Articles | Volume 16, issue 24
https://doi.org/10.5194/gmd-16-7491-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-7491-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
22 Dec 2023
Development and technical paper |
| 22 Dec 2023
| 22 Dec 2023
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Chris McLinden
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
Debora Griffin
Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada
Daniel Zawada
Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Doug Degenstein
Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Adam Bourassa
Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024, https://doi.org/10.5194/amt-17-6889-2024, 2024
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Alexei Rozanov, Christine Pohl, Carlo Arosio, Adam Bourassa, Klaus Bramstedt, Elizaveta Malinina, Landon Rieger, and John P. Burrows
Atmos. Meas. Tech., 17, 6677–6695, https://doi.org/10.5194/amt-17-6677-2024, https://doi.org/10.5194/amt-17-6677-2024, 2024
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We developed a new algorithm to retrieve vertical distributions of aerosol extinction coefficients in the stratosphere. The algorithm is applied to measurements of scattered solar light from the spaceborne OMPS-LP (Ozone Mapper and Profiler Suite Limb Profiler) instrument. The retrieval results are compared to data from other spaceborne instruments and used to investigate the evolution of the aerosol plume following the eruption of the Hunga Tonga–Hunga Ha'apai volcano in January 2022.
Kimberlee Dubé, Susann Tegtmeier, Adam Bourassa, Daniel Zawada, Douglas Degenstein, William Randel, Sean Davis, Michael Schwartz, Nathaniel Livesey, and Anne Smith
Atmos. Chem. Phys., 24, 12925–12941, https://doi.org/10.5194/acp-24-12925-2024, https://doi.org/10.5194/acp-24-12925-2024, 2024
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Viktoria F. Sofieva, Alexei Rozanov, Monika Szelag, John P. Burrows, Christian Retscher, Robert Damadeo, Doug Degenstein, Landon A. Rieger, and Adam Bourassa
Earth Syst. Sci. Data, 16, 5227–5241, https://doi.org/10.5194/essd-16-5227-2024, https://doi.org/10.5194/essd-16-5227-2024, 2024
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Sujan Khanal, Matthew Toohey, Adam Bourassa, C. Thomas McElroy, Christopher Sioris, and Kaley A. Walker
EGUsphere, https://doi.org/10.5194/egusphere-2024-3286, https://doi.org/10.5194/egusphere-2024-3286, 2024
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Measurements of stratospheric aerosol from the MAESTRO instrument are compared to other measurements to assess their scientific value. We find that medians of MAESTRO measurements binned by month and latitude show reasonable correlation with other data sets, with notable increases after volcanic eruptions, and that biases in the data can be alleviated through a simple correction technique. Used with care, MAESTRO aerosol measurements provide information that can complement other data sets.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
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Atmos. Chem. Phys., 24, 10159–10186, https://doi.org/10.5194/acp-24-10159-2024, https://doi.org/10.5194/acp-24-10159-2024, 2024
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Christine Pohl, Felix Wrana, Alexei Rozanov, Terry Deshler, Elizaveta Malinina, Christian von Savigny, Landon A. Rieger, Adam E. Bourassa, and John P. Burrows
Atmos. Meas. Tech., 17, 4153–4181, https://doi.org/10.5194/amt-17-4153-2024, https://doi.org/10.5194/amt-17-4153-2024, 2024
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Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Daniel Zawada, Kimberlee Dubé, Taran Warnock, Adam Bourassa, Susann Tegtmeier, and Douglas Degenstein
Atmos. Meas. Tech., 17, 1995–2010, https://doi.org/10.5194/amt-17-1995-2024, https://doi.org/10.5194/amt-17-1995-2024, 2024
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There remain large uncertainties in long-term changes of stratospheric–atmospheric temperatures. We have produced a time series of more than 20 years of satellite-based temperature measurements from the OSIRIS instrument in the upper–middle stratosphere. The dataset is publicly available and intended to be used for a better understanding of changes in stratospheric temperatures.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
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Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Kimberlee Dubé, Susann Tegtmeier, Adam Bourassa, Daniel Zawada, Douglas Degenstein, Patrick E. Sheese, Kaley A. Walker, and William Randel
Atmos. Chem. Phys., 23, 13283–13300, https://doi.org/10.5194/acp-23-13283-2023, https://doi.org/10.5194/acp-23-13283-2023, 2023
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This paper presents a technique for understanding the causes of long-term changes in stratospheric composition. By using N2O as a proxy for stratospheric circulation in the model used to calculated trends, it is possible to separate the effects of dynamics and chemistry on observed trace gas trends. We find that observed HCl increases are due to changes in the stratospheric circulation, as are O3 decreases above 30 hPa in the Northern Hemisphere.
Ethan Runge, Jeff Langille, Daniel Zawada, Adam Bourassa, and Doug Degenstein
Atmos. Meas. Tech., 16, 3123–3139, https://doi.org/10.5194/amt-16-3123-2023, https://doi.org/10.5194/amt-16-3123-2023, 2023
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The Limb Imaging Fourier Transform Spectrometer Experiment (LIFE) instrument takes vertical images of limb radiance across a wide mid-infrared spectral band from a stratospheric balloon. Measurements are used to infer vertical-trace-gas-profile retrievals of H2O, O3, HNO3, CH4, and N2O. Nearly time-/space-coincident observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Microwave Limb Sounder (MLS) instruments are compared to the LIFE results.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Yi Wang, Mark Schoeberl, Ghassan Taha, Daniel Zawada, and Adam Bourassa
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-36, https://doi.org/10.5194/amt-2023-36, 2023
Revised manuscript not accepted
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The OMPS-LP satellite instrument measures aerosol scattering properties across the atmospheric limb. Adopting an algorithm that uses extinction at two wavelengths, we retrieve vertical profiles of particle size and concentration. We demonstrate that these profiles are consistent with in-situ balloon and SAGE-III/ISS satellite measurements. We also show how aerosol size and concentration evolve during Reikoke and Hunga Tonga-Hunga Ha'apai eruptions.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
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Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Paul S. Jeffery, Kaley A. Walker, Chris E. Sioris, Chris D. Boone, Doug Degenstein, Gloria L. Manney, C. Thomas McElroy, Luis Millán, David A. Plummer, Niall J. Ryan, Patrick E. Sheese, and Jiansheng Zou
Atmos. Chem. Phys., 22, 14709–14734, https://doi.org/10.5194/acp-22-14709-2022, https://doi.org/10.5194/acp-22-14709-2022, 2022
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The upper troposphere–lower stratosphere is one of the most variable regions in the atmosphere. To improve our understanding of water vapour and ozone concentrations in this region, climatologies have been developed from 14 years of measurements from three Canadian satellite instruments. Horizontal and vertical coordinates have been chosen to minimize the effects of variability. To aid in analysis, model simulations have been used to characterize differences between instrument climatologies.
Kimberlee Dubé, Daniel Zawada, Adam Bourassa, Doug Degenstein, William Randel, David Flittner, Patrick Sheese, and Kaley Walker
Atmos. Meas. Tech., 15, 6163–6180, https://doi.org/10.5194/amt-15-6163-2022, https://doi.org/10.5194/amt-15-6163-2022, 2022
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Satellite observations are important for monitoring changes in atmospheric composition. Here we describe an improved version of the NO2 retrieval for the Optical Spectrograph and InfraRed Imager System. The resulting NO2 profiles are compared to those from the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer and the Stratospheric Aerosol and Gas Experiment III on the International Space Station. All datasets agree within 20 % throughout the stratosphere.
Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 15, 5497–5514, https://doi.org/10.5194/amt-15-5497-2022, https://doi.org/10.5194/amt-15-5497-2022, 2022
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Satellite observations provide information on the sources of SO2, an important pollutant that affects both air quality and climate. However, these observations suffer from relatively poor data quality due to weak signals of SO2. Here, we use a machine learning technique to analyze satellite SO2 observations in order to reduce the noise and artifacts over relatively clean areas while keeping the signals near pollution sources. This leads to significant improvement in satellite SO2 data.
Katherine L. Hayden, Shao-Meng Li, John Liggio, Michael J. Wheeler, Jeremy J. B. Wentzell, Amy Leithead, Peter Brickell, Richard L. Mittermeier, Zachary Oldham, Cristian M. Mihele, Ralf M. Staebler, Samar G. Moussa, Andrea Darlington, Mengistu Wolde, Daniel Thompson, Jack Chen, Debora Griffin, Ellen Eckert, Jenna C. Ditto, Megan He, and Drew R. Gentner
Atmos. Chem. Phys., 22, 12493–12523, https://doi.org/10.5194/acp-22-12493-2022, https://doi.org/10.5194/acp-22-12493-2022, 2022
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In this study, airborne measurements provided the most detailed characterization, to date, of boreal forest wildfire emissions. Measurements showed a large diversity of air pollutants expanding the volatility range typically reported. A large portion of organic species was unidentified, likely comprised of complex organic compounds. Aircraft-derived emissions improve wildfire chemical speciation and can support reliable model predictions of pollution from boreal forest wildfires.
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, https://doi.org/10.5194/acp-22-11657-2022, https://doi.org/10.5194/acp-22-11657-2022, 2022
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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.
Kristof Bognar, Susann Tegtmeier, Adam Bourassa, Chris Roth, Taran Warnock, Daniel Zawada, and Doug Degenstein
Atmos. Chem. Phys., 22, 9553–9569, https://doi.org/10.5194/acp-22-9553-2022, https://doi.org/10.5194/acp-22-9553-2022, 2022
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We quantify recent changes in stratospheric ozone (outside the polar regions) using a combination of three satellite datasets. We find that upper stratospheric ozone have increased significantly since 2000, although the recovery shows an unexpected pause in the Northern Hemisphere. Combined with the likely decrease in ozone in the lower stratosphere, this presents an interesting challenge for predicting the future of the ozone layer.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nickolay Krotkov, Fei Liu, and Henk Eskes
Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, https://doi.org/10.5194/acp-22-4201-2022, 2022
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The COVID-19 lockdown had a large impact on anthropogenic emissions and particularly on nitrogen dioxide (NO2). A new method of isolation of background, urban, and industrial components in NO2 is applied to estimate the lockdown impact on each of them. From 16 March to 15 June 2020, urban NO2 declined by −18 % to −28 % in most regions of the world, while background NO2 typically declined by less than −10 %.
Julia Koch, Adam Bourassa, Nick Lloyd, Chris Roth, and Christian von Savigny
Atmos. Chem. Phys., 22, 3191–3202, https://doi.org/10.5194/acp-22-3191-2022, https://doi.org/10.5194/acp-22-3191-2022, 2022
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The mesopause, the region of the earth's atmosphere between 85 and 100 km, is hard to access by direct measurements. Therefore we look for parameters that can be measured using satellite or ground-based measurements. In this study we researched sodium airglow, a phenomenon that occurs when sodium atoms are excited by chemical reactions. We compared satellite measurements of the airglow and resulting sodium concentration profiles to gain a better understanding of the sodium in that region.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Adam E. Bourassa, Doug A. Degenstein, Lucien Froidevaux, C. Thomas McElroy, Donal Murtagh, James M. Russell III, and Jiansheng Zou
Atmos. Meas. Tech., 15, 1233–1249, https://doi.org/10.5194/amt-15-1233-2022, https://doi.org/10.5194/amt-15-1233-2022, 2022
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This study analyzes the quality of two versions (v3.6 and v4.1) of ozone concentration measurements from the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), by comparing with data from five satellite instruments between 2004 and 2020. It was found that although the v3.6 data exhibit a better agreement than v4.1 with respect to the other instruments, v4.1 exhibits much better stability over time than v3.6. The stability of v4.1 makes it suitable for ozone trend studies.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
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A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
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Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
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We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Anqi Li, Chris Z. Roth, Adam E. Bourassa, Douglas A. Degenstein, Kristell Pérot, Ole Martin Christensen, and Donal P. Murtagh
Earth Syst. Sci. Data, 13, 5115–5126, https://doi.org/10.5194/essd-13-5115-2021, https://doi.org/10.5194/essd-13-5115-2021, 2021
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The nightglow emission originating from the vibrationally excited hydroxyl layer (about 85 km altitude) has been measured by the infrared imager (IRI) on the Odin satellite for more than 15 years. In this study, we document the retrieval steps, the resulting volume emission rates and the layer characteristics. Finally, we use the monthly zonal averages to demonstrate the fidelity of the data set. This unique, long-term data set will be valuable for studying various topics near the mesopause.
Daniel Zawada, Ghislain Franssens, Robert Loughman, Antti Mikkonen, Alexei Rozanov, Claudia Emde, Adam Bourassa, Seth Dueck, Hannakaisa Lindqvist, Didier Ramon, Vladimir Rozanov, Emmanuel Dekemper, Erkki Kyrölä, John P. Burrows, Didier Fussen, and Doug Degenstein
Atmos. Meas. Tech., 14, 3953–3972, https://doi.org/10.5194/amt-14-3953-2021, https://doi.org/10.5194/amt-14-3953-2021, 2021
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Satellite measurements of atmospheric composition often rely on computer tools known as radiative transfer models to model the propagation of sunlight within the atmosphere. Here we have performed a detailed inter-comparison of seven different radiative transfer models in a variety of conditions. We have found that the models agree remarkably well, at a level better than previously reported. This result provides confidence in our understanding of atmospheric radiative transfer.
Michaela I. Hegglin, Susann Tegtmeier, John Anderson, Adam E. Bourassa, Samuel Brohede, Doug Degenstein, Lucien Froidevaux, Bernd Funke, John Gille, Yasuko Kasai, Erkki T. Kyrölä, Jerry Lumpe, Donal Murtagh, Jessica L. Neu, Kristell Pérot, Ellis E. Remsberg, Alexei Rozanov, Matthew Toohey, Joachim Urban, Thomas von Clarmann, Kaley A. Walker, Hsiang-Jui Wang, Carlo Arosio, Robert Damadeo, Ryan A. Fuller, Gretchen Lingenfelser, Christopher McLinden, Diane Pendlebury, Chris Roth, Niall J. Ryan, Christopher Sioris, Lesley Smith, and Katja Weigel
Earth Syst. Sci. Data, 13, 1855–1903, https://doi.org/10.5194/essd-13-1855-2021, https://doi.org/10.5194/essd-13-1855-2021, 2021
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An overview of the SPARC Data Initiative is presented, to date the most comprehensive assessment of stratospheric composition measurements spanning 1979–2018. Measurements of 26 chemical constituents obtained from an international suite of space-based limb sounders were compiled into vertically resolved, zonal monthly mean time series. The quality and consistency of these gridded datasets are then evaluated using a climatological validation approach and a range of diagnostics.
Viktoria F. Sofieva, Monika Szeląg, Johanna Tamminen, Erkki Kyrölä, Doug Degenstein, Chris Roth, Daniel Zawada, Alexei Rozanov, Carlo Arosio, John P. Burrows, Mark Weber, Alexandra Laeng, Gabriele P. Stiller, Thomas von Clarmann, Lucien Froidevaux, Nathaniel Livesey, Michel van Roozendael, and Christian Retscher
Atmos. Chem. Phys., 21, 6707–6720, https://doi.org/10.5194/acp-21-6707-2021, https://doi.org/10.5194/acp-21-6707-2021, 2021
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The MErged GRIdded Dataset of Ozone Profiles is a long-term (2001–2018) stratospheric ozone profile climate data record with resolved longitudinal structure that combines the data from six limb satellite instruments. The dataset can be used for various analyses, some of which are discussed in the paper. In particular, regionally and vertically resolved ozone trends are evaluated, including trends in the polar regions.
Xiaoyi Zhao, Vitali Fioletov, Michael Brohart, Volodya Savastiouk, Ihab Abboud, Akira Ogyu, Jonathan Davies, Reno Sit, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, Moritz Müller, Debora Griffin, and Chris McLinden
Atmos. Meas. Tech., 14, 2261–2283, https://doi.org/10.5194/amt-14-2261-2021, https://doi.org/10.5194/amt-14-2261-2021, 2021
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The Brewer spectrophotometer is one of the main instruments for measurements of atmospheric total column ozone. The global Brewer network largely relies on the world reference instruments (the Brewer triad) operated by Environment and Climate Change Canada since the early 1980s. This study provides an updated assessment (1999–2019) of the reference instrument performance, in terms of random uncertainties and long-term stability.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Doug A. Degenstein, Felicia Kolonjari, David Plummer, Douglas E. Kinnison, Patrick Jöckel, and Thomas von Clarmann
Atmos. Meas. Tech., 14, 1425–1438, https://doi.org/10.5194/amt-14-1425-2021, https://doi.org/10.5194/amt-14-1425-2021, 2021
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Output from climate chemistry models (CMAM, EMAC, and WACCM) is used to estimate the expected geophysical variability of ozone concentrations between coincident satellite instrument measurement times and geolocations. We use the Canadian ACE-FTS and OSIRIS instruments as a case study. Ensemble mean estimates are used to optimize coincidence criteria between the two instruments, allowing for the use of more coincident profiles while providing an estimate of the geophysical variation.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
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This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Kimberlee Dubé, Adam Bourassa, Daniel Zawada, Douglas Degenstein, Robert Damadeo, David Flittner, and William Randel
Atmos. Meas. Tech., 14, 557–566, https://doi.org/10.5194/amt-14-557-2021, https://doi.org/10.5194/amt-14-557-2021, 2021
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SAGE III/ISS measures profiles of NO2; however the algorithm to convert raw measurements to NO2 concentration neglects variations caused by changes in chemistry over the course of a day. We devised a procedure to account for these diurnal variations and assess their impact on NO2 measurements from SAGE III/ISS. We find that the new NO2 concentration is more than 10 % lower than NO2 from the standard algorithm below 30 km, showing that this effect is important to consider at lower altitudes.
Anqi Li, Chris Z. Roth, Kristell Pérot, Ole Martin Christensen, Adam Bourassa, Doug A. Degenstein, and Donal P. Murtagh
Atmos. Meas. Tech., 13, 6215–6236, https://doi.org/10.5194/amt-13-6215-2020, https://doi.org/10.5194/amt-13-6215-2020, 2020
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The OSIRIS IR imager, one of the instruments on the Odin satellite, routinely measures the oxygen airglow at 1.27 μm. In this study, we primarily focus on the steps done for retrieving the calibrated IRA band limb radiance, the volume emission rate of O2(a1∆g) and finally the ozone number density. Specifically, we use a novel approach to address the issue of the measurements that were made close to the local sunrise, where the O2(a1∆g) diverges from the equilibrium state.
Mahesh Kovilakam, Larry W. Thomason, Nicholas Ernest, Landon Rieger, Adam Bourassa, and Luis Millán
Earth Syst. Sci. Data, 12, 2607–2634, https://doi.org/10.5194/essd-12-2607-2020, https://doi.org/10.5194/essd-12-2607-2020, 2020
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A robust stratospheric aerosol climatology is important as many global climate models (GCMs) make use of observed aerosol properties to prescribe aerosols in the stratosphere. Here, we present version 2.0 of the GloSSAC data set in which a new methodology is used for the post-2005 data that improves the quality of data in the lower stratosphere, which includes an improved 1020 nm extinction. Additionally, size information from multiwavelength measurements of SAGE III/ISS is provided.
Thomas von Clarmann, Douglas A. Degenstein, Nathaniel J. Livesey, Stefan Bender, Amy Braverman, André Butz, Steven Compernolle, Robert Damadeo, Seth Dueck, Patrick Eriksson, Bernd Funke, Margaret C. Johnson, Yasuko Kasai, Arno Keppens, Anne Kleinert, Natalya A. Kramarova, Alexandra Laeng, Bavo Langerock, Vivienne H. Payne, Alexei Rozanov, Tomohiro O. Sato, Matthias Schneider, Patrick Sheese, Viktoria Sofieva, Gabriele P. Stiller, Christian von Savigny, and Daniel Zawada
Atmos. Meas. Tech., 13, 4393–4436, https://doi.org/10.5194/amt-13-4393-2020, https://doi.org/10.5194/amt-13-4393-2020, 2020
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Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. This paper summarizes related techniques and provides recommendations for unified error reporting.
Monika E. Szeląg, Viktoria F. Sofieva, Doug Degenstein, Chris Roth, Sean Davis, and Lucien Froidevaux
Atmos. Chem. Phys., 20, 7035–7047, https://doi.org/10.5194/acp-20-7035-2020, https://doi.org/10.5194/acp-20-7035-2020, 2020
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We analyze seasonal dependence of stratospheric ozone trends over 2000–2018. We demonstrate that the mid-latitude upper stratospheric ozone recovery maximizes during local winters and equinoxes. In the tropics, a very strong seasonal dependence of ozone trends is observed at all altitudes. We found hemispheric asymmetry of summertime ozone trend patterns below 35 km. The seasonal dependence of ozone trends and stratospheric temperature trends shows a clear inter-relation of the trend patterns.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nicolas Theys, Diego G. Loyola, Pascal Hedelt, Nickolay A. Krotkov, and Can Li
Atmos. Chem. Phys., 20, 5591–5607, https://doi.org/10.5194/acp-20-5591-2020, https://doi.org/10.5194/acp-20-5591-2020, 2020
Jeffery Langille, Adam Bourassa, Laura L. Pan, Daniel Letros, Brian Solheim, Daniel Zawada, and Doug Degenstein
Atmos. Chem. Phys., 20, 5477–5486, https://doi.org/10.5194/acp-20-5477-2020, https://doi.org/10.5194/acp-20-5477-2020, 2020
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Water vapour (WV) is a highly variable and extremely important trace gas in Earth’s atmosphere. Due to its radiative and chemical properties, it is coupled to the climate in an extremely complex manner. This is especially true in the lowermost stratosphere (LMS). Despite its importance, the physical processes that control mixing and the distribution of WV in the LMS are poorly understood. This study provides observational evidence of moistening the LMS via mixing across the subtropical jet.
Xiaoyi Zhao, Debora Griffin, Vitali Fioletov, Chris McLinden, Alexander Cede, Martin Tiefengraber, Moritz Müller, Kristof Bognar, Kimberly Strong, Folkert Boersma, Henk Eskes, Jonathan Davies, Akira Ogyu, and Sum Chi Lee
Atmos. Meas. Tech., 13, 2131–2159, https://doi.org/10.5194/amt-13-2131-2020, https://doi.org/10.5194/amt-13-2131-2020, 2020
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Pandora NO2 measurements made at three sites located in the Toronto area are used to evaluate the TROPOspheric Monitoring Instrument (TROPOMI) NO2 data products, including standard NO2 and research data developed using a high-resolution regional air quality forecast model. TROPOMI pixels located upwind and downwind from the Pandora sites were analyzed by a new wind-based validation method, which revealed the spatial patterns of local and transported emissions and regional air quality changes.
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, https://doi.org/10.5194/amt-13-1427-2020, 2020
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This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Zoë Y. W. Davis, Udo Frieß, Kevin B. Strawbridge, Monika Aggarwaal, Sabour Baray, Elijah G. Schnitzler, Akshay Lobo, Vitali E. Fioletov, Ihab Abboud, Chris A. McLinden, Jim Whiteway, Megan D. Willis, Alex K. Y. Lee, Jeff Brook, Jason Olfert, Jason O'Brien, Ralf Staebler, Hans D. Osthoff, Cristian Mihele, and Robert McLaren
Atmos. Meas. Tech., 13, 1129–1155, https://doi.org/10.5194/amt-13-1129-2020, https://doi.org/10.5194/amt-13-1129-2020, 2020
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Here, we evaluate a ground-based remote sensing method (MAX-DOAS) for measuring total pollutant loading and vertical profiles of pollution in the lower atmosphere by comparing our method to a variety of other measurement methods (lidar, sunphotometer, active DOAS, and aircraft measurements). Measurements were made in the Athabasca Oil Sands Region in Alberta, Canada. The complex dataset provided a rare opportunity to evaluate the performance of MAX-DOAS under varying atmospheric conditions.
Mark W. Shephard, Enrico Dammers, Karen E. Cady-Pereira, Shailesh K. Kharol, Jesse Thompson, Yonatan Gainariu-Matz, Junhua Zhang, Chris A. McLinden, Andrew Kovachik, Michael Moran, Shabtai Bittman, Christopher E. Sioris, Debora Griffin, Matthew J. Alvarado, Chantelle Lonsdale, Verica Savic-Jovcic, and Qiong Zheng
Atmos. Chem. Phys., 20, 2277–2302, https://doi.org/10.5194/acp-20-2277-2020, https://doi.org/10.5194/acp-20-2277-2020, 2020
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Presented is a description and survey demonstrating the capabilities of the CrIS ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emission estimates of an agricultural hotspot.
Fei Liu, Bryan N. Duncan, Nickolay A. Krotkov, Lok N. Lamsal, Steffen Beirle, Debora Griffin, Chris A. McLinden, Daniel L. Goldberg, and Zifeng Lu
Atmos. Chem. Phys., 20, 99–116, https://doi.org/10.5194/acp-20-99-2020, https://doi.org/10.5194/acp-20-99-2020, 2020
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We present a novel method to infer CO2 emissions from individual power plants, based on satellite observations of co-emitted NO2. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the CEMS measurements for US power plants. The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting.
Zoe Y. W. Davis, Sabour Baray, Chris A. McLinden, Aida Khanbabakhani, William Fujs, Csilla Csukat, Jerzy Debosz, and Robert McLaren
Atmos. Chem. Phys., 19, 13871–13889, https://doi.org/10.5194/acp-19-13871-2019, https://doi.org/10.5194/acp-19-13871-2019, 2019
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In this paper, we describe the use of mobile vehicle-mounted instrumentation to measure pollutants both at the surface and overhead (via a telescope) that are coming from a source. This allows us to calculate the total emissions from the source, in this case the city of Sarnia, ON, including both industrial emissions and emissions from the city populace. In this paper, we talk about improvements to the technique in the form of extra instrumentation in the vehicle.
Katerina Garane, Maria-Elissavet Koukouli, Tijl Verhoelst, Christophe Lerot, Klaus-Peter Heue, Vitali Fioletov, Dimitrios Balis, Alkiviadis Bais, Ariane Bazureau, Angelika Dehn, Florence Goutail, Jose Granville, Debora Griffin, Daan Hubert, Arno Keppens, Jean-Christopher Lambert, Diego Loyola, Chris McLinden, Andrea Pazmino, Jean-Pierre Pommereau, Alberto Redondas, Fabian Romahn, Pieter Valks, Michel Van Roozendael, Jian Xu, Claus Zehner, Christos Zerefos, and Walter Zimmer
Atmos. Meas. Tech., 12, 5263–5287, https://doi.org/10.5194/amt-12-5263-2019, https://doi.org/10.5194/amt-12-5263-2019, 2019
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The Sentinel-5 Precursor TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are validated against direct-sun and twilight zenith-sky ground-based TOC measurements and other already known spaceborne sensors. The results show that the TROPOMI TOC measurements are in very good agreement with the ground-based measurements and satellite sensor measurements and that they are well within the product requirements.
Enrico Dammers, Chris A. McLinden, Debora Griffin, Mark W. Shephard, Shelley Van Der Graaf, Erik Lutsch, Martijn Schaap, Yonatan Gainairu-Matz, Vitali Fioletov, Martin Van Damme, Simon Whitburn, Lieven Clarisse, Karen Cady-Pereira, Cathy Clerbaux, Pierre Francois Coheur, and Jan Willem Erisman
Atmos. Chem. Phys., 19, 12261–12293, https://doi.org/10.5194/acp-19-12261-2019, https://doi.org/10.5194/acp-19-12261-2019, 2019
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Ammonia is an essential molecule in the environment, but at its current levels it is unsustainable. However, the emissions are highly uncertain. We explore the use of satellites to estimate the ammonia lifetime and emissions around point sources to help improve the budget. The same method applied to different satellite instruments shows consistent results. Comparison to the emission inventories shows that those are underestimating emissions of point sources by on average a factor of 2.5.
Xiaoyi Zhao, Debora Griffin, Vitali Fioletov, Chris McLinden, Jonathan Davies, Akira Ogyu, Sum Chi Lee, Alexandru Lupu, Michael D. Moran, Alexander Cede, Martin Tiefengraber, and Moritz Müller
Atmos. Chem. Phys., 19, 10619–10642, https://doi.org/10.5194/acp-19-10619-2019, https://doi.org/10.5194/acp-19-10619-2019, 2019
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New nitrogen dioxide (NO2) retrieval algorithms are developed for Pandora zenith-sky measurements. A column-to-surface conversion look-up table was produced for the Pandora instruments; therefore, quick and practical Pandora-based surface NO2 concentration data can be obtained for air quality monitoring purposes. It is demonstrated that the surface NO2 concentration is controlled not only by the planetary boundary layer height but also by both boundary layer dynamics and photochemistry.
Jacob Zalach, Christian von Savigny, Arvid Langenbach, Gerd Baumgarten, Franz-Josef Lübken, and Adam Bourassa
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-267, https://doi.org/10.5194/amt-2019-267, 2019
Revised manuscript not accepted
Elizaveta Malinina, Alexei Rozanov, Landon Rieger, Adam Bourassa, Heinrich Bovensmann, John P. Burrows, and Doug Degenstein
Atmos. Meas. Tech., 12, 3485–3502, https://doi.org/10.5194/amt-12-3485-2019, https://doi.org/10.5194/amt-12-3485-2019, 2019
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This paper covers the problems related to the derivation of aerosol extinction coefficients and Ångström exponents from space-borne instruments working in limb and occultation viewing geometries. Aerosol extinction coefficients and Ångström exponents were calculated from the SCIAMACHY aerosol particle size data set. The results were compared with the data from SAGE II and OSIRIS. The Ångström exponent in the tropical regions and its dependency on particle size parameters are discussed.
Cristen Adams, Chris A. McLinden, Mark W. Shephard, Nolan Dickson, Enrico Dammers, Jack Chen, Paul Makar, Karen E. Cady-Pereira, Naomi Tam, Shailesh K. Kharol, Lok N. Lamsal, and Nickolay A. Krotkov
Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, https://doi.org/10.5194/acp-19-2577-2019, 2019
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We estimated how much carbon monoxide, ammonia, and nitrogen oxides were emitted in the smoke from the Fort McMurray Horse River wildfire using satellite data and air quality models. The fire emitted amounts of carbon monoxide that were similar to anthropogenic (human-caused) emissions for all of Alberta over a full year. We also estimated large amounts of ammonia and nitrogen oxides emitted from the fire. These results can be used to evaluate the performance of air quality forecasting models.
Jeffery Langille, Daniel Letros, Adam Bourassa, Brian Solheim, Doug Degenstein, Fabien Dupont, Daniel Zawada, and Nick D. Lloyd
Atmos. Meas. Tech., 12, 431–455, https://doi.org/10.5194/amt-12-431-2019, https://doi.org/10.5194/amt-12-431-2019, 2019
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The SHOW instrument is a prototype satellite concept that is being developed through collaboration between the University of Saskatchewan, the Canadian Space Agency, and ABB Inc. to provide high vertical resolution (< 200 m) measurements of UTLS water vapour with < 1 ppm accuracy. This paper presents suborbital measurements obtained during a demonstration flight aboard NASA's ER-2 aircraft. These measurements are validated through a comparison with coincident radiosonde measurements.
Debora Griffin, Kaley A. Walker, Ingo Wohltmann, Sandip S. Dhomse, Markus Rex, Martyn P. Chipperfield, Wuhu Feng, Gloria L. Manney, Jane Liu, and David Tarasick
Atmos. Chem. Phys., 19, 577–601, https://doi.org/10.5194/acp-19-577-2019, https://doi.org/10.5194/acp-19-577-2019, 2019
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Ozone in the stratosphere is important to protect the Earth from UV radiation. Using measurements taken by the Atmospheric Chemistry Experiment satellite between 2005 and 2013, we examine different methods to calculate the ozone loss in the high Arctic and establish the altitude at which most of the ozone is destroyed. Our results show that the different methods agree within the uncertainties. Recommendations are made on which methods are most appropriate to use.
Fei Liu, Sungyeon Choi, Can Li, Vitali E. Fioletov, Chris A. McLinden, Joanna Joiner, Nickolay A. Krotkov, Huisheng Bian, Greet Janssens-Maenhout, Anton S. Darmenov, and Arlindo M. da Silva
Atmos. Chem. Phys., 18, 16571–16586, https://doi.org/10.5194/acp-18-16571-2018, https://doi.org/10.5194/acp-18-16571-2018, 2018
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Sulfur dioxide measurements from space have been used to detect emissions from large sources. We developed a new emission inventory by combining the satellite-based emission estimates and the conventional bottom-up inventory for smaller sources. The new inventory improves the model agreement with in situ observations and offers the possibility of rapid updates to emissions.
Jeffrey A. Geddes, Randall V. Martin, Eric J. Bucsela, Chris A. McLinden, and Daniel J. M. Cunningham
Atmos. Meas. Tech., 11, 6271–6287, https://doi.org/10.5194/amt-11-6271-2018, https://doi.org/10.5194/amt-11-6271-2018, 2018
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This paper describes an approach for separating the stratospheric and tropospheric contributions in geostationary observations of nitrogen dioxide from the upcoming TEMPO instrument. We find minimal impact of the limited field of observation compared to previous low-Earth-observing systems with global coverage. We find that continued development of low-Earth-orbit retrievals will benefit geostationary data by providing important context outside the field of regard.
Landon A. Rieger, Elizaveta P. Malinina, Alexei V. Rozanov, John P. Burrows, Adam E. Bourassa, and Doug A. Degenstein
Atmos. Meas. Tech., 11, 3433–3445, https://doi.org/10.5194/amt-11-3433-2018, https://doi.org/10.5194/amt-11-3433-2018, 2018
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This paper compares aerosol extinction records from two limb scattering instruments, OSIRIS and SCIAMACHY, to that from the occultation instrument SAGE II. Differences are investigated through modelling and retrieval studies and important sources of systematic errors are quantified. It is found that the largest biases come from uncertainties in the aerosol size distribution and the aerosol particle concentration at altitudes above 30 km.
Matthew J. Cooper, Randall V. Martin, Alexei I. Lyapustin, and Chris A. McLinden
Atmos. Meas. Tech., 11, 2983–2994, https://doi.org/10.5194/amt-11-2983-2018, https://doi.org/10.5194/amt-11-2983-2018, 2018
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To accurately infer air pollutant concentrations from satellite observations, we must first know the reflectivity of the Earth’s surface. Using a model, we show that satellite observations are better able to observe NO2 near the surface if snow is present. However, knowing when snow is present is difficult due to its variability. We test seven existing snow cover data sets to assess their ability to inform future satellite observations and find that the IMS data set is best suited for this task.
Natalya A. Kramarova, Pawan K. Bhartia, Glen Jaross, Leslie Moy, Philippe Xu, Zhong Chen, Matthew DeLand, Lucien Froidevaux, Nathaniel Livesey, Douglas Degenstein, Adam Bourassa, Kaley A. Walker, and Patrick Sheese
Atmos. Meas. Tech., 11, 2837–2861, https://doi.org/10.5194/amt-11-2837-2018, https://doi.org/10.5194/amt-11-2837-2018, 2018
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The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) is a newly designed research sensor aiming to continue high vertical resolution ozone records from space-borne sensors. In summer 2017 all LP measurements were processed with the new version 2.5 algorithm. In this paper we provide a description of the key changes implemented in the new algorithm and evaluate the quality of ozone retrievals by comparing with independent satellite profile measurements (MLS, ACE-FTS and OSIRIS).
Daniel J. Zawada, Landon A. Rieger, Adam E. Bourassa, and Douglas A. Degenstein
Atmos. Meas. Tech., 11, 2375–2393, https://doi.org/10.5194/amt-11-2375-2018, https://doi.org/10.5194/amt-11-2375-2018, 2018
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The Ozone Mapping and Profiler Suite Limb Profiler measures scattered sunlight, which is then inverted to obtain vertical profiles of ozone in the atmosphere. We have developed a new algorithm for inverting the data which is better suited for areas with large horizontal ozone gradients, such as the polar vortex. Data from the full currently 5-year mission have been processed and are publicly available.
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
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The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Keith A. Tereszchuk, Yves J. Rochon, Chris A. McLinden, and Paul A. Vaillancourt
Geosci. Model Dev., 11, 1093–1113, https://doi.org/10.5194/gmd-11-1093-2018, https://doi.org/10.5194/gmd-11-1093-2018, 2018
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To reduce computational costs, ECCC's new method to calculate the UV Index involves scaling and weighting the irradiance contribution of four low-res UV broadbands currently produced by the GEM forecast model. A high-res irradiance spectrum was produced using Cloud-J to create simulated GEM broadbands to calibrate the original GEM broadbands. The scaled GEM broadbands are then weighted accordingly so that the resultant UV Index field emulates the high-res UV Index field calculated from Cloud-J.
Larry W. Thomason, Nicholas Ernest, Luis Millán, Landon Rieger, Adam Bourassa, Jean-Paul Vernier, Gloria Manney, Beiping Luo, Florian Arfeuille, and Thomas Peter
Earth Syst. Sci. Data, 10, 469–492, https://doi.org/10.5194/essd-10-469-2018, https://doi.org/10.5194/essd-10-469-2018, 2018
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We describe the construction of a continuous 38-year record of stratospheric aerosol optical properties. The Global Space-based Stratospheric Aerosol Climatology, or GloSSAC, provided the input data to the construction of the Climate Model Intercomparison Project stratospheric aerosol forcing data set (1979 to 2014) and is now extended through 2016. GloSSAC focuses on the the SAGE series of instruments through mid-2005 and on OSIRIS and CALIPSO after that time.
William T. Ball, Justin Alsing, Daniel J. Mortlock, Johannes Staehelin, Joanna D. Haigh, Thomas Peter, Fiona Tummon, Rene Stübi, Andrea Stenke, John Anderson, Adam Bourassa, Sean M. Davis, Doug Degenstein, Stacey Frith, Lucien Froidevaux, Chris Roth, Viktoria Sofieva, Ray Wang, Jeannette Wild, Pengfei Yu, Jerald R. Ziemke, and Eugene V. Rozanov
Atmos. Chem. Phys., 18, 1379–1394, https://doi.org/10.5194/acp-18-1379-2018, https://doi.org/10.5194/acp-18-1379-2018, 2018
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Using a robust analysis, with artefact-corrected ozone data, we confirm upper stratospheric ozone is recovering following the Montreal Protocol, but that lower stratospheric ozone (50° S–50° N) has continued to decrease since 1998, and the ozone layer as a whole (60° S–60° N) may be lower today than in 1998. No change in total column ozone may be due to increasing tropospheric ozone. State-of-the-art models do not reproduce lower stratospheric ozone decreases.
Adam E. Bourassa, Chris Z. Roth, Daniel J. Zawada, Landon A. Rieger, Chris A. McLinden, and Douglas A. Degenstein
Atmos. Meas. Tech., 11, 489–498, https://doi.org/10.5194/amt-11-489-2018, https://doi.org/10.5194/amt-11-489-2018, 2018
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OSIRIS satellite measurements of ozone in the stratosphere are corrected for slowly varying errors. These changes make the OSIRIS data compare better with other satellite measurements over the long term and make an impact on our understanding of the recovery of the ozone layer.
Viktoria F. Sofieva, Erkki Kyrölä, Marko Laine, Johanna Tamminen, Doug Degenstein, Adam Bourassa, Chris Roth, Daniel Zawada, Mark Weber, Alexei Rozanov, Nabiz Rahpoe, Gabriele Stiller, Alexandra Laeng, Thomas von Clarmann, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Claus Zehner, Robert Damadeo, Joseph Zawodny, Natalya Kramarova, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 12533–12552, https://doi.org/10.5194/acp-17-12533-2017, https://doi.org/10.5194/acp-17-12533-2017, 2017
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We present a merged dataset of ozone profiles from several satellite instruments: SAGE II, GOMOS, SCIAMACHY, MIPAS, OSIRIS, ACE-FTS and OMPS. For merging, we used the latest versions of the original ozone datasets.
The merged SAGE–CCI–OMPS dataset is used for evaluating ozone trends in the stratosphere through multiple linear regression. Negative ozone trends in the upper stratosphere are observed before 1997 and positive trends are found after 1997.
Wolfgang Steinbrecht, Lucien Froidevaux, Ryan Fuller, Ray Wang, John Anderson, Chris Roth, Adam Bourassa, Doug Degenstein, Robert Damadeo, Joe Zawodny, Stacey Frith, Richard McPeters, Pawan Bhartia, Jeannette Wild, Craig Long, Sean Davis, Karen Rosenlof, Viktoria Sofieva, Kaley Walker, Nabiz Rahpoe, Alexei Rozanov, Mark Weber, Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Natalya Kramarova, Sophie Godin-Beekmann, Thierry Leblanc, Richard Querel, Daan Swart, Ian Boyd, Klemens Hocke, Niklaus Kämpfer, Eliane Maillard Barras, Lorena Moreira, Gerald Nedoluha, Corinne Vigouroux, Thomas Blumenstock, Matthias Schneider, Omaira García, Nicholas Jones, Emmanuel Mahieu, Dan Smale, Michael Kotkamp, John Robinson, Irina Petropavlovskikh, Neil Harris, Birgit Hassler, Daan Hubert, and Fiona Tummon
Atmos. Chem. Phys., 17, 10675–10690, https://doi.org/10.5194/acp-17-10675-2017, https://doi.org/10.5194/acp-17-10675-2017, 2017
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Thanks to the 1987 Montreal Protocol and its amendments, ozone-depleting chlorine (and bromine) in the stratosphere has declined slowly since the late 1990s. Improved and extended long-term ozone profile observations from satellites and ground-based stations confirm that ozone is responding as expected and has increased by about 2 % per decade since 2000 in the upper stratosphere, around 40 km altitude. At lower altitudes, however, ozone has not changed significantly since 2000.
Debora Griffin, Kaley A. Walker, Stephanie Conway, Felicia Kolonjari, Kimberly Strong, Rebecca Batchelor, Chris D. Boone, Lin Dan, James R. Drummond, Pierre F. Fogal, Dejian Fu, Rodica Lindenmaier, Gloria L. Manney, and Dan Weaver
Atmos. Meas. Tech., 10, 3273–3294, https://doi.org/10.5194/amt-10-3273-2017, https://doi.org/10.5194/amt-10-3273-2017, 2017
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Measurements in the high Arctic from two ground-based and one space-borne infrared Fourier transform spectrometer agree well over an 8-year time period (2006–2013). These comparisons show no notable degradation, indicating the consistency of these data sets and suggesting that the space-borne measurements have been stable. Increasing ozone, as well as increases of some other atmospheric gases, has been found over this same time period.
Cristen Adams, Adam E. Bourassa, Chris A. McLinden, Chris E. Sioris, Thomas von Clarmann, Bernd Funke, Landon A. Rieger, and Douglas A. Degenstein
Atmos. Chem. Phys., 17, 8063–8080, https://doi.org/10.5194/acp-17-8063-2017, https://doi.org/10.5194/acp-17-8063-2017, 2017
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We measured the relationship between volcanic aerosol and trace gases in the stratosphere using the OSIRIS and MIPAS satellite instruments between 2002 and 2014. We found that levels of stratospheric NO2 and N2O5 both decreased significantly in the presence of volcanic aerosol. These decreases were consistent with the modeling results.
Shailesh K. Kharol, Chris A. McLinden, Christopher E. Sioris, Mark W. Shephard, Vitali Fioletov, Aaron van Donkelaar, Sajeev Philip, and Randall V. Martin
Atmos. Chem. Phys., 17, 5921–5929, https://doi.org/10.5194/acp-17-5921-2017, https://doi.org/10.5194/acp-17-5921-2017, 2017
Yan Zhang, Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 10, 1495–1509, https://doi.org/10.5194/amt-10-1495-2017, https://doi.org/10.5194/amt-10-1495-2017, 2017
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In this study, we demonstrate a very good consistency of the SO2 retrievals from OMI and OMPS using our state-of-the-art principal component analysis technique. Four full years of OMI and OMPS SO2 retrievals, during 2012–2015 have been analyzed over some of the world’s most polluted regions: eastern China, Mexico, and South Africa. The consistency of retrievals between OMI and OMPS make it possible to continue the long-term global SO2 pollution monitoring.
Christopher E. Sioris, Landon A. Rieger, Nicholas D. Lloyd, Adam E. Bourassa, Chris Z. Roth, Douglas A. Degenstein, Claude Camy-Peyret, Klaus Pfeilsticker, Gwenaël Berthet, Valéry Catoire, Florence Goutail, Jean-Pierre Pommereau, and Chris A. McLinden
Atmos. Meas. Tech., 10, 1155–1168, https://doi.org/10.5194/amt-10-1155-2017, https://doi.org/10.5194/amt-10-1155-2017, 2017
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A new OSIRIS NO2 retrieval algorithm is described and validated using > 40 balloon-based profile measurements. The validation results indicate a slight improvement relative to the existing operational algorithm in terms of the bias versus the balloon data, particularly in the lower stratosphere. The implication is that this new algorithm should replace the operational one. The motivation was to combine spectral fitting and the SaskTRAN radiative transfer model to achieve an improved product.
Gwenaël Berthet, Fabrice Jégou, Valéry Catoire, Gisèle Krysztofiak, Jean-Baptiste Renard, Adam E. Bourassa, Doug A. Degenstein, Colette Brogniez, Marcel Dorf, Sebastian Kreycy, Klaus Pfeilsticker, Bodo Werner, Franck Lefèvre, Tjarda J. Roberts, Thibaut Lurton, Damien Vignelles, Nelson Bègue, Quentin Bourgeois, Daniel Daugeron, Michel Chartier, Claude Robert, Bertrand Gaubicher, and Christophe Guimbaud
Atmos. Chem. Phys., 17, 2229–2253, https://doi.org/10.5194/acp-17-2229-2017, https://doi.org/10.5194/acp-17-2229-2017, 2017
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Since the last major volcanic event, i.e. the Pinatubo eruption in 1991, only
moderateeruptions have regularly injected sulfur into the stratosphere, typically enhancing the aerosol loading for several months. We investigate here for the first time the chemical perturbation associated with the Sarychev eruption in June 2009, using balloon-borne instruments and model calculations. Some chemical compounds are significantly affected by the aerosols, but the impact on stratospheric ozone is weak.
Christopher E. Sioris, Chris A. McLinden, Mark W. Shephard, Vitali E. Fioletov, and Ihab Abboud
Atmos. Chem. Phys., 17, 1931–1943, https://doi.org/10.5194/acp-17-1931-2017, https://doi.org/10.5194/acp-17-1931-2017, 2017
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The contribution of the oil sands region to the local aerosol optical depth (AOD) is sought. Satellite data are used since they provide spatial coverage over many years. Satellites measure AOD with high correlation and small biases relative to coincident AERONET AODs. Trends are determined using annual mean AODs, and an increasing trend is found near the Shell mines. Spatially variable and high surface albedo is challenging for some sensors. Measuring polarization appears to be an asset.
Sergey M. Khaykin, Sophie Godin-Beekmann, Philippe Keckhut, Alain Hauchecorne, Julien Jumelet, Jean-Paul Vernier, Adam Bourassa, Doug A. Degenstein, Landon A. Rieger, Christine Bingen, Filip Vanhellemont, Charles Robert, Matthew DeLand, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, https://doi.org/10.5194/acp-17-1829-2017, 2017
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The article is devoted to the long-term evolution and variability of stratospheric aerosol, which plays an important role in climate change and the ozone layer. We use 22-year long continuous observations using laser radar soundings in southern France and satellite-based observations to distinguish between natural aerosol variability (caused by volcanic eruptions) and human-induced change in aerosol concentration. An influence of growing pollution above Asia on stratospheric aerosol is found.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Chris A. McLinden, Peter F. Bernath, Adam E. Bourassa, John P. Burrows, Doug A. Degenstein, Bernd Funke, Didier Fussen, Gloria L. Manney, C. Thomas McElroy, Donal Murtagh, Cora E. Randall, Piera Raspollini, Alexei Rozanov, James M. Russell III, Makoto Suzuki, Masato Shiotani, Joachim Urban, Thomas von Clarmann, and Joseph M. Zawodny
Atmos. Meas. Tech., 9, 5781–5810, https://doi.org/10.5194/amt-9-5781-2016, https://doi.org/10.5194/amt-9-5781-2016, 2016
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This study validates version 3.5 of the ACE-FTS NOy species data sets by comparing diurnally scaled ACE-FTS data to correlative data from 11 other satellite limb sounders. For all five species examined (NO, NO2, HNO3, N2O5, and ClONO2), there is good agreement between ACE-FTS and the other data sets in various regions of the atmosphere. In these validated regions, these NOy data products can be used for further investigation into the composition, dynamics, and climate of the stratosphere.
Charles Étienne Robert, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Emmanuel Dekemper, Cédric Tétard, Didier Fussen, Adam Bourassa, and Claus Zehner
Atmos. Meas. Tech., 9, 4701–4718, https://doi.org/10.5194/amt-9-4701-2016, https://doi.org/10.5194/amt-9-4701-2016, 2016
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We compare stratospheric aerosol loading computed with a new computer algorithm with various established datasets to determine the overall agreement. Since the new results are based on observation of starlight through the Earth's atmosphere, various aspects of these measurements can influence the final results. A systematic analysis of these aspects, such as the star brightness and temperature, is carried out to see if, and how, they influence the agreement of the results with other datasets.
Vitali E. Fioletov, Chris A. McLinden, Nickolay Krotkov, Can Li, Joanna Joiner, Nicolas Theys, Simon Carn, and Mike D. Moran
Atmos. Chem. Phys., 16, 11497–11519, https://doi.org/10.5194/acp-16-11497-2016, https://doi.org/10.5194/acp-16-11497-2016, 2016
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We introduce the first space-based catalogue of SO2 emission sources seen by OMI. The inventory contains about 500 sources. They account for about a half of all SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr−1 and not detected by OMI. The sources are grouped by type (volcanoes, power plants, oil- and gas-related sources, and smelters) and country. The catalogue presented herein can be used for verification of available SO2 emission inventories.
Cristen Adams, Elise N. Normand, Chris A. McLinden, Adam E. Bourassa, Nicholas D. Lloyd, Douglas A. Degenstein, Nickolay A. Krotkov, Maria Belmonte Rivas, K. Folkert Boersma, and Henk Eskes
Atmos. Meas. Tech., 9, 4103–4122, https://doi.org/10.5194/amt-9-4103-2016, https://doi.org/10.5194/amt-9-4103-2016, 2016
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A new "OMI-minus-OSIRIS" (OmO) prototype dataset for tropospheric NO2 was created by combining information from the OMI satellite instrument, which is sensitive to NO2 in both the troposphere and stratosphere, with information from the OSIRIS satellite instrument, which measures NO2 in the stratosphere. This paper demonstrates that this approach is feasible and could be applied to future geostationary missions.
Vitali E. Fioletov, Chris A. McLinden, Alexander Cede, Jonathan Davies, Cristian Mihele, Stoyka Netcheva, Shao-Meng Li, and Jason O'Brien
Atmos. Meas. Tech., 9, 2961–2976, https://doi.org/10.5194/amt-9-2961-2016, https://doi.org/10.5194/amt-9-2961-2016, 2016
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, https://doi.org/10.5194/amt-9-2497-2016, https://doi.org/10.5194/amt-9-2497-2016, 2016
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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.
Nickolay A. Krotkov, Chris A. McLinden, Can Li, Lok N. Lamsal, Edward A. Celarier, Sergey V. Marchenko, William H. Swartz, Eric J. Bucsela, Joanna Joiner, Bryan N. Duncan, K. Folkert Boersma, J. Pepijn Veefkind, Pieternel F. Levelt, Vitali E. Fioletov, Russell R. Dickerson, Hao He, Zifeng Lu, and David G. Streets
Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, https://doi.org/10.5194/acp-16-4605-2016, 2016
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We examine changes in SO2 and NO2 over the world's most polluted regions during the first decade of Aura OMI observations. Over the eastern US, both NO2 and SO2 levels decreased by 40 % and 80 %, respectively. OMI confirmed large reductions in SO2 over eastern Europe's largest coal power plants. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend been observed since 2011, with a 50 % reduction in 2012–2014. India's SO2 and NO2 levels are growing at a fast pace.
B. J. Elash, A. E. Bourassa, P. R. Loewen, N. D. Lloyd, and D. A. Degenstein
Atmos. Meas. Tech., 9, 1261–1277, https://doi.org/10.5194/amt-9-1261-2016, https://doi.org/10.5194/amt-9-1261-2016, 2016
M. W. Shephard, C. A. McLinden, K. E. Cady-Pereira, M. Luo, S. G. Moussa, A. Leithead, J. Liggio, R. M. Staebler, A. Akingunola, P. Makar, P. Lehr, J. Zhang, D. K. Henze, D. B. Millet, J. O. Bash, L. Zhu, K. C. Wells, S. L. Capps, S. Chaliyakunnel, M. Gordon, K. Hayden, J. R. Brook, M. Wolde, and S.-M. Li
Atmos. Meas. Tech., 8, 5189–5211, https://doi.org/10.5194/amt-8-5189-2015, https://doi.org/10.5194/amt-8-5189-2015, 2015
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This study provides direct validations of Tropospheric Emission Spectrometer (TES) satellite retrieved profiles against coincident aircraft profiles of carbon monoxide, ammonia, methanol, and formic acid, all of which are of interest for air quality. The comparisons are performed over the Canadian oil sands region during an intensive field campaign in support of the Joint Canada-Alberta Implementation Plan for the Oil Sands Monitoring (JOSM). Initial model evaluations are also provided.
D. Pendlebury, D. Plummer, J. Scinocca, P. Sheese, K. Strong, K. Walker, and D. Degenstein
Atmos. Chem. Phys., 15, 12465–12485, https://doi.org/10.5194/acp-15-12465-2015, https://doi.org/10.5194/acp-15-12465-2015, 2015
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The CMAM30 data set takes a chemistry-climate model and relaxes the dynamics to reanalysis, which can then provide chemistry fields not available from the reanalysis data set. This paper addresses this gap by comparing temperature, water vapour, ozone and methane to satellite data to determine and document any biases in the model fields. The lack of ozone destruction and dehydration in the SH polar vortex is shown to be due to the treatment of polar stratosphere clouds in the model.
F. Deng, D. B. A. Jones, T. W. Walker, M. Keller, K. W. Bowman, D. K. Henze, R. Nassar, E. A. Kort, S. C. Wofsy, K. A. Walker, A. E. Bourassa, and D. A. Degenstein
Atmos. Chem. Phys., 15, 11773–11788, https://doi.org/10.5194/acp-15-11773-2015, https://doi.org/10.5194/acp-15-11773-2015, 2015
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The upper troposphere and lower stratosphere (UTLS) is characterized by strong gradients in the distribution of long-lived tracers, which are sensitive to discrepancies in transport in models. We found that our model overestimates CO2 in the polar UTLS through comparison of modeled CO2 with aircraft observations. We then corrected the modeled CO2 and quantified the impact of the correction on the flux estimates using an atmospheric model together with atmospheric CO2 measured from a satellite.
N. Rahpoe, M. Weber, A. V. Rozanov, K. Weigel, H. Bovensmann, J. P. Burrows, A. Laeng, G. Stiller, T. von Clarmann, E. Kyrölä, V. F. Sofieva, J. Tamminen, K. Walker, D. Degenstein, A. E. Bourassa, R. Hargreaves, P. Bernath, J. Urban, and D. P. Murtagh
Atmos. Meas. Tech., 8, 4369–4381, https://doi.org/10.5194/amt-8-4369-2015, https://doi.org/10.5194/amt-8-4369-2015, 2015
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The analyses among six satellite instruments measuring ozone reveals that the relative drift between the sensors is not significant in the stratosphere and we conclude that merging of data from these instruments is possible. The merged ozone profiles can then be ingested in global climate models for long-term forecasts of ozone and climate change in the atmosphere. The added drift uncertainty is estimated at about 3% per decade (1 sigma) and should be applied in the calculation of ozone trends.
N. R. P. Harris, B. Hassler, F. Tummon, G. E. Bodeker, D. Hubert, I. Petropavlovskikh, W. Steinbrecht, J. Anderson, P. K. Bhartia, C. D. Boone, A. Bourassa, S. M. Davis, D. Degenstein, A. Delcloo, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, N. Jones, M. J. Kurylo, E. Kyrölä, M. Laine, S. T. Leblanc, J.-C. Lambert, B. Liley, E. Mahieu, A. Maycock, M. de Mazière, A. Parrish, R. Querel, K. H. Rosenlof, C. Roth, C. Sioris, J. Staehelin, R. S. Stolarski, R. Stübi, J. Tamminen, C. Vigouroux, K. A. Walker, H. J. Wang, J. Wild, and J. M. Zawodny
Atmos. Chem. Phys., 15, 9965–9982, https://doi.org/10.5194/acp-15-9965-2015, https://doi.org/10.5194/acp-15-9965-2015, 2015
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Trends in the vertical distribution of ozone are reported for new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere peaked in the second half of the 1990s. We examine the trends before and after that peak to see if any change in trend is discernible. The previously reported decreases are confirmed. Furthermore, the downward trend in upper stratospheric ozone has not continued. The possible significance of any increase is discussed in detail.
D. J. Zawada, S. R. Dueck, L. A. Rieger, A. E. Bourassa, N. D. Lloyd, and D. A. Degenstein
Atmos. Meas. Tech., 8, 2609–2623, https://doi.org/10.5194/amt-8-2609-2015, https://doi.org/10.5194/amt-8-2609-2015, 2015
F. Tummon, B. Hassler, N. R. P. Harris, J. Staehelin, W. Steinbrecht, J. Anderson, G. E. Bodeker, A. Bourassa, S. M. Davis, D. Degenstein, S. M. Frith, L. Froidevaux, E. Kyrölä, M. Laine, C. Long, A. A. Penckwitt, C. E. Sioris, K. H. Rosenlof, C. Roth, H.-J. Wang, and J. Wild
Atmos. Chem. Phys., 15, 3021–3043, https://doi.org/10.5194/acp-15-3021-2015, https://doi.org/10.5194/acp-15-3021-2015, 2015
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Understanding ozone trends in the vertical is vital in terms of assessing the success of the Montreal Protocol. This paper compares and analyses the long-term trends in stratospheric ozone from seven new merged satellite data sets. The data sets largely agree well with each other, particularly for the negative trends seen in the early period 1984-1997. For the 1998-2011 period there is less agreement, but a clear shift from negative to mostly positive trends.
A. Laeng, U. Grabowski, T. von Clarmann, G. Stiller, N. Glatthor, M. Höpfner, S. Kellmann, M. Kiefer, A. Linden, S. Lossow, V. Sofieva, I. Petropavlovskikh, D. Hubert, T. Bathgate, P. Bernath, C. D. Boone, C. Clerbaux, P. Coheur, R. Damadeo, D. Degenstein, S. Frith, L. Froidevaux, J. Gille, K. Hoppel, M. McHugh, Y. Kasai, J. Lumpe, N. Rahpoe, G. Toon, T. Sano, M. Suzuki, J. Tamminen, J. Urban, K. Walker, M. Weber, and J. Zawodny
Atmos. Meas. Tech., 7, 3971–3987, https://doi.org/10.5194/amt-7-3971-2014, https://doi.org/10.5194/amt-7-3971-2014, 2014
J. E. Franklin, J. R. Drummond, D. Griffin, J. R. Pierce, D. L. Waugh, P. I. Palmer, M. Parrington, J. D. Lee, A. C. Lewis, A. R. Rickard, J. W. Taylor, J. D. Allan, H. Coe, K. A. Walker, L. Chisholm, T. J. Duck, J. T. Hopper, Y. Blanchard, M. D. Gibson, K. R. Curry, K. M. Sakamoto, G. Lesins, L. Dan, J. Kliever, and A. Saha
Atmos. Chem. Phys., 14, 8449–8460, https://doi.org/10.5194/acp-14-8449-2014, https://doi.org/10.5194/acp-14-8449-2014, 2014
A. E. Bourassa, D. A. Degenstein, W. J. Randel, J. M. Zawodny, E. Kyrölä, C. A. McLinden, C. E. Sioris, and C. Z. Roth
Atmos. Chem. Phys., 14, 6983–6994, https://doi.org/10.5194/acp-14-6983-2014, https://doi.org/10.5194/acp-14-6983-2014, 2014
B. Hassler, I. Petropavlovskikh, J. Staehelin, T. August, P. K. Bhartia, C. Clerbaux, D. Degenstein, M. De Mazière, B. M. Dinelli, A. Dudhia, G. Dufour, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, J. Granville, N. R. P. Harris, K. Hoppel, D. Hubert, Y. Kasai, M. J. Kurylo, E. Kyrölä, J.-C. Lambert, P. F. Levelt, C. T. McElroy, R. D. McPeters, R. Munro, H. Nakajima, A. Parrish, P. Raspollini, E. E. Remsberg, K. H. Rosenlof, A. Rozanov, T. Sano, Y. Sasano, M. Shiotani, H. G. J. Smit, G. Stiller, J. Tamminen, D. W. Tarasick, J. Urban, R. J. van der A, J. P. Veefkind, C. Vigouroux, T. von Clarmann, C. von Savigny, K. A. Walker, M. Weber, J. Wild, and J. M. Zawodny
Atmos. Meas. Tech., 7, 1395–1427, https://doi.org/10.5194/amt-7-1395-2014, https://doi.org/10.5194/amt-7-1395-2014, 2014
C. A. McLinden, V. Fioletov, K. F. Boersma, S. K. Kharol, N. Krotkov, L. Lamsal, P. A. Makar, R. V. Martin, J. P. Veefkind, and K. Yang
Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, https://doi.org/10.5194/acp-14-3637-2014, 2014
C. E. Sioris, C. A. McLinden, V. E. Fioletov, C. Adams, J. M. Zawodny, A. E. Bourassa, C. Z. Roth, and D. A. Degenstein
Atmos. Chem. Phys., 14, 3479–3496, https://doi.org/10.5194/acp-14-3479-2014, https://doi.org/10.5194/acp-14-3479-2014, 2014
L. A. Rieger, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 7, 777–780, https://doi.org/10.5194/amt-7-777-2014, https://doi.org/10.5194/amt-7-777-2014, 2014
E. Eckert, T. von Clarmann, M. Kiefer, G. P. Stiller, S. Lossow, N. Glatthor, D. A. Degenstein, L. Froidevaux, S. Godin-Beekmann, T. Leblanc, S. McDermid, M. Pastel, W. Steinbrecht, D. P. J. Swart, K. A. Walker, and P. F. Bernath
Atmos. Chem. Phys., 14, 2571–2589, https://doi.org/10.5194/acp-14-2571-2014, https://doi.org/10.5194/acp-14-2571-2014, 2014
L. A. Rieger, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 7, 507–522, https://doi.org/10.5194/amt-7-507-2014, https://doi.org/10.5194/amt-7-507-2014, 2014
C. Gebhardt, A. Rozanov, R. Hommel, M. Weber, H. Bovensmann, J. P. Burrows, D. Degenstein, L. Froidevaux, and A. M. Thompson
Atmos. Chem. Phys., 14, 831–846, https://doi.org/10.5194/acp-14-831-2014, https://doi.org/10.5194/acp-14-831-2014, 2014
C. Adams, A. E. Bourassa, V. Sofieva, L. Froidevaux, C. A. McLinden, D. Hubert, J.-C. Lambert, C. E. Sioris, and D. A. Degenstein
Atmos. Meas. Tech., 7, 49–64, https://doi.org/10.5194/amt-7-49-2014, https://doi.org/10.5194/amt-7-49-2014, 2014
E. N. Normand, J. T. Wiensz, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 6, 3359–3368, https://doi.org/10.5194/amt-6-3359-2013, https://doi.org/10.5194/amt-6-3359-2013, 2013
V. F. Sofieva, N. Rahpoe, J. Tamminen, E. Kyrölä, N. Kalakoski, M. Weber, A. Rozanov, C. von Savigny, A. Laeng, T. von Clarmann, G. Stiller, S. Lossow, D. Degenstein, A. Bourassa, C. Adams, C. Roth, N. Lloyd, P. Bernath, R. J. Hargreaves, J. Urban, D. Murtagh, A. Hauchecorne, F. Dalaudier, M. van Roozendael, N. Kalb, and C. Zehner
Earth Syst. Sci. Data, 5, 349–363, https://doi.org/10.5194/essd-5-349-2013, https://doi.org/10.5194/essd-5-349-2013, 2013
J. Liu, D. W. Tarasick, V. E. Fioletov, C. McLinden, T. Zhao, S. Gong, C. Sioris, J. J. Jin, G. Liu, and O. Moeini
Atmos. Chem. Phys., 13, 11441–11464, https://doi.org/10.5194/acp-13-11441-2013, https://doi.org/10.5194/acp-13-11441-2013, 2013
A. Wiacek, R. V. Martin, A. E. Bourassa, N. D. Lloyd, and D. A. Degenstein
Atmos. Meas. Tech., 6, 2761–2776, https://doi.org/10.5194/amt-6-2761-2013, https://doi.org/10.5194/amt-6-2761-2013, 2013
D. Griffin, K. A. Walker, J. E. Franklin, M. Parrington, C. Whaley, J. Hopper, J. R. Drummond, P. I. Palmer, K. Strong, T. J. Duck, I. Abboud, P. F. Bernath, C. Clerbaux, P.-F. Coheur, K. R. Curry, L. Dan, E. Hyer, J. Kliever, G. Lesins, M. Maurice, A. Saha, K. Tereszchuk, and D. Weaver
Atmos. Chem. Phys., 13, 10227–10241, https://doi.org/10.5194/acp-13-10227-2013, https://doi.org/10.5194/acp-13-10227-2013, 2013
Y. Kasai, H. Sagawa, D. Kreyling, E. Dupuy, P. Baron, J. Mendrok, K. Suzuki, T. O. Sato, T. Nishibori, S. Mizobuchi, K. Kikuchi, T. Manabe, H. Ozeki, T. Sugita, M. Fujiwara, Y. Irimajiri, K. A. Walker, P. F. Bernath, C. Boone, G. Stiller, T. von Clarmann, J. Orphal, J. Urban, D. Murtagh, E. J. Llewellyn, D. Degenstein, A. E. Bourassa, N. D. Lloyd, L. Froidevaux, M. Birk, G. Wagner, F. Schreier, J. Xu, P. Vogt, T. Trautmann, and M. Yasui
Atmos. Meas. Tech., 6, 2311–2338, https://doi.org/10.5194/amt-6-2311-2013, https://doi.org/10.5194/amt-6-2311-2013, 2013
P. I. Palmer, M. Parrington, J. D. Lee, A. C. Lewis, A. R. Rickard, P. F. Bernath, T. J. Duck, D. L. Waugh, D. W. Tarasick, S. Andrews, E. Aruffo, L. J. Bailey, E. Barrett, S. J.-B. Bauguitte, K. R. Curry, P. Di Carlo, L. Chisholm, L. Dan, G. Forster, J. E. Franklin, M. D. Gibson, D. Griffin, D. Helmig, J. R. Hopkins, J. T. Hopper, M. E. Jenkin, D. Kindred, J. Kliever, M. Le Breton, S. Matthiesen, M. Maurice, S. Moller, D. P. Moore, D. E. Oram, S. J. O'Shea, R. C. Owen, C. M. L. S. Pagniello, S. Pawson, C. J. Percival, J. R. Pierce, S. Punjabi, R. M. Purvis, J. J. Remedios, K. M. Rotermund, K. M. Sakamoto, A. M. da Silva, K. B. Strawbridge, K. Strong, J. Taylor, R. Trigwell, K. A. Tereszchuk, K. A. Walker, D. Weaver, C. Whaley, and J. C. Young
Atmos. Chem. Phys., 13, 6239–6261, https://doi.org/10.5194/acp-13-6239-2013, https://doi.org/10.5194/acp-13-6239-2013, 2013
C. Adams, A. E. Bourassa, A. F. Bathgate, C. A. McLinden, N. D. Lloyd, C. Z. Roth, E. J. Llewellyn, J. M. Zawodny, D. E. Flittner, G. L. Manney, W. H. Daffer, and D. A. Degenstein
Atmos. Meas. Tech., 6, 1447–1459, https://doi.org/10.5194/amt-6-1447-2013, https://doi.org/10.5194/amt-6-1447-2013, 2013
R. A. Stachnik, L. Millán, R. Jarnot, R. Monroe, C. McLinden, S. Kühl, J. Puķīte, M. Shiotani, M. Suzuki, Y. Kasai, F. Goutail, J. P. Pommereau, M. Dorf, and K. Pfeilsticker
Atmos. Chem. Phys., 13, 3307–3319, https://doi.org/10.5194/acp-13-3307-2013, https://doi.org/10.5194/acp-13-3307-2013, 2013
J. T. Wiensz, D. A. Degenstein, N. D. Lloyd, and A. E. Bourassa
Atmos. Meas. Tech., 6, 105–119, https://doi.org/10.5194/amt-6-105-2013, https://doi.org/10.5194/amt-6-105-2013, 2013
C. Adams, K. Strong, X. Zhao, A. E. Bourassa, W. H. Daffer, D. Degenstein, J. R. Drummond, E. E. Farahani, A. Fraser, N. D. Lloyd, G. L. Manney, C. A. McLinden, M. Rex, C. Roth, S. E. Strahan, K. A. Walker, and I. Wohltmann
Atmos. Chem. Phys., 13, 611–624, https://doi.org/10.5194/acp-13-611-2013, https://doi.org/10.5194/acp-13-611-2013, 2013
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Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
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Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Cited articles
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Dueck, S. R., Bourassa, A. E., and Degenstein, D. A.: An efficient algorithm for polarization in the SASKTRAN radiative transfer framework, J. Quant. Spectrosc. Ra., 199, 1–11, https://doi.org/10.1016/j.jqsrt.2017.05.016, 2017. a
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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., Linden, M. t., Geffen, J. v., 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. a, b
Griffin, D., McLinden, C. A., Dammers, E., Adams, C., Stockwell, C. E., Warneke, C., Bourgeois, I., Peischl, J., Ryerson, T. B., Zarzana, K. J., Rowe, J. P., Volkamer, R., Knote, C., Kille, N., Koenig, T. K., Lee, C. F., Rollins, D., Rickly, P. S., Chen, J., Fehr, L., Bourassa, A., Degenstein, D., Hayden, K., Mihele, C., Wren, S. N., Liggio, J., Akingunola, A., and Makar, P.: Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation, Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, 2021. a, b
Hu, L., Keller, C. A., Long, M. S., Sherwen, T., Auer, B., Da Silva, A., Nielsen, J. E., Pawson, S., Thompson, M. A., Trayanov, A. L., Travis, K. R., Grange, S. K., Evans, M. J., and Jacob, D. J.: Global simulation of tropospheric chemistry at 12.5 km resolution: performance and evaluation of the GEOS-Chem chemical module (v10-1) within the NASA GEOS Earth system model (GEOS-5 ESM), Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, 2018. a, b, c
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Short summary
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the...
