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  <front>
    <journal-meta><journal-id journal-id-type="publisher">ESSD</journal-id><journal-title-group>
    <journal-title>Earth System Science Data</journal-title>
    <abbrev-journal-title abbrev-type="publisher">ESSD</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Sci. Data</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1866-3516</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/essd-12-2183-2020</article-id><title-group><article-title>The Aerosol Characterization from Polarimeter <?xmltex \hack{\break}?>and Lidar (ACEPOL) airborne
field campaign</article-title><alt-title>The ACEPOL airborne
field campaign</alt-title>
      </title-group><?xmltex \runningtitle{The ACEPOL airborne
field campaign}?><?xmltex \runningauthor{K.~Knobelspiesse et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Knobelspiesse</surname><given-names>Kirk</given-names></name>
          <email>kirk.knobelspiesse@nasa.gov</email>
        <ext-link>https://orcid.org/0000-0001-5986-1751</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2 aff11">
          <name><surname>Barbosa</surname><given-names>Henrique M. J.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4027-1855</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Bradley</surname><given-names>Christine</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Bruegge</surname><given-names>Carol</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7568-6743</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Cairns</surname><given-names>Brian</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Chen</surname><given-names>Gao</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4 aff6">
          <name><surname>Chowdhary</surname><given-names>Jacek</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Cook</surname><given-names>Anthony</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8">
          <name><surname>Di Noia</surname><given-names>Antonio</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-5052-0763</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4 aff7">
          <name><surname>van Diedenhoven</surname><given-names>Bastiaan</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-5622-8619</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Diner</surname><given-names>David J.</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Ferrare</surname><given-names>Richard</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff9">
          <name><surname>Fu</surname><given-names>Guangliang</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-8916-0243</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff10">
          <name><surname>Gao</surname><given-names>Meng</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Garay</surname><given-names>Michael</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Hair</surname><given-names>Johnathan</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Harper</surname><given-names>David</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>van Harten</surname><given-names>Gerard</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8">
          <name><surname>Hasekamp</surname><given-names>Otto</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Helmlinger</surname><given-names>Mark</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Hostetler</surname><given-names>Chris</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Kalashnikova</surname><given-names>Olga</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff10">
          <name><surname>Kupchock</surname><given-names>Andrew</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4810-4154</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff16">
          <name><surname>Longo De Freitas</surname><given-names>Karla</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff11">
          <name><surname>Maring</surname><given-names>Hal</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff12">
          <name><surname>Martins</surname><given-names>J. Vanderlei</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff12">
          <name><surname>McBride</surname><given-names>Brent</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>McGill</surname><given-names>Matthew</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff13">
          <name><surname>Norlin</surname><given-names>Ken</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff12">
          <name><surname>Puthukkudy</surname><given-names>Anin</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-7371-2338</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Rheingans</surname><given-names>Brian</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff9">
          <name><surname>Rietjens</surname><given-names>Jeroen</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff11">
          <name><surname>Seidel</surname><given-names>Felix C.</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-4282-2198</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>da Silva</surname><given-names>Arlindo</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff9">
          <name><surname>Smit</surname><given-names>Martijn</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Stamnes</surname><given-names>Snorre</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-6666-0672</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff14">
          <name><surname>Tan</surname><given-names>Qian</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Val</surname><given-names>Sebastian</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-2166-9817</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Wasilewski</surname><given-names>Andrzej</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff15">
          <name><surname>Xu</surname><given-names>Feng</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff12">
          <name><surname>Xu</surname><given-names>Xiaoguang</given-names></name>
          
        <ext-link>https://orcid.org/0000-0001-9583-980X</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Yorks</surname><given-names>John</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>NASA Goddard Space Flight Center, Greenbelt, MD, USA</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Instituto de Física, Universidade de Sāo Paulo, Sāo Paulo, Brazil</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>NASA Goddard Institute for Space Studies, New York, NY, USA</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>NASA Langley Research Center, Hampton, VA, USA</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>Earth Institute, Columbia University, New York, NY, USA</institution>
        </aff>
        <aff id="aff8"><label>8</label><institution>Department of Physics and Astronomy, University of Leicester, Leicestershire, UK</institution>
        </aff>
        <aff id="aff9"><label>9</label><institution>SRON Netherlands Institute for Space Research, Utrecht, the Netherlands</institution>
        </aff>
        <aff id="aff10"><label>10</label><institution>Science Systems and Applications, Inc., Greenbelt, MD, USA</institution>
        </aff>
        <aff id="aff11"><label>11</label><institution>NASA Headquarters, Washington, D.C., USA</institution>
        </aff>
        <aff id="aff12"><label>12</label><institution>Department of Physics, University of Maryland, Baltimore County, Baltimore, MD, USA</institution>
        </aff>
        <aff id="aff13"><label>13</label><institution>NASA Armstrong Flight Research Center, Edwards, CA, USA</institution>
        </aff>
        <aff id="aff14"><label>14</label><institution>NASA Ames Research Center, Moffett Field, CA, USA</institution>
        </aff>
        <aff id="aff15"><label>15</label><institution>School of Meteorology, University of Oklahoma, Norman, OK, USA</institution>
        </aff>
        <aff id="aff16"><label>16</label><institution>Universities Space Research Association, Columbia, MD, USA</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Kirk Knobelspiesse (kirk.knobelspiesse@nasa.gov)</corresp></author-notes><pub-date><day>14</day><month>September</month><year>2020</year></pub-date>
      
      <volume>12</volume>
      <issue>3</issue>
      <fpage>2183</fpage><lpage>2208</lpage>
      <history>
        <date date-type="received"><day>25</day><month>March</month><year>2020</year></date>
           <date date-type="rev-request"><day>27</day><month>April</month><year>2020</year></date>
           <date date-type="rev-recd"><day>19</day><month>July</month><year>2020</year></date>
           <date date-type="accepted"><day>31</day><month>July</month><year>2020</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2020 Kirk Knobelspiesse et al.</copyright-statement>
        <copyright-year>2020</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020.html">This article is available from https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020.html</self-uri><self-uri xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e563">In the fall of 2017, an airborne field campaign was conducted from the NASA
Armstrong Flight Research Center in Palmdale, California, to advance the
remote sensing of aerosols and clouds with multi-angle polarimeters (MAP)
and lidars. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL)
campaign was jointly sponsored by NASA and the Netherlands Institute for
Space Research (SRON). Six instruments were deployed on the ER-2 high-altitude aircraft. Four were MAPs: the Airborne Hyper Angular Rainbow
Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager
(AirMSPI), the Airborne Spectrometer for Planetary EXploration (SPEX
airborne), and the Research Scanning Polarimeter (RSP). The remainder were
lidars, including the Cloud Physics Lidar (CPL) and the High Spectral
Resolution Lidar 2 (HSRL-2). The southern California base of ACEPOL enabled
observation of a wide variety of scene types, including urban, desert,
forest, coastal ocean, and agricultural areas, with clear, cloudy, polluted,
and pristine atmospheric conditions. Flights were performed in coordination
with satellite overpasses and ground-based observations, including the
Ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI), sun
photometers, and a surface reflectance spectrometer.</p>
    <?pagebreak page2184?><p id="d1e566">ACEPOL is a resource for remote sensing communities as they prepare for the
next generation of spaceborne MAP and lidar missions. Data are appropriate
for algorithm development and testing, instrument intercomparison, and
investigations of active and passive instrument data fusion. They are freely
available to the public. The DOI for the primary database
is <ext-link xlink:href="https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001" ext-link-type="DOI">10.5067/SUBORBITAL/ACEPOL2017/DATA001</ext-link> (ACEPOL Science Team, 2017), while
for AirMSPI it is <ext-link xlink:href="https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006" ext-link-type="DOI">10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006</ext-link> and <ext-link xlink:href="https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006" ext-link-type="DOI">10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006</ext-link> (ACEPOL AirMSPI 75 Science Team, 2017a, b). GroundMSPI data are at <ext-link xlink:href="https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009" ext-link-type="DOI">10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009</ext-link> (GroundMSPI Science Team, 2017). Table 3 lists further details of these archives.
This paper describes ACEPOL for potential data users
and also provides an outline of requirements for future field missions with
similar objectives.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e590">Aerosols, clouds, and their interactions are the largest source of
uncertainty in estimates of the radiative forcing of the Earth. Reducing
this uncertainty requires global observations to act as constraints for
studies of the role of aerosols and clouds in a changing climate (Boucher et
al., 2013). While existing passive orbital sensors show observational skill,
they are limited in their consistency and underdetermined for retrieval of
the relevant geophysical parameters (Mishchenko et al., 2004). In other
words, the remote sensing retrieval solutions are often nonunique, and
they require the use of constraints in the form of, for example, aerosol models,
which may or may not represent geophysical reality. For this reason, the
2007 Decadal Survey of the National Research Council recommended to the
National Aeronautics and Space Administration (NASA) the creation of the
Aerosol-Cloud-Ecosystems (ACE) mission, with the stated goal to reduce
climate forcing uncertainty of aerosol–cloud interactions and to better
understand ocean ecosystem carbon dioxide uptake (National Research Council, 2007). This
recommendation led to the ACE pre-formulation mission study (da Silva et
al., 2019). This study (2008–2018) was devoted to technological and
scientific developments to address aerosol–cloud climate forcing uncertainty
along with improved observations of ocean color to better characterize ocean
biology. Designs for an ocean color instrument were enhancements of previous
ocean color satellite instruments, such as the Sea-viewing Wide
Field-of-view Sensor (SeaWiFS; McClain et al., 2004). These prototypes were,
in part, developed and tested by deploying airborne instruments on high-altitude aircraft. Thus, airborne field campaigns were a key component of
the ACE pre-formulation study.</p>
      <p id="d1e593">ACEPOL was one of several field campaigns supported by ACE, with the
specific objective of testing lidar and multi-angle polarimeter (MAP)
instruments in a variety of conditions. Such instruments reduce aerosol and
cloud climate forcing uncertainties by accurately determining aerosol and
cloud optical and microphysical properties and vertical distribution. They
are, however, diverse in their measurement characteristics, retrieval
approaches, and capability (Weitkamp, 2006; Kokhanovsky et al., 2015;
Dubovik et al., 2019). Six of these instruments were installed on the ER-2
aircraft, which, because of its capability for high-altitude, long-range
flights, provides an ideal platform for exploring measurement concepts of
relevance to ACE. Two were lidars: the Cloud Physics Lidar (CPL), and the
High Spectral Resolution Lidar 2 (HSRL-2), while the remaining four
instruments were MAPs: the Airborne Hyper Angular Rainbow Polarimeter
(AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the
Airborne Spectrometer for Planetary EXploration (SPEX airborne) and the
Research Scanning Polarimeter (RSP). See Table 1 for
a summary of the characteristics of these instruments and Sect. 3 for
more detail.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e599">Airborne instrument characteristics as implemented on the ER-2
during ACEPOL. </p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.85}[.85]?><oasis:tgroup cols="6">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="justify" colwidth="4cm"/>
     <oasis:colspec colnum="3" colname="col3" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="4" colname="col4" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="5" colname="col5" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="6" colname="col6" align="justify" colwidth="3cm"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Polarimeters</oasis:entry>
         <oasis:entry colname="col2">Principal investigator</oasis:entry>
         <oasis:entry colname="col3">Spectral band centers</oasis:entry>
         <oasis:entry colname="col4">View angles</oasis:entry>
         <oasis:entry colname="col5">Spatial sampling</oasis:entry>
         <oasis:entry colname="col6">Spatial resolution</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">AirHARP</oasis:entry>
         <oasis:entry colname="col2">J. Vanderlei Martins, UMBC</oasis:entry>
         <oasis:entry colname="col3">4: 440, 550, 670, 870 nm</oasis:entry>
         <oasis:entry colname="col4">670 nm: 60 in <inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">57</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> fore to aft of nadir, other channels: 20 in <inline-formula><mml:math id="M3" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">57</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> fore to aft of nadir</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M5" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">47</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> cross-track field of view (FOV), targeted sampling mode (<inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">42.9</mml:mn></mml:mrow></mml:math></inline-formula> km at ground)</oasis:entry>
         <oasis:entry colname="col6">Gridded to 2000 pixels per latitude degree, native value: <inline-formula><mml:math id="M8" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">55</mml:mn></mml:mrow></mml:math></inline-formula> m</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">AirMSPI</oasis:entry>
         <oasis:entry colname="col2">David J. Diner, JPL</oasis:entry>
         <oasis:entry colname="col3">8: 355, 380, 445, 470*, 555, 660*, 865*, 935 nm</oasis:entry>
         <oasis:entry colname="col4">Varies with targeting mode, 10 or 15 angle pseudo-stare or continuous sweep</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M9" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">15</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> cross-track FOV (9 km at ground), targeted sampling mode</oasis:entry>
         <oasis:entry colname="col6">10 m at ground for pseudo-stare, 25 m for continuous sweep</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">RSP</oasis:entry>
         <oasis:entry colname="col2">Brian Cairns, NASA GISS</oasis:entry>
         <oasis:entry colname="col3">9: 410.3, 555, 469.1, 670, 863.5, 960, 1593.5, 1880, 2263.5 nm</oasis:entry>
         <oasis:entry colname="col4">120 from 45<inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> fore to 65<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> aft of nadir</oasis:entry>
         <oasis:entry colname="col5">Single pixel (280 m), continuous sample</oasis:entry>
         <oasis:entry colname="col6">280 m, partial successive pixel overlap</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">SPEX airborne</oasis:entry>
         <oasis:entry colname="col2">Otto Hasekamp, SRON</oasis:entry>
         <oasis:entry colname="col3">400–800 nm, <inline-formula><mml:math id="M13" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> nm resolution for intensity, 10–40 nm for polarization</oasis:entry>
         <oasis:entry colname="col4">9: <inline-formula><mml:math id="M14" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">57</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, <inline-formula><mml:math id="M16" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">42</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M17" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, <inline-formula><mml:math id="M18" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">28</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M19" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>, <inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula>, and 0<inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">6<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> cross-track, continuous sample</oasis:entry>
         <oasis:entry colname="col6">Native resolution <inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">200</mml:mn></mml:mrow></mml:math></inline-formula> m (nadir) – 1 km (<inline-formula><mml:math id="M24" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">57</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>).</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Lidars</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">Backscatter channels</oasis:entry>
         <oasis:entry colname="col4">Extinction channels</oasis:entry>
         <oasis:entry colname="col5">Horizontal resolution</oasis:entry>
         <oasis:entry colname="col6">Vertical resolution</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">CPL</oasis:entry>
         <oasis:entry colname="col2">Matthew McGill, NASA GSFC</oasis:entry>
         <oasis:entry colname="col3">355, 532, 1064 nm</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
         <oasis:entry colname="col5"><inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">200</mml:mn></mml:mrow></mml:math></inline-formula> m</oasis:entry>
         <oasis:entry colname="col6">30 m</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">HSRL-2</oasis:entry>
         <oasis:entry colname="col2">Chris Hostetler, NASA LaRC</oasis:entry>
         <oasis:entry colname="col3">355, 532, 1064 nm</oasis:entry>
         <oasis:entry colname="col4">355, 532 nm</oasis:entry>
         <oasis:entry colname="col5">1–2 km</oasis:entry>
         <oasis:entry colname="col6">15 m</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table><table-wrap-foot><p id="d1e602">* AirMSPI has polarization sensitivity for 470, 660, and 865 nm
only; all other polarimeters have polarization sensitivity in all spectral
channels.</p></table-wrap-foot></table-wrap>

      <p id="d1e1043">In addition to supporting ACE, an ACEPOL objective was to provide a
calibration reference for the Cloud-Aerosol Lidar with Orthogonal
Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared
Pathfinder Satellite Observations (CALIPSO) mission (Winker et al., 2009).
This was performed with coordinated flights along the satellite ground track
at the time of overpass. A coordinated underflight of the Cloud-Aerosol
Transport System (CATS) orbital lidar (McGill et al., 2015) was also
conducted. The third sponsor of the ACEPOL field campaign was the
Netherlands Institute for Space Research (SRON), partly funded through the
NWO/NSO project ACEPOL (ALW-GO/16-09), to further advance aerosol
measurement capabilities from space and the technological development of the
SPEX airborne instrument in particular.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e1048">Photograph from the ER-2 of smoke from prescribed burns in Kaibab
National Forest in Arizona on 9 November 2017. Credit: NASA/Stu Broce.</p></caption>
        <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f01.jpg"/>

      </fig>

      <?pagebreak page2186?><p id="d1e1057">ACEPOL consisted of nine flights from the Armstrong Flight Research Center
(AFRC) in Palmdale, California, in October and November 2017. AFRC is the
home base of the ER-2 aircraft and has excellent supporting facilities.
Furthermore, it is within range of a variety of types of scenes, oceans
off the California coast, urban areas in Los Angeles, intensive agriculture
in the California central valley, forests in the Sierra Nevada mountains, and
the high desert in California, Nevada, and Arizona. Aerosol and clouds within
these regions are similarly varied. An additional benefit is the
accessibility of many ground validation sites, in particular the aerosol
observations of the Aerosol Robotic Network (AERONET; Holben et al., 1998),
and desert salt pans such as Rosamond Dry Lake for which comprehensive
surface reflectance characterization allows vicarious calibration of
airborne sensors. Figure 1 is a pilot's photograph
from the cockpit of the ER-2, which illustrates the unique, high-altitude
vantage point of the aircraft. Deployment of an instrument on this aircraft
is a close analog for the space environment and observation conditions.
Figures 2 and 3 show
the ER-2 on the ground with a portion of the ACEPOL team and the ACEPOL
emblem, respectively. The latter indicates the position of the remote
sensing instruments on board the aircraft, with two on the fuselage and two
in each wing pod.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e1062">A portion of the ACEPOL team with the NASA ER-2 at the NASA
Armstrong Flight Research Center in Palmdale, California.</p></caption>
        <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f02.jpg"/>

      </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F3"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e1074">The ACEPOL field campaign emblem, which also shows the positions of
instruments on board the ER-2 aircraft.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f03.png"/>

      </fig>

      <p id="d1e1083">Consistent with NASA's policy on data collection and availability, ACEPOL
data are publicly available (see Data availability). The purpose of this article
is to document the conditions under which these data were collected to aid
their use by the scientific community and to describe initial efforts by
the ACEPOL team to analyze and compare results. As such, Sect. 2 describes
the ACEPOL measurement objectives, while Sect. 3 covers instrument
specifics. Section 4 chronicles the field deployment and identifies
successful observations of targets described in Sect. 2. Section 5
discusses the value of ACEPOL for various current and planned missions,
while Sect. 7 concludes.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Objectives</title>
      <p id="d1e1094">The overall objectives of the ACEPOL field campaign, as is described below,
were to test new observation systems, develop new algorithms, and validate
orbital observations. For that reason, a wide range of observation
conditions were desired. This differs from field campaigns investigating
specific processes for the purpose of broader scientific understanding. The
goals of this campaign instead focused on improvement of measurement
techniques, instrument calibration, and algorithm development. All flights
started and ended in southern California, enabling flights over urban,
rural, mountainous, desert, coastal, and deep ocean regions in a variety of
atmospheric conditions. To better organize flight planning, the ACEPOL
measurement objectives were condensed into a list of prioritized targets, as
described in Table 2 and below.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2" specific-use="star"><?xmltex \currentcnt{2}?><label>Table 2</label><caption><p id="d1e1100">Prioritized ACEPOL measurement targets. In this table, low aerosol
loading indicates a mid-visible aerosol optical depth (AOD) less than 0.1,
moderate AOD between 0.1 and 0.2, and high AOD greater than 0.2.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="justify" colwidth="4cm"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Target</oasis:entry>
         <oasis:entry colname="col2">Description</oasis:entry>
         <oasis:entry colname="col3">Achieved?</oasis:entry>
         <oasis:entry colname="col4">Dates (2017)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">1a</oasis:entry>
         <oasis:entry colname="col2">Calibration over ocean with no clouds or aerosols</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">23 Oct, 25 Oct, 7 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1b</oasis:entry>
         <oasis:entry colname="col2">Calibration over land with no clouds or aerosols</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">25 Oct</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1c</oasis:entry>
         <oasis:entry colname="col2">Calibration over spatially uniform cloud deck</oasis:entry>
         <oasis:entry colname="col3">Partially</oasis:entry>
         <oasis:entry colname="col4">1 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1d</oasis:entry>
         <oasis:entry colname="col2">Geolocation using coastlines with no clouds</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">23 Oct, 25 Oct , 26 Oct, 7 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1e</oasis:entry>
         <oasis:entry colname="col2">Coordinated CALIOP/CALIPSO or CATS underflight</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">19 Oct, 26 Oct, 7 Nov, 9 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2a</oasis:entry>
         <oasis:entry colname="col2">Validation with AERONET with medium to high aerosol loading</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">23 Oct, 25 Oct, 26 Oct, 1 Nov, 7 Nov, 9 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2b</oasis:entry>
         <oasis:entry colname="col2">Validation with AERONET with low aerosol loading</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">23 Oct, 25 Oct, 26 Oct, 1 Nov, 7 Nov, 9 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2c</oasis:entry>
         <oasis:entry colname="col2">Validation against CASPER field campaign</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">None, but one overlap with an AJAX flight on 9 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">3a</oasis:entry>
         <oasis:entry colname="col2">Satellite intercomparison for aerosol retrievals</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">23 Oct, 27 Oct, 1 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">3b</oasis:entry>
         <oasis:entry colname="col2">Satellite intercomparison for cloud retrievals</oasis:entry>
         <oasis:entry colname="col3">Partially</oasis:entry>
         <oasis:entry colname="col4">9 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">4a</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: high aerosol loads over ocean</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">4b</oasis:entry>
         <oasis:entry colname="col2">Target of opportunity: high aerosol loads over land</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">27 Oct, 1 Nov, 7 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">4c</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: multiple aerosol layers</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">5</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: aerosol above cloud</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">6</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: high aerosol loads over urban surfaces</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">7</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: marine stratocumulus clouds far from land</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">8</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: broken clouds far from land</oasis:entry>
         <oasis:entry colname="col3">No</oasis:entry>
         <oasis:entry colname="col4">–</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">9</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: low clouds over land</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">1 Nov, 3 Nov</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">10</oasis:entry>
         <oasis:entry colname="col2">Targets of opportunity: cirrus clouds</oasis:entry>
         <oasis:entry colname="col3">Yes</oasis:entry>
         <oasis:entry colname="col4">19 Oct, 23 Oct, 3 Nov, 7 Nov, 9 Nov</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p id="d1e1426">Target types fell into four broad categories: calibration, geolocation,
validation, and targets of opportunity. Calibration targets (1a, 1b, and 1c)
were meant to provide spatially uniform observations with which radiometric
and polarimetric measurements between multi-angle polarimeters can be
compared. A similar intercomparison was performed during the Polarimeter
Definition Experiment (PODEX) between the RSP and AirMSPI instruments
(Knobelspiesse et al., 2019). Intercomparison can now be performed with
those instruments plus AirHARP and SPEX airborne. Such intercomparisons can
confirm measurement uncertainty estimates and identify calibration problems.
Different scene types are useful for intercomparison: cloud-free ocean
observations (1a) provide low-reflectance, potentially highly polarized
measurements, while land scenes can have high reflectance but moderate to
low polarization. Cloud scenes provide high reflectance and low
polarization. Intercomparison requires accurate geolocation, so minimizing
scene heterogeneity and atmospheric variation is important. Furthermore,
scenes with distinct features, such as coastlines, were targeted to provide
a geolocation reference (1d). Validation targets are used to test the
geophysical products retrieved by the airborne sensors against similar
observations on the ground (2a, 2b), by other field campaigns (2c), and by
satellites (3a, 3b). Targets of opportunity are intended for algorithm
development and represent infrequently observed or difficult scenes.
Finally, it should be noted that the target number designation roughly
indicates priority. Low numbered targets are of highest priority and are
generally organized such that targets supporting validation or calibration
of radiometric quantities have the greatest precedence, followed by validation
of geophysical products derived from such observations, and then special
cases and difficult scenes (targets of opportunity).</p>
      <p id="d1e1430">Most of the highest-priority targets were observed successfully during
ACEPOL, although conditions precluded observation of uniform marine
stratocumulus cloud decks (target 1c) and most cases of high aerosol loads.
The latter was highly unusual for this part of the world, as California's
San Joaquin Valley and the Los Angeles metropolitan area are known for
typically high aerosol loads. The solution was to overfly controlled forest
fire burns farther afield in Arizona. Attempted coordination with the
Coupled Air–Sea Processes and EM Ducting Research (CASPER) east (Wang et al.,
2018) field campaign was unfortunately not possible because of scheduling
difficulty and weather. Serendipitously, one flight overlapped with a flight
by the Alpha Jet Atmospheric Experiment (AJAX), which carried a payload of
atmospheric gas sensors. High aerosol loads over the ocean (4a) were not
observed, but low aerosol load overflights of an AERONET site (2b) on a
platform off Long Beach, CA, have become the basis for several analysis
papers (e.g., Fu et al., 2020; Gao et al., 2020). Another important
accomplishment was the successful overflight of Rosamond Dry Lake from
multiple headings while a ground-based team characterized the spectral
reflectance of the lake bed. This was used to vicariously adjust the AirMSPI
calibration and serves as a reference for other measurements as well.</p>
      <p id="d1e1433">Furthermore, the value of ACEPOL observations exceeds these initial
objectives. For example, polarimetric observations of land surfaces may be
useful for assessment of bidirectional reflectance distribution function
(BRDF) and bidirectional polarization distribution function (BPDF) models
even by other instruments, and observations over the ocean can be used to
help develop ocean remote sensing algorithms (see Sect. 5.4 for more
details on the latter).</p>
<?pagebreak page2187?><sec id="Ch1.S2.SS1">
  <label>2.1</label><title>The Aerosol Cloud Ecosystems (ACE) mission study</title>
      <p id="d1e1443">ACE pre-formulation study activities included defining mission requirements,
advancing algorithms and instrument technical readiness by convening science
workshops, developing mission design white papers, and supporting new or
augmenting otherwise planned field campaigns (see
<uri>https://acemission.gsfc.nasa.gov</uri>, last access: 3 September 2020). Technological development and scientific
utilization of three classes of instruments were supported by the ACE study.
These instruments included cloud and precipitation radars, atmospheric
profiling aerosol and cloud lidars, and MAPs. Lidars and MAPs are the most
relevant for aerosol remote sensing and were deployed in early 2013 for
PODEX (Diner et al., 2013; Alexandrov et al., 2015; Van Harten et al., 2018;
Knobelspiesse et al., 2019) and in ACEPOL during the fall of 2017. In some
ways, PODEX can be considered a precursor to ACEPOL. Both used the
high-altitude ER-2 aircraft based at AFRC, flew in a variety of conditions,
and deployed AirMSPI, CPL, and RSP (among other instruments). PODEX also
deployed the Passive Aerosol and Cloud Suite (PACS), an earlier version of
AirHARP. ACEPOL offers a larger collection of more mature instruments,
notably the SPEX airborne<?pagebreak page2188?> and AirHARP polarimeters and the HSRL-2 lidar.
ACEPOL offers an opportunity to also intercompare single-instrument and
synergistic algorithms involving lidars and MAPs.</p>
</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations
(CALIPSO) mission validation</title>
      <p id="d1e1457">Airborne measurements of particulate backscatter and extinction have been
important for assessing CALIOP 532 nm (Powell et al., 2009; Rogers et al.,
2011) and 1064 nm (Vaughan et al., 2010, 2019) level 1 attenuated
backscatter profiles, level 2 aerosol optical depth (AOD) retrievals (Rogers
et al., 2014), aerosol classification methodology (Burton et al., 2013),
cirrus cloud properties (Yorks et al., 2011), and combined active (CALIOP)
passive (Moderate Resolution Imaging Spectroradiometer, MODIS) retrievals of
aerosol extinction profiles (Burton et al., 2010). Using airborne
measurements to evaluate CALIOP aerosol backscatter measurements avoids
uncertainties caused by systematic errors, spatial inhomogeneities, and
distortions associated with using ground-based lidar measurements for such
validation (Gimmestad et al., 2017). Consequently, ACEPOL also collected
measurements under the CALIOP on flights conducted on 26 October and
7 and 9 November and under the CATS sensor on 19 October.</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S2.SS3">
  <label>2.3</label><title>Netherlands Institute for Space Research (SRON) studies</title>
      <p id="d1e1469">The ACEPOL campaign served several SRON objectives related to the
improvement of MAP instrument performance and aerosol retrievals and
investigation of algorithm development for aerosol retrievals using both
polarimeter and lidar measurements. Specifically, the SPEX airborne
instrument deployed during ACEPOL is a prototype of the SPEXone instrument
that is contributed to the upcoming NASA PACE mission, due to be launched in
late 2022. Validation of the SPEX airborne level 1 data products (radiance
and degree of linear polarization, DoLP) during ACEPOL serves to identify
possible improvements to be implemented in the SPEXone instrument that is to
be contributed to NASA's Plankton-Aerosol-Cloud-ocean Ecosystem (PACE;
Werdell et al., 2019) mission. The PACE spacecraft will fly three
instruments in low Earth orbit. The primary instrument is a UV–NIR (ultraviolet and near infrared) imaging
spectrometer with additional shortwave infrared (SWIR) bands, while two MAPs will be contributed:
SPEXone and HARP-2 (see Sect. 3.1.1 for a description of the airborne
prototype of that instrument). Additionally, ACEPOL provides a test dataset
for level 2 algorithm development for SPEXone on PACE. The SRON
participation in ACEPOL was funded by the Netherlands Organization for
Scientific Research (NWO) and the Netherlands Space Office (NSO).</p><?xmltex \hack{\newpage}?>
</sec>
</sec>
<?pagebreak page2189?><sec id="Ch1.S3">
  <label>3</label><title>Observations</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Polarimeters</title>
<sec id="Ch1.S3.SS1.SSS1">
  <label>3.1.1</label><title>The Airborne Hyper Angular Rainbow Polarimeter (AirHARP)</title>
      <p id="d1e1496">AirHARP is a wide field-of-view imaging polarimeter designed for
characterization of cloud and aerosol optical properties. AirHARP is an
amplitude-splitting polarimeter: light entering the front lens is decomposed
into three orthogonal linear polarization states (0, 45, and 90<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>)
by a modified three-way Phillips prism. Each polarization state is imaged by
a unique detector array, so the first three parameters of the Stokes vector
(<inline-formula><mml:math id="M28" display="inline"><mml:mi>I</mml:mi></mml:math></inline-formula>, <inline-formula><mml:math id="M29" display="inline"><mml:mi>Q</mml:mi></mml:math></inline-formula>, and <inline-formula><mml:math id="M30" display="inline"><mml:mi>U</mml:mi></mml:math></inline-formula>) are retrieved at pixel level by combining co-located information
from all three detectors. Stripe filters on the detectors define 120
distinct along-track viewing angles across the four HARP wavelengths
(spectral widths): 440 (14), 550 (12), 670 (18), and 870 (38) nm, across a
total swath of <inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">57</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> (<inline-formula><mml:math id="M33" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">47</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M34" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) along track
(cross track). A total of 60 of these angles are at 670 nm, specifically designed for
studying the structure of the polarized cloudbow. The high angular
resolution (roughly 2<inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) enables AirHARP to measure the cloudbow
structure at all individual pixels. The remaining three wavelengths have 20
angles each for characterization of aerosols. Figure 4a shows an illustration of the sampling scheme applied by the HARP
polarimeters, where each along-track viewing angle of the instrument
produces a full push-broom image. The figure also shows an example of data
collected during the ACEPOL campaign, its second deployment. The
instrument's maiden field campaign was the Lake Michigan Ozone Study (LMOS)
in 2017 (McBride et al., 2020). For ACEPOL, AirHARP collected data over
defined targets, as the processing speed of the onboard data acquisition
system precluded continuous data collection.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e1577"><bold>(a)</bold> Illustration of the AirHARP sampling scheme applied during the
ACEPOL experiment. Each along-track viewing angle produces a full push-broom
image. Six along-track viewing angles are shown in the subplot. HARP has up
to 60 along-track viewing angles for 670 nm and up to 20 viewing angles for
other wavelengths; <bold>(b)</bold> AirHARP measured (solid circles) <inline-formula><mml:math id="M36" display="inline"><mml:mi>I</mml:mi></mml:math></inline-formula>, <inline-formula><mml:math id="M37" display="inline"><mml:mrow><mml:mi>Q</mml:mi><mml:mo>/</mml:mo><mml:mi>I</mml:mi></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M38" display="inline"><mml:mrow><mml:mi>U</mml:mi><mml:mo>/</mml:mo><mml:mi>I</mml:mi></mml:mrow></mml:math></inline-formula>, and DoLP
for a pixel marked by red cross wire in <bold>(c)</bold>, plotted as a function of
scattering angle and GRASP forward model fit for the variables of the same pixel
(solid black lines); <bold>(c)</bold> RGB composite image of a smoke scene collected on 9 November 2017 at 19:31 UTC; <bold>(d)</bold> map of aerosol optical
depth (AOD) at 440 nm retrieved for the same scene using AirHARP measurements
and the GRASP inversion algorithm.</p></caption>
            <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f04.png"/>

          </fig>

      <p id="d1e1632">AirHARP is an aircraft demonstration for the HARP CubeSat instrument, a
stand-alone satellite that was successfully launched on 19 February 2020 from
the International Space Station (ISS) conducting Earth observations for a
year-long mission. A third member of the HARP family is the HARP2 sensor,
which will provide global coverage in 2 d, as part of the NASA PACE
mission due to launch no earlier than 2022 (Werdell et al., 2019).</p>
      <p id="d1e1636">AirHARP Level 0 ACEPOL data are corrected, reconstructed, geolocated, and
calibrated in the Hyper-Angular Image Processing Pipeline (HIPP) Level 1B
algorithm. These data products are gridded to a horizontal resolution of
2000 pixels per latitude degree and packaged into HDF5 files for
distribution in the ACEPOL data archive. A Level 2 aerosol retrieval algorithm
has been implemented using the Generalized Retrieval for Aerosol and Surface
Properties (GRASP) scheme (Dubovik et al., 2011; Puthukkudy et al., 2020).
Figure 4d shows the AOD map retrieved using AirHARP measurements and
the GRASP inversion algorithm for a smoke scene in Fig. 4c. The magnitude
and spatial variability of retrieved AirHARP AOD are in good agreement with
collocated lidar (i.e., HSRL-2) observations (Puthukkudy et al., 2020) and
are also consistent with the AOD retrieved from AirSPEX and RSP instruments
(Fu et al., 2020). Cloud droplet size distribution retrievals are
implemented using a traditional parametric fit to Mie scattering curves for
liquid water droplets (McBride et al., 2020). Retrievals of ice cloud
characteristics, aerosols above clouds, ocean and surface reflectance
properties, and atmospheric correction are also important potential uses of
HARP data.</p>
</sec>
<sec id="Ch1.S3.SS1.SSS2">
  <label>3.1.2</label><title>The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)</title>
      <p id="d1e1647">The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI; Diner et al.,
2013b) is push-broom imaging camera used for the characterization of
atmospheric aerosols and clouds. In addition to radiometric channels,
AirMSPI employs photoelastic modulators (PEMs) to enable accurate
measurements of the degree and angle of linear polarization (Diner et al.,
2010; van Harten et al., 2018). These polarimetric data help discriminate
between different aerosol particle types, which is crucial to improving our
understanding on climate and air quality. The instrument flies aboard NASA's
high-altitude ER-2 aircraft and acquires Earth imagery with <inline-formula><mml:math id="M39" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">10</mml:mn></mml:mrow></mml:math></inline-formula> m spatial resolution across a 9 km wide swath. Radiance data are obtained
at 355, 380, 445, 470, 555, 660, 865, and 935 nm. The polarimetric channels at
470, 660, and 865 nm report both radiances and the linear polarization
Stokes components <inline-formula><mml:math id="M40" display="inline"><mml:mi>Q</mml:mi></mml:math></inline-formula> and <inline-formula><mml:math id="M41" display="inline"><mml:mi>U</mml:mi></mml:math></inline-formula>. AirMSPI is a precursor to the future Multi-Angle
Imager for Aerosols (MAIA) satellite instrument (see Sect. 5.3), which
will be used to improve our understanding of the health risks associated
with airborne particulate matter.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><?xmltex \currentcnt{5}?><label>Figure 5</label><caption><p id="d1e1676">AirMSPI quick looks for the three different multi-angle observation
modes. Aircraft flight direction is indicated by arrows.</p></caption>
            <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f05.png"/>

          </fig>

      <p id="d1e1685">The AirMSPI camera is mounted on a motorized single-axis gimbal to enable
multiple views of a science target from different along-track view angles.
The number of views and specific set of angles for each observing sequence
are programmable prior to flight. While approaching the target in a straight
and level flight line, the pilot presses one of three buttons to start the
corresponding multi-angle acquisition sequence. Figure 5 shows example
imagery of the sequences used during the ACEPOL campaign. All three modes begin
and end with views of the onboard dark target and polarization validator
light source.</p>
      <p id="d1e1689">AirMSPI observed a total of 24 targets in the nine-angle step-and-pseudostare
mode, 32 targets in the 15-angle mode, and 209 continuous-sweep images.
AirMSPI L1B2 geolocated radiometric and polarimetric data and quick looks are
available as noted in the Data availability section. For a further analysis and comparison
with other MAPs and lidars during ACEPOL, see Fu et al. (2020).</p><?xmltex \hack{\newpage}?>
</sec>
<?pagebreak page2190?><sec id="Ch1.S3.SS1.SSS3">
  <label>3.1.3</label><title>The Research Scanning Polarimeter (RSP)</title>
      <p id="d1e1701">A pair of RSP instruments (denoted RSP1 and RSP2; the latter was used in
ACEPOL) have been deployed on more than 25 field missions in the last 20 years. The RSP is an airborne multi-angle and multispectral polarimeter
that continuously scans in the aircraft along-track direction. During a
complete scanner rotation, a total of 205 samples, each with a
0.8<inline-formula><mml:math id="M42" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> (14 mrad) field of view, are collected. The 205 samples
include 152 views between 60<inline-formula><mml:math id="M43" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> forward and aft of the normal to
its baseplate, 10 samples viewing an internal dark reference, and 43 samples
through an Earth-viewing polarization scrambler. Samples are obtained by a
rotating polarization-compensated mirror assembly with six bore-sighted
telescopes, to simultaneously obtain nine Stokes parameter spectral bands.
Each telescope uses a Wollaston prism to split the incoming intensity into
two spatially separated orthogonally polarized components, which are then
further split and passed through dichroic filters, defined by the spectral
bandpass: (full width at half maximum bandwidths in parentheses) 410.3 (30),
469.1 (20), 555.0 (20), 670.0 (20), 863.5 (20), 960.0 (20), 1593.5 (60),
1880.0 (90), and 2263.5 (120) nm. On the ER-2, the un-vignetted viewing angle
range is from 65<inline-formula><mml:math id="M44" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> aft to 45<inline-formula><mml:math id="M45" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> forward, for a total of 120
samples. The single nadir ground pixel size from an altitude of 20 km is 280 m, and successive pixels partially overlap.</p>
      <?pagebreak page2191?><p id="d1e1740">RSP2 was calibrated in the Airborne Sensor Facility at NASA Ames Research
Center before and after ACEPOL. Radiometric calibration was stable to within
roughly 1 % for all bands, except for 410.3 nm, where a 4 % decrease in
radiometric throughput was observed (polarimetric calibration was stable to
within <inline-formula><mml:math id="M46" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">0.1</mml:mn></mml:mrow></mml:math></inline-formula> %). Data processing to level 1b (calibrated and
geolocated at-sensor measurements) consists of dark subtraction for each
scan and application of calibration coefficients to generate Stokes
parameters, together with the geolocation of each viewing angle sample.
Processing from level 1b to level 1c consists of collocating the different
viewing angles about a defined altitude, either at the ground or at cloud-top if a cloud is present. The latter requires cloud identification and a
cloud top height estimate (Sinclair et al., 2017). Level 2 processing of
cloudy scenes is split between water and ice clouds. Water cloud retrievals
include cloud optical depth and standard bi-spectral droplet size estimates
(Platnick et al., 2016), as well as both parametric (Alexandrov et al., 2012b)
and nonparametric (Alexandrov et al., 2012a) droplet size distribution
estimates that use polarization (Alexandrov et al., 2018). Most clouds
observed during ACEPOL were low-level water clouds, but when ice clouds were
detected, cloud optical depth, particle size, and particle shape/roughness
retrievals (Van Diedenhoven et al., 2012, 2013; Van Diedenhoven, 2018) were
retrieved. Level 2 processing for aerosol retrievals uses the Microphysical
Aerosol Properties from Polarimetry (MAPP) algorithm (Stamnes et al., 2018).
The MAPP land surface model consists of a Fresnel reflectance with shadowing
for the polarized reflectance (Waquet et al., 2009) together with a RossThick
(Ross, 1981; Roujean et al., 1992) LiSparse (Li and Strahler, 1992) kernel
model (Wanner et al., 1995), similar to that used for operational processing
of MODIS land surface products (Schaaf et al., 2002). RSP was operational
for all ACEPOL flights, and data are available at the ACEPOL data archive
(see Data availability section). Example RSP observations of a liquid phase cloud are shown in
Fig. 6.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6" specific-use="star"><?xmltex \currentcnt{6}?><label>Figure 6</label><caption><p id="d1e1755">RSP quick look image <bold>(a, b)</bold> from 1 November 2017. The vertical
dimension represents view angle and the horizontal dimension scan number
(time elapsed). Panel <bold>(c)</bold> is a single level 1C scan corresponding to scan 1235
at <bold>(a, b)</bold>. It shows the signature of cloud bows at large scattering angles
(135–180<inline-formula><mml:math id="M47" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) and molecular (Rayleigh) scattering for 410 nm at
scattering angles smaller than 130<inline-formula><mml:math id="M48" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>. Retrieved droplet size
parameters are effective radius of 11.5 <inline-formula><mml:math id="M49" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> and effective variance of
0.008.</p></caption>
            <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f06.png"/>

          </fig>

</sec>
<sec id="Ch1.S3.SS1.SSS4">
  <label>3.1.4</label><title>The Airborne Spectrometer for Planetary EXploration (SPEX airborne)</title>
      <p id="d1e1810">The SPEX airborne instrument (Smit et al., 2019) employs the spectral
modulation technique (Snik et al., 2009), in which the degree and angle of
linear polarization are encoded in a modulation of the radiance spectrum as
a function of wavelength. This modulation is achieved by placing a set of
dedicated optical components (quarter wave retarder, multiple order
retarder) in front of the telescope. The resulting two light beams
contain a modulation pattern as a function of wavelength (out of phase with
each other) that enter a spectrometer and are focused on a detector.
Radiance measurements are obtained between 400 and 800 nm at the spectral
resolution of the spectrometer (<inline-formula><mml:math id="M50" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula> nm), while for DoLP the
spectral resolution is determined by the modulation period, which is
conservatively estimated at 10 nm at 400 nm and 40 nm at 800 nm.</p>
      <?pagebreak page2192?><p id="d1e1823"><?xmltex \hack{\newpage}?>An example of a SPEX airborne radiance and DoLP measurement obtained during
ACEPOL is shown in Fig. 7.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7"><?xmltex \currentcnt{7}?><label>Figure 7</label><caption><p id="d1e1829">Example of SPEX airborne measurements over vegetation, for radiance
(black line) and DoLP (blue line) as function of wavelength. The modulated
spectra from which radiance and DoLP are derived are shown in green and red.</p></caption>
            <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f07.png"/>

          </fig>

      <p id="d1e1839">SPEX airborne has nine view ports that are projected on one detector, at
angles (<inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">57</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M52" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">42</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M53" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">28</mml:mn></mml:mrow></mml:math></inline-formula>,
<inline-formula><mml:math id="M54" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">14</mml:mn></mml:mrow></mml:math></inline-formula>, and 0<inline-formula><mml:math id="M55" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>). The SPEX airborne cross-track swath
is 6<inline-formula><mml:math id="M56" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>. The data processing from level 0 (detector counts) to level 1b
(calibrated and geolocated radiance and DoLP values) consists of the
following steps: dark image subtraction, spectral extraction and
line-of-sight annotation, wavelength annotation, spectral alignment of the two
modulated spectra, radiometric correction, demodulation, and geolocation.
Next, data of the different view ports are all aggregated on the same spatial
grid, yielding the level 1C data product, currently computed at 1 km <inline-formula><mml:math id="M57" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 1 km
spatial resolution.</p>
      <p id="d1e1908">For level 2 processing (Fu et al., 2020), the SPEX airborne team has focused
on aerosol retrievals, building further on the SRON aerosol retrieval
algorithm previously used for POLDER-3 processing (Hasekamp et al., 2011;
Lacagnina et al., 2015, 2017) and groundSPEX (van Harten et al., 2014; di Noia
et al., 2015). The algorithm has been extended from a bimodal retrieval
scheme to multimode retrieval scheme for an arbitrary number of modes (Fu
and Hasekamp, 2018). For processing ACEPOL data, a setup with five modes has
been used, where for each mode the aerosol column number is retrieved
corresponding to a set of fine- and coarse-mode spectrally varying
refractive indices, the fraction of spherical particles (Dubovik et al.,
2006), and the aerosol layer height. SPEX airborne data have been processed
using 16 discrete wavelengths between 450 and 750 nm. Wavelengths less than
450 nm and greater than 750 nm are excluded because of lower data quality.
SPEX airborne was operational for all ACEPOL flights, and data are available
at the ACEPOL data archive.</p>
</sec>
</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Lidars</title>
<sec id="Ch1.S3.SS2.SSS1">
  <label>3.2.1</label><title>The Cloud Physics Lidar (CPL)</title>
      <p id="d1e1927">The Cloud Physics Lidar (CPL) is a nadir-pointing, multi-wavelength (355,
532, 1064 nm) elastic backscatter lidar that measures vertical profiles of
cloud and aerosol properties (McGill et al., 2002). CPL has participated in
numerous field campaigns since its first deployment in 2000 on the ER-2,
often in tandem with the other remote sensing instruments<?pagebreak page2193?> involved in
ACEPOL. Raw CPL data are calibrated by normalizing the 355, 532, and 1064 nm
signals to the Rayleigh (molecular) backscatter between 15 and 18 km,
creating vertical profiles of the total attenuated backscatter (McGill et
al., 2007). CPL data products retrieved from the calibrated backscatter
include vertical profiles of depolarization ratio, particulate backscatter
coefficient, and particulate extinction coefficients, as well as layer
properties such as top and base altitudes, aerosol type, and optical depth
(Yorks et al., 2011; Hlavka et al., 2012).</p>
      <p id="d1e1930">CPL data products, with vertical resolution of 30 m and 1 s frequencies
(<inline-formula><mml:math id="M58" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">200</mml:mn></mml:mrow></mml:math></inline-formula> m horizontal resolution), enable a wide range of
applications including the analysis of cloud properties (McGill et al.,
2004; Bucholtz et al., 2010; Yorks et al., 2011; Alexandrov et al., 2015),
as well as aerosol and dust properties (McGill et al., 2003; Nowottnick et
al., 2011; Wu et al., 2016). CPL data from ACEPOL are fully processed and
data products are available at the ACEPOL data repository. However, an
electronics controller failed in the CPL laser during the second flight of
the campaign. The cause of this failure was not immediately apparent, and
there was no time to take the instrument out of service during the ACEPOL
campaign. Thus, the ACEPOL CPL data products after the first flight are
nonstandard, as they required more averaging, sometimes as much as 10 s
(2 km horizontal), and removal of some data at specific wavelengths due to
poor quality. Nevertheless, data are useful for validation of CALIPSO
(McGill et al., 2007; Yorks et al., 2011; Hlavka et al., 2012) and CATS data
(Yorks et al., 2016; Pauly et al., 2019.)</p>
</sec>
<sec id="Ch1.S3.SS2.SSS2">
  <label>3.2.2</label><title>The High Spectral Resolution Lidar (HSRL-2)</title>
      <p id="d1e1951">HSRL-2 is the second-generation airborne High Spectral Resolution Lidar
developed at NASA Langley Research Center. Like the first-generation HSRL-1
(Hair et al., 2008), HSRL-2 independently measures aerosol backscatter and
extinction (532 nm) using the HSRL technique, aerosol backscatter (1064 nm)
using the standard backscatter technique (Müller et al., 2014; Sawamura
et al., 2017), and aerosol depolarization at both wavelengths. HSRL-2 adds
measurements of aerosol backscatter and extinction at 355 nm using the HSRL
technique as well as measurements of aerosol depolarization at 355 nm. These
HSRL-2 measurements are used to compute AOD as well as the aerosol
extinction <inline-formula><mml:math id="M59" display="inline"><mml:mo>/</mml:mo></mml:math></inline-formula> backscatter ratio (“lidar ratio”) at 355 and 532 nm. Rogers et
al. (2009) evaluated the HSRL extinction coefficient profiles and found that
the HSRL extinction profiles are within the systematic errors of airborne in
situ measurements at visible wavelengths. Derived products include, first,
estimates of planetary boundary layer heights which use the vertically
resolved profile measurements of aerosol backscatter to derive aerosol mixed-layer heights during the daytime (Scarino et al., 2014). Second, aerosol
classification uses an algorithm to interpret the information about
aerosol physical properties indicated by the HSRL-2 aerosol intensive
parameters to qualitatively infer aerosol type (Burton et al., 2012). HSRL-2
measurements have also been used to retrieve height-resolved parameters such
as aerosol effective radius and concentrations (number, surface, volume)
(Müller et al., 2014; Sawamura et al., 2017).</p>
      <p id="d1e1961">HSRL-2 has been deployed on various NASA aircraft for both NASA and DOE
field missions (Berg et al., 2016; Sawamura et al., 2017; Burton et al.,
2018). During ACEPOL, HSRL-2 operated autonomously from the NASA ER-2
aircraft. When operated from the ER-2, the nominal HSRL-2 aerosol
backscatter profiles are reported at a vertical resolution of 15 m and a
horizontal (temporal) resolution of 1–2 km (10 s). Aerosol
depolarization ratios at all three wavelengths are reported at the same
resolutions. For ACEPOL, aerosol extinction, AOD, and lidar ratio from the
HSRL methodology are not available in some cases, particularly when the
aerosol loading was small. In these cases, the aerosol extinction at 355
and 532 nm is derived using the aerosol backscatter and an assumed lidar
ratio of 40 sr and reported at the backscatter resolution. In other cases
where the HSRL method is available for extinction products, they are
reported at 150 m vertical resolution and at temporal resolution of 60 s
generally and 10 s within smoke plumes. Calibrated aerosol backscatter
derived using the HSRL method is available in all cases. Problems with the
ER-2 coolenol pump and a circuit breaker caused HSRL-2 data gaps on the
27 October flight and loss of HSRL-2 data on the 1 November flight.</p>
</sec>
</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Ground observations</title>
      <p id="d1e1973">Ground-based observations are valuable in that they can be used to validate
or calibrate aircraft instrument measurements, or provide context for those
observations. While not part of the ACEPOL field campaign, ground sites of
two instrument networks served as targets for overflights. These networks
(the Aerosol Robotic Network, or AERONET, and air quality monitors of the
California Air Resources Board, or CARB) host their data in separate
archives that are not under direct control of ACEPOL participants. A third
effort, also ground based, involved deployment of radiometric and
atmospheric measurement at Rosamond Dry Lake. The collection of these data
was funded by ACEPOL, and they are archived at the locations in Table 3.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3" specific-use="star"><?xmltex \currentcnt{3}?><label>Table 3</label><caption><p id="d1e1979">ACEPOL data availability. Archives for the primary ACEPOL
instruments (ASDC, AirMSPI, and GroundMSPI) contain calibrated Level 1 data
with direct physical observations, e.g., radiance, degree of linear
polarization, and backscatter. Level 2 data are products of retrieval algorithms
and include, for example, aerosol intensive and extensive parameters. These
may or may not exist in the database(s) depending on the retrieval algorithm
maturity. Last access for all URLs: 3 September 2020.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="2">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Archive</oasis:entry>
         <oasis:entry colname="col2">URL, DOI</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">ASDC</oasis:entry>
         <oasis:entry colname="col2"><uri>https://asdc.larc.nasa.gov/project/ACEPOL</uri></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"><uri>https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001</uri></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AirMSPI</oasis:entry>
         <oasis:entry colname="col2"><uri>https://eosweb.larc.nasa.gov/project/airmspi/airmspi_table</uri></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"><uri>https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006</uri></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"><uri>https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006</uri></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GroundMSPI</oasis:entry>
         <oasis:entry colname="col2"><uri>https://eosweb.larc.nasa.gov/project/airmspi/airmspi_table</uri></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"><uri>https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009</uri></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">AERONET</oasis:entry>
         <oasis:entry colname="col2"><uri>https://aeronet.gsfc.nasa.gov/</uri></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CARB</oasis:entry>
         <oasis:entry colname="col2"><uri>https://www.arb.ca.gov/adam/index.html</uri></oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

<sec id="Ch1.S3.SS3.SSS1">
  <label>3.3.1</label><title>Aerosol Robotic Network (AERONET) sites</title>
      <p id="d1e2100">The Aerosol Robotic Network (AERONET; Holben et al., 1998) is a system of sun
photometers used to produce global measurements of AOD, intensive properties
(e.g., refractive index, size distribution), and precipitable water. This
NASA product provides data recorded every 15 <inline-formula><mml:math id="M60" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">min</mml:mi></mml:mrow></mml:math></inline-formula> utilizing many spectral
bands, and the data are available at the AERONET archive (<uri>https://aeronet.gsfc.nasa.gov/</uri>, last access: 3 September 2020).
During ACEPOL, the Modesto, Fresno-2, CalTech, and Bakersfield sites in
California were operational<?pagebreak page2194?> and were routinely targeted. Additional AERONET
sites that were targeted during the campaign are the USGS Flagstaff site in
Arizona and the USC SeaPRISM site. The latter is part of a sub-network
designated AERONET-Ocean Color (AERONET-OC). This network comprises enhanced
instruments that have the ability to determine water-leaving radiance in
addition to aerosol optical properties (Zibordi et al., 2009).</p>
</sec>
<sec id="Ch1.S3.SS3.SSS2">
  <label>3.3.2</label><title>California Air Resources Board (CARB) sites</title>
      <p id="d1e2123">Air particulates are measured by the California Air Resources Board (CARB)
throughout the state. A majority of CARB sites report PM<inline-formula><mml:math id="M61" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2.5</mml:mn></mml:msub></mml:math></inline-formula> (particulate
matter with an aerodynamic diameter of less than 2.5 <inline-formula><mml:math id="M62" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>) and PM<inline-formula><mml:math id="M63" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">10</mml:mn></mml:msub></mml:math></inline-formula>
(particulate matter with a diameter of less than 10 <inline-formula><mml:math id="M64" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>), as determined
by a variety of measurements, including particle counting and mass
spectrometry. Gaseous criteria for air pollutants that are regulated in
California and at the national level are also measured and reported to
ensure compliance with U.S. Environmental Protection Agency (U.S. EPA) air
quality standards and are stored at the CARB archive
(<uri>https://www.arb.ca.gov/adam/index.html</uri>, last access: 3 September 2020).</p>
      <p id="d1e2167">In addition to CARB total PM monitors, several speciated EPA PM monitors are
located in California's San Joaquin Valley (SJV) including Modesto, Fresno,
Visalia, and Bakersfield. The speciated PM monitors in Modesto, Fresno, and
Bakersfield are collocated with AERONET instruments making these sites very
useful for determining connections between near-surface PM loading and
atmospheric aerosols. Modesto, Fresno, and Bakersfield sites were regularly
targeted throughout the campaign.</p><?xmltex \hack{\newpage}?>
</sec>
<sec id="Ch1.S3.SS3.SSS3">
  <label>3.3.3</label><title>Rosamond Dry Lake ground instrumentation</title>
      <p id="d1e2179">Vicarious calibration (VicCal) is the process of calibrating an on-orbit or
aircraft sensor by observation of an Earth target which is characterized for
its optical properties. A radiative transfer program is then used to
propagate the surface measurements into a radiance incident on the flight
sensor. Ground measurements made in support of ACEPOL vicarious calibration
were performed on 25 October 2017, at Rosamond Dry Lake
(34.858704<inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 118.07638<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W). This included
measurements of surface reflectance and total column optical depth at the
time of overflight, roughly 18:00 UTC. Data were processed at JPL and are
hosted in the ACEPOL archive. These data were used by the AirMSPI team to
derive a multiplier needed to adjust the laboratory-derived radiometric gain
coefficient. For the Rosamond VicCal, the ratio of radiances using the
laboratory calibration to the VicCal-measured radiances was found to be low
for the UV bands (0.85) but within 2 % of unity for the remaining visible
bands. The discrepancy in the UV lands is under investigation, but one error
candidate is the low light level for these bands during the laboratory
calibration.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><?xmltex \currentcnt{8}?><label>Figure 8</label><caption><p id="d1e2202">GroundMSPI, two Microtops sun photometers, and a University of
Arizona Reagan sun photometer deployed on 25 October 2017 at Rosamond
Dry Lake in California. (Inset) AOD as measured by the Microtops and Reagan
sun photometers, plus a Junge model fit to the Microtops data.</p></caption>
            <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f08.jpg"/>

          </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9" specific-use="star"><?xmltex \currentcnt{9}?><label>Figure 9</label><caption><p id="d1e2213">Surface characterization on 25 October 2017 at Rosamond Dry
Lake in California using a Spectralon reflectance standard and ASD
FieldSpec Pro. (Inset) Mean and standard deviation of surface reflectance
(black, blue lines) with maxima and minima spectra (green). Reflectances are
presented in terms of the hemispherical-directional reflectance factor
(HDRF), Schaepman-Strub et al. (2006).</p></caption>
            <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f09.jpg"/>

          </fig>

      <p id="d1e2223">The VicCal campaign at Rosamond included measurements of surface reflectance
and total column optical depth at the time of overflight, roughly 18:00 UTC.
Results of these measurements are shown in Figs. 8
and 9. AOD was measured by two Microtops and
a Reagan sun photometer. The Microtops are handheld instruments, with
spectral bands at 440, 675, 870, 938, and 1020 nm. The Reagan sun photometer
(Bruegge et al., 1992; Shaw et al., 1973), built at the University of Arizona,
is an auto-tracking sun photometer, with channels at 370, 400, 440, 520, 620,
670, 780, 870, 940, and 1030 nm. The instrument was calibrated via the
Langley method by taking early morning data the day before the ER-2
overflight. A discrepancy is noted in the Microtops data, perhaps due to an
error in its surface pressure.<?pagebreak page2195?> As the Reagan instrument was calibrated
in situ, its output was considered higher in accuracy and used in the
AirMSPI VicCal. Also shown in Fig. 8 is the Junge model fit to the
Microtops data, which assumes a linear relationship on a log-log scale of
aerosol optical depth versus wavelength. Surface reflectance was measured by
the Analytical Spectral Devices (ASD) FieldSpec 4 instrument. This measures
from 350 to 2500 nm with 1 nm samples with resolution at 3 nm (VIS, NIR) and
10 nm (SWIR). Data were taken over a 500 m<inline-formula><mml:math id="M67" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 500 m area, along with spectra of a
Spectralon 100 % diffuse reflectance standard. To report radiances, the
Spectralon data are interpolated at the target sample times and corrected
for Spectralon bidirectional reflectance. The ratio of the target to
interpolated Spectralon data provides a per-sample reflectance, which is
then averaged to provide a site average.</p>
      <p id="d1e2233">Operating alongside the vicarious calibration instrumentation was the
Ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI) instrument
(see Fig. 8). The specifications of the GroundMSPI camera are similar to
AirMSPI (see Sect. 3.1.2), including the eight spectral bands within 355–935 nm, with 470, 660, and 865 nm being polarimetric. The camera is mounted
<inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula> m from the ground on a motorized altazimuth tripod.
GroundMSPI performed continuous elevation scans at different azimuths to
image the surface as well as the clear sky. The surface observations provide
a direct measurement of the polarized bidirectional reflectance distribution
function (p-BRDF), including potential spectral variance, whereas the sky
radiance and polarization data serve as input for aerosol retrievals, either
independently or combined with the airborne sensors. On 7 November 2017,
GroundMSPI performed sky scans at the Fresno AERONET station during ER2 and
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)
overpasses. GroundMSPI L1B2 rectified and co-registered radiometric and
polarimetric data, and quick looks are available as noted in the Data availability section.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T4" specific-use="star"><?xmltex \currentcnt{4}?><label>Table 4</label><caption><p id="d1e2249">Daily description of ACEPOL flights. Nine flights, with a total of
40.1 flight hours, were carried out between 19 October 2017 and 9 November 2017 for ACEPOL. Scenes of particular interest are highlighted in bold.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.90}[.90]?><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="5" colname="col5" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="6" colname="col6" align="justify" colwidth="2cm"/>
     <oasis:colspec colnum="7" colname="col7" align="justify" colwidth="3cm"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Flight date</oasis:entry>
         <oasis:entry colname="col2">Takeoff (UTC)</oasis:entry>
         <oasis:entry colname="col3">Duration (h)</oasis:entry>
         <oasis:entry colname="col4">Targets achieved</oasis:entry>
         <oasis:entry colname="col5">Instrument status</oasis:entry>
         <oasis:entry colname="col6">Coordinated observations</oasis:entry>
         <oasis:entry colname="col7">Notes</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">19 Oct</oasis:entry>
         <oasis:entry colname="col2">16:09</oasis:entry>
         <oasis:entry colname="col3">2</oasis:entry>
         <oasis:entry colname="col4"><bold>1e</bold>, CATS: 17:32 <?xmltex \hack{\hfill\break}?> <bold>10</bold>: 18:00</oasis:entry>
         <oasis:entry colname="col5">All instruments functioning</oasis:entry>
         <oasis:entry colname="col6">CATS, AERONET</oasis:entry>
         <oasis:entry colname="col7">Test flight recalled early due to high winds at landing site. Because of recall, missed potential coordination with CASPER in situ sampling in Central Valley.</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">23 Oct</oasis:entry>
         <oasis:entry colname="col2">17:01</oasis:entry>
         <oasis:entry colname="col3">5.7</oasis:entry>
         <oasis:entry colname="col4"><bold>1a, </bold>late in flight <?xmltex \hack{\hfill\break}?> <bold>1d</bold>, San Francisco Bay: 19:27 <?xmltex \hack{\hfill\break}?>Catalina Island: 21:07 <?xmltex \hack{\hfill\break}?> <bold>2a</bold>, Bakersfield: 17:50, 18:40 <?xmltex \hack{\hfill\break}?> <bold>2b</bold>, Modesto: 19:20 <?xmltex \hack{\hfill\break}?> <bold>USC_SeaPRISM: 21:07</bold> <?xmltex \hack{\hfill\break}?> <bold>3a</bold>, Terra: 18:40 <?xmltex \hack{\hfill\break}?> <bold>10</bold>: 19:54-20:26</oasis:entry>
         <oasis:entry colname="col5">All instruments functioning</oasis:entry>
         <oasis:entry colname="col6">Terra (MODIS &amp; MISR) <?xmltex \hack{\hfill\break}?>AERONET, AERONET-OC</oasis:entry>
         <oasis:entry colname="col7">Severe clear (few clouds, low aerosol load) flight with satellite coordination. <bold>Overflight of ocean AERONET USC_SeaPRISM site has ideal geometry for polarimeters, subject of comparison studies.</bold></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">25 Oct</oasis:entry>
         <oasis:entry colname="col2">16:30</oasis:entry>
         <oasis:entry colname="col3">5.9</oasis:entry>
         <oasis:entry colname="col4"><bold>1a</bold>, near coast: 20:49 <?xmltex \hack{\hfill\break}?> <bold>1b, five legs over Rosamond Dry lake: 17:18, 17:50, 18:21, 18:47, 19:24</bold> <?xmltex \hack{\hfill\break}?> <bold>1d</bold>, near coast: 20:49, Salton Sea: 21:17 <?xmltex \hack{\hfill\break}?> <bold>2a</bold>, CalTech: 18:25, Fresno: 20:15, <?xmltex \hack{\hfill\break}?> <bold>2b</bold>,  USC_SeaPrism:18:30, Bakersfield: 19:45</oasis:entry>
         <oasis:entry colname="col5">All instruments functioning</oasis:entry>
         <oasis:entry colname="col6">GroundMSPI at Rosamond Dry Lake (34.85636<inline-formula><mml:math id="M69" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> N, 118.07649<inline-formula><mml:math id="M70" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> W), AERONET, AERONET-OC</oasis:entry>
         <oasis:entry colname="col7">Severe clear, primary focus was <bold>overflights of Rosamond Dry Lake</bold> while a ground team characterized surface reflectance.</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">26 Oct</oasis:entry>
         <oasis:entry colname="col2">18:00</oasis:entry>
         <oasis:entry colname="col3">4.5</oasis:entry>
         <oasis:entry colname="col4"><bold>1d</bold>, S. California coast: 19:40, Salton Sea: 19:53 <?xmltex \hack{\hfill\break}?> <bold>1e</bold>, CALIPSO underflight: 20:50 <?xmltex \hack{\hfill\break}?> <bold>2a, Fresno: 18:48</bold> <?xmltex \hack{\hfill\break}?> <bold>2b, Bakersfield: 19:11</bold></oasis:entry>
         <oasis:entry colname="col5">All instruments functioning</oasis:entry>
         <oasis:entry colname="col6">CALIPSO, AERONET</oasis:entry>
         <oasis:entry colname="col7"><bold>Central Valley AERONET overflights</bold>, followed by CALIPSO track coordination. Cloud free.</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">27 Oct</oasis:entry>
         <oasis:entry colname="col2">17:00</oasis:entry>
         <oasis:entry colname="col3">3.2</oasis:entry>
         <oasis:entry colname="col4"><bold>3a</bold>, Terra: 18:21 <?xmltex \hack{\hfill\break}?> <bold>4b</bold>, smoke from fires: 18:00, 18:32, 18:55</oasis:entry>
         <oasis:entry colname="col5">All instruments functioning, some HSRL gaps (ER-2 cooling problem)</oasis:entry>
         <oasis:entry colname="col6">AERONET <?xmltex \hack{\hfill\break}?>Terra (MODIS &amp; MISR)</oasis:entry>
         <oasis:entry colname="col7">Flight targeting prescribed burns in Arizona. Cloud free.</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">1 Nov</oasis:entry>
         <oasis:entry colname="col2">16:35</oasis:entry>
         <oasis:entry colname="col3">5</oasis:entry>
         <oasis:entry colname="col4"><bold>1c</bold>, S. California coast: 17:30 <?xmltex \hack{\hfill\break}?> <bold>2a</bold>, Bakersfield: 17:00 <?xmltex \hack{\hfill\break}?> <bold>2b</bold>, Flagstaff: 19:20 <?xmltex \hack{\hfill\break}?> <bold>3a</bold>, Terra: 18:39 <?xmltex \hack{\hfill\break}?> <bold>4b</bold>, smoke from fires: 19:12 <?xmltex \hack{\hfill\break}?> <bold>9</bold>, Los Angeles basin: 17:45</oasis:entry>
         <oasis:entry colname="col5">No HSRL (ER-2 cooling problem), only one AirMSPI target, Reduced AirHARP observations</oasis:entry>
         <oasis:entry colname="col6">AERONET <?xmltex \hack{\hfill\break}?>Terra (MODIS &amp; MISR)</oasis:entry>
         <oasis:entry colname="col7">Marine stratocumulus clouds off S. California, then smoke in Arizona.</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">3 Nov</oasis:entry>
         <oasis:entry colname="col2">18:58</oasis:entry>
         <oasis:entry colname="col3">2.9</oasis:entry>
         <oasis:entry colname="col4"><bold>9</bold>: 20:00, 20:42 <?xmltex \hack{\hfill\break}?> <bold>10</bold>: 21:10</oasis:entry>
         <oasis:entry colname="col5">All instruments functioning</oasis:entry>
         <oasis:entry colname="col6"/>
         <oasis:entry colname="col7">Short flight to test aircraft/instrument repairs. California Central Valley with multilayered clouds.</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T5" specific-use="star"><?xmltex \currentcnt{4}?><label>Table 4</label><caption><p id="d1e2637">Continued.</p></caption><oasis:table frame="topbot"><?xmltex \begin{scaleboxenv}{.90}[.90]?><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="5" colname="col5" align="justify" colwidth="3cm"/>
     <oasis:colspec colnum="6" colname="col6" align="justify" colwidth="2cm"/>
     <oasis:colspec colnum="7" colname="col7" align="justify" colwidth="3cm"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">Flight date</oasis:entry>
         <oasis:entry colname="col2">Takeoff (UTC)</oasis:entry>
         <oasis:entry colname="col3">Duration (h)</oasis:entry>
         <oasis:entry colname="col4">Targets achieved</oasis:entry>
         <oasis:entry colname="col5">Instrument status</oasis:entry>
         <oasis:entry colname="col6">Coordinated observations</oasis:entry>
         <oasis:entry colname="col7">Notes</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">7 Nov</oasis:entry>
         <oasis:entry colname="col2">17:19</oasis:entry>
         <oasis:entry colname="col3">5.3</oasis:entry>
         <oasis:entry colname="col4"><bold>1a</bold>: 20:31 <?xmltex \hack{\hfill\break}?> <bold>1d</bold>, Monterey Bay: 20:16 <?xmltex \hack{\hfill\break}?> <bold>1e</bold>, CALIPSO underflight, California Central Valley: 21:18 <?xmltex \hack{\hfill\break}?> <bold>2a</bold>, Bakersfield: 17:55, 19:06, 21:57, Fresno: 19:40, Modesto: 20:06 <?xmltex \hack{\hfill\break}?> <bold>2b</bold>, CalTech: 18:10 <?xmltex \hack{\hfill\break}?> <bold>10</bold>: 18:21, 20:40</oasis:entry>
         <oasis:entry colname="col5">AirHARP lost heater, no data for end of flight</oasis:entry>
         <oasis:entry colname="col6">CALIPSO, AERONET</oasis:entry>
         <oasis:entry colname="col7">Targeting AERONET sites and CALIPSO track, plus clear segment over the ocean.</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">9 Nov</oasis:entry>
         <oasis:entry colname="col2">17:16</oasis:entry>
         <oasis:entry colname="col3">5.6</oasis:entry>
         <oasis:entry colname="col4"><bold>1e</bold>, CALIPSO underflight, California and Nevada desert: 21:07 <?xmltex \hack{\hfill\break}?> <bold>2a</bold>, Fresno: 22:02 <?xmltex \hack{\hfill\break}?> <bold>2b</bold>, Flagstaff: 18:24, 19:55 <?xmltex \hack{\hfill\break}?> <bold>2c</bold>, AJAX flight overlap, 21:50 <?xmltex \hack{\hfill\break}?> <bold>4b, smoke from fires: 19:36, 19:52</bold> <?xmltex \hack{\hfill\break}?> <bold>10</bold>, end of flight</oasis:entry>
         <oasis:entry colname="col5">All instruments functioning</oasis:entry>
         <oasis:entry colname="col6">CALIPSO, AERONET, AJAX</oasis:entry>
         <oasis:entry colname="col7"><bold>Return to Arizona for smoke near the Grand Canyon, successfully observed high aerosol loads.</bold> CALIPSO under flight, coincident measurement with AJAX flight.</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup><?xmltex \end{scaleboxenv}?></oasis:table></table-wrap>

</sec>
</sec>
</sec>
<?pagebreak page2196?><sec id="Ch1.S4">
  <label>4</label><title>Deployment</title>
<sec id="Ch1.S4.SS1">
  <label>4.1</label><title>Flight planning</title>
      <p id="d1e2816">Daily flight planning was informed by weather and aerosol forecasts from
NASA's Global Modeling and Assimilation Office (GMAO,
<uri>https://gmao.gsfc.nasa.gov</uri>, last access: 3 September 2020) and the European Centre for Medium-Range Weather
Forecasts (ECMWF, <uri>http://ecmwf.int</uri>, last access: 3 September 2020), satellite imagery from several
geostationary and polar orbiting satellites (e.g., GOES-16, MODIS, VIIRS),
and fire weather outlooks from NOAA's Storm Prediction Center
(<uri>https://www.spc.noaa.gov/products/fire_wx</uri>, last access: 3 September 2020). Flight plans
were drafted based on forecast information and adjusted in real time to
account for the rapid changes in fire and weather conditions. See
Table 4 for detailed information about each flight.
This table lists relevant information about each flight, including observed
targets, instrument status, and coordinated observations with satellite,
ground, or other aircraft observations. Local time at AFRC is UTC <inline-formula><mml:math id="M71" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula> 08:00.
Scenes of particular interest are highlighted in bold. The “Moving Lines”
flight planning tool (LeBlanc, 2018) was used to prepare for all flights,
along with weather forecasting support of the NASA Global Modeling and
Assimilation Office (GMAO).</p>
</sec>
<sec id="Ch1.S4.SS2">
  <label>4.2</label><title>Aircraft operations</title>
      <p id="d1e2843">All airborne sensors were deployed together on the NASA Lockheed Earth
Resources (ER-2) aircraft, based at the NASA AFRC in Palmdale, California.
The ER-2 is a high-altitude aircraft, capable of flying up to roughly 21 km
(68 000 ft), above most of the Earth's atmosphere. Flights were contained
within the continental United States and offshore, primarily in California,
Nevada, and Arizona. The aircraft altitude, range, and the variety of
conditions within that range made the ER-2 deployment from AFRC an excellent
orbital analogue platform.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F10" specific-use="star"><?xmltex \currentcnt{10}?><label>Figure 10</label><caption><p id="d1e2848">Flight tracks for the ACEPOL field campaign. Nine flights were
conducted from 19 October to 9 November 2017 over California,
Nevada, Arizona, New Mexico, and the coastal Pacific Ocean from the Armstrong
Flight Research Center in Palmdale, California. Image mapped using Google
Earth, © 2018 Google.</p></caption>
          <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f10.png"/>

        </fig>

      <?pagebreak page2199?><p id="d1e2857">Figure 10 is a graphical illustration of ACEPOL flight tracks with more
information in Table 4. Generally, atmospheric conditions during ACEPOL were
clear, with very low aerosol loads, and few clouds. The range of the ER-2
helped compensate for these somewhat unusual low aerosol conditions,
providing for cloud observations in northern California or offshore, and
deployments east over Arizona to overfly prescribed forest fire burns near
the Grand Canyon in Arizona.</p>
      <p id="d1e2861">One of the priorities of ACEPOL was coordinated overflights of ground sites
to validate retrievals by the remote sensing instruments. AERONET sun
photometers were overflown on all days except the test flights on 19 October
and 3 November. Often, these overflights were planned so
that the aircraft heading was close to the solar principal plane (SPP),
which maximizes the scattering angle range of MAP observations in order to
increase the measured information. The AERONET-OC site “USC_SEAPRISM”, located on an oil platform off Newport Beach, California, was of
particular interest because of the capability for concurrent ocean and
atmosphere measurements. This site was targeted on multiple days. Since CARB
particulate matter monitoring sites are often co-located with AERONET sites
(especially in the California Central Valley), these were frequently
monitored as well.</p>
      <p id="d1e2864">On the last ACEPOL flight (9 November), there was a serendipitous
overflight of a (lower-altitude) flight by an Alpha Jet stationed at the
NASA Ames Research Center (ARC) as part of the Alpha Jet Atmospheric
Experiment (AJAX) flight series (Hamill et al., 2016). The Alpha Jet was
instrumented with a wing pod sampling gas concentrations of <inline-formula><mml:math id="M72" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>,
<inline-formula><mml:math id="M73" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CH</mml:mi><mml:mn mathvariant="normal">4</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M74" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">H</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:mi mathvariant="normal">O</mml:mi></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M75" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, and HCHO, plus 3D wind speeds, temperature, and
pressure, and preceded the ER-2 by about 1 h in an area of the eastern
Sierra Nevada Mountains.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F11" specific-use="star"><?xmltex \currentcnt{11}?><label>Figure 11</label><caption><p id="d1e2915">Example of variable instrument observation characteristics for a
scene on 27 October 2017, of biomass burning smoke from prescribed burns
near the Grand Canyon. Image mapped using Google Earth, © 2018 Google.</p></caption>
          <?xmltex \igopts{width=483.69685pt}?><graphic xlink:href="https://essd.copernicus.org/articles/12/2183/2020/essd-12-2183-2020-f11.png"/>

        </fig>

</sec>
<sec id="Ch1.S4.SS3">
  <label>4.3</label><title>Example scene</title>
      <p id="d1e2932">ACEPOL brings together four multi-angle polarimeters and two lidars which
have disparate observation characteristics. An example of this is shown in
Fig. 11. This scene, an overflight of prescribed
burns near the Grand Canyon on 27 October 2017, was observed by all
instruments, although CPL and RSP data are omitted from this figure for
clarity. Aerosol backscatter in the lidar data (HSRL shown, CPL omitted)
shows smoke in the process of either being lofted by surface topography or
trapped by that topography. Large-scale AirHARP data indicate the horizontal
extent of the smoke plume, while high-spatial-resolution AirMSPI data
demonstrate fine-scale spatial variability. Continuous sampling polarimeters
(SPEX airborne, shown, RSP, omitted) capture the atmospheric state for the
entire flight. All instruments can be used to further derive the aerosol
optical properties to varying degrees of success, depending on observation
information content and retrieval algorithm design. Because of the
overlapping nature of such observations, these scenes provide a test of
retrieval capability (e.g., Fu et al., 2020; Gao et al., 2020; McBride et
al., 2020; Puthukkudy et al., 2020) . They can also be used to investigate
algorithms that incorporate data from multiple instruments.</p>
</sec>
</sec>
<sec id="Ch1.S5">
  <label>5</label><title>Value for future missions</title>
<sec id="Ch1.S5.SS1">
  <label>5.1</label><title>Aerosol, Cloud, Convection and Precipitation (ACCP) mission study</title>
      <p id="d1e2952">ACEPOL was designed to evaluate instrument designs under consideration for
the ACE mission study, which had scientific goals that are still relevant
today. As evidence, the 2017 Decadal Survey of the National Academies of
Sciences, Engineering, and Medicine (National Academies of Sciences,
Engineering, and Medicine, 2018) identified targeted observables
(“aerosols” and “clouds, convection, and precipitation”). In response,
NASA is now conducting the Aerosol, Cloud, Convection and Precipitation
(ACCP) pre-formulation study
(<uri>https://science.nasa.gov/earth-science/decadal-accp</uri>, last access: 3 September 2020). Spaceborne versions
of the airborne lidar and polarimeters that participated in ACEPOL are under
consideration for ACCP. Hence, ACEPOL data play an important role in ACCP
activities.</p>
</sec>
<sec id="Ch1.S5.SS2">
  <label>5.2</label><title>Hyper Angular Rainbow Polarimeter (HARP) CubeSat</title>
      <p id="d1e2966">AirHARP provides an excellent proxy dataset for the development of HARP
CubeSat algorithms. The two instruments are nearly identical, although
AirHARP experienced temperature, vibrational, and humidified conditions on
aircraft that are not present in space. Like AirHARP, the HARP CubeSat does
not have an onboard calibrator, so many of the correction techniques used
on the AirHARP data will carry over to the CubeSat data. However, by
pointing the spacecraft, the HARP CubeSat sensor is capable of lunar, limb,
and deep space views, as well as coverage over a larger variety of surfaces,
which may improve post-processing and vicarious data calibrations.</p>
      <p id="d1e2969">The synergy between AirHARP and other ACEPOL instruments provides excellent
opportunities to study design and sampling, with relevance to HARP CubeSat.
Because of altitude and bandwidth limitations, the instruments have
different spatial resolutions. For AirHARP, ground pixel is much smaller
(55 <inline-formula><mml:math id="M76" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>) than it will be from HARP CubeSat (about 4 km at nadir). AirHARP
retrievals can be used to study small-scale variabilities in a cloud field
(McBride et al., 2020) and smoke plume (Puthukkudy et al., 2020). These
features will be much less resolved in HARP CubeSat data, which is better
suited for intercomparisons with MODIS and other satellite instruments. As
a technology demonstration, the amount of data collected by HARP CubeSat is
severely constrained by spacecraft storage and downlink capabilities,
allowing for a single scene per day. This limitation is not<?pagebreak page2200?> present in
future versions of the HARP payload, such as HARP2 on PACE.</p>
</sec>
<sec id="Ch1.S5.SS3">
  <label>5.3</label><title>Multi-Angle Imager for Aerosols (MAIA)</title>
      <p id="d1e2988">NASA selected the Multi-Angle Imager for Aerosols (MAIA) investigation
(Diner et al., 2018) as part of the third Earth Venture Instrument (EVI-3)
solicitation. MAIA's primary objective is to assess the impacts of different
types of airborne particulate matter (PM) on human health, where “type”
refers to the proportions of aerosols having different sizes, shapes,
compositions, and speciated particulate matter counts. The satellite
instrument contains a push-broom multispectral and polarimetric camera
mounted on a two-axis gimbal. Along-track pointing (up to <inline-formula><mml:math id="M77" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">60</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M78" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>) enables multiangle observations over a discrete set of
globally distributed target areas, while cross-track pointing provides the
camera with a wide cross-track field of regard (<inline-formula><mml:math id="M79" display="inline"><mml:mrow><mml:mo>±</mml:mo><mml:mn mathvariant="normal">45</mml:mn></mml:mrow></mml:math></inline-formula><inline-formula><mml:math id="M80" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>), permitting frequent revisits of the designated targets. MAIA makes use of
the same dual-PEM polarimetric imaging approach as AirMSPI and extends the
spectral range into the shortwave infrared (SWIR). The camera includes 14
spectral bands in the ultraviolet (UV), visible–near-infrared (VNIR), and
SWIR, of which three are polarimetric (442, 645, and 1040 nm). Channels near the
<inline-formula><mml:math id="M81" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> A-band (749, 762.5 nm) are included to explore sensitivity to
aerosol layer (and cloud) height. Launch into a 740 km sun-synchronous,
ascending node orbit with 10:30 Equator-crossing time is planned for
mid-2022 aboard the General Atomics Orbital Test Bed-2 spacecraft. MAIA
measurements will be used to retrieve total AOD and column effective aerosol
optical and microphysical properties at 1 km spatial resolution, using an
optimal estimation algorithm (Xu et al., 2017). A geostatistical regression
modeling framework will be used to transform column aerosol optical and
microphysical properties to speciated, near-surface PM concentrations
(Kalashnikova et al., 2018). During ACEPOL, AirMSPI collected imagery over
speciated PM and AERONET sites, while HSRL-2 obtained independent data
regarding aerosol types and their vertical distributions, making the
campaign a valuable source of information for testing and validation of MAIA
algorithms.</p>
</sec>
<sec id="Ch1.S5.SS4">
  <label>5.4</label><title>Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission</title>
      <p id="d1e3046">The NASA PACE mission, due to be launched in late 2022, will contain three
instruments. The primary instrument is the Ocean Color Imager (OCI), a
UV–VIS spectrometer designed for Ocean Color remote sensing applications.
OCI also has channels in the SWIR and will also perform retrievals of
aerosol, cloud, and land surface geophysical properties. The PACE payload
will also contain two, contributed, MAPs. Airborne prototypes of these
instruments, with similar characteristics, were flown as part of ACEPOL.
AirHARP<?pagebreak page2201?> is the airborne prototype of PACE/HARP2, while SPEX airborne is the
prototype of PACE/SPEXone (Werdell et al., 2019; Hasekamp et al., 2019). For
these reasons, ACEPOL data provide a valuable resource for the development
of remote sensing strategies for PACE, by acting as a proxy for the MAPs on
PACE. The spectrometer characteristics of SPEX airborne can also serve as a
proxy for the OCI UV–VIS spectrometer, while the SWIR channels on RSP (with some
exceptions) can stand in for those on OCI. Furthermore, the characteristics
of other MAPs deployed during ACEPOL can be used to understand the impact of
PACE design decisions. Additionally, coincident observation by other
instruments, namely the CPL and HSRL-2 lidars, can be used to validate
assessed retrievals. Studies of these observations in the context of PACE
are active and underway (e.g., Smit et al., 2019; Fu et al., 2020).</p>
</sec>
<sec id="Ch1.S5.SS5">
  <label>5.5</label><title>Upcoming SPEX airborne deployments</title>
      <p id="d1e3058">As part of the EU Horizon 2020 project SCARBO (Space Carbon Observatory) it
is planned that SPEX airborne will participate in an airborne campaign in
September 2020 (depending on the COVID-19 situation), flying together with
two instruments that measure <inline-formula><mml:math id="M82" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>. The goal is to use aerosol measurements
from SPEX airborne to improve <inline-formula><mml:math id="M83" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> retrievals from two instruments dedicated to
<inline-formula><mml:math id="M84" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> retrieval: the MAMAP (Methane Airborne Mapper) spectrometer (Krings et
al., 2011) and the NanoCarb interferometer (Ferrec et al., 2019) The flights
will depart from Toulouse and will cover (parts of) France, Spain, Italy, and
Germany. The aircraft for the SCARBO campaign will be a Falcon that will fly
between 2 and 10 km altitude. For upcoming deployments, the data-processing
chain (from level 0 to level 2) will make full use of the algorithm
processor performed for ACEPOL (Smit et al., 2019; Fu et al., 2020).</p>
</sec>
</sec>
<sec id="Ch1.S6">
  <label>6</label><title>Data availability</title>
      <p id="d1e3103">The primary repository for ACEPOL data is the NASA Atmospheric Science Data
Center (ASDC), at the Langley Research Center. AirMSPI and GroundMSPI data
are stored separately at the ASDC, while AERONET data are located at their
own archive. Air quality from California are stored at the CARB website.
AJAX data are available by request to the PI, Laura Iraci, at NASA ARC.
The DOI for the primary database is <ext-link xlink:href="https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001">https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/ DATA001</ext-link>
(ACEPOL Science Team, 2017), while for AirMSPI it is
<ext-link xlink:href="https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006">https://doi.org/10.5067/AIRCRAFT/ AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006</ext-link> and
<ext-link xlink:href="https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006">https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/ RADIANCE/TERRAIN_V006</ext-link> (ACEPOL
AirMSPI Science Team, 2017a, b). GroundMSPI data are at
<ext-link xlink:href="https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009">https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/ RADIANCE_v009</ext-link> (GroundMSPI
Science Team, 2017). Table 3 lists further details of
these archives.</p>
</sec>
<sec id="Ch1.S7" sec-type="conclusions">
  <label>7</label><title>Conclusions</title>
      <p id="d1e3126">The ACEPOL field campaign explored techniques for remote sensing of aerosol
and cloud optical properties with a variety of MAP and lidar designs.
Roughly four categories of observations were targeted: those that aid in
radiometric property calibration or validation, those supporting geolocation
tests, those for validating the retrieval of derived geophysical parameters,
and “targets of opportunity” representing difficult or rarely observed
scenes to use in algorithm development. The field campaign was largely a
success: all instruments were operational with limited outages for technical
or engineering problems, and data have been processed and archived.
Conditions were sufficient to achieve most of the primary objectives,
although unusually low aerosol loads compelled the research aircraft to
target forest fires further afield.</p>
      <p id="d1e3129">These co-located observations, gathered in a diversity of conditions, are a
valuable resource for algorithm development, instrument design, and other
studies, and they are archived in publicly available databases. Furthermore, the
coordination and teamwork demonstrated during this successful field campaign
can serve as a model for future campaigns, especially those that have
multiple objectives, instrument teams, and funding institutions.</p><?xmltex \hack{\clearpage}?>
</sec>

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

<?pagebreak page2202?><app id="App1.Ch1.S1">
  <?xmltex \currentcnt{A}?><label>Appendix A</label><title>Abbreviations and units</title>
      <p id="d1e3144"><table-wrap id="Taba" position="anchor"><oasis:table><oasis:tgroup cols="2">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="justify" colwidth="14cm"/>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">ABI</oasis:entry>
         <oasis:entry colname="col2">Advanced Baseline Imager</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ACCP</oasis:entry>
         <oasis:entry colname="col2">Aerosol, Cloud, Convection and Precipitation</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ACEPOL</oasis:entry>
         <oasis:entry colname="col2">Aerosol Characterization from Polarimeter and Lidar</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AERONET</oasis:entry>
         <oasis:entry colname="col2">Aerosol Robotic Network</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AERONET-OC</oasis:entry>
         <oasis:entry colname="col2">Aerosol Robotic Network – Ocean Color</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AFRC NASA</oasis:entry>
         <oasis:entry colname="col2">Armstrong Flight Research Center</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AirHARP</oasis:entry>
         <oasis:entry colname="col2">Airborne Hyper Angular Rainbow Polarimeter</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AirMSPI</oasis:entry>
         <oasis:entry colname="col2">Airborne Multiangle SpectroPolarimetric Imager</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AJAX</oasis:entry>
         <oasis:entry colname="col2">Alpha Jet Atmospheric Experiment</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">AOD</oasis:entry>
         <oasis:entry colname="col2">Aerosol optical depth</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ARC</oasis:entry>
         <oasis:entry colname="col2">NASA Ames Research Center</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ASD-AC</oasis:entry>
         <oasis:entry colname="col2">Airborne Science Data for Atmospheric Composition</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ASDC</oasis:entry>
         <oasis:entry colname="col2">Atmospheric Science Data Center (at NASA Langley Research Center)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">BPDF</oasis:entry>
         <oasis:entry colname="col2">Bidirectional polarization distribution function</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">BRDF</oasis:entry>
         <oasis:entry colname="col2">Bidirectional reflectance distribution function</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CALIOP</oasis:entry>
         <oasis:entry colname="col2">Cloud-Aerosol Lidar with Orthogonal Polarization</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CALIPSO</oasis:entry>
         <oasis:entry colname="col2">Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CARB</oasis:entry>
         <oasis:entry colname="col2">California Air Resources Board</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CASPER</oasis:entry>
         <oasis:entry colname="col2">Coupled Air Sea Processes and EM Ducting Research</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CATS</oasis:entry>
         <oasis:entry colname="col2">Cloud-Aerosol Transport System</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">CPL</oasis:entry>
         <oasis:entry colname="col2">Cloud Physics Lidar</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">DISCOVER-AQ</oasis:entry>
         <oasis:entry colname="col2">Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">DOE</oasis:entry>
         <oasis:entry colname="col2">Department of Energy</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">DoLP</oasis:entry>
         <oasis:entry colname="col2">Degree of Linear Polarization (unitless)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ECMWF</oasis:entry>
         <oasis:entry colname="col2">European Centre for Medium-Range Weather Forecasts</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">EPA</oasis:entry>
         <oasis:entry colname="col2">U.S. Environmental Protection Agency</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ER-2</oasis:entry>
         <oasis:entry colname="col2">Lockheed Earth Resources 2 (aircraft)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">EVI</oasis:entry>
         <oasis:entry colname="col2">Earth Venture Instrument</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GroundMSPI</oasis:entry>
         <oasis:entry colname="col2">Ground-based Multiangle SpectroPolarimetric Imager</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GMAO</oasis:entry>
         <oasis:entry colname="col2">Global Modeling and Assimilation Office</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GOES-16</oasis:entry>
         <oasis:entry colname="col2">Geostationary Operational Environmental Satellite – 16</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">GRASP</oasis:entry>
         <oasis:entry colname="col2">Generalized Retrieval for Aerosol and Surface Properties</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">HARP2</oasis:entry>
         <oasis:entry colname="col2">Hyper Angular Rainbow Polarimeter 2 (contribution to PACE mission)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">HDRF</oasis:entry>
         <oasis:entry colname="col2">Hemispherical-directional reflectance factor</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">HIPP</oasis:entry>
         <oasis:entry colname="col2">Hyper-Angular Image Processing Pipeline</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">HSRL-2</oasis:entry>
         <oasis:entry colname="col2">High Spectral Resolution Lidar 2</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">LaRC</oasis:entry>
         <oasis:entry colname="col2">NASA Langley Research Center</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">LMOS</oasis:entry>
         <oasis:entry colname="col2">Lake Michigan Ozone Study</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MAIA</oasis:entry>
         <oasis:entry colname="col2">Multi-angle Imager for Aerosols</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MAMAP</oasis:entry>
         <oasis:entry colname="col2">Methane Airborne Mapper</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MAP</oasis:entry>
         <oasis:entry colname="col2">Multi-angle polarimeter</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MAPP</oasis:entry>
         <oasis:entry colname="col2">Microphysical Aerosol Properties from Polarimetry (RSP algorithm)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MISR</oasis:entry>
         <oasis:entry colname="col2">Multi-angle Imaging SpectroRadiometer</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">MODIS</oasis:entry>
         <oasis:entry colname="col2">Moderate Resolution Imaging Spectroradiometer</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">NASA</oasis:entry>
         <oasis:entry colname="col2">National Aeronautics and Space Administration</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">NIR</oasis:entry>
         <oasis:entry colname="col2">Near infrared</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">NIST</oasis:entry>
         <oasis:entry colname="col2">National Institute of Standards and Technology</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">NSO</oasis:entry>
         <oasis:entry colname="col2">Netherlands Space Office</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">NWO</oasis:entry>
         <oasis:entry colname="col2">Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organization for Scientific Research)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap></p><?xmltex \hack{\clearpage}?>
      <p id="d1e3607"><table-wrap id="Tabb" position="anchor"><oasis:table><oasis:tgroup cols="2">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">ORACLES</oasis:entry>
         <oasis:entry colname="col2">ObseRvations of Aerosols above CLouds and their intEractionS</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">P-3</oasis:entry>
         <oasis:entry colname="col2">Lockheed P-3 Orion (aircraft)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">PACE</oasis:entry>
         <oasis:entry colname="col2">Plankton, Aerosol, Cloud, ocean Ecosystem</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">PACS</oasis:entry>
         <oasis:entry colname="col2">Passive Aerosol and Cloud Suite</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">PM</oasis:entry>
         <oasis:entry colname="col2">Particulate matter</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">PODEX</oasis:entry>
         <oasis:entry colname="col2">Polarimeter Definition Experiment</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">RSP</oasis:entry>
         <oasis:entry colname="col2">Research Scanning Polarimeter</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SCARBO</oasis:entry>
         <oasis:entry colname="col2">Space Carbon Observatory</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SeaBASS</oasis:entry>
         <oasis:entry colname="col2">SeaWiFS Bio-Optical Archive and Storage System</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SeaWiFS</oasis:entry>
         <oasis:entry colname="col2">Sea-viewing Wide Field-of-view Sensor</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SJV</oasis:entry>
         <oasis:entry colname="col2">San Joaquin Valley</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SPEX</oasis:entry>
         <oasis:entry colname="col2">Airborne Spectrometer for Planetary Exploration</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SPEXone</oasis:entry>
         <oasis:entry colname="col2">Spectrometer for Planetary Exploration (contribution to PACE mission)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SPP</oasis:entry>
         <oasis:entry colname="col2">Solar principal plane</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">sr</oasis:entry>
         <oasis:entry colname="col2">Steradian</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SRON</oasis:entry>
         <oasis:entry colname="col2">Netherlands Institute for Space Research</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">SWIR</oasis:entry>
         <oasis:entry colname="col2">Shortwave infrared</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">TCAP</oasis:entry>
         <oasis:entry colname="col2">Two-Column Aerosol Project</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">ViCal</oasis:entry>
         <oasis:entry colname="col2">Vicarious calibration</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">VIIRS</oasis:entry>
         <oasis:entry colname="col2">Visible Infrared Imaging Radiometer Suite</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">VIS</oasis:entry>
         <oasis:entry colname="col2">Visible (wavelengths)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap></p><?xmltex \hack{\clearpage}?>
</app>
  </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d1e3817">The ACEPOL field campaign is the product of a large team, many of whom are
co-authors of this paper. KK led the creation of the manuscript. HM,
AdS, and FCS conceived and supported the ACEPOL field campaign from NASA HQ.
OH coordinated support of ACEPOL at NWO/NSO. RF and KK performed flight
planning and coordinated the campaign in the field. AdS and KLDF provided
meteorological support for field operations. KN led ground and aircraft
support at AFRC. JVM is the PI for AirHARP, DJD is the PI for AirMSPI, BC is
the PI for RSP, OH is the PI for SPEX airborne, MM is the PI for CPL, and JH
is the PI for HSRL-2. CB lead the ground characterization at Rosamond Dry
Lake. GC coordinates the data archive. All authors provided material for the
manuscript and overall review.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3823">The authors declare that they have no conflict of interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3829">The ACEPOL field campaign would not have been possible without the
professionalism and energy of the ER-2 pilots and ground crew and the
overall support at the NASA Armstrong Flight Research Center.</p><p id="d1e3831">Research at the Jet Propulsion Laboratory, California Institute of
Technology was carried out under a contract with the National Aeronautics
and Space Administration (80NM0018D0004).</p><p id="d1e3833">We thank the United States Forest Service, in particular Jason Clawson and
David Hercher, for providing information about planned prescribed burns in
the Kaibab National Forest.</p><p id="d1e3835">The principal investigator for the USC_SEAPRISM AERONET-OC
site is Curtiss O. Davis of Oregon State University. The site manager is
Matthew Ragan of the University of Southern California.</p><p id="d1e3837">Figure 11 was visualized using Google Earth.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d1e3842">This research has been supported by the National Aeronautics and Space Administration (ACE mission study and CALIPSO mission), the Netherlands Institute for Space Research (SPEX instrument development), and the Netherlands Space Office (SPEX instrument development).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d1e3849">This paper was edited by Alexander Kokhanovsky and reviewed by Meloë Kacenelenbogen and two anonymous referees.</p>
  </notes><ref-list>
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    <!--<article-title-html>The Aerosol Characterization from Polarimeter and Lidar (ACEPOL) airborne field campaign</article-title-html>
<abstract-html><p>In the fall of 2017, an airborne field campaign was conducted from the NASA
Armstrong Flight Research Center in Palmdale, California, to advance the
remote sensing of aerosols and clouds with multi-angle polarimeters (MAP)
and lidars. The Aerosol Characterization from Polarimeter and Lidar (ACEPOL)
campaign was jointly sponsored by NASA and the Netherlands Institute for
Space Research (SRON). Six instruments were deployed on the ER-2 high-altitude aircraft. Four were MAPs: the Airborne Hyper Angular Rainbow
Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager
(AirMSPI), the Airborne Spectrometer for Planetary EXploration (SPEX
airborne), and the Research Scanning Polarimeter (RSP). The remainder were
lidars, including the Cloud Physics Lidar (CPL) and the High Spectral
Resolution Lidar 2 (HSRL-2). The southern California base of ACEPOL enabled
observation of a wide variety of scene types, including urban, desert,
forest, coastal ocean, and agricultural areas, with clear, cloudy, polluted,
and pristine atmospheric conditions. Flights were performed in coordination
with satellite overpasses and ground-based observations, including the
Ground-based Multiangle SpectroPolarimetric Imager (GroundMSPI), sun
photometers, and a surface reflectance spectrometer.</p><p>ACEPOL is a resource for remote sensing communities as they prepare for the
next generation of spaceborne MAP and lidar missions. Data are appropriate
for algorithm development and testing, instrument intercomparison, and
investigations of active and passive instrument data fusion. They are freely
available to the public. The DOI for the primary database
is <a href="https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001" target="_blank">https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001</a> (ACEPOL Science Team, 2017), while
for AirMSPI it is <a href="https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006" target="_blank">https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/ELLIPSOID_V006</a> and <a href="https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006" target="_blank">https://doi.org/10.5067/AIRCRAFT/AIRMSPI/ACEPOL/RADIANCE/TERRAIN_V006</a> (ACEPOL AirMSPI 75 Science Team, 2017a, b). GroundMSPI data are at <a href="https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009" target="_blank">https://doi.org/10.5067/GROUND/GROUNDMSPI/ACEPOL/RADIANCE_v009</a> (GroundMSPI Science Team, 2017). Table 3 lists further details of these archives.
This paper describes ACEPOL for potential data users
and also provides an outline of requirements for future field missions with
similar objectives.</p></abstract-html>
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