Author: "Piters, Ankie" - Searchworks@Jio Institute Digital Library Search Results

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133 results on '"Piters, Ankie"'

1. OZONESONDE QUALITY ASSURANCE : The JOSIE–SHADOZ (2017) Experience

Author: Thompson, Anne M., Smit, Herman G. J., Witte, Jacquelyn C., Stauffer, Ryan M., Johnson, Bryan J., Morris, Gary, von der Gathen, Peter, Van Malderen, Roeland, Davies, Jonathan, Piters, Ankie, Allaart, Marc, Posny, Françoise, Kivi, Rigel, Cullis, Patrick, Anh, Nguyen Thi Hoang, Corrales, Ernesto, Machinini, Tshidi, da Silva, Francisco R., Paiman, George, Thiong’o, Kennedy, Zainal, Zamuna, Brothers, George B., Wolff, Katherine R., Nakano, Tatsumi, Stübi, Rene, Romanens, Gonzague, Coetzee, Gert J. R., Diaz, Jorge A., Mitro, Sukarni, Mohamad, Maznorizan, and Ogino, Shin-Ya
Published: 2019

2. Weekly derived top-down volatile-organic-compound fluxes over Europe from TROPOMI HCHO data from 2018 to 2021.

Author: Oomen, Glenn-Michael, Müller, Jean-François, Stavrakou, Trissevgeni, De Smedt, Isabelle, Blumenstock, Thomas, Kivi, Rigel, Makarova, Maria, Palm, Mathias, Röhling, Amelie, Té, Yao, Vigouroux, Corinne, Friedrich, Martina M., Frieß, Udo, Hendrick, François, Merlaud, Alexis, Piters, Ankie, Richter, Andreas, Van Roozendael, Michel, and Wagner, Thomas
Subjects: SEMIVOLATILE organic compounds, TROPOSPHERIC ozone, BIOMASS burning, VOLATILE organic compounds, CLOUDINESS, CHEMICAL models, REMOTE sensing
Abstract: Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at the regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN–MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tgyr-1), which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+ 13 %) and anthropogenic VOCs (- 17 %) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50 ∘ N but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism, leading to differences of up to 10 % in the total emissions. However, the top-down emissions are very sensitive to the bias correction of the observed columns, as the biogenic emissions are 3 times lower when the correction is not applied. Furthermore, the use of different a priori biogenic emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. The sensitivity run using CAMS-GLOB-BIOv3.1 as a priori emissions in the inversion results in 30 % lower emissions with respect to the optimization using MEGAN–MOHYCAN. In regions with large temperature and cloud cover variations, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]
Published: 2024
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3. Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021

Author: Oomen, Glenn-Michael, primary, Müller, Jean-François, additional, Stavrakou, Trissevgeni, additional, De Smedt, Isabelle, additional, Blumenstock, Thomas, additional, Kivi, Rigel, additional, Makarova, Maria, additional, Palm, Mathias, additional, Röhling, Amelie, additional, Té, Yao, additional, Vigouroux, Corinne, additional, Friedrich, Martina M., additional, Frieß, Udo, additional, Hendrick, François, additional, Merlaud, Alexis, additional, Piters, Ankie, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, and Wagner, Thomas, additional
Published: 2023
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4. Supplementary material to "Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021"

Author: Oomen, Glenn-Michael, primary, Müller, Jean-François, additional, Stavrakou, Trissevgeni, additional, De Smedt, Isabelle, additional, Blumenstock, Thomas, additional, Kivi, Rigel, additional, Makarova, Maria, additional, Palm, Mathias, additional, Röhling, Amelie, additional, Té, Yao, additional, Vigouroux, Corinne, additional, Friedrich, Martina M., additional, Frieß, Udo, additional, Hendrick, François, additional, Merlaud, Alexis, additional, Piters, Ankie, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, and Wagner, Thomas, additional
Published: 2023
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5. Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021.

Author: Oomen, Glenn-Michael, Müller, Jean-François, Stavrakou, Trissevgeni, Smedt, Isabelle De, Blumenstock, Thomas, Kivi, Rigel, Makarova, Maria, Palm, Mathias, Röhling, Amelie, Té, Yao, Vigouroux, Corinne, Friedrich, Martina M., Frieß, Udo, Hendrick, François, Merlaud, Alexis, Piters, Ankie, Richter, Andreas, Roozendael, Michel Van, and Wagner, Thomas
Subjects: TROPOSPHERIC ozone, BIOMASS burning, CHEMICAL models, REMOTE sensing, VOLATILE organic compounds
Abstract: Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly-averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN-MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tg yr-1) which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+13 %) and anthropogenic VOCs (-17 %) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50° N, but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism. However, the top-down emissions are very sensitive to the bias correction of the observed columns. Furthermore, the use of different a priori emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. In regions with variable meteorology, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]
Published: 2023
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6. Global Ozone Monitoring Experiment-2 (GOME-2) Daily and Monthly Level 3 Products of Atmospheric Trace Gas Columns

Author: Chan, Ka Lok, primary, Valks, Pieter, additional, Heue, Klaus-Peter, additional, Lutz, Ronny, additional, Hedelt, Pascal, additional, Loyola, Diego, additional, Pinardi, Gaia, additional, Van Roozendael, Michel, additional, Hendrick, François, additional, Wagner, Thomas, additional, Kumar, Vinod, additional, Bais, Alkis, additional, Piters, Ankie, additional, Irie, Hitoshi, additional, Kanaya, Yugo, additional, Takashima, Hisahiro, additional, Choi, Yongjoo, additional, Park, Kihong, additional, Chong, Jihyo, additional, Cede, Alexander, additional, Frieß, Udo, additional, Richter, Andreas, additional, Ma, Jianzhong, additional, Benavent, Nuria, additional, Holla, Robert, additional, Postylyakov, Oleg, additional, Rivera Cárdenas, Claudia, additional, and Wenig, Mark, additional
Published: 2022
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7. Homogenization of the long-term global ozonesonde records

Author: Malderen, Roeland van, Poyraz, D., Smit, Herman G. J., Stauffer, Ryan M., Kois, Bogumil, Gathen, Peter von der, Querel, Richard, Ancellet, Gerard, Godin-Beekmann, Sophie, Díaz Rodríguez, Ana María, Hernández Pérez, José Luis, Jepsen, Nis, Kivi, Rigel, Prats Porta, Natalia, Torres, Carlos, Romanens, Gonzague, Stübi, Rene, Steinbrecht, Wolfgang, Allaart, Marc, Piters, Ankie J. M., Tully, Matt, Klikova, B., Motl, M., Skrivánková, Pavla, Lyall, Norrie, Gill, Michael, Oelsner, Peter, Rizi, V., Iarlori, M., Tarasick, David W., Johnson, B. J., and Thompson, Anne M.
Subjects: Homogenization, Stratospheric ozone, Ozonesondes
Abstract: Póster presentado en: WMO Technical Conference on Meteorological and Environmental Instruments and Methods of Observation celebrada del 10 al 13 de octubre de 2022 en París.
Published: 2022

8. Data Quality and Validation of Satellite Measurements of Tropospheric Composition

Author: Piters, Ankie J. M., Buchmann, Brigitte, Brunner, Dominik, Cohen, Ronald C., Lambert, Jean-Christopher, de Leeuw, Gerrit, Stammes, Piet, van Weele, Michiel, Wittrock, Folkard, Burrows, John P., editor, Borrell, Peter, editor, and Platt, Ulrich, editor
Published: 2011
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9. Tropospheric and stratospheric ozone profiles during the 2019 TROpomi vaLIdation eXperiment (TROLIX-19)

Author: Sullivan, John T., primary, Apituley, Arnoud, additional, Mettig, Nora, additional, Kreher, Karin, additional, Knowland, K. Emma, additional, Allaart, Marc, additional, Piters, Ankie, additional, Van Roozendael, Michel, additional, Veefkind, Pepijn, additional, Ziemke, Jerry R., additional, Kramarova, Natalya, additional, Weber, Mark, additional, Rozanov, Alexei, additional, Twigg, Laurence, additional, Sumnicht, Grant, additional, and McGee, Thomas J., additional
Published: 2022
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10. Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns.

Author: Chan, Ka Lok, Valks, Pieter, Heue, Klaus-Peter, Lutz, Ronny, Hedelt, Pascal, Loyola, Diego, Pinardi, Gaia, Van Roozendael, Michel, Hendrick, François, Wagner, Thomas, Kumar, Vinod, Bais, Alkis, Piters, Ankie, Irie, Hitoshi, Takashima, Hisahiro, Kanaya, Yugo, Choi, Yongjoo, Park, Kihong, Chong, Jihyo, and Cede, Alexander
Subjects: TRACE gases, OZONE, AIR pollutants, WATER vapor, TROPOSPHERIC ozone, NITROGEN dioxide, SCIENTIFIC community
Abstract: We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O 3), total and tropospheric column nitrogen dioxide (NO 2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO 2) (daily products 10.15770/EUM_SAF_AC_0048, ; monthly products 10.15770/EUM_SAF_AC_0049,). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public. [ABSTRACT FROM AUTHOR]
Published: 2023
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11. Combined UV and IR ozone profile retrieval from TROPOMI and CrIS measurements

Author: Mettig, Nora, primary, Weber, Mark, additional, Rozanov, Alexei, additional, Burrows, John P., additional, Veefkind, Pepijn, additional, Thompson, Anne M., additional, Stauffer, Ryan M., additional, Leblanc, Thierry, additional, Ancellet, Gerard, additional, Newchurch, Michael J., additional, Kuang, Shi, additional, Kivi, Rigel, additional, Tully, Matthew B., additional, Van Malderen, Roeland, additional, Piters, Ankie, additional, Kois, Bogumil, additional, Stübi, René, additional, and Skrivankova, Pavla, additional
Published: 2022
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12. Measurement Report: Tropospheric and Stratospheric Ozone Profiles during the 2019 TROpomi vaLIdation eXperiment (TROLIX-19)

Author: Sullivan, John, primary, Apituley, Arnoud, additional, Mettig, Nora, additional, Kreher, Karin, additional, Knowland, K. Emma, additional, Allart, Marc, additional, Piters, Ankie, additional, Van Roozendael, Michel, additional, Veefkind, Pepijn, additional, Ziemke, Jerry, additional, Kramarova, Natalya, additional, Weber, Mark, additional, Rozanov, Alexei, additional, Twigg, Laurence, additional, Sumnicht, Grant, additional, and McGee, Thomas, additional
Published: 2022
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13. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author: Verhoelst, Tiji, Pinardi, Gala, Eskes, Henk J., Fjæraa, Ann Mari, Boersma, Klaas Folkert, Levelt, Pieternel F., Navarro-Comas, Monica, Piters, Ankie J. M., Sinyakov, Valery P., Strong, Kimberley, Veefkind, Pepijn J., Yela-González, Margarita, Verhoelst, Tijl, Compernolle, Steven, Pinardi, Gaia, Lambert, Jean-Christopher, Eskes, Henk, Eichmann, Kai-Uwe, Fjaeraa, Ann, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmino, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Folkert Boersma, K, Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, Elokhov, Aleksandr, Gebetsberger, Manuel, Goutail, Florence, Grutter de la Mora, Michel, Gruzdev, Aleksandr, Gratsea, Myrto, Hansen, Georg, Irie, Hitoshi, Jepsen, Nis, Kanaya, Yugo, Karagkiozidis, Dimitris, Kivi, Rigel, Kreher, Karin, Levelt, Pieternel, Liu, Cheng, Müller, Moritz, Navarro Comas, Monica, Piters, Ankie, Pommereau, Jean-Pierre, Portafaix, Thierry, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Remmers, Julia, Richter, Andreas, Rimmer, John, Rivera Cárdenas, Claudia, Saavedra De Miguel, Lidia, Sinyakov, Valery, Stremme, Wolfgang, Strong, Kimberly, Van Roozendaël, Michel, Pepijn Veefkind, J, Wagner, Thomas, Wittrock, Folkard, Yela González, Margarita, Zehner, Claus, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Royal Netherlands Meteorological Institute (KNMI), Norsk Institutt for Luftforskning (NILU), Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Delft University of Technology (TU Delft), Instituto Nacional de Técnica Aeroespacial (INTA), Kyrgyz National University of Jusup Balasagyn, Department of Physics [Toronto], University of Toronto, BK Scientific GmbH, Institut für Umweltphysik [Bremen] (IUP), Universität Bremen, Science [&] Technology Corporation [Delft] (S [&] T), NASA Goddard Space Flight Center (GSFC), Institute of Meteorology and Geophysics [Innsbruck], University of Innsbruck, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, European Space Research Institute (ESRIN), European Space Agency (ESA), Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Centro de Ciencias de la Atmosfera [Mexico], Universidad Nacional Autónoma de México (UNAM), National Observatory of Athens (NOA), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Danish Meteorological Institute (DMI), Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Space and Earth Observation Centre [Sodankylä], Finnish Meteorological Institute (FMI), Department of Precision Machinery and Precision Instrumentation [Hefei], University of Science and Technology of China [Hefei] (USTC), Laboratoire de l'Atmosphère et des Cyclones (LACy), Centre National de la Recherche Scientifique (CNRS)-Université de La Réunion (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France, National Institute of Water and Atmospheric Research [Lauder] (NIWA), University of Manchester [Manchester], Institute of Environmental Physics [Bremen] (IUP), and University of Bremen
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract: International audience; This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.
Published: 2021

14. An improved TROPOMI tropospheric NO2 research product over Europe

Author: Liu, Song, Valks, Pieter, Pinardi, Gaia, Xu, Jian, Chan, Ka Lok, Argyrouli, Athina, Lutz, Ronny, Beirle, Steffen, Khorsandi, Ehsan, Baier, Frank, Huijnen, Vincent, Bais, Alkiviadis, Donner, Sebastian, Dörner, Steffen, Gratsea, M., Hendrick, Francoise, Karagkiozidis, D., Lange, Kezia, Piters, Ankie, Remmers, J., Richter, A., Van Roozendael, M., Wagner, T., Wenig, M., and Loyola, Diego
Subjects: troposphere, TROPOMI, NO2, Air Quality
Abstract: Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.
Published: 2021

15. Supplementary material to "Combined UV and IR ozone profile retrieval from TROPOMI and CrIS measurements"

Author: Mettig, Nora, primary, Weber, Mark, additional, Rozanov, Alexei, additional, Burrows, John P., additional, Veefkind, Pepijn, additional, Smith, Nadia, additional, Thompson, Anne M., additional, Stauffer, Ryan M., additional, Leblanc, Thierry, additional, Kivi, Rigel, additional, Tully, Matthew B., additional, Van Malderen, Roeland, additional, Piters, Ankie, additional, Kois, Bogumil, additional, Stübi, René, additional, and Skrivankova, Pavla, additional
Published: 2021
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16. Combined UV and IR ozone profile retrieval from TROPOMI and CrIS measurements

Author: Mettig, Nora, primary, Weber, Mark, additional, Rozanov, Alexei, additional, Burrows, John P., additional, Veefkind, Pepijn, additional, Smith, Nadia, additional, Thompson, Anne M., additional, Stauffer, Ryan M., additional, Leblanc, Thierry, additional, Kivi, Rigel, additional, Tully, Matthew B., additional, Van Malderen, Roeland, additional, Piters, Ankie, additional, Kois, Bogumil, additional, Stübi, René, additional, and Skrivankova, Pavla, additional
Published: 2021
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17. TROPOMI tropospheric ozone column data: geophysical assessment and comparison to ozonesondes, GOME-2B and OMI

Author: Hubert, Daan, primary, Heue, Klaus-Peter, additional, Lambert, Jean-Christopher, additional, Verhoelst, Tijl, additional, Allaart, Marc, additional, Compernolle, Steven, additional, Cullis, Patrick D., additional, Dehn, Angelika, additional, Félix, Christian, additional, Johnson, Bryan J., additional, Keppens, Arno, additional, Kollonige, Debra E., additional, Lerot, Christophe, additional, Loyola, Diego, additional, Maata, Matakite, additional, Mitro, Sukarni, additional, Mohamad, Maznorizan, additional, Piters, Ankie, additional, Romahn, Fabian, additional, Selkirk, Henry B., additional, da Silva, Francisco R., additional, Stauffer, Ryan M., additional, Thompson, Anne M., additional, Veefkind, J. Pepijn, additional, Vömel, Holger, additional, Witte, Jacquelyn C., additional, and Zehner, Claus, additional
Published: 2021
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18. An improved TROPOMI tropospheric NO2 research product over Europe

Author: Liu, Song, primary, Valks, Pieter, additional, Pinardi, Gaia, additional, Xu, Jian, additional, Chan, Ka Lok, additional, Argyrouli, Athina, additional, Lutz, Ronny, additional, Beirle, Steffen, additional, Khorsandi, Ehsan, additional, Baier, Frank, additional, Huijnen, Vincent, additional, Bais, Alkiviadis, additional, Donner, Sebastian, additional, Dörner, Steffen, additional, Gratsea, Myrto, additional, Hendrick, François, additional, Karagkiozidis, Dimitris, additional, Lange, Kezia, additional, Piters, Ankie J. M., additional, Remmers, Julia, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, Wagner, Thomas, additional, Wenig, Mark, additional, and Loyola, Diego G., additional
Published: 2021
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19. Global Ozone Monitoring Experiment-2 (GOME-2) Daily and Monthly Level 3 Products of Atmospheric Trace Gas Columns.

Author: Ka Lok Chan, Valks, Pieter, Heue, Klaus-Peter, Lutz, Ronny, Hedelt, Pascal, Loyola, Diego, Pinardi, Gaia, Van Roozendael, Michel, Hendrick, François, Wagner, Thomas, Kumar, Vinod, Bais, Alkis, Piters, Ankie, Hitoshi Irie, Hisahiro Takashima, Yugo Kanaya, Yongjoo Choi, Kihong Park, Jihyo Chong, and Cede, Alexander
Subjects: COLUMNS, TRACE gases, OZONE, WATER vapor, NITROGEN dioxide, TROPOSPHERIC ozone, AIR pollutants
Abstract: We introduce the new GOME-2 daily and monthly level 3 product of total column ozone (O3), total and tropospheric column nitrogen dioxide (NO2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO) and total column sulphur dioxide (SO2). The GOME-2 level 3 products are aimed to provide easily translatable and userfriendly data sets to the scientific community for scientific progress as well as satisfying public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level 3 products. The GOME-2 level 3 products are produced using the overlapping area weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level 3 products is selected based on sensitivity study. The consistency of the resulting level 3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparing to ground-based observations. The verification and validation results show that the GOME-2 level 3 products are consistent with the level 2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in instrument characteristic and level 2 processor. The comparison of GOME-2 level 3 products to ground-based observations in general shows very good agreement, indicating the products are consistent and fulfil the requirements to serve the scientific community and general public. [ABSTRACT FROM AUTHOR]
Published: 2022
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20. Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements

Author: De Smedt, Isabelle, primary, Pinardi, Gaia, additional, Vigouroux, Corinne, additional, Compernolle, Steven, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Boersma, Folkert, additional, Chan, Ka-Lok, additional, Donner, Sebastian, additional, Eichmann, Kai-Uwe, additional, Hedelt, Pascal, additional, Hendrick, François, additional, Irie, Hitoshi, additional, Kumar, Vinod, additional, Lambert, Jean-Christopher, additional, Langerock, Bavo, additional, Lerot, Christophe, additional, Liu, Cheng, additional, Loyola, Diego, additional, Piters, Ankie, additional, Richter, Andreas, additional, Rivera Cárdenas, Claudia, additional, Romahn, Fabian, additional, Ryan, Robert George, additional, Sinha, Vinayak, additional, Theys, Nicolas, additional, Vlietinck, Jonas, additional, Wagner, Thomas, additional, Wang, Ting, additional, Yu, Huan, additional, and Van Roozendael, Michel, additional
Published: 2021
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21. An improved tropospheric NO2 column retrieval algorithm for TROPOMI over Europe

Author: Liu, Song, Valks, Pieter, Pinardi, Gaia, Xu, Jian, Chan, Ka Lok, Argyrouli, Athina, Lutz, Ronny, Beirle, Steffen, Khorsandi, Ehsan, Baier, Frank, Huijnen, Vincent, Bais, Alkiviadis, Donner, Sebastian, Dörner, Steffen, Gratsea, Myrto, Hendrick, François, Karagkiozidis, Dimitris, Lange, Kezia, Piters, Ankie J. M., Remmers, Julia, Richter, Andreas, Roozendael, Michel, Wagner, Thomas, Wenig, Mark, and Loyola, Diego G.
Abstract: Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2 × 1014 molec/cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5 × 1014 molec/cm2 for polluted conditions. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes are captured. For AMF calculation, the climatological surface albedo data is replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a clouds-as-layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the clouds-as-reflecting-boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the improved tropospheric NO2 data shows good correlations for nine European urban/suburban stations with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average.
Published: 2021

22. Comparative assessment of TROPOMI and OMI formaldehyde observations against MAX-DOAS network column measurements

Author: De Smedt, Isabelle, primary, Pinardi, Gaia, additional, Vigouroux, Corinne, additional, Compernolle, Steven, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Boersma, Folkert, additional, Chan, Ka-Lok, additional, Donner, Sebastian, additional, Eichmann, Kai-Uwe, additional, Hedelt, Pascal, additional, Hendrick, François, additional, Irie, Hitoshi, additional, Kumar, Vinod, additional, Lambert, Jean-Christopher, additional, Langerock, Bavo, additional, Lerot, Christophe, additional, Liu, Cheng, additional, Loyola, Diego, additional, Piters, Ankie, additional, Richter, Andreas, additional, Rivera Cárdenas, Claudia Inés, additional, Romahn, Fabian, additional, Ryan, Robert George, additional, Sinha, Vinayak, additional, Theys, Nicolas, additional, Vlietinck, Jonas, additional, Wagner, Thomas, additional, Wang, Ting, additional, Yu, Huan, additional, and Van Roozendael, Michel, additional
Published: 2021
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23. Supplementary material to "Comparative assessment of TROPOMI and OMI formaldehyde observations against MAX-DOAS network column measurements"

Author: De Smedt, Isabelle, primary, Pinardi, Gaia, additional, Vigouroux, Corinne, additional, Compernolle, Steven, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Boersma, Folkert, additional, Chan, Ka-Lok, additional, Donner, Sebastian, additional, Eichmann, Kai-Uwe, additional, Hedelt, Pascal, additional, Hendrick, François, additional, Irie, Hitoshi, additional, Kumar, Vinod, additional, Lambert, Jean-Christopher, additional, Langerock, Bavo, additional, Lerot, Christophe, additional, Liu, Cheng, additional, Loyola, Diego, additional, Piters, Ankie, additional, Richter, Andreas, additional, Rivera Cárdenas, Claudia Inés, additional, Romahn, Fabian, additional, Ryan, Robert George, additional, Sinha, Vinayak, additional, Theys, Nicolas, additional, Vlietinck, Jonas, additional, Wagner, Thomas, additional, Wang, Ting, additional, Yu, Huan, additional, and Van Roozendael, Michel, additional
Published: 2021
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24. An improved TROPOMI tropospheric NO2 research product over Europe

Author: Liu, Song, Valks, Pieter, Pinardi, Gaia, Xu, Jian, Chan, Ka Lok, Argyrouli, Athina, Lutz, Ronny, Beirle, Steffen, Khorsandi, Ehsan, Baier, Frank, Huijnen, Vincent, Bais, Alkiviadis, Donner, Sebastian, Dörner, Steffen, Gratsea, Myrto, Hendrick, François, Karagkiozidis, Dimitris, Lange, Kezia, Piters, Ankie J. M., Remmers, Julia, Richter, Andreas, Van Roozendael, Michel, Wagner, Thomas, Wenig, Mark, and Loyola, Diego G.
Subjects: ddc
Published: 2020

25. Supplementary material to "An improved tropospheric NO2 column retrieval algorithm for TROPOMI over Europe"

Author: Liu, Song, primary, Valks, Pieter, additional, Pinardi, Gaia, additional, Xu, Jian, additional, Chan, Ka Lok, additional, Argyrouli, Athina, additional, Lutz, Ronny, additional, Beirle, Steffen, additional, Khorsandi, Ehsan, additional, Baier, Frank, additional, Huijnen, Vincent, additional, Bais, Alkiviadis, additional, Donner, Sebastian, additional, Dörner, Steffen, additional, Gratsea, Myrto, additional, Hendrick, François, additional, Karagkiozidis, Dimitris, additional, Lange, Kezia, additional, Piters, Ankie J. M., additional, Remmers, Julia, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, Wagner, Thomas, additional, Wenig, Mark, additional, and Loyola, Diego G., additional
Published: 2021
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26. An improved tropospheric NO2 column retrieval algorithm for TROPOMI over Europe

Author: Liu, Song, primary, Valks, Pieter, additional, Pinardi, Gaia, additional, Xu, Jian, additional, Chan, Ka Lok, additional, Argyrouli, Athina, additional, Lutz, Ronny, additional, Beirle, Steffen, additional, Khorsandi, Ehsan, additional, Baier, Frank, additional, Huijnen, Vincent, additional, Bais, Alkiviadis, additional, Donner, Sebastian, additional, Dörner, Steffen, additional, Gratsea, Myrto, additional, Hendrick, François, additional, Karagkiozidis, Dimitris, additional, Lange, Kezia, additional, Piters, Ankie J. M., additional, Remmers, Julia, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, Wagner, Thomas, additional, Wenig, Mark, additional, and Loyola, Diego G., additional
Published: 2021
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27. COVID‐19 Crisis Reduces Free Tropospheric Ozone Across the Northern Hemisphere

Author: Steinbrecht, Wolfgang, primary, Kubistin, Dagmar, additional, Plass‐Dülmer, Christian, additional, Davies, Jonathan, additional, Tarasick, David W., additional, von der Gathen, Peter, additional, Deckelmann, Holger, additional, Jepsen, Nis, additional, Kivi, Rigel, additional, Lyall, Norrie, additional, Palm, Matthias, additional, Notholt, Justus, additional, Kois, Bogumil, additional, Oelsner, Peter, additional, Allaart, Marc, additional, Piters, Ankie, additional, Gill, Michael, additional, Van Malderen, Roeland, additional, Delcloo, Andy W., additional, Sussmann, Ralf, additional, Mahieu, Emmanuel, additional, Servais, Christian, additional, Romanens, Gonzague, additional, Stübi, Rene, additional, Ancellet, Gerard, additional, Godin‐Beekmann, Sophie, additional, Yamanouchi, Shoma, additional, Strong, Kimberly, additional, Johnson, Bryan, additional, Cullis, Patrick, additional, Petropavlovskikh, Irina, additional, Hannigan, James W., additional, Hernandez, Jose‐Luis, additional, Diaz Rodriguez, Ana, additional, Nakano, Tatsumi, additional, Chouza, Fernando, additional, Leblanc, Thierry, additional, Torres, Carlos, additional, Garcia, Omaira, additional, Röhling, Amelie N., additional, Schneider, Matthias, additional, Blumenstock, Thomas, additional, Tully, Matt, additional, Paton‐Walsh, Clare, additional, Jones, Nicholas, additional, Querel, Richard, additional, Strahan, Susan, additional, Stauffer, Ryan M., additional, Thompson, Anne M., additional, Inness, Antje, additional, Engelen, Richard, additional, Chang, Kai‐Lan, additional, and Cooper, Owen R., additional
Published: 2021
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28. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign

Author: Tirpitz, Jan-Lukas, primary, Frieß, Udo, additional, Hendrick, François, additional, Alberti, Carlos, additional, Allaart, Marc, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Berkhout, Stijn, additional, Bognar, Kristof, additional, Bösch, Tim, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, den Hoed, Mirjam, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Frumau, Arnoud, additional, Gast, Lou, additional, Gielen, Clio, additional, Gomez-Martín, Laura, additional, Hao, Nan, additional, Hensen, Arjan, additional, Henzing, Bas, additional, Hermans, Christian, additional, Jin, Junli, additional, Kreher, Karin, additional, Kuhn, Jonas, additional, Lampel, Johannes, additional, Li, Ang, additional, Liu, Cheng, additional, Liu, Haoran, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Puentedura, Olga, additional, Richter, Andreas, additional, Schmitt, Stefan, additional, Spinei, Elena, additional, Stein Zweers, Deborah, additional, Strong, Kimberly, additional, Swart, Daan, additional, Tack, Frederik, additional, Tiefengraber, Martin, additional, van der Hoff, René, additional, van Roozendael, Michel, additional, Vlemmix, Tim, additional, Vonk, Jan, additional, Wagner, Thomas, additional, Wang, Yang, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wiegner, Matthias, additional, Wittrock, Folkard, additional, Xie, Pinhua, additional, Xing, Chengzhi, additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional
Published: 2021
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29. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author: Verhoelst, Tiji, Compernolle, Steven, Pinardi, Gala, Lambert, Jean-Christopher, Eskes, Henk J., Eichmann, Kai-Uwe, Fjæraa, Ann Mari, Granville, José, Niemeijer, Sander, Cede, Alexander, Tiefengraber, Martin, Hendrick, François, Pazmino, Andrea, Bais, Alkiviadis, Bazureau, Ariane, Boersma, Klaas Folkert, Bognar, Kristof, Dehn, Angelika, Donner, Sebastian, Elokhov, Aleksandr, Gebetsberger, Manuel, Goutail, Florence, Grutter de la Mora, Michel, Gruzdev, Aleksandr, Gratsea, Myrto, Hansen, Georg, Irie, Hitoshi, Jepsen, Nis, Kanaya, Yugo, Karagkiozidis, Dimitris, Kivi, Rigel, Kreher, Karin, Levelt, Pieternel F., Liu, Cheng, Müller, Moritz, Navarro-Comas, Monica, Piters, Ankie J. M., Pommereau, Jean-Pierre, Portafaix, Thierry, Puentedura, Olga, Querel, Richard, Remmers, Julia, Richter, Andreas, Rimmer, John, Rivera Cárdenas, Claudia, Saavedra De Miguel, Lidia, Sinyakov, Valery P., Strong, Kimberley, Van Roozendaël, Michel, Veefkind, Pepijn J., Wagner, Thomas, Wittrock, Folkard, Yela-González, Margarita, Zehner, Claus, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Royal Netherlands Meteorological Institute (KNMI), Institut für Umweltphysik [Bremen] (IUP), Universität Bremen, Norsk Institutt for Luftforskning (NILU), Science [&] Technology Corporation [Delft] (S [&] T), NASA Goddard Space Flight Center (GSFC), Institute of Meteorology and Geophysics [Innsbruck], University of Innsbruck, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Department of Physics [Toronto], University of Toronto, European Space Research Institute (ESRIN), European Space Agency (ESA), Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Centro de Ciencias de la Atmosfera [Mexico], Universidad Nacional Autónoma de México (UNAM), National Observatory of Athens (NOA), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Danish Meteorological Institute (DMI), Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Space and Earth Observation Centre [Sodankylä], Finnish Meteorological Institute (FMI), BK Scientific GmbH, Delft University of Technology (TU Delft), Department of Precision Machinery and Precision Instrumentation [Hefei], University of Science and Technology of China [Hefei] (USTC), Instituto Nacional de Técnica Aeroespacial (INTA), Laboratoire de l'Atmosphère et des Cyclones (LACy), Météo France-Université de La Réunion (UR)-Centre National de la Recherche Scientifique (CNRS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), University of Manchester [Manchester], Kyrgyz National University, Institute of Environmental Physics [Bremen] (IUP), and University of Bremen
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere
Abstract: This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.
Published: 2020

30. Intercomparison of NO2, O-4, O-3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-visible spectrometers during CINDI-2

Author: Kreher, Karin, Van Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Friess, Udo, Richter, Andreas, Wagner, Thomas, Lampel, Johannes, Abuhassan, Nader, Ang, Li, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Boesch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka Lok, Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, Garcia-Nieto, David, Gielen, Clio, Gomez-Martin, Laura, Hao, Nan, Henzing, Bas, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Irie, Hitoshi, Jin, Junli, Johnston, Paul, Butt, Junaid Khayyam, Khokhar, Fahim, Koenig, Theodore K., Kuhn, Jonas, Kumar, Vinod, Liu, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, Abhishek K., Mueller, Moritz, Navarro-Comas, Monica, Ostendorf, Mareike, Pazmino, Andrea, Peters, Enno, Pinardi, Gaia, Pinharanda, Manuel, Piters, Ankie, Platt, Ulrich, Postylyakov, Oleg, Prados-Roman, Cristina, Puentedura, Olga, Querel, Richard, Saiz-Lopez, Alfonso, Schoenhardt, Anja, Schreier, Stefan F., Seyler, Andre, Sinha, Vinayak, Spinei, Elena, Strong, Kimberly, Tack, Frederik, Tian, Xin, Tiefengraber, Martin, Tirpitz, Jan-Lukas, van Gent, Jeron, Volkamer, Rainer, Vrekoussis, Mihalis, Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, Folkard, Xie, Pinhua H., Xu, Jin, Yela, Margarita, Zhang, Chengxin, Zhao, Xiaoyi, BK Scientific GmbH, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Royal Netherlands Meteorological Institute (KNMI), Institut für Umweltphysik [Heidelberg], Universität Heidelberg [Heidelberg], Institute of Environmental Physics [Bremen] (IUP), University of Bremen, Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, NASA Goddard Space Flight Center (GSFC), Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences [Changchun Branch] (CAS), Instituto de Química Física Rocasolano (IQFR), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Department of Physics [Toronto], University of Toronto, A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Belarusian State University, Meteorologisches Institut München (MIM), Ludwig-Maximilians-Universität München (LMU), School of Earth and Space Sciences [Hefei], University of Science and Technology of China [Hefei] (USTC), Department of Chemistry and Biochemistry [Boulder], University of Colorado [Boulder], Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), Instituto Nacional de Técnica Aeroespacial (INTA), European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), The Netherlands Organisation for Applied Scientific Research (TNO), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Chinese Academy of Meteorological Sciences (CAMS), National Institute of Water and Atmospheric Research [Lauder] (NIWA), National University of Sciences and Technology [Islamabad] (NUST), Institute of Environmental Physics [Heidelberg] (IUP), Indian Institute of Science Education and Research Mohali (IISER Mohali), Department of Earth and Environmental Sciences [Mohali], Department of Atmospheric and Cryospheric Sciences [Innsbruck] (ACINN), Universität Innsbruck [Innsbruck], STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Institute for the Protection of Maritime Infrastructures, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institute for Meteorology and Climatology [Vienna] (BOKU-Met), University of Natural Resources and Life Sciences (BOKU), Virginia Polytechnic Institute and State University [Blacksburg], Center for Marine Environmental Sciences [Bremen] (MARUM), Universität Bremen, Energy, Environment and Water Research Center (EEWRC), Cyprus Institute (CyI), Liaoning Technical University [Huludao], Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University [Shanghai], DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute (IMF), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Environment and Climate Change Canada, and Electrical and Computer Engineering
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Science & Technology, RAMAN-SCATTERING, RETRIEVAL, CROSS-SECTIONS, BRO, RADIATIVE-TRANSFER, Physical Sciences, Meteorology & Atmospheric Sciences, OPTICAL-ABSORPTION SPECTROSCOPY, FORMALDEHYDE, CAMPAIGN, NITROGEN-DIOXIDE, AEROSOL EXTINCTION
Abstract: 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 degrees N, 4.93 degrees 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 (O-4) and ozone (O-3) 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. Netherlands Space Office (NSO); ESA through the CINDI-2 (ESA) project [4000118533/16/I-Sbo]; ESA through the FRM4DOAS (ESA) project [4000118181/16/I-EF]; EU 7th Framework Programme QA4ECV projectEuropean Union (EU) [607405]; Austrian Science Fund (FWF)Austrian Science Fund (FWF) [I 2296-N29]; Canadian Space Agency (AVATARS project); Natural Sciences and Engineering Research Council (PAHA project); Canada Foundation for InnovationCanada Foundation for Innovation; UVAS ("Ultraviolet and Visible Atmospheric Sounder") projects SEOSAT/INGENIO [ESP2015-71299-R]; DFG project RAPSODI [PL 193/17-1]; Centre National de la Recherche Scientifique (CNRS)Centre National de la Recherche Scientifique (CNRS); Centre National d'Etudes Spatiales (CNES)Centre National D'etudes Spatiales; National funding project HELADO [CTM2013-41311-P]; National funding project AVATAR [CGL2014-55230-R]; Russian Science FoundationRussian Science Foundation (RSF) [16-17-10275]; Russian Foundation for Basic ResearchRussian Foundation for Basic Research (RFBR) [16-05-01062, 18-35-00682]; ACTRIS-2 (H2020 grant) [654109]; NASA's Atmospheric Composition ProgramNational Aeronautics & Space Administration (NASA) [NASA-16-NUP2016-0001]; US National Science FoundationNational Science Foundation (NSF) [AGS-1620530]; NASANational Aeronautics & Space Administration (NASA); University of Bremen; DFG Research Center/Cluster of Excellence "The Ocean in the Earth System-MARUM"German Research Foundation (DFG); University of Bremen Institutional Strategy of the DFG; Luftblick through the ESA Pandonia Project; NASA Pandora Project at the Goddard Space Flight Center under NASA Headquarters' Tropospheric Composition Program CINDI-2 received funding from the Netherlands Space Office (NSO). Funding for this study was provided by ESA through the CINDI-2 (ESA contract no. 4000118533/16/I-Sbo) and FRM4DOAS (ESA contract no. 4000118181/16/I-EF) projects and partly within the EU 7th Framework Programme QA4ECV project (grant agreement no. 607405). The BOKU MAX-DOAS instrument was funded and the participation of Stefan F. Schreier was supported by the Austrian Science Fund (FWF): I 2296-N29. The participation of the University of Toronto team was supported by the Canadian Space Agency (through the AVATARS project) and the Natural Sciences and Engineering Research Council (through the PAHA project). The instrument was primarily funded by the Canada Foundation for Innovation and is usually operated at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC). Funding for CISC was provided by the UVAS ("Ultraviolet and Visible Atmospheric Sounder") projects SEOSAT/INGENIO, ESP2015-71299-R, MINECO-FEDER and UE. The activities of the IUP-Heidelberg were supported by the DFG project RAPSODI (grant no. PL 193/17-1). SAOZ and Mini-SAOZ instruments are supported by the Centre National de la Recherche Scientifique (CNRS) and the Centre National d'Etudes Spatiales (CNES). INTA recognises support from the National funding projects HELADO (CTM2013-41311-P) and AVATAR (CGL2014-55230-R). AMOIAP recognises support from the Russian Science Foundation (grant no. 16-17-10275) and the Russian Foundation for Basic Research (grant nos. 16-05-01062 and 18-35-00682). Ka L. Chan received transnational access funding from ACTRIS-2 (H2020 grant agreement no. 654109). Rainer Volkamer recognises funding from NASA's Atmospheric Composition Program (NASA-16-NUP2016-0001) and the US National Science Foundation (award AGS-1620530). Henning Finkenzeller is the recipient of a NASA graduate fellowship. Mihalis Vrekoussis recognises support from the University of Bremen and the DFG Research Center/Cluster of Excellence "The Ocean in the Earth System-MARUM". Financial support through the University of Bremen Institutional Strategy in the framework of the DFG Excellence Initiative is gratefully appreciated for Anja Schonhardt. Pandora instrument deployment was supported by Luftblick through the ESA Pandonia Project and NASA Pandora Project at the Goddard Space Flight Center under NASA Headquarters' Tropospheric Composition Program. The article processing charges for this open-access publication were covered by BK Scientific.
Published: 2020

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

Author: Kreher, Karin, Roozendael, Michel van, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Frieß, Udo, Richter, Andreas, Wagner, Thomas, Lampel, Johannes, Abuhassan, Nader, Ang, Li, Anguas, Mónica, Bais, Alkis, Benavent, N., Bösch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Lok Chan, Ka, Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, García-Nieto, D., Gielen, Clio, Gómez-Martín, L., Hao, Nan, Henzing, Bas, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Iri, Hitoshi, Jin, Junli, Johnsto, Paul, Khayyam But, Junaid, Khokhar, Fahim, Koenig, T.K., Kuhn, Jonas, Kumar, Vinod, Li, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, A.K., Müller, Moritz, Navarro-Comas, M., Ostendorf, M., Pazmin, Andrea, Peters, Enno, Pinardi, Gaia, Pinharanda, M., Piters, Ankie, Platt, Ulrich, Postylyakov, Oleg, Prados-Roman, C., Puentedura, Olga, Querel, Richard, Saiz-Lopez, A., Schönhardt, A., Schreier, S.F., Seyler, André, Sinha, V., Spinei, Elena, Strong, K., Tack, F., Tian, Xin, Tiefengraber, M., Tirpitz, J.-L., Gent, J. van, Volkamer, R., Vrekoussis, M., Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, F., Xie, P.H., Xu, Jin, Yela, M., Zhang, Chengxin, Zhao, Xiaoyi, Netherlands Space Office, European Space Agency, European Commission, Austrian Science Fund, University of Toronto, Canadian Space Agency, Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, Consejo Superior de Investigaciones Científicas (España), Ministerio de Economía y Competitividad (España), German Research Foundation, Centre National de la Recherche Scientifique (France), Centre National D'Etudes Spatiales (France), Russian Science Foundation, Russian Foundation for Basic Research, National Aeronautics and Space Administration (US), National Science Foundation (US), University of Bremen, and NASA's Goddard Space Flight Center
Abstract: 40 pags., 22 figs., 13 tabs., 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., CINDI-2 received funding from the Netherlands Space Office (NSO). Funding for this study was provided by ESA through the CINDI-2 (ESA contract no. 4000118533/16/ISbo) and FRM4DOAS (ESA contract no. 4000118181/16/I-EF) projects and partly within the EU 7th Framework Programme QA4ECV project (grant agreement no. 607405). The BOKU MAX-DOAS instrument was funded and the participation of Stefan F. Schreier was supported by the Austrian Science Fund (FWF): I 2296-N29. The participation of the University of Toronto team was supported by the Canadian Space Agency (through the AVATARS project) and the Natural Sciences and Engineering Research Council (through the PAHA project). The instrument was primarily funded by the Canada Foundation for Innovation and is usually operated at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC). Funding for CISC was provided by the UVAS (“Ultraviolet and Visible Atmospheric Sounder”) projects SEOSAT/INGENIO, ESP2015-71299- R, MINECO-FEDER and UE. The activities of the IUP-Heidelberg were supported by the DFG project RAPSODI (grant no. PL 193/17-1). SAOZ and Mini-SAOZ instruments are supported by the Centre National de la Recherche Scientifique (CNRS) and the Centre National d’Etudes Spatiales (CNES). INTA recognises support from the National funding projects HELADO (CTM2013-41311-P) and AVATAR (CGL2014-55230-R). AMOIAP recognises support from the Russian Science Foundation (grant no. 16-17-10275) and the Russian Foundation for Basic Research (grant nos. 16-05- 01062 and 18-35-00682). Ka L. Chan received transnational access funding from ACTRIS-2 (H2020 grant agreement no. 654109). Rainer Volkamer recognises funding from NASA’s Atmospheric Composition Program (NASA-16-NUP2016-0001) and the US National Science Foundation (award AGS-1620530). Henning Finkenzeller is the recipient of a NASA graduate fellowship. Mihalis Vrekoussis recognises support from the University of Bremen and the DFG Research Center/Cluster of Excellence “The Ocean in the Earth System-MARUM”. Financial support through the University of Bremen Institutional Strategy in the framework of the DFG Excellence Initiative is gratefully appreciated for Anja Schönhardt. Pandora instrument deployment was supported by Luftblick through the ESA Pandonia Project and NASA Pandora Project at the Goddard Space Flight Center under NASA Headquarters’ Tropospheric Composition Program. The article processing charges for this open-access publication were covered by BK Scientific.
Published: 2020

32. Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations

Author: Pinardi, Gaia, Roozendael, Michel, Hendrick, François, Theys, Nicolas, Abuhassan, Nader, Bais, Alkiviadis, Boersma, Folkert, Cede, Alexander, Chong, Jihyo, Donner, Sebastian, Drosoglou, Theano, Frieß, Udo, Granville, José, Herman, Jay R., Eskes, Henk, Holla, Robert, Hovila, Jari, Irie, Hitoshi, Kanaya, Yugo, Karagkiozidis, Dimitris, Kouremeti, Natalia, Lambert, Jean-Christopher, Ma, Jianzhong, Peters, Enno, Piters, Ankie, Postylyakov, Oleg, Richter, Andreas, Remmers, Julia, Takashima, Hisahiro, Tiefengraber, Martin, Valks, Pieter, Vlemmix, Tim, Wagner, Thomas, and Wittrock, Folkard
Abstract: MAX-DOAS and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOP-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results, as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −36 % for GOME-2A and −20 % for OMI. These biases are further reduced to −24 % and −8 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI is also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements.
Published: 2020

33. Validation of Aura-OMI QA4ECV NO2 climate data records with ground-based DOAS networks : The role of measurement and comparison uncertainties

Author: Compernolle, Steven, Verhoelst, Tijl, Pinardi, Gaia, Granville, Jose, Hubert, Daan, Keppens, Arno, Niemeijer, Sander, Rino, Bruno, Bais, Alkis, Beirle, Steffen, Boersma, Folkert, Burrows, John P., De Smedt, Isabelle, Eskes, Henk, Goutail, Florence, Hendrick, Francois, Lorente, Alba, Pazmino, Andrea, Piters, Ankie, Peters, Enno, Pommereau, Jean Pierre, Remmers, Julia, Richter, Andreas, Van Geffen, Jos, Van Roozendael, Michel, Wagner, Thomas, Lambert, Jean Christopher, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), Science [&] Technology Corporation [Delft] (S [&] T), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Max-Planck-Institut für Chemie (MPIC), Max-Planck-Gesellschaft, Royal Netherlands Meteorological Institute (KNMI), Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Institute of Environmental Physics [Bremen] (IUP), University of Bremen, STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), and Max Planck Institute for Chemistry (MPIC)
Subjects: [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Meteorologie en Luchtkwaliteit, WIMEK, Meteorology and Air Quality, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Life Science
Abstract: The QA4ECV (Quality Assurance for Essential Climate Variables) version 1.1 stratospheric and tropospheric NO2 vertical column density (VCD) climate data records (CDRs) from the OMI (Ozone Monitoring Instrument) satellite sensor are validated using NDACC (Network for the Detection of Atmospheric Composition Change) zenithscattered light differential optical absorption spectroscopy (ZSL-DOAS) and multi-axis DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCDs have a small bias of 0:2 Pmolec:cm-2 (5 % 10 %) and a dispersion of 0.2 to 1 Pmolec:cm-2 with respect to the ZSLDOAS measurements. QA4ECV tropospheric VCD observations from OMI are restricted to near-cloud-free scenes, leading to a negative sampling bias (with respect to the unrestricted scene ensemble) of a few peta molecules per square centimetre (Pmolec:cm-2) up to -10 Pmolec:cm-2 (-40 %) in one extreme high-pollution case. The QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (-1 to -4 Pmolec:cm-2), which is a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite measurements and ground-based data greatly exceed the combined measurement uncertainties. Depending on the site, part of the discrepancy can be attributed to a combination of comparison errors (notably horizontal smoothing difference error), measurement/retrieval errors related to clouds and aerosols, and the difference in vertical smoothing and a priori profile assumptions.
Published: 2020

34. Did the COVID-19 Crisis Reduce Free Tropospheric Ozone across the Northern Hemisphere?

Author: Steinbrecht, Wolfgang, primary, Kubistin, Dagmar, additional, Plass-Dulmer, Christian, additional, Tarasick, David W., additional, Davies, Jonathan, additional, von der Gathen, Peter, additional, Deckelmann, Holger, additional, Jepsen, Nis, additional, Kivi, Rigel, additional, Lyall, Norrie, additional, Palm, Mathias, additional, Notholt, Justus, additional, Kois, Bogumil, additional, Oelsner, Peter, additional, Allaart, Marc, additional, Piters, Ankie, additional, Gill, Michael, additional, Van Malderen, Roeland, additional, Delcloo, Andy, additional, Sussmann, Ralf, additional, Servais, Christian, additional, Mahieu, Emmanuel, additional, Romanens, Gonzague, additional, Stübi, René, additional, Ancellet, Gerard, additional, Godin-Beekmann, Sophie, additional, Yamanouchi, Shoma, additional, Strong, Kimberly, additional, Johnson, Bryan J. J., additional, Cullis, Patrick, additional, Petropavlovskikh, Irina, additional, Hannigan, James W, additional, Hernandez, Jose-Luis, additional, Rodriguez, Ana Diaz, additional, Nakano, Tatsumi, additional, Leblanc, Thierry, additional, Chouza, Fernando, additional, Torres, Carlos, additional, García, Omaira, additional, Röhling, Amelie, additional, Schneider, Matthias, additional, Blumenstock, Thomas, additional, Tully, Matthew Brian, additional, Paton-Walsh, Clare, additional, Jones, Nicholas Brian, additional, Querel, Richard, additional, Strahan, Susan E, additional, Inness, Antje, additional, Engelen, Richard J., additional, Chang, Kai-Lan, additional, Cooper, Owen R. R., additional, Stauffer, Ryan Michael, additional, and Thompson, Anne M., additional
Published: 2020
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35. Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations

Author: Pinardi, Gaia, primary, Van Roozendael, Michel, additional, Hendrick, François, additional, Theys, Nicolas, additional, Abuhassan, Nader, additional, Bais, Alkiviadis, additional, Boersma, Folkert, additional, Cede, Alexander, additional, Chong, Jihyo, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Dzhola, Anatoly, additional, Eskes, Henk, additional, Frieß, Udo, additional, Granville, José, additional, Herman, Jay R., additional, Holla, Robert, additional, Hovila, Jari, additional, Irie, Hitoshi, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kouremeti, Natalia, additional, Lambert, Jean-Christopher, additional, Ma, Jianzhong, additional, Peters, Enno, additional, Piters, Ankie, additional, Postylyakov, Oleg, additional, Richter, Andreas, additional, Remmers, Julia, additional, Takashima, Hisahiro, additional, Tiefengraber, Martin, additional, Valks, Pieter, additional, Vlemmix, Tim, additional, Wagner, Thomas, additional, and Wittrock, Folkard, additional
Published: 2020
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36. Data Quality and Validation of Satellite Measurements of Tropospheric Composition

Author: Piters, Ankie J. M., primary, Buchmann, Brigitte, additional, Brunner, Dominik, additional, Cohen, Ronald C., additional, Lambert, Jean-Christopher, additional, de Leeuw, Gerrit, additional, Stammes, Piet, additional, van Weele, Michiel, additional, and Wittrock, Folkard, additional
Published: 2010
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37. Measurement Report: Tropospheric and Stratospheric Ozone Profiles during the 2019 TROpomi vaLIdation eXperiment (TROLIX-19).

Author: Sullivan, John T., Apituley, Arnoud, Mettig, Nora, Kreher, Karin, Knowland, K. Emma, Allaart, Marc, Piters, Ankie, Roozendael, Michel Van, Veefkind, Pepijn, Ziemke, Jerry R., Kramarova, Natalya, Weber, Mark, Rozanov, Alexei, Twigg, Laurence, Sumnicht, Grant, and McGee, Thomas J.
Abstract: A TROPOspheric Monitoring Instrument (TROPOMI) validation campaign was held in the Netherlands based at the CESAR (Cabauw Experimental Site for Atmospheric Research) Observatory during September 2019. The TROpomi vaLIdation eXperiment (TROLIX-19) consisted of active and passive remote sensing platforms in conjunction with several balloon-borne and surface chemical (e.g. ozone and nitrogen dioxide) measurements. The goal of this joint NASA-KNMI geophysical validation campaign was to make intensive observations in the TROPOMI domain in order to be able to establish the quality of the L2 satellite data products under realistic conditions, such as non-idealized conditions with varying cloud cover and a range of atmospheric conditions at a rural site. The research presented here focuses on using ozone lidars from NASA’s Goddard Space Flight Center to better evaluate the characterization of ozone throughout TROLIX-19. Results of comparisons to the lidar systems with balloon, space-borne, and ground-based passive measurements are shown. In addition, results are compared to a global coupled chemistry meteorology model to illustrate the vertical variability and columnar amounts of both tropospheric and stratospheric ozone during the campaign period. [ABSTRACT FROM AUTHOR]
Published: 2022
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38. Supplementary material to "TROPOMI tropospheric ozone column data: Geophysical assessment and comparison to ozonesondes, GOME-2B and OMI"

Author: Hubert, Daan, primary, Heue, Klaus-Peter, additional, Lambert, Jean-Christopher, additional, Verhoelst, Tijl, additional, Allaart, Marc, additional, Compernolle, Steven, additional, Cullis, Patrick D., additional, Dehn, Angelika, additional, Félix, Christian, additional, Johnson, Bryan J., additional, Keppens, Arno, additional, Kollonige, Debra E., additional, Lerot, Christophe, additional, Loyola, Diego, additional, Maata, Matakite, additional, Mitro, Sukarni, additional, Mohamad, Maznorizan, additional, Piters, Ankie, additional, Romahn, Fabian, additional, Selkirk, Henry B., additional, da Silva, Francisco R., additional, Stauffer, Ryan M., additional, Thompson, Anne M., additional, Veefkind, J. Pepijn, additional, Vömel, Holger, additional, Witte, Jacquelyn C., additional, and Zehner, Claus, additional
Published: 2020
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39. TROPOMI tropospheric ozone column data: Geophysical assessment and comparison to ozonesondes, GOME-2B and OMI

Author: Hubert, Daan, primary, Heue, Klaus-Peter, additional, Lambert, Jean-Christopher, additional, Verhoelst, Tijl, additional, Allaart, Marc, additional, Compernolle, Steven, additional, Cullis, Patrick D., additional, Dehn, Angelika, additional, Félix, Christian, additional, Johnson, Bryan J., additional, Keppens, Arno, additional, Kollonige, Debra E., additional, Lerot, Christophe, additional, Loyola, Diego, additional, Maata, Matakite, additional, Mitro, Sukarni, additional, Mohamad, Maznorizan, additional, Piters, Ankie, additional, Romahn, Fabian, additional, Selkirk, Henry B., additional, da Silva, Francisco R., additional, Stauffer, Ryan M., additional, Thompson, Anne M., additional, Veefkind, J. Pepijn, additional, Vömel, Holger, additional, Witte, Jacquelyn C., additional, and Zehner, Claus, additional
Published: 2020
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40. Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

Author: Verhoelst, Tijl, primary, Compernolle, Steven, additional, Pinardi, Gaia, additional, Lambert, Jean-Christopher, additional, Eskes, Henk J., additional, Eichmann, Kai-Uwe, additional, Fjæraa, Ann Mari, additional, Granville, José, additional, Niemeijer, Sander, additional, Cede, Alexander, additional, Tiefengraber, Martin, additional, Hendrick, François, additional, Pazmiño, Andrea, additional, Bais, Alkiviadis, additional, Bazureau, Ariane, additional, Boersma, K. Folkert, additional, Bognar, Kristof, additional, Dehn, Angelika, additional, Donner, Sebastian, additional, Elokhov, Aleksandr, additional, Gebetsberger, Manuel, additional, Goutail, Florence, additional, Grutter de la Mora, Michel, additional, Gruzdev, Aleksandr, additional, Gratsea, Myrto, additional, Hansen, Georg H., additional, Irie, Hitoshi, additional, Jepsen, Nis, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kivi, Rigel, additional, Kreher, Karin, additional, Levelt, Pieternel F., additional, Liu, Cheng, additional, Müller, Moritz, additional, Navarro Comas, Monica, additional, Piters, Ankie J. M., additional, Pommereau, Jean-Pierre, additional, Portafaix, Thierry, additional, Puentedura, Olga, additional, Querel, Richard, additional, Remmers, Julia, additional, Richter, Andreas, additional, Rimmer, John, additional, Rivera Cárdenas, Claudia, additional, Saavedra de Miguel, Lidia, additional, Sinyakov, Valery P., additional, Strong, Kimberley, additional, Van Roozendael, Michel, additional, Veefkind, J. Pepijn, additional, Wagner, Thomas, additional, Wittrock, Folkard, additional, Yela González, Margarita, additional, and Zehner, Claus, additional
Published: 2020
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41. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2

Author: Kreher, Karin, primary, Van Roozendael, Michel, additional, Hendrick, Francois, additional, Apituley, Arnoud, additional, Dimitropoulou, Ermioni, additional, Frieß, Udo, additional, Richter, Andreas, additional, Wagner, Thomas, additional, Lampel, Johannes, additional, Abuhassan, Nader, additional, Ang, Li, additional, Anguas, Monica, additional, Bais, Alkis, additional, Benavent, Nuria, additional, Bösch, Tim, additional, Bognar, Kristof, additional, Borovski, Alexander, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Finkenzeller, Henning, additional, Garcia-Nieto, David, additional, Gielen, Clio, additional, Gómez-Martín, Laura, additional, Hao, Nan, additional, Henzing, Bas, additional, Herman, Jay R., additional, Hermans, Christian, additional, Hoque, Syedul, additional, Irie, Hitoshi, additional, Jin, Junli, additional, Johnston, Paul, additional, Khayyam Butt, Junaid, additional, Khokhar, Fahim, additional, Koenig, Theodore K., additional, Kuhn, Jonas, additional, Kumar, Vinod, additional, Liu, Cheng, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Mishra, Abhishek K., additional, Müller, Moritz, additional, Navarro-Comas, Monica, additional, Ostendorf, Mareike, additional, Pazmino, Andrea, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Pinharanda, Manuel, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Postylyakov, Oleg, additional, Prados-Roman, Cristina, additional, Puentedura, Olga, additional, Querel, Richard, additional, Saiz-Lopez, Alfonso, additional, Schönhardt, Anja, additional, Schreier, Stefan F., additional, Seyler, André, additional, Sinha, Vinayak, additional, Spinei, Elena, additional, Strong, Kimberly, additional, Tack, Frederik, additional, Tian, Xin, additional, Tiefengraber, Martin, additional, Tirpitz, Jan-Lukas, additional, van Gent, Jeroen, additional, Volkamer, Rainer, additional, Vrekoussis, Mihalis, additional, Wang, Shanshan, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wittrock, Folkard, additional, Xie, Pinhua H., additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional
Published: 2020
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42. Supplementary material to "Validation of tropospheric NO2 column measurements of GOME-2A and OMI using MAX-DOAS and direct sun network observations"

Author: Pinardi, Gaia, primary, Van Roozendael, Michel, additional, Hendrick, François, additional, Theys, Nicolas, additional, Abuhassan, Nader, additional, Bais, Alkiviadis, additional, Boersma, Folkert, additional, Cede, Alexander, additional, Chong, Jihyo, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Frieß, Udo, additional, Granville, José, additional, Herman, Jay R., additional, Eskes, Henk, additional, Holla, Robert, additional, Hovila, Jari, additional, Irie, Hitoshi, additional, Kanaya, Yugo, additional, Karagkiozidis, Dimitris, additional, Kouremeti, Natalia, additional, Lambert, Jean-Christopher, additional, Ma, Jianzhong, additional, Peters, Enno, additional, Piters, Ankie, additional, Postylyakov, Oleg, additional, Richter, Andreas, additional, Remmers, Julia, additional, Takashima, Hisahiro, additional, Tiefengraber, Martin, additional, Valks, Pieter, additional, Vlemmix, Tim, additional, Wagner, Thomas, additional, and Wittrock, Folkard, additional
Published: 2020
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43. Shipborne MAX-DOAS measurements for validation of TROPOMI NO2 products

Author: Wang, Ping, primary, Piters, Ankie, additional, van Geffen, Jos, additional, Tuinder, Olaf, additional, Stammes, Piet, additional, and Kinne, Stefan, additional
Published: 2020
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44. Geophysical validation of two years of Sentinel-5p tropical tropospheric ozone columns

Author: Hubert, Daan, primary, Verhoelst, Tijl, additional, Compernolle, Steven, additional, Keppens, Arno, additional, Granville, José, additional, Lambert, Jean-Christopher, additional, Heue, Klaus-Peter, additional, Loyola, Diego, additional, Eichmann, Kai-Uwe, additional, Weber, Mark, additional, Thompson, Anne M., additional, Allaart, Marc, additional, Piters, Ankie, additional, Johnson, Bryan J., additional, Selkirk, Henry B., additional, Vömel, Holger, additional, da Silva, Francisco R., additional, Mohamad, Maznorizan, additional, Félix, Christian, additional, and Stübi, René, additional
Published: 2020
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45. MAX-DOAS measurements of atmospheric rural and urban NO2 gradients during the TROLIX'19 campaign

Author: Kreher, Karin, primary, Spinei, Elena, additional, Piters, Ankie, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Doerner, Steffen, additional, Fayt, Caroline, additional, Friedrich, Martina, additional, Frumau, Arnoud, additional, Hendrick, Francois, additional, Hermans, Christian, additional, Karagkiozidis, Dimitris, additional, Querel, Richard, additional, Van Roozendael, Michel, additional, Vonk, Jan, additional, and Wagner, Thomas, additional
Published: 2020
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46. ESA FRM4DOAS: Towards the launch of the NDACC MAX-DOAS Central Processing Service

Author: Hendrick, Francois, primary, Fayt, Caroline, additional, Friedrich, Martina M., additional, Beirle, Steffen, additional, Frieẞ, Udo, additional, Richter, Andreas, additional, Bösch, Tim, additional, Kreher, Karin, additional, Piters, Ankie, additional, Wagner, Thomas, additional, Tirpitz, Jan-Lukas, additional, Bais, Alkis, additional, Prados Roman, Cristina, additional, Puentedura, Olga, additional, Cede, Alexander, additional, Lind, Elena, additional, Dehn, Angelika, additional, von Bismarck, Jonas, additional, Casadio, Stefano, additional, and Van Roozendael, Michel, additional
Published: 2020
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47. Comparison of tropospheric NO2 columns from MAX-DOAS retrievals and regional air quality model simulations

Author: Blechschmidt, Anne-Marlene, primary, Arteta, Joaquim, additional, Coman, Adriana, additional, Curier, Lyana, additional, Eskes, Henk, additional, Foret, Gilles, additional, Gielen, Clio, additional, Hendrick, Francois, additional, Marécal, Virginie, additional, Meleux, Frédérik, additional, Parmentier, Jonathan, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie J. M., additional, Plu, Matthieu, additional, Richter, Andreas, additional, Segers, Arjo, additional, Sofiev, Mikhail, additional, Valdebenito, Álvaro M., additional, Van Roozendael, Michel, additional, Vira, Julius, additional, Vlemmix, Tim, additional, and Burrows, John P., additional
Published: 2020
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48. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign

Author: Tirpitz, Jan-Lukas, primary, Frieß, Udo, additional, Hendrick, François, additional, Alberti, Carlos, additional, Allaart, Marc, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Berkhout, Stijn, additional, Bognar, Kristof, additional, Bösch, Tim, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, den Hoed, Mirjam, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Frumau, Arnoud, additional, Gast, Lou, additional, Gielen, Clio, additional, Gomez-Martín, Laura, additional, Hao, Nan, additional, Hensen, Arjen, additional, Henzing, Bas, additional, Hermans, Christian, additional, Jin, Junli, additional, Kreher, Karin, additional, Kuhn, Jonas, additional, Lampel, Johannes, additional, Li, Ang, additional, Liu, Cheng, additional, Liu, Haoran, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Puentedura, Olga, additional, Richter, Andreas, additional, Schmitt, Stefan, additional, Spinei, Elena, additional, Stein Zweers, Deborah, additional, Strong, Kimberly, additional, Swart, Daan, additional, Tack, Frederick, additional, Tiefengraber, Martin, additional, van der Hoff, René, additional, van Roozendael, Michel, additional, Vlemmix, Tim, additional, Vonk, Jan, additional, Wagner, Thomas, additional, Wang, Yang, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wiegner, Matthias, additional, Wittrock, Folkard, additional, Xie, Pinhua, additional, Xing, Chengzhi, additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional
Published: 2020
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49. Supplementary material to "Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign"

Author: Tirpitz, Jan-Lukas, primary, Frieß, Udo, additional, Hendrick, François, additional, Alberti, Carlos, additional, Allaart, Marc, additional, Apituley, Arnoud, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Berkhout, Stijn, additional, Bognar, Kristof, additional, Bösch, Tim, additional, Bruchkouski, Ilya, additional, Cede, Alexander, additional, Chan, Ka Lok, additional, den Hoed, Mirjam, additional, Donner, Sebastian, additional, Drosoglou, Theano, additional, Fayt, Caroline, additional, Friedrich, Martina M., additional, Frumau, Arnoud, additional, Gast, Lou, additional, Gielen, Clio, additional, Gomez-Martín, Laura, additional, Hao, Nan, additional, Hensen, Arjen, additional, Henzing, Bas, additional, Hermans, Christian, additional, Jin, Junli, additional, Kreher, Karin, additional, Kuhn, Jonas, additional, Lampel, Johannes, additional, Li, Ang, additional, Liu, Cheng, additional, Liu, Haoran, additional, Ma, Jianzhong, additional, Merlaud, Alexis, additional, Peters, Enno, additional, Pinardi, Gaia, additional, Piters, Ankie, additional, Platt, Ulrich, additional, Puentedura, Olga, additional, Richter, Andreas, additional, Schmitt, Stefan, additional, Spinei, Elena, additional, Stein Zweers, Deborah, additional, Strong, Kimberly, additional, Swart, Daan, additional, Tack, Frederick, additional, Tiefengraber, Martin, additional, van der Hoff, René, additional, van Roozendael, Michel, additional, Vlemmix, Tim, additional, Vonk, Jan, additional, Wagner, Thomas, additional, Wang, Yang, additional, Wang, Zhuoru, additional, Wenig, Mark, additional, Wiegner, Matthias, additional, Wittrock, Folkard, additional, Xie, Pinhua, additional, Xing, Chengzhi, additional, Xu, Jin, additional, Yela, Margarita, additional, Zhang, Chengxin, additional, and Zhao, Xiaoyi, additional
Published: 2020
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50. Validation of Aura-OMI QA4ECV NO2 Climate Data Records with ground-based DOAS networks: role of measurement and comparison uncertainties

Author: Compernolle, Steven, primary, Verhoelst, Tijl, additional, Pinardi, Gaia, additional, Granville, José, additional, Hubert, Daan, additional, Keppens, Arno, additional, Niemeijer, Sander, additional, Rino, Bruno, additional, Bais, Alkis, additional, Beirle, Steffen, additional, Boersma, Folkert, additional, Burrows, John P., additional, De Smedt, Isabelle, additional, Eskes, Henk, additional, Goutail, Florence, additional, Hendrick, François, additional, Lorente, Alba, additional, Pazmino, Andrea, additional, Piters, Ankie, additional, Peters, Enno, additional, Pommereau, Jean-Pierre, additional, Remmers, Julia, additional, Richter, Andreas, additional, van Geffen, Jos, additional, Van Roozendael, Michel, additional, Wagner, Thomas, additional, and Lambert, Jean-Christopher, additional
Published: 2020
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