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<front>
<journal-meta>
<journal-id journal-id-type="publisher">AMT</journal-id>
<journal-title-group>
<journal-title>Atmospheric Measurement Techniques</journal-title>
<abbrev-journal-title abbrev-type="publisher">AMT</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Atmos. Meas. Tech.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1867-8548</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/amt-7-523-2014</article-id>
<title-group>
<article-title>Insights into Tikhonov regularization: application to trace gas column retrieval and the efficient calculation of total column averaging kernels</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Borsdorff</surname>
<given-names>T.</given-names>
<ext-link>https://orcid.org/0000-0002-4421-0187</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hasekamp</surname>
<given-names>O. P.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wassmann</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Landgraf</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>SRON &amp;ndash; Netherlands Institute for Space Research, Utrecht, the Netherlands</addr-line>
</aff>
<pub-date pub-type="epub">
<day>14</day>
<month>02</month>
<year>2014</year>
</pub-date>
<volume>7</volume>
<issue>2</issue>
<fpage>523</fpage>
<lpage>535</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2014 T. Borsdorff et al.</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://amt.copernicus.org/articles/7/523/2014/amt-7-523-2014.html">This article is available from https://amt.copernicus.org/articles/7/523/2014/amt-7-523-2014.html</self-uri>
<self-uri xlink:href="https://amt.copernicus.org/articles/7/523/2014/amt-7-523-2014.pdf">The full text article is available as a PDF file from https://amt.copernicus.org/articles/7/523/2014/amt-7-523-2014.pdf</self-uri>
<abstract>
<p>Insights are given into Tikhonov regularization and its application
  to the retrieval of vertical column densities of atmospheric trace
  gases from remote sensing measurements. The study builds upon the
  equivalence of the least-squares profile-scaling approach and
  Tikhonov regularization method of the first kind with an infinite
  regularization strength. Here, the vertical profile is expressed
  relative to a reference profile. On the basis of this, we propose a
  new algorithm as an extension of the least-squares profile scaling
  which permits the calculation of total column averaging kernels on
  arbitrary vertical grids using an analytic expression. Moreover, we
  discuss the effective null space of the retrieval, which comprises
  those parts of a vertical trace gas distribution which cannot be
  inferred from the measurements.
  Numerically the algorithm
  can be implemented in a robust and efficient manner. In particular
  for operational data processing with challenging demands on
  processing time, the proposed inversion method in combination with
  highly efficient forward models is an asset.  For demonstration
  purposes, we apply the algorithm to CO column retrieval from
  simulated measurements in the 2.3 μm spectral region and
  to O&lt;sub&gt;3&lt;/sub&gt; column retrieval from the UV. These represent ideal
  measurements of a series of spaceborne spectrometers such as
  SCIAMACHY, TROPOMI, GOME, and GOME-2. For both spectral ranges, we
  consider clear-sky and cloudy scenes where clouds are modelled as an
  elevated Lambertian surface. Here, the smoothing error for the
  clear-sky and cloudy atmosphere is significant and reaches several
  percent, depending on the reference profile which is used for
  scaling. This underlines the importance of the column averaging
  kernel for a proper interpretation of retrieved column densities.
  Furthermore, we show that the smoothing due to regularization can be
  underestimated by calculating the column averaging kernel on a too
  coarse vertical grid.  For both retrievals, this effect becomes
  negligible for a vertical grid with 20–40 equally thick layers
  between 0 and 50 km.</p>
</abstract>
<counts><page-count count="13"/></counts>
</article-meta>
</front>
<body/>
<back>
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