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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">ACP</journal-id>
<journal-title-group>
<journal-title>Atmospheric Chemistry and Physics</journal-title>
<abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Atmos. Chem. Phys.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1680-7324</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>

    <article-meta>
      <article-id pub-id-type="doi">10.5194/acp-17-10893-2017</article-id><title-group><article-title>A meteorological and chemical overview of the DACCIWA field campaign in West
Africa in June–July 2016</article-title>
      </title-group><?xmltex \runningtitle{A meteorological and chemical overview of the DACCIWA field campaign}?><?xmltex \runningauthor{P.~Knippertz et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Knippertz</surname><given-names>Peter</given-names></name>
          <email>peter.knippertz@kit.edu</email>
        <ext-link>https://orcid.org/0000-0001-9856-619X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Fink</surname><given-names>Andreas H.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-5840-2120</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Deroubaix</surname><given-names>Adrien</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-4464-7802</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Morris</surname><given-names>Eleanor</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Tocquer</surname><given-names>Flore</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Evans</surname><given-names>Mat J.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-4775-032X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Flamant</surname><given-names>Cyrille</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-8309-6495</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Gaetani</surname><given-names>Marco</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-2923-6773</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Lavaysse</surname><given-names>Christophe</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-8704-9680</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Mari</surname><given-names>Celine</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Marsham</surname><given-names>John H.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0003-3219-8472</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8">
          <name><surname>Meynadier</surname><given-names>Rémi</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff9">
          <name><surname>Affo-Dogo</surname><given-names>Abalo</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Bahaga</surname><given-names>Titike</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Brosse</surname><given-names>Fabien</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-5652-9454</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Deetz</surname><given-names>Konrad</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Guebsi</surname><given-names>Ridha</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff9">
          <name><surname>Latifou</surname><given-names>Issaou</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Maranan</surname><given-names>Marlon</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-0324-8859</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Rosenberg</surname><given-names>Philip D.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-6920-0559</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Schlueter</surname><given-names>Andreas</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-5398-8150</ext-link></contrib>
        <aff id="aff1"><label>1</label><institution>Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Laboratoire de Météorologie Dynamique, Ecole Polytechnique, IPSL Research University,
Ecole Normale Supérieure, Université Paris-Saclay, Sorbonne Universités,
UPMC Univ Paris 06, CNRS, 91128 Palaiseau, France</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, 31400 Toulouse, France</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>LATMOS/IPSL, Sorbonne Universités, UPMC Univ Paris 06, UVSQ, CNRS, 75252 Paris, France</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>European Commission, Joint Research Centre, Ispra (VA), Italy</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>School of Earth &amp; Environment/National Centre for Atmospheric Science, University of Leeds, Leeds LS2 9JT, UK</institution>
        </aff>
        <aff id="aff8"><label>8</label><institution>AXA Group Risk Management Department, Paris, France</institution>
        </aff>
        <aff id="aff9"><label>9</label><institution>Direction Générale Météo Nationale, B.P. 1505, Lomé, Togo</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Peter Knippertz (peter.knippertz@kit.edu)</corresp></author-notes><pub-date><day>14</day><month>September</month><year>2017</year></pub-date>
      
      <volume>17</volume>
      <issue>17</issue>
      <fpage>10893</fpage><lpage>10918</lpage>
      <history>
        <date date-type="received"><day>13</day><month>April</month><year>2017</year></date>
           <date date-type="rev-request"><day>4</day><month>May</month><year>2017</year></date>
           <date date-type="rev-recd"><day>26</day><month>July</month><year>2017</year></date>
           <date date-type="accepted"><day>31</day><month>July</month><year>2017</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://acp.copernicus.org/articles/.html">This article is available from https://acp.copernicus.org/articles/.html</self-uri>
<self-uri xlink:href="https://acp.copernicus.org/articles/.pdf">The full text article is available as a PDF file from https://acp.copernicus.org/articles/.pdf</self-uri>


      <abstract>
    <p>In June
and July 2016 the Dynamics–Aerosol–Chemistry–Cloud Interactions in West
Africa (DACCIWA) project organised a major international field campaign in
southern West Africa (SWA) including measurements from three inland ground
supersites, urban sites in Cotonou and Abidjan, radiosondes, and three
research aircraft. A significant range of different weather situations were
encountered during this period, including the monsoon onset. The purpose of
this paper is to characterise the large-scale setting for the campaign as
well as synoptic and mesoscale weather systems affecting the study region in
the light of existing conceptual ideas, mainly using objective and subjective
identification algorithms based on (re-)analysis and satellite products. In
addition, it is shown how the described synoptic variations influence the
atmospheric composition over SWA through advection of mineral dust, biomass
burning and urban pollution plumes.</p>
    <p>The boreal summer of 2016 was characterised by Pacific La Niña, Atlantic
El Niño and warm eastern Mediterranean conditions, whose competing
influences on precipitation led to an overall average rainy season. During
the relatively dusty pre-onset Phase 1 (1–21 June 2016), three westward-propagating coherent cyclonic vortices between 4 and 13<inline-formula><mml:math id="M1" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N modulated
winds and rainfall in the Guinea coastal area. The monsoon onset occurred in
connection with a marked extratropical trough and cold surge over northern
Africa, leading to a breakdown of the Saharan heat low and African easterly
jet and a suppression of rainfall. During this period, quasi-stationary
low-level vortices associated with the trough transformed into more tropical,
propagating disturbances resembling an African easterly wave (AEW). To the
east of this system, moist southerlies penetrated deep into the continent.
The post-onset Phase 2 (22 June–20 July 2016) was characterised by a
significant increase in low-level cloudiness, unusually dry conditions and
strong northeastward dispersion of urban pollution plumes in SWA as well as
rainfall modulation by westward-propagating AEWs in the Sahel. Around
12–14 July 2016 an interesting and so-far undocumented cyclonic–anticyclonic
vortex couplet crossed SWA. The anticyclonic centre had its origin in the
Southern Hemisphere and transported unusually dry air filled with aged
aerosol into the region. During Phase 3 (21–26 July 2016), a similar vortex
couplet slightly farther north created enhanced westerly moisture transports
into SWA and extraordinarily wet conditions, accompanied by a deep
penetration of the biomass burning plume from central Africa. Finally, a
return to more undisturbed monsoon conditions took place during Phase 4
(27–31 July 2016). The in-depth synoptic analysis reveals that several
significant weather systems during the DACCIWA campaign cannot be attributed
unequivocally to any of the tropical waves and disturbances described in the
literature and thus deserve further study.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>The atmosphere over summertime West Africa is influenced by
processes covering a wide range of scales, which can interact with each other
in complex ways (Lafore et al., 2010; Redelsperger et al., 2006). The
dominating phenomenon is the West African monsoon (WAM), which is mainly
driven by the surface pressure contrast between the relatively cool waters of
the eastern tropical Atlantic Ocean and the Saharan heat low (SHL). The
former is related to the installation of the Atlantic cold tongue (ACT)
starting in April–May and reaching its maximum horizontal extension in
mid-August (Caniaux et al., 2011). At the Equator, colder sea surface temperatures (SSTs) increase the
stability of the marine atmospheric boundary layer and decrease the vertical
mixing of momentum, leading to weaker surface southerlies (Wallace et
al., 1989), while north of the Equator as far as the Guinea coast, the large
meridional SST gradient strengthens the surface wind through a
hydrostatically induced meridional pressure gradient (Lindzen and Nigam,
1987). This creates a low-level circulation characterised by surface wind
divergence and subsidence over the Equator and convergence and convection
close to the Guinea coast in the period before the full onset of the WAM.</p>
      <p>The SHL is a lower tropospheric thermal depression in the Sahara desert west
of 10<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, which develops in response to the intense surface heating
during boreal summer (Lavaysse et al., 2009). The monsoon typically sets in
quite abruptly around the end of June accompanied by a shift in the area of
main rainfall from the Guinea coast to the Sahel (Fitzpatrick et al., 2015;
Sultan and Janicot, 2003). This event is usually preceded by a northward
shift in the so-called intertropical discontinuity (ITD), the near-surface
confluence zone between southwesterly and northeasterly winds, which marks a
northern limit of rainfall occurrence (Fitzpatrick et al., 2016; Lélé
and Lamb, 2010). After the monsoon onset, the mid-tropospheric circulation
over West Africa is dominated by the African easterly jet (AEJ), which is
caused by the strong meridional temperature and moisture gradient at low
levels (Cook, 1999; Wu et al., 2009). The AEJ is maintained by the
anticyclonic circulation associated with the monsoonal subsidence, which
characterises the mid-upper troposphere over the Sahara (Chen, 2005;
Thorncroft and Blackburn, 1999) and above the shallow dry convection in the
SHL (Garcia-Carreras et al., 2015; Ryder et al., 2015). Barotropic and
baroclinic instabilities associated with the jet create an environment
favourable to the generation of African easterly waves (AEWs) (Thorncroft and
Hoskins, 1994a, b; Wu et al., 2012), synoptic-scale disturbances
characterised by a 2–6-day period in the Sahel. Diedhiou et al. (1999)
present evidence for a more intermittent, slower (6–9-day period) wave
regime with cyclonic and anticyclonic centres straddling the AEJ, longer
wavelengths and an activity maximum over the continent in June and July.</p>
      <p>On multi-decadal to inter-annual timescales, WAM variability is strongly
associated with global SST anomalies (Rodríguez-Fonseca et al., 2015;
Rowell, 2013). For example, positive phases of the Atlantic multi-decadal
variability favour precipitation in the Sahel (Ting et al., 2011; Zhang and
Delworth, 2006). On inter-annual timescales, SST variability in the tropical
Atlantic modulates the land–sea thermal gradient, leading to meridional
displacements of the precipitation belt over West Africa (Losada et
al., 2010; Polo et al., 2008). SSTs over the Mediterranean Sea influence the
amount of moisture being transported across the Sahara desert and converging
over the eastern Sahel (Fontaine et al., 2010; Gaetani et al., 2010).
Inter-annual variability in the WAM is also influenced by the SST variability
in the tropical Indian and Pacific oceans, which
may trigger stationary waves along the Equator interacting over the Sahel
(Mohino et al., 2011; Rowell, 2001).</p>
      <p>On intra-seasonal to synoptic timescales, an important source of variability
is the propagation of convectively coupled equatorial wave (CCEW)
disturbances and the Madden–Julian oscillation (MJO) (Mohino et al., 2012;
Pohl et al., 2009). In addition, variability in the SHL strength and position
modulate the distribution of the monsoonal precipitation in the Sahel in the
zonal direction. During periods of a deeper SHL, the shallow cyclonic
circulation associated with the thermal low is intensified, strengthening the
Atlantic westerly flow and the convergence in the Sahel, which leads to wet
(dry) anomalies in the eastern (western) Sahel (Lavaysse et al., 2010b). The
SHL phases are modulated on synoptic timescales by both tropical and
midlatitude disturbances (Chauvin et al., 2010; Lavaysse et al., 2010a).
Other types of intra-seasonal variability include the Sahelian and
quasi-biweekly zonal dipole (QBZD) modes on timescales of 10–25 days
(Janicot et al., 2011; Mounier et al., 2008; Roehrig et al., 2011).
Variations in the intensity and position of the AEJ influence the location,
amplitude and propagation speed of AEWs, which play a crucial role in the
modulation of convective precipitation in the Sahel, mainly through their
influence on thermodynamics and vertical wind shear (Gu et al., 2004; Skinner
and Diffenbaugh, 2013). To the south of the Sahel, low-level vortices
unrelated to AEWs can affect rainfall (e.g. Fink et al., 2006). Convection in
West Africa is often organised on the mesoscale, particularly in the form of
fast-propagating squall line systems (Fink and Reiner, 2003), but more
isolated thunderstorms or showers also occur, e.g. triggered by the
sea-breeze convergence along the Guinea coast (Fink et al., 2010). The moist
convection embedded within the monsoon flow has been shown to be intrinsic to
the monsoon, and the poor representation of convection in models leads to
biases in the WAM (Birch et al., 2014; Garcia-Carreras et al., 2013; Marsham
et al., 2013).</p>
      <p>The atmospheric composition over southern West Africa (SWA hereafter) during
the wet season is a complex combination of air masses transported from remote
sources, bringing desert dust or biomass burning aerosol, and local
anthropogenic pollution (Mari et al., 2011). The Sahara desert to the north
of the region is the largest aerosol source in the world and the transport of dust southwards is a significant source of aerosol for SWA (e.g. Chiapello, 2014; Shao et
al., 2011). Forest fires in the immediate region are not thought to be
significant in this period, but the transport of biomass burning species from
the Southern Hemisphere (SH) has been observed (Mari et al., 2008).
Anthropogenic emissions from the combustion of fossil fuels, biofuels and
refuse are on the rise and expected to keep increasing significantly in the
near future due to the rapid growth of cities in the region (Knippertz et
al., 2015b; Liousse et al., 2014). Air quality is thus a concern, with
multiple sources of anthropogenic emissions from domestic open fires, road
traffic, street dust, waste burning, oil extraction and refining, ships,
industrial activity, power plants, etc. SWA is also characterized by a
south–north gradient of vegetation, from rainforest in the coastal belt to
the sub-Sahelian savannah in the north. The dense vegetation can emit large
quantities of biogenic compounds (isoprene, monoterpenes, etc.), which
profoundly alter the gas and aerosol composition in the region (Mari et
al., 2011). The relative role of local biogenic and anthropogenic emissions,
the long-range transport of other compounds into the SWA atmosphere, coupled
to the peculiar dynamics of the region during the monsoonal period leads to a
chemically complex region.</p>
      <p>A lack of an observational network adequate to better understand processes
and to evaluate model simulations and satellite data has impeded scientific
progress in West Africa for a long time and motivated the organisation of
large international field campaigns. An early example, which revolutionised
the understanding of the WAM system at that time, is the Global Atmospheric
Research Program (GARP) Atlantic Tropical Experiment (GATE) (Kuettner, 1974).
The largest such programme in recent decades is the African Monsoon
Multidisciplinary Analysis (AMMA),
which took place in 2006 with a focus on Sahelian convection (Lebel et
al., 2010). More recently, the Dynamics–Aerosol–Chemistry–Cloud
Interactions in West Africa (DACCIWA) project (Knippertz et al., 2015a)
organised a major international field campaign during June and July 2016,
focusing for the first time on the most populated southern coastal region of
West Africa. In addition to a number of meteorological aspects, the DACCIWA
campaign also had a focus on atmospheric composition, including questions of
air pollution and cloud–aerosol interactions (Knippertz et al., 2015b).
Field activities included measurements from three inland ground supersites
(Savé in Benin, Kumasi in Ghana, Ile-Ife in Nigeria), urban sites
(Cotonou in Benin, Abidjan in Côte d'Ivoire), radiosondes and three
research aircraft stationed in Lomé (Togo). A detailed description of the
field activities is given in Flamant et al. (2017).</p>
      <p>The objectives of this paper are to (a) place the campaign period June–July
2016 into a larger-scale climatological context, (b) describe the behaviour
of the WAM system (e.g. onset, AEJ and SHL positions), (c) characterise the
most important synoptic-scale weather systems affecting SWA (e.g. AEWs,
vortices), and (d) discuss impacts on rainfall, clouds and atmospheric
composition. This way the paper aims to fulfil a similar role as Janicot et
al. (2008) for AMMA. The analysis will build on and expand some of the
concepts introduced in this section and provide a consistent framework for
the detailed analysis of DACCIWA field campaign data in following years. From
an atmospheric dynamics and chemistry perspective, SWA is of particular
interest and has not been studied much in the past. AMMA had fewer stations
in SWA and only a few publications covering this region. During GATE, data
quality (e.g. from radiosondes and satellites) and data assimilation (e.g.
use of cloud motion vectors) had not evolved enough to allow a reliable
analysis of 850 <inline-formula><mml:math id="M3" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> streamlines for example, especially over the Gulf
of Guinea (e.g. Sadler and Oda, 1979). Relying on the densest radiosonde
network at the Guinea coast and in the Sudanian zone (Côte d'Ivoire, Ghana,
Togo, Benin, Nigeria) ever, DACCIWA can for the first time provide a detailed account of SWA weather
systems and their impacts on precipitation and atmospheric composition. In
contrast to the Sahel, SWA is often characterised by situations with high
moisture and relatively low convective inhibition (CIN), while the vertical
wind shear is typically weak. Thus, convection is relatively easy to trigger
and remains less well organised, yet brings substantial rains. These are
often connected to weak and vertically shallow cyclonic and anticyclonic
vortices (e.g. Fink et al., 2006), but details of this relationship are still
unclear as is their linkage to classical equatorial wave and AEW
disturbances. This paper will shed some new light on these fundamental
unexplored dynamical features, including the specific question of onset
dynamics.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Geographical overview of the study region
with sites and names. The purple rectangle marks the main DACCIWA focus
region (5–10<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 8<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E).</p></caption>
        <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f01.pdf"/>

      </fig>

      <p>The paper is structured as follows: in Sect. 2 an overview of the employed
data and methods will be given. Section 3 contains a relatively short
discussion of the large-scale settings followed by a more detailed analysis
of the synoptic-scale evolution in Sect. 4. Section 5 discusses the
implication of meteorological variation on atmospheric composition, focusing
on Saharan and Sahelian dust, biomass burning
aerosol from the SH and pollution plumes from the cities along the Guinea
coast. Main conclusions will then be given in Sect. 6.</p>
</sec>
<sec id="Ch1.S2">
  <title>Data and methods</title>
<sec id="Ch1.S2.SS1">
  <title>Data</title>
      <p>For the investigation of atmospheric dynamics, analysis and reanalysis data
from the European Centre for Medium-Range Weather Forecasts (ECMWF) are used.
Most of the analyses are based on
the ERA-Interim (hereafter ERA-I) reanalysis at about 0.7<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid
spacing (Dee et al., 2011), which allows the computation of background
climatologies back to 1979. For investigations focusing on the campaign
period in 2016 alone, the higher-resolution operational analyses (native
resolution of <inline-formula><mml:math id="M8" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 9 <inline-formula><mml:math id="M9" display="inline"><mml:mi mathvariant="normal">km</mml:mi></mml:math></inline-formula>; model version Cy41r2; see
<uri>www.ecmwf.int</uri>) are employed. As there was no change to the operational
system during the study period, these data can be regarded as homogeneous, in
contrast to longer time spans of operational data. The majority of
radiosondes launched during the DACCIWA field campaign were distributed
through the Global Telecommunication System and were assimilated at ECMWF.
For the analysis of ocean influences on West Africa, the 0.25<inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> daily
Reynolds Optimum Interpolation SST data are used. The dataset combines
observations from different platforms (satellites, ships, buoys) on a regular
global grid. A spatially complete SST map is produced by interpolating to
fill in gaps (Reynolds et al., 2007). Data have been retrieved from the NOAA
NCDC (National Oceanic and Atmospheric Administration – National Climatic
Data Center) FTP site (<uri>http://www.ncdc.noaa.gov</uri>). Monthly anomalies for
June–July 2016 and daily anomalies are based on the 1981–2016 climatology.</p>
      <p>As a precipitation estimate, the standard Tropical Rainfall Measuring Mission
(TRMM) product 3B42 (v7) with 0.25<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> grid spacing is used (Huffman et
al., 2007). This product combines information from space-borne radar and
microwave and infrared channels, subject to monthly calibration with surface
rain gauges if available. Since September 2014, the real-time calibration of
microwave radiances using the precipitation radar has ceased due to the
decommissioning of the TRMM satellite and was replaced by using
climatological adjustments. Although this caused a discontinuity, the TRMM
3B42 product was prioritised over the Global Precipitation Measurement (GPM)
Integrated Multi-satellite Retrievals for GPM (IMERG) successor product due
to the longer availability (1998–2016), which allowed for the calculation of
anomalies. The temporal resolution of this product is once every 3 h, but
here daily accumulations (22:30–22:30 UTC) are used for most
investigations. In addition, outgoing longwave radiation (OLR) data from the
Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the geostationary
Meteosat Second Generation (MSG) satellites with a spatial and temporal
resolution of <inline-formula><mml:math id="M12" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 3 <inline-formula><mml:math id="M13" display="inline"><mml:mi mathvariant="normal">km</mml:mi></mml:math></inline-formula> at nadir and 15 min, respectively, are
used as a proxy for convective activity (Schmetz et al., 2002). In
particular, channel 9 (i.e. approximately 9.80–11.80 <inline-formula><mml:math id="M14" display="inline"><mml:mrow><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>) of the
thermal infrared band is taken to retrieve cloud-top temperatures and to
ensure day and night coverage. Different types of clouds are analysed using
information on cloud-top characteristics (CTX) and the cloud mask (CMA) from
the Satellite Application Facility on Climate Monitoring (CM SAF). Both the
CTX and CMA subsets are part of the CLAAS-2 (Finkensieper et al., 2016)
dataset, which is derived from information provided by SEVIRI (Stengel et
al., 2013). Therefore, CLAAS data have the same temporal and spatial
resolution as the SEVIRI dataset.</p>
      <p>As this paper is meant to give a broad overview of meteorological and
chemical conditions only, a detailed analysis of DACCIWA field campaign data
is left to follow-up studies. The only exception is radiosonde data from
Abidjan (for location, see Fig. 1) used to illustrate a period of unusual
dryness during July 2016. Relative humidity was derived from (00:00, 06:00,
12:00 and 18:00 UTC) soundings four times daily using the high-resolution
vertical profiles obtained from the MODEM radiosonde system. The analysis
will concentrate on the main DACCIWA study region
(8<inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M16" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, 5–10<inline-formula><mml:math id="M17" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, see Fig. 1), but influences
on that region from a much wider area will be considered.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <title>Methods</title>
      <p>In order to better understand and characterise atmospheric variability during
the DACCIWA campaign, a number of features important for SWA were objectively
or subjectively identified:
<list list-type="custom"><list-item><label>1.</label>
      <p>Equatorial waves: the presence of CCEWs is identified using the wave
filtering method in specific wave-number–frequency domains as
described in Wheeler and Kiladis (1999). In addition to the CCEWs (Kelvin
waves, MJO, mixed Rossby-gravity and equatorial Rossby waves), tropical
depression-like disturbances (TD) are filtered following the method by Roundy
and Frank (2004). These often correspond to AEWs over West Africa. The
filtering is applied to the 3-hourly TRMM 3B42 (v7) precipitation dataset
(see Sect. 2.1) within the northern equatorial band 5–15<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, which
contains the bulk of the convective precipitation during the campaign period
but excludes some heavier oceanic rainfalls (see Fig. 5b).</p></list-item><list-item><label>2.</label>
      <p>Heat low index: following Lavaysse et al. (2009), the low-level
atmospheric thickness between 925 and 700 <inline-formula><mml:math id="M19" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> over a domain that
covers northern and West Africa is used to determine the location and the
intensity of the SHL. The location corresponds to the region with thickness
values larger than the 90th percentile. The intensity is defined directly
through the thickness in geopotential metres (gpm), indicating the thermal
dilation of the lower atmosphere. Once the SHL is detected and the intensity
of each grid point calculated, the centre of the SHL is defined as the
barycentre in longitude and latitude, which is closely linked to the east
and west phases of temperature
anomalies proposed by Chauvin et al. (2010) when the SHL is located in its
Saharan location (from end of June to mid-September). These computations are
based on ERA-I (see Sect. 2.1).</p></list-item><list-item><label>3.</label>
      <p>AEJ index: average position and strength of the AEJ are objectively
calculated based on Berry et al. (2007). Within the region 0–30<inline-formula><mml:math id="M20" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and
8<inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (longitudinal extent of DACCIWA focus region;
see Fig. 1), 6-hourly ERA-I winds at
700 <inline-formula><mml:math id="M23" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> are used. A spatial low-pass filter with a cut-off wavelength of
1000 <inline-formula><mml:math id="M24" display="inline"><mml:mi mathvariant="normal">km</mml:mi></mml:math></inline-formula> is applied to calculate shear vorticity, which is then used
to determine the jet axis. The average wind speed along the jet axis and the
mean latitudinal position is estimated for June–July 2016 and the long-term
climatology (1987–2016) for comparison.</p></list-item><list-item><label>4.</label>
      <p>Mesoscale convective system (MCS) identification: the evolution of deep convective clouds
is monitored by applying an overlap-based tracking algorithm (Mathon and
Laurent, 2001; Schröder et al., 2009; Williams and Houze, 1987) to the
15 min infrared data of SEVIRI. In two successive images, cold cloud regions
are identified first and then connected in time by determining the highest
accordance with respect to area, area overlap and spatial translation. Here,
deep convective clouds are defined as regions with a brightness temperature
of <inline-formula><mml:math id="M25" display="inline"><mml:mo>≤</mml:mo></mml:math></inline-formula> 233 <inline-formula><mml:math id="M26" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula> and an area of least 100 contiguous pixels (i.e.
<inline-formula><mml:math id="M27" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 900 <inline-formula><mml:math id="M28" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="normal">km</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>). The former criterion is widely used as a proxy for
deep precipitating convection in tropical regions, whereas the latter
excludes convective systems with low contribution to total cold cloud cover
(Mathon and Laurent, 2001; Schröder et al., 2009).</p></list-item><list-item><label>5.</label>
      <p>Synoptic-scale vortices: close inspection of daily weather charts
suggests that only a few classical AEWs occurred during the study period and
that a more flexible approach is needed to fully represent the observed
richness of coherent features. After some testing, a combination of
subjective tracking of vortex centres from unfiltered 850 hPa streamlines
with Hovmöller plots of 850 hPa vorticity and meridional wind was
selected.</p></list-item><list-item><label>6.</label>
      <p>Long-range transport of biomass burning and dust enriched air masses:
biomass burning plumes from central Africa transported into the domain were
tracked with carbon monoxide (CO) calculated from the ECMWF Copernicus
Atmosphere Monitoring Service-Integrated Forecasting System (CAMS-IFS; Inness
et al., 2013). Dust plumes from Sahelian and Saharan sources, north of the
DACCIWA domain, were identified using the CAMS-IFS dust aerosol optical depth
(DAOD). Where available, CAMS-IFS assimilates satellite information to bring
the model output closer to reality.</p></list-item><list-item><label>7.</label>
      <p>Turbulent dispersion of urban plumes from the five major cities, where
DACCIWA aircraft and ground measurements were taken (Abidjan, Kumasi, Accra,
Lomé, Cotonou; see Fig. 1), were calculated daily using forward
trajectories of passive tracers in a Lagrangian framework. Two models were
used: (a) FLEXPART v6.2 (<uri>https://www.flexpart.eu/</uri>; Stohl et al., 2005)
driven with ECMWF ERA-I winds and (b) HYSPLIT v4.8 (Stein et al., 2015)
driven by GDAS (Global Data Assimilation System) winds. Both models were run
for 24 <inline-formula><mml:math id="M29" display="inline"><mml:mi mathvariant="normal">h</mml:mi></mml:math></inline-formula> with continuous emissions of the tracer. The extent of the
plume was calculated in FLEXPART using the root mean square distance of
particles from the source at the end of the 24 h simulation. For HYSPLIT the
plume boundary was defined at the end of the 24 <inline-formula><mml:math id="M30" display="inline"><mml:mi mathvariant="normal">h</mml:mi></mml:math></inline-formula> at a threshold
concentration of 10<inline-formula><mml:math id="M31" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">14</mml:mn></mml:msup></mml:math></inline-formula> <inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, with one unit of tracer being emitted from the source in
24 <inline-formula><mml:math id="M33" display="inline"><mml:mi mathvariant="normal">h</mml:mi></mml:math></inline-formula>.</p></list-item></list></p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><caption><p>Global SST anomalies for June–July 2016 (<inline-formula><mml:math id="M34" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C). Basis is
the Reynolds Optimal Interpolated SST v2 dataset and anomalies are relative
to 1981–2016. Only anomalies above the 95 % confidence level based on a
two-sided Student's <inline-formula><mml:math id="M35" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula> test are plotted. The black box marks the area used for
Fig. 3.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f02.pdf"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Large-scale settings</title>
      <p>This short section aims to characterise the large-scale setting the DACCIWA
field campaign period, June–July 2016, was embedded in. Figure 2 shows
global SST anomalies for June–July 2016. While at the beginning of the year
El Niño conditions were still prevalent (not shown), by June a transition
to La Niña had occurred, which usually favours monsoonal precipitation in
the Sahel (Joly and Voldoire, 2009). At the same time, the equatorial
Atlantic Ocean was relatively warm with widespread anomalies above
1 <inline-formula><mml:math id="M36" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula> (Fig. 2). These warm events, sometimes referred to as Atlantic El
Niños (Okumura and Xie, 2006), are associated with a suppressed ACT and
are linked with westerly surface wind perturbations at the Equator. The
reduced surface wind stress causes less surface oceanic divergence and
vertical mixing, leading to reduced SST cooling. This reduces the pressure
gradient towards the SHL and thus the inland penetration of monsoonal rains.
Since the 1970s, a frequent anticorrelation between El Niño in the
Atlantic Ocean and El Niño in the Pacific Ocean has been observed
(Rodríguez-Fonseca et al., 2015).</p>
      <p>Warmer equatorial waters in the Gulf of Guinea as in 2016 exhibit a strong
correlation with above-normal rainfall at the Guinea coast, which has been
robust throughout the 20th century (Diatta and Fink, 2014). Mohino et
al. (2011) argue that a warm eastern equatorial Atlantic Ocean and a
simultaneous cold eastern Pacific Ocean exert compensational forcings on
Sahelian rainfall, such that the archetypical dipole response during warm
years in the Gulf of Guinea has rarely been observed after the 1970s. In the
Mediterranean Sea, positive SST anomalies are found over the eastern basin
accompanied by negative anomalies in the northwestern part of the Indian
Ocean (Fig. 2). Positive SST differences between these two areas are
associated with rainfall excess over the Sahel (Fontaine et al., 2011; Park
et al., 2016). Overall, it appears that a combination of these different
factors was in place in 2016 since the June–September Sahelian
rainfall was only very slightly above normal (not shown). Standard indices
indicate that the MJO was not active over West Africa in June–July 2016 (not
shown).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><caption><p>Daily SST behaviour over the eastern tropical Atlantic during
June–July 2016. SSTs (<inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C) are averaged between 10<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W and
4<inline-formula><mml:math id="M39" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (see box in Fig. 2) and shown as absolute values (lines) and
anomalies (shading). Basis is the Reynolds Optimal Interpolated SST dataset
and anomalies are relative to 1981–2016 as in Fig. 2. Only values greater
than the SST Reynolds daily error estimation are plotted. The four phases of the DACCIWA campaign are marked
with thin green lines.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f03.pdf"/>

      </fig>

      <p>For the DACCIWA focus region (Fig. 1) and along most of the Guinea coast,
June–September rainfall turned out to be normal (not shown), despite the
extended dry spell during Phase 2 discussed in Sect. 4 (Fig. S1b in the
Supplement). Only the Guinea and Cameroon line mountains and the Bight of
Bonny had above-normal rainfall. It is unclear why the warmer waters in the Gulf of
Guinea did not cause more rainfall in lowland areas. A possible explanation
is warm SSTs in the South Atlantic (Fig. 2), which seem to reduce the
positive effect of the equatorial Atlantic (Nnamchi and Li, 2011). In 2016,
the situation was further complicated by relatively cold SSTs along the
coasts of Senegal, Ghana and Togo, whose impacts on rainfall are not clear.</p>
      <p>An inspection of the daily evolution of zonally averaged
(10<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–4<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E) SSTs over the tropical eastern Atlantic
during June–July 2016 reveals the typical establishment of the equatorial
cold tongue (1<inline-formula><mml:math id="M42" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N–5<inline-formula><mml:math id="M43" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) and of upwelling of cooler water
along the Guinea coast (4–6<inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) (Fig. 3). The onset of the ACT
occurs around 10 June 2016 (mean date is 11 June with a standard deviation
of 12 days according to Caniaux et al., 2011) with SSTs slightly below the
long-term average, followed by a significant warming and southward retreat
between mid-June and 5 July 2016, with warm anomalies surpassing
1.5 <inline-formula><mml:math id="M45" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula>. After that, the ACT is re-established but absolute
temperatures stay above average by 0.5 <inline-formula><mml:math id="M46" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula> or more until the end of July 2016, consistent with the
anomalies shown in Fig. 2. The coastal upwelling sets in much later (Fig. 3).
First indications of a cooling are found around 18 June 2016, but a more
substantial cooling begins on 27 June 2016 until SSTs drop below
26 <inline-formula><mml:math id="M47" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C across a broader coastal strip until the end of July. The
phenomenon is a little stronger in 2016 than in other years, with negative
anomalies of the order of 0.5 <inline-formula><mml:math id="M48" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula>, particularly along 5<inline-formula><mml:math id="M49" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N.</p>
      <p>The other important driver of the WAM is the SHL. Figure 4 shows its
intensity and position on a daily basis during June–July 2016. During the
first 3 weeks of June, the SHL is in an intense phase (Fig. 4a) and shows
large east–west fluctuations with a period of about 10 days, remaining
mostly to the east of the climatological position (Fig. 4b). This shows some
resemblance with the SHL variations described by Chauvin et al. (2010) but on
rather short timescales. The SHL is also located further to the north than
usual, associated with large positive temperature anomalies over northeastern
Africa and anomalous southwesterly flow over the eastern Sahel (not shown).
Around 20 June, the SHL abruptly weakens and shifts to a more southerly
position, followed by a gradual intensification and northward retreat during
the following week (Fig. 4a). It is still located east of its climatological
position during this period (Fig. 4b). After that, a long strong phase begins
to last until 18 July (Fig. 4a), during which the SHL gradually shifts
westward (Fig. 4b) and also slightly northward. Around 18 July another abrupt
weakening occurs and continues until the end of July 2016, only shortly
interrupted by positive values (Fig. 4a). The SHL is located to the west of
its climatological position during this time (Fig. 4b) and then migrates to
the south at the end of July (Fig. 4a). In the next section, the impact of
these fluctuations and those of SSTs on synoptic-scale variability over SWA
will be discussed.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4"><caption><p>SHL evolution during June–July 2016. <bold>(a)</bold> Time–latitude
anomalies of the SHL intensity (gpm) defined as the thickness between 925 and 700 <inline-formula><mml:math id="M50" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula>
(relative to 1979–2016). <bold>(b)</bold> Longitudinal location of the SHL
barycentre (black line) with the 1979–2016 percentiles in colour shading.
See Sect. 2.2 for more details. The four phases of the DACCIWA campaign are
marked with thin black lines.</p></caption>
        <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f04.pdf"/>

      </fig>

</sec>
<sec id="Ch1.S4">
  <title>Detailed synoptic analysis</title>
<sec id="Ch1.S4.SS1">
  <title>General approach</title>
      <p>In order to guide the discussion of the DACCIWA field measurements, the study
period is divided into distinctive phases and the most significant weather
systems are labelled for better reference in other papers. The division into
phases is mainly based on the north–south precipitation difference (NSPD
hereafter) between the coastal zone (0–7.5<inline-formula><mml:math id="M51" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) and the
Sudanian–Sahelian zone (7.5–15<inline-formula><mml:math id="M52" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N), both
averaged across the longitude range 8<inline-formula><mml:math id="M53" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M54" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (see Fig. 6
for orientation). Figure 5a shows daily values of the NSPD based on TRMM
precipitation estimates for June–July 2016. Figure 5b shows the
corresponding zonally averaged rainfall values against latitude. Four
distinct phases are recognisable from this analysis.</p>
      <p>Phase 1 lasts from 1 to 21 June 2016 and is characterised by a rainfall
maximum near the coast. However, it shows large fluctuations with periods
around 5 days (Fig. 5a). Particularly the middle part of Phase 1 is very wet,
while the earlier and later parts are characterised by more isolated rainfall
peaks near 4<inline-formula><mml:math id="M55" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 5b). This modulation is consistent with the
QBZD index, showing a significant minimum around 14  2016 (see
<uri>http://misva.sedoo.fr</uri>). Rainfall during this period is unusually
intense offshore of the Niger Delta area stretching across the Gulf of Guinea
towards Cape Palmas (Fig. 6a; see also Fig. S1a for anomalies). A second
rainfall maximum is located over the tropical Atlantic to the west of West
Africa in Fig. 6a, where SSTs are climatologically much warmer (not shown).
Precipitation does already stretch far inland into the Sahel but amounts are
relatively low with the exception of the Cameroon line highland region along
the border of Nigeria and Cameroon. The moderate changes from drier to wetter
and back to drier conditions in the Sahel during Phase 1 are reflected in
weak but hardly significant undulations of the intra-seasonal Sahelian index
reaching a minimum on 12 June 2016 (see <uri>http://misva.sedoo.fr</uri>). The
pre-monsoonal conditions are also reflected in fields of zonally averaged
total column water vapour (TCWV) with values above 45 <inline-formula><mml:math id="M56" display="inline"><mml:mi mathvariant="normal">mm</mml:mi></mml:math></inline-formula> mostly
restricted to south of 12<inline-formula><mml:math id="M57" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 7). The ITD (identified by the
14 <inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C isoline of 2 m dew point) fluctuates around 16<inline-formula><mml:math id="M59" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N
(Fig. 7).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p>Rainfall evolution during June–July 2016. <bold>(a)</bold> North–south
precipitation difference based on the 7.5–15 and 0–7.5<inline-formula><mml:math id="M60" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N bands
(see boxes in Fig. 6). <bold>(b)</bold> Latitudinal distribution of rainfall.
Both panels are based on daily TRMM precipitation values averaged over
8<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M62" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (longitudes bordering DACCIWA focus region; see
Fig. 1). The four phases of the DACCIWA campaign and significant
synoptic-scale features A–J are marked at the approximate time (and also
latitude in <bold>b</bold>) of crossing the DACCIWA focus region.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f05.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><caption><p>Horizontal distribution of mean precipitation during the four phases
of the DACCIWA campaign. Plots are based on TRMM precipitation and given in
millimetres per hour. <bold>(a)</bold> Phase 1 (1–21 June 2016),
<bold>(b)</bold> Phase 2 (22 June–20 July 2016), <bold>(c)</bold> Phase 3
(21–26 July 2016) and <bold>(d)</bold> Phase 4 (27–31 July 2016). The black
boxes mark the areas used to compute the north–south precipitation
difference shown in Fig. 5a. Corresponding anomalies are shown in Fig. S1.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f06.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p>Evolution of TCWV (shading in millimetres) and the ITD (black line,
identified from the 14 <inline-formula><mml:math id="M63" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C isoline of 2 m dew point) during
June–July 2016 based on ECMWF operational analysis. The four phases of the
DACCIWA campaign and significant synoptic-scale features A–J are marked at
the approximate time and latitude of crossing the DACCIWA focus region as in
Fig. 5b.</p></caption>
          <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f07.png"/>

        </fig>

      <p>Phase 1 corresponds closely to the period of anomalously strong SHL that
fluctuates from east to west
discussed in Sect. 3 (see Fig. 4), while correspondence to SST behaviour in
the Gulf of Guinea (Fig. 3) is less clear. It is interesting to note that
despite a strong SHL and an established ACT, rainfall remains strongest along
the coast, indicating that monsoon onset has not yet occurred. This aspect
will be discussed further in Sect. 4.3. In Fig. 5, significant synoptic
disturbances are labelled with the capital letters A–J. These were
subjectively identified from 850 hPa streamline plots at 00:00 UTC each day
and often show a noticeable correspondence to the precipitation and TCWV
behaviour. A summary of their most important characteristics is given in
Table 1 and individual tracks are shown in Figs. 11, 13, 14 and 16. The
locations of the feature labels in Figs. 5 and 7 correspond to the times when
they cross the Greenwich meridian (i.e. centre of the DACCIWA focus region)
and their latitudinal position (Figs. 5b and 7 only).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p>Characterisation of the labelled (Column 1) synoptic-scale features.
Columns 2 and 3 give the time period and longitude range for which a coherent
vortex was tracked in 850 <inline-formula><mml:math id="M64" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> streamlines (see Figs. 11, 13, 14
and 16). Column 4 gives a general description, including aspects such as
propagation speed, latitude and reflection in wind and vorticity anomalies.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.98}[.98]?><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1">Label</oasis:entry>  
         <oasis:entry colname="col2">Time</oasis:entry>  
         <oasis:entry colname="col3">Long</oasis:entry>  
         <oasis:entry colname="col4">Description</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">A</oasis:entry>  
         <oasis:entry colname="col2">9–12 June</oasis:entry>  
         <oasis:entry colname="col3">22<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–25<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">fast-propagating (16.8 <inline-formula><mml:math id="M67" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) Sudanian (<inline-formula><mml:math id="M68" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 11<inline-formula><mml:math id="M69" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) cyclonic vortex and tropical disturbance,</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">weak vorticity signal but clear southerly wind signal, long-lived MCSs embedded</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">B</oasis:entry>  
         <oasis:entry colname="col2">12–15 June</oasis:entry>  
         <oasis:entry colname="col3">9<inline-formula><mml:math id="M70" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–21<inline-formula><mml:math id="M71" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">moderately fast (11.2 <inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) coastal (<inline-formula><mml:math id="M73" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 5<inline-formula><mml:math id="M74" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) cyclonic vortex and tropical disturbance,</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">moderate vorticity and meridional wind signals, intense, long-lived MCSs embedded</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">C</oasis:entry>  
         <oasis:entry colname="col2">15–18 June</oasis:entry>  
         <oasis:entry colname="col3">11<inline-formula><mml:math id="M75" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–8<inline-formula><mml:math id="M76" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">moderately fast (11.0 <inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) Sudanian (<inline-formula><mml:math id="M78" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 9<inline-formula><mml:math id="M79" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) cyclonic vortex and tropical disturbance,</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">patchy vorticity and meridional wind signals, long-lived MCS embedded</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">D</oasis:entry>  
         <oasis:entry colname="col2">15–25 June</oasis:entry>  
         <oasis:entry colname="col3">17<inline-formula><mml:math id="M80" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–23<inline-formula><mml:math id="M81" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">low-pressure trough turning into westward-propagating disturbance with two cyclonic</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">centres, large meridional wind anomalies, relative dryness, triggering monsoon onset</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">E</oasis:entry>  
         <oasis:entry colname="col2">27–30 June</oasis:entry>  
         <oasis:entry colname="col3">2<inline-formula><mml:math id="M82" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–27<inline-formula><mml:math id="M83" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">AEW with two cyclonic centres and typical propagation speed of 9.6 <inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, with coherent</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">signals in meridional wind and vorticity, leading to increased Sahelian rainfall</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">F</oasis:entry>  
         <oasis:entry colname="col2">29 June–3 July</oasis:entry>  
         <oasis:entry colname="col3">14<inline-formula><mml:math id="M85" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–21<inline-formula><mml:math id="M86" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">AEW with two cyclonic centres and a fast propagation speed of 10.6 <inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, with coherent</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">signals in meridional wind and vorticity, leading to increased Sahelian rainfall</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">G</oasis:entry>  
         <oasis:entry colname="col2">3–8 July</oasis:entry>  
         <oasis:entry colname="col3">12<inline-formula><mml:math id="M88" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–18<inline-formula><mml:math id="M89" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">unorganised AEW with ill-defined southern centre, northward moving northern centre</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">and varying propagation speed, but discernable rainfall signal</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">H</oasis:entry>  
         <oasis:entry colname="col2">9–16 July</oasis:entry>  
         <oasis:entry colname="col3">12<inline-formula><mml:math id="M90" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–22<inline-formula><mml:math id="M91" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">slowly moving (7.1 <inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) northern (<inline-formula><mml:math id="M93" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 15<inline-formula><mml:math id="M94" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) cyclonic and southern anticyclonic</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">(<inline-formula><mml:math id="M95" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 4<inline-formula><mml:math id="M96" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) vortex originating from SH, westerly wind anomaly between centres</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">I</oasis:entry>  
         <oasis:entry colname="col2">17–27 July</oasis:entry>  
         <oasis:entry colname="col3">23<inline-formula><mml:math id="M97" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–25<inline-formula><mml:math id="M98" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">relatively slow-moving northern (<inline-formula><mml:math id="M99" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 13<inline-formula><mml:math id="M100" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) cyclonic and southern (<inline-formula><mml:math id="M101" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 5<inline-formula><mml:math id="M102" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) anticyclonic</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">vortex with westerly wind anomaly in-between, creating conditions for wet period</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">J</oasis:entry>  
         <oasis:entry colname="col2">23–30 July</oasis:entry>  
         <oasis:entry colname="col3">19<inline-formula><mml:math id="M103" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E–25<inline-formula><mml:math id="M104" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W</oasis:entry>  
         <oasis:entry colname="col4">mostly slow moving Sudanian (<inline-formula><mml:math id="M105" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 9<inline-formula><mml:math id="M106" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N) cyclonic vortex, coherent vorticity but less clear</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2"/>  
         <oasis:entry colname="col3"/>  
         <oasis:entry colname="col4">wind signal, occurring in an environment of MCSs, high moisture and widespread rain</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

      <p>Phase 2 lasts from 22 June to 20 July 2016 and is characterised by a rainfall
maximum inland with smaller and less regular fluctuations of the NSPD
(Fig. 5a) and only occasional and weaker convective systems around
4<inline-formula><mml:math id="M107" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 5b). This indicates a fully developed WAM with a deeper
penetration of rainfalls and TCWV into the continent, and a northward-shifted
ITD, while marine precipitation is restricted to the Bight of
Bonny and the waters along the West
African west coast (Figs. 6b and 7). Large parts of the inland DACCIWA region
were virtually dry during this period, much drier than in other years
(Fig. S1b), despite relatively high TCWV values (Fig. 7). The transition from
Phase 1 to Phase 2 is marked by strikingly dry conditions across most of the
area of interest (Fig. 5b), much reduced TCWV (Fig. 7), strong fluctuations
of the ITD (Fig. 7) and an abrupt breakdown of the SHL (Fig. 4a). During
Phase 2 the SHL then gradually intensifies and shifts westward (Fig. 4).
There is also a gradual increase in coastal upwelling during this period
(Fig. 3), which is consistent with more stable, near-surface monsoonal winds.
The behaviour of the ACT, which is relatively weak and shifted to the south
during most of Phase 2, does not seem to be closely related to the
precipitation shift.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8"><caption><p>AEJ evolution during June–July 2016. Time series of <bold>(a)</bold>
latitudinal position and <bold>(b)</bold> mean speed in metres per second of the
AEJ objectively identified from ERA-I reanalysis data. The red lines
indicate the 2016 evolution, the blue lines the 1987–2016 climatological
mean (see Sect. 2.2 for more details). The four phases of the DACCIWA
campaign are indicated by vertical lines. The significant synoptic-scale
features A–J are marked at the approximate time and latitude of crossing the
DACCIWA focus region.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f08.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><caption><p>Coherent wind and vorticity features affecting the DACCIWA region.
Hovmöller diagram showing 4–18<inline-formula><mml:math id="M108" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N meridionally averaged
vorticity (colours, <inline-formula><mml:math id="M109" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M110" display="inline"><mml:mrow><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) and meridional wind (black
lines, <inline-formula><mml:math id="M111" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) based on operational ECMWF analyses at 1<inline-formula><mml:math id="M112" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>
resolution (in order to smooth noisy vorticity fields). The four phases of
the DACCIWA campaign and significant synoptic-scale features A–J are marked
as well as the longitudinal bounds of the DACCIWA focus region
8<inline-formula><mml:math id="M113" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M114" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E (see Fig. 1).</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f09.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F10" specific-use="star"><caption><p>Tropical wave phenomena and long-lived MCSs during June–July 2016.
Hovmöller diagram of 5–15<inline-formula><mml:math id="M115" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N meridionally averaged
precipitation from TRMM (<inline-formula><mml:math id="M116" display="inline"><mml:mrow><mml:mi mathvariant="normal">mm</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">h</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, colour shading according to
legend) with objectively identified waves marked with coloured lines
according to the legend in the top right corner and long-lived MCSs with at
least 24 <inline-formula><mml:math id="M117" display="inline"><mml:mi mathvariant="normal">h</mml:mi></mml:math></inline-formula> of lifetime marked with thick black lines (for details on
detection of both features, see Sect. 2.2). Contour lines for the wave
features correspond to a modulation of precipitation of more than
0.12 <inline-formula><mml:math id="M118" display="inline"><mml:mrow><mml:mi mathvariant="normal">mm</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">h</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. Note that while the tropical waves are identified
for the entire longitudinal range of 35<inline-formula><mml:math id="M119" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–25<inline-formula><mml:math id="M120" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, the MCS
identification is limited to the land-dominated area
20<inline-formula><mml:math id="M121" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–25<inline-formula><mml:math id="M122" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E. The four phases of the DACCIWA campaign and
significant synoptic-scale features A–J as well as the
longitudinal bounds of the DACCIWA focus region 8<inline-formula><mml:math id="M123" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M124" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E
(see Fig. 1) are marked.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f10.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F11"><caption><p>Significant synoptic-scale features during 9–18 June 2016
(Phase 1). To create this graph, vortices were subjectively identified in
850 hPa streamlines based on operational ECMWF analyses. All vortex
positions refer to 00:00 UTC with the dates given as numbers. Round symbols
mark cyclonic systems (labelled A, B and C). Paler colours are used for days
when the vortices were not clearly identifiable. The boxes mark the areas
used to compute the NSPD shown in Fig. 5a. The stippled lines show the
latitude range used to produce Fig. 9.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f11.pdf"/>

        </fig>

      <p>During 21–26 July 2016 (Phase 3), the rainfall maximum shifts back to the
coastal zone (Fig. 5a), accompanied by wet conditions spanning large parts of
the latitude band from 1 to 22<inline-formula><mml:math id="M125" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 5b), where TCWV is enhanced
and the ITD reaches its northernmost extension (Fig. 7). A horizontal
distribution of rainfall during this period (Fig. 6c) shows unusually intense
convection across the entire Gulf of Guinea, widespread rain across the
entire Sudanian zone and more patchy local maxima
stretching into the Sahel and even southern Sahara (see anomalies in
Fig. S1c). Even larger amounts are found along the
coast of Guinea and Sierra Leone.
This wet phase is preceded and accompanied by a second breakdown of the SHL
as well as a marked westward shift in its centre (Fig. 4). Coastal upwelling
is increased during this period, while no major change in the ACT is seen
(Fig. 3).</p>
      <p>During the last 5 days of July 2016 (Phase 4), the WAM system returns to a
more typical behaviour for this time of the year with a precipitation maximum
in the Sahel, similar to Phase 2 (Fig. 5). As in Phase 2, the southern parts
of the DACCIWA region are rather dry and coastal rainfalls are restricted to
the Niger Delta region (Fig. 6d). Rainfall along the coast of Guinea,
however, is even more abnormal than in Phase 3 (Fig. S1d). Overall,
conditions are somewhat wetter than during Phase 2. This is accompanied by a
partial recovery of the SHL (Fig. 4) and weakening of coastal upwelling
(Fig. 3).</p>
      <p>In the remainder of this section, the four phases outlined above as well as
the transition between Phases 1 and 2 (the monsoon onset) will be analysed in
detail, focusing on the synoptic-scale features labelled in Fig. 5. To aid
the characterisation of these features, the following additional diagrams
will be considered (see Sect. 2.2 for more details): (a) objective analyses
of AEJ position and speed (Fig. 8), (b) Hovmöller plots of 850 hPa
vorticity and meridional wind for the 4–18<inline-formula><mml:math id="M126" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N latitude band
(Fig. 9), and (c) Hovmöller plots of equatorial wave disturbances in the
0–15<inline-formula><mml:math id="M127" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N band based on TRMM rainfall as well as tracks of long-lived
MCSs (Fig. 10).</p>
</sec>
<sec id="Ch1.S4.SS2">
  <title>Phase 1: pre-onset (1–21 June 2016)</title>
      <p>As stated in Sect. 4.1, the pre-onset period is characterised by a coastal
rainfall maximum (Fig. 5), a strong eastward-shifted SHL (Fig. 4) and a weak
ACT (Fig. 3). The AEJ is still located close to the coast during most of this
phase (Fig. 8a; see also Fig. S2a). The first week (1–6 June) is relatively
quiet with overall little rainfall across the region (Fig. 5b). The AEJ is
anomalously far south (Fig. 8a) with a below-normal intensity (Fig. 8b). No
significant coherent features are detected during this period, neither in
850 hPa vorticity and meridional winds (Fig. 9) nor in terms of filtered
equatorial waves (Fig. 10). The enhanced vorticity feature starting on 5 June
2016 (Fig. 9) is related to a northern area of high horizontal wind shear
(not shown) and is thus not associated with coherent meridional wind signals.
The activity of long-lived MCSs is also relatively weak (black lines in
Fig. 10; see also Fig. S3).</p>
      <p>Between 7 and 15 June 2016 the AEJ begins shifting northward, showing two
distinct mean speed maxima of more than 14 <inline-formula><mml:math id="M128" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> (Fig. 8). On
7 June the jet maximum is located over southern Chad (not shown). The
enhanced shear associated with this feature appears to have supported the
formation of a large and long-lived MCS (Fig. 10) that brings substantial
rainfall to southern areas (Fig. 5b) and thus creates a minimum in NSPD
(Fig. 5a). In the following days, three relatively weak cyclonic disturbances
cross the region (Fig. 11). As already mentioned, Table 1 provides a summary
of the main characteristics of these disturbances and all subsequent ones. The
first disturbance (labelled A in Fig. 11) propagates quickly westward
from eastern Chad to northern Côte d'Ivoire between 9 and 11 June 2016, in
accordance with the relatively strong AEJ during this period (Fig. 8b). When
it passes the DACCIWA region, the increase in southerly flow seen in Fig. 9
(solid black lines) is associated with an increase in rainfall inland, while
coastal rainfall is also still active, leading to an NSPD near zero
(Fig. 5a). The vorticity signature of Feature A is relatively weak (Fig. 9),
but there are several long-lived MCSs embedded in this system and the latter
stages are identified as a TD (Fig. 10).</p>
      <p>The immediately following second disturbance (labelled B in Fig. 11)
propagates a little slower and on a more southern track from the border of
Nigeria and Cameroon parallel to the coast out to the Atlantic past
20<inline-formula><mml:math id="M129" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W. When the centre of the vortex passes the DACCIWA region on
12 and 13 June, a strong increase in rainfall over the ocean is observed,
creating a sharp minimum in NSPD (Fig. 5a). The slower propagation of this
feature is consistent with the larger distance to the strong AEJ core near
9<inline-formula><mml:math id="M130" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 8). Feature B shows a more coherent signature in
vorticity and meridional wind (Fig. 9), as well as TCWV (Fig. 7), and is
identified as a TD with two very long-lived and intense MCSs embedded over
the DACCIWA region (Fig. 10).</p>
      <p>From 15 to 18 June 2016 the AEJ is weak and shifts northward (Fig. 8), while
a third cyclonic feature becomes evident in the 850 <inline-formula><mml:math id="M131" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> streamlines
(labelled C in Fig. 11). It propagates relatively slowly from eastern
Nigeria across the DACCIWA region, reaching northwestern Côte d'Ivoire by
00:00 UTC on 18 June. It is associated with a moderate increase in rainfall
inland, while the coast is conspicuously dry, leading to a slightly positive
NSPD (Fig. 5a). Interestingly, Feature C appears to be related to a
longer-lived, somewhat patchy vorticity and meridional wind feature (white
line in Fig. 9), which is also identified as a TD (Fig. 10). The vortex
identified from the streamlines appears to move somewhat slower than this
disturbance and is only found during the period of strongest southerlies
immediately over the DACCIWA region (not shown). The vorticity feature moves
at a similar speed as the embedded MCS (Fig. 10). Interestingly, during the
middle part of Phase 1, the rainfall in the 5–15<inline-formula><mml:math id="M132" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N latitude band
appears to be modulated by two Kelvin waves propagating across the DACCIWA
region (green lines in Fig. 10), which superpose with the TD signals. There
is also some indication for equatorial Rossby wave activity in the western
part of the domain, but this signal is harder to see in the unfiltered TRMM
data (Fig. 10).</p>
</sec>
<sec id="Ch1.S4.SS3">
  <title>Transition from Phase 1 to Phase 2: the onset (16–26 June 2016)</title>
      <p>The monsoon onset is often defined as a more permanent shift in the rainfall
maximum into the continent (e.g. Fitzpatrick et al., 2015). According to the
NSPD (Fig. 5a), this occurred on 21–22 June in 2016, the transition from
Phase 1 to Phase 2. As this date is of such a large importance for the WAM, a
dedicated discussion of the 5 days before and after this date
is presented here. Overall this
10-day period has relatively low rainfall in the DACCIWA region, the two
noteworthy exceptions being the enhanced coastal rainfall around 19 and 20
June and a Sahelian maximum on 24–25 June (Fig. 5b). Consistently, the
activity of equatorial waves and long-lived MCSs is strongly suppressed
(Fig. 10).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F12"><caption><p>Extratropical influences during the monsoon onset. Shown are
streamlines coloured by wind speed (scale at bottom), at 600 <inline-formula><mml:math id="M133" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> and
mean sea level pressure (grey shading) at 00:00 UTC on 17 July based on ECMWF
operational analyses. The two disturbances from Fig. 13 are marked in red.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f12.pdf"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F13"><caption><p>Significant synoptic-scale features during 15–25 July 2016
(transition from Phase 1 to Phase 2). To create this graph, vortices were
subjectively identified in 850 <inline-formula><mml:math id="M134" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> streamlines based on operational
ECMWF analyses. All vortex positions refer to 00:00 UTC with the dates given
as numbers. Round symbols mark cyclonic vortices (labelled D<inline-formula><mml:math id="M135" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>, D<inline-formula><mml:math id="M136" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
and D<inline-formula><mml:math id="M137" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) and the thick orange line shows the southernmost extension of a
significant trough at 600 <inline-formula><mml:math id="M138" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> (see Fig. 12). Vortices with a joint
propagation are linked with dashed grey lines. The boxes mark the areas used
to compute the NSPD shown in Fig. 5a. The stippled lines show the latitude
range used to produce Fig. 9.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f13.pdf"/>

        </fig>

      <p>The synoptic development during the onset is characterised by substantial
extratropical influences disturbing the circulation over northern Africa with
high-amplitude waves and wave breaking in the subtropical upper troposphere.
On 15 June 2016, the polar and subtropical jets merge over the Mediterranean
Sea and a high-amplitude ridge is located upstream over the central North
Atlantic (not shown). This period is characterised by a substantial drop in
the inertial stability index defined by Cook (2015) but negative values are
only reached for short periods (not shown). While the Atlantic ridge
continues to propagate eastward, the downstream trough and ridge amplify
strongly until 17 June. On this day, the trough stretches all the way to the
Mauritanian coast and leads to a strong southwesterly flow at 600 <inline-formula><mml:math id="M139" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula>
across the western Sahara (Fig. 12). It is conceivable that subsidence
associated with the ridge stretching from eastern Europe into northeastern
Africa (Fig. 12) contributed to the suppression of rainfall evident from
Fig. 5b. The inflow of cool maritime air from the Atlantic Ocean leads to an
abrupt ventilation of the SHL, causing a weakening of its intensity and rapid
eastward shift in the centre
(Fig. 4) with some resemblance to the situation Todd et al. (2013) refer to
as the “maritime phase”. According to <uri>http://misva.sedoo.fr</uri>, the
intra-seasonal SHL index reached a distinct maximum on 17 and 18 June 2016.
The extreme nature of this cold surge is visible in
20<inline-formula><mml:math id="M140" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–0<inline-formula><mml:math id="M141" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E averaged temperature anomalies at
850 <inline-formula><mml:math id="M142" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula>, showing a very distinct and unusual cooling during this
period, with anomalies below <inline-formula><mml:math id="M143" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>6 <inline-formula><mml:math id="M144" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula> north of 30<inline-formula><mml:math id="M145" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and below
<inline-formula><mml:math id="M146" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>4 <inline-formula><mml:math id="M147" display="inline"><mml:mi mathvariant="normal">K</mml:mi></mml:math></inline-formula> down to almost 20<inline-formula><mml:math id="M148" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. S4a). Over the next few
days, the whole wave slowly drifts eastwards, allowing the northerlies
associated with the trough to penetrate into the eastern parts of the Sahara
as well. The associated cooling, which is overall less dramatic in the east
(Fig. S4b), finally leads to the conspicuous collapse of the SHL between 20
and 25 June 2016 shown in Fig. 4a. This development is also reflected in an
abrupt northward jump of the AEJ core accompanied by a significant weakening
around 21 June 2016 (Fig. 8).</p>
      <p>Within the large area of reduced surface pressure to the southeast of the
trough that stretches unusually far south (Fig. 12), three cyclonic vortices
form at 850 <inline-formula><mml:math id="M149" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> (Fig. 13). The first one (labelled D<inline-formula><mml:math id="M150" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>) first
appears over the Hoggar Mountains in southern Algeria on 15 June 2016 and
then remains rather stationary over northern Niger between 16 and 18 June
2016. The second (labelled D<inline-formula><mml:math id="M151" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>) forms farther to the east and slowly
moves along the border between Chad and Niger between 17 and 19 June 2016
(see also Fig. 12). The last one (labelled D<inline-formula><mml:math id="M152" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula>) is only discernable
in 850 hPa streamlines on 19 and 20 June 2016 along the border of northern
Chad and Sudan. On these two days, the three centres form a zonally elongated
area of cyclonic rotation with marked northerlies to the west and southerlies
to the east. Between 19 and 21 June 2016, D<inline-formula><mml:math id="M153" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and D<inline-formula><mml:math id="M154" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> rotate
cyclonically around each other while beginning to propagate westward in a
fashion similar to an AEW (Fig. 13). Both cyclonic centres slow down and
weaken between 22 and 25 June 2016 near the West African west coast. To the
northwest of D<inline-formula><mml:math id="M155" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and D<inline-formula><mml:math id="M156" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>, northerly flow reaches values of
15–25 <inline-formula><mml:math id="M157" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> between 18 and 21 June 2016 (not shown), which leads
to a marked southward push of TCWV (Fig. 7).</p>
      <p>Figure 9 shows how this unusual development is reflected in 850 <inline-formula><mml:math id="M158" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula>
vorticity and meridional wind (labelled D). On 18 June 2016, D<inline-formula><mml:math id="M159" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and
D<inline-formula><mml:math id="M160" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> are still located to the north of 18<inline-formula><mml:math id="M161" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and thus signals in
the Hovmöller plot are weak. On 19 June 2016, the strong northerlies
begin to penetrate into the DACCIWA region, helping to suppress rainfall (see
Fig. 5b). This is followed by unusually large vorticity values on 20 June
2016, when D<inline-formula><mml:math id="M162" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> moves south of 18<inline-formula><mml:math id="M163" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 13). On 20 and into
21 June 2016 a wide area of very strong southerlies spreads across the
DACCIWA region. These bring moisture far into the continent, shifting the ITD
northward (Fig. 7), and thus create the conditions for an inland rainfall
maximum between 23 and 25 June 2016, indicating that the onset has in fact
occurred. After the turbulent transition phase, the WAM system becomes
relatively quiet and the AEJ slowly gets re-established near its
climatological latitudinal position until 26 June 2016 (Fig. 8) with the SHL
also beginning to re-intensify (Fig. 4).</p>
      <p>The analysis above strongly suggests that in 2016 the monsoon onset was
triggered by very strong interactions with the midlatitudes that supported a
suppression of rainfall over West Africa. Low-rainfall conditions around the
onset have been documented for other years as well (Sultan and Janicot, 2003).</p>
</sec>
<sec id="Ch1.S4.SS4">
  <title>Phase 2: post-onset (22 June–20 July 2016)</title>
      <p>Phase 2 comprises a period of relatively undisturbed monsoon conditions. The
entire DACCIWA aircraft campaign fell into this period (see Flamant et
al., 2017). The NSPD is positive through most of this phase and is modulated
by the significant weather systems E–I, with centres between 12 and
16<inline-formula><mml:math id="M164" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N and thus farther north than the Phase 1 features A–C (see
Fig. 5). This period was anomalously dry along the Guinea Coast (Fig. S1b).
Features E–I also modulate the speed and latitude of the AEJ (Fig. 8).</p>
      <p>At the very beginning of this phase, between 23 and 26 June 2016, while the
monsoon is still being established, a relatively weak (and therefore
unlabelled) cyclonic feature crosses the southern part of SWA, creating some
moderate rainfalls in the Sahel around 24 June 2016 (Fig. 5b). This is the
first time during the DACCIWA campaign that the precipitation maximum has
fully shifted inland. After this system, the SHL starts intensifying and
shifts northward (Fig. 4a), the AEJ accelerates (Fig. 8b) and a deep
southwesterly monsoon flow gets established (not shown).</p>
      <p>Between 27 June and 8 July 2016, three AEWs (Fig. 14a) associated
with moderate fluctuations in TCWV (Fig. 7) develop. The first two (Features E and F)
form on a relatively well organised AEJ (Fig. 8b) and show rather classical
propagation characteristics with coherent signals in meridionally averaged
vorticity and meridional wind at 850 <inline-formula><mml:math id="M165" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> (Fig. 9). Both have two
cyclonic centres at 850 <inline-formula><mml:math id="M166" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> straddling the jet to the north and south
(Fig. 14a) and are also objectively identified as TDs (Fig. 10). Feature E,
which forms near the Greenwich meridian, appears to be associated with the
slight rainfall enhancement on 26 and 27 June 2016, while Feature F forming
near 12<inline-formula><mml:math id="M167" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E creates a peak in rain in the northern box on 29 June
2016 (Fig. 5b). Finally, Feature G forms during a period when the AEJ weakens
and becomes more fragmented, which makes its latitudinal position vary
strongly (Fig. 8). This leads to less clear and slower propagation behaviour
(Fig. 14a). The northern centre propagates from central Niger to eastern
Mauritania between 3 and 6 July 2016 and then drifts northwestward towards
the border with Western Sahara. This behaviour is accompanied by a rapid
shift in the SHL to the west (Fig. 4b). The southern centre shows a less
coherent propagation. This is consistent with the relatively patchy signals
in wind and vorticity shown in Fig. 9, apart maybe from the final stages over
the open Atlantic Ocean. Feature G is also not matched with a TD like the
previous features are (Fig. 10). Nevertheless, a marked increase in rainfall is
observed when this feature crosses the DACCIWA region on 4 July 2016
(Fig. 5b).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F14"><caption><p>Significant synoptic-scale features during 27 June–16 July 2016
(beginning <bold>(a)</bold> and middle <bold>(b)</bold> of Phase 2). To create these
graphs, vortices were subjectively identified in 850 <inline-formula><mml:math id="M168" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> streamlines
based on operational ECMWF analyses. All vortex positions refer to 00:00 UTC
with the dates given as numbers. Round symbols mark cyclonic systems (labelled
E, F, G and H<inline-formula><mml:math id="M169" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula>), squares anticyclonic systems (labelled H<inline-formula><mml:math id="M170" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>). Vortices
with a joint propagation are linked with dashed grey lines. The cores of
significant 850 hPa jets are indicated with light blue arrows, again with
the date at 00:00 UTC given as numbers. The boxes mark the areas used to
compute the NSPD shown in Fig. 5a. The stippled lines show the latitude
range used to produce Fig. 9.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f14.pdf"/>

        </fig>

      <p>After that, between 9 and 16 July 2016, a fundamentally different and quite
unusual development occurs. While in the north, a cyclonic feature slowly
tracks from eastern Mali to Cabo Verde between 8 and 13 July 2016 and then
out to the Atlantic (Feature H<inline-formula><mml:math id="M171" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> in Fig. 14b), there is no clear
corresponding southern vortex. Instead, an anticyclonic system (H<inline-formula><mml:math id="M172" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>)
slowly propagates from Gabon on 11 July across the tropical eastern Atlantic,
reaching the coast of Sierra Leone on 14 July 2016, after which it begins to
weaken over the ocean to the west. As this system moves a little faster than
its cyclonic counterpart to the north, the two centres approach each other,
creating an area of marked low- to mid-level southwesterly winds in between
them, particularly on 12–14 July 2016 along the western border of the DACCIWA region (arrows in Fig. 14b). This behaviour
is associated with a weakening and northward shift in the AEJ (Fig. 8). It is
conceivable that these westerly wind anomalies also helped to intensify
coastal upwelling as shown in Fig. 3. Given the zonal distance between the
two centres, both positive and negative vorticity signals are apparent in the
Hovmöller plot shown in Fig. 9, although the negative one is only strong
past 10<inline-formula><mml:math id="M173" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W. Propagation of these two features is relatively slow,
with about 7 <inline-formula><mml:math id="M174" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. While the signal in the northerlies at
850 <inline-formula><mml:math id="M175" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> is somewhat patchy, the signal in the southerlies, created by
the positive superposition of the wind disturbances associated with the
staggered northern and southern vortices, is coherent and strong,
particularly to the west of 10<inline-formula><mml:math id="M176" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W (Fig. 9), as also reflected in
TCWV (Fig. 7). This has likely supported a deeper inland penetration and
slight intensification of rainfall (Fig. 5b). Given the somewhat unusual
behaviour of this system, it is no surprise that there is no matching between
the TDs and long-lived MCSs objectively identified during this period
(Fig. 10). This propagating cyclonic–anticyclonic vortex couplet appears
unrelated to any of the classical equatorial waves, but the slow propagation
speed and the opposing circulation centres are consistent with the 6–9-day
wave regime described by Diedhiou et al. (1999). To the best of our
knowledge, the dynamical origin of such features is still somewhat unclear.
In particular, the southern origin of the anticyclonic centre and its faster
propagation seem unusual.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F15"><caption><p>Vertical structure of the atmosphere during part of Phase 2. Shown
are relative humidity (shading according to scale, four times daily), wind
(barbs) and 600–925 hPa vertical wind shear (below main plot) (both two
times daily) from radiosondes launched at Abidjan (for location see Fig. 1)
during 7–16 July 2016.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f15.pdf"/>

        </fig>

      <p>An interesting effect on the coastal region is that the southern anticyclonic
vortex (Feature H<inline-formula><mml:math id="M177" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in Fig. 14b) appears to have brought with it dry air
from the area of subsidence in the equatorial zone or even SH. To illustrate
this, Fig. 15 shows a time series of radiosoundings made four times daily
from Abidjan for the period 7–16 July 2016. While most days show a
well-developed monsoon layer with high relative humidity and winds from
westerly directions, very dry air suddenly intrudes into the 850–700 hPa
layer at midday on 11 July (drop from <inline-formula><mml:math id="M178" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 85 to under 20 %)
persisting until the morning of 14  July 2016. Winds blow from southwesterly
to westerly directions during this period. Indications of aged aerosol
particles were found when the DACCIWA research aircraft penetrated this layer
over several days. These aged aerosol particles were likely from fires in the
SH (Flamant et al., 2017). Interestingly the usually easterly 600–925 hPa
shear vector backs to northerly
just before the dry event – signalling the changes in the 600 hPa
circulation due to the vortex couplet.</p>
</sec>
<sec id="Ch1.S4.SS5">
  <title>Phase 3: wet westerly regime (21–26 July 2016)</title>
      <p>Phase 3 is characterized by wet conditions stretching from the tropical
Atlantic far into the Sahel and even southern Sahara, particularly on
23–25 July 2016 (Fig. 5). Rainfalls are most abundant over the ocean,
particularly off the coast of Nigeria and stretching west to Côte d'Ivoire as
well as off the coasts of Liberia and Guinea (Fig. 6), creating large positive
anomalies (Fig. S1c). There is also a marked Sahelian band that dips south
into Ghana. The relatively large rainfall over the ocean coincides with an
area of enhanced meridional SST gradients (Fig. 3) that influence surface
wind convergence. Within the DACCIWA region (8<inline-formula><mml:math id="M179" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M180" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E),
rainfalls to the south of 7.5<inline-formula><mml:math id="M181" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N dominate, leading to a sharp drop
in NSPD to negative values during this period (Fig. 5a). Similar to the
monsoon onset period during the transition from Phase 1 to Phase 2, Phase 3
is characterised by a breakdown of the SHL (Fig. 4a) and low inertial
stability according to the index defined by Cook (2015) (not shown), but this
time the responsible cold intrusion from the midlatitudes occurs over
northeastern Africa (Fig. S4b), leading to a marked westward excursion of the
SHL (Fig. 4b). Triggered by an upper-wave in the subtropics, an
intensification of the low-level northeasterlies is observed, particularly on
23 and 24 July 2016 over Egypt and Sudan. Such a situation has been referred
to as a cold surge by Vizy and Cook (2009), and this type appears to be more
frequent than the event in the west before the onset (see Sect. 4.3).</p>
      <p>An unusual and interesting synoptic development leads up to this event. On
17 July 2016, an anticyclonic centre appears over the northern Central
African Republic and swiftly propagates westward, reaching the border between
Nigeria and Benin on 19 July 2016 (propagation speed
<inline-formula><mml:math id="M182" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 12 <inline-formula><mml:math id="M183" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>; Feature I<inline-formula><mml:math id="M184" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> in Fig. 16). Strong southerlies
ahead of this system lead to an increase in TCWV (Fig. 7). After this day,
the vortex slows down substantially (average propagation speed
<inline-formula><mml:math id="M185" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 4 <inline-formula><mml:math id="M186" display="inline"><mml:mrow><mml:mi mathvariant="normal">m</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">s</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) and shifts to a more southern track just off the
Guinea coast and then out to the open Atlantic, reaching 25<inline-formula><mml:math id="M187" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W on
27 July 2016. During this period the vortex centre is not always clearly
identifiable. Somewhat similar to Feature H (see Fig. 14b), the anticyclonic
vortex is accompanied by a cyclonic centre to the north, which is first
evident in streamlines at 850 <inline-formula><mml:math id="M188" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> on 19 July 2016 close to the border
between northeastern Nigeria and Chad (Feature I<inline-formula><mml:math id="M189" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> in Fig. 16). During
the slow propagation phase from 21 to 26 July 2016, when the two centres are
almost aligned latitudinally with a distance of about 10<inline-formula><mml:math id="M190" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, a strong
westerly jet develops between them with a maximum near 10<inline-formula><mml:math id="M191" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, which
also propagates westward. The occurrence of this jet (see arrows in Fig. 16),
which brings large amounts of moisture into SWA from the west, where much
warmer SSTs prevail, exactly marks the beginning and end of Phase 3.
Nicholson (2009) and Nicholson and Webster (2007) have shown that summers
with a strong westerly flow at 850 <inline-formula><mml:math id="M192" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> are on average associated with
particularly wet conditions. The situation discussed here is therefore one
possible synoptic-scale manifestation of this climatological result. Finally,
southerlies to the east of I<inline-formula><mml:math id="M193" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> lead to a northward extension of the moist
zone and an unusual ITD position at 24<inline-formula><mml:math id="M194" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N (Fig. 7).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F16"><caption><p>Significant synoptic-scale features during 17–30 July 2016 (end of
Phases 2–4). To create this graph, vortices were subjectively identified in
850 <inline-formula><mml:math id="M195" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> streamlines based on operational ECMWF analyses. All vortex
positions refer to 00:00 UTC with the date given as numbers. Round symbols
mark cyclonic systems (labelled I<inline-formula><mml:math id="M196" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and J), squares anticyclonic systems
(labelled I<inline-formula><mml:math id="M197" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>). Paler colours are used for days when the vortices were not
clearly identifiable. Vortices with a joint propagation are linked with
dashed grey lines. The cores of significant 850 hPa jets are indicated with
light blue arrows, again with the dates at 00:00 UTC given as numbers. The boxes mark the areas used to
compute the NSPD shown in Fig. 5a. The stippled lines show the latitude range
used to produce Fig. 9.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f16.pdf"/>

        </fig>

      <p>As with Feature H, the increasing westerly flow between the cyclonic and
anticyclonic centres leads to a weakening and north- and eastward shift in
the AEJ (Fig. 8, Fig. S2c) as well as an increase in coastal upwelling
(Fig. 3). The weakening of the AEJ may also be related to the weakened SHL
discussed above. However, in contrast to Feature H, the latitudinal alignment
of the vortices leads to a cancellation of signals in the Hovmöller
diagram, making Feature I barely detectable in Fig. 9. So unusual is this
situation that there is also very little in terms of objectively identified
wave features during this period (Fig. 10). However, some modulation of
rainfall by an eastward-propagating Kelvin wave is evident between 18 and
22 July 2016. Mounier et al. (2008) also discuss enhanced westerly inflow,
moist conditions and a Kelvin wave influence in connection with the QBZD but
the match with their concept is hard to establish for a single case. Feature
I is too slow to match the 6–9-day
wave regime described by Diedhiou et al. (1999).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F17"><caption><p>Time evolution of low-cloud fraction over the DACCIWA focus region
(5–10<inline-formula><mml:math id="M198" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 8<inline-formula><mml:math id="M199" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M200" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E, land pixels only; see
Fig. 1 for location) during June–July 2016. Depicted as a black line is the
average fraction of pixels covered with low clouds (i.e. cloud-top pressure
of 800 <inline-formula><mml:math id="M201" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> or higher). Pixels that are covered with obscuring mid- or
high-level clouds (fraction given as red line) are disregarded, leading to a
relatively large uncertainty in the low-cloud estimates on some days. Basis
for this analysis is daily 00:00 UTC CLAAS-2 images (see Sect. 2.1). The
four phases of the DACCIWA campaign are marked with different orange
shadings.</p></caption>
          <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f17.pdf"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS6">
  <title>Phase 4: recovery (27–31 July 2016)</title>
      <p>On 26 July 2006 the widespread rainfall characterising Phase 3 ceases and the
precipitation maximum shifts back to the Sahel for the rest of the DACCIWA
campaign period, as indicated by a positive NSPD (Figs. 5 and 6d). There is
also evidence for a return of the SHL and the ITD to more climatological
positions and intensity (Figs. 4 and 7). Thus, overall this phase marks the
return to more undisturbed monsoonal conditions similar to Phase 2. A last
significant cyclonic feature occurs during this period (Fig. 16,
labelled J). This feature is first detected over South Sudan on 23 and 24 July 2016. Until 27 July it swiftly
crosses the DACCIWA region, reaching the Guinea highlands. After that, it
slows down over the Atlantic on 28–30 July 2016. Figure 8 shows that the
period of fast propagation is concomitant with an enhanced and
southward-shifted AEJ. Feature J can be identified well in the north–south
averaged 850 hPa vorticity in the eastern and western parts of the study
region but is somewhat diffuse around 10<inline-formula><mml:math id="M202" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W (Fig. 9). Nevertheless,
the fast-propagation phase is evident from the vorticity as well. Meridional
wind signals associated with Feature J, however, are rather weak and only the
western parts are concomitant with an objectively identified TD, which in
turn appears to be related to a long-lived MCS (Fig. 10). Feature J also
creates some mild fluctuations in TCWV (Fig. 7).</p>
</sec>
</sec>
<sec id="Ch1.S5">
  <title>Impact on low clouds, dust, biomass burning aerosol and city pollution
dispersion</title>
      <p>After the detailed discussion of the large-scale settings in Sect. 3 and the
synoptic evolution in Sect. 4, this section aims to discuss the impact of
these variability patterns on low clouds and atmospheric composition, two
particular scientific interests of the DACCIWA project (Knippertz et
al., 2015a). Evaluating the behaviour of low clouds is difficult over
SWA in summer due to a relatively sparse observational network at the
surface and regular obscuring by mid- and high-level clouds (van der Linden
et al., 2015). Figure 17 shows the fraction of low clouds (defined here as
cloud-top pressure of 800 <inline-formula><mml:math id="M203" display="inline"><mml:mi mathvariant="normal">hPa</mml:mi></mml:math></inline-formula> and lower) daily at 00:00 UTC in the
5–10<inline-formula><mml:math id="M204" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 8<inline-formula><mml:math id="M205" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M206" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E box (see Fig. 1) as analysed
from the CLAAS-2 dataset (see Sect. 2). This fraction is relative to the
number of pixels not obscured by higher clouds, which can be as high as
85 % (red curve in Fig. 17), indicating a large uncertainty in the
low-cloud estimate. Despite this, a clear difference in low-cloud cover
between the four phases can be seen. Typical fractions during Phase 1 range
around 60 %. Given the large uncertainty, day-to-day variations should be
regarded with caution. Thus, it is no surprise that the impact of
individual synoptic features is generally hard to discern. Only the wet
Feature A and dry Feature D stand out, with a high fraction of obscuring high
clouds and a low fraction of low clouds for Feature A and the opposite for
Feature D. During Phase 2, fractions of low clouds typically range around
85 %, while the very variable fraction of obscuring high clouds is on
average a little lower than in Phase 1 (Fig. 17). This suggests that the
onset is a prerequisite for the occurrence of the extensive stratus decks in
SWA. Again, a clear influence of the synoptic features E–I is hard to
discern. During Phase 3, the wet 24 July 2016 stands out as a day with a very
high fraction of obscuring clouds and a very low (but also very uncertain)
fraction of low clouds. Finally, Phase 4 returns to the more typical abundant
low and less-frequent high clouds, also observed during Phase 2. During
Phase 1, there is frequent evidence for a land–sea breeze convergence,
creating clouds in a line parallel to the coast around midday, at least in
areas away from deep convection (not shown). Such behaviour is much more
difficult to detect during the cloudier Phases 2–4.</p>
      <p>Figure 18 shows vertically integrated fields from the ECMWF CAMS-IFS
analysis, again averaged zonally from 8<inline-formula><mml:math id="M207" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W to 8<inline-formula><mml:math id="M208" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E. The
loading of mineral dust is given as DAOD at 550 <inline-formula><mml:math id="M209" display="inline"><mml:mi mathvariant="normal">nm</mml:mi></mml:math></inline-formula> (Fig. 18a), while
the impact of biomass burning is indicated here through the vertically
integrated number of CO molecules per surface area (Fig. 18b). With respect
to dust, differences between the four phases are again evident. Before the
onset, the dust plume stretches farther south and sometimes even reaches the
coast (around 6<inline-formula><mml:math id="M210" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N). In particular, Features C and D create
significant southward excursions of the dust plume, in contrast to the
relatively weak southern disturbance B and the fast-propagating disturbance
A. With the onset in Phase 2, the dusty zone retreats to the north of
8<inline-formula><mml:math id="M211" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N with visible modulation by all four cyclonic features E, F, G
and H. The area of southwesterlies between the cyclonic vortex H<inline-formula><mml:math id="M212" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and
the anticyclonic vortex H<inline-formula><mml:math id="M213" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (see Fig. 14b) pushes the dust northwards. A
few days later, a similar but even stronger northward push to beyond
15<inline-formula><mml:math id="M214" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N is evident in the aftermath of Feature I, creating a
relatively dust-free Phase 3. Finally, a return to conditions similar to
Phase 2 occurs with the arrival of Feature J and throughout Phase 4.</p>
      <p>For CO (Fig. 18b), the dispersal of the SH biomass burning plume northwards
generally covers a wider latitudinal range and the modulation by the four
phases and the 10 synoptic features is not quite as clear as for the dust.
During Phase 1 a considerable amount of CO reaches as far north as the Sahel, particularly
in the area of southerlies following the passage of the centre of Feature A
(see also Fig. 9). The more southern Feature B also instigates a northward
transport, but this does not reach 10<inline-formula><mml:math id="M215" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N. Finally, Feature C is
associated with a latitudinally extended but somewhat weaker CO plume.
Comparing the two panels of Fig. 18 shows that during most of Phase 1 dust
and biomass burning signatures coexisted in the vertical column over SWA,
particularly in the latitudinal range 8–10<inline-formula><mml:math id="M216" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N. The arrival of
Feature D associated with the monsoon onset pushes higher CO values back into
the SH, with the exception of a small plume around 20 June 2016. After the
onset, higher CO slowly returns to the DACCIWA region, reaching a peak
northward extent of 12<inline-formula><mml:math id="M217" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N around 2 July 2016. For the rest of
Phase 2 and until the arrival of Feature I, CO retreats to the coastal and
oceanic areas. Remarkably, the time after the passing of Feature H, which is
associated with an anticyclonic vortex from the SH, does not show outstanding
vertically integrated CO concentrations. The DACCIWA aircraft frequently
measured aged aerosol particles during this period. Further study is needed
to check where this aerosol comes from and how deep the layer was vertically
using the detailed field measurements. A marked increase in CO is found to
occur with the arrival of Feature I, leading up to the highest values during
the entire 2-month period according to CAMS-IFS. It appears that this plume
is transported into the region around the anticyclonic feature I<inline-formula><mml:math id="M218" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula>
(Fig. 16). Finally, towards Phase 4, Feature J is associated with a return to
values similar to the middle of Phase 2. It is interesting to note that
during Phases 2–4, there is generally very little overlap between the
vertically integrated dust and CO fields (cf. Fig. 18a with b) in contrast to
Phase 1. During most of this time, there appears to be a narrow, meandering,
relatively clean strip of air with dust to the north and CO to the south.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F18"><caption><p>Occurrence of mineral dust <bold>(a)</bold> and CO <bold>(b)</bold> plumes
over the DACCIWA region. Hovmöller plots for the longitude range
8<inline-formula><mml:math id="M219" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W–8<inline-formula><mml:math id="M220" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> E covering the whole June–July 2016 period
generated from CAMS-IFS forecast data. Mineral dust plumes are indicated by
DAOD at 550 <inline-formula><mml:math id="M221" display="inline"><mml:mi mathvariant="normal">nm</mml:mi></mml:math></inline-formula> and show the transport of dust from north of the
domain (i.e. Sahel and Sahara). The CO is column
integrated and primarily shows the transport of air from the SH influenced by
biomass burning. The four phases of the DACCIWA campaign are indicated with
blue lines. The most significant synoptic features A–J are marked at the
approximate time and latitude of crossing the DACCIWA focus region.</p></caption>
        <?xmltex \igopts{width=227.622047pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f18.pdf"/>

      </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F19" specific-use="star"><caption><p>Pollution plumes for the
five main cities of interest during DACCIWA (Abidjan, Kumasi, Accra,
Lomé, Cotonou) during Phase 1 (top, 1–21 June 2016) and Phase 2
(bottom, 22 June–20 July 2016). Shown are
results from daily 24 h simulations using the FLEXPART model (see
Sect. 2.2). Each dot is coloured according to its city source with the
opacity increasing with the occurrences of pollution tracers at each point
location. The quarter circles show distances of 250 <inline-formula><mml:math id="M222" display="inline"><mml:mi mathvariant="normal">km</mml:mi></mml:math></inline-formula> around the
main dispersion direction towards the northeast (dashed line).</p></caption>
        <?xmltex \igopts{width=312.980315pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f19.png"/>

      </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F20" specific-use="star"><caption><p>Pollution roses of urban plumes from the five main cities of
interest during DACCIWA (Abidjan, Kumasi, Accra, Lomé, Cotonou) during
Phase 2 (22 June–20 July 2016). Each rose shows the predominant direction of
plumes and their horizontal extension (colour code). The radius values
correspond to the percentage of pollution plume direction occurrence in each
sector. Pollution roses derived from FLEXPART simulations are superimposed on
the map. HYSPLIT-derived pollution roses are at the top. See Sect. 2.2 for
more details.</p></caption>
        <?xmltex \igopts{width=426.791339pt}?><graphic xlink:href="https://acp.copernicus.org/articles/17/10893/2017/acp-17-10893-2017-f20.png"/>

      </fig>

      <p>Finally, the dispersion of urban pollution plumes from the five cities of
greatest interest to DACCIWA (Abidjan, Kumasi, Accra, Lomé and Cotonou)
is discussed based on FLEXPART and HYSPLIT results (see Sect. 2.2). Figure 19
illustrates the spatial distribution of particles emitted and dispersed
during Phases 1 and 2 simulated by the FLEXPART model. During Phase 1, when
the monsoon flow is less established, pollution dispersion is more local and
mostly directed into north- to eastward directions. During Phase 2, plumes
are more clearly concentrated around the northeastward direction and
stretch over long distances. Given the geographical distribution of the
cities, Lomé and Cotonou are likely impacted by emissions from Accra
during Phase 2, and Kumasi is likely impacted by emissions from Abidjan. Evidently quite
remote areas can be affected by pollution from coastal cities in relatively
short time. The supersite in Savé for example, is close to the main Accra
and Lomé pollution plumes. Whether these upwind plumes actually degrade
air quality in receptor cities requires further exploration using
ground-based and aircraft measurements from the DACCIWA field campaign.
During the 5-day period of Phase 3, due to the increased westerlies
between the cyclonic and anticyclonic centres I<inline-formula><mml:math id="M223" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">1</mml:mn></mml:msub></mml:math></inline-formula> and I<inline-formula><mml:math id="M224" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> (Fig. 16),
the dominant direction shifted from northeast to east-northeast, while Phase
4 is more similar to Phase 2 (not shown).</p>
      <p>Figure 20 summarises the results for Phase 2 in the form of pollution roses
for both models, giving some estimate for typical uncertainties in the
dispersion estimates. As expected, the dominant transport direction is
northeastward for both models and all cities, but some details clearly
differ. For example, a considerable fraction is transported east-northeastward
for Accra in the HYSPLIT simulations and north-northeastward for Abidjan in
FLEXPART. City pollution plumes generally reach a distance of around
300 <inline-formula><mml:math id="M225" display="inline"><mml:mi mathvariant="normal">km</mml:mi></mml:math></inline-formula> from the source point over the course of the 24 h simulations,
with the exception of shorter plumes from Abidjan (<inline-formula><mml:math id="M226" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 200 <inline-formula><mml:math id="M227" display="inline"><mml:mi mathvariant="normal">km</mml:mi></mml:math></inline-formula>) in
the FLEXPART simulations.</p>
</sec>
<sec id="Ch1.S6" sec-type="conclusions">
  <title>Conclusions</title>
      <p>Atmospheric variability over West Africa in summer is controlled
by a wide range of different factors reaching from global SST patterns to
local convection. Here we analysed these factors and their interplay
exemplarily for the period of the main DACCIWA field campaign, i.e.
June–July 2016, on the basis of ECMWF model products and satellite and
radiosonde data. The DACCIWA campaign fell into a period of Pacific La
Niña and Atlantic El Niño conditions, which statistically have
opposing effects on Sahel rainfall. Mediterranean and Indian Ocean SSTs
pointed towards a wetter than normal Sahel, but most likely the relatively
warm SSTs in the tropical Atlantic dominated and led to near-normal rainfalls
across the whole of West Africa during 2016.</p>
      <p>In order to better characterise the observed changes on a day-to-day basis,
objective analysis of tropical wave features and tracking of long-lived MCSs
were used together with a subjective tracking of vortices in 850 hPa
streamlines. A summary of the latter is provided in Table 1. This analysis
shed new light on the richness of synoptic-scale features affecting the
region and their impacts on wind, precipitation, cloudiness, and the
distribution of dust and biomass burning plumes. It serves as valuable
background information for the more detailed examinations of the
comprehensive dataset collected during the DACCIWA campaign from ground
stations, aircraft, radiosondes, and satellites and as inspiration for a deeper
analysis of the under-researched propagating synoptic systems of SWA and
their dynamics. The 2-month DACCIWA period can be divided into four distinct
phases:
<list list-type="bullet"><list-item>
      <p>Phase 1 (1–21 June 2016): this period is characterised by pre-onset
conditions with the rainfall maximum close to the Guinea coast. The ACT
becomes established in the course of this period, but coastal upwelling is
still weak. The SHL is relatively intense with large east–west fluctuations,
also accompanied by large variations in AEJ speed. Three relatively weak
westward-propagating vortices (A, B and C) affect the region, which are
associated with TDs and long-lived MCSs, creating marked variations in
precipitation. Typical coverage with low clouds over SWA during this phase is
about 60 %. Mineral dust from the Sahara and Sahel penetrates far
south and occasionally reaches the coast in significant concentrations, while
at the same time high values of CO, used here as an indicator of biomass
burning activity, push inland from the south. The weaker monsoon flow leads
to less pollution dispersion from coastal cities. Towards the end of the
phase, strong influences from the extratropics occur in the form of a deep
trough and cold surge over the western Sahara around 17 June 2016, leading to
a collapse of the SHL and AEJ. A cyclonic disturbance (labelled D) with two
centres develops, creating an area of strong, dry, dusty northerlies to the
west, followed by a deep penetration of southerlies and re-moistening of the
area, which finally creates the monsoon onset. This period is also
characterised by a conspicuous absence of tropical wave features.</p></list-item><list-item>
      <p>Phase 2 (22 June–20 July 2016): the post-onset Phase 2 is characterised
by a gradual re-intensification and westward shift in the SHL with an AEJ
close to climatological position and speed for most of the period. The
rainfall maximum has permanently shifted inland with an anomalously dry
Guinea coastal region. Rainfalls and AEJ speed are modulated by five
significant synoptic-scale features E–I. While the first three show
characteristics of classical AEWs, the latter two consist of a northern
cyclonic centre and a southern anticyclonic centre. For Feature H, the anticyclonic
centre is shifted eastward and slowly moves north from the SH, bringing with
it a shallow layer of dry air filled with aged aerosol. For Feature I, the
anticyclonic centre has an origin over central Africa and is more aligned
meridionally with its cyclonic counterpart. Together they create a more
westerly near-surface flow accompanied by peaks in coastal upwelling. During
Phase 2, low-cloud cover over SWA generally increases to about 85 %.
Mineral dust retreats to the Sahel and Sudanian zones with clear modulations
by the major synoptic-scale features, while CO fields show a marked peak
around 2 July 2016 and then weaker values afterwards. Pollution dispersion
from coastal cities is stronger and mostly towards north-northeast or northeast.</p></list-item><list-item>
      <p>Phase 3 (21–26 July 2016): the transition between Phases 2 and 3 is
accompanied by a moderate cold-air intrusion into northeastern Africa. This
is associated with a second breakdown of the SHL and a northward shift in and
weakening of the AEJ. The short Phase 3 itself is then characterised by
overall wet conditions stretching from the tropical Atlantic into the
southern Sahara, with a maximum in the coastal zone. The main reason for this
appears to be the moisture transport associated with the strong westerly flow
between the cyclonic and anticyclonic centres of Feature I already starting
in Phase 2. One further cyclonic feature (J) occurs during this period and
modulates wind and rainfall. Notably, the wet Phase 3 is almost dust-free,
but high column loadings of CO penetrate deep into SWA. Pollution dispersion
from coastal cities is strongest and mostly towards the northeast or even
east-northeast.</p></list-item><list-item>
      <p>Phase 4 (27–31 July 2016): the final 5 days of the DACCIWA period
are characterised by a return to more undisturbed monsoonal conditions with a
more climatological SHL, AEJ and rainfall distribution. Dust, CO and city
pollution plumes also return to conditions similar to Phase 2.</p></list-item></list></p>
      <p>This analysis demonstrates the significant range of features affecting SWA
around the period of the monsoon onset with marked impacts on cloudiness,
rainfall, wind and pollution transport. Four types of behaviours can be
distinguished: particularly before the onset, but also during the
re-establishment of the monsoon at the end of Phase 3, single cyclonic
vortices occur at different latitudes with different propagation speeds
(Features A, B, C and J). These are typically related to TDs and long-lived
MCSs, but the exact dynamical reason for their existence is not entire clear
(see also Fig. 4 in Schrage et al., 2006, for other examples). The second
type is classical AEWs with a northern and southern cyclonic vortex (Features
E, F and G). These have been described extensively in the literature and
their dynamics are well understood (e.g. Hall et al., 2006). They usually
have a discernable signal in vorticity, wind and precipitation fields and are
also objectively identified as TDs. The third type, which appears to be rarer
and whose climatological and dynamical characteristics are barely covered in
the literature, are jointly propagating cyclonic and anticyclonic vortices
(Features H and I), which create an anomalous westerly flow in between them,
associated with enhanced coastal upwelling and a more eastward transport of
city pollution plumes. The resulting conditions appear to depend on the exact
origin of the involved air masses. If the strong westerly flow taps into
moist air off the west coast, where high SSTs are common, this can lead to
anomalously moist conditions across the region, as has been described
climatologically by Nicholson (2009) and Nicholson and Webster (2007).
Hand-analysed surface weather charts from Phase II of GATE show couplets of
cyclonic–anticyclonic vortices, but no details are discussed (Sadler and
Oda, 1979). There are some similarities with the 6–9-day wave regime
described by Diedhiou et al. (1999) but the dynamical causes are not clear.
Finally, extratropical influences can markedly impact weather conditions over
SWA. This is usually associated with midlatitude troughs penetrating into the
Sahara, cold surges and disruptions to the SHL and AEJ. During the DACCIWA
period, Feature D is of particular interest, as it appears to have caused a
substantial dry anomaly before the actual monsoon onset. Such behaviour has
been described in the literature (e.g. Sultan and Janicot, 2003), but the
role of the extratropics in a given year is yet to be explored, ideally also
with model sensitivity experiments. Feature D is also striking since it
transforms from a rather stationary low-pressure zone with several centres
downstream of an extratropical trough into a westward propagating vortex
couplet that is much more tropical-like and that has some resemblance to an
AEW. A detailed analysis of the dynamics of this transition is beyond the
scope of this study and left for future work. It is noteworthy that periods
of extratropical influences appear to create the most persistent meridional
flow anomalies, leading to extreme excursions of mineral dust and biomass
burning plumes over SWA.</p>
      <p>In the future, it would be desirable to study the four characteristic types
of variability patterns described above in a climatological (comparing 2016
to other years) and dynamical sense. The latter could be achieved both
through theoretical work on linear tropical modes taking into account the
specific conditions over SWA in summer or possibly in a full non-linear sense
through idealised model experiments or realistic case studies. An interesting
idea to be explored further in this context is interactions between AEWs and
mixed Rossby-gravity waves as suggested by Cheng et al. (2017).</p>
</sec>

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

      <p>The majority
of data used in this study are publicly available through third parties:
<list list-type="bullet"><list-item>
      <p>ERA-I (Dee et al., 2011), ECMWF operational analyses and dust and CO fields
from CAMS-IFS (Inness et al., 2013) can be retrieved from the ECMWF website
<uri>http://www.ecmwf.int</uri> or ECMWF's Meteorological Archival and Retrieval
System (MARS).</p></list-item><list-item>
      <p>Reynolds SST data (Reynolds et al., 2007) can be retrieved from <uri>http://www.ncdc.noaa.gov</uri>.</p></list-item><list-item>
      <p>TRMM product 3B42 v7 (Huffman et al., 2007) can be retrieved from
<uri>https://giovanni.gsfc.nasa.gov</uri>.</p></list-item><list-item>
      <p>CLAAS-2 CTX and  CMA products (Stengel et al., 2013; Finkensieper et al., 2016)
can be found at
<uri>https://doi.org/doi:10.5676/EUM_SAF_CM/CLAAS/V002</uri>.</p></list-item><list-item>
      <p>SEVIRI OLR data (Schmetz et al., 2002) can be accessed via
<uri>https://www.eumetsat.int/website/home/Data/MeteosatServices/0DegreeService</uri>.</p></list-item><list-item>
      <p>Dispersion of city plumes based on HYSPLIT using GDAS winds is described at
<uri>http://www.ready.noaa.gov</uri>.</p></list-item></list></p>

      <p>The only data used that are original to DACCIWA are the high-resolution
radiosonde measurements from Abidjan. These are available from the DACCIWA
database at
<uri>http://baobab.sedoo.fr/Data-Search/?datsId=1656&amp;project_name=DACCIWA</uri>.
They do not have a DOI yet. At lower, standard TEMP resolution, they are
available via
<uri>https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosonde-archive</uri>.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p><bold>The Supplement related to this article is available online at <inline-supplementary-material xlink:href="https://doi.org/10.5194/acp-17-10893-2017-supplement" xlink:title="pdf">https://doi.org/10.5194/acp-17-10893-2017-supplement</inline-supplementary-material>.</bold></p></supplementary-material>
        </app-group><notes notes-type="competinginterests">

      <p>The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p>The DACCIWA project has received funding from the European Union Seventh
Framework Programme (FP7/2007-2013) under grant agreement no. 603502. AS has
been supported from subproject “C2 – Prediction of wet and dry periods of
the West African monsoon” of the Transregional Collaborative Research
Center SFB-TR 165 “Waves to
Weather” funded by the German Research Foundation (DFG), MG by the LABEX
project funded by Agence Nationale de la Recherche (French National Research
Agency, grant ANR-10-LABX-18-01), and TB by BMBF grant no. 01LP1520D
(MIKLIP-PROMISA). The authors gratefully acknowledge the NOAA Air Resources
Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion
model and READY website (<uri>http://www.ready.noaa.gov</uri>) used in this
publication. The AERIS/SEDOO data infrastructure provided access to the
GIRAFE/FLEXPART simulations, CAMS-IFS forecasts and data used in this study
(<uri>http://www.aeris-data.fr</uri> and <uri>http://dacciwa.sedoo.fr</uri>).
The GIRAFE/FLEXPART simulations were provided by Alain Fontaine (SEDOO). The
authors would also like to thank Gregor Pante for help with producing
Figs. 12 and 15, Robert Redl for his development of the AEJ detection tool, and Serge Janicot and Thierry Lefort for their effort to carefully review
this paper and for their constructive criticism.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
The article processing charges for this open-access <?xmltex \hack{\newline}?>
publication were covered by a research <?xmltex \hack{\newline}?> centre of the
Helmholtz Association.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: Anna Jones <?xmltex \hack{\newline}?>
Reviewed by: Serge Janicot and Thierry Lefort</p></ack><ref-list>
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    <!--<article-title-html>A meteorological and chemical overview of the DACCIWA field campaign in West Africa in June–July 2016</article-title-html>
<abstract-html><p class="p">In June
and July 2016 the Dynamics–Aerosol–Chemistry–Cloud Interactions in West
Africa (DACCIWA) project organised a major international field campaign in
southern West Africa (SWA) including measurements from three inland ground
supersites, urban sites in Cotonou and Abidjan, radiosondes, and three
research aircraft. A significant range of different weather situations were
encountered during this period, including the monsoon onset. The purpose of
this paper is to characterise the large-scale setting for the campaign as
well as synoptic and mesoscale weather systems affecting the study region in
the light of existing conceptual ideas, mainly using objective and subjective
identification algorithms based on (re-)analysis and satellite products. In
addition, it is shown how the described synoptic variations influence the
atmospheric composition over SWA through advection of mineral dust, biomass
burning and urban pollution plumes.</p><p class="p">The boreal summer of 2016 was characterised by Pacific La Niña, Atlantic
El Niño and warm eastern Mediterranean conditions, whose competing
influences on precipitation led to an overall average rainy season. During
the relatively dusty pre-onset Phase 1 (1–21 June 2016), three westward-propagating coherent cyclonic vortices between 4 and 13° N modulated
winds and rainfall in the Guinea coastal area. The monsoon onset occurred in
connection with a marked extratropical trough and cold surge over northern
Africa, leading to a breakdown of the Saharan heat low and African easterly
jet and a suppression of rainfall. During this period, quasi-stationary
low-level vortices associated with the trough transformed into more tropical,
propagating disturbances resembling an African easterly wave (AEW). To the
east of this system, moist southerlies penetrated deep into the continent.
The post-onset Phase 2 (22 June–20 July 2016) was characterised by a
significant increase in low-level cloudiness, unusually dry conditions and
strong northeastward dispersion of urban pollution plumes in SWA as well as
rainfall modulation by westward-propagating AEWs in the Sahel. Around
12–14 July 2016 an interesting and so-far undocumented cyclonic–anticyclonic
vortex couplet crossed SWA. The anticyclonic centre had its origin in the
Southern Hemisphere and transported unusually dry air filled with aged
aerosol into the region. During Phase 3 (21–26 July 2016), a similar vortex
couplet slightly farther north created enhanced westerly moisture transports
into SWA and extraordinarily wet conditions, accompanied by a deep
penetration of the biomass burning plume from central Africa. Finally, a
return to more undisturbed monsoon conditions took place during Phase 4
(27–31 July 2016). The in-depth synoptic analysis reveals that several
significant weather systems during the DACCIWA campaign cannot be attributed
unequivocally to any of the tropical waves and disturbances described in the
literature and thus deserve further study.</p></abstract-html>
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