
toward the back, or ahead of the LLJ, which is located along the cold front.
Both events are clear examples of ARs from the point of view of vertically
integrated variables, such as IWV and IVT used in most detection algorithms;
however, the vertical distribution of moisture of tropical origin reflects
the complex processes leading to precipitation. The new 3-D tracer tool will
allow us to delve into these processes and explore the role of tropical
moisture exports in the initiation and intensification of AR events.</p>
</sec>

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

      <p id="d1e1094">No public data are derived from this research. For further
information on the WRF tracer tool, please contact the corresponding
author.</p>
  </notes><?xmltex \hack{\clearpage}?><app-group>

<app id="App1.Ch1.S1">
  <title>Supplementary figures</title>

      <?xmltex \floatpos{h!}?><fig id="App1.Ch1.F1"><caption><p id="d1e1108">Front maps for the Pacific Great Coastal Gale of 2007 event.</p></caption>
        <?xmltex \hack{\hsize\textwidth}?>
        <?xmltex \igopts{width=497.923228pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f10.png"/>

      </fig>

      <?xmltex \floatpos{h!}?><fig id="App1.Ch1.F2"><caption><p id="d1e1121">Showing the 500 hPa geopotential field together with sea level
pressure <bold>(a–c)</bold> and 850 hPa
temperature <bold>(d–f)</bold> in the Great Storm of 1987 event from 14 to
16 October. The figure highlights the cooperative linkage between a trough
and low-level baroclinicity in the rapid development of the cyclonic system.
</p></caption>
        <?xmltex \hack{\hsize\textwidth}?>
        <?xmltex \igopts{width=469.470472pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f11.png"/>

      </fig>

<?xmltex \hack{\clearpage}?><?xmltex \floatpos{h!}?><fig id="App1.Ch1.F3"><caption><p id="d1e1142">Same as Fig. <xref ref-type="fig" rid="Ch1.F8"/> but for the Atlantic case. The
corresponding latitudes are 41.8<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> for transversal cross section A1
and 38.0<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> for transversal cross section A2. </p></caption>
        <?xmltex \hack{\hsize\textwidth}?>
        <?xmltex \igopts{width=384.112205pt}?><graphic xlink:href="https://esd.copernicus.org/articles/8/1247/2017/esd-8-1247-2017-f12.png"/>

      </fig>

<?xmltex \hack{\clearpage}?><supplementary-material position="anchor"><p id="d1e1174"><bold>The Supplement related to this article is available online at <inline-supplementary-material xlink:href="https://doi.org/10.5194/esd-8-1247-2017-supplement" xlink:title="zip">https://doi.org/10.5194/esd-8-1247-2017-supplement</inline-supplementary-material>.</bold></p></supplementary-material>
</app>
  </app-group><notes notes-type="competinginterests">

      <p id="d1e1182">The authors declare that they have no conflict of
interest.</p>
  </notes><notes notes-type="sistatement">

      <p id="d1e1188">This article is part of the special issue “The 8th EGU Leonardo
Conference: From evaporation to precipitation: the atmospheric moisture
transport”. It is a result of the 8th EGU Leonardo Conference, Ourense,
Spain, 25–27 October 2016.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e1194">This work has been founded by the Ministerio de Economía y Competitivad
(CGL2013-45932-R) from the Spanish Government and its mobility grants for
pre-doc researchers. Jorge Eiras-Barca would like to express his gratitude to
the Department of Atmospheric Sciences of the University of Illinois at
Urbana–Champaign for the kind support in this project. Funding for Dominguez
and Hu comes from NASA
grant NNX14AD77G.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited by: Diego G. Miralles
<?xmltex \hack{\newline}?> Reviewed by: Brianna Pagán, Ruud van der Ent, <?xmltex \hack{\newline}?>and Lan
Wang-Erlandsson</p></ack><ref-list>
    <title>References</title>

      <ref id="bib1.bibx1"><label>Arnault et al.(2016)</label><mixed-citation>Arnault, J., Knoche, R., Wei, J., and Kunstmann, H.: Evaporation tagging and
atmospheric water budget analysis with WRF: A regional
precipitation recycling study for West Africa, Water Resour. Res., 52, 1544–1567, <ext-link xlink:href="https://doi.org/10.1002/2015WR017704" ext-link-type="DOI">10.1002/2015WR017704</ext-link>,
2016.</mixed-citation></ref>
      <ref id="bib1.bibx2"><label>Avelino and Dall'erba(2016)</label><mixed-citation>
Avelino, A. and Dall'erba, S.: Comparing the economic impact of natural
disasters generated by different input-output models. An application to the
2007 Chehalis River Flood (WA), North American Regional Science Conference,
Minneapolis, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx3"><label>Bao et al.(2006)Bao, Michelson, Neiman, Ralph, and Wilczak</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, <ext-link xlink:href="https://doi.org/10.1175/MWR3123.1" ext-link-type="DOI">10.1175/MWR3123.1</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bibx4"><label>Belo-Pereira et al.(2011)Belo-Pereira, Dutra, and
Viterbo</label><mixed-citation>Belo-Pereira, M., Dutra, E., and Viterbo, P.: Evaluation of global
precipitation data sets over the Iberian Peninsula, J. Geophys. Res., 116,
D20101, <ext-link xlink:href="https://doi.org/10.1029/2010JD015481" ext-link-type="DOI">10.1029/2010JD015481</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bibx5"><label>Brands et al.(2016)Brands, Gutiérrez, and
San-Martín</label><mixed-citation>
Brands, S., Gutiérrez, J., and San-Martín, D.: Twentieth-century
atmospheric river activity along the west coasts of Europe and North America:
algorithm formulation, reanalysis uncertainty and links to atmospheric
circulation patterns, Clim. Dynam., 48, 2771–2795, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx6"><label>Buckley and Marshall(2016)</label><mixed-citation>
Buckley, M. W. and Marshall, J.: Observations, inferences, and mechanisms of
the Atlantic Meridional Overturning Circulation: A review, Rev.
Geophys., 54, 5–63, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx7"><label>Buishand(1978)</label><mixed-citation>
Buishand, T.: Some remarks on the use of daily rainfall models, J.
Hydrol., 36, 295–308, 1978.</mixed-citation></ref>
      <ref id="bib1.bibx8"><label>Bullock and Johnson(1971)</label><mixed-citation>
Bullock, B. R. and Johnson, D. R.: The generation of available potential
energy by latent heat release in a mid-latitude cyclone, Mon. Weather Rev.,
99, 1–14, 1971.</mixed-citation></ref>
      <ref id="bib1.bibx9"><label>Burt and Mansfield(1988)</label><mixed-citation>
Burt, S. and Mansfield, A.: The Great Storm of 15–16 October 1987, Weather,
43,
90–110, 1988.</mixed-citation></ref>
      <ref id="bib1.bibx10"><label>Cordeira et al.(2013)Cordeira, Ralph, and Moore</label><mixed-citation>
Cordeira, J. M., Ralph, F. M., and Moore, B. J.: The development and evolution
of two atmospheric rivers in proximity to western North Pacific tropical
cyclones in October 2010, Mon. Weather Rev., 141, 4234–4255, 2013.</mixed-citation></ref>
      <ref id="bib1.bibx11"><label>Crout et al.(2008)Crout, Sears, and Locke</label><mixed-citation>Crout, R. L., Sears, I. T., and Locke, L. K.: The Great Coastal Gale of 2007
from Coastal Storms Program Buoy 46089, OCEANS 2008, Quebec City, QC, 1–7,
<ext-link xlink:href="https://doi.org/10.1109/OCEANS.2008.5152026" ext-link-type="DOI">10.1109/OCEANS.2008.5152026</ext-link>, 2008.</mixed-citation></ref>
      <ref id="bib1.bibx12"><label>Dacre et al.(2014)Dacre, Clark, Martinez-Alvarado, Stringer, and
Lavers</label><mixed-citation>
Dacre, H. F., Clark, P. A., Martinez-Alvarado, O., Stringer, M. A., and
Lavers, D. A.: How
do atmospheric rivers form?, B. Am. Meteorol. Soc., 96, 1243–1255,
2014.</mixed-citation></ref>
      <ref id="bib1.bibx13"><label>Dettinger(2011)</label><mixed-citation>Dettinger, M.: Climate Change, Atmospheric Rivers, and Floods in California
– A
Multimodel Analysis of Storm Frequency and Magnitude Changes, J.
Am. Water Resour. As., 47, 514–523,
<ext-link xlink:href="https://doi.org/10.1111/j.1752-1688.2011.00546.x" ext-link-type="DOI">10.1111/j.1752-1688.2011.00546.x</ext-link>,  2011.</mixed-citation></ref>
      <ref id="bib1.bibx14"><label>Dettinger et al.(2015)Dettinger, Ralph, and Lavers</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="https://doi.org/10.1029/2015EO038675" ext-link-type="DOI">10.1029/2015EO038675</ext-link>,
2015.</mixed-citation></ref>
      <ref id="bib1.bibx15"><label>Dettinger et al.(2011)Dettinger, Ralph, Das, Neiman, and
Cayan</label><mixed-citation>Dettinger, M. D., 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, <ext-link xlink:href="https://doi.org/10.3390/w3020445" ext-link-type="DOI">10.3390/w3020445</ext-link>, 2011.</mixed-citation></ref>
      <ref id="bib1.bibx16"><label>Dominguez et al.(2016)Dominguez, Miguez-Macho, and
Hu</label><mixed-citation>
Dominguez, F., Miguez-Macho, G., and Hu, H.: WRF with Water Vapor Tracers: A
Study of Moisture Sources for the North American Monsoon, J.
Hydrometeorol., 17, 1915–1927, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx17"><label>Dominguez et al.(2017)</label><mixed-citation>Dominguez, F., Dall'erba, S., Huang, S., Avelino, A., Mehran, A., Hu, H.,
Schmidt, A., Schick, L., and Lettenmaier, D.: Tracking an Atmospheric River
in a Warmer Climate: from Water Vapor to Economic Impacts, Earth Syst. Dynam.
Discuss., <ext-link xlink:href="https://doi.org/10.5194/esd-2017-64" ext-link-type="DOI">10.5194/esd-2017-64</ext-link>, in review, 2017.</mixed-citation></ref>
      <ref id="bib1.bibx18"><label>Dudhia(1989)</label><mixed-citation>
Dudhia, J.: Numerical study of convection observed during the winter monsoon
experiment using a mesoscale two-dimensional model, J.
Atmos. Sci., 46, 3077–3107, 1989.</mixed-citation></ref>
      <ref id="bib1.bibx19"><label>Eiras-Barca et al.(2016)Eiras-Barca, Brands, and
Miguez-Macho</label><mixed-citation>
Eiras-Barca, J., Brands, S., and Miguez-Macho, G.: Seasonal variations in
North Atlantic atmospheric river activity and associations with anomalous
precipitation over the Iberian Atlantic Margin, J. Geophys.
Res.-Atmos.,  121, 931–948, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx20"><label>Gimeno et al.(2016)Gimeno, Dominguez, Nieto, Trigo, Drumond, Reason,
Taschetto, Ramos, Kumar, and Marengo</label><mixed-citation>
Gimeno, L., Dominguez, F., Nieto, R., Trigo, R., Drumond, A., Reason, C. J.,
Taschetto, A. S., Ramos, A. M., Kumar, R., and Marengo, J.: Major mechanisms
of atmospheric moisture transport and their role in extreme precipitation
events, Annu. Rev. Env. Resour., 41, 117–141, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx21"><label>Gómez and Miguez-Macho(2017)</label><mixed-citation>
Gómez, B. and Miguez-Macho, G.: The impact of wave number selection and
spin up time when using spectral nudging for dynamical downscaling
applications,
Geophys. Res. Abstr.,
EGU2017-18466, EGU General Assembly 2017, Vienna, Austria, 2017.</mixed-citation></ref>
      <ref id="bib1.bibx22"><label>Guan and Waliser(2015)</label><mixed-citation>
Guan, B. and Waliser, D. E.: Detection of atmospheric rivers: Evaluation and
application of an algorithm for global studies, J. Geophys.
Res.-Atmos., 120, 12514–12535, 2015.</mixed-citation></ref>
      <ref id="bib1.bibx23"><label>Herrera et al.(2012)</label><mixed-citation>Herrera, S., Gutiérrez, J. M., Ancell, R., Pons, M. R., Frías, M. D.,
and
Fernández, J.: Development and analysis of a 50-year high-resolution daily
gridded precipitation dataset over Spain (Spain02), Int. J.
Climatol., 32, 74–85, <ext-link xlink:href="https://doi.org/10.1002/joc.2256" ext-link-type="DOI">10.1002/joc.2256</ext-link>,  2012.</mixed-citation></ref>
      <ref id="bib1.bibx24"><label>Higgins et al.(2000)Higgins, Schemm, Shi, and Leetmaa</label><mixed-citation>Higgins, R., Schemm, J., Shi, W., and Leetmaa, A.: Extreme precipitation events
in the western United States related to tropical forcing, journal of climate,
13, 793–820, <ext-link xlink:href="https://doi.org/10.1175/1520-0442(2000)013&lt;0793:EPEITW&gt;2.0.CO;2" ext-link-type="DOI">10.1175/1520-0442(2000)013&lt;0793:EPEITW&gt;2.0.CO;2</ext-link>, 2000.</mixed-citation></ref>
      <ref id="bib1.bibx25"><label>Hong and Lim(2006)</label><mixed-citation>
Hong, S.-Y. and Lim, J.-O. J.: The WRF single-moment 6-class microphysics
scheme (WSM6), J. Korean Meteor. Soc., 42, 129–151, 2006.</mixed-citation></ref>
      <ref id="bib1.bibx26"><label>Hong et al.(2006)Hong, Noh, and Dudhia</label><mixed-citation>
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an
explicit treatment of entrainment processes, Mon. Weather Rev., 134,
2318–2341, 2006.</mixed-citation></ref>
      <ref id="bib1.bibx27"><label>Hoskins and Berrisford(1988)</label><mixed-citation>
Hoskins, B. and Berrisford, P.: A potential vorticity perspective of the storm
of 15–16 October 1987, Weather, 43, 122–129, 1988.</mixed-citation></ref>
      <ref id="bib1.bibx28"><label>Hu et al.(2010)Hu, Nielsen-Gammon, and Zhang</label><mixed-citation>
Hu, X.-M., Nielsen-Gammon, J. W., and Zhang, F.: Evaluation of three planetary
boundary layer schemes in the WRF model, J. Appl. Meteorol.
Clim., 49, 1831–1844, 2010.</mixed-citation></ref>
      <ref id="bib1.bibx29"><label>Hu et al.(2013)Hu, Klein, and Xue</label><mixed-citation>Hu, X.-M., Klein, P. M., and Xue, M.: Evaluation of the updated YSU planetary
boundary layer scheme within WRF for wind resource and air quality
assessments, J. Geophys. Res.-Atmos., 118, 10490–10505  <ext-link xlink:href="https://doi.org/10.1002/jgrd.50823" ext-link-type="DOI">10.1002/jgrd.50823</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bibx30"><label>Insua-Costa and Miguez-Macho(2017)</label><mixed-citation>Insua-Costa, D. and Miguez-Macho, G.: A new moisture tagging capability in
the Weather Research and Forecasting Model: formulation, validation and
application to the 2014 Great Lake-effect snowstorm, Earth Syst. Dynam.
Discuss., <ext-link xlink:href="https://doi.org/10.5194/esd-2017-80" ext-link-type="DOI">10.5194/esd-2017-80</ext-link>, in review, 2017.</mixed-citation></ref>
      <ref id="bib1.bibx31"><label>Kain(2004)</label><mixed-citation>
Kain, J. S.: The Kain–Fritsch convective parameterization: an update, J.
Appl. Meteorol., 43, 170–181, 2004.</mixed-citation></ref>
      <ref id="bib1.bibx32"><label>Kim et al.(2013)Kim, Waliser, Neiman, Guan, Ryoo, and Wick</label><mixed-citation>Kim, J., Waliser, D., Neiman, P., Guan, B., Ryoo, J.-M., and Wick, G.: Effects
of atmospheric river landfalls on the cold season precipitation in
California, Clim. Dynam., 40, 465–474, <ext-link xlink:href="https://doi.org/10.1007/s00382-012-1322-3" ext-link-type="DOI">10.1007/s00382-012-1322-3</ext-link>,  2013.</mixed-citation></ref>
      <ref id="bib1.bibx33"><label>Knippertz and Wernli(2010)</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.bibx34"><label>Knippertz et al.(2013)Knippertz, Wernli, and
Gläser</label><mixed-citation>
Knippertz, P., Wernli, H., and Gläser, G.: A global climatology of tropical
moisture exports, J. Climate, 26, 3031–3045, 2013.</mixed-citation></ref>
      <ref id="bib1.bibx35"><label>Lavers and Villarini(2013)</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, <ext-link xlink:href="https://doi.org/10.1002/grl.50636" ext-link-type="DOI">10.1002/grl.50636</ext-link>,  2013.</mixed-citation></ref>
      <ref id="bib1.bibx36"><label>Lavers and Villarini(2014)</label><mixed-citation>Lavers, D. A. and Villarini, G.: The relationship between daily European
precipitation and measures of atmospheric water vapour transport,
Int. J. Climatol., 35, 2187–2192, <ext-link xlink:href="https://doi.org/10.1002/joc.4119" ext-link-type="DOI">10.1002/joc.4119</ext-link>,  2014.</mixed-citation></ref>
      <ref id="bib1.bibx37"><label>Lavers et al.(2011)Lavers, Allan, Wood, Villarini, Brayshaw, and
Wade</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="https://doi.org/10.1029/2011GL049783" ext-link-type="DOI">10.1029/2011GL049783</ext-link>,  2011.</mixed-citation></ref>
      <ref id="bib1.bibx38"><label>Lavers et al.(2012)Lavers, Villarini, Allan, Wood, and
Wade</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.-Atmos., 117, D20106, <ext-link xlink:href="https://doi.org/10.1029/2012JD018027" ext-link-type="DOI">10.1029/2012JD018027</ext-link>,  2012.</mixed-citation></ref>
      <ref id="bib1.bibx39"><label>Lavers et al.(2013)Lavers, Allan, Villarini, Lloyd-Hughes, Brayshaw,
and Wade</label><mixed-citation>Lavers, D. A., Allan, R. P., Villarini, G., Lloyd-Hughes, B., Brayshaw, D. J.,
and Wade, A. J.: Future changes in atmospheric rivers and their implications
for winter flooding in Britain, Environ. Res. Lett., 8, 034010, <ext-link xlink:href="https://doi.org/10.1088/1748-9326/8/3/034010" ext-link-type="DOI">10.1088/1748-9326/8/3/034010</ext-link>,
2013.</mixed-citation></ref>
      <ref id="bib1.bibx40"><label>Leung and Qian(2009)</label><mixed-citation>Leung, L. R. and Qian, Y.: Atmospheric rivers induced heavy precipitation and
flooding in the western U.S. simulated by the WRF regional climate model,
Geophys. Res. Lett., 36, L03820, <ext-link xlink:href="https://doi.org/10.1029/2008GL036445" ext-link-type="DOI">10.1029/2008GL036445</ext-link>,  2009.</mixed-citation></ref>
      <ref id="bib1.bibx41"><label>Livneh et al.(2015)Livneh, Bohn, Pierce, Munoz-Arriola, Nijssen,
Vose, Cayan, and Brekke</label><mixed-citation>
Livneh, B., Bohn, T. J., Pierce, D. W., Munoz-Arriola, F., Nijssen, B., Vose,
R., Cayan, D. R., and Brekke, L.: A spatially comprehensive,
hydrometeorological data set for Mexico, the US, and Southern Canada
1950–2013, Scientific data, 2, 2015.</mixed-citation></ref>
      <ref id="bib1.bibx42"><label>Mahoney et al.(2016)Mahoney, Jackson, Neiman, Hughes, Darby, Wick,
White, Sukovich, and Cifelli</label><mixed-citation>
Mahoney, K., Jackson, D. L., Neiman, P., Hughes, M., Darby, L., Wick, G.,
White, A., Sukovich, E., and Cifelli, R.: Understanding the role of
atmospheric rivers in heavy precipitation in the southeast United States,
Mon. Weather Rev., 144, 1617–1632, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx43"><label>Maraun et al.(2010)</label><mixed-citation>Maraun, D.,  Wetterhall, F.,  Ireson, A. M.,  Chandler, R. E.,  Kendon, E. J.,
Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema,
V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and
Thiele-Eich, I.: Precipitation
downscaling under climate change: Recent developments to bridge the gap
between dynamical models and the end user, Rev. Geophys., 48, RG3003,
<ext-link xlink:href="https://doi.org/10.1029/2009RG000314" ext-link-type="DOI">10.1029/2009RG000314</ext-link>,
2010.</mixed-citation></ref>
      <ref id="bib1.bibx44"><label>Michalakes et al.(2005)Michalakes, Dudhia, Gill, Henderson, Klemp,
Skamarock, and Wang</label><mixed-citation>
Michalakes, J., Dudhia, J., Gill, D., Henderson, T., Klemp, J., Skamarock, W.,
and Wang, W.: The weather research and forecast model: software architecture
and performance, in: Proceedings of the Eleventh ECMWF Workshop on the Use of
High Performance Computing in Meteorology,  156–168, World Scientific:
Singapore, 2005.</mixed-citation></ref>
      <ref id="bib1.bibx45"><label>Miguez-Macho et al.(2004)Miguez-Macho, Stenchikov, and
Robock</label><mixed-citation>Miguez-Macho, G., Stenchikov, G. L., and Robock, A.: Spectral nudging to
eliminate the effects of domain position and geometry in regional climate
model simulations, J. Geophys. Res.-Atmos., 109, D13104, <ext-link xlink:href="https://doi.org/10.1029/2003JD004495" ext-link-type="DOI">10.1029/2003JD004495</ext-link>, 2004.</mixed-citation></ref>
      <ref id="bib1.bibx46"><label>Miguez-Macho et al.(2005)Miguez-Macho, Stenchikov, and
Robock</label><mixed-citation>
Miguez-Macho, G., Stenchikov, G. L., and Robock, A.: Regional climate
simulations over North America: Interaction of local processes with improved
large-scale flow, J. Climate, 18, 1227–1246, 2005.</mixed-citation></ref>
      <ref id="bib1.bibx47"><label>Miguez-Macho et al.(2013)Miguez-Macho, Rios-Entenza, and
Dominguez</label><mixed-citation>
Miguez-Macho, G., Rios-Entenza, A., and Dominguez, F.: Regional climate
simulations with moisture tracers to investigate land-atmosphere interactions
in the terrestrial water cycle over the Iberian Peninsula,
Geophys. Res. Abstr.,
EGU2013-12677, EGU General Assembly 2013, Vienna, Austria, 2013.</mixed-citation></ref>
      <ref id="bib1.bibx48"><label>Mlawer et al.(1997)Mlawer, Taubman, Brown, Iacono, and
Clough</label><mixed-citation>
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.:
Radiative transfer for inhomogeneous atmospheres: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, 1997.</mixed-citation></ref>
      <ref id="bib1.bibx49"><label>Mundhenk et al.(2016)Mundhenk, Barnes, Maloney, and
Nardi</label><mixed-citation>Mundhenk, B. D., Barnes, E. A., Maloney, E. D., and Nardi, K. M.: Modulation of
atmospheric rivers near Alaska and the US West Coast by northeast Pacific
height anomalies, J. Geophys. Res.-Atmos., 121,
12751–12765, <ext-link xlink:href="https://doi.org/10.1002/2016JD025350" ext-link-type="DOI">10.1002/2016JD025350</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx50"><label>Nayak et al.(2014)Nayak, Villarini, and Lavers</label><mixed-citation>
Nayak, M. A., Villarini, G., and Lavers, D. A.: On the skill of numerical
weather prediction models to forecast atmospheric rivers over the central
United States, Geophys. Res. Lett., 41, 4354–4362, 2014.</mixed-citation></ref>
      <ref id="bib1.bibx51"><label>Neiman et al.(2008a)Neiman, Ralph, Wick, Kuo, Wee, Ma, Taylor, and
Dettinger</label><mixed-citation>
Neiman, P. J., Ralph, F. M., Wick, G. A., Kuo, Y.-H., Wee, T.-K., Ma, Z.,
Taylor, G. H., and Dettinger, M. D.: Diagnosis of an Intense Atmospheric
River Impacting the Pacific Northwest: Storm Summary and Offshore Vertical
Structure Observed with COSMIC Satellite Retrievals, Mon. Weather Rev., 136,
4398–4420,   2008a.</mixed-citation></ref>
      <ref id="bib1.bibx52"><label>Neiman et al.(2008b)Neiman, Ralph, Wick, Lundquist, and
Dettinger</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,
<ext-link xlink:href="https://doi.org/10.1175/2007JHM855.1" ext-link-type="DOI">10.1175/2007JHM855.1</ext-link>,  2008b.</mixed-citation></ref>
      <ref id="bib1.bibx53"><label>NOAA(2008)</label><mixed-citation>
NOAA (National Oceanic and Atmosphere Administration): Pacific Northwest
Storms of December, U.S. DEPARTMENT OF COMMERCE National Oceanic and
Atmospheric Administration National Weather Service Silver Spring, Maryland,
1–3, 2008.</mixed-citation></ref>
      <ref id="bib1.bibx54"><label>Payne and Magnusdottir(2015)</label><mixed-citation>Payne, A. E. and Magnusdottir, G.: An evaluation of atmospheric rivers over the
North Pacific in CMIP5 and their response to warming under RCP 8.5, J.
Geophys. Res.-Atmos., 120, 11173–11190, <ext-link xlink:href="https://doi.org/10.1002/2015JD023586" ext-link-type="DOI">10.1002/2015JD023586</ext-link>, 2015.</mixed-citation></ref>
      <ref id="bib1.bibx55"><label>Ralph and Dettinger(2011)</label><mixed-citation>Ralph, F. M. and Dettinger, M. D.: Storms, floods, and the science of
atmospheric rivers, Eos T. Am. Geophys. Un., 92,
265–266, <ext-link xlink:href="https://doi.org/10.1029/2011EO320001" ext-link-type="DOI">10.1029/2011EO320001</ext-link>,  2011.</mixed-citation></ref>
      <ref id="bib1.bibx56"><label>Ralph et al.(2004)Ralph, Neiman, and Wick</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,
<ext-link xlink:href="https://doi.org/10.1175/1520-0493(2004)132&lt;1721:SACAOO&gt;2.0.CO;2" ext-link-type="DOI">10.1175/1520-0493(2004)132&lt;1721:SACAOO&gt;2.0.CO;2</ext-link>,
2004.</mixed-citation></ref>
      <ref id="bib1.bibx57"><label>Ralph et al.(2005)Ralph, Neiman, and Rotunno</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="https://doi.org/10.1175/MWR2896.1" ext-link-type="DOI">10.1175/MWR2896.1</ext-link>, 2005.</mixed-citation></ref>
      <ref id="bib1.bibx58"><label>Ralph et al.(2006)Ralph, Neiman, Wick, Gutman, Dettinger, Cayan, and
White</label><mixed-citation>Ralph, F. M., Neiman, P. J., Wick, G. A., Gutman, S. I., Dettinger, M. D.,
Cayan, D. R., and White, A. B.: Flooding on California's Russian River: Role
of atmospheric rivers, Geophys. Res. Lett., 33, L13801,
<ext-link xlink:href="https://doi.org/10.1029/2006GL026689" ext-link-type="DOI">10.1029/2006GL026689</ext-link>, 2006.</mixed-citation></ref>
      <ref id="bib1.bibx59"><label>Ralph et al.(2013)Ralph, Coleman, Neiman, Zamora, and
Dettinger</label><mixed-citation>Ralph, F. M., Coleman, T., Neiman, P. J., Zamora, R. J., and 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, <ext-link xlink:href="https://doi.org/{10.1175/JHM-D-12-076.1}" ext-link-type="DOI">10.1175/JHM-D-12-076.1</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bibx60"><label>Ramos et al.(2015)Ramos, Trigo, Liberato, and Tomé</label><mixed-citation>Ramos, A. M., Trigo, R. M., Liberato, M. L. R., and Tomé, R.: Daily
precipitation extreme events in the Iberian Peninsula and its association
with Atmospheric Rivers, J. Hydrometeorol., 16, 579–597,
<ext-link xlink:href="https://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.bibx61"><label>Ramos et al.(2016)Ramos, Trigo, Liberato, and Lavers</label><mixed-citation>Ramos, A. M., Nieto, R., Tomé, R., Gimeno, L., Trigo, R. M., Liberato, M.
L. R., and Lavers, D. A.: Atmospheric rivers moisture sources from a
Lagrangian perspective, Earth Syst. Dynam., 7, 371–384,
<ext-link xlink:href="https://doi.org/10.5194/esd-7-371-2016" ext-link-type="DOI">10.5194/esd-7-371-2016</ext-link>, 2016.</mixed-citation></ref>
      <ref id="bib1.bibx62"><label>Rienecker et al.(2011)Rienecker, Suarez, Gelaro, Todling, Bacmeister,
Liu, Bosilovich, Schubert, Takacs, Kim et al.</label><mixed-citation>Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J.,
Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G., Bloom, S.,
Chen, J.,  Collins, D.,  Conaty, A.,  da Silva, A.,  Gu, W.,  Joiner, J.,  Koster, R.
D.,
Lucchesi, R.,  Molod, A.,  Owens, T.,  Pawson, S.,  Pegion, P.,  Redder, C. R.,
Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen,
J.:
MERRA: NASA's modern-era retrospective analysis for research and
applications, J. Climate, 24, 3624–3648, <ext-link xlink:href="https://doi.org/10.1175/JCLI-D-11-00015.1" ext-link-type="DOI">10.1175/JCLI-D-11-00015.1</ext-link>, 2011.
</mixed-citation></ref><?xmltex \hack{\newpage}?>
      <ref id="bib1.bibx63"><label>Rutz et al.(2013)Rutz, Steenburgh, and Ralph</label><mixed-citation>Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological
Characteristics of Atmospheric Rivers and Their Inland Penetration over the
Western United States, Mon. Weather Rev., 142, 905–921,
<ext-link xlink:href="https://doi.org/10.1175/MWR-D-13-00168.1" ext-link-type="DOI">10.1175/MWR-D-13-00168.1</ext-link>,  2013.</mixed-citation></ref>
      <ref id="bib1.bibx64"><label>Rutz et al.(2014)Rutz, Steenburgh, and Ralph</label><mixed-citation>
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological
characteristics of atmospheric rivers and their inland penetration over the
western United States, Mon. Weather Rev., 142, 905–921, 2014.</mixed-citation></ref>
      <ref id="bib1.bibx65"><label>Ryoo et al.(2015)Ryoo, Waliser, Waugh, Wong, Fetzer, and
Fung</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 US West Coast using a
trajectory model, J. Geophys. Res.-Atmos., 120,
3007–3028, 2015.</mixed-citation></ref>
      <ref id="bib1.bibx66"><label>Shin and Hong(2011)</label><mixed-citation>
Shin, H. H. and Hong, S.-Y.: Intercomparison of planetary boundary-layer
parametrizations in the WRF model for a single day from CASES-99,
Bound.-Lay. Meteorol., 139, 261–281, 2011.</mixed-citation></ref>
      <ref id="bib1.bibx67"><label>Shutts(1990)</label><mixed-citation>
Shutts, G. J.: Dynamical aspects of the October storm, 1987: A study of a
successful fine-mesh simulation, Q. J. Roy. Meteor. Soc,  116, 1315–1347,
1990.</mixed-citation></ref>
      <ref id="bib1.bibx68"><label>Skamarock et al.(2005)Skamarock, Klemp, Dudhia, Gill, Barker, Wang,
and Powers</label><mixed-citation>
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang,
W., and Powers, J. G.: A description of the advanced research WRF version 2,
Tech. rep., DTIC Document, 2005.</mixed-citation></ref>
      <ref id="bib1.bibx69"><label>Sodemann and Stohl(2013)</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, <ext-link xlink:href="https://doi.org/10.1175/MWR-D-12-00256.1" ext-link-type="DOI">10.1175/MWR-D-12-00256.1</ext-link>, 2013.</mixed-citation></ref>
      <ref id="bib1.bibx70"><label>Warner et al.(2012)Warner, Mass, and Salathé</label><mixed-citation>Warner, M. D., Mass, C. F., and Salathé, E. P.: Wintertime Extreme
Precipitation Events along the Pacific Northwest Coast: Climatology and
Synoptic Evolution, Mon. Weather Rev., 140, 2021–2043,
<ext-link xlink:href="https://doi.org/10.1175/MWR-D-11-00197.1" ext-link-type="DOI">10.1175/MWR-D-11-00197.1</ext-link>,  2012.</mixed-citation></ref>
      <ref id="bib1.bibx71"><label>Warner et al.(2014)Warner, Mass, and Salathé</label><mixed-citation>Warner, M. D., Mass, C. F., and Salathé, E. P.: Changes in Winter
Atmospheric
Rivers along the North American West Coast in CMIP5 Climate Models, J.
Hydrometeorol., 16, 118–128, <ext-link xlink:href="https://doi.org/10.1175/JHM-D-14-0080.1" ext-link-type="DOI">10.1175/JHM-D-14-0080.1</ext-link>,  2014.</mixed-citation></ref>
      <ref id="bib1.bibx72"><label>Zhu and Newell(1998)</label><mixed-citation>Zhu, Y. and Newell, R. E.: A Proposed Algorithm for Moisture Fluxes from
Atmospheric Rivers, Mon. Weather Rev., 126, 725–735,
<ext-link xlink:href="https://doi.org/10.1175/1520-0493(1998)126&lt;0725:APAFMF&gt;2.0.CO;2" ext-link-type="DOI">10.1175/1520-0493(1998)126&lt;0725:APAFMF&gt;2.0.CO;2</ext-link>,
1998.</mixed-citation></ref>

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

    </app></app-group></back>
    <!--<article-title-html>Evaluation of the moisture sources in two extreme landfalling atmospheric river events using an Eulerian WRF tracers tool</article-title-html>
<abstract-html><p class="p">A new 3-D tracer tool is coupled to the WRF model to analyze the origin of
the moisture in two extreme atmospheric river (AR) events: the so-called
<q>Great Coastal Gale of 2007</q> in the
Pacific Ocean and the <q>Great Storm of
1987</q> in the North Atlantic. Results show that
between 80 and 90 % of moisture advected by the ARs, and a high
percentage of the total precipitation produced by the systems have a
tropical origin. The tropical contribution to precipitation is in general
above 50 % and largely exceeds this value in the most affected areas.
Local convergence transport is responsible for the remaining moisture and
precipitation. The ratio of tropical moisture to total moisture is maximized
as the cold front arrives on land. Vertical cross sections of the moisture
content suggest that the maximum in tropical humidity does not necessarily
coincide with the low-level jet (LLJ) of the extratropical cyclone. Instead,
the amount of tropical humidity is maximized in the lowest atmospheric level
in southern latitudes and can be located above, below or ahead of the LLJ
in northern latitudes in both analyzed cases.</p></abstract-html>
<ref-html id="bib1.bib1"><label>Arnault et al.(2016)</label><mixed-citation>
Arnault, J., Knoche, R., Wei, J., and Kunstmann, H.: Evaporation tagging and
atmospheric water budget analysis with WRF: A regional
precipitation recycling study for West Africa, Water Resour. Res., 52, 1544–1567, <a href="https://doi.org/10.1002/2015WR017704" target="_blank">https://doi.org/10.1002/2015WR017704</a>,
2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>Avelino and Dall'erba(2016)</label><mixed-citation>
Avelino, A. and Dall'erba, S.: Comparing the economic impact of natural
disasters generated by different input-output models. An application to the
2007 Chehalis River Flood (WA), North American Regional Science Conference,
Minneapolis, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>Bao et al.(2006)Bao, Michelson, Neiman, Ralph, and Wilczak</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, <a href="https://doi.org/10.1175/MWR3123.1" target="_blank">https://doi.org/10.1175/MWR3123.1</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>Belo-Pereira et al.(2011)Belo-Pereira, Dutra, and
Viterbo</label><mixed-citation>
Belo-Pereira, M., Dutra, E., and Viterbo, P.: Evaluation of global
precipitation data sets over the Iberian Peninsula, J. Geophys. Res., 116,
D20101, <a href="https://doi.org/10.1029/2010JD015481" target="_blank">https://doi.org/10.1029/2010JD015481</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>Brands et al.(2016)Brands, Gutiérrez, and
San-Martín</label><mixed-citation>
Brands, S., Gutiérrez, J., and San-Martín, D.: Twentieth-century
atmospheric river activity along the west coasts of Europe and North America:
algorithm formulation, reanalysis uncertainty and links to atmospheric
circulation patterns, Clim. Dynam., 48, 2771–2795, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>Buckley and Marshall(2016)</label><mixed-citation>
Buckley, M. W. and Marshall, J.: Observations, inferences, and mechanisms of
the Atlantic Meridional Overturning Circulation: A review, Rev.
Geophys., 54, 5–63, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib7"><label>Buishand(1978)</label><mixed-citation>
Buishand, T.: Some remarks on the use of daily rainfall models, J.
Hydrol., 36, 295–308, 1978.
</mixed-citation></ref-html>
<ref-html id="bib1.bib8"><label>Bullock and Johnson(1971)</label><mixed-citation>
Bullock, B. R. and Johnson, D. R.: The generation of available potential
energy by latent heat release in a mid-latitude cyclone, Mon. Weather Rev.,
99, 1–14, 1971.
</mixed-citation></ref-html>
<ref-html id="bib1.bib9"><label>Burt and Mansfield(1988)</label><mixed-citation>
Burt, S. and Mansfield, A.: The Great Storm of 15–16 October 1987, Weather,
43,
90–110, 1988.
</mixed-citation></ref-html>
<ref-html id="bib1.bib10"><label>Cordeira et al.(2013)Cordeira, Ralph, and Moore</label><mixed-citation>
Cordeira, J. M., Ralph, F. M., and Moore, B. J.: The development and evolution
of two atmospheric rivers in proximity to western North Pacific tropical
cyclones in October 2010, Mon. Weather Rev., 141, 4234–4255, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib11"><label>Crout et al.(2008)Crout, Sears, and Locke</label><mixed-citation>
Crout, R. L., Sears, I. T., and Locke, L. K.: The Great Coastal Gale of 2007
from Coastal Storms Program Buoy 46089, OCEANS 2008, Quebec City, QC, 1–7,
<a href="https://doi.org/10.1109/OCEANS.2008.5152026" target="_blank">https://doi.org/10.1109/OCEANS.2008.5152026</a>, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib12"><label>Dacre et al.(2014)Dacre, Clark, Martinez-Alvarado, Stringer, and
Lavers</label><mixed-citation>
Dacre, H. F., Clark, P. A., Martinez-Alvarado, O., Stringer, M. A., and
Lavers, D. A.: How
do atmospheric rivers form?, B. Am. Meteorol. Soc., 96, 1243–1255,
2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib13"><label>Dettinger(2011)</label><mixed-citation>
Dettinger, M.: Climate Change, Atmospheric Rivers, and Floods in California
– A
Multimodel Analysis of Storm Frequency and Magnitude Changes, J.
Am. Water Resour. As., 47, 514–523,
<a href="https://doi.org/10.1111/j.1752-1688.2011.00546.x" target="_blank">https://doi.org/10.1111/j.1752-1688.2011.00546.x</a>,  2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib14"><label>Dettinger et al.(2015)Dettinger, Ralph, and Lavers</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="https://doi.org/10.1029/2015EO038675" target="_blank">https://doi.org/10.1029/2015EO038675</a>,
2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib15"><label>Dettinger et al.(2011)Dettinger, Ralph, Das, Neiman, and
Cayan</label><mixed-citation>
Dettinger, M. D., 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, <a href="https://doi.org/10.3390/w3020445" target="_blank">https://doi.org/10.3390/w3020445</a>, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib16"><label>Dominguez et al.(2016)Dominguez, Miguez-Macho, and
Hu</label><mixed-citation>
Dominguez, F., Miguez-Macho, G., and Hu, H.: WRF with Water Vapor Tracers: A
Study of Moisture Sources for the North American Monsoon, J.
Hydrometeorol., 17, 1915–1927, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib17"><label>Dominguez et al.(2017)</label><mixed-citation>
Dominguez, F., Dall'erba, S., Huang, S., Avelino, A., Mehran, A., Hu, H.,
Schmidt, A., Schick, L., and Lettenmaier, D.: Tracking an Atmospheric River
in a Warmer Climate: from Water Vapor to Economic Impacts, Earth Syst. Dynam.
Discuss., <a href="https://doi.org/10.5194/esd-2017-64" target="_blank">https://doi.org/10.5194/esd-2017-64</a>, in review, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib18"><label>Dudhia(1989)</label><mixed-citation>
Dudhia, J.: Numerical study of convection observed during the winter monsoon
experiment using a mesoscale two-dimensional model, J.
Atmos. Sci., 46, 3077–3107, 1989.
</mixed-citation></ref-html>
<ref-html id="bib1.bib19"><label>Eiras-Barca et al.(2016)Eiras-Barca, Brands, and
Miguez-Macho</label><mixed-citation>
Eiras-Barca, J., Brands, S., and Miguez-Macho, G.: Seasonal variations in
North Atlantic atmospheric river activity and associations with anomalous
precipitation over the Iberian Atlantic Margin, J. Geophys.
Res.-Atmos.,  121, 931–948, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib20"><label>Gimeno et al.(2016)Gimeno, Dominguez, Nieto, Trigo, Drumond, Reason,
Taschetto, Ramos, Kumar, and Marengo</label><mixed-citation>
Gimeno, L., Dominguez, F., Nieto, R., Trigo, R., Drumond, A., Reason, C. J.,
Taschetto, A. S., Ramos, A. M., Kumar, R., and Marengo, J.: Major mechanisms
of atmospheric moisture transport and their role in extreme precipitation
events, Annu. Rev. Env. Resour., 41, 117–141, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib21"><label>Gómez and Miguez-Macho(2017)</label><mixed-citation>
Gómez, B. and Miguez-Macho, G.: The impact of wave number selection and
spin up time when using spectral nudging for dynamical downscaling
applications,
Geophys. Res. Abstr.,
EGU2017-18466, EGU General Assembly 2017, Vienna, Austria, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib22"><label>Guan and Waliser(2015)</label><mixed-citation>
Guan, B. and Waliser, D. E.: Detection of atmospheric rivers: Evaluation and
application of an algorithm for global studies, J. Geophys.
Res.-Atmos., 120, 12514–12535, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib23"><label>Herrera et al.(2012)</label><mixed-citation>
Herrera, S., Gutiérrez, J. M., Ancell, R., Pons, M. R., Frías, M. D.,
and
Fernández, J.: Development and analysis of a 50-year high-resolution daily
gridded precipitation dataset over Spain (Spain02), Int. J.
Climatol., 32, 74–85, <a href="https://doi.org/10.1002/joc.2256" target="_blank">https://doi.org/10.1002/joc.2256</a>,  2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib24"><label>Higgins et al.(2000)Higgins, Schemm, Shi, and Leetmaa</label><mixed-citation>
Higgins, R., Schemm, J., Shi, W., and Leetmaa, A.: Extreme precipitation events
in the western United States related to tropical forcing, journal of climate,
13, 793–820, <a href="https://doi.org/10.1175/1520-0442(2000)013&lt;0793:EPEITW&gt;2.0.CO;2" target="_blank">https://doi.org/10.1175/1520-0442(2000)013&lt;0793:EPEITW&gt;2.0.CO;2</a>, 2000.
</mixed-citation></ref-html>
<ref-html id="bib1.bib25"><label>Hong and Lim(2006)</label><mixed-citation>
Hong, S.-Y. and Lim, J.-O. J.: The WRF single-moment 6-class microphysics
scheme (WSM6), J. Korean Meteor. Soc., 42, 129–151, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib26"><label>Hong et al.(2006)Hong, Noh, and Dudhia</label><mixed-citation>
Hong, S.-Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an
explicit treatment of entrainment processes, Mon. Weather Rev., 134,
2318–2341, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib27"><label>Hoskins and Berrisford(1988)</label><mixed-citation>
Hoskins, B. and Berrisford, P.: A potential vorticity perspective of the storm
of 15–16 October 1987, Weather, 43, 122–129, 1988.
</mixed-citation></ref-html>
<ref-html id="bib1.bib28"><label>Hu et al.(2010)Hu, Nielsen-Gammon, and Zhang</label><mixed-citation>
Hu, X.-M., Nielsen-Gammon, J. W., and Zhang, F.: Evaluation of three planetary
boundary layer schemes in the WRF model, J. Appl. Meteorol.
Clim., 49, 1831–1844, 2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib29"><label>Hu et al.(2013)Hu, Klein, and Xue</label><mixed-citation>
Hu, X.-M., Klein, P. M., and Xue, M.: Evaluation of the updated YSU planetary
boundary layer scheme within WRF for wind resource and air quality
assessments, J. Geophys. Res.-Atmos., 118, 10490–10505  <a href="https://doi.org/10.1002/jgrd.50823" target="_blank">https://doi.org/10.1002/jgrd.50823</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib30"><label>Insua-Costa and Miguez-Macho(2017)</label><mixed-citation>
Insua-Costa, D. and Miguez-Macho, G.: A new moisture tagging capability in
the Weather Research and Forecasting Model: formulation, validation and
application to the 2014 Great Lake-effect snowstorm, Earth Syst. Dynam.
Discuss., <a href="https://doi.org/10.5194/esd-2017-80" target="_blank">https://doi.org/10.5194/esd-2017-80</a>, in review, 2017.
</mixed-citation></ref-html>
<ref-html id="bib1.bib31"><label>Kain(2004)</label><mixed-citation>
Kain, J. S.: The Kain–Fritsch convective parameterization: an update, J.
Appl. Meteorol., 43, 170–181, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib32"><label>Kim et al.(2013)Kim, Waliser, Neiman, Guan, Ryoo, and Wick</label><mixed-citation>
Kim, J., Waliser, D., Neiman, P., Guan, B., Ryoo, J.-M., and Wick, G.: Effects
of atmospheric river landfalls on the cold season precipitation in
California, Clim. Dynam., 40, 465–474, <a href="https://doi.org/10.1007/s00382-012-1322-3" target="_blank">https://doi.org/10.1007/s00382-012-1322-3</a>,  2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib33"><label>Knippertz and Wernli(2010)</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.bib34"><label>Knippertz et al.(2013)Knippertz, Wernli, and
Gläser</label><mixed-citation>
Knippertz, P., Wernli, H., and Gläser, G.: A global climatology of tropical
moisture exports, J. Climate, 26, 3031–3045, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib35"><label>Lavers and Villarini(2013)</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, <a href="https://doi.org/10.1002/grl.50636" target="_blank">https://doi.org/10.1002/grl.50636</a>,  2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib36"><label>Lavers and Villarini(2014)</label><mixed-citation>
Lavers, D. A. and Villarini, G.: The relationship between daily European
precipitation and measures of atmospheric water vapour transport,
Int. J. Climatol., 35, 2187–2192, <a href="https://doi.org/10.1002/joc.4119" target="_blank">https://doi.org/10.1002/joc.4119</a>,  2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib37"><label>Lavers et al.(2011)Lavers, Allan, Wood, Villarini, Brayshaw, and
Wade</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="https://doi.org/10.1029/2011GL049783" target="_blank">https://doi.org/10.1029/2011GL049783</a>,  2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib38"><label>Lavers et al.(2012)Lavers, Villarini, Allan, Wood, and
Wade</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.-Atmos., 117, D20106, <a href="https://doi.org/10.1029/2012JD018027" target="_blank">https://doi.org/10.1029/2012JD018027</a>,  2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib39"><label>Lavers et al.(2013)Lavers, Allan, Villarini, Lloyd-Hughes, Brayshaw,
and Wade</label><mixed-citation>
Lavers, D. A., Allan, R. P., Villarini, G., Lloyd-Hughes, B., Brayshaw, D. J.,
and Wade, A. J.: Future changes in atmospheric rivers and their implications
for winter flooding in Britain, Environ. Res. Lett., 8, 034010, <a href="https://doi.org/10.1088/1748-9326/8/3/034010" target="_blank">https://doi.org/10.1088/1748-9326/8/3/034010</a>,
2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib40"><label>Leung and Qian(2009)</label><mixed-citation>
Leung, L. R. and Qian, Y.: Atmospheric rivers induced heavy precipitation and
flooding in the western U.S. simulated by the WRF regional climate model,
Geophys. Res. Lett., 36, L03820, <a href="https://doi.org/10.1029/2008GL036445" target="_blank">https://doi.org/10.1029/2008GL036445</a>,  2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib41"><label>Livneh et al.(2015)Livneh, Bohn, Pierce, Munoz-Arriola, Nijssen,
Vose, Cayan, and Brekke</label><mixed-citation>
Livneh, B., Bohn, T. J., Pierce, D. W., Munoz-Arriola, F., Nijssen, B., Vose,
R., Cayan, D. R., and Brekke, L.: A spatially comprehensive,
hydrometeorological data set for Mexico, the US, and Southern Canada
1950–2013, Scientific data, 2, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib42"><label>Mahoney et al.(2016)Mahoney, Jackson, Neiman, Hughes, Darby, Wick,
White, Sukovich, and Cifelli</label><mixed-citation>
Mahoney, K., Jackson, D. L., Neiman, P., Hughes, M., Darby, L., Wick, G.,
White, A., Sukovich, E., and Cifelli, R.: Understanding the role of
atmospheric rivers in heavy precipitation in the southeast United States,
Mon. Weather Rev., 144, 1617–1632, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib43"><label>Maraun et al.(2010)</label><mixed-citation>
Maraun, D.,  Wetterhall, F.,  Ireson, A. M.,  Chandler, R. E.,  Kendon, E. J.,
Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema,
V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and
Thiele-Eich, I.: Precipitation
downscaling under climate change: Recent developments to bridge the gap
between dynamical models and the end user, Rev. Geophys., 48, RG3003,
<a href="https://doi.org/10.1029/2009RG000314" target="_blank">https://doi.org/10.1029/2009RG000314</a>,
2010.
</mixed-citation></ref-html>
<ref-html id="bib1.bib44"><label>Michalakes et al.(2005)Michalakes, Dudhia, Gill, Henderson, Klemp,
Skamarock, and Wang</label><mixed-citation>
Michalakes, J., Dudhia, J., Gill, D., Henderson, T., Klemp, J., Skamarock, W.,
and Wang, W.: The weather research and forecast model: software architecture
and performance, in: Proceedings of the Eleventh ECMWF Workshop on the Use of
High Performance Computing in Meteorology,  156–168, World Scientific:
Singapore, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib45"><label>Miguez-Macho et al.(2004)Miguez-Macho, Stenchikov, and
Robock</label><mixed-citation>
Miguez-Macho, G., Stenchikov, G. L., and Robock, A.: Spectral nudging to
eliminate the effects of domain position and geometry in regional climate
model simulations, J. Geophys. Res.-Atmos., 109, D13104, <a href="https://doi.org/10.1029/2003JD004495" target="_blank">https://doi.org/10.1029/2003JD004495</a>, 2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib46"><label>Miguez-Macho et al.(2005)Miguez-Macho, Stenchikov, and
Robock</label><mixed-citation>
Miguez-Macho, G., Stenchikov, G. L., and Robock, A.: Regional climate
simulations over North America: Interaction of local processes with improved
large-scale flow, J. Climate, 18, 1227–1246, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib47"><label>Miguez-Macho et al.(2013)Miguez-Macho, Rios-Entenza, and
Dominguez</label><mixed-citation>
Miguez-Macho, G., Rios-Entenza, A., and Dominguez, F.: Regional climate
simulations with moisture tracers to investigate land-atmosphere interactions
in the terrestrial water cycle over the Iberian Peninsula,
Geophys. Res. Abstr.,
EGU2013-12677, EGU General Assembly 2013, Vienna, Austria, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib48"><label>Mlawer et al.(1997)Mlawer, Taubman, Brown, Iacono, and
Clough</label><mixed-citation>
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.:
Radiative transfer for inhomogeneous atmospheres: RRTM, a validated
correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, 1997.
</mixed-citation></ref-html>
<ref-html id="bib1.bib49"><label>Mundhenk et al.(2016)Mundhenk, Barnes, Maloney, and
Nardi</label><mixed-citation>
Mundhenk, B. D., Barnes, E. A., Maloney, E. D., and Nardi, K. M.: Modulation of
atmospheric rivers near Alaska and the US West Coast by northeast Pacific
height anomalies, J. Geophys. Res.-Atmos., 121,
12751–12765, <a href="https://doi.org/10.1002/2016JD025350" target="_blank">https://doi.org/10.1002/2016JD025350</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib50"><label>Nayak et al.(2014)Nayak, Villarini, and Lavers</label><mixed-citation>
Nayak, M. A., Villarini, G., and Lavers, D. A.: On the skill of numerical
weather prediction models to forecast atmospheric rivers over the central
United States, Geophys. Res. Lett., 41, 4354–4362, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib51"><label>Neiman et al.(2008a)Neiman, Ralph, Wick, Kuo, Wee, Ma, Taylor, and
Dettinger</label><mixed-citation>
Neiman, P. J., Ralph, F. M., Wick, G. A., Kuo, Y.-H., Wee, T.-K., Ma, Z.,
Taylor, G. H., and Dettinger, M. D.: Diagnosis of an Intense Atmospheric
River Impacting the Pacific Northwest: Storm Summary and Offshore Vertical
Structure Observed with COSMIC Satellite Retrievals, Mon. Weather Rev., 136,
4398–4420,   2008a.
</mixed-citation></ref-html>
<ref-html id="bib1.bib52"><label>Neiman et al.(2008b)Neiman, Ralph, Wick, Lundquist, and
Dettinger</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,
<a href="https://doi.org/10.1175/2007JHM855.1" target="_blank">https://doi.org/10.1175/2007JHM855.1</a>,  2008b.
</mixed-citation></ref-html>
<ref-html id="bib1.bib53"><label>NOAA(2008)</label><mixed-citation>
NOAA (National Oceanic and Atmosphere Administration): Pacific Northwest
Storms of December, U.S. DEPARTMENT OF COMMERCE National Oceanic and
Atmospheric Administration National Weather Service Silver Spring, Maryland,
1–3, 2008.
</mixed-citation></ref-html>
<ref-html id="bib1.bib54"><label>Payne and Magnusdottir(2015)</label><mixed-citation>
Payne, A. E. and Magnusdottir, G.: An evaluation of atmospheric rivers over the
North Pacific in CMIP5 and their response to warming under RCP 8.5, J.
Geophys. Res.-Atmos., 120, 11173–11190, <a href="https://doi.org/10.1002/2015JD023586" target="_blank">https://doi.org/10.1002/2015JD023586</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib55"><label>Ralph and Dettinger(2011)</label><mixed-citation>
Ralph, F. M. and Dettinger, M. D.: Storms, floods, and the science of
atmospheric rivers, Eos T. Am. Geophys. Un., 92,
265–266, <a href="https://doi.org/10.1029/2011EO320001" target="_blank">https://doi.org/10.1029/2011EO320001</a>,  2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib56"><label>Ralph et al.(2004)Ralph, Neiman, and Wick</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,
<a href="https://doi.org/10.1175/1520-0493(2004)132&lt;1721:SACAOO&gt;2.0.CO;2" target="_blank">https://doi.org/10.1175/1520-0493(2004)132&lt;1721:SACAOO&gt;2.0.CO;2</a>,
2004.
</mixed-citation></ref-html>
<ref-html id="bib1.bib57"><label>Ralph et al.(2005)Ralph, Neiman, and Rotunno</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="https://doi.org/10.1175/MWR2896.1" target="_blank">https://doi.org/10.1175/MWR2896.1</a>, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib58"><label>Ralph et al.(2006)Ralph, Neiman, Wick, Gutman, Dettinger, Cayan, and
White</label><mixed-citation>
Ralph, F. M., Neiman, P. J., Wick, G. A., Gutman, S. I., Dettinger, M. D.,
Cayan, D. R., and White, A. B.: Flooding on California's Russian River: Role
of atmospheric rivers, Geophys. Res. Lett., 33, L13801,
<a href="https://doi.org/10.1029/2006GL026689" target="_blank">https://doi.org/10.1029/2006GL026689</a>, 2006.
</mixed-citation></ref-html>
<ref-html id="bib1.bib59"><label>Ralph et al.(2013)Ralph, Coleman, Neiman, Zamora, and
Dettinger</label><mixed-citation>
Ralph, F. M., Coleman, T., Neiman, P. J., Zamora, R. J., and 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, <a href="https://doi.org/{10.1175/JHM-D-12-076.1}" target="_blank">https://doi.org/10.1175/JHM-D-12-076.1</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib60"><label>Ramos et al.(2015)Ramos, Trigo, Liberato, and Tomé</label><mixed-citation>
Ramos, A. M., Trigo, R. M., Liberato, M. L. R., and Tomé, R.: Daily
precipitation extreme events in the Iberian Peninsula and its association
with Atmospheric Rivers, J. Hydrometeorol., 16, 579–597,
<a href="https://doi.org/10.1175/JHM-D-14-0103.1" target="_blank">https://doi.org/10.1175/JHM-D-14-0103.1</a>,  2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib61"><label>Ramos et al.(2016)Ramos, Trigo, Liberato, and Lavers</label><mixed-citation>
Ramos, A. M., Nieto, R., Tomé, R., Gimeno, L., Trigo, R. M., Liberato, M.
L. R., and Lavers, D. A.: Atmospheric rivers moisture sources from a
Lagrangian perspective, Earth Syst. Dynam., 7, 371–384,
<a href="https://doi.org/10.5194/esd-7-371-2016" target="_blank">https://doi.org/10.5194/esd-7-371-2016</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib62"><label>Rienecker et al.(2011)Rienecker, Suarez, Gelaro, Todling, Bacmeister,
Liu, Bosilovich, Schubert, Takacs, Kim et al.</label><mixed-citation>
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J.,
Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G., Bloom, S.,
Chen, J.,  Collins, D.,  Conaty, A.,  da Silva, A.,  Gu, W.,  Joiner, J.,  Koster, R.
D.,
Lucchesi, R.,  Molod, A.,  Owens, T.,  Pawson, S.,  Pegion, P.,  Redder, C. R.,
Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen,
J.:
MERRA: NASA's modern-era retrospective analysis for research and
applications, J. Climate, 24, 3624–3648, <a href="https://doi.org/10.1175/JCLI-D-11-00015.1" target="_blank">https://doi.org/10.1175/JCLI-D-11-00015.1</a>, 2011.

</mixed-citation></ref-html>
<ref-html id="bib1.bib63"><label>Rutz et al.(2013)Rutz, Steenburgh, and Ralph</label><mixed-citation>
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological
Characteristics of Atmospheric Rivers and Their Inland Penetration over the
Western United States, Mon. Weather Rev., 142, 905–921,
<a href="https://doi.org/10.1175/MWR-D-13-00168.1" target="_blank">https://doi.org/10.1175/MWR-D-13-00168.1</a>,  2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib64"><label>Rutz et al.(2014)Rutz, Steenburgh, and Ralph</label><mixed-citation>
Rutz, J. J., Steenburgh, W. J., and Ralph, F. M.: Climatological
characteristics of atmospheric rivers and their inland penetration over the
western United States, Mon. Weather Rev., 142, 905–921, 2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib65"><label>Ryoo et al.(2015)Ryoo, Waliser, Waugh, Wong, Fetzer, and
Fung</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 US West Coast using a
trajectory model, J. Geophys. Res.-Atmos., 120,
3007–3028, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib66"><label>Shin and Hong(2011)</label><mixed-citation>
Shin, H. H. and Hong, S.-Y.: Intercomparison of planetary boundary-layer
parametrizations in the WRF model for a single day from CASES-99,
Bound.-Lay. Meteorol., 139, 261–281, 2011.
</mixed-citation></ref-html>
<ref-html id="bib1.bib67"><label>Shutts(1990)</label><mixed-citation>
Shutts, G. J.: Dynamical aspects of the October storm, 1987: A study of a
successful fine-mesh simulation, Q. J. Roy. Meteor. Soc,  116, 1315–1347,
1990.
</mixed-citation></ref-html>
<ref-html id="bib1.bib68"><label>Skamarock et al.(2005)Skamarock, Klemp, Dudhia, Gill, Barker, Wang,
and Powers</label><mixed-citation>
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Wang,
W., and Powers, J. G.: A description of the advanced research WRF version 2,
Tech. rep., DTIC Document, 2005.
</mixed-citation></ref-html>
<ref-html id="bib1.bib69"><label>Sodemann and Stohl(2013)</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, <a href="https://doi.org/10.1175/MWR-D-12-00256.1" target="_blank">https://doi.org/10.1175/MWR-D-12-00256.1</a>, 2013.
</mixed-citation></ref-html>
<ref-html id="bib1.bib70"><label>Warner et al.(2012)Warner, Mass, and Salathé</label><mixed-citation>
Warner, M. D., Mass, C. F., and Salathé, E. P.: Wintertime Extreme
Precipitation Events along the Pacific Northwest Coast: Climatology and
Synoptic Evolution, Mon. Weather Rev., 140, 2021–2043,
<a href="https://doi.org/10.1175/MWR-D-11-00197.1" target="_blank">https://doi.org/10.1175/MWR-D-11-00197.1</a>,  2012.
</mixed-citation></ref-html>
<ref-html id="bib1.bib71"><label>Warner et al.(2014)Warner, Mass, and Salathé</label><mixed-citation>
Warner, M. D., Mass, C. F., and Salathé, E. P.: Changes in Winter
Atmospheric
Rivers along the North American West Coast in CMIP5 Climate Models, J.
Hydrometeorol., 16, 118–128, <a href="https://doi.org/10.1175/JHM-D-14-0080.1" target="_blank">https://doi.org/10.1175/JHM-D-14-0080.1</a>,  2014.
</mixed-citation></ref-html>
<ref-html id="bib1.bib72"><label>Zhu and Newell(1998)</label><mixed-citation>
Zhu, Y. and Newell, R. E.: A Proposed Algorithm for Moisture Fluxes from
Atmospheric Rivers, Mon. Weather Rev., 126, 725–735,
<a href="https://doi.org/10.1175/1520-0493(1998)126&lt;0725:APAFMF&gt;2.0.CO;2" target="_blank">https://doi.org/10.1175/1520-0493(1998)126&lt;0725:APAFMF&gt;2.0.CO;2</a>,
1998.
</mixed-citation></ref-html>--></article>
