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. 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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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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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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Interpolating turbulent heat fluxes missing from a prairie observation on the Tibetan Plateau using artificial intelligence models
Carbon dioxide plume dispersion simulated at the hectometer scale using DALES: model formulation and observational evaluation
Low-level jets in the North and Baltic seas: mesoscale model sensitivity and climatology using WRF V4.2.1
SynRad v1.0: a radar forward operator to simulate synthetic weather radar observations from volcanic ash clouds
Chempath 1.0: an open-source pathway analysis program for photochemical models
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Atmospheric moisture tracking with WAM2layers v3
A new set of indicators for model evaluation complementing FAIRMODE's modelling quality objective (MQO)
Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
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Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
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Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
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Quanzhe Hou, Zhiqiu Gao, Zexia Duan, and Minghui Yu
Geosci. Model Dev., 18, 4625–4641, https://doi.org/10.5194/gmd-18-4625-2025, https://doi.org/10.5194/gmd-18-4625-2025, 2025
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This study evaluates various machine learning and statistical methods for interpolating turbulent heat flux data over the Tibetan Plateau. The Transformer model showed the best performance, leading to the development of the Transformer_CNN model, which combines global and local attention mechanisms. Results show that Transformer_CNN outperforms the other models and was successfully applied to interpolate heat flux data from 2007 to 2016.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart J. H. van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
Geosci. Model Dev., 18, 4571–4599, https://doi.org/10.5194/gmd-18-4571-2025, https://doi.org/10.5194/gmd-18-4571-2025, 2025
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We introduce a new simulation platform based on the Dutch Atmospheric Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in turbulent environments at a hectometer resolution. This model incorporates both anthropogenic emission inventories and online ecosystem fluxes. Simulation results for the main urban area in the Netherlands demonstrate the strong potential of DALES to improve CO2 emission modeling and to support mitigation strategies.
Bjarke T. E. Olsen, Andrea N. Hahmann, Nicolas G. Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
Geosci. Model Dev., 18, 4499–4533, https://doi.org/10.5194/gmd-18-4499-2025, https://doi.org/10.5194/gmd-18-4499-2025, 2025
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Low-level jets (LLJs) are strong winds in the lower atmosphere that are 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.
Vishnu Nair, Anujah Mohanathan, Michael Herzog, David G. Macfarlane, and Duncan A. Robertson
Geosci. Model Dev., 18, 4417–4432, https://doi.org/10.5194/gmd-18-4417-2025, https://doi.org/10.5194/gmd-18-4417-2025, 2025
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A numerical model that simulates the measurement processes behind the ground-based radars used to detect volcanic ash clouds is introduced. Using weather radars to detect volcanic clouds is not ideal, as fine ash particles are smaller than raindrops and remain undetected. We evaluate the performance of weather radars to study ash clouds and to identify optimal frequencies that balance the trade-off between a higher return signal and the higher path attenuation that comes at these higher frequencies.
Daniel Garduno Ruiz, Colin Goldblatt, and Anne-Sofie Ahm
Geosci. Model Dev., 18, 4433–4454, https://doi.org/10.5194/gmd-18-4433-2025, https://doi.org/10.5194/gmd-18-4433-2025, 2025
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Photochemical models describe how the composition of the atmosphere changes due to chemical reactions, transport, and other processes. These models are useful for studying the composition of the Earth's and other planets' atmospheres. Understanding the results of these models can be difficult. Here, we build on previous work to develop open-source code that can identify the reaction chains (pathways) that produce the results of these models, facilitating the understanding of these results.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
Geosci. Model Dev., 18, 4353–4398, https://doi.org/10.5194/gmd-18-4353-2025, https://doi.org/10.5194/gmd-18-4353-2025, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line And Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, this model is valuable for airglow research and astronomical observatories.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
Geosci. Model Dev., 18, 4335–4352, https://doi.org/10.5194/gmd-18-4335-2025, https://doi.org/10.5194/gmd-18-4335-2025, 2025
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We introduce a new version of WAM2layers (Water Accounting Model – 2 layers), a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data had become a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent, reliable, and easier to maintain.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
Geosci. Model Dev., 18, 4231–4245, https://doi.org/10.5194/gmd-18-4231-2025, https://doi.org/10.5194/gmd-18-4231-2025, 2025
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We assess relevance and utility indicators by evaluating nine Copernicus Atmospheric Monitoring Service models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and winter–summer gradients reveal issues. O3 evaluation shows that seasonal gradients are useful. Overall, the indicators reveal model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev., 18, 4075–4101, https://doi.org/10.5194/gmd-18-4075-2025, https://doi.org/10.5194/gmd-18-4075-2025, 2025
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective-scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing–Tianjin–Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
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., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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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-kilometre-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 an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the 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 between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently 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 has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Joseph Mouallem, Kun Gao, Brandon G. Reichl, Lauren Chilutti, Lucas Harris, Rusty Benson, Niki Zadeh, Jing Chen, Jan-Huey Chen, and Cheng Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1690, https://doi.org/10.5194/egusphere-2025-1690, 2025
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We introduce a new high-resolution model that couple the atmosphere and ocean to better simulate extreme weather events. It combines GFDL’s advanced atmospheric and ocean models with a powerful coupling system that allows robust and efficient two-way interactions. Simulations show the model accurately captures hurricane behavior and its impact on the ocean. It also runs efficiently on supercomputers. This model is a key step toward improving extreme weather forecast.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
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.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
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.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Cited articles
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Bourassa, A., Degenstein, D., and Llewellyn, E.: SASKTRAN: A spherical geometry radiative transfer code for efficient estimation of limb scattered sunlight, J. Quant. Spectrosc. Ra., 109, 52–73, https://doi.org/10.1016/j.jqsrt.2007.07.007, 2008. a
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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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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...
