@article{garane_lerot_coldewey-egbers_verhoelst_koukouli_zyrichidou_balis_danckaert_goutail_granville_et al._2018, 
  title={Quality assessment of the Ozone_cci Climate Research Data Package (release 2017) – Part 1:  Ground-based validation of total ozone column data products}, 
  volume={11}, 
  DOI={10.5194/amt-11-1385-2018}, 
  abstractNote={<jats:p>&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a level-3 data record, which combines individual sensor products into one single cohesive record covering the 22-year period from 1995 to 2016, generated in the frame of the European Space Agency's Climate Change Initiative Phase II. It is based on level-2 total ozone data produced by the GODFIT (GOME-type Direct FITting) v4 algorithm as applied to the GOME/ERS-2, OMI/Aura, SCIAMACHY/Envisat and GOME-2/Metop-A and Metop-B observations. In this paper we examine whether GTO-ECV meets the specific requirements set by the international climate–chemistry modelling community for decadal stability long-term and short-term accuracy. In the following, we present the validation of the 2017 release of the Climate Research Data Package Total Ozone Column (CRDP TOC) at both level 2 and level 3. The inter-sensor consistency of the individual level-2 data sets has mean differences generally within 0.5&lt;span class="thinspace"&gt;&lt;/span&gt;% at moderate latitudes (±50°), whereas the level-3 data sets show mean differences with respect to the OMI reference data record that span between −0.2&lt;span class="thinspace"&gt;&lt;/span&gt;±&lt;span class="thinspace"&gt;&lt;/span&gt;0.9&lt;span class="thinspace"&gt;&lt;/span&gt;% (for GOME-2B) and 1.0&lt;span class="thinspace"&gt;&lt;/span&gt;±&lt;span class="thinspace"&gt;&lt;/span&gt;1.4&lt;span class="thinspace"&gt;&lt;/span&gt;% (for SCIAMACHY). Very similar findings are reported for the level-2 validation against independent ground-based TOC observations reported by Brewer, Dobson and SAOZ instruments: the mean bias between GODFIT v4 satellite TOC and the ground instrument is well within 1.0&lt;span class="thinspace"&gt;&lt;/span&gt;±&lt;span class="thinspace"&gt;&lt;/span&gt;1.0&lt;span class="thinspace"&gt;&lt;/span&gt;% for all sensors, the drift per decade spans between −0.5&lt;span class="thinspace"&gt;&lt;/span&gt;% and 1.0&lt;span class="thinspace"&gt;&lt;/span&gt;±&lt;span class="thinspace"&gt;&lt;/span&gt;1.0&lt;span class="thinspace"&gt;&lt;/span&gt;% depending on the sensor, and the peak-to-peak seasonality of the differences ranges from ∼ 1&lt;span class="thinspace"&gt;&lt;/span&gt;% for GOME and OMI to  ∼ 2&lt;span class="thinspace"&gt;&lt;/span&gt;% for SCIAMACHY. For the level-3 validation, our first goal was to show that the level-3 CRDP produces findings consistent with the level-2 individual sensor comparisons. We show a very good agreement with 0.5 to 2&lt;span class="thinspace"&gt;&lt;/span&gt;% peak-to-peak amplitude for the monthly mean difference time series and a negligible drift per decade of the differences in the Northern Hemisphere of −0.11&lt;span class="thinspace"&gt;&lt;/span&gt;±&lt;span class="thinspace"&gt;&lt;/span&gt;0.10&lt;span class="thinspace"&gt;&lt;/span&gt;%&lt;span class="thinspace"&gt;&lt;/span&gt;decade&lt;sup&gt;−1&lt;/sup&gt; for Dobson and +0.22&lt;span class="thinspace"&gt;&lt;/span&gt;±&lt;span class="thinspace"&gt;&lt;/span&gt;0.08&lt;span class="thinspace"&gt;&lt;/span&gt;%&lt;span class="thinspace"&gt;&lt;/span&gt;decade&lt;sup&gt;−1&lt;/sup&gt; for Brewer collocations. The exceptional quality of the level-3 GTO-ECV v3 TOC record temporal stability satisfies well the requirements for the total ozone measurement decadal stability of 1–3&lt;span class="thinspace"&gt;&lt;/span&gt;% and the short-term and long-term accuracy requirements of 2 and 3&lt;span class="thinspace"&gt;&lt;/span&gt;%, respectively, showing a remarkable inter-sensor consistency, both in the level-2 GODFIT v4 and in the level-3 GTO-ECV v3 datasets, and thus can be used for longer-term analysis of the ozone layer, such as decadal trend studies, chemistry–climate model evaluation and data assimilation applications.&lt;/p&gt;
                    </jats:p>}, 
  publisher={Copernicus GmbH}, 
  author={Garane and Lerot and Coldewey-Egbers and Verhoelst and Koukouli and Zyrichidou and Balis and Danckaert and Goutail and Granville and et al.}, 
  year={2018}, 
  month={Mar}
  }