Articles | Volume 9, issue 8
https://doi.org/10.5194/amt-9-3999-2016
© Author(s) 2016. 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-9-3999-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Aug 2016
Research article |
| 23 Aug 2016
Validation and analysis of MOPITT CO observations of the Amazon Basin
M. N. Deeter
CORRESPONDING AUTHOR
Atmospheric Chemistry Observations and Modeling Laboratory,
National Center for Atmospheric Research, Boulder, CO, USA
S. Martínez-Alonso
Atmospheric Chemistry Observations and Modeling Laboratory,
National Center for Atmospheric Research, Boulder, CO, USA
L. V. Gatti
Instituto de Pesquisas Energéticas e Nucleares (IPEN)–Comissao
Nacional de Energia Nuclear (CNEN)–Atmospheric Chemistry Laboratory, 2242
Avenida Professor Lineu Prestes, Cidade Universitaria, Sao Paulo CEP
05508-000, Brazil
M. Gloor
School of Geography, University of Leeds, Woodhouse Lane, Leeds LS9 2JT, UK
J. B. Miller
Global Monitoring Division, Earth System Research Laboratory,
National Oceanic and Atmospheric Administration, 325 Broadway, Boulder,
CO 80305, USA
Cooperative Institute for Research in Environmental Sciences
(CIRES), University of Colorado, Boulder, CO 80309, USA
L. G. Domingues
Instituto de Pesquisas Energéticas e Nucleares (IPEN)–Comissao
Nacional de Energia Nuclear (CNEN)–Atmospheric Chemistry Laboratory, 2242
Avenida Professor Lineu Prestes, Cidade Universitaria, Sao Paulo CEP
05508-000, Brazil
C. S. C. Correia
Instituto de Pesquisas Energéticas e Nucleares (IPEN)–Comissao
Nacional de Energia Nuclear (CNEN)–Atmospheric Chemistry Laboratory, 2242
Avenida Professor Lineu Prestes, Cidade Universitaria, Sao Paulo CEP
05508-000, Brazil
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Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
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Sourish Basu, Xin Lan, Edward Dlugokencky, Sylvia Michel, Stefan Schwietzke, John B. Miller, Lori Bruhwiler, Youmi Oh, Pieter P. Tans, Francesco Apadula, Luciana V. Gatti, Armin Jordan, Jaroslaw Necki, Motoki Sasakawa, Shinji Morimoto, Tatiana Di Iorio, Haeyoung Lee, Jgor Arduini, and Giovanni Manca
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Atmospheric methane (CH4) has been growing steadily since 2007 for reasons that are not well understood. Here we determine sources of methane using a technique informed by atmospheric measurements of CH4 and its isotopologue 13CH4. Measurements of 13CH4 provide for better separation of microbial, fossil, and fire sources of methane than CH4 measurements alone. Compared to previous assessments such as the Global Carbon Project, we find a larger microbial contribution to the post-2007 increase.
Ali Jalali, Kaley A. Walker, Kimberly Strong, Rebecca R. Buchholz, Merritt N. Deeter, Debra Wunch, Sébastien Roche, Tyler Wizenberg, Erik Lutsch, Erin McGee, Helen M. Worden, Pierre Fogal, and James R. Drummond
Atmos. Meas. Tech., 15, 6837–6863, https://doi.org/10.5194/amt-15-6837-2022, https://doi.org/10.5194/amt-15-6837-2022, 2022
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This study validates MOPITT version 8 carbon monoxide measurements over the Canadian high Arctic for the period 2006 to 2019. The MOPITT products from different detector pixels and channels are compared with ground-based measurements from the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada. These results show good consistency between the satellite and ground-based measurements and provide guidance on the usage of these MOPITT data at high latitudes.
Stijn Naus, Lucas G. Domingues, Maarten Krol, Ingrid T. Luijkx, Luciana V. Gatti, John B. Miller, Emanuel Gloor, Sourish Basu, Caio Correia, Gerbrand Koren, Helen M. Worden, Johannes Flemming, Gabrielle Pétron, and Wouter Peters
Atmos. Chem. Phys., 22, 14735–14750, https://doi.org/10.5194/acp-22-14735-2022, https://doi.org/10.5194/acp-22-14735-2022, 2022
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We assimilate MOPITT CO satellite data in the TM5-4D-Var inverse modelling framework to estimate Amazon fire CO emissions for 2003–2018. We show that fire emissions have decreased over the analysis period, coincident with a decrease in deforestation rates. However, interannual variations in fire emissions are large, and they correlate strongly with soil moisture. Our results reveal an important role for robust, top-down fire CO emissions in quantifying and attributing Amazon fire intensity.
Sara Martínez-Alonso, Merritt N. Deeter, Bianca C. Baier, Kathryn McKain, Helen Worden, Tobias Borsdorff, Colm Sweeney, and Ilse Aben
Atmos. Meas. Tech., 15, 4751–4765, https://doi.org/10.5194/amt-15-4751-2022, https://doi.org/10.5194/amt-15-4751-2022, 2022
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Merritt Deeter, Gene Francis, John Gille, Debbie Mao, Sara Martínez-Alonso, Helen Worden, Dan Ziskin, James Drummond, Róisín Commane, Glenn Diskin, and Kathryn McKain
Atmos. Meas. Tech., 15, 2325–2344, https://doi.org/10.5194/amt-15-2325-2022, https://doi.org/10.5194/amt-15-2325-2022, 2022
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The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument uses remote sensing to obtain retrievals (measurements) of carbon monoxide (CO) in the atmosphere. This paper describes the latest MOPITT data product, Version 9. Globally, the number of daytime MOPITT retrievals over land has increased by 30 %–40 % compared to the previous product. The reported improvements in the MOPITT product should benefit a wide variety of applications including studies of pollution sources.
Heba S. Marey, James R. Drummond, Dylan B. A. Jones, Helen Worden, Merritt N. Deeter, John Gille, and Debbie Mao
Atmos. Meas. Tech., 15, 701–719, https://doi.org/10.5194/amt-15-701-2022, https://doi.org/10.5194/amt-15-701-2022, 2022
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In this study, an analysis has been performed to understand the improvements in observational coverage over Canada in the new MOPITT V9 product. Temporal and spatial analysis of V9 indicates a general coverage gain of 15–20 % relative to V8, which varies regionally and seasonally; e.g., the number of successful MOPITT retrievals in V9 was doubled over Canada in winter. Also, comparison with the corresponding IASI instrument indicated generally good agreement, with about a 5–10 % positive bias.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565, https://doi.org/10.5194/bg-18-6547-2021, https://doi.org/10.5194/bg-18-6547-2021, 2021
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The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Bharat Rastogi, John B. Miller, Micheal Trudeau, Arlyn E. Andrews, Lei Hu, Marikate Mountain, Thomas Nehrkorn, Bianca Baier, Kathryn McKain, John Mund, Kaiyu Guan, and Caroline B. Alden
Atmos. Chem. Phys., 21, 14385–14401, https://doi.org/10.5194/acp-21-14385-2021, https://doi.org/10.5194/acp-21-14385-2021, 2021
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Predicting Earth's climate is difficult, partly due to uncertainty in forecasting how much CO2 can be removed by oceans and plants, because we cannot measure these exchanges directly on large scales. Satellites such as NASA's OCO-2 can provide part of the needed information, but data need to be highly precise and accurate. We evaluate these data and find small biases in certain months that are similar to the signals of interest. We argue that continued improvement of these data is necessary.
Chris Wilson, Martyn P. Chipperfield, Manuel Gloor, Robert J. Parker, Hartmut Boesch, Joey McNorton, Luciana V. Gatti, John B. Miller, Luana S. Basso, and Sarah A. Monks
Atmos. Chem. Phys., 21, 10643–10669, https://doi.org/10.5194/acp-21-10643-2021, https://doi.org/10.5194/acp-21-10643-2021, 2021
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Methane (CH4) is an important greenhouse gas emitted from wetlands like those found in the basin of the Amazon River. Using an atmospheric model and observations from GOSAT, we quantified CH4 emissions from Amazonia during the previous decade. We found that the largest emissions came from a region in the eastern basin and that emissions there were rising faster than in other areas of South America. This finding was supported by CH4 observations made on aircraft within the basin.
Wenfu Tang, David P. Edwards, Louisa K. Emmons, Helen M. Worden, Laura M. Judd, Lok N. Lamsal, Jassim A. Al-Saadi, Scott J. Janz, James H. Crawford, Merritt N. Deeter, Gabriele Pfister, Rebecca R. Buchholz, Benjamin Gaubert, and Caroline R. Nowlan
Atmos. Meas. Tech., 14, 4639–4655, https://doi.org/10.5194/amt-14-4639-2021, https://doi.org/10.5194/amt-14-4639-2021, 2021
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We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability within satellite pixels over urban regions. The sub-grid variability within satellite pixels increases with increasing satellite pixel sizes. Temporal variability within satellite pixels decreases with increasing satellite pixel sizes. This work is particularly relevant and useful for future satellite design, satellite data interpretation, and point-grid data comparisons.
Elizabeth B. Wiggins, Arlyn Andrews, Colm Sweeney, John B. Miller, Charles E. Miller, Sander Veraverbeke, Roisin Commane, Steven Wofsy, John M. Henderson, and James T. Randerson
Atmos. Chem. Phys., 21, 8557–8574, https://doi.org/10.5194/acp-21-8557-2021, https://doi.org/10.5194/acp-21-8557-2021, 2021
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We analyzed high-resolution trace gas measurements collected from a tower in Alaska during a very active fire season to improve our understanding of trace gas emissions from boreal forest fires. Our results suggest previous studies may have underestimated emissions from smoldering combustion in boreal forest fires.
Jessica C. A. Baker, Luis Garcia-Carreras, Manuel Gloor, John H. Marsham, Wolfgang Buermann, Humberto R. da Rocha, Antonio D. Nobre, Alessandro Carioca de Araujo, and Dominick V. Spracklen
Hydrol. Earth Syst. Sci., 25, 2279–2300, https://doi.org/10.5194/hess-25-2279-2021, https://doi.org/10.5194/hess-25-2279-2021, 2021
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Evapotranspiration (ET) is a vital part of the Amazon water cycle, but it is difficult to measure over large areas. In this study, we compare spatial patterns, seasonality, and recent trends in Amazon ET from a water-budget analysis with estimates from satellites, reanalysis, and global climate models. We find large differences between products, showing that many widely used datasets and climate models may not provide a reliable representation of this crucial variable over the Amazon.
Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, and Steven Wofsy
Earth Syst. Sci. Data, 13, 299–330, https://doi.org/10.5194/essd-13-299-2021, https://doi.org/10.5194/essd-13-299-2021, 2021
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On average, the terrestrial biosphere carbon sink is equivalent to ~ 20 % of fossil fuel emissions. Understanding where and why the terrestrial biosphere absorbs carbon from the atmosphere is pivotal to any mitigation policy. Here we present a regionally resolved satellite-constrained net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: CMS-Flux NBE 2020. The dataset provides a unique perspective on monitoring regional contributions to the CO2 growth rate.
Haeyoung Lee, Edward J. Dlugokencky, Jocelyn C. Turnbull, Sepyo Lee, Scott J. Lehman, John B. Miller, Gabrielle Pétron, Jeong-Sik Lim, Gang-Woong Lee, Sang-Sam Lee, and Young-San Park
Atmos. Chem. Phys., 20, 12033–12045, https://doi.org/10.5194/acp-20-12033-2020, https://doi.org/10.5194/acp-20-12033-2020, 2020
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To understand South Korea's CO2 emissions and sinks as well as those of the surrounding region, we used flask-air samples collected for 2 years at Anmyeondo (36.53° N, 126.32° E; 46 m a.s.l.), South Korea, for analysis of observed 14C in atmospheric CO2 as a tracer of fossil fuel CO2 contribution (Cff). Here, we showed our observation result of 14C and Cff. SF6 and CO can be good proxies of Cff in this study, and the ratio of CO to Cff was compared to a bottom-up inventory.
Sara Martínez-Alonso, Merritt Deeter, Helen Worden, Tobias Borsdorff, Ilse Aben, Róisin Commane, Bruce Daube, Gene Francis, Maya George, Jochen Landgraf, Debbie Mao, Kathryn McKain, and Steven Wofsy
Atmos. Meas. Tech., 13, 4841–4864, https://doi.org/10.5194/amt-13-4841-2020, https://doi.org/10.5194/amt-13-4841-2020, 2020
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CO is of great importance in climate and air quality studies. To understand newly available TROPOMI data in the frame of the global CO record, we compared those to satellite (MOPITT) and airborne (ATom) CO datasets. The MOPITT dataset is the longest to date (2000–present) and is well-characterized. We used ATom to validate cloudy TROPOMI data over oceans and investigate TROPOMI's vertical sensitivity to CO. Our results show that TROPOMI CO data are in excellent agreement with the other datasets.
Dipayan Paul, Hubertus A. Scheeren, Henk G. Jansen, Bert A. M. Kers, John B. Miller, Andrew M. Crotwell, Sylvia E. Michel, Luciana V. Gatti, Lucas G. Domingues, Caio S. C. Correia, Raiane A. L. Neves, Harro A. J. Meijer, and Wouter Peters
Atmos. Meas. Tech., 13, 4051–4064, https://doi.org/10.5194/amt-13-4051-2020, https://doi.org/10.5194/amt-13-4051-2020, 2020
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For reliable measurements of CO2 mole fractions and its stable isotope composition in air samples, one needs to carefully dry them during collection. Here we describe evaluation of a portable, consumable-free and power-free Nafion-based drying system that is currently being used for sample collection over the Amazon. Laboratory tests indicate that this Nafion-based system does not influence the mole fraction measurements of CH4, CO, N2O, SF6, and CO2 and the stable isotope composition of CO2.
Wenfu Tang, Helen M. Worden, Merritt N. Deeter, David P. Edwards, Louisa K. Emmons, Sara Martínez-Alonso, Benjamin Gaubert, Rebecca R. Buchholz, Glenn S. Diskin, Russell R. Dickerson, Xinrong Ren, Hao He, and Yutaka Kondo
Atmos. Meas. Tech., 13, 1337–1356, https://doi.org/10.5194/amt-13-1337-2020, https://doi.org/10.5194/amt-13-1337-2020, 2020
Bo Zheng, Frederic Chevallier, Yi Yin, Philippe Ciais, Audrey Fortems-Cheiney, Merritt N. Deeter, Robert J. Parker, Yilong Wang, Helen M. Worden, and Yuanhong Zhao
Earth Syst. Sci. Data, 11, 1411–1436, https://doi.org/10.5194/essd-11-1411-2019, https://doi.org/10.5194/essd-11-1411-2019, 2019
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We use a multi-species atmospheric Bayesian inversion approach to attribute satellite-observed atmospheric carbon monoxide (CO) variations to its sources and sinks in order to achieve a full closure of the global CO budget during 2000–2017. We identify a declining trend in the global CO budget since 2000, driven by reduced anthropogenic emissions in the US, Europe, and China, as well as by reduced biomass burning emissions globally, especially in equatorial Africa.
Merritt N. Deeter, David P. Edwards, Gene L. Francis, John C. Gille, Debbie Mao, Sara Martínez-Alonso, Helen M. Worden, Dan Ziskin, and Meinrat O. Andreae
Atmos. Meas. Tech., 12, 4561–4580, https://doi.org/10.5194/amt-12-4561-2019, https://doi.org/10.5194/amt-12-4561-2019, 2019
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The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument has been making nearly continuous observations of atmospheric carbon monoxide (CO) since 2000. MOPITT CO retrievals are routinely used to analyze emissions from fossil fuels and biomass burning, as well as the atmospheric transport of those emissions. This paper describes recent enhancements to the MOPITT retrieval algorithm. New validation results illustrate clear improvements in the fidelity of the MOPITT product.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Richard Coppell, Emanuel Gloor, and Joseph Holden
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-51, https://doi.org/10.5194/gmd-2019-51, 2019
Publication in GMD not foreseen
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(1) We developed a new Sphagnum model for ecosystem exchange. (2) The model is implemented in TRIFFID which is part of the JULES land surface model. (3) Outputs compare well to empirical field data. (4) JULES can now better incorporate peatland-climate feedbacks.
Joe McNorton, Chris Wilson, Manuel Gloor, Rob J. Parker, Hartmut Boesch, Wuhu Feng, Ryan Hossaini, and Martyn P. Chipperfield
Atmos. Chem. Phys., 18, 18149–18168, https://doi.org/10.5194/acp-18-18149-2018, https://doi.org/10.5194/acp-18-18149-2018, 2018
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Since 2007 atmospheric methane (CH4) has been unexpectedly increasing following a 6-year hiatus. We have used an atmospheric model to attribute regional sources and global sinks of CH4 using observations for the 2003–2015 period. Model results show the renewed growth is best explained by decreased atmospheric removal, decreased biomass burning emissions, and an increased energy sector (mainly from Africa–Middle East and Southern Asia–Oceania) and wetland emissions (mainly from northern Eurasia).
Wei He, Ivar R. van der Velde, Arlyn E. Andrews, Colm Sweeney, John Miller, Pieter Tans, Ingrid T. van der Laan-Luijkx, Thomas Nehrkorn, Marikate Mountain, Weimin Ju, Wouter Peters, and Huilin Chen
Geosci. Model Dev., 11, 3515–3536, https://doi.org/10.5194/gmd-11-3515-2018, https://doi.org/10.5194/gmd-11-3515-2018, 2018
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We have implemented a regional, high-resolution, and computationally attractive carbon dioxide data assimilation system. This system, named CTDAS-Lagrange, is capable of simultaneously optimizing terrestrial biosphere fluxes and the lateral boundary conditions. The CTDAS-Lagrange system can be easily extended to assimilate an additional tracer, e.g., carbonyl sulfide (COS or OCS), for regional estimates of both net and gross carbon fluxes.
Paul I. Palmer, Simon O'Doherty, Grant Allen, Keith Bower, Hartmut Bösch, Martyn P. Chipperfield, Sarah Connors, Sandip Dhomse, Liang Feng, Douglas P. Finch, Martin W. Gallagher, Emanuel Gloor, Siegfried Gonzi, Neil R. P. Harris, Carole Helfter, Neil Humpage, Brian Kerridge, Diane Knappett, Roderic L. Jones, Michael Le Breton, Mark F. Lunt, Alistair J. Manning, Stephan Matthiesen, Jennifer B. A. Muller, Neil Mullinger, Eiko Nemitz, Sebastian O'Shea, Robert J. Parker, Carl J. Percival, Joseph Pitt, Stuart N. Riddick, Matthew Rigby, Harjinder Sembhi, Richard Siddans, Robert L. Skelton, Paul Smith, Hannah Sonderfeld, Kieran Stanley, Ann R. Stavert, Angelina Wenger, Emily White, Christopher Wilson, and Dickon Young
Atmos. Chem. Phys., 18, 11753–11777, https://doi.org/10.5194/acp-18-11753-2018, https://doi.org/10.5194/acp-18-11753-2018, 2018
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This paper provides an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) experiment. GAUGE was designed to quantify nationwide GHG emissions of the UK, bringing together measurements and atmospheric transport models. This novel experiment is the first of its kind. We anticipate it will inform the blueprint for countries that are building a measurement infrastructure in preparation for global stocktakes, which are a key part of the Paris Agreement.
James S. Wang, S. Randolph Kawa, G. James Collatz, Motoki Sasakawa, Luciana V. Gatti, Toshinobu Machida, Yuping Liu, and Michael E. Manyin
Atmos. Chem. Phys., 18, 11097–11124, https://doi.org/10.5194/acp-18-11097-2018, https://doi.org/10.5194/acp-18-11097-2018, 2018
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We used measurements of CO2 in the atmosphere from the GOSAT satellite and from surface sites around the world, together with a transport model and a unique estimation technique, to quantify CO2 sources and removals over a recent period. We find that climate variations can strongly influence uptake by vegetation and release in decay and fires. However, regional gaps in observations and inaccuracies to which current satellite technology is susceptible result in important estimation biases.
Sourish Basu, David F. Baker, Frédéric Chevallier, Prabir K. Patra, Junjie Liu, and John B. Miller
Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, https://doi.org/10.5194/acp-18-7189-2018, 2018
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CO2 measurements from the global surface network and CO2 estimates from satellites such as the Orbiting Carbon Observatory 2 (OCO-2) are currently used to quantify the surface sources and sinks of CO2, using what we know about atmospheric transport of gases. In this work, we quantify the uncertainties in those surface source/sink estimates that stem from errors in our atmospheric transport models, using an observing system simulation experiment (OSSE).
Taku Umezawa, Carl A. M. Brenninkmeijer, Thomas Röckmann, Carina van der Veen, Stanley C. Tyler, Ryo Fujita, Shinji Morimoto, Shuji Aoki, Todd Sowers, Jochen Schmitt, Michael Bock, Jonas Beck, Hubertus Fischer, Sylvia E. Michel, Bruce H. Vaughn, John B. Miller, James W. C. White, Gordon Brailsford, Hinrich Schaefer, Peter Sperlich, Willi A. Brand, Michael Rothe, Thomas Blunier, David Lowry, Rebecca E. Fisher, Euan G. Nisbet, Andrew L. Rice, Peter Bergamaschi, Cordelia Veidt, and Ingeborg Levin
Atmos. Meas. Tech., 11, 1207–1231, https://doi.org/10.5194/amt-11-1207-2018, https://doi.org/10.5194/amt-11-1207-2018, 2018
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Isotope measurements are useful for separating different methane sources. However, the lack of widely accepted standards and calibration methods for stable carbon and hydrogen isotopic ratios of methane in air has caused significant measurement offsets among laboratories. We conducted worldwide interlaboratory comparisons, surveyed the literature and assessed them systematically. This study may be of help in future attempts to harmonize data sets of isotopic composition of atmospheric methane.
Ivar R. van der Velde, John B. Miller, Michiel K. van der Molen, Pieter P. Tans, Bruce H. Vaughn, James W. C. White, Kevin Schaefer, and Wouter Peters
Geosci. Model Dev., 11, 283–304, https://doi.org/10.5194/gmd-11-283-2018, https://doi.org/10.5194/gmd-11-283-2018, 2018
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We explored an inverse modeling technique to interpret global atmospheric measurements of CO2 and the ratio of its stable carbon isotopes (δ13C). We detected the possible underestimation of drought stress in biosphere models after applying combined atmospheric CO2 and δ13C constraints. This study highlights the importance of improving the representation of the biosphere in carbon–climate models, in particular in a world where droughts become more extreme and more frequent.
Demerval S. Moreira, Karla M. Longo, Saulo R. Freitas, Marcia A. Yamasoe, Lina M. Mercado, Nilton E. Rosário, Emauel Gloor, Rosane S. M. Viana, John B. Miller, Luciana V. Gatti, Kenia T. Wiedemann, Lucas K. G. Domingues, and Caio C. S. Correia
Atmos. Chem. Phys., 17, 14785–14810, https://doi.org/10.5194/acp-17-14785-2017, https://doi.org/10.5194/acp-17-14785-2017, 2017
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Fire in the Amazon forest produces a large amount of smoke that is released into the atmosphere and covers a large portion of South America for about 3 months each year. The smoke affects the energy and CO2 budgets. Using a numerical atmospheric model, we demonstrated that the smoke changes the forest from a source to a sink of CO2 to the atmosphere. The smoke ultimately acts to at least partially compensate for the forest carbon lost due to fire emissions.
Iris N. Dekker, Sander Houweling, Ilse Aben, Thomas Röckmann, Maarten Krol, Sara Martínez-Alonso, Merritt N. Deeter, and Helen M. Worden
Atmos. Chem. Phys., 17, 14675–14694, https://doi.org/10.5194/acp-17-14675-2017, https://doi.org/10.5194/acp-17-14675-2017, 2017
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This study estimates carbon monoxide emissions from the city of Madrid using MOPITT satellite data. There are two methods used and reviewed in this paper: a method that can only estimate a trend in the emission and a newly developed method that also includes model data from WRF to quantify the emissions. We find Madrid CO emissions to be lower by 48 % for 2002 and by 17 % for 2006 compared with the EdgarV4.2 emission inventory, but uncertainty (20 to 50 %) remains.
Merritt N. Deeter, David P. Edwards, Gene L. Francis, John C. Gille, Sara Martínez-Alonso, Helen M. Worden, and Colm Sweeney
Atmos. Meas. Tech., 10, 2533–2555, https://doi.org/10.5194/amt-10-2533-2017, https://doi.org/10.5194/amt-10-2533-2017, 2017
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This manuscript describes the methods used for deriving the latest version 7 product for atmospheric carbon monoxide (CO) from measurements made by the MOPITT (Measurements of Pollution in the Troposphere) satellite instrument. Comparisons of MOPITT-retrieved CO vertical profiles with in situ data measured from aircraft are also presented, and they demonstrate clear improvements relative to earlier MOPITT products. The new CO product is appropriate for a wide variety of applications.
Kristal R. Verhulst, Anna Karion, Jooil Kim, Peter K. Salameh, Ralph F. Keeling, Sally Newman, John Miller, Christopher Sloop, Thomas Pongetti, Preeti Rao, Clare Wong, Francesca M. Hopkins, Vineet Yadav, Ray F. Weiss, Riley M. Duren, and Charles E. Miller
Atmos. Chem. Phys., 17, 8313–8341, https://doi.org/10.5194/acp-17-8313-2017, https://doi.org/10.5194/acp-17-8313-2017, 2017
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We present the first carbon dioxide (CO2) and methane (CH4) measurements from an extensive surface network as part of the Los Angeles Megacity Carbon Project. We describe methods that are essential for understanding carbon fluxes from complex urban environments. CO2 and CH4 levels are spatially and temporally variable, with urban sites showing significant enhancements relative to background. In 2015, the median afternoon enhancement near downtown Los Angeles was ~15 ppm CO2 and ~80 ppb CH4.
Rebecca R. Buchholz, Merritt N. Deeter, Helen M. Worden, John Gille, David P. Edwards, James W. Hannigan, Nicholas B. Jones, Clare Paton-Walsh, David W. T. Griffith, Dan Smale, John Robinson, Kimberly Strong, Stephanie Conway, Ralf Sussmann, Frank Hase, Thomas Blumenstock, Emmanuel Mahieu, and Bavo Langerock
Atmos. Meas. Tech., 10, 1927–1956, https://doi.org/10.5194/amt-10-1927-2017, https://doi.org/10.5194/amt-10-1927-2017, 2017
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The study presents the first systematic use of ground-based remote-sensing data from the Network for the Detection of Atmospheric Composition Change (NDACC) to validate satellite-based Measurements of Pollution in the Troposphere (MOPITT) total column carbon monoxide (CO). MOPITT generally shows low bias with respect to the ground-based instruments. The geographic and temporal dependence of validation results are determined. Our findings inform some recommendations for using MOPITT measurements.
Liang Feng, Paul I. Palmer, Hartmut Bösch, Robert J. Parker, Alex J. Webb, Caio S. C. Correia, Nicholas M. Deutscher, Lucas G. Domingues, Dietrich G. Feist, Luciana V. Gatti, Emanuel Gloor, Frank Hase, Rigel Kivi, Yi Liu, John B. Miller, Isamu Morino, Ralf Sussmann, Kimberly Strong, Osamu Uchino, Jing Wang, and Andreas Zahn
Atmos. Chem. Phys., 17, 4781–4797, https://doi.org/10.5194/acp-17-4781-2017, https://doi.org/10.5194/acp-17-4781-2017, 2017
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We use the GEOS-Chem global 3-D model of atmospheric chemistry and transport and an ensemble Kalman filter to simultaneously infer regional fluxes of methane (CH4) and carbon dioxide (CO2) directly from GOSAT retrievals of XCH4:XCO2, using sparse ground-based CH4 and CO2 mole fraction data to anchor the ratio. Our results show that assimilation of GOSAT data significantly reduced the posterior uncertainty and changed the a priori spatial distribution of CH4 emissions.
Zhe Jiang, John R. Worden, Helen Worden, Merritt Deeter, Dylan B. A. Jones, Avelino F. Arellano, and Daven K. Henze
Atmos. Chem. Phys., 17, 4565–4583, https://doi.org/10.5194/acp-17-4565-2017, https://doi.org/10.5194/acp-17-4565-2017, 2017
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We constrain the long-term variation in global CO emissions for 2001–2015. Our results confirm that the decreasing trend of tropospheric CO in the Northern Hemisphere is due to decreasing CO emissions from anthropogenic and biomass burning sources. In particular, we find decreasing CO emissions from the United States and China in the past 15 years, unchanged anthropogenic CO emissions from Europe since 2008, and likely a positive trend from India and southeast Asia.
Bradley O. Christoffersen, Manuel Gloor, Sophie Fauset, Nikolaos M. Fyllas, David R. Galbraith, Timothy R. Baker, Bart Kruijt, Lucy Rowland, Rosie A. Fisher, Oliver J. Binks, Sanna Sevanto, Chonggang Xu, Steven Jansen, Brendan Choat, Maurizio Mencuccini, Nate G. McDowell, and Patrick Meir
Geosci. Model Dev., 9, 4227–4255, https://doi.org/10.5194/gmd-9-4227-2016, https://doi.org/10.5194/gmd-9-4227-2016, 2016
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We developed a plant hydraulics model for tropical forests based on established plant physiological theory, and parameterized it by conducting a pantropical hydraulic trait survey. We show that a substantial amount of trait diversity can be represented in the model by a reduced set of trait dimensions. The fully parameterized model is able capture tree-level variation in water status and improves simulations of total ecosystem transpiration, showing how to incorporate hydraulic traits in models.
Sourish Basu, John Bharat Miller, and Scott Lehman
Atmos. Chem. Phys., 16, 5665–5683, https://doi.org/10.5194/acp-16-5665-2016, https://doi.org/10.5194/acp-16-5665-2016, 2016
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We present a dual tracer atmospheric inversion technique to separately estimate biospheric and fossil fuel CO2 fluxes from atmospheric measurements of CO2 and 14CO2. In addition to estimating monthly regional fossil fuel fluxes of CO2, this system can also reduce biases in biospheric fluxes that arise in a traditional CO2 inversion from prescribing a fixed but inaccurate fossil fuel flux.
Anna Karion, Colm Sweeney, John B. Miller, Arlyn E. Andrews, Roisin Commane, Steven Dinardo, John M. Henderson, Jacob Lindaas, John C. Lin, Kristina A. Luus, Tim Newberger, Pieter Tans, Steven C. Wofsy, Sonja Wolter, and Charles E. Miller
Atmos. Chem. Phys., 16, 5383–5398, https://doi.org/10.5194/acp-16-5383-2016, https://doi.org/10.5194/acp-16-5383-2016, 2016
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Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Here we use carbon dioxide and methane measurements from a tower near Fairbanks AK to investigate regional Alaskan fluxes of CO2 and CH4 for 2012–2014.
Sudhanshu Pandey, Sander Houweling, Maarten Krol, Ilse Aben, Frédéric Chevallier, Edward J. Dlugokencky, Luciana V. Gatti, Emanuel Gloor, John B. Miller, Rob Detmers, Toshinobu Machida, and Thomas Röckmann
Atmos. Chem. Phys., 16, 5043–5062, https://doi.org/10.5194/acp-16-5043-2016, https://doi.org/10.5194/acp-16-5043-2016, 2016
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This study investigates the constraint provided by measurements of Xratio (XCH4/XCO2) from space on surface fluxes of CH4 and CO2. We apply the ratio inversion method described in Pandey et al. (2015) to Xratio retrievals from the GOSAT with the TM5-4DVAR inverse modeling system, to constrain the surface fluxes of CH4 and CO2 for 2009 and 2010. The results are compared to proxy CH4 inversions using model-derived-XCO2 mixing ratios from CarbonTracker and MACC.
M. George, C. Clerbaux, I. Bouarar, P.-F. Coheur, M. N. Deeter, D. P. Edwards, G. Francis, J. C. Gille, J. Hadji-Lazaro, D. Hurtmans, A. Inness, D. Mao, and H. M. Worden
Atmos. Meas. Tech., 8, 4313–4328, https://doi.org/10.5194/amt-8-4313-2015, https://doi.org/10.5194/amt-8-4313-2015, 2015
L. Molina, G. Broquet, P. Imbach, F. Chevallier, B. Poulter, D. Bonal, B. Burban, M. Ramonet, L. V. Gatti, S. C. Wofsy, J. W. Munger, E. Dlugokencky, and P. Ciais
Atmos. Chem. Phys., 15, 8423–8438, https://doi.org/10.5194/acp-15-8423-2015, https://doi.org/10.5194/acp-15-8423-2015, 2015
S. Tilmes, J.-F. Lamarque, L. K. Emmons, D. E. Kinnison, P.-L. Ma, X. Liu, S. Ghan, C. Bardeen, S. Arnold, M. Deeter, F. Vitt, T. Ryerson, J. W. Elkins, F. Moore, J. R. Spackman, and M. Val Martin
Geosci. Model Dev., 8, 1395–1426, https://doi.org/10.5194/gmd-8-1395-2015, https://doi.org/10.5194/gmd-8-1395-2015, 2015
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The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. Both configurations are well suited as tools for atmospheric chemistry modeling studies in the troposphere and lower stratosphere.
A. P. Ballantyne, R. Andres, R. Houghton, B. D. Stocker, R. Wanninkhof, W. Anderegg, L. A. Cooper, M. DeGrandpre, P. P. Tans, J. B. Miller, C. Alden, and J. W. C. White
Biogeosciences, 12, 2565–2584, https://doi.org/10.5194/bg-12-2565-2015, https://doi.org/10.5194/bg-12-2565-2015, 2015
S. Gonzi, P. I. Palmer, R. Paugam, M. Wooster, and M. N. Deeter
Atmos. Chem. Phys., 15, 4339–4355, https://doi.org/10.5194/acp-15-4339-2015, https://doi.org/10.5194/acp-15-4339-2015, 2015
J. M. Henderson, J. Eluszkiewicz, M. E. Mountain, T. Nehrkorn, R. Y.-W. Chang, A. Karion, J. B. Miller, C. Sweeney, N. Steiner, S. C. Wofsy, and C. E. Miller
Atmos. Chem. Phys., 15, 4093–4116, https://doi.org/10.5194/acp-15-4093-2015, https://doi.org/10.5194/acp-15-4093-2015, 2015
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This paper describes the atmospheric modeling that underlies the science analysis for the NASA Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Summary statistics of the WRF meteorological model performance on a 3.3 km grid indicate good overall agreement with surface and radiosonde observations. The high quality of the WRF meteorological fields inspires confidence in their use to drive the STILT transport model for the purpose of computing surface influence fields (“footprints”).
A. Ghosh, P. K. Patra, K. Ishijima, T. Umezawa, A. Ito, D. M. Etheridge, S. Sugawara, K. Kawamura, J. B. Miller, E. J. Dlugokencky, P. B. Krummel, P. J. Fraser, L. P. Steele, R. L. Langenfelds, C. M. Trudinger, J. W. C. White, B. Vaughn, T. Saeki, S. Aoki, and T. Nakazawa
Atmos. Chem. Phys., 15, 2595–2612, https://doi.org/10.5194/acp-15-2595-2015, https://doi.org/10.5194/acp-15-2595-2015, 2015
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Atmospheric CH4 increased from 900ppb to 1800ppb during the period 1900–2010 at a rate unprecedented in any observational records. We use bottom-up emissions and a chemistry-transport model to simulate CH4. The optimized global total CH4 emission, estimated from the model–observation differences, increased at fastest rate during 1940–1990. Using δ13C of CH4 measurements we attribute this emission increase to biomass burning. Total CH4 lifetime is shortened by 4% over the simulation period.
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
M. O. Johnson, M. Gloor, M. J. Kirkby, and J. Lloyd
Biogeosciences, 11, 6873–6894, https://doi.org/10.5194/bg-11-6873-2014, https://doi.org/10.5194/bg-11-6873-2014, 2014
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We present a soil evolution model which incorporates the major processes of pedogenesis: mineral weathering, leaching, erosion, bioturbation, nutrient cycling and organic carbon inputs. We compare the modelled soil properties with soil chronosequences from Hawaii and demonstrate that the model captures well the key components of soil development. The model also highlights the important role that vegetation plays in accelerating the weathering and the release of globally important nutrients.
I. R. van der Velde, J. B. Miller, K. Schaefer, G. R. van der Werf, M. C. Krol, and W. Peters
Biogeosciences, 11, 6553–6571, https://doi.org/10.5194/bg-11-6553-2014, https://doi.org/10.5194/bg-11-6553-2014, 2014
A. T. J. de Laat, I. Aben, M. Deeter, P. Nédélec, H. Eskes, J.-L. Attié, P. Ricaud, R. Abida, L. El Amraoui, and J. Landgraf
Atmos. Meas. Tech., 7, 3783–3799, https://doi.org/10.5194/amt-7-3783-2014, https://doi.org/10.5194/amt-7-3783-2014, 2014
M. N. Deeter, S. Martínez-Alonso, D. P. Edwards, L. K. Emmons, J. C. Gille, H. M. Worden, C. Sweeney, J. V. Pittman, B. C. Daube, and S. C. Wofsy
Atmos. Meas. Tech., 7, 3623–3632, https://doi.org/10.5194/amt-7-3623-2014, https://doi.org/10.5194/amt-7-3623-2014, 2014
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The MOPITT Version 6 product for carbon monoxide (CO) incorporates several enhancements. First, a geolocation bias has been eliminated. Second, the new variable a priori for CO concentrations is based on simulations performed with the CAM-Chem chemical transport model for the years 2000-2009. Third, required meteorological fields are extracted from the MERRA reanalysis. Finally, a retrieval bias in the upper troposphere was substantially reduced. Validation results are presented.
C. Wilson, M. P. Chipperfield, M. Gloor, and F. Chevallier
Geosci. Model Dev., 7, 2485–2500, https://doi.org/10.5194/gmd-7-2485-2014, https://doi.org/10.5194/gmd-7-2485-2014, 2014
L. Bruhwiler, E. Dlugokencky, K. Masarie, M. Ishizawa, A. Andrews, J. Miller, C. Sweeney, P. Tans, and D. Worthy
Atmos. Chem. Phys., 14, 8269–8293, https://doi.org/10.5194/acp-14-8269-2014, https://doi.org/10.5194/acp-14-8269-2014, 2014
P. Ciais, A. J. Dolman, A. Bombelli, R. Duren, A. Peregon, P. J. Rayner, C. Miller, N. Gobron, G. Kinderman, G. Marland, N. Gruber, F. Chevallier, R. J. Andres, G. Balsamo, L. Bopp, F.-M. Bréon, G. Broquet, R. Dargaville, T. J. Battin, A. Borges, H. Bovensmann, M. Buchwitz, J. Butler, J. G. Canadell, R. B. Cook, R. DeFries, R. Engelen, K. R. Gurney, C. Heinze, M. Heimann, A. Held, M. Henry, B. Law, S. Luyssaert, J. Miller, T. Moriyama, C. Moulin, R. B. Myneni, C. Nussli, M. Obersteiner, D. Ojima, Y. Pan, J.-D. Paris, S. L. Piao, B. Poulter, S. Plummer, S. Quegan, P. Raymond, M. Reichstein, L. Rivier, C. Sabine, D. Schimel, O. Tarasova, R. Valentini, R. Wang, G. van der Werf, D. Wickland, M. Williams, and C. Zehner
Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, https://doi.org/10.5194/bg-11-3547-2014, 2014
N. M. Fyllas, E. Gloor, L. M. Mercado, S. Sitch, C. A. Quesada, T. F. Domingues, D. R. Galbraith, A. Torre-Lezama, E. Vilanova, H. Ramírez-Angulo, N. Higuchi, D. A. Neill, M. Silveira, L. Ferreira, G. A. Aymard C., Y. Malhi, O. L. Phillips, and J. Lloyd
Geosci. Model Dev., 7, 1251–1269, https://doi.org/10.5194/gmd-7-1251-2014, https://doi.org/10.5194/gmd-7-1251-2014, 2014
M. R. Raupach, M. Gloor, J. L. Sarmiento, J. G. Canadell, T. L. Frölicher, T. Gasser, R. A. Houghton, C. Le Quéré, and C. M. Trudinger
Biogeosciences, 11, 3453–3475, https://doi.org/10.5194/bg-11-3453-2014, https://doi.org/10.5194/bg-11-3453-2014, 2014
B. W. LaFranchi, G. Pétron, J. B. Miller, S. J. Lehman, A. E. Andrews, E. J. Dlugokencky, B. Hall, B. R. Miller, S. A. Montzka, W. Neff, P. C. Novelli, C. Sweeney, J. C. Turnbull, D. E. Wolfe, P. P. Tans, K. R. Gurney, and T. P. Guilderson
Atmos. Chem. Phys., 13, 11101–11120, https://doi.org/10.5194/acp-13-11101-2013, https://doi.org/10.5194/acp-13-11101-2013, 2013
R. Locatelli, P. Bousquet, F. Chevallier, A. Fortems-Cheney, S. Szopa, M. Saunois, A. Agusti-Panareda, D. Bergmann, H. Bian, P. Cameron-Smith, M. P. Chipperfield, E. Gloor, S. Houweling, S. R. Kawa, M. Krol, P. K. Patra, R. G. Prinn, M. Rigby, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 9917–9937, https://doi.org/10.5194/acp-13-9917-2013, https://doi.org/10.5194/acp-13-9917-2013, 2013
D. S. Moreira, S. R. Freitas, J. P. Bonatti, L. M. Mercado, N. M. É. Rosário, K. M. Longo, J. B. Miller, M. Gloor, and L. V. Gatti
Geosci. Model Dev., 6, 1243–1259, https://doi.org/10.5194/gmd-6-1243-2013, https://doi.org/10.5194/gmd-6-1243-2013, 2013
H. M. Worden, D. P. Edwards, M. N. Deeter, D. Fu, S. S. Kulawik, J. R. Worden, and A. Arellano
Atmos. Meas. Tech., 6, 1633–1646, https://doi.org/10.5194/amt-6-1633-2013, https://doi.org/10.5194/amt-6-1633-2013, 2013
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, https://doi.org/10.5194/acp-13-1093-2013, 2013
H. M. Worden, M. N. Deeter, C. Frankenberg, M. George, F. Nichitiu, J. Worden, I. Aben, K. W. Bowman, C. Clerbaux, P. F. Coheur, A. T. J. de Laat, R. Detweiler, J. R. Drummond, D. P. Edwards, J. C. Gille, D. Hurtmans, M. Luo, S. Martínez-Alonso, S. Massie, G. Pfister, and J. X. Warner
Atmos. Chem. Phys., 13, 837–850, https://doi.org/10.5194/acp-13-837-2013, https://doi.org/10.5194/acp-13-837-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Evaluation of total ozone measurements from Geostationary Environmental Monitoring Spectrometer (GEMS)
To new heights by flying low: comparison of aircraft vertical NO2 profiles to model simulations and implications for TROPOMI NO2 retrievals
Local comparisons of tropospheric ozone: vertical soundings at two neighbouring stations in southern Bavaria
Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of NO2 and H2CO at Kinshasa and comparisons with TROPOMI observations
Total column ozone trends from the NASA Merged Ozone time series 1979 to 2021 showing latitude-dependent ozone recovery dates (1994 to 1998)
The SPARC water vapour assessment II: biases and drifts of water vapour satellite data records with respect to frost point hygrometer records
Vicarious calibration of the Tropospheric Monitoring Instrument (TROPOMI) short-wave infrared (SWIR) module over the Railroad Valley Playa
Evaluation of the first year of Pandora NO2 measurements over Beijing and application to satellite validation
First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements
A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Single-blind test of nine methane-sensing satellite systems from three continents
Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm
OLCI-A/B tandem phase: evaluation of FLuorescence EXplorer (FLEX)-like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX
Multi-parameter dynamical diagnostics for upper tropospheric and lower stratospheric studies
An approach to track instrument calibration and produce consistent products with the version-8 total column ozone algorithm (V8TOZ)
Methane Point Source Quantification Using MethaneAIR: A New Airborne Imaging Spectrometer
Satellite remote-sensing capability to assess tropospheric-column ratios of formaldehyde and nitrogen dioxide: case study during the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) field campaign
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
Evaluation of open- and closed-path sampling systems for the determination of emission rates of NH3 and CH4 with inverse dispersion modeling
Performance of AIRS ozone retrieval over the central Himalayas: use of ozonesonde and other satellite datasets
Validation of NH3 observations from AIRS and CrIS against aircraft measurements from DISCOVER-AQ and a surface network in the Magic Valley
Solar occultation measurement of mesospheric ozone by SAGE III/ISS: impact of variations along the line of sight caused by photochemistry
Understanding the potential of Sentinel-2 for monitoring methane point emissions
TROPOMI/S5P Total Column Water Vapor validation against AERONET ground-based measurements
Assessing the consistency of satellite-derived upper tropospheric humidity measurements
A comparison of carbon monoxide retrievals between the MOPITT satellite and Canadian high-Arctic ground-based NDACC and TCCON FTIR measurements
Long-term validation of MIPAS ESA operational products using MIPAS-B measurements
Comparison of OCO-2 target observations to MUCCnet – is it possible to capture urban XCO2 gradients from space?
SAGE III/ISS ozone and NO2 validation using diurnal scaling factors
An improved OSIRIS NO2 profile retrieval in the upper troposphere–lower stratosphere and intercomparison with ACE-FTS and SAGE III/ISS
TROPESS/CrIS carbon monoxide profile validation with NOAA GML and ATom in situ aircraft observations
Validation of Copernicus Sentinel-3/OLCI Level 2 Land Integrated Water Vapour product
Evaluation of MOPITT and TROPOMI carbon monoxide retrievals using AirCore in situ vertical profiles
Horizontal distribution of tropospheric NO2 and aerosols derived by dual-scan multi-wavelength multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in Uccle, Belgium
On the influence of underlying elevation data on Sentinel-5 Precursor TROPOMI satellite methane retrievals over Greenland
Satellite measurements of peroxyacetyl nitrate from the Cross-Track Infrared Sounder: comparison with ATom aircraft measurements
The SPARC Water Vapor Assessment II: assessment of satellite measurements of upper tropospheric humidity
Ground-based validation of the MetOp-A and MetOp-B GOME-2 OClO measurements
Satellite data validation: a parametrization of the natural variability of atmospheric mixing ratios
Investigation of spaceborne trace gas products over St Petersburg and Yekaterinburg, Russia, by using COllaborative Column Carbon Observing Network (COCCON) observations
A comparison of the impact of TROPOMI and OMI tropospheric NO2 on global chemical data assimilation
Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 1: Synthetic dataset for validation of trace gas retrieval algorithms
Variations of Arctic winter ozone from the LIMS Level 3 dataset
Retrieval of tropospheric aerosol, NO2, and HCHO vertical profiles from MAX-DOAS observations over Thessaloniki, Greece: intercomparison and validation of two inversion algorithms
Assessment of the quality of ACE-FTS stratospheric ozone data
Validation and error estimation of AIRS MUSES CO profiles with HIPPO, ATom, and NOAA GML aircraft observations
Dealing with spatial heterogeneity in pointwise-to-gridded- data comparisons
Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation
Intercomparison of CO measurements from TROPOMI, ACE-FTS, and a high-Arctic ground-based Fourier transform spectrometer
Kanghyun Baek, Jae Hwan Kim, Juseon Bak, David P. Haffner, Mina Kang, and Hyunkee Hong
Atmos. Meas. Tech., 16, 5461–5478, https://doi.org/10.5194/amt-16-5461-2023, https://doi.org/10.5194/amt-16-5461-2023, 2023
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The GEMS mission was the first mission of the geostationary satellite constellation for hourly atmospheric composition monitoring. The GEMS ozone measurements were cross-compared to those of Pandora, OMPS, and TROPOMI satellite sensors and excellent agreement was found. GEMS has proven to be a powerful new instrument for monitoring and assessing the diurnal variation in atmospheric ozone. This experience can be used to advance research with future geostationary environmental satellite missions.
Tobias Christoph Valentin Werner Riess, Klaas Folkert Boersma, Ward Van Roy, Jos de Laat, Enrico Dammers, and Jasper van Vliet
Atmos. Meas. Tech., 16, 5287–5304, https://doi.org/10.5194/amt-16-5287-2023, https://doi.org/10.5194/amt-16-5287-2023, 2023
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Satellite retrievals of trace gases require prior knowledge of the vertical distribution of the pollutant, which is usually obtained from models. Using aircraft-measured vertical NO2 profiles over the North Sea in summer 2021, we evaluate the Transport Model 5 profiles used in the TROPOMI NO2 retrieval. We conclude that driven by the low horizontal resolution and the overestimated vertical mixing, resulting NO2 columns are 20 % too low. This has important implications for emission estimates.
Thomas Trickl, Martin Adelwart, Dina Khordakova, Ludwig Ries, Christian Rolf, Michael Sprenger, Wolfgang Steinbrecht, and Hannes Vogelmann
Atmos. Meas. Tech., 16, 5145–5165, https://doi.org/10.5194/amt-16-5145-2023, https://doi.org/10.5194/amt-16-5145-2023, 2023
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Tropospheric ozone have been measured for more than a century. Highly quantitative ozone measurements have been made at monitoring stations. However, deficits have been reported for vertical sounding systems. Here, we report a thorough intercomparison effort between a differential-absorption lidar system and two types of balloon-borne ozone sondes, also using ozone sensors at nearby mountain sites as references. The sondes agree very well with the lidar after offset corrections.
Rodriguez Yombo Phaka, Alexis Merlaud, Gaia Pinardi, Martina M. Friedrich, Michel Van Roozendael, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, François Hendrick, Ermioni Dimitropoulou, Richard Bopili Mbotia Lepiba, Edmond Phuku Phuati, Buenimio Lomami Djibi, Lars Jacobs, Caroline Fayt, Jean-Pierre Mbungu Tsumbu, and Emmanuel Mahieu
Atmos. Meas. Tech., 16, 5029–5050, https://doi.org/10.5194/amt-16-5029-2023, https://doi.org/10.5194/amt-16-5029-2023, 2023
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We present air quality measurements in Kinshasa, Democratic Republic of the Congo, performed with a newly developed instrument which was installed on a roof of the University of Kinshasa in November 2019. The instrument records spectra of the scattered sunlight, from which we derive the abundances of nitrogen dioxide and formaldehyde, two important pollutants. We compare our ground-based measurements with those of the TROPOspheric Monitoring Instrument (TROPOMI).
Jay Herman, Jerald Ziemke, and Richard McPeters
Atmos. Meas. Tech., 16, 4693–4707, https://doi.org/10.5194/amt-16-4693-2023, https://doi.org/10.5194/amt-16-4693-2023, 2023
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Fourier series multivariate linear regression trends (% per decade) in ozone were estimated from the Merged Ozone Data Set (MOD) from 1979 to 2021 in two different regimes, from 1979 to TA (the date when ozone stopped decreasing) and TA to 2021. The derived TA is a latitude-dependent date, ranging from 1994 to 1998. TA(θ) is a marker for photochemistry dynamics models attempting to represent ozone change over the past 42 years.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
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We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Tim A. van Kempen, Tim J. Rotmans, Richard M. van Hees, Carol Bruegge, Dejian Fu, Ruud Hoogeveen, Thomas J. Pongetti, Robert Rosenberg, and Ilse Aben
Atmos. Meas. Tech., 16, 4507–4527, https://doi.org/10.5194/amt-16-4507-2023, https://doi.org/10.5194/amt-16-4507-2023, 2023
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Validation of satellite measurements is essential for providing reliable and consistent products. In this paper, a validation method for TROPOMI-SWIR (Tropospheric Measurement Instrument in the short-wavelength infrared) is explored. TROPOMI-SWIR has been shown to be exceptionally stable, a necessity to explore the methodology. Railroad Valley, Nevada, is a prime location to perform the necessary measurements to validate the satellite measurements of TROPOMI-SWIR.
Ouyang Liu, Zhengqiang Li, Yangyan Lin, Cheng Fan, Ying Zhang, Kaitao Li, Peng Zhang, Yuanyuan Wei, Tianzeng Chen, Jiantao Dong, and Gerrit de Leeuw
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-177, https://doi.org/10.5194/amt-2023-177, 2023
Revised manuscript accepted for AMT
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Nitrogen dioxide (NO2) is a trace gas which is important for atmospheric chemistry and may affect human health. To understand processes leading to harmful concentrations, it is important to monitor NO2 concentrations near the surface and higher up. To this end, a Pandora instrument has been installed in Beijing. An overview of the first year of data shows the large variability on diurnal to seasonal time scales and how this is affected by wind speed and direction and chemistry.
Serin Kim, Daewon Kim, Hyunkee Hong, Lim-Seok Chang, Hanlim Lee, Deok-Rae Kim, Donghee Kim, Jeong-Ah Yu, Dongwon Lee, Ukkyo Jeong, Chang-Kuen Song, Sang-Woo Kim, Sang Seo Park, Jhoon Kim, Thomas F. Hanisco, Junsung Park, Wonei Choi, and Kwangyul Lee
Atmos. Meas. Tech., 16, 3959–3972, https://doi.org/10.5194/amt-16-3959-2023, https://doi.org/10.5194/amt-16-3959-2023, 2023
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A first evaluation of the Geostationary Environmental Monitoring Spectrometer (GEMS) NO2 was carried out via comparison with the NO2 data obtained from the ground-based Pandora direct-sun measurements at four sites in Seosan, Republic of Korea. Comparisons between GEMS NO2 and Pandora NO2 were performed according to GEMS cloud fraction. GEMS NO2 showed good agreement with that of Pandora NO2 under less cloudy conditions.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Alana Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew Thorpe, and Riley Duren
EGUsphere, https://doi.org/10.5194/egusphere-2023-1420, https://doi.org/10.5194/egusphere-2023-1420, 2023
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Methane is a powerful greenhouse gas and a significant portion of methane comes from large individual plumes. Recently, airplane mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image there are two widely used approaches, in this study we assess the performance of both approaches using controlled release experiments. We also examine the minimum detection limit of the infrared technology.
Evan Sherwin, Sahar El Abbadi, Philippine Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey Rutherford, Yuanlei Chen, and Adam Brandt
EGUsphere, https://doi.org/10.31223/X56089, https://doi.org/10.31223/X56089, 2023
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Satellites measurements of climate-warming methane emissions at oil and natural gas facilities could facilitate major international methane reduction efforts, but doing so requires trust from many international stakeholders. To test nine methane-sensing satellite systems, we released undisclosed quantities of methane, which multiple teams successfully detected and quantified. We show that Europe, Asia, and North America all host reliable methane-sensing satellites.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Lena Katharina Jänicke, Rene Preusker, Marco Celesti, Marin Tudoroiu, Jürgen Fischer, Dirk Schüttemeyer, and Matthias Drusch
Atmos. Meas. Tech., 16, 3101–3121, https://doi.org/10.5194/amt-16-3101-2023, https://doi.org/10.5194/amt-16-3101-2023, 2023
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To compare two top-of-atmosphere radiances measured by instruments with different spectral characteristics, a transfer function has been developed. It is applied to a tandem data set of Sentinel-3A and B, for which OLCI-B mimicked the ESA’s eighth Earth Explorer FLEX. We found that OLCI-A measured radiances about 2 % brighter than OLCI-FLEX. Only at larger wavelengths were OLCI-A measurements about 5 % darker. The method is thus successful, being sensitive to calibration and processing issues.
Luis F. Millán, Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, Irina Petropavlovskikh, Kaley Walker, Krzysztof Wargan, and Andreas Zahn
Atmos. Meas. Tech., 16, 2957–2988, https://doi.org/10.5194/amt-16-2957-2023, https://doi.org/10.5194/amt-16-2957-2023, 2023
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The determination of atmospheric composition trends in the upper troposphere and lower stratosphere (UTLS) is still highly uncertain. We present the creation of dynamical diagnostics to map several ozone datasets (ozonesondes, lidars, aircraft, and satellite measurements) in geophysically based coordinate systems. The diagnostics can also be used to analyze other greenhouse gases relevant to surface climate and UTLS chemistry.
Zhihua Zhang, Jianguo Niu, Lawrence E. Flynn, Eric Beach, and Trevor Beck
Atmos. Meas. Tech., 16, 2919–2941, https://doi.org/10.5194/amt-16-2919-2023, https://doi.org/10.5194/amt-16-2919-2023, 2023
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This study mainly focused on addressing stability and improvement when using a broadband approach, establishing soft-calibration adjustments for both OMPS S-NPP and N20, analyzing error biases based on multi-sensor bias correction, and comparing total column ozone and aerosol index retrievals from NOAA OMPS with those from other products.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly V. Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
EGUsphere, https://doi.org/10.5194/egusphere-2023-822, https://doi.org/10.5194/egusphere-2023-822, 2023
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021. Results from our two independent quantification methods suggest the accuracy of our framework is better than 25 % for sources emitting 200 kg/hr or more. Insights gained from these experiments help refine algorithms for our instruments, further strengthening the capabilities of our instruments.
Matthew S. Johnson, Amir H. Souri, Sajeev Philip, Rajesh Kumar, Aaron Naeger, Jeffrey Geddes, Laura Judd, Scott Janz, Heesung Chong, and John Sullivan
Atmos. Meas. Tech., 16, 2431–2454, https://doi.org/10.5194/amt-16-2431-2023, https://doi.org/10.5194/amt-16-2431-2023, 2023
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Satellites provide vital information for studying the processes controlling ozone formation. Based on the abundance of particular gases in the atmosphere, ozone formation is sensitive to specific human-induced and natural emission sources. However, errors and biases in satellite retrievals hinder this data source’s application for studying ozone formation sensitivity. We conducted a thorough statistical evaluation of two commonly applied satellites for investigating ozone formation sensitivity.
Kezia Lange, Andreas Richter, Anja Schönhardt, Andreas C. Meier, Tim Bösch, André Seyler, Kai Krause, Lisa K. Behrens, Folkard Wittrock, Alexis Merlaud, Frederik Tack, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Vinod Kumar, Sebastian Donner, Steffen Dörner, Bianca Lauster, Maria Razi, Christian Borger, Katharina Uhlmannsiek, Thomas Wagner, Thomas Ruhtz, Henk Eskes, Birger Bohn, Daniel Santana Diaz, Nader Abuhassan, Dirk Schüttemeyer, and John P. Burrows
Atmos. Meas. Tech., 16, 1357–1389, https://doi.org/10.5194/amt-16-1357-2023, https://doi.org/10.5194/amt-16-1357-2023, 2023
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We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted during the S5P-VAL-DE-Ruhr campaign in the Rhine-Ruhr region. The measurements are used to validate spaceborne NO2 data products from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). Auxiliary data of the TROPOMI NO2 retrieval, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity, and cloud treatment are investigated to evaluate their impact.
Yolanda Maria Lemes, Christoph Häni, Jesper Nørlem Kamp, and Anders Feilberg
Atmos. Meas. Tech., 16, 1295–1309, https://doi.org/10.5194/amt-16-1295-2023, https://doi.org/10.5194/amt-16-1295-2023, 2023
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The implementation of a new method, line-averaged concentration measurement with a closed-path analyzer, will enable the measurement of fluxes of multiple gases from different types of sources and will evaluate the effects of mitigation strategies on emissions. In addition, this method allows for continuous online measurements that resolve temporal variation in ammonia emissions and the peak emissions of methane.
Prajjwal Rawat, Manish Naja, Evan Fishbein, Pradeep K. Thapliyal, Rajesh Kumar, Piyush Bhardwaj, Aditya Jaiswal, Sugriva N. Tiwari, Sethuraman Venkataramani, and Shyam Lal
Atmos. Meas. Tech., 16, 889–909, https://doi.org/10.5194/amt-16-889-2023, https://doi.org/10.5194/amt-16-889-2023, 2023
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Satellite-based ozone observations have gained importance due to their global coverage. However, satellite-retrieved products are indirect and need to be validated, particularly over mountains. Ozonesondes launched from a Himalayan site are used to assess the Atmospheric Infrared Sounder (AIRS) ozone retrieval. AIRS is shown to overestimate ozone in the upper troposphere and lower stratosphere, while the differences from ozonesondes are more minor in the middle troposphere and stratosphere.
Karen Elena Cady-Pereira, Xuehui Guo, Rui Wang, April Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin H. Kantchev
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-336, https://doi.org/10.5194/amt-2022-336, 2023
Revised manuscript accepted for AMT
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Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are significant differences, which can be explained mainly by different vertical and horizontal sampling scales.
Murali Natarajan, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 16, 75–87, https://doi.org/10.5194/amt-16-75-2023, https://doi.org/10.5194/amt-16-75-2023, 2023
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Photochemically induced changes in mesospheric O3 concentration at twilight can cause asymmetry in the distribution along the line of sight of solar occultation observations that must be considered in the retrieval algorithm. Correction factors developed from diurnal photochemical model simulations were used to modify the archived SAGE III/ISS mesospheric O3 concentrations. For June 2021 the bias caused by the neglect of diurnal variations is over 30% at 64 km altitude and low latitudes.
Javier Gorroño, Daniel J. Varon, Itziar Irakulis-Loitxate, and Luis Guanter
Atmos. Meas. Tech., 16, 89–107, https://doi.org/10.5194/amt-16-89-2023, https://doi.org/10.5194/amt-16-89-2023, 2023
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We present a methane flux rate retrieval methodology using the Sentinel-2 mission, validating the algorithm for different scenes and plumes. The detection limit is 1000–2000 kg h−1 for homogeneous scenes and temporally invariant surfaces and above 5000 kg h−1 for heterogeneous ones. Dominant quantification errors are wind-related or plume mask-related. For heterogeneous scenes, the surface structure underlying the methane plume can become a dominant source of uncertainty.
Katerina Garane, Ka Lok Chan, Maria-Elissavet Koukouli, Diego Loyola, and Dimitris Balis
Atmos. Meas. Tech., 16, 57–74, https://doi.org/10.5194/amt-16-57-2023, https://doi.org/10.5194/amt-16-57-2023, 2023
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In this work, 2.5 years of TROPOMI/S5P Total Column Water Vapor (TCWV) observations retrieved from the blue wavelength band are validated against co-located precipitable water measurements from NASA AERONET, which uses Cimel Sun photometers globally. Overall, the TCWV product agrees well on a global scale with the ground-based dataset (Pearson correl. coefficient 0.909) and has a mean relative bias of −2.7 ± 4.9 % with respect to the AERONET observations for moderate albedo and cloudiness.
Lei Shi, Carl J. Schreck III, Viju O. John, Eui-Seok Chung, Theresa Lang, Stefan A. Buehler, and Brian J. Soden
Atmos. Meas. Tech., 15, 6949–6963, https://doi.org/10.5194/amt-15-6949-2022, https://doi.org/10.5194/amt-15-6949-2022, 2022
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Four upper tropospheric humidity (UTH) datasets derived from satellite microwave and infrared sounders are evaluated to assess their consistency as part of the activities for the Global Energy and Water Exchanges (GEWEX) water vapor assessment project. The study shows that the four datasets are consistent in the interannual temporal and spatial variability of the tropics. However, differences are found in the magnitudes of the anomalies and in the changing rates during the common period.
Ali Jalali, Kaley A. Walker, Kimberly Strong, Rebecca R. Buchholz, Merritt N. Deeter, Debra Wunch, Sébastien Roche, Tyler Wizenberg, Erik Lutsch, Erin McGee, Helen M. Worden, Pierre Fogal, and James R. Drummond
Atmos. Meas. Tech., 15, 6837–6863, https://doi.org/10.5194/amt-15-6837-2022, https://doi.org/10.5194/amt-15-6837-2022, 2022
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This study validates MOPITT version 8 carbon monoxide measurements over the Canadian high Arctic for the period 2006 to 2019. The MOPITT products from different detector pixels and channels are compared with ground-based measurements from the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada. These results show good consistency between the satellite and ground-based measurements and provide guidance on the usage of these MOPITT data at high latitudes.
Gerald Wetzel, Michael Höpfner, Hermann Oelhaf, Felix Friedl-Vallon, Anne Kleinert, Guido Maucher, Miriam Sinnhuber, Janna Abalichin, Angelika Dehn, and Piera Raspollini
Atmos. Meas. Tech., 15, 6669–6704, https://doi.org/10.5194/amt-15-6669-2022, https://doi.org/10.5194/amt-15-6669-2022, 2022
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Satellite measurements of stratospheric trace gases are essential for monitoring distributions and trends of these species on a global scale. Here, we compare the final MIPAS ESA Level 2 version 8 data (temperature and trace gases) with measurements obtained with the balloon version of MIPAS in terms of data agreement of both sensors, including combined errors. For most gases, we find a 5 % to 20 % agreement of the retrieved vertical profiles of both MIPAS instruments in the lower stratosphere.
Maximilian Rißmann, Jia Chen, Gregory Osterman, Xinxu Zhao, Florian Dietrich, Moritz Makowski, Frank Hase, and Matthäus Kiel
Atmos. Meas. Tech., 15, 6605–6623, https://doi.org/10.5194/amt-15-6605-2022, https://doi.org/10.5194/amt-15-6605-2022, 2022
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The Orbiting Carbon Observatory 2 (OCO-2) measures atmospheric concentrations of the most potent greenhouse gas, CO2, globally. By comparing its measurements to a ground-based monitoring network in Munich (MUCCnet), we find that the satellite is able to reliably detect urban CO2 concentrations. Furthermore, spatial CO2 differences captured by OCO-2 and MUCCnet are strongly correlated, which indicates that OCO-2 could be helpful in determining urban CO2 emissions from space.
Sarah A. Strode, Ghassan Taha, Luke D. Oman, Robert Damadeo, David Flittner, Mark Schoeberl, Christopher E. Sioris, and Ryan Stauffer
Atmos. Meas. Tech., 15, 6145–6161, https://doi.org/10.5194/amt-15-6145-2022, https://doi.org/10.5194/amt-15-6145-2022, 2022
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We use a global atmospheric chemistry model simulation to generate scaling factors that account for the daily cycle of NO2 and ozone. These factors facilitate comparisons between sunrise and sunset observations from SAGE III/ISS and observations from other instruments. We provide the scaling factors as monthly zonal means for different latitudes and altitudes. We find that applying these factors yields more consistent comparisons between observations from SAGE III/ISS and other instruments.
Kimberlee Dubé, Daniel Zawada, Adam Bourassa, Doug Degenstein, William Randel, David Flittner, Patrick Sheese, and Kaley Walker
Atmos. Meas. Tech., 15, 6163–6180, https://doi.org/10.5194/amt-15-6163-2022, https://doi.org/10.5194/amt-15-6163-2022, 2022
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Satellite observations are important for monitoring changes in atmospheric composition. Here we describe an improved version of the NO2 retrieval for the Optical Spectrograph and InfraRed Imager System. The resulting NO2 profiles are compared to those from the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer and the Stratospheric Aerosol and Gas Experiment III on the International Space Station. All datasets agree within 20 % throughout the stratosphere.
Helen M. Worden, Gene L. Francis, Susan S. Kulawik, Kevin W. Bowman, Karen Cady-Pereira, Dejian Fu, Jennifer D. Hegarty, Valentin Kantchev, Ming Luo, Vivienne H. Payne, John R. Worden, Róisín Commane, and Kathryn McKain
Atmos. Meas. Tech., 15, 5383–5398, https://doi.org/10.5194/amt-15-5383-2022, https://doi.org/10.5194/amt-15-5383-2022, 2022
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Satellite observations of global carbon monoxide (CO) are essential for understanding atmospheric chemistry and pollution sources. This paper describes a new data product using radiance measurements from the Cross-track Infrared Sounder (CrIS) instrument on the Suomi National Polar-orbiting Partnership (SNPP) satellite that provides vertical profiles of CO from single-field-of-view observations. We show how these satellite CO profiles compare to aircraft observations and evaluate their biases.
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.
Sara Martínez-Alonso, Merritt N. Deeter, Bianca C. Baier, Kathryn McKain, Helen Worden, Tobias Borsdorff, Colm Sweeney, and Ilse Aben
Atmos. Meas. Tech., 15, 4751–4765, https://doi.org/10.5194/amt-15-4751-2022, https://doi.org/10.5194/amt-15-4751-2022, 2022
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AirCore is a novel balloon sampling system that can measure, among others, vertical profiles of carbon monoxide (CO) from 25–30 km of altitude to near the surface. Our analyses of AirCore and satellite CO data show that AirCore profiles are suited for satellite data validation, the use of shorter aircraft vertical profiles in satellite validation results in small errors (1–3 percent points) mostly at 300 hPa and above, and the error introduced by clouds in TROPOMI land data is small (1–2 %).
Ermioni Dimitropoulou, François Hendrick, Martina Michaela Friedrich, Frederik Tack, Gaia Pinardi, Alexis Merlaud, Caroline Fayt, Christian Hermans, Frans Fierens, and Michel Van Roozendael
Atmos. Meas. Tech., 15, 4503–4529, https://doi.org/10.5194/amt-15-4503-2022, https://doi.org/10.5194/amt-15-4503-2022, 2022
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A total of 2 years of dual-scan ground-based MAX-DOAS measurements of tropospheric NO2 and aerosols in Uccle (Belgium) have been used to develop a new optimal-estimation-based inversion approach to retrieve horizontal profiles of surface NO2 concentration and aerosol extinction profiles. We show that the combination of an appropriate sampling of TROPOMI pixels by ground-based measurements and an adequate a priori NO2 profile shape in TROPOMI retrievals improves the agreement between datasets.
Jonas Hachmeister, Oliver Schneising, Michael Buchwitz, Alba Lorente, Tobias Borsdorff, John P. Burrows, Justus Notholt, and Matthias Buschmann
Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, https://doi.org/10.5194/amt-15-4063-2022, 2022
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Sentinel-5P trace gas retrievals rely on elevation data in their calculations. Outdated or inaccurate data can lead to significant errors in e.g. dry-air mole fractions of methane (XCH4). We show that the use of inadequate elevation data leads to strong XCH4 anomalies in Greenland. Similar problems can be expected for other regions with inaccurate elevation data. However, we expect these to be more localized. We show that updating elevation data used in the retrieval solves this issue.
Vivienne H. Payne, Susan S. Kulawik, Emily V. Fischer, Jared F. Brewer, L. Gregory Huey, Kazuyuki Miyazaki, John R. Worden, Kevin W. Bowman, Eric J. Hintsa, Fred Moore, James W. Elkins, and Julieta Juncosa Calahorrano
Atmos. Meas. Tech., 15, 3497–3511, https://doi.org/10.5194/amt-15-3497-2022, https://doi.org/10.5194/amt-15-3497-2022, 2022
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We compare new satellite measurements of peroxyacetyl nitrate (PAN) with reference aircraft measurements from two different instruments flown on the same platform. While there is a systematic difference between the two aircraft datasets, both show the same large-scale distribution of PAN and the discrepancy between aircraft datasets is small compared to the satellite uncertainties. The satellite measurements show skill in capturing large-scale variations in PAN.
William G. Read, Gabriele Stiller, Stefan Lossow, Michael Kiefer, Farahnaz Khosrawi, Dale Hurst, Holger Vömel, Karen Rosenlof, Bianca M. Dinelli, Piera Raspollini, Gerald E. Nedoluha, John C. Gille, Yasuko Kasai, Patrick Eriksson, Christopher E. Sioris, Kaley A. Walker, Katja Weigel, John P. Burrows, and Alexei Rozanov
Atmos. Meas. Tech., 15, 3377–3400, https://doi.org/10.5194/amt-15-3377-2022, https://doi.org/10.5194/amt-15-3377-2022, 2022
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This paper attempts to provide an assessment of the accuracy of 21 satellite-based instruments that remotely measure atmospheric humidity in the upper troposphere of the Earth's atmosphere. The instruments made their measurements from 1984 to the present time; however, most of these instruments began operations after 2000, and only a few are still operational. The objective of this study is to quantify the accuracy of each satellite humidity data set.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Andreas Richter, Pieter Valks, Ramina Alwarda, Kristof Bognar, Udo Frieß, José Granville, Myojeong Gu, Paul Johnston, Cristina Prados-Roman, Richard Querel, Kimberly Strong, Thomas Wagner, Folkard Wittrock, and Margarita Yela Gonzalez
Atmos. Meas. Tech., 15, 3439–3463, https://doi.org/10.5194/amt-15-3439-2022, https://doi.org/10.5194/amt-15-3439-2022, 2022
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We report on the GOME-2A and GOME-2B OClO dataset (2007 to 2016, from the EUMETSAT's AC SAF) validation using data from nine NDACC zenith-scattered-light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Specific sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings and their typical errors. Good agreement is found for both the inter-annual variability and the overall OClO seasonal behavior.
Alexandra Laeng, Thomas von Clarmann, Quentin Errera, Udo Grabowski, and Shawn Honomichl
Atmos. Meas. Tech., 15, 2407–2416, https://doi.org/10.5194/amt-15-2407-2022, https://doi.org/10.5194/amt-15-2407-2022, 2022
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In validation exercises, a universal excuse used to explain the residual discrepancy between the data is the natural atmospheric variability due to imperfect co-locations. This work is the first attempt to quantify this atmospheric variability for a large sample of atmospheric constituents and to provide the user with a tool to substract the natural atmospheric variability portion from the residual variability.
Carlos Alberti, Qiansi Tu, Frank Hase, Maria V. Makarova, Konstantin Gribanov, Stefani C. Foka, Vyacheslav Zakharov, Thomas Blumenstock, Michael Buchwitz, Christopher Diekmann, Benjamin Ertl, Matthias M. Frey, Hamud Kh. Imhasin, Dmitry V. Ionov, Farahnaz Khosrawi, Sergey I. Osipov, Maximilian Reuter, Matthias Schneider, and Thorsten Warneke
Atmos. Meas. Tech., 15, 2199–2229, https://doi.org/10.5194/amt-15-2199-2022, https://doi.org/10.5194/amt-15-2199-2022, 2022
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Satellite and ground-based observations at high latitudes are much sparser than at low or mid latitudes, which makes direct coincident comparisons between remote-sensing observations more difficult. Therefore, a method of scaling continuous CAMS model data to the ground-based observations is developed and used for creating virtual COCCON observations. These adjusted CAMS data are then used for satellite inter-comparison, showing good agreement in both Peterhof and Yekaterinburg cities.
Takashi Sekiya, Kazuyuki Miyazaki, Henk Eskes, Kengo Sudo, Masayuki Takigawa, and Yugo Kanaya
Atmos. Meas. Tech., 15, 1703–1728, https://doi.org/10.5194/amt-15-1703-2022, https://doi.org/10.5194/amt-15-1703-2022, 2022
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This study gives a systematic comparison of TROPOMI version 1.2 and OMI QA4ECV tropospheric NO2 column through global chemical data assimilation (DA) integration for April–May 2018. DA performance is controlled by measurement sensitivities, retrieval errors, and coverage. Due to reduced errors in TROPOMI, agreements against assimilated and independent observations were improved by TROPOMI DA compared to OMI DA. These results demonstrate that TROPOMI DA improves global analyses of NO2 and ozone.
Claudia Emde, Huan Yu, Arve Kylling, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer
Atmos. Meas. Tech., 15, 1587–1608, https://doi.org/10.5194/amt-15-1587-2022, https://doi.org/10.5194/amt-15-1587-2022, 2022
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Retrievals of trace gas concentrations from satellite observations can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. We used a Monte Carlo radiative transfer model to generate synthetic satellite observations, which we used to test retrieval algorithms and to quantify the error of retrieved NO2 vertical column density due to cloud scattering.
Ellis Remsberg, Murali Natarajan, and Ernest Hilsenrath
Atmos. Meas. Tech., 15, 1521–1535, https://doi.org/10.5194/amt-15-1521-2022, https://doi.org/10.5194/amt-15-1521-2022, 2022
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Ozone (O3) is an excellent tracer of atmospheric transport processes in the middle atmosphere during Arctic winter. The Nimbus 7 LIMS O3 profiles of late October 1978 through May 1979 now extend to the upper mesosphere via its Version 6 (V6) algorithm. We describe the generation of zonal Fourier coefficients from the profiles, followed by their gridding to daily synoptic maps of O3. We then present several examples of how V6 O3 varies in the upper stratosphere and mesosphere during winter.
Dimitris Karagkiozidis, Martina Michaela Friedrich, Steffen Beirle, Alkiviadis Bais, François Hendrick, Kalliopi Artemis Voudouri, Ilias Fountoulakis, Angelos Karanikolas, Paraskevi Tzoumaka, Michel Van Roozendael, Dimitris Balis, and Thomas Wagner
Atmos. Meas. Tech., 15, 1269–1301, https://doi.org/10.5194/amt-15-1269-2022, https://doi.org/10.5194/amt-15-1269-2022, 2022
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In this study we focus on the retrieval of aerosol, NO2, and HCHO vertical profiles from multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations for the first time over Thessaloniki, Greece. We use two independent inversion algorithms for the profile retrievals. We evaluate their performance, we intercompare their results, and we validate their products with ancillary data, measured by other co-located reference instruments.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Adam E. Bourassa, Doug A. Degenstein, Lucien Froidevaux, C. Thomas McElroy, Donal Murtagh, James M. Russell III, and Jiansheng Zou
Atmos. Meas. Tech., 15, 1233–1249, https://doi.org/10.5194/amt-15-1233-2022, https://doi.org/10.5194/amt-15-1233-2022, 2022
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This study analyzes the quality of two versions (v3.6 and v4.1) of ozone concentration measurements from the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), by comparing with data from five satellite instruments between 2004 and 2020. It was found that although the v3.6 data exhibit a better agreement than v4.1 with respect to the other instruments, v4.1 exhibits much better stability over time than v3.6. The stability of v4.1 makes it suitable for ozone trend studies.
Jennifer D. Hegarty, Karen E. Cady-Pereira, Vivienne H. Payne, Susan S. Kulawik, John R. Worden, Valentin Kantchev, Helen M. Worden, Kathryn McKain, Jasna V. Pittman, Róisín Commane, Bruce C. Daube Jr., and Eric A. Kort
Atmos. Meas. Tech., 15, 205–223, https://doi.org/10.5194/amt-15-205-2022, https://doi.org/10.5194/amt-15-205-2022, 2022
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Carbon monoxide (CO) is produced by combustion of substances such as fossil fuels and plays an important role in atmospheric pollution and climate. We evaluated estimates of atmospheric CO derived from outgoing radiation measurements of the Atmospheric Infrared Sounder (AIRS) on a satellite orbiting the Earth against CO measurements from aircraft to show that these satellite measurements are reliable for continuous global monitoring of atmospheric CO concentrations.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
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The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
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Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
Atmos. Meas. Tech., 14, 7707–7728, https://doi.org/10.5194/amt-14-7707-2021, https://doi.org/10.5194/amt-14-7707-2021, 2021
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CO is an important atmospheric gas that influences both air quality and the climate. Here, we compare CO measurements from TROPOMI with those from ACE-FTS and an Arctic ground-based FTS at Eureka, Nunavut, to further characterize the accuracy of TROPOMI measurements. CO columns from the instruments agree well but show larger differences at high latitudes. Despite this, the results fall within the TROPOMI accuracy target, indicating good data quality at high latitudes.
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Short summary
Satellite methods allow biomass burning emissions to be accurately quantified with high spatial and temporal resolution. With that ultimate goal, we analyze satellite retrievals of carbon monoxide from the MOPITT instrument over the Amazon Basin. Validation results for four Amazonian sites indicate a significant negative bias in retrieved lower-tropospheric CO concentrations. The interannual variability of biomass burning emissions from 2000 to 2015 is also studied using the MOPITT record.
Satellite methods allow biomass burning emissions to be accurately quantified with high spatial...
