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

Karin Kreher (1) , Michel van Roozendael (2) , François Hendrick (2) , Arnoud Apituley (3) , Ermioni Dimitropoulou (2) , Udo Friess (4) , Andreas Richter (5) , Thomas Wagner (6) , Johannes Lampel (4) , Nader Abuhassan (7) , Li Ang (8) , Monica Anguas (9) , Alkis Bais (10) , Nuria Benavent (9) , Tim Bösch (5) , Kristof Bognar (11) , Alexander Borovski (12) , Ilya Bruchkouski (13) , Alexander Cede (7) , Ka Lok Chan (14, 15) , Sebastian Donner (6) , Theano Drosoglou (10) , Caroline Fayt (2) , Henning Finkenzeller (16, 17) , David Garcia-Nieto (9) , Clio Gielen (2) , Laura Gómez-Martín (18) , Nan Hao (19) , Bas Henzing (20) , Jay Herman (7) , Christian Hermans (2) , Syedul Hoque (21) , Hitoshi Irie (21) , Junli Jin (22) , Paul Johnston (23) , Junaid Khayyam Butt (24) , Fahim Khokhar (24) , Theodore Koenig (16, 17) , Jonas Kuhn (25, 6) , Vinod Kumar (26) , Cheng Liu (15) , Jianzhong Ma (22) , Alexis Merlaud (2) , Abhishek Mishra (27) , Moritz Müller (28) , Monica Navarro-Comas (18) , Mareike Ostendorf (5) , Andrea Pazmino (29) , Enno Peters (5, 30) , Gaia Pinardi (2) , Manuel Pinharanda (29) , Ankie Piters (3) , Ulrich Platt (25) , Oleg Postylyakov (12) , Cristina Prados-Roman (18) , Olga Puentedura (18) , Richard Querel (23) , Alfonso Saiz-Lopez (9) , Anja Schönhardt (5) , Stefan Schreier (31) , André Seyler (5) , Vinayak Sinha (26) , Elena Spinei (7, 32) , Kimberly Strong (11) , Frederik Tack (2) , Xin Tian (8) , Martin Tiefengraber (28) , Jan-Lukas Tirpitz (25) , Jeroen van Gent (2) , Rainer Volkamer (16, 17) , Mihalis Vrekoussis (5, 33, 34) , Shanshan Wang (35, 9, 36) , Zhuoru Wang (37) , Mark Wenig (14) , Folkard Wittrock (5) , Pinhua Xie (8) , Jin Xu (8) , Margarita Yela (18) , Chengxin Zhang (15) , Xiaoyi Zhao (11, 38)

1 BK Scientific GmbH
2 BIRA-IASB - Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique
3 KNMI - Royal Netherlands Meteorological Institute
4 Institut für Umweltphysik [Heidelberg]
5 IUP - Institute of Environmental Physics [Bremen]
6 MPIC - Max-Planck-Institut für Chemie
7 GSFC - NASA Goddard Space Flight Center
8 Anhui Institute of Optics and Fine Mechanics
9 IQFR - Instituto de Química Física Rocasolano
10 Laboratory of Atmospheric Physics [Thessaloniki]
11 Department of Physics [Toronto]
12 IAP - A.M.Obukhov Institute of Atmospheric Physics
13 Belarusian State University
14 MIM - Meteorologisches Institut München
15 School of Earth and Space Sciences [Hefei]
16 Department of Chemistry and Biochemistry [Boulder]
17 CIRES - Cooperative Institute for Research in Environmental Sciences
18 INTA - Instituto Nacional de Técnica Aeroespacial
19 EUMETSAT - European Organisation for the Exploitation of Meteorological Satellites
20 TNO - The Netherlands Organisation for Applied Scientific Research
21 CEReS - Center for Environmental Remote Sensing [Chiba]
22 CAMS - Chinese Academy of Meteorological Sciences
23 NIWA - National Institute of Water and Atmospheric Research [Lauder]
24 NUST - National University of Sciences and Technology [Islamabad]
25 IUP - Institute of Environmental Physics [Heidelberg]
26 IISER Mohali - Indian Institute of Science Education and Research Mohali
27 Department of Earth and Environmental Sciences [Mohali]
28 ACINN - Department of Atmospheric and Cryospheric Sciences [Innsbruck]
29 STRATO - LATMOS
30 Institute for the Protection of Maritime Infrastructures
31 BOKU-Met - Institute for Meteorology and Climatology [Vienna]
32 Virginia Polytechnic Institute and State University [Blacksburg]
33 MARUM - Center for Marine Environmental Sciences [Bremen]
34 EEWRC - Energy, Environment and Water Research Center
35 Liaoning Technical University [Huludao]
36 LAP3 - Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention
37 IMF - DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute
38 ECCC - Environment and Climate Change Canada

In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 d 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 (1) 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, (2) to define a robust methodology for performance assessment of all participating instruments, and (3) 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 collision complex (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 region. 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 a unique 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 selected reference (which is obtained from the median of either all data sets or a subset), 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 consistency between all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.

Domaines: Océan, Atmosphère

Karin Kreher, Michel van Roozendael, François Hendrick, Arnoud Apituley, Ermioni Dimitropoulou, et al.. Intercomparison of NO₂, O₄, O₃ and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-visible spectrometers during CINDI-2. Atmospheric Measurement Techniques, 2020, 13 (5), pp.2169-2208. ⟨10.5194/amt-13-2169-2020⟩. ⟨insu-02566681⟩