Articles | Volume 16, issue 2
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium
Atmospheric Composition Department, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Brussels, Belgium
Atmospheric Composition Department, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Brussels, Belgium
Atmospheric Composition Department, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Brussels, Belgium
Environmental Modelling Unit, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
Scientific Division Observations, Royal Meteorological Institute of Belgium (RMI), Ringlaan 3, 1180 Brussels, Belgium
Roeland Van Malderen
Scientific Division Observations, Royal Meteorological Institute of Belgium (RMI), Ringlaan 3, 1180 Brussels, Belgium
Environmental Modelling Unit, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
No articles found.
Glenn-Michael Oomen, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, Thomas Blumenstock, Rigel Kivi, Maria Makarova, Mathias Palm, Amelie Röhling, Yao Té, Corinne Vigouroux, Martina M. Friedrich, Udo Frieß, François Hendrick, Alexis Merlaud, Ankie Piters, Andreas Richter, Michel Van Roozendael, and Thomas Wagner
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).Short summary
Natural emissions from vegetation have a profound impact on air quality for their role in the formation of harmful tropospheric ozone and organic aerosols, yet these emissions are highly uncertain. In this study, we quantify emissions of organic gases over Europe using high-quality satellite measurements of formaldehyde. These satellite observations suggest that emissions from vegetation are much higher than predicted by models, especially in southern Europe.
Herman G.J. Smit, Deniz Poyraz, Roeland Van Malderen, Anne M. Thompson, David W. Tarasick, Ryan M. Stauffer, Bryan J. Johnson, and Debra E. Kollonige
This paper revisits fundamentals of ECC ozonesonde measurements to develop and characterize a methodology to correct for the fast and slow time responses using the JOSIE (Jülich Ozone Sonde Intercomparison Experiment) simulation chamber data. Comparing the new corrected ozonesonde profiles to an accurate ozone UV-photometer (OPM) as reference, allows us to evaluate the time responses correction (TRC) method and to determine calibration functions traceable to one reference with 5 % uncertainty.
Peng Yuan, Roeland Van Malderen, Xungang Yin, Hannes Vogelmann, Weiping Jiang, Joseph Awange, Bernhard Heck, and Hansjörg Kutterer
Atmos. Chem. Phys., 23, 3517–3541,Short summary
Water vapour plays an important role in various weather and climate processes. However, due to its large spatiotemporal variability, its high-accuracy quantification remains a challenge. In this study, 20+ years of GPS-derived integrated water vapour (IWV) retrievals in Europe were obtained. They were then used to characterise the temporal features of Europe's IWV and assess six atmospheric reanalyses. Results show that ERA5 outperforms the other reanalyses at most temporal scales.
Kezia Lange, Andreas Richter, Anja Schönhardt, Andreas C. Meier, Tim Bösch, André Seyler, Kai Krause, Lisa K. Behrens, Folkard Wittrock, Alexis Merlaud, Frederik Tack, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Vinod Kumar, Sebastian Donner, Steffen Dörner, Bianca Lauster, Maria Razi, Christian Borger, Katharina Uhlmannsiek, Thomas Wagner, Thomas Ruhtz, Henk Eskes, Birger Bohn, Daniel Santana Diaz, Nader Abuhassan, Dirk Schüttemeyer, and John P. Burrows
Atmos. Meas. Tech., 16, 1357–1389,Short summary
We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted during the S5P-VAL-DE-Ruhr campaign in the Rhine-Ruhr region. The measurements are used to validate spaceborne NO2 data products from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). Auxiliary data of the TROPOMI NO2 retrieval, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity, and cloud treatment are investigated to evaluate their impact.
Peng Yuan, Geoffrey Blewitt, Corné Kreemer, William C. Hammond, Donald Argus, Xungang Yin, Roeland Van Malderen, Michael Mayer, Weiping Jiang, Joseph Awange, and Hansjörg Kutterer
Earth Syst. Sci. Data, 15, 723–743,Short summary
We developed a 5 min global integrated water vapour (IWV) product from 12 552 ground-based GPS stations in 2020. It contains more than 1 billion IWV estimates. The dataset is an enhanced version of the existing operational GPS IWV dataset from the Nevada Geodetic Laboratory. The enhancement is reached by using accurate meteorological information from ERA5 for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. The dataset is recommended for high-accuracy applications.
Rodriguez Yombo Phaka, Alexis Merlaud, Gaia Pinardi, Martina M. Friedrich, François Hendrick, Jean-François Müller, Jenny Stavrakou, Isabelle De Smedt, Ermioni Dimitropoulou, Richard Bopili Mbotia Lepiba, Edmond Phuku Phuati, Buenimio Lomami Djibi, Lars Jacob, Caroline Fayt, Michel Van Roozendael, Jean-Perre Mbungu Tsumbu, and Emmanuel Mahieu
Atmos. Meas. Tech. Discuss.,
Revised manuscript accepted for AMTShort summary
We present air quality measurements in Kinshasa, Democratic Republic of the Congo, performed with a newly developed instrument which was installed on a roof of the University of Kinshasa in November 2019. The instrument records spectra of the scattered sun light, from which we derive the abundances of nitrogen dioxide and formaldehyde, two important pollutants. We compare our ground-based measurements with those of a satellite, namely TROPOMI; and TROPOMI with a chemistry model, GEOS-Chem.
Sophie Godin-Beekmann, Niramson Azouz, Viktoria F. Sofieva, Daan Hubert, Irina Petropavlovskikh, Peter Effertz, Gérard Ancellet, Doug A. Degenstein, Daniel Zawada, Lucien Froidevaux, Stacey Frith, Jeannette Wild, Sean Davis, Wolfgang Steinbrecht, Thierry Leblanc, Richard Querel, Kleareti Tourpali, Robert Damadeo, Eliane Maillard Barras, René Stübi, Corinne Vigouroux, Carlo Arosio, Gerald Nedoluha, Ian Boyd, Roeland Van Malderen, Emmanuel Mahieu, Dan Smale, and Ralf Sussmann
Atmos. Chem. Phys., 22, 11657–11673,Short summary
An updated evaluation up to 2020 of stratospheric ozone profile long-term trends at extrapolar latitudes based on satellite and ground-based records is presented. Ozone increase in the upper stratosphere is confirmed, with significant trends at most latitudes. In this altitude region, a very good agreement is found with trends derived from chemistry–climate model simulations. Observed and modelled trends diverge in the lower stratosphere, but the differences are non-significant.
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351,Short summary
Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
Ermioni Dimitropoulou, François Hendrick, Martina Michaela Friedrich, Frederik Tack, Gaia Pinardi, Alexis Merlaud, Caroline Fayt, Christian Hermans, Frans Fierens, and Michel Van Roozendael
Atmos. Meas. Tech., 15, 4503–4529,Short summary
A total of 2 years of dual-scan ground-based MAX-DOAS measurements of tropospheric NO2 and aerosols in Uccle (Belgium) have been used to develop a new optimal-estimation-based inversion approach to retrieve horizontal profiles of surface NO2 concentration and aerosol extinction profiles. We show that the combination of an appropriate sampling of TROPOMI pixels by ground-based measurements and an adequate a priori NO2 profile shape in TROPOMI retrievals improves the agreement between datasets.
Sieglinde Callewaert, Jérôme Brioude, Bavo Langerock, Valentin Duflot, Dominique Fonteyn, Jean-François Müller, Jean-Marc Metzger, Christian Hermans, Nicolas Kumps, Michel Ramonet, Morgan Lopez, Emmanuel Mahieu, and Martine De Mazière
Atmos. Chem. Phys., 22, 7763–7792,Short summary
A regional atmospheric transport model is used to analyze the factors contributing to CO2, CH4, and CO observations at Réunion Island. We show that the surface observations are dominated by local fluxes and dynamical processes, while the column data are influenced by larger-scale mechanisms such as biomass burning plumes. The model is able to capture the measured time series well; however, the results are highly dependent on accurate boundary conditions and high-resolution emission inventories.
Gérard Ancellet, Sophie Godin-Beekmann, Herman G. J. Smit, Ryan M. Stauffer, Roeland Van Malderen, Renaud Bodichon, and Andrea Pazmiño
Atmos. Meas. Tech., 15, 3105–3120,Short summary
The 1991–2021 Observatoire de Haute Provence electrochemical concentration cell (ECC) ozonesonde data have been homogenized according to the recommendations of the Ozonesonde Data Quality Assessment panel. Comparisons with ground-based instruments also measuring ozone at the same station (lidar, surface measurements) and with colocated satellite observations show the benefits of this homogenization. Remaining differences between ECC and other observations in the stratosphere are also discussed.
Nora Mettig, Mark Weber, Alexei Rozanov, John P. Burrows, Pepijn Veefkind, Anne M. Thompson, Ryan M. Stauffer, Thierry Leblanc, Gerard Ancellet, Michael J. Newchurch, Shi Kuang, Rigel Kivi, Matthew B. Tully, Roeland Van Malderen, Ankie Piters, Bogumil Kois, René Stübi, and Pavla Skrivankova
Atmos. Meas. Tech., 15, 2955–2978,Short summary
Vertical ozone profiles from combined spectral measurements in the UV and IR spectral ranges were retrieved by using data from TROPOMI/S5P and CrIS/Suomi-NPP. The vertical resolution and accuracy of the ozone profiles are improved by combining both wavelength ranges compared to retrievals limited to UV or IR spectral data only. The advancement of our TOPAS algorithm for combined measurements is required because in the UV-only retrieval the vertical resolution in the troposphere is very limited.
Christophe Lerot, François Hendrick, Michel Van Roozendael, Leonardo M. A. Alvarado, Andreas Richter, Isabelle De Smedt, Nicolas Theys, Jonas Vlietinck, Huan Yu, Jeroen Van Gent, Trissevgeni Stavrakou, Jean-François Müller, Pieter Valks, Diego Loyola, Hitoshi Irie, Vinod Kumar, Thomas Wagner, Stefan F. Schreier, Vinayak Sinha, Ting Wang, Pucai Wang, and Christian Retscher
Atmos. Meas. Tech., 14, 7775–7807,Short summary
Global measurements of glyoxal tropospheric columns from the satellite instrument TROPOMI are presented. Such measurements can contribute to the estimation of atmospheric emissions of volatile organic compounds. This new glyoxal product has been fully characterized with a comprehensive error budget, with comparison with other satellite data sets as well as with validation based on independent ground-based remote sensing glyoxal observations.
Sharmine Akter Simu, Yuzo Miyazaki, Eri Tachibana, Henning Finkenzeller, Jérôme Brioude, Aurélie Colomb, Olivier Magand, Bert Verreyken, Stephanie Evan, Rainer Volkamer, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 21, 17017–17029,Short summary
The tropical Indian Ocean (IO) is expected to be a significant source of water-soluble organic carbon (WSOC), which is relevant to cloud formation. Our study showed that marine secondary organic formation dominantly contributed to the aerosol WSOC mass at the high-altitude observatory in the southwest IO in the wet season in both marine boundary layer and free troposphere (FT). This suggests that the effect of marine secondary sources is important up to FT, a process missing in climate models.
Bert Verreyken, Crist Amelynck, Niels Schoon, Jean-François Müller, Jérôme Brioude, Nicolas Kumps, Christian Hermans, Jean-Marc Metzger, Aurélie Colomb, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 21, 12965–12988,Short summary
We present a 2-year dataset of trace gas concentrations, specifically an array of volatile organic compounds (VOCs), recorded at the Maïdo observatory, a remote tropical high-altitude site located on a small island in the southwest Indian Ocean. We found that island-scale transport is an important driver for the daily cycle of VOC concentrations. During the day, surface emissions from the island affect the atmospheric composition at Maïdo greatly, while at night this impact is strongly reduced.
Thierno Doumbia, Claire Granier, Nellie Elguindi, Idir Bouarar, Sabine Darras, Guy Brasseur, Benjamin Gaubert, Yiming Liu, Xiaoqin Shi, Trissevgeni Stavrakou, Simone Tilmes, Forrest Lacey, Adrien Deroubaix, and Tao Wang
Earth Syst. Sci. Data, 13, 4191–4206,Short summary
Most countries around the world have implemented control measures to combat the spread of the COVID-19 pandemic, resulting in significant changes in economic and personal activities. We developed the CONFORM (COvid-19 adjustmeNt Factors fOR eMissions) dataset to account for changes in emissions during lockdowns. This dataset was created with the intention of being directly applicable to existing global and regional inventories used in chemical transport models.
Roeland Van Malderen, Dirk De Muer, Hugo De Backer, Deniz Poyraz, Willem W. Verstraeten, Veerle De Bock, Andy W. Delcloo, Alexander Mangold, Quentin Laffineur, Marc Allaart, Frans Fierens, and Valérie Thouret
Atmos. Chem. Phys., 21, 12385–12411,Short summary
The main aim of initiating measurements of the vertical distribution of the ozone concentration by means of ozonesondes attached to weather balloons at Uccle in 1969 was to improve weather forecasts. Since then, this measurement technique has barely changed, but the dense, long-term, and homogeneous Uccle dataset currently remains crucial for studying the temporal evolution of ozone from the surface to the stratosphere and is also the backbone of the validation of satellite ozone retrievals.
Beata Opacka, Jean-François Müller, Trissevgeni Stavrakou, Maite Bauwens, Katerina Sindelarova, Jana Markova, and Alex B. Guenther
Atmos. Chem. Phys., 21, 8413–8436,Short summary
Isoprene is mainly emitted from plants, and about 80 % of its global emissions occur in the tropics. Current isoprene inventories are usually based on modelled vegetation maps, but high pressure on land use over the last decades has led to severe losses, especially in tropical forests, that are not considered by models. We provide a study on the present-day impact of spaceborne land cover changes on isoprene emissions and the first inventory based on high-resolution Landsat tree cover dataset.
Thomas Wagner, Steffen Beirle, Steffen Dörner, Christian Borger, and Roeland Van Malderen
Atmos. Chem. Phys., 21, 5315–5353,Short summary
A global long-term (1995–2015) data set of total column water vapour (TCWV) derived from satellite observations is used to quantify the influence of teleconnections. Based on a newly developed empirical method more than 40 teleconnection indices are significantly detected in our global TCWV data set. After orthogonalisation, only 20 indices are left significant. The global distribution of the cumulative influence of teleconnection indices is strongest in the tropics and high latitudes.
Ioanna Skoulidou, Maria-Elissavet Koukouli, Astrid Manders, Arjo Segers, Dimitris Karagkiozidis, Myrto Gratsea, Dimitris Balis, Alkiviadis Bais, Evangelos Gerasopoulos, Trisevgeni Stavrakou, Jos van Geffen, Henk Eskes, and Andreas Richter
Atmos. Chem. Phys., 21, 5269–5288,Short summary
The performance of LOTOS-EUROS v2.2.001 regional chemical transport model NO2 simulations is investigated over Greece from June to December 2018. Comparison with in situ NO2 measurements shows a spatial correlation coefficient of 0.86, while the model underestimates the concentrations mostly during daytime (12 to 15:00 local time). Further, the simulated tropospheric NO2 columns are evaluated against ground-based MAX-DOAS NO2 measurements and S5P/TROPOMI observations for July and December 2018.
Frederik Tack, Alexis Merlaud, Marian-Daniel Iordache, Gaia Pinardi, Ermioni Dimitropoulou, Henk Eskes, Bart Bomans, Pepijn Veefkind, and Michel Van Roozendael
Atmos. Meas. Tech., 14, 615–646,Short summary
We assess the TROPOMI tropospheric NO2 product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) based on coinciding airborne APEX reference observations (~75 m × 120 m), acquired over polluted regions in Belgium. The TROPOMI NO2 product meets the mission requirements in terms of precision and accuracy. However, we show that TROPOMI is biased low over polluted areas, mainly due to the limited spatial resolution of a priori input for the AMF computation.
Jan-Lukas Tirpitz, Udo Frieß, François Hendrick, Carlos Alberti, Marc Allaart, Arnoud Apituley, Alkis Bais, Steffen Beirle, Stijn Berkhout, Kristof Bognar, Tim Bösch, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Mirjam den Hoed, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Martina M. Friedrich, Arnoud Frumau, Lou Gast, Clio Gielen, Laura Gomez-Martín, Nan Hao, Arjan Hensen, Bas Henzing, Christian Hermans, Junli Jin, Karin Kreher, Jonas Kuhn, Johannes Lampel, Ang Li, Cheng Liu, Haoran Liu, Jianzhong Ma, Alexis Merlaud, Enno Peters, Gaia Pinardi, Ankie Piters, Ulrich Platt, Olga Puentedura, Andreas Richter, Stefan Schmitt, Elena Spinei, Deborah Stein Zweers, Kimberly Strong, Daan Swart, Frederik Tack, Martin Tiefengraber, René van der Hoff, Michel van Roozendael, Tim Vlemmix, Jan Vonk, Thomas Wagner, Yang Wang, Zhuoru Wang, Mark Wenig, Matthias Wiegner, Folkard Wittrock, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 14, 1–35,Short summary
Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a ground-based remote sensing measurement technique that derives atmospheric aerosol and trace gas vertical profiles from skylight spectra. In this study, consistency and reliability of MAX-DOAS profiles are assessed by applying nine different evaluation algorithms to spectral data recorded during an intercomparison campaign in the Netherlands and by comparing the results to colocated supporting observations.
Bert Verreyken, Crist Amelynck, Jérôme Brioude, Jean-François Müller, Niels Schoon, Nicolas Kumps, Aurélie Colomb, Jean-Marc Metzger, Christopher F. Lee, Theodore K. Koenig, Rainer Volkamer, and Trissevgeni Stavrakou
Atmos. Chem. Phys., 20, 14821–14845,Short summary
Biomass burning (BB) plumes arriving at the Maïdo observatory located in the south-west Indian Ocean during August 2018 and August 2019 are studied using trace gas measurements, Lagrangian transport models and the CAMS near-real-time atmospheric composition service. We investigate (i) secondary production of volatile organic compounds during transport, (ii) efficacy of the CAMS model to reproduce the chemical makeup of BB plumes and (iii) the impact of BB on the remote marine boundary layer.
Holger Vömel, Herman G. J. Smit, David Tarasick, Bryan Johnson, Samuel J. Oltmans, Henry Selkirk, Anne M. Thompson, Ryan M. Stauffer, Jacquelyn C. Witte, Jonathan Davies, Roeland van Malderen, Gary A. Morris, Tatsumi Nakano, and Rene Stübi
Atmos. Meas. Tech., 13, 5667–5680,Short summary
The time response of electrochemical concentration cell (ECC) ozonesondes points to at least two distinct reaction pathways with time constants of approximately 20 s and 25 min. Properly considering these time constants eliminates the need for a poorly defined "background" and allows reducing ad hoc corrections based on laboratory tests. This reduces the uncertainty of ECC ozonesonde measurements throughout the profile and especially in regions of low ozone and strong gradients of ozone.
Alexis Merlaud, Livio Belegante, Daniel-Eduard Constantin, Mirjam Den Hoed, Andreas Carlos Meier, Marc Allaart, Magdalena Ardelean, Maxim Arseni, Tim Bösch, Hugues Brenot, Andreea Calcan, Emmanuel Dekemper, Sebastian Donner, Steffen Dörner, Mariana Carmelia Balanica Dragomir, Lucian Georgescu, Anca Nemuc, Doina Nicolae, Gaia Pinardi, Andreas Richter, Adrian Rosu, Thomas Ruhtz, Anja Schönhardt, Dirk Schuettemeyer, Reza Shaiganfar, Kerstin Stebel, Frederik Tack, Sorin Nicolae Vâjâiac, Jeni Vasilescu, Jurgen Vanhamel, Thomas Wagner, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 5513–5535,Short summary
The AROMAT campaigns took place in Romania in 2014 and 2015. They aimed to test airborne observation systems dedicated to air quality studies and to verify the concept of such campaigns in support of the validation of space-borne atmospheric missions. We show that airborne measurements of NO2 can be valuable for the validation of air quality satellites. For H2CO and SO2, the validation should involve ground-based measurement systems at key locations that the AROMAT measurements help identify.
Ermioni Dimitropoulou, François Hendrick, Gaia Pinardi, Martina M. Friedrich, Alexis Merlaud, Frederik Tack, Helene De Longueville, Caroline Fayt, Christian Hermans, Quentin Laffineur, Frans Fierens, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 5165–5191,Short summary
We present 1 year of dual-scan ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of aerosol and tropospheric NO2 in Uccle (Belgium). Measuring tropospheric NO2 vertical column densities (VCDs) in different azimuthal directions has a positive effect on comparison with measurements from TROPOMI. We prove that the use of inadequate a priori NO2 profile shape data in the TROPOMI retrieval is responsible for the systematic underestimation of S5P NO2 data.
Karin Kreher, Michel Van Roozendael, Francois Hendrick, Arnoud Apituley, Ermioni Dimitropoulou, Udo Frieß, Andreas Richter, Thomas Wagner, Johannes Lampel, Nader Abuhassan, Li Ang, Monica Anguas, Alkis Bais, Nuria Benavent, Tim Bösch, Kristof Bognar, Alexander Borovski, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Henning Finkenzeller, David Garcia-Nieto, Clio Gielen, Laura Gómez-Martín, Nan Hao, Bas Henzing, Jay R. Herman, Christian Hermans, Syedul Hoque, Hitoshi Irie, Junli Jin, Paul Johnston, Junaid Khayyam Butt, Fahim Khokhar, Theodore K. Koenig, Jonas Kuhn, Vinod Kumar, Cheng Liu, Jianzhong Ma, Alexis Merlaud, Abhishek K. Mishra, Moritz Müller, Monica Navarro-Comas, Mareike Ostendorf, Andrea Pazmino, Enno Peters, Gaia Pinardi, Manuel Pinharanda, Ankie Piters, Ulrich Platt, Oleg Postylyakov, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Alfonso Saiz-Lopez, Anja Schönhardt, Stefan F. Schreier, André Seyler, Vinayak Sinha, Elena Spinei, Kimberly Strong, Frederik Tack, Xin Tian, Martin Tiefengraber, Jan-Lukas Tirpitz, Jeroen van Gent, Rainer Volkamer, Mihalis Vrekoussis, Shanshan Wang, Zhuoru Wang, Mark Wenig, Folkard Wittrock, Pinhua H. Xie, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 13, 2169–2208,Short summary
In September 2016, 36 spectrometers from 24 institutes measured a number of key atmospheric pollutants during an instrument intercomparison campaign (CINDI-2) at Cabauw, the Netherlands. Here we report on the outcome of this intercomparison exercise. The three major goals were to characterise the differences between the participating instruments, to define a robust methodology for performance assessment, and to contribute to the harmonisation of the measurement settings and retrieval methods.
Helen M. Worden, A. Anthony Bloom, John R. Worden, Zhe Jiang, Eloise A. Marais, Trissevgeni Stavrakou, Benjamin Gaubert, and Forrest Lacey
Atmos. Chem. Phys., 19, 13569–13579,Short summary
Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation play a significant role in air quality and climate. However, there are large uncertainties in their role for climate. We present a Bayesian approach to estimate carbon monoxide fluxes that are chemically produced from biogenic sources. This provides independent constraints on models that predict biogenic emissions in order improve their capability for predicting air quality and future climate scenarios.
Jean-François Müller, Trissevgeni Stavrakou, and Jozef Peeters
Geosci. Model Dev., 12, 2307–2356,Short summary
A new oxidation mechanism for biogenic volatile organic compounds is presented and implemented in the large-scale chemistry transport model MAGRITTE. The mechanism accounts for all major recent advances regarding isoprene oxidation. Evaluation against airborne measurements over the US demonstrates a good overall agreement. The mechanism incorporates newly-proposed pathways for formic and acetic acid formation, representing ~ 20 % of their global identified source.
Frederik Tack, Alexis Merlaud, Andreas C. Meier, Tim Vlemmix, Thomas Ruhtz, Marian-Daniel Iordache, Xinrui Ge, Len van der Wal, Dirk Schuettemeyer, Magdalena Ardelean, Andreea Calcan, Daniel Constantin, Anja Schönhardt, Koen Meuleman, Andreas Richter, and Michel Van Roozendael
Atmos. Meas. Tech., 12, 211–236,Short summary
We present an intercomparison study of four airborne imaging DOAS instruments, dedicated to the retrieval and high-resolution mapping of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs). The AROMAPEX campaign took place in Berlin, Germany, in April 2016 with the primary objectives (1) to test and intercompare the performance of experimental airborne imagers and (2) to prepare the validation and calibration campaigns for the Sentinel-5 Precursor/TROPOMI mission.
Jean-François Müller, Trissevgeni Stavrakou, Maite Bauwens, Steven Compernolle, and Jozef Peeters
Geosci. Model Dev. Discuss.,
Publication in GMD not foreseenShort summary
A new dry deposition model for gaseous species is presented. It relies on the species reactivity and water-solubility, for which a new prediction method is also presented. The deposition model parameters are adjusted based on comparisons with field data for ozone and organic compounds at numerous sites. The importance of dry deposition as a sink of oxygenated organic compounds and nitrogen oxides is demonstrated by global model simulations with the new deposition scheme.
Julie Berckmans, Roeland Van Malderen, Eric Pottiaux, Rosa Pacione, and Rafiq Hamdi
Atmos. Chem. Phys. Discuss.,
Preprint withdrawnShort summary
The use of ground-based observations is suitable for the assessment of atmospheric water vapour in climate models. We used water vapour observations from 100 European sites to evaluate two models: a reanalysis product and a regional climate model. The results reveal patterns in the water vapour distribution both in time and space that are relevant as water vapour plays a key role in the feedback process of a changing climate.
Roeland Van Malderen, Eric Pottiaux, Gintautas Stankunavicius, Steffen Beirle, Thomas Wagner, Hugues Brenot, and Carine Bruyninx
Atmos. Chem. Phys. Discuss.,
Revised manuscript not acceptedShort summary
The study investigates the long-term time variability of the integrated water vapour retrieved by different techniques (GPS, UV/VIS satellites and numerical weather prediction reanalyses) for a global dataset of almost 120 sites and for the time period 1995–2010. A stepwise multiple linear regression technique is applied to ascribe the time variability of integrated water vapour to surface measurements at the sites, but also using teleconnection patterns or climate/oceanic indices.
Corinne Vigouroux, Carlos Augusto Bauer Aquino, Maite Bauwens, Cornelis Becker, Thomas Blumenstock, Martine De Mazière, Omaira García, Michel Grutter, César Guarin, James Hannigan, Frank Hase, Nicholas Jones, Rigel Kivi, Dmitry Koshelev, Bavo Langerock, Erik Lutsch, Maria Makarova, Jean-Marc Metzger, Jean-François Müller, Justus Notholt, Ivan Ortega, Mathias Palm, Clare Paton-Walsh, Anatoly Poberovskii, Markus Rettinger, John Robinson, Dan Smale, Trissevgeni Stavrakou, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, and Geoffrey Toon
Atmos. Meas. Tech., 11, 5049–5073,Short summary
A few ground-based stations have provided time series of HCHO columns until now, which was not optimal for providing good diagnostics for satellite or model validation. In this work, HCHO time series have been determined in a harmonized way at 21 stations ensuring, in addition to a better spatial and level of abundances coverage, that internal biases within the network have been minimized. This data set shows consistent good agreement with model data and is ready for future satellite validation.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Bert Van Schaeybroeck, Lesley De Cruz, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Quentin Laffineur, Crist Amelynck, Niels Schoon, Bernard Heinesch, Thomas Holst, Almut Arneth, Reinhart Ceulemans, Arturo Sanchez-Lorenzo, and Alex Guenther
Biogeosciences, 15, 3673–3690,Short summary
Biogenic isoprene fluxes are simulated over Europe with the MEGAN–MOHYCAN model for the recent past and end-of-century climate at high spatiotemporal resolution (0.1°, 3 min). Due to climate change, fluxes increased by 40 % over 1979–2014. Climate scenarios for 2070–2099 suggest an increase by 83 % due to climate, and an even stronger increase when the potential impact of CO2 fertilization is considered (up to 141 %). Accounting for CO2 inhibition cancels out a large part of these increases.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, Pawan K. Bhartia, Zhaonan Cai, Marc Allaart, Gérard Ancellet, Bertrand Calpini, Gerrie J. R. Coetzee, Emilio Cuevas-Agulló, Manuel Cupeiro, Hugo De Backer, Manvendra K. Dubey, Henry E. Fuelberg, Masatomo Fujiwara, Sophie Godin-Beekmann, Tristan J. Hall, Bryan Johnson, Everette Joseph, Rigel Kivi, Bogumil Kois, Ninong Komala, Gert König-Langlo, Giovanni Laneve, Thierry Leblanc, Marion Marchand, Kenneth R. Minschwaner, Gary Morris, Michael J. Newchurch, Shin-Ya Ogino, Nozomu Ohkawara, Ankie J. M. Piters, Françoise Posny, Richard Querel, Rinus Scheele, Frank J. Schmidlin, Russell C. Schnell, Otto Schrems, Henry Selkirk, Masato Shiotani, Pavla Skrivánková, René Stübi, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Valérie Thouret, Matthew B. Tully, Roeland Van Malderen, Holger Vömel, Peter von der Gathen, Jacquelyn C. Witte, and Margarita Yela
Atmos. Meas. Tech., 10, 2455–2475,Short summary
It is essential to understand the data quality of +10-year OMI ozone product and impacts of the “row anomaly” (RA). We validate the OMI Ozone Profile (PROFOZ) product from Oct 2004 to Dec 2014 against ozonesonde observations globally. Generally, OMI has good agreement with ozonesondes. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability.
Frederik Tack, Alexis Merlaud, Marian-Daniel Iordache, Thomas Danckaert, Huan Yu, Caroline Fayt, Koen Meuleman, Felix Deutsch, Frans Fierens, and Michel Van Roozendael
Atmos. Meas. Tech., 10, 1665–1688,Short summary
This paper presents retrieval results of NO2 vertical column densities mapped at high spatial resolution over three Belgian cities, based on the DOAS analysis of Airborne APEX observations. A major objective of the study is to assess the technical and operational capabilities of the APEX hyperspectral pushbroom imager to map the NO2 horizontal distribution field over urbanised areas.
Yang Wang, Steffen Beirle, Johannes Lampel, Mariliza Koukouli, Isabelle De Smedt, Nicolas Theys, Ang Li, Dexia Wu, Pinhua Xie, Cheng Liu, Michel Van Roozendael, Trissevgeni Stavrakou, Jean-François Müller, and Thomas Wagner
Atmos. Chem. Phys., 17, 5007–5033,Short summary
A long-term MAX-DOAS measurement from 2011 to 2014 was operated in Wuxi, part of the most industrialized area of the Yangtze River delta region of China. The tropospheric VCDs and vertical profiles of NO2, SO2 and HCHO derived from the MAX-DOAS are used to validate the products derived from OMI and GOME-2A/B by different scientific teams (daily- and bimonthly-averaged data). We investigate the effects of clouds, aerosols and a priori profile shapes on satellite retrievals of tropospheric VCDs.
Clio Gielen, François Hendrick, Gaia Pinardi, Isabelle De Smedt, Caroline Fayt, Christian Hermans, Trissevgeni Stavrakou, Maite Bauwens, Jean-Francois Müller, Eugène Ndenzako, Pierre Nzohabonayo, Rachel Akimana, Sebastien Niyonzima, Michel Van Roozendael, and Martine De Mazière
Atmos. Chem. Phys. Discuss.,
Revised manuscript has not been submittedShort summary
In this paper we study the composition of the lower atmosphere above the Central-African capital city of Burundi (Bujumbura) by measuring the amount of aerosol dust particles and trace gases in the air. We find that the aerosol and trace gas seasonal and daily variation is driven by the alternation of rain periods and dry periods associated with intense biomass burning in the vicinity of Bujumbura, and the influence of human activities in the city center.
Roeland Van Malderen, Marc A. F. Allaart, Hugo De Backer, Herman G. J. Smit, and Dirk De Muer
Atmos. Meas. Tech., 9, 3793–3816,Short summary
Thanks to the Montreal Protocol regulations for ozone-depleting substances, the decline of ozone concentrations has been stopped. A remaining major issue today is if the onset of ozone recovery can be detected. Ozonesondes have provided vertical distribution of ozone with high vertical resolution for several decades. In this study, we investigate how different operating procedures at ozonesonde stations and different ozonesonde data correction strategies affect trends in ozone concentrations.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Isabelle De Smedt, Michel Van Roozendael, Guido R. van der Werf, Christine Wiedinmyer, Johannes W. Kaiser, Katerina Sindelarova, and Alex Guenther
Atmos. Chem. Phys., 16, 10133–10158,Short summary
Relying on a 9-year record of satellite observations of formaldehyde, we use inverse techniques to derive global top–down hydrocarbon fluxes over 2005–2013, infer seasonal and interannual variability, and detect emission trends. Our results suggest changes in fire seasonal patterns, a stronger contribution of agricultural burning, overestimated isoprene flux rates in the tropics, overly decreased isoprene emissions due to soil moisture stress in arid areas, and enhanced isoprene trends.
Matthieu Pommier, Cathy Clerbaux, Pierre-François Coheur, Emmanuel Mahieu, Jean-François Müller, Clare Paton-Walsh, Trissevgeni Stavrakou, and Corinne Vigouroux
Atmos. Chem. Phys., 16, 8963–8981,Short summary
This work presents for the first time 7 years of formic acid (HCOOH) measurements recorded by the satellite instrument, IASI. The comparison of the data set with ground-based FTIR measurements and a CTM shows the interannual and the seasonal variation are well captured. Global distributions are provided, highlighting the long-range transport of tropospheric HCOOH over the oceans and the detection of source regions e.g. over India, USA, and Africa.
Daan Hubert, Jean-Christopher Lambert, Tijl Verhoelst, José Granville, Arno Keppens, Jean-Luc Baray, Adam E. Bourassa, Ugo Cortesi, Doug A. Degenstein, Lucien Froidevaux, Sophie Godin-Beekmann, Karl W. Hoppel, Bryan J. Johnson, Erkki Kyrölä, Thierry Leblanc, Günter Lichtenberg, Marion Marchand, C. Thomas McElroy, Donal Murtagh, Hideaki Nakane, Thierry Portafaix, Richard Querel, James M. Russell III, Jacobo Salvador, Herman G. J. Smit, Kerstin Stebel, Wolfgang Steinbrecht, Kevin B. Strawbridge, René Stübi, Daan P. J. Swart, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Joachim Urban, Joanna A. E. van Gijsel, Roeland Van Malderen, Peter von der Gathen, Kaley A. Walker, Elian Wolfram, and Joseph M. Zawodny
Atmos. Meas. Tech., 9, 2497–2534,Short summary
A more detailed understanding of satellite O3 profile data records is vital for further progress in O3 research. To this end, we made a comprehensive assessment of 14 limb/occultation profilers using ground-based reference data. The mutual consistency of satellite O3 in terms of bias, short-term variability and decadal stability is generally good over most of the stratosphere. However, we identified some exceptions that impact the quality of recently merged data sets and ozone trend assessments.
Eliane G. Alves, Kolby Jardine, Julio Tota, Angela Jardine, Ana Maria Yãnez-Serrano, Thomas Karl, Julia Tavares, Bruce Nelson, Dasa Gu, Trissevgeni Stavrakou, Scot Martin, Paulo Artaxo, Antonio Manzi, and Alex Guenther
Atmos. Chem. Phys., 16, 3903–3925,Short summary
For a long time, it was thought that tropical rainforests are evergreen forests and the processes involved in these ecosystems do not change all year long. However, some satellite retrievals have suggested that ecophysiological processes may present seasonal variations mainly due to variation in light and leaf phenology in Amazonia. These in situ measurements are the first showing of a seasonal trend of volatile organic compound emissions, correlating with light and leaf phenology in Amazonia.
I. De Smedt, T. Stavrakou, F. Hendrick, T. Danckaert, T. Vlemmix, G. Pinardi, N. Theys, C. Lerot, C. Gielen, C. Vigouroux, C. Hermans, C. Fayt, P. Veefkind, J.-F. Müller, and M. Van Roozendael
Atmos. Chem. Phys., 15, 12519–12545,Short summary
We present the new version of the BIRA-IASB algorithm for the retrieval of H2CO columns from OMI and GOME-2A and B measurements. Validation results at seven stations in Europe, China and Africa confirm the capacity of the satellite measurements to resolve diurnal variations in H2CO columns. Furthermore, vertical profiles derived from MAX-DOAS measurements in Beijing and in Bujumbura are used for a more detailed validation exercise. Finally trends are estimated using 10 years of OMI observations.
T. Stavrakou, J.-F. Müller, M. Bauwens, I. De Smedt, M. Van Roozendael, M. De Mazière, C. Vigouroux, F. Hendrick, M. George, C. Clerbaux, P.-F. Coheur, and A. Guenther
Atmos. Chem. Phys., 15, 11861–11884,Short summary
Formaldehyde columns from two space sensors, GOME-2 and OMI, constrain by inverse modeling the global emissions of HCHO precursors in 2010. The resulting biogenic and pyrogenic fluxes from both optimizations show a very good degree of consistency. The isoprene fluxes are reduced globally by ca. 10%, and emissions from fires decrease by ca. 35%, compared to the prior. Anthropogenic emissions are weakly constrained except over China. Sensitivity inversions show robustness of the inferred fluxes.
F. Tack, F. Hendrick, F. Goutail, C. Fayt, A. Merlaud, G. Pinardi, C. Hermans, J.-P. Pommereau, and M. Van Roozendael
Atmos. Meas. Tech., 8, 2417–2435,Short summary
An algorithm is presented for retrieving tropospheric NO2 vertical column densities from ground-based zenith-sky (ZS) measurements of scattered sunlight. The different steps are fully characterized and recommendations are given for each of them. The retrieval algorithm is applied on a 2-month ZS data set acquired during the CINDI campaign and on a 2-year data set acquired at the OHP NDACC station. The error budget assessment indicates that the overall error on the column values is less than 28%.
B. Franco, F. Hendrick, M. Van Roozendael, J.-F. Müller, T. Stavrakou, E. A. Marais, B. Bovy, W. Bader, C. Fayt, C. Hermans, B. Lejeune, G. Pinardi, C. Servais, and E. Mahieu
Atmos. Meas. Tech., 8, 1733–1756,Short summary
Formaldehyde (HCHO) amounts are obtained from ground-based Fourier transform infrared solar spectra and UV-visible Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) scans recorded at the Jungfraujoch station (46.5°N, 8.0°E, 3580m a.s.l.). Using HCHO amounts simulated by the chemical transport models GEOS-Chem and IMAGES as intermediates, comparisons reveal that FTIR and MAX-DOAS provide complementary products for the HCHO retrieval.
S. Compernolle and J.-F. Müller
Atmos. Chem. Phys., 14, 12815–12837,Short summary
Aqueous phase occurs in the atmosphere as cloud droplets and aqueous aerosol. The Henry's law constant regulates the water-gas partitioning of a molecule, but experimental data on polyols are limited. New values are derived for molecules with 2-6 hydroxyl groups, by combining other thermophysical data (e.g. vapour pressure, water activity, solubility). It is analysed which molecules will stay mostly in the gas phase, and which will preferably partition to droplet or aqueous aerosol.
W. Bader, T. Stavrakou, J.-F. Muller, S. Reimann, C. D. Boone, J. J. Harrison, O. Flock, B. Bovy, B. Franco, B. Lejeune, C. Servais, and E. Mahieu
Atmos. Meas. Tech., 7, 3861–3872,
V. De Bock, H. De Backer, R. Van Malderen, A. Mangold, and A. Delcloo
Atmos. Chem. Phys., 14, 12251–12270,
K. Tsigaridis, N. Daskalakis, M. Kanakidou, P. J. Adams, P. Artaxo, R. Bahadur, Y. Balkanski, S. E. Bauer, N. Bellouin, A. Benedetti, T. Bergman, T. K. Berntsen, J. P. Beukes, H. Bian, K. S. Carslaw, M. Chin, G. Curci, T. Diehl, R. C. Easter, S. J. Ghan, S. L. Gong, A. Hodzic, C. R. Hoyle, T. Iversen, S. Jathar, J. L. Jimenez, J. W. Kaiser, A. Kirkevåg, D. Koch, H. Kokkola, Y. H Lee, G. Lin, X. Liu, G. Luo, X. Ma, G. W. Mann, N. Mihalopoulos, J.-J. Morcrette, J.-F. Müller, G. Myhre, S. Myriokefalitakis, N. L. Ng, D. O'Donnell, J. E. Penner, L. Pozzoli, K. J. Pringle, L. M. Russell, M. Schulz, J. Sciare, Ø. Seland, D. T. Shindell, S. Sillman, R. B. Skeie, D. Spracklen, T. Stavrakou, S. D. Steenrod, T. Takemura, P. Tiitta, S. Tilmes, H. Tost, T. van Noije, P. G. van Zyl, K. von Salzen, F. Yu, Z. Wang, Z. Wang, R. A. Zaveri, H. Zhang, K. Zhang, Q. Zhang, and X. Zhang
Atmos. Chem. Phys., 14, 10845–10895,
K. Sindelarova, C. Granier, I. Bouarar, A. Guenther, S. Tilmes, T. Stavrakou, J.-F. Müller, U. Kuhn, P. Stefani, and W. Knorr
Atmos. Chem. Phys., 14, 9317–9341,
R. Van Malderen, H. Brenot, E. Pottiaux, S. Beirle, C. Hermans, M. De Mazière, T. Wagner, H. De Backer, and C. Bruyninx
Atmos. Meas. Tech., 7, 2487–2512,
D. Lauwaet, P. Viaene, E. Brisson, N.P.M. van Lipzig, T. van Noije, A. Strunk, S. Van Looy, N. Veldeman, L. Blyth, K. De Ridder, and S. Janssen
Atmos. Chem. Phys., 14, 5893–5904,
T. Stavrakou, J.-F. Müller, M. Bauwens, I. De Smedt, M. Van Roozendael, A. Guenther, M. Wild, and X. Xia
Atmos. Chem. Phys., 14, 4587–4605,
S. Compernolle and J.-F. Müller
Atmos. Chem. Phys., 14, 2699–2712,
J.-F. Müller, J. Peeters, and T. Stavrakou
Atmos. Chem. Phys., 14, 2497–2508,
F. Hendrick, J.-F. Müller, K. Clémer, P. Wang, M. De Mazière, C. Fayt, C. Gielen, C. Hermans, J. Z. Ma, G. Pinardi, T. Stavrakou, T. Vlemmix, and M. Van Roozendael
Atmos. Chem. Phys., 14, 765–781,
T. Stavrakou, J.-F. Müller, K. F. Boersma, R. J. van der A, J. Kurokawa, T. Ohara, and Q. Zhang
Atmos. Chem. Phys., 13, 9057–9082,
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Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Geosci. Model Dev., 16, 5323–5338,Short summary
Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev., 16, 5281–5303,Short summary
A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Junsu Gil, Meehye Lee, Jeonghwan Kim, Gangwoong Lee, Joonyoung Ahn, and Cheol-Hee Kim
Geosci. Model Dev., 16, 5251–5263,Short summary
In this study, the framework for calculating reactive nitrogen species using a deep neural network (RND) was developed. It works through simple Python codes and provides high-accuracy reactive nitrogen oxide data. In the first version (RNDv1.0), the model calculates the nitrous acid (HONO) in urban areas, which has an important role in producing O3 and fine aerosol.
Daniel Yazgi and Tinja Olenius
Geosci. Model Dev., 16, 5237–5249,Short summary
We present flexible tools to implement aerosol formation rate predictions in climate and chemical transport models. New-particle formation is a significant but uncertain factor affecting aerosol numbers and an active field within molecular modeling which provides data for assessing formation rates for different chemical species. We introduce tools to generate and interpolate formation rate lookup tables for user-defined data, thus enabling the easy inclusion and testing of formation schemes.
Vineet Yadav, Subhomoy Ghosh, and Charles E. Miller
Geosci. Model Dev., 16, 5219–5236,Short summary
Measuring the performance of inversions in linear Bayesian problems is crucial in real-life applications. In this work, we provide analytical forms of the local and global sensitivities of the estimated fluxes with respect to various inputs. We provide methods to uniquely map the observational signal to spatiotemporal domains. Utilizing this, we also show techniques to assess correlations between the Jacobians that naturally translate to nonstationary covariance matrix components.
Mingzhao Liu, Lars Hoffmann, Sabine Griessbach, Zhongyin Cai, Yi Heng, and Xue Wu
Geosci. Model Dev., 16, 5197–5217,Short summary
We introduce new and revised chemistry and physics modules in the Massive-Parallel Trajectory Calculations (MPTRAC) Lagrangian transport model aiming to improve the representation of volcanic SO2 transport and depletion. We test these modules in a case study of the Ambae eruption in July 2018 in which the SO2 plume underwent wet removal and convection. The lifetime of SO2 shows highly variable and complex dependencies on the atmospheric conditions at different release heights.
Bernhard M. Enz, Jan P. Engelmann, and Ulrike Lohmann
Geosci. Model Dev., 16, 5093–5112,Short summary
An algorithm to track tropical cyclones in model simulation data has been developed. The algorithm uses many combinations of varying parameter thresholds to detect weaker phases of tropical cyclones while still being resilient to false positives. It is shown that the algorithm performs well and adequately represents the tropical cyclone activity of the underlying simulation data. The impact of false positives on overall tropical cyclone activity is shown to be insignificant.
Sepehr Fathi, Mark Gordon, and Yongsheng Chen
Geosci. Model Dev., 16, 5069–5091,Short summary
We have combined various capabilities within a WRF model to generate simulations of atmospheric pollutant dispersion at 50 m resolution. The study objective was to resolve transport processes at the scale of measurements to assess and optimize aircraft-based emission rate retrievals. Model performance evaluation resulted in agreement within 5 % of observed meteorological and within 1–2 standard deviations of observed wind fields. Mass was conserved in the model within 5 % of input emissions.
Dylan Reynolds, Ethan Gutmann, Bert Kruyt, Michael Haugeneder, Tobias Jonas, Franziska Gerber, Michael Lehning, and Rebecca Mott
Geosci. Model Dev., 16, 5049–5068,Short summary
The challenge of running geophysical models is often compounded by the question of where to obtain appropriate data to give as input to a model. Here we present the HICAR model, a simplified atmospheric model capable of running at spatial resolutions of hectometers for long time series or over large domains. This makes physically consistent atmospheric data available at the spatial and temporal scales needed for some terrestrial modeling applications, for example seasonal snow forecasting.
Li Fang, Jianbing Jin, Arjo Segers, Hong Liao, Ke Li, Bufan Xu, Wei Han, Mijie Pang, and Hai Xiang Lin
Geosci. Model Dev., 16, 4867–4882,Short summary
Machine learning models have gained great popularity in air quality prediction. However, they are only available at air quality monitoring stations. In contrast, chemical transport models (CTM) provide predictions that are continuous in the 3D field. Owing to complex error sources, they are typically biased. In this study, we proposed a gridded prediction with high accuracy by fusing predictions from our regional feature selection machine learning prediction (RFSML v1.0) and a CTM prediction.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852,Short summary
A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810,Short summary
We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
Geosci. Model Dev., 16, 4749–4766,Short summary
The Earth's atmosphere can support various types of global-scale waves. Some waves propagate eastward and others westward, and they can have different zonal wavenumbers. The Fourier–wavelet analysis is a useful technique for identifying different components of global-scale waves and their temporal variability. This paper introduces an easy-to-implement method to derive Fourier–wavelet spectra from 2-D space–time data. Application examples are presented using atmospheric models.
Bok H. Baek, Carlie Coats, Siqi Ma, Chi-Tsan Wang, Yunyao Li, Jia Xing, Daniel Tong, Soontae Kim, and Jung-Hun Woo
Geosci. Model Dev., 16, 4659–4676,Short summary
To enable the direct feedback effects of aerosols and local meteorology in an air quality modeling system without any computational bottleneck, we have developed an inline meteorology-induced emissions coupler module within the U.S. Environmental Protection Agency’s Community Multiscale Air Quality modeling system to dynamically model the complex MOtor Vehicle Emission Simulator (MOVES) on-road mobile emissions inline without a separate dedicated emissions processing model like SMOKE.
Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, and Rüdiger Westermann
Geosci. Model Dev., 16, 4617–4638,Short summary
Numerical weather prediction models rely on parameterizations for sub-grid-scale processes, which are a source of uncertainty. We present novel visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along trajectories regarding similarities in temporal development and spatiotemporal relationships. The proposed workflow is applied to cloud microphysical sensitivities along coherent strongly ascending trajectories.
Yingqi Zheng, Minttu Havu, Huizhi Liu, Xueling Cheng, Yifan Wen, Hei Shing Lee, Joyson Ahongshangbam, and Leena Järvi
Geosci. Model Dev., 16, 4551–4579,Short summary
The performance of the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated against the observed surface exchanges (fluxes) of heat and carbon dioxide in a densely built neighborhood in Beijing. The heat flux modeling is noticeably improved by using the observed maximum conductance and by optimizing the vegetation phenology modeling. SUEWS also performs well in simulating carbon dioxide flux.
Simone Dietmüller, Sigrun Matthes, Katrin Dahlmann, Hiroshi Yamashita, Abolfazl Simorgh, Manuel Soler, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Christian Weder, Volker Grewe, Feijia Yin, and Federica Castino
Geosci. Model Dev., 16, 4405–4425,Short summary
Climate-optimized aircraft trajectories avoid atmospheric regions with a large climate impact due to aviation emissions. This requires spatially and temporally resolved information on aviation's climate impact. We propose using algorithmic climate change functions (aCCFs) for CO2 and non-CO2 effects (ozone, methane, water vapor, contrail cirrus). Merged aCCFs combine individual aCCFs by assuming aircraft-specific parameters and climate metrics. Technically this is done with a Python library.
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450,Short summary
We investigate the benefit of objective 3-D front detection with modern interactive visual analysis techniques for case studies of extra-tropical cyclones and comparisons of frontal structures between different numerical weather prediction models. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment them in the vertical dimension. We see great potential for more complex studies of atmospheric dynamics and for operational weather forecasting.
Zhenxin Liu, Yuanhao Chen, Yuhang Wang, Cheng Liu, Shuhua Liu, and Hong Liao
Geosci. Model Dev., 16, 4385–4403,Short summary
The heterogeneous layout of urban buildings leads to the complex wind field in and over the urban canopy. Large discrepancies between the observations and the current simulations result from misunderstanding the character of the wind field. The Inhomogeneous Wind Scheme in Urban Street (IWSUS) was developed to simulate the heterogeneity of the wind speed in a typical street and then improve the simulated energy budget in the lower atmospheric layer over the urban canopy.
Kai Cao, Qizhong Wu, Lingling Wang, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongqing Li, and Lanning Wang
Geosci. Model Dev., 16, 4367–4383,Short summary
Offline performance experiment results show that the GPU-HADVPPM on a V100 GPU can achieve up to 1113.6 × speedups to its original version on an E5-2682 v4 CPU. A series of optimization measures are taken, and the CAMx-CUDA model improves the computing efficiency by 128.4 × on a single V100 GPU card. A parallel architecture with an MPI plus CUDA hybrid paradigm is presented, and it can achieve up to 4.5 × speedup when launching eight CPU cores and eight GPU cards.
Geosci. Model Dev., 16, 4265–4281,Short summary
This study analyzes forecasts that were made in 2021 to help trigger measurements during the CADDIWA experiment. The WRF and CHIMERE models were run each day, and the first goal is to quantify the variability of the forecast as a function of forecast leads and forecast location. The possibility of using the different leads as an ensemble is also tested. For some locations, the correlation scores are better with this approach. This could be tested on operational forecast chains in the future.
Emily de Jong, John Ben Mackay, Oleksii Bulenok, Anna Jaruga, and Sylwester Arabas
Geosci. Model Dev., 16, 4193–4211,Short summary
In clouds, collisional breakup occurs when two colliding droplets splinter into new, smaller fragments. Particle-based modeling approaches often do not represent breakup because of the computational demands of creating new droplets. We present a particle-based breakup method that preserves the computational efficiency of these methods. In a series of simple demonstrations, we show that this representation alters cloud processes in reasonable and expected ways.
Caiyi Jin, Qiangqiang Yuan, Tongwen Li, Yuan Wang, and Liangpei Zhang
Geosci. Model Dev., 16, 4137–4154,Short summary
The semi-empirical physical approach derives PM2.5 with strong physical significance. However, due to the complex optical characteristic, the physical parameters are difficult to express accurately. Thus, combining the atmospheric physical mechanism and machine learning, we propose an optimized model. It creatively embeds the random forest model into the physical PM2.5 remote sensing approach to simulate a physical parameter. Our method shows great optimized performance in the validations.
Cyril Caram, Sophie Szopa, Anne Cozic, Slimane Bekki, Carlos A. Cuevas, and Alfonso Saiz-Lopez
Geosci. Model Dev., 16, 4041–4062,Short summary
We studied the role of halogenated compounds (containing chlorine, bromine and iodine), emitted by natural processes (mainly above the oceans), in the chemistry of the lower layers of the atmosphere. We introduced this relatively new chemistry in a three-dimensional climate–chemistry model and looked at how this chemistry will disrupt the ozone. We showed that the concentration of ozone decreases by 22 % worldwide and that of the atmospheric detergent, OH, by 8 %.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016,Short summary
Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Min-Seop Ahn, Paul A. Ullrich, Peter J. Gleckler, Jiwoo Lee, Ana C. Ordonez, and Angeline G. Pendergrass
Geosci. Model Dev., 16, 3927–3951,Short summary
We introduce a framework for regional-scale evaluation of simulated precipitation distributions with 62 climate reference regions and 10 metrics and apply it to evaluate CMIP5 and CMIP6 models against multiple satellite-based precipitation products. The common model biases identified in this study are mainly associated with the overestimated light precipitation and underestimated heavy precipitation. These biases persist from earlier-generation models and have been slightly improved in CMIP6.
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
Geosci. Model Dev., 16, 3873–3891,Short summary
The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detection and better represents both large and small fires. FINNv2.5 generates more emissions than FINNv1 and is in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
Lichao Yang, Wansuo Duan, and Zifa Wang
Geosci. Model Dev., 16, 3827–3848,Short summary
An approach is proposed to refine a ground meteorological observation network to improve the PM2.5 forecasts in the Beijing–Tianjin–Hebei region. A cost-effective observation network is obtained and makes the relevant PM2.5 forecasts assimilate fewer observations but achieve the forecasting skill comparable to or higher than that obtained by assimilating all ground station observations, suggesting that many of the current ground stations can be greatly scattered to avoid much unnecessary work.
Abhishekh Kumar Srivastava, Paul Aaron Ullrich, Deeksha Rastogi, Pouya Vahmani, Andrew Jones, and Richard Grotjahn
Geosci. Model Dev., 16, 3699–3722,Short summary
Stakeholders need high-resolution regional climate data for applications such as assessing water availability and mountain snowpack. This study examines 3 h and 24 h historical precipitation over the contiguous United States in the 12 km WRF version 4.2.1-based dynamical downscaling of the ERA5 reanalysis. WRF improves precipitation characteristics such as the annual cycle and distribution of the precipitation maxima, but it also displays regionally and seasonally varying precipitation biases.
Haixia Xiao, Yaqiang Wang, Yu Zheng, Yuanyuan Zheng, Xiaoran Zhuang, Hongyan Wang, and Mei Gao
Geosci. Model Dev., 16, 3611–3628,Short summary
Due to the small-scale and nonstationary nature of convective wind gusts (CGs), reliable CG nowcasting has remained unattainable. Here, we developed a deep learning model — namely CGsNet — for 0—2 h of quantitative CG nowcasting, first achieving minute—kilometer-level forecasts. Based on the CGsNet model, the average surface wind speed (ASWS) and peak wind gust speed (PWGS) predictions are obtained. Experiments indicate that CGsNet exhibits higher accuracy than the traditional method.
Maria Krutova, Mostafa Bakhoday-Paskyabi, Joachim Reuder, and Finn Gunnar Nielsen
Geosci. Model Dev., 16, 3553–3564,Short summary
Local refinement of the grid is a powerful method allowing us to reduce the computational time while preserving the accuracy in the area of interest. Depending on the implementation, the local refinement may introduce unwanted numerical effects into the results. We study the wind speed common to the wind turbine operational speeds and confirm strong alteration of the result when the heat fluxes are present, except for the specific refinement scheme used.
Sylvia Sullivan, Behrooz Keshtgar, Nicole Albern, Elzina Bala, Christoph Braun, Anubhav Choudhary, Johannes Hörner, Hilke Lentink, Georgios Papavasileiou, and Aiko Voigt
Geosci. Model Dev., 16, 3535–3551,Short summary
Clouds absorb and re-emit infrared radiation from Earth's surface and absorb and reflect incoming solar radiation. As a result, they change atmospheric temperature gradients that drive large-scale circulation. To better simulate this circulation, we study how the radiative heating and cooling from clouds depends on model settings like grid spacing; whether we describe convection approximately or exactly; and the level of detail used to describe small-scale processes, or microphysics, in clouds.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavcic, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben J. Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
3D climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
James Weber, James A. King, Katerina Sindelarova, and Maria Val Martin
Geosci. Model Dev., 16, 3083–3101,Short summary
The emissions of volatile organic compounds from vegetation (BVOCs) influence atmospheric composition and contribute to certain gases and aerosols (tiny airborne particles) which play a role in climate change. BVOC emissions are likely to change in the future due to changes in climate and land use. Therefore, accurate simulation of BVOC emission is important, and this study describes an update to the simulation of BVOC emissions in the United Kingdom Earth System Model (UKESM).
Koichi Sakaguchi, L. Ruby Leung, Colin M. Zarzycki, Jihyeon Jang, Seth McGinnis, Bryce E. Harrop, William C. Skamarock, Andrew Gettelman, Chun Zhao, William J. Gutowski, Stephen Leak, and Linda Mearns
Geosci. Model Dev., 16, 3029–3081,Short summary
We document details of the regional climate downscaling dataset produced by a global variable-resolution model. The experiment is unique in that it follows a standard protocol designed for coordinated experiments of regional models. We found negligible influence of post-processing on statistical analysis, importance of simulation quality outside of the target region, and computational challenges that our model code faced due to rapidly changing super computer systems.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 Tracking Aerosol Convection Experiment Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Xiaohan Li, Yi Zhang, Xindong Peng, Baiquan Zhou, Jian Li, and Yiming Wang
Geosci. Model Dev., 16, 2975–2993,Short summary
The weather and climate physics suites used in GRIST-A22.7.28 are compared using single-column modeling. The source of their discrepancies in terms of modeling cloud and precipitation is explored. Convective parameterization is found to be a key factor responsible for the differences. The two suites also have intrinsic differences in the interaction between microphysics and other processes, resulting in different cloud features and time step sensitivities.
Owen Kenneth Hughes and Christiane Jablonowski
Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model designs and the impact of mountains on the flow.
Shaohui Zhou, Yuchao Gao, Zexia Duan, Xingya Xi, and Yubin Li
The proposed wind speed correction model (VMD-PCA-RF) demonstrates the highest prediction accuracy and stability in the five southern provinces in nearly a year and at different heights. VMD-PCA-RF evaluation indexes for 10 months remain relatively stable: accuracy rate FA is above 85 %. In future research, the proposed VMD-PCA-RF algorithm can be extrapolated to the 3 km grid points of the five southern provinces to generate a 3 km grid-corrected wind speed product.
Virginie Marécal, Ronan Voisin-Plessis, Tjarda Jane Roberts, Alessandro Aiuppa, Herizo Narivelo, Paul David Hamer, Béatrice Josse, Jonathan Guth, Luke Surl, and Lisa Grellier
Geosci. Model Dev., 16, 2873–2898,Short summary
We implemented a halogen volcanic chemistry scheme in a one-dimensional modelling framework preparing for further use in a three-dimensional global chemistry-transport model. The results of the simulations for an eruption of Mt Etna in 2008, including various sensitivity tests, show a good consistency with previous modelling studies.
Zhe Feng, Joseph Hardin, Hannah C. Barnes, Jianfeng Li, L. Ruby Leung, Adam Varble, and Zhixiao Zhang
Geosci. Model Dev., 16, 2753–2776,Short summary
PyFLEXTRKR is a flexible atmospheric feature tracking framework with specific capabilities to track convective clouds from a variety of observations and model simulations. The package has a collection of multi-object identification algorithms and has been optimized for large datasets. This paper describes the algorithms and demonstrates applications for tracking deep convective cells and mesoscale convective systems from observations and model simulations at a wide range of scales.
Yan Ji, Bing Gong, Michael Langguth, Amirpasha Mozaffari, and Xiefei Zhi
Geosci. Model Dev., 16, 2737–2752,Short summary
Formulating short-term precipitation forecasting as a video prediction task, a novel deep learning architecture (convolutional long short-term memory generative adversarial network, CLGAN) is proposed. A benchmark dataset is built on minute-level precipitation measurements. Results show that with the GAN component the model generates predictions sharing statistical properties with observations, resulting in it outperforming the baseline in dichotomous and spatial scores for heavy precipitation.
Aleksander Lacima, Hervé Petetin, Albert Soret, Dene Bowdalo, Oriol Jorba, Zhaoyue Chen, Raúl F. Méndez Turrubiates, Hicham Achebak, Joan Ballester, and Carlos Pérez García-Pando
Geosci. Model Dev., 16, 2689–2718,Short summary
Understanding how air pollution varies across space and time is of key importance for the safeguarding of human health. This work arose in the context of the project EARLY-ADAPT, for which the Barcelona Supercomputing Center developed an air pollution database covering all of Europe. Through different statistical methods, we compared two global pollution models against measurements from ground stations and found significant discrepancies between the observed and the modeled surface pollution.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and evaluate modeled results against TROPOMI v2 over multiple power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind direction and prior emissions.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
It's important to know how well atmospheric models do in the mountains, but there aren't very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado river basin against the data that's available. The model works pretty well but, there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we couldn't before.
Andrew Geiss, Po-Lun Ma, Balwinder Singh, and Joseph C. Hardin
Geosci. Model Dev., 16, 2355–2370,Short summary
Atmospheric aerosols play a critical role in Earth's climate, but it is too computationally expensive to directly model their interaction with radiation in climate simulations. This work develops a new neural-network-based parameterization of aerosol optical properties for use in the Energy Exascale Earth System Model that is much more accurate than the current one; it also introduces a unique model optimization method that involves randomly generating neural network architectures.
Joey C. Y. Lam, Amos P. K. Tai, Jason A. Ducker, and Christopher D. Holmes
Geosci. Model Dev., 16, 2323–2342,Short summary
We developed a new component within an atmospheric chemistry model to better simulate plant ecophysiological processes relevant for ozone air quality. We showed that it reduces simulated biases in plant uptake of ozone in prior models. The new model enables us to explore how future climatic changes affect air quality via affecting plants, examine ozone–vegetation interactions and feedbacks, and evaluate the impacts of changing atmospheric chemistry and climate on vegetation productivity.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations, and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model-satellite discrepancies, we find that future field campaigns in an East African region (30° E – 45° E, 5° S – 5° N) could substantially improve the predictive skill of air quality models.
Qian Shu, Sergey L. Napelenok, William T. Hutzell, Kirk R. Baker, Barron H. Henderson, Benjamin N. Murphy, and Christian Hogrefe
Geosci. Model Dev., 16, 2303–2322,Short summary
Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
We implemented an alternative aerosol scheme in the high and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. The development enables the comparison of different aerosol schemes with different complexity in the same model framework and identifies improvements in comparison to a range of observations in both the troposphere and stratosphere.
Angevine, W. M., Jiang, H., and Mauritsen, T.: Performance of an eddy diffusivity–mass flux scheme for shallow cumulus boundary layers, Mon. Weather Rev., 138, 2895–2912, https://doi.org/10.1175/2010MWR3142.1, 2010.
Belgian Interregional Environmental Agency (IRCEL-CELINE): Air Quality Measurements, IRCEL-CELINE [data set], https://irceline.be/en/air-quality/measurements/monitoring-stations, last access: 16 January 2023.
Boersma, K. F., Eskes, H. J., Veefkind, J. P., Brinksma, E. J., van der A, R. J., Sneep, M., van den Oord, G. H. J., Levelt, P. F., Stammes, P., Gleason, J. F., and Bucsela, E. J.: Near-real time retrieval of tropospheric NO2 from OMI, Atmos. Chem. Phys., 7, 2103–2118, https://doi.org/10.5194/acp-7-2103-2007, 2007.
Botero, A. Y., Lopez-Restrepo, S., Pelaez, N. P., Quintero, O. L., Segers, A., and Heemink, A. W.: Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation, Atmosphere, 12, 1633, https://doi.org/10.3390/atmos12121633, 2021.
Bougeault, P. and Lacarrere, P.: Parameterization of Orography-Induced Turbulence in a Mesobeta–Scale Model, Mon. Weather Rev., 117, 1872–1890, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2, 1989.
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission Objectives and Measurement Modes, J. Atmos. Sci, 56, 127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999.
Bretherton, C. S. and Park, S.: A New Moist Turbulence Parameterization in the Community Atmosphere Model, J. Climate, 22, 3422–3448, https://doi.org/10.1175/2008JCLI2556.1, 2009.
Buchholz, R. R., Emmons, L. K., Tilmes, S., and The CESM2 Development Team: CESM2.1/CAM-chem Instantaneous Output for Boundary Conditions, UCAR/NCAR – Atmospheric Chemistry Observations and Modeling Laboratory. (e.g. Lat: 40 to 60, Lon: 355 to 10, 10 June 2019–01 July 2019), UCAR [data set], https://doi.org/10.5065/NMP7-EP60 (last access: 16 January 2023), 2019.
Burkholder, J. B., Sander, S. P., Abbatt, J. P. D., Barker, J. R., Cappa, C., Crounse, J. D., Dibble, T. S., Huie, R. E., Kolb, C. E., Kurylo, M. J., Orkin, V. L., Percival, C. J., Wilmouth, D. M., and Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation No. 19, JPL Publication 19-5, Jet Propulsion Laboratory, Pasadena, https://jpldataeval.jpl.nasa.gov/pdf/NASA-JPL Evaluation 19-5.pdf (last access: 9 January 2023), 2020.
Burrows, J. P., Weber, M., Buchwitz, M., Rozanov, V., Ladstätter-Weißenmayer, A., Richter, A., DeBeek, R., Hoogen, R., Bramstedt, K., Eichmann, K.-U., Eisinger, M., and Perner, D.,: The Global Ozone Monitoring Experiment (GOME): Mission Concept and First Scientific Result, J. Atmos. Sci., 56, 151–175, https://doi.org/10.1175/1520-0469(1999)056<0151:TGOMEG>2.0.CO;2, 1999.
Chan, K. L., Wiegner, M., van Geffen, J., De Smedt, I., Alberti, C., Cheng, Z., Ye, S., and Wenig, M.: MAX-DOAS measurements of tropospheric NO2 and HCHO in Munich and the comparison to OMI and TROPOMI satellite observations, Atmos. Meas. Tech., 13, 4499–4520, https://doi.org/10.5194/amt-13-4499-2020, 2020.
Chen, F., Kusaka, H., Bornstein, R., Ching, J., Grimmond, C. S. B., Grossman-Clarke, S., Loridan, T., Manning, K. W., Martilli, A., Miao, S., Sailor, D., Salamanca, F. P., Taha, H., Tewari, M., Wang, X., Wyszogrodzki, A. A., and Zhang, C.: The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems, Int. J. Climatol., 31, 273–288, https://doi.org/10.1002/joc.2158, 2011.
Chen, Y., Wild, O., Ryan, E., Sahu, S. K., Lowe, D., Archer-Nicholls, S., Wang, Y., McFiggans, G., Ansari, T., Singh, V., Sokhi, R. S., Archibald, A., and Beig, G.: Mitigation of PM2.5 and ozone pollution in Delhi: a sensitivity study during the pre-monsoon period, Atmos. Chem. Phys., 20, 499–514, https://doi.org/10.5194/acp-20-499-2020, 2020.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M., Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution temporal profiles in the Emissions Database for Global Atmospheric Research, Sci. Data, 7, 121, https://doi.org/10.1038/s41597-020-0462-2, 2020 (data available at: https://edgar.jrc.ec.europa.eu/dataset_temp_profile, last access: 9 January 2023).
De Haij, M., Wauben, W., and Klein Baltink, H.: Continuous mixing layer height determination using the LD-40 ceilometer: a feasibility study, Royal Netherlands Meteorological Institute (KNMI), https://cdn.knmi.nl/system/data_center_publications/files/000/067/473/original/rp_bsikinsa_knmi_20070117_wr200701.pdf?1495620777 (last access: 16 January 2023), 2007.
Deshler, T., Stübi, R., Schmidlin, F. J., Mercer, J. L., Smit, H. G. J., Johnson, B. J., Kivi, R., and Nardi, B.: Methods to homogenize electrochemical concentration cell (ECC) ozonesonde measurements across changes in sensing solution concentration or ozonesonde manufacturer, Atmos. Meas. Tech., 10, 2021–2043, https://doi.org/10.5194/amt-10-2021-2017, 2017.
Dimitropoulou, E., Hendrick, F., Pinardi, G., Friedrich, M. M., Merlaud, A., Tack, F., De Longueville, H., Fayt, C., Hermans, C., Laffineur, Q., Fierens, F., and Van Roozendael, M.: Validation of TROPOMI tropospheric NO2 columns using dual-scan multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in Uccle, Brussels, Atmos. Meas. Tech., 13, 5165–5191, https://doi.org/10.5194/amt-13-5165-2020, 2020.
Ding, J., van der A, R. J., Eskes, H. J., Mijling, B., Stavrakou, T., van Geffen, J. H. G. M., and Veefkind, J. P.: NOx Emissions Reduction and Rebound in China Due to the COVID-19 Crisis, Geophys. Res. Lett., 46, e2020GL089912, https://doi.org/10.1029/2020GL089912, 2020.
Douros, J., Eskes, H., van Geffen, J., Boersma, K. F., Compernolle, S., Pinardi, G., Blechschmidt, A.-M., Peuch, V.-H., Colette, A., and Veefkind, P.: Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS-regional air quality ensemble, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-365, 2022.
Emmons, L. K., Schwantes, R. H., Orlando, J. J., Tyndall, G., Kinnison, D., Lamarque, J., Marsh, D., Mills, M. J., Tilmes, S., Bardeen, C., Buchholz, R. R., Conley, A., Gettelman, A., Garcia, R., Simpson, I., Blake, D. R., Meinardi, S., and Pétron, G.: The Chemistry Mechanism in the Community Earth System Model Version 2 (CESM2), J. Adv. Model. Earth Syst., 12, e2019MS001882, https://doi.org/10.1029/2019MS001882, 2020.
Eskes, H., van Geffen, J., Sneep, M., Veefkind, P., Niemeijer, S., and Zehner, C.: S5P Nitrogen Dioxide v02.03.01 intermediate reprocessing on the S5P-PAL system, S5P [data set], https://data-portal.s5p-pal.com/browser/ (last access: 16 January 2023), 2021.
Eskes, H. J. and Boersma, K. F.: Averaging kernels for DOAS total-column satellite retrievals, Atmos. Chem. Phys., 3, 1285–1291, https://doi.org/10.5194/acp-3-1285-2003, 2003.
European Comission: Global Air Pollutant Emissions Emissions EDGAR V5.0, European Comission [data set], https://edgar.jrc.ec.europa.eu/dataset_ap50 (last access: 16 January 2023), 2019.
European Monitoring and Evaluation Programme Centre on Emission Inventories and Projections: Grid emissions in 0.1∘ × 0.1∘ long-lat resolution, European Monitoring and Evaluation Programme Centre on Emission Inventories and Projections [data set], https://www.ceip.at/the-emep-grid/gridded-emissions (last access: 16 January 2023), 2022.
European Space Agency: TROPOMI Level 2 Nitrogen Dioxide total column products Version 01, European Space Agency [data set], https://doi.org/10.5270/S5P-s4ljg54 (last access: 16 January 2023), 2018.
Feng, S., Lauvaux, T., Newman, S., Rao, P., Ahmadov, R., Deng, A., Díaz-Isaac, L. I., Duren, R. M., Fischer, M. L., Gerbig, C., Gurney, K. R., Huang, J., Jeong, S., Li, Z., Miller, C. E., O'Keeffe, D., Patarasuk, R., Sander, S. P., Song, Y., Wong, K. W., and Yung, Y. L.: Los Angeles megacity: a high-resolution land–atmosphere modelling system for urban CO2 emissions, Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, 2016.
Fioletov, V., McLinden, C. A., Griffin, D., Krotkov, N., Liu, F., and Eskes, H.: Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations, Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, 2022.
Flanders Environment Agency (VMM): Annual air report – Flanders (Belgium), Emissions 2000–2016 and air quality in Flanders in 2017, https://en.vmm.be/publications/annual-report-air-quality-in-the-flanders-region-2017 (last access: 9 January 2023), 2017.
Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi, N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse, C., Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version), Copernicus Atmosphere Monitoring Service (CAMS) report, https://doi.org/10.24380/d0bn-kx16, 2019.
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within the WRF model, Atmos. Environ., 39, 6957–6975, https://doi.org/10.1016/j.atmosenv.2005.04.027, 2005.
Grell, G. A. and Freitas, S. R.: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling, Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, 2014.
Grenier, H. and Bretherton, C. S.: A Moist PBL Parameterization for Large-Scale Models and Its Application to Subtropical Cloud-Topped Marine Boundary Layers, Mon. Weather Rev., 129, 357–377, https://doi.org/10.1175/1520-0493(2001)129<0357:AMPPFL>2.0.CO;2, 2001.
Griffin, D., Zhao, X., McLinden, C. A., Boersma, F., Bourassa, A., Dammers, E., Degenstein, D., Eskes, H., Fehr, L., Fioletov, V., Hayden, K., Kharol, S. K., Li, S.-M., Makar, P., Martin, R. V., Mihele, C. Mittermeier, R. L., Krotkov, N., Sneep, M., Lamsal, L. N., ter Linden, M., van Geffen, J., Veefkind, P., and Wolde, M.: High-Resolution Mapping of Nitrogen Dioxide With TROPOMI: First Results and Validation Over the Canadian Oil Sands, Geophys. Res. Lett., 46, 1049–1060, https://doi.org/10.1029/2018GL081095, 2019.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Haeffelin, M., Angelini, F., Morille, Y., Martucci, G., Frey, S., Gobbi, G. P., Lolli, S., O'Dowd, C. D., Sauvage, L., Xueref-Rémy, I., Wastine, B., and Feist, D. G.: Evaluation of Mixing-Height Retriveals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe, Bound.-Lay. Meteorol., 143, 49–75, https://doi.org/10.1007/s10546-011-9643-z, 2012.
Haeffelin, M., Laffineur, Q., Bravo-Aranda, J.-A., Drouin, M.-A., Casquero-Vera, J.-A., Dupont, J.-C., and De Backer, H.: Radiation fog formation alerts using attenuated backscatter power from automatic lidars and ceilometers, Atmos. Meas. Tech., 9, 5347–5365, https://doi.org/10.5194/amt-9-5347-2016, 2016.
Han, S., Bian, H., Feng, Y., Liu, A., Li, X., Zeng, F., and Zhang, X.: Analysis of the Relationship between O3, NO and NO2 in Tianjin, China, Aerosol Air Qual. Res., 11, 128–139, https://doi.org/10.4209/aaqr.2010.07.0055, 2011.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Hong, S.-Y., Noh, Y., and Dudhia, J.: A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes, Mon. Weather Rev., 134, 2318–2341, https://doi.org/10.1175/MWR3199.1, 2006.
Hu, B., Duan, J., Hong, Y., Xu, L., Li, M., Bian, Y., Qin, M., Fang, W., Xie, P., and Chen, J.: Exploration of the atmospheric chemistry of nitrous acid in a coastal city of southeastern China: results from measurements across four seasons, Atmos. Chem. Phys., 22, 371–393, https://doi.org/10.5194/acp-22-371-2022, 2022.
Huang, G., Brook, R., Crippa, M., Janssens-Maenhout, G., Schieberle, C., Dore, C., Guizzardi, D., Muntean, M., Schaaf, E., and Friedrich, R.: Speciation of anthropogenic emissions of non-methane volatile organic compounds: a global gridded data set for 1970–2012, Atmos. Chem. Phys., 17, 7683–7701, https://doi.org/10.5194/acp-17-7683-2017, 2017.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins: Radiative forcing by long–lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008.
Ialongo, I., Virta, H., Eskes, H., Hovila, J., and Douros, J.: Comparison of TROPOMI/Sentinel-5 Precursor NO2 observations with ground-based measurements in Helsinki, Atmos. Meas. Tech., 13, 205–218, https://doi.org/10.5194/amt-13-205-2020, 2020.
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: The CAMS reanalysis of atmospheric composition, Atmos. Chem. Phys., 19, 3515–3556, https://doi.org/10.5194/acp-19-3515-2019, 2019a.
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A., Dominguez, J., Engelen, R., Eskes, H., Flemming, J., Huijnen, V., Jones, L., Kipling, Z., Massart, S., Parrington, M., Peuch, V.-H., Razinger, M., Remy, S., Schulz, M., and Suttie, M.: CAMS global reanalysis (EAC4), Copernicus Atmosphere Monitoring Service (CAMS) Atmosphere Data Store (ADS) [data set], https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-reanalysis-eac4?tab=form (last access: 16 January 2023), 2019b.
Janjić, Z. I.: The Step-Mountain Eta Coordinate Model: Further Developments of the Convection, Viscous Sublayer, and Turbulence Closure Schemes, Mon. Weather Rev., 122, 927–945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2, 1994.
Jiménez, P., Dudhia, J., González-Rouco, J., Navarro, J., Montávez, J. and García-Bustamante, E.: A Revised Scheme for the WRF Surface Layer Formulation, Mon. Weather Rev., 140, 898–918, https://doi.org/10.1175/MWR-D-11-00056.1, 2012.
Judd, L. M., Al-Saadi, J. A., Szykman, J. J., Valin, L. C., Janz, S. J., Kowalewski, M. G., Eskes, H. J., Veefkind, J. P., Cede, A., Mueller, M., Gebetsberger, M., Swap, R., Pierce, R. B., Nowlan, C. R., Abad, G. G., Nehrir, A., and Williams, D.: Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound, Atmos. Meas. Tech., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, 2020.
Kim, Y., Sartelet, K., Raut, J.-C., and Chazette, P.: Evaluation of the Weather Research and Forecast/Urban Model Over Greater Paris, Bound.-Lay. Meteorol., 149, 105–132, https://doi.org/10.1007/s10546-013-9838-6, 2013.
Kleffmann, J., Kurtenbach, R. Lörzer, J., Wiesen, P., Kalthoff, N., Vogel, B., and Vogel, H.: Measured and simulated vertical profiles of nitrous acid – Part I: Field measurements, Atmos. Environ., 37, 3949–3955, https://doi.org/10.1016/S1352-2310(03)00242-5, 2003.
Kleinman, L. I.: Low and high NOx tropospheric photochemistry, J. Geophys. Res.-Atmos., 99, 16831–16838, https://doi.org/10.1029/94JD01028, 1994.
Kuik, F., Lauer, A., Churkina, G., Denier van der Gon, H. A. C., Fenner, D., Mar, K. A., and Butler, T. M.: Air quality modelling in the Berlin–Brandenburg region using WRF-Chem v3.7.1: sensitivity to resolution of model grid and input data, Geosci. Model Dev., 9, 4339–4363, https://doi.org/10.5194/gmd-9-4339-2016, 2016.
Lamsal, L. N., Martin, R. V., van Donkelaar, A., Steinbacher, M., Celarier, E. A., Bucsela, E., Dunlea, E. J., and Pinto, J. P.: Ground-level nitrogen dioxide concentrations inferred from the satellite-borne Ozone Monitoring Instrument, J. Geophys. Res., 113, D16308, https://doi.org/10.1029/2007JD009235, 2008.
Lange, K., Richter, A., and Burrows, J. P.: Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations, Atmos. Chem. Phys., 22, 2745–2767, https://doi.org/10.5194/acp-22-2745-2022, 2022.
Lelieveld, J., Evans, J., Fnais, M., Giannadaki, D., and Pozzer, A.: The contribution of outdoor air pollution sources to premature mortality on a global scale, Nature, 525, 367–371, https://doi.org/10.1038/nature15371, 2015.
Lelieveld, J., Gromov, S., Pozzer, A., and Taraborrelli, D.: Global tropospheric hydroxyl distribution, budget and reactivity, Atmos. Chem. Phys., 16, 12477–12493, https://doi.org/10.5194/acp-16-12477-2016, 2016.
Lamarque, J.-F., Emmons, L. K., Hess, P. G., Kinnison, D. E., Tilmes, S., Vitt, F., Heald, C. L., Holland, E. A., Lauritzen, P. H., Neu, J., Orlando, J. J., Rasch, P. J., and Tyndall, G. K.: CAM-chem: description and evaluation of interactive atmospheric chemistry in the Community Earth System Model, Geosci. Model Dev., 5, 369–411, https://doi.org/10.5194/gmd-5-369-2012, 2012.
Levelt, P. F., van den Oord, G. H. J, Dobber, M. R., Mälkki, A., Visser, H., de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44, 1093–1101, https://doi.org/10.1109/TGRS.2006.872333, 2006.
Liu, S., Valks, P., Pinardi, G., Xu, J., Chan, K. L., Argyrouli, A., Lutz, R., Beirle, S., Khorsandi, E., Baier, F., Huijnen, V., Bais, A., Donner, S., Dörner, S., Gratsea, M., Hendrick, F., Karagkiozidis, D., Lange, K., Piters, A. J. M., Remmers, J., Richter, A., Van Roozendael, M., Wagner, T., Wenig, M., and Loyola, D. G.: An improved TROPOMI tropospheric NO2 research product over Europe, Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, 2021.
Lorente, A., Boersma, K. F., Eskes, H. J., Veefkind, J. P., van Geffen, J. H. G. M., de Zeeuw, M. B., Denier van der Gon, H. A. C., Beirle, S., Krol, M. C.: Quantification of nitrogen oxides emissions from build-up pollution over Paris with TROPOMI, Sci. Rep., 9, 20033, https://doi.org/10.1038/s41598-019-56428-5, 2019.
Menut, L., Flamant, C., Pelon, J., and Flamant, P. H.: Urban boundary-layer height determination from lidar measurements over the Paris Area, Appl. Opt., 38, 945–954, https://doi.org/10.1364/AO.38.000945, 1999.
Mesinger, F.: Forecasting upper tropospheric turbulence within the framework of the Mellor-Yamada 2.5 closure, Res. Activ. in Atmos. and Ocean. Mod., WMO, Geneva, CAS/JSC WGNE Rep. No. 18, 4.28–4.29, https://www.researchgate.net/profile/Fedor-Mesinger/publication/343610849_Forecasting_upper_tropospheric_turbulence_within_the_framework_of_the_Mellor-Yamada_25_closure/ (last access: 19 January 2023), 1993.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line: Comparison of One- and Two-Moment Schemes, Mon. Weather Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
Müller, J.-F. and Stavrakou, T.: Inversion of CO and NOx emissions using the adjoint of the IMAGES model, Atmos. Chem. Phys., 5, 1157–1186, https://doi.org/10.5194/acp-5-1157-2005, 2005.
Nakanishi, M. and Niino, H.: An Improved Mellor–Yamada Level-3 Model: Its Numerical Stability and Application to a Regional Prediction of Advection Fog, Bound.-Layer Meteorol., 119, 397–407, https://doi.org/10.1007/s10546-005-9030-8, 2006.
National Center for Atmospheric Research (NCAR): Weather Research and Forecasting Model Version 4.1.5, NCAR [code], https://doi.org/10.5065/D6MK6B4K, 2020.
National Center for Atmospheric Research (NCAR): WRF-Chem tools for the Community, NCAR [code], https://www2.acom.ucar.edu/wrf-chem/wrf-chem-tools-community, last access: 9 January 2023.
Pal, S., Haeffelin, M., and Batchvarova, E.: Exploring a geophysical process-based attribution technique for the determination of the atmospheric boundary layer depth using aerosol lidar and near-surface meteorological measurements, J. Geophys. Res.-Atmos., 118, 9277–9295, https://doi.org/10.1002/jgrd.50710, 2013.
Price, C. and Rind, D.: A simple lightning parameterization for calculating global lightning distributions, J. Geophys. Res., 97, 9919–9933, https://doi.org/10.1029/92JD00719, 1992.
Rey-Pommier, A., Chevallier, F., Ciais, P., Broquet, G., Christoudias, T., Kushta, J., Hauglustaine, D., and Sciare, J.: Quantifying NOx emissions in Egypt using TROPOMI observations, Atmos. Chem. Phys., 22, 11505–11527, https://doi.org/10.5194/acp-22-11505-2022, 2022.
Rijksinstituut voor Volksgezondheid en Milieu (RIVM): Grafieken en kaarten, RIVM [data set], https://www.emissieregistratie.nl/data/grafieken-en-kaarten (last access: 16 January 2023), 2021.
Rodgers, C. D., and Connor, B. J.: Intercomparison of remote sounding instruments, J. Geophys. Res., 108, 4116, https://doi.org/10.1029/2002JD002299, 2003.
Scaperdas, A. and Colvile, R. N.: Assessing the representativeness of monitoring data from an urban intersection site in central London, UK, Atmos. Env., 33, 661–674, https://doi.org/10.1016/S1352-2310(98)00096-X, 1999.
Sessions, W. R., Fuelberg, H. E., Kahn, R. A., and Winker, D. M.: An investigation of methods for injecting emissions from boreal wildfires using WRF-Chem during ARCTAS, Atmos. Chem. Phys., 11, 5719–5744, https://doi.org/10.5194/acp-11-5719-2011, 2011.
Shen, C., A. Shen, C. Tian, S. Zhou, L. Zhu, P. Chan, Q. Fan, S. Fan, and W. Li: Evaluating the impacts of updated aerodynamic roughness length in the WRF/Chem model over Pearl River Delta, Meteorol. Atmos. Phys., 132, 427–440, https://doi.org/10.1007/s00703-019-00698-1, 2020.
Shin, H. H. and Hong, S.-Y.: Representation of the Subgrid-Scale Turbulent Transport in Convective Boundary Layers at Gray-Zone Resolutions, Mon. Weather Rev., 143, 250–271, https://doi.org/10.1175/MWR-D-14-00116.1, 2015.
Sillman, S., Logan, J. A., and Wofsy, S. C.: The sensitivity of ozone to nitrogen oxides and hydrocarbons in regional ozone episodes, J. Geophys. Res.-Atmos., 95, 1837–1851, https://doi.org/10.1029/JD095iD02p01837, 1990.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D. M., and Huang, X.-Y.: A Description of the Advanced Research WRF Version 4, NCAR Tech. Note NCAR/TN-556+STR, 145 pp., https://doi.org/10.5065/1dfh-6p97, 2019.
Souri, A. H., Chance, K., Bak, J., Nowlan, C. R., González Abad, G., Jung, Y., Wong, D. C., Mao, J., and Liu, X.: Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI, Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, 2021.
Stavrakou, T., Müller, J.-F., Bauwens, M., Boersma, K. F., and van Geffen, J.: Satellite evidence for changes in the NO2 weekly cycle over large cities, Sci. Rep., 10, 10066, https://doi.org/10.1038/s41598-020-66891-0, 2020.
Stipa, T., Jalkanen, J.-P., Kalli, J., and Brink, A.: Emissions of NOx from Baltic shipping and first estimates on air quality and eutrophication of the Baltic sea, Finnish Ministry of Transport and Communication and the Finnish Maritime Administration, Finland, 33 pp., ISBN: 978-951-53-3028-4, https://helda.helsinki.fi/bitstream/handle/10138/1209/NOx_emissions_Baltic_ISBN978-951-53-3028-4.pdf?sequence=1 (last access: 9 January 2023), 2007.
Sukoriansky, S., Galperin, B., and Perov, V.: Application of a New Spectral Theory of Stably Stratified Turbulence to the Atmospheric Boundary Layer over Sea Ice, Bound.-Lay. Meteorol., 117, 231–257, https://doi.org/10.1007/s10546-004-6848-4, 2005.
Tack, F., Merlaud, A., Iordache, M.-D., Danckaert, T., Yu, H., Fayt, C., Meuleman, K., Deutsch, F., Fierens, F., and Van Roozendael, M.: High-resolution mapping of the NO2 spatial distribution over Belgian urban areas based on airborne APEX remote sensing, Atmos. Meas. Tech., 10, 1665–1688, https://doi.org/10.5194/amt-10-1665-2017, 2017.
Tack, F., Merlaud, A., Iordache, M.-D., Pinardi, G., Dimitropoulou, E., Eskes, H., Bomans, B., Veefkind, P., and Van Roozendael, M.: Assessment of the TROPOMI tropospheric NO2 product based on airborne APEX observations, Atmos. Meas. Tech., 14, 615–646, https://doi.org/10.5194/amt-14-615-2021, 2021.
Tewari, M., Chen, F., Wang, W., Dudhia, J., LeMone, M. A., Mitchell, K., Ek, M., Gayno, G., Wegiel, J., and Cuenca, R. H.: Implementation and verification of the unified NOAH land surface model in the WRF model, in: 20th conference on weather analysis and forecasting/16th conference on numerical weather prediction, Seattle, WA, USA, 10–16 January 2004, Abstract 14.2A, https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm (last access: 19 January 2023), 2004.
Tuccella, P., Curci, G., Visconti, G., Bessagnet, B., Menut, L., and Park, R. J.: Modeling of gas and aerosol with WRF/Chem over Europe: Evaluation and sensitivity study, J. Geophys. Res., 117, D03303, https://doi.org/10.1029/2011JD016302, 2012.
Valin, L. C., Russell, A. R., and Cohen, R. C.: Chemical feedback effects on the spatial patterns of the NOx weekend effect: a sensitivity analysis, Atmos. Chem. Phys., 14, 1–9, https://doi.org/10.5194/acp-14-1-2014, 2014.
van Geffen, J., Eskes, H., Boersma, K., Maasakkers, J., and Veefkind, J.: TROPOMI ATBD of the total and tropospheric NO2 data products, S5P-KNMI-L2-0005-RP Issue 1.3.0, Royal Netherlands Meteorological Institute (KNMI), https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-NO2-data-products (last access: 9 January 2023), 2018.
van Geffen, J., Boersma, K. F., Eskes, H., Sneep, M., ter Linden, M., Zara, M., and Veefkind, J. P.: S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI, Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, 2020.
van Geffen, J., Eskes, H., Compernolle, S., Pinardi, G., Verhoelst, T., Lambert, J.-C., Sneep, M., ter Linden, M., Ludewig, A., Boersma, K. F., and Veefkind, J. P.: Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data, Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022, 2022.
Van Malderen, R., De Muer, D., De Backer, H., Poyraz, D., Verstraeten, W. W., De Bock, V., Delcloo, A. W., Mangold, A., Laffineur, Q., Allaart, M., Fierens, F., and Thouret, V.: Fifty years of balloon-borne ozone profile measurements at Uccle, Belgium: a short history, the scientific relevance, and the achievements in understanding the vertical ozone distribution, Atmos. Chem. Phys., 21, 12385–12411, https://doi.org/10.5194/acp-21-12385-2021, 2021.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications, Remote Sens. Environ., 120, 70–83, https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Verhoelst, T., Compernolle, S., Pinardi, G., Lambert, J.-C., Eskes, H. J., Eichmann, K.-U., Fjæraa, A. M., Granville, J., Niemeijer, S., Cede, A., Tiefengraber, M., Hendrick, F., Pazmiño, A., Bais, A., Bazureau, A., Boersma, K. F., Bognar, K., Dehn, A., Donner, S., Elokhov, A., Gebetsberger, M., Goutail, F., Grutter de la Mora, M., Gruzdev, A., Gratsea, M., Hansen, G. H., Irie, H., Jepsen, N., Kanaya, Y., Karagkiozidis, D., Kivi, R., Kreher, K., Levelt, P. F., Liu, C., Müller, M., Navarro Comas, M., Piters, A. J. M., Pommereau, J.-P., Portafaix, T., Prados-Roman, C., Puentedura, O., Querel, R., Remmers, J., Richter, A., Rimmer, J., Rivera Cárdenas, C., Saavedra de Miguel, L., Sinyakov, V. P., Stremme, W., Strong, K., Van Roozendael, M., Veefkind, J. P., Wagner, T., Wittrock, F., Yela González, M., and Zehner, C.: Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks, Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, 2021.
Vigouroux, C., Langerock, B., Bauer Aquino, C. A., Blumenstock, T., Cheng, Z., De Mazière, M., De Smedt, I., Grutter, M., Hannigan, J. W., Jones, N., Kivi, R., Loyola, D., Lutsch, E., Mahieu, E., Makarova, M., Metzger, J.-M., Morino, I., Murata, I., Nagahama, T., Notholt, J., Ortega, I., Palm, M., Pinardi, G., Röhling, A., Smale, D., Stremme, W., Strong, K., Sussmann, R., Té, Y., van Roozendael, M., Wang, P., and Winkler, H.: TROPOMI–Sentinel-5 Precursor formaldehyde validation using an extensive network of ground-based Fourier-transform infrared stations, Atmos. Meas. Tech., 13, 3751–3767, https://doi.org/10.5194/amt-13-3751-2020, 2020.
Whittaker, J.: Pyproj [code], https://pyproj4.github.io/pyproj/stable/index.html (last access: 19 January 2023), 2019.
Williams, J. E., Boersma, K. F., Le Sager, P., and Verstraeten, W. W.: The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation, Geosci. Model Dev., 10, 721–750, https://doi.org/10.5194/gmd-10-721-2017, 2017.
Zaveri, R. A. and Peters, L. K.: A new lumped structure photochemical mechanism for large-scale applications, J. Geophys. Res., 104, 30387–30415, https://doi.org/10.1029/1999JD900876, 1999.
Zaveri, R. A., Easter, R. C., Fast, J. D., and Peters, L. K.: Model for Simulating Aerosol Interactions and Chemistry (MOSAIC), J. Geophys. Res., 113, D13204, https://doi.org/10.1029/2007JD008782, 2008.
Zhao, X., Griffin, D., Fioletov, V., McLinden, C., Cede, A., Tiefengraber, M., Müller, M., Bognar, K., Strong, K., Boersma, F., Eskes, H., Davies, J., Ogyu, A., and Lee, S. C.: Assessment of the quality of TROPOMI high-spatial-resolution NO2 data products in the Greater Toronto Area, Atmos. Meas. Tech., 13, 2131–2159, https://doi.org/10.5194/amt-13-2131-2020, 2020.
Zhu, Y., Hu, Q., Gao, M., Zhao, C., Zhang, C., Liu, T., Tian, Y., Yan, L., Su, W., Hong, X., and Liu, C.: Quantifying Contributions of Local Emissions and Regional Transport to NOx in Beijing Using TROPOMI Constrained WRF-Chem Simulation, Remote Sens., 13, 1798, https://doi.org/10.3390/rs13091798, 2021.
High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and evaluated using meteorological data and in situ, airborne, and spaceborne NO2 measurements. An intercomparison of model, aircraft, and TROPOMI NO2 columns is conducted to characterize biases in versions 1.3.1 and 2.3.1 of the satellite product. A mass balance method is implemented to provide improved emissions for simulating NO2 distribution over the study area.
High-resolution WRF-Chem simulations are conducted over Antwerp, Belgium, in June 2019 and...