Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
    3.841
  • CiteScore value: 3.71 CiteScore
    3.71
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
Discussion papers
https://doi.org/10.5194/amt-2019-157
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-157
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 27 May 2019

Submitted as: research article | 27 May 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Atmospheric Measurement Techniques (AMT).

Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign

Karin Kreher1, Michel Van Roozendael2, Francois Hendrick2, Arnoud Apituley3, Ermioni Dimitropoulou2, Udo Frieß4, Andreas Richter5, Thomas Wagner6, Nader Abuhassan31, Li Ang7, Monica Anguas8, Alkis Bais9, Nuria Benavent8, Tim Bösch5, Kristof Bognar10, Alexander Borovski11, Ilya Bruchkouski12, Alexander Cede13,31, Ka L. Chan14,27, Sebastian Donner6, Theano Drosoglou9, Caroline Fayt2, Henning Finkenzeller15, David Garcia-Nieto8, Clio Gielen2, Laura Gómez-Martín23, Nan Hao34, Jay R. Herman31, Christian Hermans2, Syedul Hoque17, Hitoshi Irie17, Junli Jin18,19, Paul Johnston20, Junaid Khayyam Butt21, Fahim Khokhar21, Theodore K. Koenig15, Jonas Kuhn4,6, Vinod Kumar22, Johannes Lampel4,33, Cheng Liu16, Jianzhong Ma18,19, Alexis Merlaud2, Abhishek K. Mishra22, Moritz Müller13,32, Monica Navarro-Comas23, Mareike Ostendorf5, Andrea Pazmino24, Enno Peters5,a, Gaia Pinardi2, Manuel Pinharanda24, Ankie Piters3, Ulrich Platt4, Oleg Postylyakov11, Cristina Prados-Roman23, Olga Puentedura23, Richard Querel20, Alfonso Saiz-Lopez8, Anja Schönhardt5, Stefan F. Schreier25, Andre Seyler5, Vinayak Sinha22, Elena Spinei26,31, Kimberly Strong10, Frederik Tack2, Xin Tian7, Martin Tiefengraber13,32, Jan-Lukas Tirpitz4, Jeron van Gent2, Rainer Volkamer15, Mihalis Vrekoussis5,29,30, Shanshan Wang8,28, Zhuoru Wang27, Mark Wenig14, Folkard Wittrock5, Pinhua H. Xie7, Jin Xu7, Margarita Yela23, Chengxin Zhang16, and Xiaoyi Zhao10,b Karin Kreher et al.
  • 1BK Scientific, Mainz, Germany
  • 2Royal Belgian Institute for Space Aeronomy, Brussels, Belgium
  • 3Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
  • 4Institute of Environmental Physics, University of Heidelberg, Heidelberg, Germany
  • 5Institute of Environmental Physics, University of Bremen, Bremen, Germany
  • 6Max Planck Institute for Chemistry, Mainz, Germany
  • 7Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, China
  • 8Department of Atmospheric Chemistry and Climate, Institute of Physical Chemistry Rocasolano, Madrid, Spain
  • 9Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 10Department of Physics, University of Toronto, Toronto, Canada
  • 11A.M.Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia
  • 12Belarusian State University, Minsk, Belarus
  • 13LuftBlickEarth Observation Technologies, Mutters, Austria
  • 14Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany
  • 15Department of Chemistry & Cooperative Institute for Research on Environmental Sciences (CIRES), University of Colorado, Boulder, USA
  • 16School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui, China
  • 17Center for Environmental Remote Sensing, Chiba University, Chiba, Japan
  • 18Meteorological Observation Center, China Meteorological Administration, Beijing, China
  • 19Chinese Academy of Meteorological Science, China Meteorological Administration, Beijing, China
  • 20National Institute of Water and Atmospheric Research, Lauder, New Zealand
  • 21National University of Sciences and Technology, Islamabad, Pakistan
  • 22Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Punjab, India
  • 23National Institute forAerospaceTechnology(INTA), Madrid, Spain
  • 24Laboratoire Atmosphère, Milieux, Observations Spatiales, Université de Versailles Saint-Quentin-en-Yvelines, Centre National de la Recherche Scientifique, Guyancourt, France
  • 25Institute of Meteorology, University of Natural Resources and Life Sciences, Vienna, Austria
  • 26Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
  • 27Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
  • 28Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, China
  • 29Center of Marine Environmental Sciences (MARUM), University of Bremen, Bremen, Germany
  • 30Energy, Environment and Water Research Center (EEWRC), The Cyprus Institute, Nicosia, Cyprus
  • 31NASA Goddard Space Flight Center, USA
  • 32Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
  • 33Airyx GmbH, Justus-von-Liebig-Straße 14, 69214 Eppelheim, Germany
  • 34European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Darmstadt, German
  • anow at: Institute for the Protection of Maritime Infrastructures, German Aerospace Center (DLR), Bremerhaven, Germany
  • bnow at: Measurement and Analysis Research Section, Environment and Climate Change Canada, Toronto, M3H 5T4, Canada

Abstract. In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were to characterise and better understand the differences between a large number of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation.

The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen dimer (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region and NO2 in an additional (smaller) wavelength range in the visible. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in an unprecedented set of measurements made under highly comparable air mass conditions.

The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the reference, and the RMS error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Karin Kreher et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Karin Kreher et al.
Karin Kreher et al.
Viewed  
Total article views: 978 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
753 219 6 978 41 12 7
  • HTML: 753
  • PDF: 219
  • XML: 6
  • Total: 978
  • Supplement: 41
  • BibTeX: 12
  • EndNote: 7
Views and downloads (calculated since 27 May 2019)
Cumulative views and downloads (calculated since 27 May 2019)
Viewed (geographical distribution)  
Total article views: 681 (including HTML, PDF, and XML) Thereof 673 with geography defined and 8 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 13 Dec 2019
Publications Copernicus
Download
Short summary
In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants during an instrument intercomparison campaign (CINDI-2) at Cabauw, The Netherlands. Here we report on the outcome of this intercomparison exercise. The three major goals were to characterise the differences between the 36 spectrometers, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods.
In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric...
Citation