Articles | Volume 7, issue 6
https://doi.org/10.5194/amt-7-1891-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-1891-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
26 Jun 2014
Research article |
| 26 Jun 2014
On sampling uncertainty of satellite ozone profile measurements
V. F. Sofieva
Finnish Meteorological Institute, Helsinki, Finland
N. Kalakoski
Finnish Meteorological Institute, Helsinki, Finland
S.-M. Päivärinta
Finnish Meteorological Institute, Helsinki, Finland
J. Tamminen
Finnish Meteorological Institute, Helsinki, Finland
Finnish Meteorological Institute, Helsinki, Finland
L. Froidevaux
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
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Robert P. Damadeo, Viktoria F. Sofieva, Alexei Rozanov, and Larry W. Thomason
Atmos. Meas. Tech., 17, 3669–3678, https://doi.org/10.5194/amt-17-3669-2024, https://doi.org/10.5194/amt-17-3669-2024, 2024
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Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech., 17, 3085–3101, https://doi.org/10.5194/amt-17-3085-2024, https://doi.org/10.5194/amt-17-3085-2024, 2024
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We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.
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
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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).
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
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Niilo Kalakoski, Viktoria F. Sofieva, René Preusker, Claire Henocq, Matthieu Denisselle, Steffen Dransfeld, and Silvia Scifoni
Atmos. Meas. Tech., 15, 5129–5140, https://doi.org/10.5194/amt-15-5129-2022, https://doi.org/10.5194/amt-15-5129-2022, 2022
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Geophysical validation of the Integrated Water Vapour (IWV) product from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) was performed against reference observations from SUOMINET and IGRA databases. Results for cloud-free matchups over land show a wet bias of 7 %–10 % for OLCI, with a high correlation against the reference observations (0.98 against SUOMINET and 0.90 against IGRA). Special attention is given to validation of uncertainty estimates and cloud flagging.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
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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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Mikhail Sofiev, Rostislav Kouznetsov, Risto Hänninen, and Viktoria F. Sofieva
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Alain Hauchecorne, Laurent Blanot, Robin Wing, Philippe Keckhut, Sergey Khaykin, Jean-Loup Bertaux, Mustapha Meftah, Chantal Claud, and Viktoria Sofieva
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Viktoria F. Sofieva, Francis Dalaudier, Alain Hauchecorne, and Valery Kan
Atmos. Meas. Tech., 12, 585–598, https://doi.org/10.5194/amt-12-585-2019, https://doi.org/10.5194/amt-12-585-2019, 2019
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This paper describes the temperature profiles in the stratosphere obtained from unique stellar scintillation measurements by the GOMOS instrument operated on board Envisat in 2002–2012. The high-resolution temperature profiles (HRTPs) are retrieved with a very good vertical resolution of ~ 200 m and a high accuracy of ~ 1–3 K for altitudes 15–32 km as well as a global coverage. HRTPs can be assimilated into atmospheric models and used in analyses of internal gravity wave activity.
Christos Zerefos, John Kapsomenakis, Kostas Eleftheratos, Kleareti Tourpali, Irina Petropavlovskikh, Daan Hubert, Sophie Godin-Beekmann, Wolfgang Steinbrecht, Stacey Frith, Viktoria Sofieva, and Birgit Hassler
Atmos. Chem. Phys., 18, 6427–6440, https://doi.org/10.5194/acp-18-6427-2018, https://doi.org/10.5194/acp-18-6427-2018, 2018
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We point out the representativeness of single lidar stations for zonally averaged ozone profile variations in the middle/upper stratosphere. We examine the contribution of chemistry and natural proxies to ozone profile trends. Above 10 hPa an “inflection point” between 1997–99 marks the end of significant negative ozone trends, followed by a recent period of positive ozone change in 1998–2015. Below 15 hPa the pre-1998 negative ozone trends tend to become insignificant as we move to 2015.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Angela Gardini, Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Alexandra Laeng, Martin Kaufmann, Viktoria F. Sofieva, Lucien Froidevaux, Kaley A. Walker, and Masato Shiotani
Atmos. Meas. Tech., 11, 2187–2212, https://doi.org/10.5194/amt-11-2187-2018, https://doi.org/10.5194/amt-11-2187-2018, 2018
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This paper describes the inversion of O3 data from MIPAS middle atmosphere spectra which requires non-LTE. The O3 dataset comprises from 20 to 100 km, has a pole-to-pole latitude coverage, day and nighttime, and span from 2005 until 2012. A validation of the data against other satellite measurements and an overall description of O3 is also presented. This is an important dataset for the community and describes the major characteristics of stratospheric and mesospheric O3.
Valery Kan, Michael E. Gorbunov, and Viktoria F. Sofieva
Atmos. Meas. Tech., 11, 663–680, https://doi.org/10.5194/amt-11-663-2018, https://doi.org/10.5194/amt-11-663-2018, 2018
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We discuss the relationships that link the observed fluctuation spectra of the amplitude and phase of signals used for the radio occultation sounding of the Earth's atmosphere with the spectra of atmospheric inhomogeneities. We demonstrate that the main contribution into the radio signal fluctuations comes from the internal gravity waves. These results may serve as the basis for the global monitoring of the wave activity in the stratosphere and upper troposphere.
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.
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.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
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Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Bianca Maria Dinelli, Anu Dudhia, Piera Raspollini, Norbert Glatthor, Udo Grabowski, Viktoria Sofieva, Lucien Froidevaux, Kaley A. Walker, and Claus Zehner
Atmos. Meas. Tech., 10, 1511–1518, https://doi.org/10.5194/amt-10-1511-2017, https://doi.org/10.5194/amt-10-1511-2017, 2017
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A MIPAS instrument was flown in 2002–2012 on the Envisat satellite and measured atmospheric composition. There exist four processors retrieving atmospheric profiles from MIPAS spectra. We performed a mathematically clean merging of 2007–2008 datasets of ozone from these four processors. The merged product was compared with ozone datasets from ACE-FTS and MLS instruments. The advantages and the shortcomings of this merged product are discussed.
Viktoria F. Sofieva, Iolanda Ialongo, Janne Hakkarainen, Erkki Kyrölä, Johanna Tamminen, Marko Laine, Daan Hubert, Alain Hauchecorne, Francis Dalaudier, Jean-Loup Bertaux, Didier Fussen, Laurent Blanot, Gilbert Barrot, and Angelika Dehn
Atmos. Meas. Tech., 10, 231–246, https://doi.org/10.5194/amt-10-231-2017, https://doi.org/10.5194/amt-10-231-2017, 2017
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This paper presents a new ozone profile inversion algorithm for GOMOS/Envisat satellite data. This algorithm is enhanced with a DOAS-type method at visible wavelengths in the upper troposphere and the lower stratosphere. The new GOMOS ozone profiles have a significantly improved data quality in the UTLS compared to the official IPF V6 ozone profiles. The paper describes the inversion algorithm and present inter-comparisons with ozonesonde and satellite measurements.
Filip Vanhellemont, Nina Mateshvili, Laurent Blanot, Charles Étienne Robert, Christine Bingen, Viktoria Sofieva, Francis Dalaudier, Cédric Tétard, Didier Fussen, Emmanuel Dekemper, Erkki Kyrölä, Marko Laine, Johanna Tamminen, and Claus Zehner
Atmos. Meas. Tech., 9, 4687–4700, https://doi.org/10.5194/amt-9-4687-2016, https://doi.org/10.5194/amt-9-4687-2016, 2016
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The GOMOS instrument on Envisat has delivered a valuable aerosol extinction data set for the Earth's upper troposphere and stratosphere, from 2002 to 2012. However, at many optical wavelengths, data quality was not optimal. This article describes the AerGOM retrieval algorithm that was built to solve the problem and presents a first look at the reprocessed GOMOS data, clearly demonstrating the improvement. Multi-wavelength studies of atmospheric aerosol–cloud properties will now be possible.
Niilo Kalakoski, Jukka Kujanpää, Viktoria Sofieva, Johanna Tamminen, Margherita Grossi, and Pieter Valks
Atmos. Meas. Tech., 9, 1533–1544, https://doi.org/10.5194/amt-9-1533-2016, https://doi.org/10.5194/amt-9-1533-2016, 2016
A. Kauppi, O. N. E. Tuinder, S. Tukiainen, V. Sofieva, and J. Tamminen
Atmos. Meas. Tech., 9, 249–261, https://doi.org/10.5194/amt-9-249-2016, https://doi.org/10.5194/amt-9-249-2016, 2016
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This paper presents a comparison of operational vertical ozone profiles retrieved by OPERA algorithm from the GOME-2 measurements on board Metop-A with space borne high-vertical-resolution ozone profiles by GOMOS, OSIRIS and MLS. The overall agreement of ozone profiles from GOME-2 and reference instruments is within 15 % below 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to underestimate the ozone concentration above 30 km.
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.
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
V. F. Sofieva, J. Tamminen, E. Kyrölä, A. Laeng, T. von Clarmann, F. Dalaudier, A. Hauchecorne, J.-L. Bertaux, G. Barrot, L. Blanot, D. Fussen, and F. Vanhellemont
Atmos. Meas. Tech., 7, 2147–2158, https://doi.org/10.5194/amt-7-2147-2014, https://doi.org/10.5194/amt-7-2147-2014, 2014
V. Kan, V. F. Sofieva, and F. Dalaudier
Atmos. Meas. Tech., 7, 1861–1872, https://doi.org/10.5194/amt-7-1861-2014, https://doi.org/10.5194/amt-7-1861-2014, 2014
V. F. Sofieva, J. Tamminen, E. Kyrölä, T. Mielonen, P. Veefkind, B. Hassler, and G.E. Bodeker
Atmos. Chem. Phys., 14, 283–299, https://doi.org/10.5194/acp-14-283-2014, https://doi.org/10.5194/acp-14-283-2014, 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
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
E. Kyrölä, M. Laine, V. Sofieva, J. Tamminen, S.-M. Päivärinta, S. Tukiainen, J. Zawodny, and L. Thomason
Atmos. Chem. Phys., 13, 10645–10658, https://doi.org/10.5194/acp-13-10645-2013, https://doi.org/10.5194/acp-13-10645-2013, 2013
C. Tétard, D. Fussen, F. Vanhellemont, C. Bingen, E. Dekemper, N. Mateshvili, D. Pieroux, C. Robert, E. Kyrölä, J. Tamminen, V. Sofieva, A. Hauchecorne, F. Dalaudier, J.-L. Bertaux, O. Fanton d'Andon, G. Barrot, L. Blanot, A. Dehn, and L. Saavedra de Miguel
Atmos. Meas. Tech., 6, 2953–2964, https://doi.org/10.5194/amt-6-2953-2013, https://doi.org/10.5194/amt-6-2953-2013, 2013
Tuomas Häkkilä, Maxime Grandin, Markus Battarbee, Monika E. Szeląg, Markku Alho, Leo Kotipalo, Niilo Kalakoski, Pekka T. Verronen, and Minna Palmroth
Ann. Geophys., 43, 217–240, https://doi.org/10.5194/angeo-43-217-2025, https://doi.org/10.5194/angeo-43-217-2025, 2025
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We study the atmospheric impact of auroral electron precipitation through the novel combination of both magnetospheric modelling and atmospheric modelling. We first simulate fluxes of auroral electrons and then use these fluxes to model their atmospheric impact. We find an increase of more than 200 % in thermospheric odd nitrogen and a corresponding decrease in stratospheric ozone of around 0.8 %. The produced auroral electron precipitation is realistic and shows potential for future studies.
Pekka T. Verronen, Akira Mizuno, Yoshizumi Miyoshi, Sandeep Kumar, Taku Nakajima, Shin-Ichiro Oyama, Tomoo Nagahama, Satonori Nozawa, Monika E. Szelag, Tuomas Häkkilä, Niilo Kalakoski, Antti Kero, Esa Turunen, Satoshi Kasahara, Shoichiro Yokota, Kunihiro Keika, Tomoaki Hori, Takefumi Mitani, Takeshi Takashima, and Iku Shinohara
EGUsphere, https://doi.org/10.5194/egusphere-2025-1691, https://doi.org/10.5194/egusphere-2025-1691, 2025
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We use NO column density data from the Syowa station in Antarctica from 2012–2017. We compare these ground-based radiometer observations with results from a global atmosphere model to understand the year-to-year and day-to-day variability, shortcomings of current electron forcing, and how geomagnetic storms are driving the variability of NO. Our results demonstrate an underestimation in the magnitude of day-to-day variability in simulations, which calls for improved electron forcing in models.
Arno Keppens, Daan Hubert, José Granville, Oindrila Nath, Jean-Christopher Lambert, Catherine Wespes, Pierre-François Coheur, Cathy Clerbaux, Anne Boynard, Richard Siddans, Barry Latter, Brian Kerridge, Serena Di Pede, Pepijn Veefkind, Juan Cuesta, Gaelle Dufour, Klaus-Peter Heue, Melanie Coldewey-Egbers, Diego Loyola, Andrea Orfanoz-Cheuquelaf, Swathi Maratt Satheesan, Kai-Uwe Eichmann, Alexei Rozanov, Viktoria F. Sofieva, Jerald R. Ziemke, Antje Inness, Roeland Van Malderen, and Lars Hoffmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3746, https://doi.org/10.5194/egusphere-2024-3746, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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The first Tropospheric Ozone Assessment Report (TOAR) encountered discrepancies between several satellite sensors’ estimates of the distribution and change of ozone in the free troposphere. Therefore, contributing to the second TOAR, we harmonise as much as possible the observational perspective of sixteen tropospheric ozone products from satellites. This only partially accounts for the observed discrepancies, with a reduction of 10–40 % of the inter-product dispersion upon harmonisation.
Ella Kivimäki, Tuula Aalto, Michael Buchwitz, Kari Luojus, Jouni Pulliainen, Kimmo Rautiainen, Oliver Schneising, Anu-Maija Sundström, Johanna Tamminen, Aki Tsuruta, and Hannakaisa Lindqvist
EGUsphere, https://doi.org/10.5194/egusphere-2025-249, https://doi.org/10.5194/egusphere-2025-249, 2025
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We investigate how environmental variables influencing natural methane fluxes explain the large-scale seasonal variability of satellite-observed methane at Northern high latitudes. Our findings show that soil moisture, snow cover, and soil temperature have the strongest influence, with snowmelt playing a surprisingly significant role, likely through soil isolation and wetting. This study highlights the value of multi-satellite observations for understanding large-scale wetland emissions.
Diego Santaren, Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Frédéric Chevallier, Iolanda Ialongo, Hannakaisa Lindqvist, Janne Nurmela, Johanna Tamminen, Laia Amorós, Dominik Brunner, and Grégoire Broquet
Atmos. Meas. Tech., 18, 211–239, https://doi.org/10.5194/amt-18-211-2025, https://doi.org/10.5194/amt-18-211-2025, 2025
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This study evaluates data-driven inversion methods for estimating CO2 emissions from local sources, such as power plants and cities, using meteorological data and XCO2 and NO2 satellite images rather than atmospheric transport modeling. We assess and compare the performance of five different methods using simulations of 1 year of satellite images, taken from the upcoming Copernicus CO2 Monitoring Mission, covering 15 power plants and the city of Berlin, Germany.
Carlo Arosio, Viktoria Sofieva, Andrea Orfanoz-Cheuquelaf, Alexei Rozanov, Klaus-Peter Heue, Edward Malina, Ryan M. Stauffer, David Tarasick, Roeland Van Malderen, Jerry R. Ziemke, and Mark Weber
EGUsphere, https://doi.org/10.5194/egusphere-2024-3737, https://doi.org/10.5194/egusphere-2024-3737, 2024
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Tropospheric ozone affects air quality and climate, being a pollutant and a greenhouse gas. We analysed satellite data of tropospheric ozone that combine two types of observations: one providing stratospheric ozone and another measuring total ozone. We compare common climatological features and study the influence of the tropopause (troposphere to stratosphere boundary) on the results. We also examine trends over the last 20 years and compare satellite data with ozonesondes to identify drifts.
Stephanie Bohlmann and Marko Laine
Nat. Hazards Earth Syst. Sci., 24, 4225–4235, https://doi.org/10.5194/nhess-24-4225-2024, https://doi.org/10.5194/nhess-24-4225-2024, 2024
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Probabilistic ensemble forecasts of the Canadian Forest Fire Weather Index (FWI) can be used to estimate the possible wildfire risk but require post-processing to provide accurate and reliable predictions. This article presents a calibration method using non-homogeneous Gaussian regression to statistically post-process FWI forecasts up to 15 d. Calibration improves the forecast especially at short lead times and in regions with high fire risk.
Viktoria F. Sofieva, Alexei Rozanov, Monika Szelag, John P. Burrows, Christian Retscher, Robert Damadeo, Doug Degenstein, Landon A. Rieger, and Adam Bourassa
Earth Syst. Sci. Data, 16, 5227–5241, https://doi.org/10.5194/essd-16-5227-2024, https://doi.org/10.5194/essd-16-5227-2024, 2024
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Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth’s atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived from data of six limb and occultation satellite instruments. The created aerosol climate record covers the period from October 1984 to December 2023. It can be used in various climate-related studies.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Robert P. Damadeo, Viktoria F. Sofieva, Alexei Rozanov, and Larry W. Thomason
Atmos. Meas. Tech., 17, 3669–3678, https://doi.org/10.5194/amt-17-3669-2024, https://doi.org/10.5194/amt-17-3669-2024, 2024
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Comparing different aerosol data sets for scientific studies often requires converting aerosol extinction data between different wavelengths. A common approximation for the spectral behavior of aerosol is the Ångström formula; however, this introduces biases. Using measurements across many different wavelengths from a single instrument, we derive an empirical relationship to both characterize this bias and offer a correction for other studies that may employ this analysis approach.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Didier Fussen, Christine Bingen, Filip Vanhellemont, Nina Mateshvili, Alexei Rozanov, and Christine Pohl
Atmos. Meas. Tech., 17, 3085–3101, https://doi.org/10.5194/amt-17-3085-2024, https://doi.org/10.5194/amt-17-3085-2024, 2024
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We have developed the new multi-wavelength dataset of aerosol extinction profiles, which are retrieved from the averaged transmittance spectra by the Global Ozone Monitoring by Occultation of Stars instrument aboard Envisat. The retrieved aerosol extinction profiles are provided in the altitude range 10–40 km at 400, 440, 452, 470, 500, 525, 550, 672 and 750 nm for the period 2002–2012. FMI-GOMOSaero aerosol profiles have improved quality; they are in good agreement with other datasets.
Markku Kulmala, Anna Lintunen, Hanna Lappalainen, Annele Virtanen, Chao Yan, Ekaterina Ezhova, Tuomo Nieminen, Ilona Riipinen, Risto Makkonen, Johanna Tamminen, Anu-Maija Sundström, Antti Arola, Armin Hansel, Kari Lehtinen, Timo Vesala, Tuukka Petäjä, Jaana Bäck, Tom Kokkonen, and Veli-Matti Kerminen
Atmos. Chem. Phys., 23, 14949–14971, https://doi.org/10.5194/acp-23-14949-2023, https://doi.org/10.5194/acp-23-14949-2023, 2023
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To be able to meet global grand challenges, we need comprehensive open data with proper metadata. In this opinion paper, we describe the SMEAR (Station for Measuring Earth surface – Atmosphere Relations) concept and include several examples (cases), such as new particle formation and growth, feedback loops and the effect of COVID-19, and what has been learned from these investigations. The future needs and the potential of comprehensive observations of the environment are summarized.
Olle Räty, Marko Laine, Ulpu Leijala, Jani Särkkä, and Milla M. Johansson
Nat. Hazards Earth Syst. Sci., 23, 2403–2418, https://doi.org/10.5194/nhess-23-2403-2023, https://doi.org/10.5194/nhess-23-2403-2023, 2023
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We studied annual maximum sea levels in the Finnish coastal region. Our aim was to better quantify the uncertainty in them compared to previous studies. Using four statistical models, we found out that hierarchical models, which shared information on sea-level extremes across Finnish tide gauges, had lower uncertainty in their results in comparison with tide-gauge-specific fits. These models also suggested that the shape of the distribution for extreme sea levels is similar on the Finnish coast.
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).
Michael J. Prather, Lucien Froidevaux, and Nathaniel J. Livesey
Atmos. Chem. Phys., 23, 843–849, https://doi.org/10.5194/acp-23-843-2023, https://doi.org/10.5194/acp-23-843-2023, 2023
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From satellite data for nitrous oxide (N2O), ozone and temperature, we calculate the monthly loss of N2O and find it is increasing faster than expected, resulting in a shorter lifetime, which reduces the impact of anthropogenic emissions. We identify the cause as enhanced vertical lofting of high-N2O air into the tropical middle stratosphere, where it is destroyed photochemically. Because global warming is due in part to N2O, this finding presents a new negative climate-chemistry feedback.
Eliane Maillard Barras, Alexander Haefele, René Stübi, Achille Jouberton, Herbert Schill, Irina Petropavlovskikh, Koji Miyagawa, Martin Stanek, and Lucien Froidevaux
Atmos. Chem. Phys., 22, 14283–14302, https://doi.org/10.5194/acp-22-14283-2022, https://doi.org/10.5194/acp-22-14283-2022, 2022
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Intercomparisons of three Dobson and three Brewer spectrophotometers at Arosa/Davos, Switzerland, are used for the homogenization of the longest Umkehr ozone profiles time series worldwide. Dynamic linear modeling (DLM) reveals a significant positive trend after 2004 in the upper stratosphere, a persistent negative trend between 25 and 30 km in the middle stratosphere, and a negative trend at 20 km in the lower stratosphere, with different levels of significance depending on the dataset.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
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Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
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.
Niilo Kalakoski, Viktoria F. Sofieva, René Preusker, Claire Henocq, Matthieu Denisselle, Steffen Dransfeld, and Silvia Scifoni
Atmos. Meas. Tech., 15, 5129–5140, https://doi.org/10.5194/amt-15-5129-2022, https://doi.org/10.5194/amt-15-5129-2022, 2022
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Geophysical validation of the Integrated Water Vapour (IWV) product from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) was performed against reference observations from SUOMINET and IGRA databases. Results for cloud-free matchups over land show a wet bias of 7 %–10 % for OLCI, with a high correlation against the reference observations (0.98 against SUOMINET and 0.90 against IGRA). Special attention is given to validation of uncertainty estimates and cloud flagging.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
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We present tropospheric ozone column datasets that have been created using combinations of total ozone column from OMI and TROPOMI with stratospheric ozone column datasets from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The main results are (i) several methodological developments, (ii) new tropospheric ozone column datasets from OMI and TROPOMI, and (iii) a new high-resolution dataset of ozone profiles from limb satellite instruments.
Anu Kauppi, Antti Kukkurainen, Antti Lipponen, Marko Laine, Antti Arola, Hannakaisa Lindqvist, and Johanna Tamminen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2021-328, https://doi.org/10.5194/amt-2021-328, 2021
Revised manuscript not accepted
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We present a methodology in Bayesian framework for retrieving atmospheric aerosol optical depth and aerosol type from the pre-computed look-up tables (LUTs). Especially, we consider Bayesian model averaging and uncertainty originating from aerosol model selection and imperfect forward modelling. Our aim is to get more realistic uncertainty estimates. We have applied the methodology to TROPOMI/S5P satellite observations and evaluated the results against ground-based data from the AERONET.
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957, https://doi.org/10.5194/amt-14-4947-2021, https://doi.org/10.5194/amt-14-4947-2021, 2021
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Methods to estimate surface UV radiation from satellite measurements offer the only means to obtain global coverage, and the development of satellite-based UV algorithms has been ongoing since the early 1990s. One of the main challenges in this development has been how to account for the overall effect of absorption by atmospheric aerosols. One such method was suggested roughly a decade ago, and in this study we propose further improvements for this kind of approach.
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.
Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola
Atmos. Meas. Tech., 14, 2993–3002, https://doi.org/10.5194/amt-14-2993-2021, https://doi.org/10.5194/amt-14-2993-2021, 2021
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Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.
Emily M. Gordon, Annika Seppälä, Bernd Funke, Johanna Tamminen, and Kaley A. Walker
Atmos. Chem. Phys., 21, 2819–2836, https://doi.org/10.5194/acp-21-2819-2021, https://doi.org/10.5194/acp-21-2819-2021, 2021
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Energetic particle precipitation (EPP) is the rain of solar energetic particles into the Earth's atmosphere. EPP is known to deplete O3 in the polar mesosphere–upper stratosphere via the formation of NOx. NOx also causes chlorine deactivation in the lower stratosphere and has, thus, been proposed to potentially result in reduced ozone depletion in the spring. We provide the first evidence to show that NOx formed by EPP is able to remove active chlorine, resulting in enhanced total ozone column.
Tuomas Häkkilä, Pekka T. Verronen, Luis Millán, Monika E. Szeląg, Niilo Kalakoski, and Antti Kero
Ann. Geophys., 38, 1299–1312, https://doi.org/10.5194/angeo-38-1299-2020, https://doi.org/10.5194/angeo-38-1299-2020, 2020
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The atmospheric impacts of energetic particle precipitation (EPP) can be useful in understanding the uncertainties of measuring the precipitation. Hence, information on how strong of an EPP flux has observable atmospheric impacts is needed. In this study, we find such threshold flux values using odd hydrogen concentrations from both satellite observations and model simulations. We consider the effects of solar proton events and radiation belt electron precipitation in the middle atmosphere.
Anna Shcherbacheva, Tracey Balehowsky, Jakub Kubečka, Tinja Olenius, Tapio Helin, Heikki Haario, Marko Laine, Theo Kurtén, and Hanna Vehkamäki
Atmos. Chem. Phys., 20, 15867–15906, https://doi.org/10.5194/acp-20-15867-2020, https://doi.org/10.5194/acp-20-15867-2020, 2020
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Atmospheric new particle formation and cluster growth to aerosol particles is an important field of research, in particular due to the climate change phenomenon. Evaporation rates are very difficult to account for but they are important to explain the formation and growth of particles. Different quantum chemistry (QC) methods produce substantially different values for the evaporation rates. We propose a novel approach for inferring evaporation rates of clusters from available measurements.
Kaisa Lakkala, Jukka Kujanpää, Colette Brogniez, Nicolas Henriot, Antti Arola, Margit Aun, Frédérique Auriol, Alkiviadis F. Bais, Germar Bernhard, Veerle De Bock, Maxime Catalfamo, Christine Deroo, Henri Diémoz, Luca Egli, Jean-Baptiste Forestier, Ilias Fountoulakis, Katerina Garane, Rosa Delia Garcia, Julian Gröbner, Seppo Hassinen, Anu Heikkilä, Stuart Henderson, Gregor Hülsen, Bjørn Johnsen, Niilo Kalakoski, Angelos Karanikolas, Tomi Karppinen, Kevin Lamy, Sergio F. León-Luis, Anders V. Lindfors, Jean-Marc Metzger, Fanny Minvielle, Harel B. Muskatel, Thierry Portafaix, Alberto Redondas, Ricardo Sanchez, Anna Maria Siani, Tove Svendby, and Johanna Tamminen
Atmos. Meas. Tech., 13, 6999–7024, https://doi.org/10.5194/amt-13-6999-2020, https://doi.org/10.5194/amt-13-6999-2020, 2020
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The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite was launched on 13 October 2017 to provide the atmospheric composition for atmosphere and climate research. Ground-based data from 25 sites located in Arctic, subarctic, temperate, equatorial and Antarctic
areas were used for the validation of the TROPOMI surface ultraviolet (UV) radiation product. For most sites 60 %–80 % of TROPOMI data was within ± 20 % of ground-based data.
Jia Jia, Antti Kero, Niilo Kalakoski, Monika E. Szeląg, and Pekka T. Verronen
Atmos. Chem. Phys., 20, 14969–14982, https://doi.org/10.5194/acp-20-14969-2020, https://doi.org/10.5194/acp-20-14969-2020, 2020
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Recent studies have reported up to a 10 % average decrease of lower stratospheric ozone at 20 km altitude following solar proton events (SPEs). Our study uses 49 events that occurred after the launch of Aura MLS (July 2004–now) and 177 events that occurred in the WACCM-D simulation period (Jan 1989–Dec 2012) to evaluate ozone changes following SPEs. The statistical and case-by-case studies show no solid evidence of SPE's direct impact on the lower stratospheric ozone.
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.
Niilo Kalakoski, Pekka T. Verronen, Annika Seppälä, Monika E. Szeląg, Antti Kero, and Daniel R. Marsh
Atmos. Chem. Phys., 20, 8923–8938, https://doi.org/10.5194/acp-20-8923-2020, https://doi.org/10.5194/acp-20-8923-2020, 2020
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Effects of solar proton events (SPEs) on middle atmosphere chemistry were studied using the WACCM-D chemistry–climate model, including an improved representation of lower ionosphere ion chemistry. This study includes 66 events in the years 1989–2012 and uses a statistical approach to determine the impact of the improved chemistry scheme. The differences shown highlight the importance of ion chemistry in models used to study energetic particle precipitation.
Pekka T. Verronen, Daniel R. Marsh, Monika E. Szeląg, and Niilo Kalakoski
Ann. Geophys., 38, 833–844, https://doi.org/10.5194/angeo-38-833-2020, https://doi.org/10.5194/angeo-38-833-2020, 2020
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This paper is the first to study how the representation of the magnetic-local-time (MLT) dependency of electron precipitation impacts middle-atmospheric-ozone response on monthly timescales. We use a state-of-the-art chemistry–climate model with detailed lower-ionospheric chemistry for an advanced representation of atmospheric impacts of electron forcing. We find that the use of daily zonal-mean electron forcing will provide an accurate ozone response in long-term climate simulations.
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.
Emily M. Gordon, Annika Seppälä, and Johanna Tamminen
Atmos. Chem. Phys., 20, 6259–6271, https://doi.org/10.5194/acp-20-6259-2020, https://doi.org/10.5194/acp-20-6259-2020, 2020
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The Sun constantly emits high-energy charged particles that produce the ozone destroying chemical NOx in the polar atmosphere. NOx is transported to the stratosphere, where the ozone layer is. Satellite observations show that the NOx gases remain in the atmosphere longer than previously reported. This is influenced by the strength of atmospheric large-scale dynamics, suggesting that there are specific times when this type of solar influence on the Antarctic atmosphere becomes more pronounced.
Mikhail Sofiev, Rostislav Kouznetsov, Risto Hänninen, and Viktoria F. Sofieva
Atmos. Chem. Phys., 20, 1839–1847, https://doi.org/10.5194/acp-20-1839-2020, https://doi.org/10.5194/acp-20-1839-2020, 2020
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An episode of anomalously low ozone concentrations in the stratosphere over northern Europe occurred on 3–5 November 2018. The 30 % reduction of the ozone layer was predicted by the global chemistry-transport model of the Finnish Meteorological Institute driven by weather forecasts of ECMWF. The reduction was subsequently observed by ozone monitoring satellites. The episode was caused by a storm in the northern Atlantic, which uplifted air from the troposphere to stratosphere.
Samuel Quesada-Ruiz, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, Andrea Piacentini, Mathieu Joly, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Christiaan Plechelmus Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 131–152, https://doi.org/10.5194/amt-13-131-2020, https://doi.org/10.5194/amt-13-131-2020, 2020
Alain Hauchecorne, Laurent Blanot, Robin Wing, Philippe Keckhut, Sergey Khaykin, Jean-Loup Bertaux, Mustapha Meftah, Chantal Claud, and Viktoria Sofieva
Atmos. Meas. Tech., 12, 749–761, https://doi.org/10.5194/amt-12-749-2019, https://doi.org/10.5194/amt-12-749-2019, 2019
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This paper presents a new dataset of temperature profiles in the upper stratosphere and mesosphere acquired with the GOMOS spectrometer on board the European satellite ENVISAT. The principle is to observe the scattering of sunlight by air molecules at the Earth limb. The observed signal is proportional to the atmospheric density from which the temperature is derived. This technique provides a new source of information on temperature where satellite observations are sparse.
Viktoria F. Sofieva, Francis Dalaudier, Alain Hauchecorne, and Valery Kan
Atmos. Meas. Tech., 12, 585–598, https://doi.org/10.5194/amt-12-585-2019, https://doi.org/10.5194/amt-12-585-2019, 2019
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This paper describes the temperature profiles in the stratosphere obtained from unique stellar scintillation measurements by the GOMOS instrument operated on board Envisat in 2002–2012. The high-resolution temperature profiles (HRTPs) are retrieved with a very good vertical resolution of ~ 200 m and a high accuracy of ~ 1–3 K for altitudes 15–32 km as well as a global coverage. HRTPs can be assimilated into atmospheric models and used in analyses of internal gravity wave activity.
Christos Zerefos, John Kapsomenakis, Kostas Eleftheratos, Kleareti Tourpali, Irina Petropavlovskikh, Daan Hubert, Sophie Godin-Beekmann, Wolfgang Steinbrecht, Stacey Frith, Viktoria Sofieva, and Birgit Hassler
Atmos. Chem. Phys., 18, 6427–6440, https://doi.org/10.5194/acp-18-6427-2018, https://doi.org/10.5194/acp-18-6427-2018, 2018
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We point out the representativeness of single lidar stations for zonally averaged ozone profile variations in the middle/upper stratosphere. We examine the contribution of chemistry and natural proxies to ozone profile trends. Above 10 hPa an “inflection point” between 1997–99 marks the end of significant negative ozone trends, followed by a recent period of positive ozone change in 1998–2015. Below 15 hPa the pre-1998 negative ozone trends tend to become insignificant as we move to 2015.
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.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Angela Gardini, Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Alexandra Laeng, Martin Kaufmann, Viktoria F. Sofieva, Lucien Froidevaux, Kaley A. Walker, and Masato Shiotani
Atmos. Meas. Tech., 11, 2187–2212, https://doi.org/10.5194/amt-11-2187-2018, https://doi.org/10.5194/amt-11-2187-2018, 2018
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This paper describes the inversion of O3 data from MIPAS middle atmosphere spectra which requires non-LTE. The O3 dataset comprises from 20 to 100 km, has a pole-to-pole latitude coverage, day and nighttime, and span from 2005 until 2012. A validation of the data against other satellite measurements and an overall description of O3 is also presented. This is an important dataset for the community and describes the major characteristics of stratospheric and mesospheric O3.
Erkki Kyrölä, Monika E. Andersson, Pekka T. Verronen, Marko Laine, Simo Tukiainen, and Daniel R. Marsh
Atmos. Chem. Phys., 18, 5001–5019, https://doi.org/10.5194/acp-18-5001-2018, https://doi.org/10.5194/acp-18-5001-2018, 2018
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In this work we compare three key constituents of the middle atmosphere (ozone, NO2, and NO3) from the GOMOS satellite instrument with the WACCM model. We find that in the stratosphere (below 50 km) ozone differences are very small, but in the mesosphere large deviations are found. GOMOS and WACCM NO2 agree reasonably well except in the polar areas. These differences can be connected to the solar particle storms. For NO3, WACCM results agree with GOMOS with a very high correlation.
Jouni Susiluoto, Maarit Raivonen, Leif Backman, Marko Laine, Jarmo Makela, Olli Peltola, Timo Vesala, and Tuula Aalto
Geosci. Model Dev., 11, 1199–1228, https://doi.org/10.5194/gmd-11-1199-2018, https://doi.org/10.5194/gmd-11-1199-2018, 2018
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Methane is an important greenhouse gas and methane emissions from wetlands contribute to the warming of the climate. Wetland methane emissions are also challenging to estimate. We analyze the performance of a new wetland emission computer model utilizing mathematical methods and using data from a wetland in southern Finland. The analysis helps to explain how wetlands produce methane and how emission modeling can be improved and uncertainties in the emission estimates reduced in future studies.
Anders V. Lindfors, Jukka Kujanpää, Niilo Kalakoski, Anu Heikkilä, Kaisa Lakkala, Tero Mielonen, Maarten Sneep, Nickolay A. Krotkov, Antti Arola, and Johanna Tamminen
Atmos. Meas. Tech., 11, 997–1008, https://doi.org/10.5194/amt-11-997-2018, https://doi.org/10.5194/amt-11-997-2018, 2018
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This paper describes the algorithm that will be used for estimating surface UV radiation from TROPOMI (TROPOspheric Monitoring Instrument) measurements. TROPOMI is the only payload of the Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of the European Space Agency (ESA). The presented algorithm has been tested using input based on previous satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.
Valery Kan, Michael E. Gorbunov, and Viktoria F. Sofieva
Atmos. Meas. Tech., 11, 663–680, https://doi.org/10.5194/amt-11-663-2018, https://doi.org/10.5194/amt-11-663-2018, 2018
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We discuss the relationships that link the observed fluctuation spectra of the amplitude and phase of signals used for the radio occultation sounding of the Earth's atmosphere with the spectra of atmospheric inhomogeneities. We demonstrate that the main contribution into the radio signal fluctuations comes from the internal gravity waves. These results may serve as the basis for the global monitoring of the wave activity in the stratosphere and upper troposphere.
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.
Anu Kauppi, Pekka Kolmonen, Marko Laine, and Johanna Tamminen
Atmos. Meas. Tech., 10, 4079–4098, https://doi.org/10.5194/amt-10-4079-2017, https://doi.org/10.5194/amt-10-4079-2017, 2017
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The paper focuses on the aerosol microphysical model selection and characterisation of uncertainty in the retrieved aerosol type and aerosol optical depth (AOD). The proposed method is based on Bayesian inference approach and can account for the model error and also include the model selection uncertainty in the total uncertainty budget. The method is applied to OMI measurements but is also applicable to other instruments. The retrieval was evaluated by comparison with ground-based measurements.
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.
Christopher J. Merchant, Frank Paul, Thomas Popp, Michael Ablain, Sophie Bontemps, Pierre Defourny, Rainer Hollmann, Thomas Lavergne, Alexandra Laeng, Gerrit de Leeuw, Jonathan Mittaz, Caroline Poulsen, Adam C. Povey, Max Reuter, Shubha Sathyendranath, Stein Sandven, Viktoria F. Sofieva, and Wolfgang Wagner
Earth Syst. Sci. Data, 9, 511–527, https://doi.org/10.5194/essd-9-511-2017, https://doi.org/10.5194/essd-9-511-2017, 2017
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Climate data records (CDRs) contain data describing Earth's climate and should address uncertainty in the data to communicate what is known about climate variability or change and what range of doubt exists. This paper discusses good practice for including uncertainty information in CDRs for the essential climate variables (ECVs) derived from satellite data. Recommendations emerge from the shared experience of diverse ECV projects within the European Space Agency Climate Change Initiative.
Alexandra Laeng, Thomas von Clarmann, Gabriele Stiller, Bianca Maria Dinelli, Anu Dudhia, Piera Raspollini, Norbert Glatthor, Udo Grabowski, Viktoria Sofieva, Lucien Froidevaux, Kaley A. Walker, and Claus Zehner
Atmos. Meas. Tech., 10, 1511–1518, https://doi.org/10.5194/amt-10-1511-2017, https://doi.org/10.5194/amt-10-1511-2017, 2017
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A MIPAS instrument was flown in 2002–2012 on the Envisat satellite and measured atmospheric composition. There exist four processors retrieving atmospheric profiles from MIPAS spectra. We performed a mathematically clean merging of 2007–2008 datasets of ozone from these four processors. The merged product was compared with ozone datasets from ACE-FTS and MLS instruments. The advantages and the shortcomings of this merged product are discussed.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Ed Dlugokencky, Angel J. Gomez-Pelaez, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, Jgor Arduini, Francesco Apadula, Christoph Gerbig, Dietrich G. Feist, Rigel Kivi, Yukio Yoshida, and Wouter Peters
Geosci. Model Dev., 10, 1261–1289, https://doi.org/10.5194/gmd-10-1261-2017, https://doi.org/10.5194/gmd-10-1261-2017, 2017
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In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Philippe Ricaud, William Lahoz, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, https://doi.org/10.5194/acp-17-1081-2017, 2017
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A detailed Observing System Simulation Experiment is performed to quantify the impact of future satellite instrument S-5P carbon monoxide (CO) on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode. S-5P is able to capture the CO from forest fires that occurred in Portugal. Furthermore, our results provide evidence of S-5P CO benefits for monitoring processes contributing to atmospheric pollution.
Viktoria F. Sofieva, Iolanda Ialongo, Janne Hakkarainen, Erkki Kyrölä, Johanna Tamminen, Marko Laine, Daan Hubert, Alain Hauchecorne, Francis Dalaudier, Jean-Loup Bertaux, Didier Fussen, Laurent Blanot, Gilbert Barrot, and Angelika Dehn
Atmos. Meas. Tech., 10, 231–246, https://doi.org/10.5194/amt-10-231-2017, https://doi.org/10.5194/amt-10-231-2017, 2017
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This paper presents a new ozone profile inversion algorithm for GOMOS/Envisat satellite data. This algorithm is enhanced with a DOAS-type method at visible wavelengths in the upper troposphere and the lower stratosphere. The new GOMOS ozone profiles have a significantly improved data quality in the UTLS compared to the official IPF V6 ozone profiles. The paper describes the inversion algorithm and present inter-comparisons with ozonesonde and satellite measurements.
Colette Brogniez, Frédérique Auriol, Christine Deroo, Antti Arola, Jukka Kujanpää, Béatrice Sauvage, Niilo Kalakoski, Mikko Riku Aleksi Pitkänen, Maxime Catalfamo, Jean-Marc Metzger, Guy Tournois, and Pierre Da Conceicao
Atmos. Chem. Phys., 16, 15049–15074, https://doi.org/10.5194/acp-16-15049-2016, https://doi.org/10.5194/acp-16-15049-2016, 2016
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The atmospheric ozone layer is changing, thus the UV radiation at the surface is changing. Due to both beneficial and adverse effects of UV on the biosphere, monitoring of UV is essential. Satellite sensors provide estimates of UV at the surface with a global coverage. Validation of satellite-sensor UV is therefore needed and this can be done by comparison with ground-based measurements. The present validation in three sites (midlatitude, tropical) shows that OMI and GOME-2 provide reliable UV.
Iolanda Ialongo, Jay Herman, Nick Krotkov, Lok Lamsal, K. Folkert Boersma, Jari Hovila, and Johanna Tamminen
Atmos. Meas. Tech., 9, 5203–5212, https://doi.org/10.5194/amt-9-5203-2016, https://doi.org/10.5194/amt-9-5203-2016, 2016
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We present the comparison between satellite- and ground-based atmospheric NO2 observations in Helsinki (Finland). The results show that, despite some limitations due to cloud contamination and low solar angles, satellite data are able to describe urban air quality features such as the weekly and seasonal cycles. The results support air quality satellite data exploitation at high latitudes and prepare for similar applications for future missions.
Filip Vanhellemont, Nina Mateshvili, Laurent Blanot, Charles Étienne Robert, Christine Bingen, Viktoria Sofieva, Francis Dalaudier, Cédric Tétard, Didier Fussen, Emmanuel Dekemper, Erkki Kyrölä, Marko Laine, Johanna Tamminen, and Claus Zehner
Atmos. Meas. Tech., 9, 4687–4700, https://doi.org/10.5194/amt-9-4687-2016, https://doi.org/10.5194/amt-9-4687-2016, 2016
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The GOMOS instrument on Envisat has delivered a valuable aerosol extinction data set for the Earth's upper troposphere and stratosphere, from 2002 to 2012. However, at many optical wavelengths, data quality was not optimal. This article describes the AerGOM retrieval algorithm that was built to solve the problem and presents a first look at the reprocessed GOMOS data, clearly demonstrating the improvement. Multi-wavelength studies of atmospheric aerosol–cloud properties will now be possible.
Aki Tsuruta, Tuula Aalto, Leif Backman, Janne Hakkarainen, Ingrid T. van der Laan-Luijkx, Maarten C. Krol, Renato Spahni, Sander Houweling, Marko Laine, Marcel van der Schoot, Ray Langenfelds, Raymond Ellul, and Wouter Peters
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-181, https://doi.org/10.5194/gmd-2016-181, 2016
Revised manuscript has not been submitted
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In this study, we found that methane emission estimates, driven by the CTE-CH4 model, depend on model setups and inputs, especially for regional estimates. An optimal setup makes the estimates stable, but inputs, such as emission estimates from inventories, and observations, also play significant role. The results can be used for an extended analysis on relative contributions of methane emissions to atmospheric methane concentration changes in recent decades.
Emmihenna Jääskeläinen, Terhikki Manninen, Johanna Tamminen, and Marko Laine
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-180, https://doi.org/10.5194/amt-2016-180, 2016
Revised manuscript not accepted
Niilo Kalakoski, Jukka Kujanpää, Viktoria Sofieva, Johanna Tamminen, Margherita Grossi, and Pieter Valks
Atmos. Meas. Tech., 9, 1533–1544, https://doi.org/10.5194/amt-9-1533-2016, https://doi.org/10.5194/amt-9-1533-2016, 2016
S. Hassinen, D. Balis, H. Bauer, M. Begoin, A. Delcloo, K. Eleftheratos, S. Gimeno Garcia, J. Granville, M. Grossi, N. Hao, P. Hedelt, F. Hendrick, M. Hess, K.-P. Heue, J. Hovila, H. Jønch-Sørensen, N. Kalakoski, A. Kauppi, S. Kiemle, L. Kins, M. E. Koukouli, J. Kujanpää, J.-C. Lambert, R. Lang, C. Lerot, D. Loyola, M. Pedergnana, G. Pinardi, F. Romahn, M. van Roozendael, R. Lutz, I. De Smedt, P. Stammes, W. Steinbrecht, J. Tamminen, N. Theys, L. G. Tilstra, O. N. E. Tuinder, P. Valks, C. Zerefos, W. Zimmer, and I. Zyrichidou
Atmos. Meas. Tech., 9, 383–407, https://doi.org/10.5194/amt-9-383-2016, https://doi.org/10.5194/amt-9-383-2016, 2016
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The three GOME-2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007–2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. The GOME-2 products (ozone, trace gases, aerosols and UV radiation) are important for ozone chemistry, air quality studies, climate modeling, policy monitoring and hazard warnings. The processing and dissemination is done by EUMETSAT O3M SAF project.
A. Kauppi, O. N. E. Tuinder, S. Tukiainen, V. Sofieva, and J. Tamminen
Atmos. Meas. Tech., 9, 249–261, https://doi.org/10.5194/amt-9-249-2016, https://doi.org/10.5194/amt-9-249-2016, 2016
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This paper presents a comparison of operational vertical ozone profiles retrieved by OPERA algorithm from the GOME-2 measurements on board Metop-A with space borne high-vertical-resolution ozone profiles by GOMOS, OSIRIS and MLS. The overall agreement of ozone profiles from GOME-2 and reference instruments is within 15 % below 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to underestimate the ozone concentration above 30 km.
J. Kujanpää and N. Kalakoski
Atmos. Meas. Tech., 8, 4399–4414, https://doi.org/10.5194/amt-8-4399-2015, https://doi.org/10.5194/amt-8-4399-2015, 2015
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The surface ultraviolet radiation product generated operationally in the framework of the Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring of the European Organisation for the Exploitation of Meteorological Satellites is described. The product is derived from measurements of polar orbiting satellites and contains important quantities of solar radiation that can be harmful to life on the Earth and affect atmospheric reactions related to air quality and climate change.
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.
J. Kuttippurath, S. Godin-Beekmann, F. Lefèvre, M. L. Santee, L. Froidevaux, and A. Hauchecorne
Atmos. Chem. Phys., 15, 10385–10397, https://doi.org/10.5194/acp-15-10385-2015, https://doi.org/10.5194/acp-15-10385-2015, 2015
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Our study finds large interannual variability in Antarctic ozone loss in the recent decade, with a number of winters showing shallow ozone holes but also with the year of the largest ozone hole in the last decades. These smaller ozone holes or ozone losses are mainly related to the year-to-year changes in dynamical processes rather than the variations in anthropogenic ozone-depleting substances (ODSs), as the change in ODS levels during the study period was very small.
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.
S. Tukiainen, E. Kyrölä, J. Tamminen, J. Kujanpää, and L. Blanot
Atmos. Meas. Tech., 8, 3107–3115, https://doi.org/10.5194/amt-8-3107-2015, https://doi.org/10.5194/amt-8-3107-2015, 2015
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A novel daytime ozone profile data set was created from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. These stratospheric ozone profiles cover the years 2002-2012 with good accuracy, vertical resolution, and global coverage.
G. Bernhard, A. Arola, A. Dahlback, V. Fioletov, A. Heikkilä, B. Johnsen, T. Koskela, K. Lakkala, T. Svendby, and J. Tamminen
Atmos. Chem. Phys., 15, 7391–7412, https://doi.org/10.5194/acp-15-7391-2015, https://doi.org/10.5194/acp-15-7391-2015, 2015
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Surface erythemal UV data from the Ozone Monitoring Instrument (OMI) are validated for high northern latitudes (Arctic and Scandinavia) using ground-based measurements. The bias in OMI data caused by incorrect assumptions of the surface albedo are quantified and the mechanism that causes this bias is discussed. Methods to improve the accuracy of OMI data products are presented.
I. Ialongo, J. Hakkarainen, R. Kivi, P. Anttila, N. A. Krotkov, K. Yang, C. Li, S. Tukiainen, S. Hassinen, and J. Tamminen
Atmos. Meas. Tech., 8, 2279–2289, https://doi.org/10.5194/amt-8-2279-2015, https://doi.org/10.5194/amt-8-2279-2015, 2015
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The SO2 observations from OMI and OMPS satellite instruments are compared to ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The best agreement with the Brewer observations in Sodankylä, Finland can be found, assuming the SO2 predominantly located in the lowest levels of the atmosphere. The analysis of the SO2 surface concentrations in northern Finland supports the hypothesis that the volcanic plume was located very close to the surface.
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
M. Laine, N. Latva-Pukkila, and E. Kyrölä
Atmos. Chem. Phys., 14, 9707–9725, https://doi.org/10.5194/acp-14-9707-2014, https://doi.org/10.5194/acp-14-9707-2014, 2014
P. Ollinaho, H. Järvinen, P. Bauer, M. Laine, P. Bechtold, J. Susiluoto, and H. Haario
Geosci. Model Dev., 7, 1889–1900, https://doi.org/10.5194/gmd-7-1889-2014, https://doi.org/10.5194/gmd-7-1889-2014, 2014
I. Ialongo, J. Hakkarainen, N. Hyttinen, J.-P. Jalkanen, L. Johansson, K. F. Boersma, N. Krotkov, and J. Tamminen
Atmos. Chem. Phys., 14, 7795–7805, https://doi.org/10.5194/acp-14-7795-2014, https://doi.org/10.5194/acp-14-7795-2014, 2014
A. Parrish, I. S. Boyd, G. E. Nedoluha, P. K. Bhartia, S. M. Frith, N. A. Kramarova, B. J. Connor, G. E. Bodeker, L. Froidevaux, M. Shiotani, and T. Sakazaki
Atmos. Chem. Phys., 14, 7255–7272, https://doi.org/10.5194/acp-14-7255-2014, https://doi.org/10.5194/acp-14-7255-2014, 2014
V. F. Sofieva, J. Tamminen, E. Kyrölä, A. Laeng, T. von Clarmann, F. Dalaudier, A. Hauchecorne, J.-L. Bertaux, G. Barrot, L. Blanot, D. Fussen, and F. Vanhellemont
Atmos. Meas. Tech., 7, 2147–2158, https://doi.org/10.5194/amt-7-2147-2014, https://doi.org/10.5194/amt-7-2147-2014, 2014
V. Kan, V. F. Sofieva, and F. Dalaudier
Atmos. Meas. Tech., 7, 1861–1872, https://doi.org/10.5194/amt-7-1861-2014, https://doi.org/10.5194/amt-7-1861-2014, 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
A. Määttä, M. Laine, J. Tamminen, and J. P. Veefkind
Atmos. Meas. Tech., 7, 1185–1199, https://doi.org/10.5194/amt-7-1185-2014, https://doi.org/10.5194/amt-7-1185-2014, 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
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
V. F. Sofieva, J. Tamminen, E. Kyrölä, T. Mielonen, P. Veefkind, B. Hassler, and G.E. Bodeker
Atmos. Chem. Phys., 14, 283–299, https://doi.org/10.5194/acp-14-283-2014, https://doi.org/10.5194/acp-14-283-2014, 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
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
P. Ollinaho, P. Bechtold, M. Leutbecher, M. Laine, A. Solonen, H. Haario, and H. Järvinen
Nonlin. Processes Geophys., 20, 1001–1010, https://doi.org/10.5194/npg-20-1001-2013, https://doi.org/10.5194/npg-20-1001-2013, 2013
E. Kyrölä, M. Laine, V. Sofieva, J. Tamminen, S.-M. Päivärinta, S. Tukiainen, J. Zawodny, and L. Thomason
Atmos. Chem. Phys., 13, 10645–10658, https://doi.org/10.5194/acp-13-10645-2013, https://doi.org/10.5194/acp-13-10645-2013, 2013
C. Tétard, D. Fussen, F. Vanhellemont, C. Bingen, E. Dekemper, N. Mateshvili, D. Pieroux, C. Robert, E. Kyrölä, J. Tamminen, V. Sofieva, A. Hauchecorne, F. Dalaudier, J.-L. Bertaux, O. Fanton d'Andon, G. Barrot, L. Blanot, A. Dehn, and L. Saavedra de Miguel
Atmos. Meas. Tech., 6, 2953–2964, https://doi.org/10.5194/amt-6-2953-2013, https://doi.org/10.5194/amt-6-2953-2013, 2013
I. Fiorucci, G. Muscari, L. Froidevaux, and M. L. Santee
Atmos. Meas. Tech., 6, 2441–2453, https://doi.org/10.5194/amt-6-2441-2013, https://doi.org/10.5194/amt-6-2441-2013, 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
G. Saponaro, P. Kolmonen, J. Karhunen, J. Tamminen, and G. de Leeuw
Atmos. Meas. Tech., 6, 2301–2309, https://doi.org/10.5194/amt-6-2301-2013, https://doi.org/10.5194/amt-6-2301-2013, 2013
M. Khosravi, P. Baron, J. Urban, L. Froidevaux, A. I. Jonsson, Y. Kasai, K. Kuribayashi, C. Mitsuda, D. P. Murtagh, H. Sagawa, M. L. Santee, T. O. Sato, M. Shiotani, M. Suzuki, T. von Clarmann, K. A. Walker, and S. Wang
Atmos. Chem. Phys., 13, 7587–7606, https://doi.org/10.5194/acp-13-7587-2013, https://doi.org/10.5194/acp-13-7587-2013, 2013
N. J. Livesey, J. A. Logan, M. L. Santee, J. W. Waters, R. M. Doherty, W. G. Read, L. Froidevaux, and J. H. Jiang
Atmos. Chem. Phys., 13, 579–598, https://doi.org/10.5194/acp-13-579-2013, https://doi.org/10.5194/acp-13-579-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Predictions of failed satellite retrieval of air quality using machine learning
Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction
Global retrieval of TROPOMI tropospheric HCHO and NO2 columns with improved consistency based on the updated Peking University OMI NO2 algorithm
Quantitative estimate of several sources of uncertainty in drone-based methane emission measurements
Implementation and application of an improved phase spectrum determination scheme for Fourier transform spectrometry
Remote sensing of lower-middle-thermosphere temperatures using the N2 Lyman–Birge–Hopfield (LBH) bands
Retrievals of water vapour and temperature exploiting the far-infrared: application to aircraft observations in preparation for the FORUM mission
Global decadal measurements of methanol, ethene, ethyne, and HCN from the Cross-track Infrared Sounder
Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation
Developments on a 22 GHz microwave radiometer and reprocessing of 13-year time series for water vapour studies
Optimal selection of satellite XCO2 images for urban CO2 emission monitoring
Separating and quantifying facility-level methane emissions with overlapping plumes for spaceborne methane monitoring
A study of measurement scenarios for the future CO2M mission: avoidance of detector saturation and the impact on XCO2 retrievals
Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks
Remote sensing of methane point sources with the MethaneAIR airborne spectrometer
The differences between remote sensing and in situ air pollutant measurements over the Canadian oil sands
Retrieval of NO2 profiles from three years of Pandora MAX-DOAS measurements in Toronto, Canada
Using the FY-3E satellite hyperspectral infrared atmospheric sounder to quantitatively monitor volcanic SO2
NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations
Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: Benefit of using time-contiguous input features for machine learning models
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean
Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements
Merging TEMPEST microwave and GOES-16 geostationary IR soundings for improved water vapor profiles
Remote Sensing Estimates of Time-Resolved HONO and NO2 Emission Rates and Lifetimes in Wildfires
Assimilation of volcanic sulfur dioxide products from IASI and TROPOMI into the chemical transport model MOCAGE: case study of the 2021 La Soufrière Saint-Vincent eruption
Robustness of atmospheric trace gas retrievals obtained from low spectral resolution Fourier-transform infrared absorption spectra
Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission
Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection
Assessment of the contribution of the Meteosat Third Generation Infrared Sounder (MTG-IRS) for the characterisation of ozone over Europe
Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Current potential of CH4 emission estimates using TROPOMI in the Middle East
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements
In-Flight Estimation of Instrument Spectral Response Functions Using Sparse Representations
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
Atmos. Meas. Tech., 18, 1689–1715, https://doi.org/10.5194/amt-18-1689-2025, https://doi.org/10.5194/amt-18-1689-2025, 2025
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The large fleet of Earth observation satellites in orbit currently generate huge volumes of data, requiring significant computational resources to process these data in a timely manner. We present a method for predicting poor-quality measurements using machine learning. We find that machine learning methods can accurately predict poor-quality measurements and remove them from the processing chain, saving time and computational resources.
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
Atmos. Meas. Tech., 18, 1675–1687, https://doi.org/10.5194/amt-18-1675-2025, https://doi.org/10.5194/amt-18-1675-2025, 2025
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Currently, measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver–Julesburg basin, where agriculture and methane extraction infrastructure is often co-located.
Yuhang Zhang, Huan Yu, Isabelle De Smedt, Jintai Lin, Nicolas Theys, Michel Van Roozendael, Gaia Pinardi, Steven Compernolle, Ruijing Ni, Fangxuan Ren, Sijie Wang, Lulu Chen, Jos Van Geffen, Mengyao Liu, Alexander M. Cede, Martin Tiefengraber, Alexis Merlaud, Martina M. Friedrich, Andreas Richter, Ankie Piters, Vinod Kumar, Vinayak Sinha, Thomas Wagner, Yongjoo Choi, Hisahiro Takashima, Yugo Kanaya, Hitoshi Irie, Robert Spurr, Wenfu Sun, and Lorenzo Fabris
Atmos. Meas. Tech., 18, 1561–1589, https://doi.org/10.5194/amt-18-1561-2025, https://doi.org/10.5194/amt-18-1561-2025, 2025
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We developed an advanced algorithm for global retrieval of TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 vertical column densities with much improved consistency. Sensitivity tests demonstrate the complexity and nonlinear interactions of auxiliary parameters in the air mass factor calculation. An improved agreement is found with measurements from a global ground-based instrument network. The scientific retrieval provides a useful source of information for studies combining HCHO and NO2.
Tannaz H. Mohammadloo, Matthew Jones, Bas van de Kerkhof, Kyle Dawson, Brendan J. Smith, Stephen Conley, Abigail Corbett, and Rutger IJzermans
Atmos. Meas. Tech., 18, 1301–1324, https://doi.org/10.5194/amt-18-1301-2025, https://doi.org/10.5194/amt-18-1301-2025, 2025
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Methane is a potent greenhouse gas. Trustable detection and quantification of methane emissions at facility level are critical for identifying the largest sources and prioritizing them for repair. We provide a systematic analysis of several sources of uncertainty in drone-based methane emission surveys based on theoretical considerations and historical data sets. We provide guidelines for industry on how to avoid or minimize errors in drone-based methane emission quantification surveys.
Frank Hase, Paolo Castracane, Angelika Dehn, Omaira Elena García, David W. T. Griffith, Lukas Heizmann, Nicholas B. Jones, Tomi Karppinen, Rigel Kivi, Martine de Mazière, Justus Notholt, and Mahesh Kumar Sha
Atmos. Meas. Tech., 18, 1257–1267, https://doi.org/10.5194/amt-18-1257-2025, https://doi.org/10.5194/amt-18-1257-2025, 2025
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The primary measurement result delivered by a Fourier transform spectrometer is an interferogram, and the spectrum required for further analysis needs to be calculated from the interferogram by Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.
Richard Eastes, J. Scott Evans, Quan Gan, William McClintock, and Jerry Lumpe
Atmos. Meas. Tech., 18, 921–928, https://doi.org/10.5194/amt-18-921-2025, https://doi.org/10.5194/amt-18-921-2025, 2025
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Temperature is essential to understanding the thermosphere. Most temperature measurements have been indirect or had large uncertainties, especially in the lower-middle thermosphere, where data are rarely available. Since October 2018, NASA’s GOLD mission has produced disk images of neutral temperatures near 160 km at locations over the Americas and Atlantic Ocean. This paper discusses both temperature retrieval techniques and issues in interpreting GOLD’s images of thermospheric temperatures.
Sanjeevani Panditharatne, Helen Brindley, Caroline Cox, Richard Siddans, Jonathan Murray, Laura Warwick, and Stuart Fox
Atmos. Meas. Tech., 18, 717–735, https://doi.org/10.5194/amt-18-717-2025, https://doi.org/10.5194/amt-18-717-2025, 2025
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Observations from the upcoming European Space Agency’s Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite are theorised to be highly sensitive to distributions of water vapour within Earth’s atmosphere. We exploit this sensitivity and extend the Infrared Microwave Sounding retrieval scheme for use on observations from FORUM. This scheme is evaluated on both simulated and observed measurements and shows good agreement with references of the atmospheric state.
Kelley C. Wells, Dylan B. Millet, Jared F. Brewer, Vivienne H. Payne, Karen E. Cady-Pereira, Rick Pernak, Susan Kulawik, Corinne Vigouroux, Nicholas Jones, Emmanuel Mahieu, Maria Makarova, Tomoo Nagahama, Ivan Ortega, Mathias Palm, Kimberly Strong, Matthias Schneider, Dan Smale, Ralf Sussmann, and Minqiang Zhou
Atmos. Meas. Tech., 18, 695–716, https://doi.org/10.5194/amt-18-695-2025, https://doi.org/10.5194/amt-18-695-2025, 2025
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Atmospheric volatile organic compounds (VOCs) affect both air quality and climate. Satellite measurements can help us to assess and predict their global impacts. We present new decadal (2012–2023) measurements of four key VOCs – methanol, ethene, ethyne, and hydrogen cyanide (HCN) – from the Cross-track Infrared Sounder. The measurements reflect emissions from major forests, wildfires, and industry and provide new information to advance understanding of these sources and their changes over time.
Otto Lamminpää, Jouni Susiluoto, Jonathan Hobbs, James McDuffie, Amy Braverman, and Houman Owhadi
Atmos. Meas. Tech., 18, 673–694, https://doi.org/10.5194/amt-18-673-2025, https://doi.org/10.5194/amt-18-673-2025, 2025
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We develop and demonstrate a fast forward function emulator for remote sensing of greenhouse gases. These forward functions are computationally expensive to evaluate, and as such the key challenge for many satellite missions in their data processing is the time used in these evaluations. Our method is fast and accurate enough, less than 1 % relative error, so that it could be safely used in operational processing.
Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, and Axel Murk
Atmos. Meas. Tech., 18, 555–567, https://doi.org/10.5194/amt-18-555-2025, https://doi.org/10.5194/amt-18-555-2025, 2025
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Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle-atmospheric water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13-year dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.
Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
Atmos. Meas. Tech., 18, 533–554, https://doi.org/10.5194/amt-18-533-2025, https://doi.org/10.5194/amt-18-533-2025, 2025
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We study the capacity of XCO2 spaceborne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods and objective criteria for image selection. The wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias in the emission estimation of −7 % and a spread of 56 %. Other images give a bias of −31 % and a spread of 99 %.
Yiguo Pang, Longfei Tian, Denghui Hu, Shuang Gao, and Guohua Liu
Atmos. Meas. Tech., 18, 455–470, https://doi.org/10.5194/amt-18-455-2025, https://doi.org/10.5194/amt-18-455-2025, 2025
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The spatial adjacency of methane point sources can result in plume overlapping, presenting challenges for quantification from space. A separation and quantification method combining the Gaussian plume model and the integrated mass enhancement method is proposed. A modern parameter estimation technique is introduced to separate the overlapping plumes from satellite observations. The proposed method is evaluated with synthesized observations and real satellite observations.
Michael Weimer, Michael Hilker, Stefan Noël, Max Reuter, Michael Buchwitz, Blanca Fuentes Andrade, Rüdiger Lang, Bernd Sierk, Yasjka Meijer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
EGUsphere, https://doi.org/10.5194/egusphere-2024-3857, https://doi.org/10.5194/egusphere-2024-3857, 2025
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Optical detectors have a maximum signal (saturation). Exceedance means that the measurement has to be discarded. We investigate where saturation will occur for the future European satellite mission dedicated to CO2 Monitoring (CO2M) and strategies to avoid saturation. It impacts coverage and precision, both important for estimation of local CO2 emissions. We find that taking two pictures per sampling should be sufficient to avoid saturation for CO2M with some impact on the CO2 precision.
Maximilian Reuter, Michael Hilker, Stefan Noël, Antonio Di Noia, Michael Weimer, Oliver Schneising, Michael Buchwitz, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 18, 241–264, https://doi.org/10.5194/amt-18-241-2025, https://doi.org/10.5194/amt-18-241-2025, 2025
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Carbon dioxide (CO2) and methane (CH4) are the main anthropogenic greenhouse gases. The European Copernicus CO2 monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.
Luis Guanter, Jack Warren, Mark Omara, Apisada Chulakadabba, Javier Roger, Maryann Sargent, Jonathan E. Franklin, Steven C. Wofsy, and Ritesh Gautam
EGUsphere, https://doi.org/10.5194/egusphere-2024-3577, https://doi.org/10.5194/egusphere-2024-3577, 2025
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This study presents a data processing scheme for the detection and quantification of methane emissions using the MethaneAIR airborne spectrometer. We show that the proposed methods enable the detection of smaller plumes than other existing methods, and that improves the potential of MethaneAIR to survey methane point sources across large regions
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech., 17, 6889–6912, https://doi.org/10.5194/amt-17-6889-2024, https://doi.org/10.5194/amt-17-6889-2024, 2024
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This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows that the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
Ramina Alwarda, Kristof Bognar, Xiaoyi Zhao, Vitali Fioletov, Jonathan Davies, Sum Chi Lee, Debora Griffin, Alexandru Lupu, Udo Frieß, Alexander Cede, Yushan Su, and Kimberly Strong
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-180, https://doi.org/10.5194/amt-2024-180, 2024
Revised manuscript accepted for AMT
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Nitrogen dioxide (NO2) is a pollutant with a short lifetime and large variability, but there are limited measurements of its distribution in the lower atmosphere. We present a new dataset of three years of NO2 vertical profiles in Toronto, Canada, and evaluate it using NO2 from satellite and surface monitoring networks and simulations by an air quality forecast model. We quantify and explain the differences among the datasets to provide information that can be used to understand NO2 variability.
Xinyu Li, Lin Zhu, Hongfu Sun, Jun Li, Ximing Lv, Chengli Qi, and Huanhuan Yan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-183, https://doi.org/10.5194/amt-2024-183, 2024
Revised manuscript accepted for AMT
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This paper proposes a novel methodology for selecting Sulfur dioxide (SO2) sensitive channels from FY-3E/HIRAS-II hyperspectral IR atmospheric sensors to quantitatively monitor volcanic SO2. This methodology considers the interference of atmospheric temperature, humidity, and surface temperature on SO2 detection and retrieval, laying the groundwork for developing a more accurate and flexible volcanic SO2 retrieval algorithm under different atmospheric conditions.
Leon Kuhn, Steffen Beirle, Sergey Osipov, Andrea Pozzer, and Thomas Wagner
Atmos. Meas. Tech., 17, 6485–6516, https://doi.org/10.5194/amt-17-6485-2024, https://doi.org/10.5194/amt-17-6485-2024, 2024
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This paper presents a new machine learning model that allows us to compute NO2 concentration profiles from satellite observations. A neural network was trained on synthetic data from the regional chemistry and transport model WRF-Chem. This is the first model of its kind. We present a thorough model validation study, covering various seasons and regions of the world.
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
Atmos. Meas. Tech., 17, 6459–6484, https://doi.org/10.5194/amt-17-6459-2024, https://doi.org/10.5194/amt-17-6459-2024, 2024
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CHORA, an advanced cloud convective differential technique, enhances the accuracy of tropospheric-ozone retrievals. Unlike the traditional Pacific cloud reference sector scheme, CHORA introduces a local-cloud reference sector and an alternative approach (CLCT) for precision. Analysing monthly averaged TROPOMI data from 2018 to 2022 and validating with SHADOZ ozonesonde data, CLCT outperforms other methods and so is the preferred choice, especially in future geostationary satellite missions.
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
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Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral resolution of 0.0035 cm-1 are applied to retrieve C3H8 columns for the first time in Xianghe, China, within the NDACC-IRWG. The mean and standard deviation of the C3H8 columns are 1.80 ± 0.81 (1σ) × 1015 molec. cm-2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R = 0.84) and C2H2 (R = 0.79), as well as between C3H8 and CO (R = 0.72).
Janek Gödeke, Andreas Richter, Kezia Lange, Peter Maaß, Hyunkee Hong, Hanlim Lee, and Junsung Park
EGUsphere, https://doi.org/10.5194/egusphere-2024-3145, https://doi.org/10.5194/egusphere-2024-3145, 2024
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The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO2. GEMS provides hourly data, improving the time-resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO2 over Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time-resolution. This is achieved by using observations from previous hours as additional inputs.
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024, https://doi.org/10.5194/amt-17-6247-2024, 2024
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Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024, https://doi.org/10.5194/amt-17-5911-2024, 2024
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Atmospheric bromine destroys ozone, impacts oxidation capacity, and oxidizes mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved two to three pieces of information vertically; we apply new methods to get five and a half vertically and two more in time. We compare with aircraft measurements to validate the methods and look at variations in BrO over the Pacific.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech., 17, 5637–5653, https://doi.org/10.5194/amt-17-5637-2024, https://doi.org/10.5194/amt-17-5637-2024, 2024
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A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Carley D. Fredrickson, Scott J. Janz, Lok N. Lamsal, Ursula A. Jongebloed, Joshua L. Laughner, and Joel A. Thornton
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-158, https://doi.org/10.5194/amt-2024-158, 2024
Revised manuscript accepted for AMT
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We present an analysis of high-resolution remote sensing measurements of nitrogen-containing trace gases emitted by wildfires. The measurements were made using an instrument on the NASA ER-2 aircraft in the summer of 2019. We find that time-resolved fire intensity is critical to quantify trace gas emissions over a fire’s entire lifespan. These findings have implications for improving air pollution forecasts downwind of wildfires using computer models of atmospheric chemistry and meteorology.
Mickaël Bacles, Jonathan Améric, and Vincent Guidard
EGUsphere, https://doi.org/10.5194/egusphere-2024-2941, https://doi.org/10.5194/egusphere-2024-2941, 2024
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Sulfur dioxide emitted during volcanic eruptions can be hazardous for aviation safety. A recent development aims at improving the forecasts of volcanic sulfur dioxide quantities made by the MOCAGE chemistry transport model. Both TROPOMI and IASI instruments are assimilated in the model. We focus on the eruption event of the La Soufrière Saint-Vincent volcano in April 2021. The combined assimilation of IASI and TROPOMI observations always leads to a better analyses and forecasts.
Bavo Langerock, Martine De Mazière, Filip Desmet, Pauli Heikkinen, Rigel Kivi, Mahesh Kumar Sha, Corinne Vigouroux, Minqiang Zhou, Gopala Khrisna Darbha, and Mohmmed Talib
EGUsphere, https://doi.org/10.5194/egusphere-2024-2764, https://doi.org/10.5194/egusphere-2024-2764, 2024
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Ground-based Fourier-transform interferometer instruments have been used for many decades to measure direct solar light in the infrared to obtain high-resolution spectra from which atmospheric gas profile concentrations can be derived. It is shown that the typical processing chain used to derive atmospheric gas columns can be sensitive to relatively small shortenings of the recorded interferograms. Low-resolution recordings, used in more recent years, are more sensitive to such adaptations.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech., 17, 5373–5396, https://doi.org/10.5194/amt-17-5373-2024, https://doi.org/10.5194/amt-17-5373-2024, 2024
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Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
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The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher J. Diekmann, and Kei Yoshimura
Atmos. Meas. Tech., 17, 5243–5259, https://doi.org/10.5194/amt-17-5243-2024, https://doi.org/10.5194/amt-17-5243-2024, 2024
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Despite its importance for extreme weather and climate feedbacks, atmospheric convection is not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events. We find that the impact of the isotopologues is small for stable atmospheric conditions but significant for unstable conditions, which have the strongest societal impacts (e.g. storms and flooding).
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
Atmos. Meas. Tech., 17, 5261–5277, https://doi.org/10.5194/amt-17-5261-2024, https://doi.org/10.5194/amt-17-5261-2024, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where it is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
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Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
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We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
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This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
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Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
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Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024, https://doi.org/10.5194/amt-17-2277-2024, 2024
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Comparison between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminates these seasonally varying differences by applying new ozone absorption cross sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Jihanne El Haouari, Jean-Michel Gaucel, Christelle Pittet, Jean-Yves Tourneret, and Herwig Wendt
EGUsphere, https://doi.org/10.48550/arXiv.2404.05298, https://doi.org/10.48550/arXiv.2404.05298, 2024
Short summary
Short summary
This paper explores new techniques based on sparse representations for estimating the spectral response functions of high-resolution spectrometers. The method is highly competitive with commonly used parametric models yielding more accurate estimates while accounting for wavelength dependence. The resulting normalized estimation errors of the spectrometer spectral responses are less than 1 %, which will allow better quantification of trace gas concentrations at the Earth surface.
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