40 results on '"Bais, Alkis"'
Search Results
2. UV Index monitoring in Europe
- Author
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Schmalwieser, Alois W., Gröbner, Julian, Blumthaler, Mario, Klotz, Barbara, De Backer, Hugo, Bolsée, David, Werner, Rolf, Tomsic, Davor, Metelka, Ladislav, Eriksen, Paul, Jepsen, Nis, Aun, Margit, Heikkilä, Anu, Duprat, Thierry, Sandmann, Henner, Weiss, Tilman, Bais, Alkis, Toth, Zoltan, Siani, Anna-Maria, Vaccaro, Luisa, Diémoz, Henri, Grifoni, Daniele, Zipoli, Gaetano, Lorenzetto, Giuseppe, Petkov, Boyan H., di Sarra, Alcide Giorgio, Massen, Francis, Yousif, Charles, Aculinin, Alexandr A., den Outer, Peter, Svendby, Tove, Dahlback, Arne, Johnsen, Bjørn, Biszczuk-Jakubowska, Julita, Krzyscin, Janusz, Henriques, Diamantino, Chubarova, Natalia, Kolarž, Predrag, Mijatovic, Zoran, Groselj, Drago, Pribullova, Anna, Gonzales, Juan Ramon Moreta, Bilbao, Julia, Guerrero, José Manuel Vilaplana, Serrano, Antonio, Andersson, Sandra, Vuilleumier, Laurent, Webb, Ann, and O’Hagan, John
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- 2017
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3. The Quadrennial Ozone Symposium 2016
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Godin-Beekmann, Sophie, Petropavloskikh, Irina, Reis, Stefan, Newman, Paul, Steinbrecht, Wolfgang, Rex, Markus, Santee, Michelle L., Eckman, Richard S., Zheng, Xiandong, Tully, Matthew B., Stevenson, David S., Young, Paul, Pyle, John, Weber, Mark, Tamminen, Johanna, Mills, Gina, Bais, Alkis F., Heaviside, Clare, and Zerefos, Christos
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- 2017
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4. Solar UV: Measurements and Trends
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Seckmeyer, Gunther, Smolskaia, Irina, Pissulla, Darius, Bais, Alkis F., Tourpali, Kleareti, Meleti, Charoula, Zerefos, Christos, Zerefos, Christos, editor, Contopoulos, Georgios, editor, and Skalkeas, Gregory, editor
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- 2009
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5. Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products of atmospheric trace gas columns.
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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
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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]
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- 2023
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- View/download PDF
6. Global Ozone Monitoring Experiment-2 (GOME-2) Daily and Monthly Level 3 Products of Atmospheric Trace Gas Columns.
- Author
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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
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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]
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- 2022
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7. Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements
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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
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- 2021
- Full Text
- View/download PDF
8. Comparative assessment of TROPOMI and OMI formaldehyde observations against MAX-DOAS network column measurements
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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
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- 2021
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9. Supplementary material to "Comparative assessment of TROPOMI and OMI formaldehyde observations against MAX-DOAS network column measurements"
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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
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- 2021
- Full Text
- View/download PDF
10. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign
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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
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- 2021
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11. Intercomparison of NO2, O-4, O-3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-visible spectrometers during CINDI-2
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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
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[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
12. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV¿visible spectrometers during CINDI-2
- Author
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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.
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- 2020
13. Validation of Aura-OMI QA4ECV NO2 climate data records with ground-based DOAS networks : The role of measurement and comparison uncertainties
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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)
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[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.
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- 2020
14. Effect of ambient temperature on Robertson-Berger-type erythemal dosimeters
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Huber, Martin, Blumthaler, Mario, Schreder, Josef, Bais, Alkis, and Topaloglou, Chrysanthi
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Optics -- Usage ,Biometric research -- Equipment and supplies ,Circadian rhythms -- Measurement ,Sunshine -- Observations ,Radiometers -- Research ,Dosimeters -- Research ,Atmospheric temperature -- Research ,Astronomy ,Physics - Abstract
To quantify the effect of ambient temperature on the voltage signal of Solar Light UV-Biometers, spectral response functions of two instruments were determined in the laboratory under various external temperature conditions. Despite the biometer's internal temperature stabilization, a temperature increase of 20 [degrees]C at the outside of an instrument's housing resulted in a reduction of the instrument's spectral response by as much as 10% in the UVB range and by as much as a factor of 2 in the UVA range, depending on the individual instrument and on its internal relative humidity. The significance of this effect for outdoor measurements is demonstrated by data from an intercomparison campaign of erythemal radiometers in Thessaloniki, Greece, organized by the Laboratory of Atmospheric Physics (Aristotle University of Thessaloniki), the Cooperation in Science and Technology (European Commission), and the World Meteorological Organization. On 16 September 1999, 12 of 16 Solar Light Biometers showed significant diurnal variation in their sensitivity (as much as 10% for some individual instruments), which can be explained through a heating of the instruments' housings due to direct solar radiation. OCIS codes: 120.0120, 120.3930, 120.5630.
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- 2002
15. Intercomparison of NO<sub>2</sub>, O<sub>4</sub>, O<sub>3</sub> and HCHO slant column measurements by MAX-DOAS and zenith-sky UV–visible spectrometers during CINDI-2
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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
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- 2020
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16. Second solar ultraviolet radiometer comparison campaign UVC-II
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Hülsen, Gregor, primary, Gröbner, Julian, additional, Bais, Alkis, additional, Blumthaler, Mario, additional, Diémoz, Henri, additional, Bolsée, David, additional, Diaz, Ana, additional, Fountoulakis, Ilias, additional, Naranen, Erik, additional, Schreder, Josef, additional, Stefania, Facta, additional, and Manuel Vilaplana Guerrero, José, additional
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- 2020
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17. MAX-DOAS measurements of atmospheric rural and urban NO2 gradients during the TROLIX'19 campaign
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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
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- 2020
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18. ESA FRM4DOAS: Towards the launch of the NDACC MAX-DOAS Central Processing Service
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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
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- 2020
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19. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign
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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
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- 2020
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20. Supplementary material to "Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign"
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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
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- 2020
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21. Validation of Aura-OMI QA4ECV NO2 Climate Data Records with ground-based DOAS networks: role of measurement and comparison uncertainties
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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
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- 2020
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22. Supplementary material to "Validation of Aura-OMI QA4ECV NO2 Climate Data Records with ground-based DOAS networks: role of measurement and comparison uncertainties"
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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
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- 2020
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23. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign
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Kreher, Karin, Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Frieß, Udo, Richter, Andreas, Wagner, Thomas, Abuhassan, Nader, Ang, Li, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Bösch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka L., Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Finkenzeller, Henning, Garcia-Nieto, David, Gielen, Clio, Gómez-Martín, Laura, Hao, Nan, Herman, Jay R., Hermans, Christian, Hoque, Syedul, Irie, Hitoshi, Jin, Junli, Johnston, Paul, Khayyam Butt, Junaid, Khokhar, Fahim, Koenig, Theodore K., Kuhn, Jonas, Kumar, Vinod, Lampel, Johannes, Liu, Cheng, Ma, Jianzhong, Merlaud, Alexis, Mishra, Abhishek K., Müller, 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, Schönhardt, Anja, Schreier, Stefan F., Seyler, Andre, Sinha, Vinayak, Spinei, Elena, Strong, Kimberly, Tack, Frederik, Tian, Xin, Tiefengraber, Martin, Tirpitz, Jan-Lukas, Gent, Jeron, Volkamer, Rainer, Vrekoussis, Mihalis, Wang, Shanshan, Wang, Zhuoru, Wenig, Mark, Wittrock, Folkard, Xie, Pinhua H., Xu, Jin, Yela, Margarita, Zhang, Chengxin, and Zhao, Xiaoyi
- Abstract
In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were to characterise and better understand the differences between a large number of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO2), the oxygen dimer (O4) and ozone (O3) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region and NO2 in an additional (smaller) wavelength range in the visible. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in an unprecedented set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the reference, and the RMS error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques.
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- 2019
24. Comparative assessment of TROPOMI and OMI formaldehyde observations against MAX-DOAS network column measurements.
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De Smedt, Isabelle, Pinardi, Gaia, Vigouroux, Corinne, Compernolle, Steven, Bais, Alkis, Benavent, Nuria, Boersma, Folkert, Ka-Lok Chan, Donner, Sebastian, Kai-Uwe Eichmann, Hedelt, Pascal, Hendrick, François, Hitoshi Irie, Kumar, Vinod, Lambert, Jean-Christopher, Langerock, Bavo, Lerot, Christophe, Cheng Liu, Loyola, Diego, and Piters, Ankie
- Abstract
The TROPOspheric Monitoring Instrument (TROPOMI), launched in October 2017 on board the Sentinel-5 Precursor (S5P) satellite, monitors the composition of the Earth's atmosphere at an unprecedented horizontal resolution as fine as 3.5 x 5.5 km
2 . This paper assess the performances of the TROPOMI formaldehyde (HCHO) operational product compared to its predecessor, the OMI HCHO QA4ECV product, at different spatial and temporal scales. The parallel development of the two algorithms favored the consistency of the products, which facilitates the production of long-term combined time series. The main difference between the two satellite products is related to the use of different cloud algorithms, leading to a positive bias of OMI compared to TROPOMI of up to 30 % in Tropical regions. We show that after switching off the explicit correction for cloud effects, the two datasets come into an excellent agreement. For medium to large HCHO vertical columns (larger than 5 x 1015 molec.cm-2 ) the median bias between OMI and TROPOMI HCHO columns is not larger than 10 % (< 0.4 x 1015 molec.cm-2 ). For lower columns, OMI observations present a remaining positive bias of about 20 % (< 0.8 x 1015 molec.cm-2 ) compared to TROPOMI in mid-latitude regions. Here, we also use a global network of 18 MAX-DOAS instruments to validate both satellite sensors for a large range of HCHO columns. This work complements the study by Vigouroux et al. (2020) where a global FTIR network is used to validate the TROPOMI HCHO operational product. Consistent with the FTIR validation study, we find that for elevated HCHO columns, TROPOMI data are systematically low (-25 % for HCHO columns larger than 8 x 1015 molec.cm- ), while no significant bias is found for medium range column values. We further show that OMI and TROPOMI data present equivalent biases for large HCHO levels. However, TROPOMI significantly improves the precision of the HCHO observations at short temporal scales, and for low HCHO columns. We show that compared to OMI, the precision of the TROPOMI HCHO columns is improved by 25 % for individual pixels, and up to a factor 3 when considering daily averages in 20 km-radius circles. The validation precision obtained with daily TROPOMI observations is comparable to the one obtained with monthly OMI observations. To illustrate the improved performances of TROPOMI in capturing weak HCHO signals, we present clear detection of HCHO column enhancements related to shipping emissions in the Indian Ocean. This is achieved by averaging data over a much shorter period (3 months) than required with previous sensors, and opens new perspectives to study shipping emissions of VOCs and related atmospheric chemical interactions. [ABSTRACT FROM AUTHOR]- Published
- 2021
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25. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign
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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, 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 L., 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, 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, Lampel, Johannes, 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, Andre, 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, Jeron, 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
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- 2019
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26. Supplementary material to "Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign"
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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, 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 L., 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, 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, Lampel, Johannes, 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, Andre, 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, Jeron, 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
- 2019
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27. Intercomparison of MAX-DOAS vertical profile retrieval algorithms: studies on field data from the CINDI-2 campaign.
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Tirpitz, Jan-Lukas, Frieß, Udo, Hendrick, François, Alberti, Carlos, Allaart, Marc, Apituley, Arnoud, Bais, Alkis, Beirle, Steffen, Berkhout, Stijn, Bognar, Kristof, Bösch, Tim, Bruchkouski, Ilya, Cede, Alexander, Ka Lok Chan, den Hoed, Mirjam, Donner, Sebastian, Drosoglou, Theano, Fayt, Caroline, Friedrich, Martina M., and Frumau, Arnoud
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TROPOSPHERIC aerosols ,TRACE gases ,GAS distribution ,RADIOMETERS ,ELECTROMAGNETIC spectrum ,PHOTOMETERS ,VISIBLE spectra ,RADIO frequency allocation - Abstract
Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) is a well-established ground-based measurement technique for the detection of aerosols and trace gases particularly in the boundary layer and the lower troposphere: ultraviolet- and visible radiation spectra of skylight are analysed to obtain information on different atmospheric parameters, integrated over the light path from space to the instrument. An appropriate set of spectra recorded under different viewing geometries ("Multi-Axis") allows retrieval of tropospheric aerosol and trace gas vertical distributions by applying numerical inversion methods. The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (The Netherlands) in September 2016 with the aim of assessing the consistency of MAX-DOAS measurements of tropospheric species (NO
2 , HCHO, O3 , HONO, CHOCHO and O4 ). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, Long-Path DOAS, sun photometer and others). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2 , HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations. The profiles were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions, however sometimes at different altitudes and of different intensity. Under clear sky conditions, the root-mean-square differences of aerosol optical thicknesses, trace gas (NO2 , HCHO) vertical columns and surface concentrations among the results of individual participants vary between 0.01-0.1, (1.5-15) x 1014 molec cm-2 and (0.3-8) x 1010 molec cm-3 , respectively. For the comparison against supporting observations, these values increase to 0.02-0.2, (11-55) x 1014 molec cm-2 and (0.8-9) x 1010 molec cm-3 . It is likely that a large part of this increase is caused by imperfect spatio-temporal overlap of the different observations. In contrast to what is often assumed, the MAX-DOAS vertically integrated extinction profiles and the sun photometer total aerosol optical thickness were found to not necessarily being comparable quantities, unless information on the real aerosol vertical distribution is available to account for the low sensitivity of MAX-DOAS observations at higher altitudes. [ABSTRACT FROM AUTHOR]- Published
- 2020
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28. Validation of Aura-OMI QA4ECV NO2 Climate Data Records with ground-based DOAS networks: role of measurement and comparison uncertainties.
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Compernolle, Steven, Verhoelst, Tijl, Pinardi, Gaia, Granville, José, 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, François, Lorente, Alba, Pazmino, Andrea, Piters, Ankie, and Peters, Enno
- Abstract
The QA4ECV version 1.1 stratospheric and tropospheric NO
2 vertical column density (VCD) climate data records (CDR) from the satellite sensor OMI are validated, using NDACC zenith scattered light DOAS (ZSL-DOAS) and Multi Axis-DOAS (MAX-DOAS) data as a reference. The QA4ECV OMI stratospheric VCD 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 ZSL-DOAS 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 Pmolec cm-2 up to -10 Pmolec cm-2 (-40 %) in one extreme high-pollution case. QA4ECV OMI tropospheric VCD has a negative bias with respect to the MAX-DOAS data (-1 to -4 Pmolec cm-2 ), a feature also found for the OMI OMNO2 standard data product. The tropospheric VCD discrepancies between satellite and ground-based data exceed by far 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 to the difference in vertical smoothing and a priori profile assumptions. [ABSTRACT FROM AUTHOR]- Published
- 2020
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29. Satellite nadir NO2 validation based on zenith-sky, direct-sun and MAXDOAS network observations
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Pinardi, Gaia, Van Roozendael, Michel, Lambert, Jean-Christopher, Granville, José, Hendrick, François, Gielen, Clio, Cede, Alexander, Kanaya, Ygo, Irie, Hitoshi, Wittrock, Folkard, Richter, Andreas, Peters, Enno, Wagner, Thomas, Gu, Myojeong, Remmers, Julia, Lampel, Johannes, Friess, Udo, Vlemmix, Tim, Piters, Ankie, Hao, Nan, Tiefengraber, Martin, Herman, Jay, Abuhassan, Nader, Holla, Robert, Bais, Alkis, Balis, Dimitris, Drosoglou, Theano, Kouremeti, Natalia, Hovila, Jari, Chong, J., Postylyakov, Oleg, Ma, Jianzhong, Goutail, Florence, Pommereau, Jean-Pierre, Pazmino, Andrea, Navarro, Monica, Puentedura, Olga, Yu, Huan, Belgian Institute for Space Aeronomy / Institut d'Aéronomie Spatiale de Belgique (BIRA-IASB), NASA Goddard Space Flight Center (GSFC), Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Center for Environmental Remote Sensing [Chiba] (CEReS), Chiba University, Institute of Environmental Physics [Bremen] (IUP), University of Bremen, Max Planck Institute for Chemistry (MPIC), Max-Planck-Gesellschaft, Institut für Umweltphysik [Heidelberg], Universität Heidelberg [Heidelberg], Department of Geoscience and Remote Sensing [Delft], Delft University of Technology (TU Delft), Royal Netherlands Meteorological Institute (KNMI), DLR Institut für Methodik der Fernerkundung / DLR Remote Sensing Technology Institute (IMF), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Institute of Meteorology and Geophysics [Innsbruck], University of Innsbruck, Joint Center for Earth Systems Technology [Baltimore] (JCET), NASA Goddard Space Flight Center (GSFC)-University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System, Meteorologisches Observatorium Hohenpeißenberg (MOHp), Deutscher Wetterdienst [Offenbach] (DWD), Laboratory of Atmospheric Physics [Thessaloniki], Aristotle University of Thessaloniki, Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC), Finnish Meteorological Institute (FMI), Gwangju Institute of Science and Technology (GIST), A.M.Obukhov Institute of Atmospheric Physics (IAP), Russian Academy of Sciences [Moscow] (RAS), Chinese Academy of Meteorological Sciences (CAMS), STRATO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Instituto Nacional de Técnica Aeroespacial (INTA), Cardon, Catherine, Universität Heidelberg [Heidelberg] = Heidelberg University, and Leopold Franzens Universität Innsbruck - University of Innsbruck
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[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] ,[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere ,[SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere ,[PHYS.PHYS.PHYS-AO-PH] Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] - Abstract
International audience; Since more than fifteen years, total and tropospheric NO2 columns have been retrieved from nadir space-borne sensors such as SCIAMACHY on ENVISAT, OMI on AURA and GOME-2 on MetOp platforms. The NO2 data products are generally retrieved in three main steps: (1) a DOAS spectral analysis yielding the total column amount of NO2 along the slant optical path, (2) an estimation of the stratospheric NO2 column, to be subtracted from the total column to derive the tropospheric contribution, and (3) a conversion of the total and tropospheric slant columns into vertical columns based on airmass factor calculations which require a-priori knowledge of the NO2 vertical distribution and surface albedo, as well as information on cloud cover and height.In this study we combine correlative measurements available from several ground-based remote sensing networks to address the validation of (1) the GOME-2 GDP 4.8 NO2 products generated within the EUMETSAT O3M-SAF project, and (2) the SCIAMACHY, OMI and GOME-2 TEMIS product. Zenith-sky DOAS/SAOZ measurements from the NDACC network are used to assess the stratospheric NO2 columns retrieved from the satellite, while the consistency of the total and tropospheric NO2 columns in urban, sub-urban and back-ground conditions is investigated using direct-sun Pandora and multi-axis MAXDOAS data sets from about 40 stations. Where available, vertical profile information from MAXDOAS measurements is used to assess the reliability of the different satellite a-priori profile shapes.Results are discussed in terms of observed biases between satellite and ground-based data sets, their dependence on location, season and cloud conditions. For stratospheric columns, the uncertainty related to the correction applied for ensuring the photochemical matching between satellite and ground-based observations is also evaluated. The satellite pixels resolution effect is statistically explored in relation to the typical extent of the emission sources at urban site locations, using data from SCIAMACHY 60x30 km², GOME-2 40x80 km² and OMI 13x24 km².
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- 2016
30. Investigating differences in DOAS retrieval codes using MAD-CAT campaign data
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Peters, Enno, primary, Pinardi, Gaia, additional, Seyler, André, additional, Richter, Andreas, additional, Wittrock, Folkard, additional, Bösch, Tim, additional, Burrows, John P., additional, Van Roozendael, Michel, additional, Hendrick, François, additional, Drosoglou, Theano, additional, Bais, Alkis F., additional, Kanaya, Yugo, additional, Zhao, Xiaoyi, additional, Strong, Kimberly, additional, Lampel, Johannes, additional, Volkamer, Rainer, additional, Koenig, Theodore, additional, Ortega, Ivan, additional, Piters, Ankie, additional, Puentedura, Olga, additional, Navarro, Mónica, additional, Gómez, Laura, additional, Yela González, Margarita, additional, Remmers, Julia, additional, Wang, Yang, additional, Wagner, Thomas, additional, Wang, Shanshan, additional, Saiz-Lopez, Alfonso, additional, García-Nieto, David, additional, Cuevas, Carlos A., additional, Benavent, Nuria, additional, Querel, Richard, additional, Johnston, Paul, additional, Postylyakov, Oleg, additional, Borovski, Alexander, additional, Elokhov, Aleksandr, additional, Bruchkouski, Ilya, additional, Liu, Cheng, additional, Hong, Qianqian, additional, Liu, Haoran, additional, Rivera, Claudia, additional, Grutter, Michel, additional, Stremme, Wolfgang, additional, Khokhar, M. Fahim, additional, and Khayyam, Junaid, additional
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- 2016
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31. Intercomparison of NO2, O4, O3 and HCHO slant column measurements by MAX-DOAS and zenith-sky UV-Visible spectrometers during the CINDI-2 campaign.
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Kreher, Karin, Van Roozendael, Michel, Hendrick, Francois, Apituley, Arnoud, Dimitropoulou, Ermioni, Frieß, Udo, Richter, Andreas, Wagner, Thomas, Abuhassan, Nader, Li Ang, Anguas, Monica, Bais, Alkis, Benavent, Nuria, Bösch, Tim, Bognar, Kristof, Borovski, Alexander, Bruchkouski, Ilya, Cede, Alexander, Chan, Ka L., and Donner, Sebastian
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MEASURING instruments ,SPECTROMETERS ,OZONE generators ,ATMOSPHERIC composition ,NITROGEN dioxide ,LIGHT absorption - Abstract
In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants for a period of 17 days during the Second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) that took place at Cabauw, The Netherlands (51.97° N, 4.93° E). We report on the outcome of the formal semi-blind intercomparison exercise, which was held under the umbrella of the Network for the Detection of Atmospheric Composition Change (NDACC) and the European Space Agency (ESA). The three major goals of CINDI-2 were to characterise and better understand the differences between a large number of Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) and zenith-sky DOAS instruments and analysis methods, to discuss the performance of the various types of instruments and to contribute to a harmonisation of the measurement settings and retrieval methods. This, in turn, creates the capability to produce consistent high-quality ground-based data sets, which are an essential requirement to generate reliable long-term measurement time series suitable for trend analysis and satellite data validation. The data products investigated during the semi-blind intercomparison are slant columns of nitrogen dioxide (NO
2 ), the oxygen dimer (O4 ) and ozone (O3 ) measured in the UV and visible wavelength region, formaldehyde (HCHO) in the UV spectral region and NO2 in an additional (smaller) wavelength range in the visible. The campaign design and implementation processes are discussed in detail including the measurement protocol, calibration procedures and slant column retrieval settings. Strong emphasis was put on the careful alignment and synchronisation of the measurement systems, resulting in an unprecedented set of measurements made under highly comparable air mass conditions. The CINDI-2 data sets were investigated using a regression analysis of the slant columns measured by each instrument and for each of the target data products. The slope and intercept of the regression analysis respectively quantify the mean systematic bias and offset of the individual data sets against the reference, and the RMS error provides an estimate of the measurement noise or dispersion. These three criteria are examined and for each of the parameters and each of the data products, performance thresholds are set and applied to all the measurements. The approach presented here has been developed based on heritage from previous intercomparison exercises. It introduces a quantitative assessment of the measurement performance of all the participating instruments for the MAX-DOAS and zenith-sky DOAS techniques. [ABSTRACT FROM AUTHOR]- Published
- 2019
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32. Investigating differences in DOAS retrieval codes using MAD-CAT campaign data.
- Author
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Peters, Enno, Pinardi, Gaia, André Seyler, Richter, Andreas, Wittrock, Folkard, Bösch, Tim, Burrows, John P., Van Roozendael, Michel, Hendrick, François, Drosoglou, Theano, Bais, Alkis F., Yugo Kanaya, Xiaoyi Zhao, Strong, Kimberly, Lampel, Johannes, Volkamer, Rainer, Koenig, Theodore, Ortega, Ivan, Piters, Ankie, and Puentedura, Olga
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TRACE gases ,ATMOSPHERIC aerosol measurement ,ABSORPTION spectra - Abstract
The Differential Optical Absorption Spectroscopy (DOAS) method is a well-known remote sensing technique that is nowadays widely used for measurements of atmospheric trace gases, creating the need for harmonization and characterization efforts. In this study, an intercomparison exercise of DOAS retrieval codes from 17 international groups is presented focusing on NO
2 slant columns. The study is based on data collected by one instrument during the Multi-Axis DOAS Comparison campaign for Aerosols and Trace gases (MAD-CAT) in Mainz, Germany, in summer 2013. As data from the same instrument is used by all groups, the results are free of biases due to instrumental differences, which is in contrast to previous intercomparison exercises. While in general an excellent correlation of NO2 slant columns between groups of > 99.98% (noon reference fits), and > 99.2% (sequential reference fits) for all elevation angles is found, differences between individual retrievals are as large as 8% for NO2 slant columns and 100% for RMS residuals. Two kinds of disagreements were identified: (1) Absolute slant column differences were found to result predominantly from the choice of the reference spectrum. (2) Relative differences were found to originate from the numerical approach for solving the DOAS equation as well as the treatment of the slit function. Differences in the implementations of the intensity offset correction lead to disagreements for retrievals close to sunrise (8-10% for NO2 , 80% for RMS residual). Apart from this, the largest effect of ≈ 8% difference in NO2 was found to arise from the reference treatment, in particular for fits using a sequential reference. In terms of RMS fit residual, the reference treatment has only a minor impact. In contrast, the wavelength calibration as well as the intensity offset correction were found to have the largest impact (up to 80%) on RMS residual while having only a minor impact on retrieved NO2 slant columns. [ABSTRACT FROM AUTHOR]- Published
- 2016
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33. Variability of UV Irradiance in Europe
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Seckmeyer, Gunther, primary, Pissulla, Darius, additional, Glandorf, Merle, additional, Henriques, Diamantino, additional, Johnsen, Bjorn, additional, Webb, Ann, additional, Siani, Anna-Maria, additional, Bais, Alkis, additional, Kjeldstad, Berit, additional, Brogniez, Colette, additional, Lenoble, Jacqueline, additional, Gardiner, Brian, additional, Kirsch, Peter, additional, Koskela, Tapani, additional, Kaurola, Jussi, additional, Uhlmann, Beate, additional, Slaper, Harry, additional, den Outer, Peter, additional, Janouch, Michal, additional, Werle, Peter, additional, Gröbner, Julian, additional, Mayer, Bernhard, additional, de la Casiniere, Alain, additional, Simic, Stana, additional, and Carvalho, Fernanda, additional
- Published
- 2007
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34. Quality assurance of spectral solar UV measurements: results from 25 UV monitoring sites in Europe, 2002 to 2004
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Gröbner, Julian, primary, Blumthaler, Mario, additional, Kazadzis, Stelios, additional, Bais, Alkis, additional, Webb, Ann, additional, Schreder, Josef, additional, Seckmeyer, Gunther, additional, and Rembges, Diana, additional
- Published
- 2006
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35. Correction of direct irradiance measurements of Brewer spectrophotometers due to the effect of internal polarization
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Cede, Alexander, primary, Kazadzis, Stelios, additional, Kowalewski, Matt, additional, Bais, Alkis, additional, Kouremeti, Natalia, additional, Blumthaler, Mario, additional, and Herman, Jay, additional
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- 2006
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36. Assessment of TOMS UV bias due to absorbing aerosols
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Arola, Antti, primary, Kazadzis, Stelios, additional, Krotkov, Nickolay, additional, Bais, Alkis, additional, Gröbner, Julian, additional, and Herman, Jay R., additional
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- 2005
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37. Assessment of TOMS UV bias due to absorbing aerosols.
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Arola, Antti, Kazadzis, Stelios, Krotkov, Nickolay A., Bais, Alkis, Herman, Jay R., and Lakkala, Kaisa
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- 2004
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38. Variability of UV Irradiance in Europe.
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Seckmeyer, Gunther, Pissulla, Darius, Glandorf, Merle, Henriques, Diamantino, Johnsen, Bjorn, Webb, Ann, Siani, Anna-Maria, Bais, Alkis, Kjeldstad, Berit, Brogniez, Colette, Lenoble, Jacqueline, Gardiner, Brian, Kirsch, Peter, Koskela, Tapani, Kaurola, Jussi, Uhlmann, Beate, Slaper, Harry, den Outer, Peter, Janouch, Michal, and Werle, Peter
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ULTRAVIOLET radiation ,RADIATIVE transfer ,OZONE layer ,CLOUDS ,CLIMATOLOGY - Abstract
The diurnal and annual variability of solar UV radiation in Europe is described for different latitudes, seasons and different biologic weighting functions. For the description of this variability under cloudless skies the widely used one-dimensional version of the radiative transfer model UVSPEC is used. We reconfirm that the major factor influencing the diurnal and annual variability of UV irradiance is solar elevation. While ozone is a strong absorber of UV radiation its effect is relatively constant when compared with the temporal variability of clouds. We show the significant role that clouds play in modifying the UV climate by analyzing erythemal irradiance measurements from 28 stations in Europe in summer. On average, the daily erythemal dose under cloudless skies varies between 2.2 kJ m
−2 at 70°N and 5.2 kJ m−2 at 35°N, whereas these values are reduced to 1.5–4.5 kJ m−2 if clouds are included. Thus clouds significantly reduce the monthly UV irradiation, with the smallest reductions, on average, at lower latitudes, which corresponds to the fact that it is often cloudless in the Mediterranean area in summer. [ABSTRACT FROM AUTHOR]- Published
- 2008
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39. Analysis and interpretation of Aerosol Optical Depth values retrieved from a Brewer spectrophotometer at Uccle, Belgium
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De Bock, Veerle, Coheur, Pierre-François, De Backer, Hugo, Vander Auwera, Jean, Clarisse, Lieven, Bais, Alkis, and Van Roozendael, Michel
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ozone ,Spectroscopie [électromagnétisme, optique, acoustique] ,Phénomènes atmosphériques ,Télédétection ,time series analysis ,retrieval method ,aerosols ,UV radiation - Abstract
Aerosols are particles in the solid or liquid phase that are suspended in the atmosphere. They have an important influence on the atmospheric chemistry and physics, affect the tropospheric chemical composition, can reduce visibility and have important impacts on human health. Aerosols also influence the Earth’s radiation budget. Although a lot of research has been done to investigate the influence of aerosols on the climate, they remain key contributors to the uncertainties in current climate studies due to the lack of information concerning their temporal and spatial distribution. One of the parameters that is of importance to understand the influence of aerosols is the aerosol optical depth (AOD), an integral measurement of the combined aerosol scattering and absorption in the atmospheric column. The first part of this PhD describes an adapted and improved method for the retrieval of AOD values using sun scan measurements from a Brewer spectrophotometer at 340 nm at Uccle. The retrieved AOD values are subjected to a cloud screening technique and are compared to quasi simultaneous, collocated CIMEL AOD values. The good agreement between both instruments highlights that the Brewer is largely sensitive to AOD at 340 nm and it justifies its use in sun scan mode to expand the AOD retrieval network of instruments. The monthly and seasonal behavior of the retrieved AOD values is also studied in this work and our results agree with results found in literature.Another point of concern in scientific communities is the known adverse effect of UV radiation on human health, the biosphere and atmospheric chemistry. Apart from its obvious relation with global solar radiation and ozone, the amount of UV radiation that reaches the surface of the Earth also depends on the characteristics and quantity of aerosols in the atmosphere and accuracy in UV prediction can be improved if the influence of aerosols on surface UV radiation is clarified. For this reason, the second part of this work focuses on the relation between the erythemal UV dose, global solar radiation, total ozone column and AOD (at 320 nm) at Uccle. Simultaneous measurements of these variables are available for a time period of 25 years (1991–2015) and this time series is long enough to allow for reliable determination of significant changes. Different analysis techniques (linear trend analysis, change point analysis and multiple linear regression) are combined to allow for an extensive study of the relations between the variables., Doctorat en Sciences, info:eu-repo/semantics/nonPublished
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- 2018
40. Reconstruction of past UV radiation
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Lindfors, Anders, University of Helsinki, Faculty of Science, Department of Physical Sciences, Division of Atmospheric Sciences, Helsingin yliopisto, matemaattis-luonnontieteellinen tiedekunta, fysikaalisten tieteiden laitos, Helsingfors universitet, matematisk-naturvetenskapliga fakulteten, institutionen för fysikaliska vetenskaper, Bais, Alkis, and Kaurola, Jussi
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meteorologia - Abstract
Solar ultraviolet (UV) radiation has a broad range of effects concerning life on Earth. Soon after the mid-1980s, it was recognized that the stratospheric ozone content was declining over large areas of the globe. Because the stratospheric ozone layer protects life on Earth from harmful UV radiation, this lead to concern about possible changes in the UV radiation due to anthropogenic activity. Initiated by this concern, many stations for monitoring of the surface UV radiation were founded in the late 1980s and early 1990s. As a consequence, there is an apparent lack of information on UV radiation further in the past: measurements cannot tell us how the UV radiation levels have changed on time scales of, for instance, several decades. The aim of this thesis was to improve our understanding of past variations in the surface UV radiation by developing techniques for UV reconstruction. Such techniques utilize commonly available meteorological data together with measurements of the total ozone column for reconstructing, or estimating, the amount of UV radiation reaching Earth's surface in the past. Two different techniques for UV reconstruction were developed. Both are based on first calculating the clear-sky UV radiation using a radiative transfer model. The clear-sky value is then corrected for the effect of clouds based on either (i) sunshine duration or (ii) pyranometer measurements. Both techniques account also for the variations in the surface albedo caused by snow, whereas aerosols are included as a typical climatological aerosol load. Using these methods, long time series of reconstructed UV radiation were produced for five European locations, namely Sodankylä and Jokioinen in Finland, Bergen in Norway, Norrköping in Sweden, and Davos in Switzerland. Both UV reconstruction techniques developed in this thesis account for the greater part of the factors affecting the amount of UV radiation reaching the Earth's surface. Thus, they are considered reliable and trustworthy, as suggested also by the good performance of the methods. The pyranometer-based method shows better performance than the sunshine-based method, especially for daily values. For monthly values, the difference between the performances of the methods is smaller, indicating that the sunshine-based method is roughly as good as the pyranometer-based for assessing long-term changes in the surface UV radiation. The time series of reconstructed UV radiation produced in this thesis provide new insight into the past UV radiation climate and how the UV radiation has varied throughout the years. Especially the sunshine-based UV time series, extending back to 1926 and 1950 at Davos and Sodankylä, respectively, also put the recent changes driven by the ozone decline observed over the last few decades into perspective. At Davos, the reconstructed UV over the period 1926-2003 shows considerable variation throughout the entire period, with high values in the mid-1940s, early 1960s, and in the 1990s. Moreover, the variations prior to 1980 were found to be caused primarily by variations in the cloudiness, while the increase of 4.5 %/decade over the period 1979-1999 was supported by both the decline in the total ozone column and changes in the cloudiness. Of the other stations included in this work, both Sodankylä and Norrköping show a clear increase in the UV radiation since the early 1980s (3-4 %/decade), driven primarily by changes in the cloudiness, and to a lesser extent by the diminution of the total ozone. At Jokioinen, a weak increase was found, while at Bergen there was no considerable overall change in the UV radiation level. Auringon ultraviolettisäteily (UV-säteily) vaikuttaa usealla tavalla elämään maan päällä. 1980-luvun puolivälin jälkeen huomattiin, että stratosfäärin otsonimäärä oli vähenemässä etenkin Etelämantereen kevätkaudella mutta myös maapallonlaajuisesti. Stratosfäärin otsonikerros suojelee elämää maan päällä haitalliselta UV-säteilyltä, ja havaitut otsonikerroksen muutokset aiheuttivat huolta ihmiskunnan mahdollisesti aiheuttamista muutoksista UV-säteilymäärissä. Tämän seurauksena useimmat UV-säteilyn mittausasemat ovat perustettuja juuri tähän aikaan 1990-luvun taitteessa. UV-säteilyn mittausaikasarjat ovat siis melko lyhyitä, ja ne pystyvät tyypillisesti kertomaan meille UV-säteilyn vaihteluista vain viimeisten noin 15 vuoden ajalta. Tämän väitöskirjatyön tavoitteena oli tuottaa uutta tietoa UV-säteilyn vaihteluista menneisyydessä kehittämällä ns. UV-rekonstruointimenetelmiä, joissa hyödynnetään yleisiä meteorologisia mittauksia ja kokonaisotsonitietoa menneen ajan UV-säteilyn arvioimiseen. Tässä työssä kehitettiin kaksi UV-rekonstruointimenetelmää. Molemmissa lasketaan aluksi säteilynkuljetusmallilla pilvettömän sään UV-säteilymäärä. Pilvien vaikutus otetaan tämän jälkeen huomioon joko auringon paistehavaintojen tai pyranometrimittauksien perusteella. Lisäksi kumpikin menetelmä ottaa huomioon lumen aiheuttamat vaihtelut maan pinnan heijastuvuudessa. Ilmakehän pienhiukkaset ovat mukana laskuissa tyypillisenä määränä kullakin paikkakunnalla. Näitä kahta menetelmää käyttäen tuotettiin pitkiä aikasarjoja menneen ajan UV-säteilystä viidelle asemalle Euroopassa. Asemat olivat Sodankylä ja Jokioinen Suomessa, Bergen Norjassa, Norrköping Ruotsissa ja Davos Sveitsissä. Kumpikin tässä työssä kehitetty menetelmä ottaa huomioon tärkeimmät UV-säteilymäärään vaikuttavat tekijät ja tulokset ovat hyviä verrattaessa riippumattomiin havaintoihin. Tämän vuoksi menetelmiä voidaan pitää luotettavina. Pyranometrimittauksiin perustuva menetelmä on tarkempi kuin paistehavaintoihin perustuva etenkin päiväkohtaisia arvoja verrattaessa. Kuitenkin paistehavaintoihin perustuva menetelmä on kuukausiarvoja tarkasteltaessa lähes yhtä tarkka kuin pyranometrimenetelmä, mikä tarkoittaa että paistemenetelmä on suurin piirtein yhtä hyvä kuin pyranometrimenetelmä arvioitaessa pidemmän aikavälin vaihteluita kuten esimerkiksi vuosi vuodelta tapahtuvaa vaihtelua. Tässä työssä tuotetut pitkät UV-aikasarjat tuovat uutta tietoa UV-säteilyn ilmastollisesta käyttäytymisestä ja siitä kuinka UV-säteily on vaihdellut menneisyydessä. Esimerkiksi auringon paistehavaintoihin perustuvat aikasarjat ulottuvat vuoteen 1926 Davosissa ja vuoteen 1950 Sodankylässä. Näin ollen ne muodostavat myös uuden vertailukohdan viimeaikaisille muutoksille, joissa otsonikadolla on ollut merkitystä (noin 1980 alkaen). Davosissa UV-säteily on vaihdellut tuntuvasti koko tarkastelujaksolla 1926-2003. Korkeita arvoja oli 1940-luvun keskivaiheilla, 1960-luvun alussa ja 1990-luvulla. Lisäksi huomattiin, että pilvisyyden vaihtelut hallitsivat ennen vuotta 1980 tapahtuneita vaihteluita UV-säteilyssä. Toisaalta sekä pilvisyys että otsonin vähentyminen vaikuttivat jakson 1979-1999 aikana todettuun kasvuun UV-säteilyssä (4,5 %/vuosikymmen). Myös Sodankylässä ja Norrköpingissä UV-säteily on lisääntynyt 1980-luvun alusta (3-4 %/vuosikymmen). Näillä asemilla kasvun aiheutti ensisijaisesti pilvisyyden muutokset ja vähemmässä määrin otsonin vähentyminen. Jokioisissa ja Bergenissä UV-säteilyn muutokset olivat pieniä.
- Published
- 2007
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