Articles | Volume 3, issue 5
https://doi.org/10.5194/amt-3-1351-2010
© Author(s) 2010. 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-3-1351-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
06 Oct 2010
Research article |
| 06 Oct 2010
Calibration of the Total Carbon Column Observing Network using aircraft profile data
D. Wunch
California Institute of Technology, Pasadena, CA, USA
G. C. Toon
California Institute of Technology, Pasadena, CA, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
P. O. Wennberg
California Institute of Technology, Pasadena, CA, USA
S. C. Wofsy
Harvard University, Cambridge, MA, USA
B. B. Stephens
National Center for Atmospheric Research, Boulder, CO, USA
M. L. Fischer
Lawrence Berkeley National Laboratories, Berkeley, CA, USA
O. Uchino
National Insitute for Environmental Studies, Tsukuba, Japan
J. B. Abshire
NASA Goddard Space Flight Center, Greenbelt, MD, USA
P. Bernath
University of Waterloo, Waterloo, ON, Canada
York University, York, UK
S. C. Biraud
Lawrence Berkeley National Laboratories, Berkeley, CA, USA
J.-F. L. Blavier
California Institute of Technology, Pasadena, CA, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
C. Boone
University of Waterloo, Waterloo, ON, Canada
K. P. Bowman
Texas A&M University, College Station, TX, USA
E. V. Browell
NASA Langley Research Center, Hampton, VA, USA
T. Campos
National Center for Atmospheric Research, Boulder, CO, USA
B. J. Connor
BC Consulting Limited, Alexandra, New Zealand
B. C. Daube
Harvard University, Cambridge, MA, USA
N. M. Deutscher
Center for Atmospheric Chemistry, University of Wollongong, Wollongong, NSW, Australia
M. Diao
Princeton University, Princeton, NJ, USA
J. W. Elkins
National Oceanic and Atmospheric Administration, Boulder, CO, USA
C. Gerbig
Max-Planck-Institut für Biogeochemie, Jena, Germany
E. Gottlieb
Harvard University, Cambridge, MA, USA
D. W. T. Griffith
Center for Atmospheric Chemistry, University of Wollongong, Wollongong, NSW, Australia
D. F. Hurst
National Oceanic and Atmospheric Administration, Boulder, CO, USA
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
R. Jiménez
Harvard University, Cambridge, MA, USA
Department of Chemical and Enivronmental Engineering, Universidad Nacional de Colombia, Bogota, DC 111321, Colombia
G. Keppel-Aleks
California Institute of Technology, Pasadena, CA, USA
E. A. Kort
Harvard University, Cambridge, MA, USA
R. Macatangay
Center for Atmospheric Chemistry, University of Wollongong, Wollongong, NSW, Australia
T. Machida
National Insitute for Environmental Studies, Tsukuba, Japan
H. Matsueda
Meteorological Research Institute, Tsukuba, Japan
F. Moore
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
I. Morino
National Insitute for Environmental Studies, Tsukuba, Japan
S. Park
Harvard University, Cambridge, MA, USA
J. Robinson
National Institute of Water & Atmospheric Research, Lauder, New Zealand
C. M. Roehl
California Institute of Technology, Pasadena, CA, USA
Y. Sawa
Meteorological Research Institute, Tsukuba, Japan
V. Sherlock
National Institute of Water & Atmospheric Research, Wellington, New Zealand
C. Sweeney
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
T. Tanaka
National Insitute for Environmental Studies, Tsukuba, Japan
M. A. Zondlo
Princeton University, Princeton, NJ, USA
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Performance of AIRS ozone retrieval over the central Himalayas: use of ozonesonde and other satellite datasets
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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
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging, ground-based stationary, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
TROPESS/CrIS carbon monoxide profile validation with NOAA GML and ATom in situ aircraft observations
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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
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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
Assessing the feasibility of using a neural network to filter Orbiting Carbon Observatory 2 (OCO-2) retrievals at northern high latitudes
TROPOMI tropospheric ozone column data: geophysical assessment and comparison to ozonesondes, GOME-2B and OMI
Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations
Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO2 measurements
Total ozone column intercomparison of Brewers, Dobsons, and BTS-Solar at Hohenpeißenberg and Davos in 2019/2020
A systematic assessment of water vapor products in the Arctic: from instantaneous measurements to monthly means
Quality assessment of Dobson spectrophotometers for ozone column measurements before and after automation at Arosa and Davos
Systematic comparison of vectorial spherical radiative transfer models in limb scattering geometry
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The world Brewer reference triad – updated performance assessment and new double triad
Intercomparison of arctic XH2O observations from three ground-based Fourier transform infrared networks and application for satellite validation
Verification of the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS) ozone algorithms based on retrieved daytime and night-time ozone
Intercomparison of Total Carbon Column Observing Network (TCCON) data from two Fourier transform spectrometers at Lauder, New Zealand
Model estimations of geophysical variability between satellite measurements of ozone profiles
Multiscale observations of NH3 around Toronto, Canada
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Formaldehyde total column densities over Mexico City: comparison between multi-axis differential optical absorption spectroscopy and solar-absorption Fourier transform infrared measurements
Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks
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.
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.
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. Discuss., https://doi.org/10.5194/amt-2022-264, https://doi.org/10.5194/amt-2022-264, 2022
Revised manuscript accepted for AMT
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We present airborne imaging DOAS, 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 space-borne 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 the cloud treatment are investigated to evaluate their impact.
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.
Yolanda Maria Lemes, Christoph Häni, Jesper Nørlem Kamp, and Anders Feilberg
EGUsphere, https://doi.org/10.5194/egusphere-2022-867, https://doi.org/10.5194/egusphere-2022-867, 2022
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The implementation of the new method, line-average concentration measurement with a closed-path analyzer, will enable measurement of fluxes of multiple gases from different types of sources and 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.
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.
Joseph Mendonca, Ray Nassar, Christopher W. O'Dell, Rigel Kivi, Isamu Morino, Justus Notholt, Christof Petri, Kimberly Strong, and Debra Wunch
Atmos. Meas. Tech., 14, 7511–7524, https://doi.org/10.5194/amt-14-7511-2021, https://doi.org/10.5194/amt-14-7511-2021, 2021
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Machine learning has become an important tool for pattern recognition in many applications. In this study, we used a neural network to improve the data quality of OCO-2 measurements made at northern high latitudes. The neural network was trained and used as a binary classifier to filter out bad OCO-2 measurements in order to increase the accuracy and precision of OCO-2 XCO2 measurements in the Boreal and Arctic regions.
Daan Hubert, Klaus-Peter Heue, Jean-Christopher Lambert, Tijl Verhoelst, Marc Allaart, Steven Compernolle, Patrick D. Cullis, Angelika Dehn, Christian Félix, Bryan J. Johnson, Arno Keppens, Debra E. Kollonige, Christophe Lerot, Diego Loyola, Matakite Maata, Sukarni Mitro, Maznorizan Mohamad, Ankie Piters, Fabian Romahn, Henry B. Selkirk, Francisco R. da Silva, Ryan M. Stauffer, Anne M. Thompson, J. Pepijn Veefkind, Holger Vömel, Jacquelyn C. Witte, and Claus Zehner
Atmos. Meas. Tech., 14, 7405–7433, https://doi.org/10.5194/amt-14-7405-2021, https://doi.org/10.5194/amt-14-7405-2021, 2021
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We assess the first 2 years of TROPOMI tropical tropospheric ozone column data. Comparisons to reference measurements by ozonesonde and satellite sensors show that TROPOMI bias (−0.1 to +2.3 DU) and precision (1.5 to 2.5 DU) meet mission requirements. Potential causes of bias and its spatio-temporal structure are discussed, as well as ways to identify sampling errors. Our analysis of known geophysical patterns demonstrates the improved performance of TROPOMI with respect to its predecessors.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
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This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
Vinod Kumar, Julia Remmers, Steffen Beirle, Joachim Fallmann, Astrid Kerkweg, Jos Lelieveld, Mariano Mertens, Andrea Pozzer, Benedikt Steil, Marc Barra, Holger Tost, and Thomas Wagner
Atmos. Meas. Tech., 14, 5241–5269, https://doi.org/10.5194/amt-14-5241-2021, https://doi.org/10.5194/amt-14-5241-2021, 2021
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We present high-resolution regional atmospheric chemistry model simulations focused around Germany. We highlight the importance of spatial resolution of the model itself as well as the input emissions inventory and short-scale temporal variability of emissions for simulations. We propose a consistent approach for evaluating the simulated vertical distribution of NO2 using MAX-DOAS measurements while also considering its spatial sensitivity volume and change in sensitivity within this volume.
Ralf Zuber, Ulf Köhler, Luca Egli, Mario Ribnitzky, Wolfgang Steinbrecht, and Julian Gröbner
Atmos. Meas. Tech., 14, 4915–4928, https://doi.org/10.5194/amt-14-4915-2021, https://doi.org/10.5194/amt-14-4915-2021, 2021
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We validated two BTS-based systems in a longer-term TOC analysis in the 2019/2020 campaign at Hohenpeißenberg and Davos. The results showed a deviation of the BTS-Solar to Brewers of < 0.1 % with a k = 2 of < 1.5 %. Koherent showed a deviation of 1.7 % with a k = 2 of 2.7 %. Resultingly, the BTS-Solar performance is comparable to Brewers in Hohenpeißenberg. Koherent shows a seasonal variation in Davos due to the sensitivity of its TOC retrieval algorithm to stratospheric temperature.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
René Stübi, Herbert Schill, Eliane Maillard Barras, Jörg Klausen, and Alexander Haefele
Atmos. Meas. Tech., 14, 4203–4217, https://doi.org/10.5194/amt-14-4203-2021, https://doi.org/10.5194/amt-14-4203-2021, 2021
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Total ozone column has been measured since 1926 in the Swiss Alps station Arosa. These worldwide series are based on Dobson sun spectrophotometers. To assure the continuity of these series, a two-stage project was realized at MeteoSwiss: first, Dobson instruments were automated, and then parallel measurements between Arosa and a nearby site in Davos were carried out. The analysis of the data of the manual-to-automated transition and coincident data between the two sites are presented here.
Daniel Zawada, Ghislain Franssens, Robert Loughman, Antti Mikkonen, Alexei Rozanov, Claudia Emde, Adam Bourassa, Seth Dueck, Hannakaisa Lindqvist, Didier Ramon, Vladimir Rozanov, Emmanuel Dekemper, Erkki Kyrölä, John P. Burrows, Didier Fussen, and Doug Degenstein
Atmos. Meas. Tech., 14, 3953–3972, https://doi.org/10.5194/amt-14-3953-2021, https://doi.org/10.5194/amt-14-3953-2021, 2021
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Satellite measurements of atmospheric composition often rely on computer tools known as radiative transfer models to model the propagation of sunlight within the atmosphere. Here we have performed a detailed inter-comparison of seven different radiative transfer models in a variety of conditions. We have found that the models agree remarkably well, at a level better than previously reported. This result provides confidence in our understanding of atmospheric radiative transfer.
Robin Wing, Sophie Godin-Beekmann, Wolfgang Steinbrecht, Thomas J. McGee, John T. Sullivan, Sergey Khaykin, Grant Sumnicht, and Laurence Twigg
Atmos. Meas. Tech., 14, 3773–3794, https://doi.org/10.5194/amt-14-3773-2021, https://doi.org/10.5194/amt-14-3773-2021, 2021
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This paper is a validation study of the newly installed ozone and temperature lidar at Hohenpeißenberg, Germany. As part of the Network for the Detection of Atmospheric Composition Change (NDACC), lidar stations are routinely compared against a travelling reference lidar operated by NASA. We have also attempted to assess potential biases in the reference lidar by comparing the results of this validation campaign with a previous campaign at the Observatoire de Haute-Provence, France.
Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola
Atmos. Meas. Tech., 14, 2993–3002, https://doi.org/10.5194/amt-14-2993-2021, https://doi.org/10.5194/amt-14-2993-2021, 2021
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Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.
Xiaoyi Zhao, Vitali Fioletov, Michael Brohart, Volodya Savastiouk, Ihab Abboud, Akira Ogyu, Jonathan Davies, Reno Sit, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, Moritz Müller, Debora Griffin, and Chris McLinden
Atmos. Meas. Tech., 14, 2261–2283, https://doi.org/10.5194/amt-14-2261-2021, https://doi.org/10.5194/amt-14-2261-2021, 2021
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The Brewer spectrophotometer is one of the main instruments for measurements of atmospheric total column ozone. The global Brewer network largely relies on the world reference instruments (the Brewer triad) operated by Environment and Climate Change Canada since the early 1980s. This study provides an updated assessment (1999–2019) of the reference instrument performance, in terms of random uncertainties and long-term stability.
Qiansi Tu, Frank Hase, Thomas Blumenstock, Matthias Schneider, Andreas Schneider, Rigel Kivi, Pauli Heikkinen, Benjamin Ertl, Christopher Diekmann, Farahnaz Khosrawi, Michael Sommer, Tobias Borsdorff, and Uwe Raffalski
Atmos. Meas. Tech., 14, 1993–2011, https://doi.org/10.5194/amt-14-1993-2021, https://doi.org/10.5194/amt-14-1993-2021, 2021
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We compare column-averaged dry-air mole fractions of water vapor (XH2O) retrievals from the COllaborative Carbon Column Observing Network (COCCON) with two co-located ground-based spectrometers as references at two boreal sites. Our study supports the assumption that COCCON also delivers a well-characterized XH2O data product. This is the first published study applying COCCON for MUSICA IASI and TROPOMI validation.
Wannan Wang, Tianhai Cheng, Ronald J. van der A, Jos de Laat, and Jason E. Williams
Atmos. Meas. Tech., 14, 1673–1687, https://doi.org/10.5194/amt-14-1673-2021, https://doi.org/10.5194/amt-14-1673-2021, 2021
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This paper is an evaluation of the AIRS and MLS ozone (O3) algorithms via comparison with daytime and night-time O3 datasets. Results show that further refinements of the AIRS O3 algorithm are required for better surface emissivity retrievals and that cloud cover is another problem that needs to be solved. An inconsistency is found in the
AscDescModeflag of the MLS v4.20 standard O3 product for 90–60° S and 60–90° N, resulting in inconsistent O3 profiles in these regions before May 2015.
David F. Pollard, John Robinson, Hisako Shiona, and Dan Smale
Atmos. Meas. Tech., 14, 1501–1510, https://doi.org/10.5194/amt-14-1501-2021, https://doi.org/10.5194/amt-14-1501-2021, 2021
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This work describes the steps taken to ensure a continuous, high-quality dataset of column-averaged greenhouse gas retrievals from the Total Carbon Column Observing Network (TCCON) site at Lauder, New Zealand, following a change in the Fourier transform spectrometer used to make the measurements from which the retrievals are made.
Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, Doug A. Degenstein, Felicia Kolonjari, David Plummer, Douglas E. Kinnison, Patrick Jöckel, and Thomas von Clarmann
Atmos. Meas. Tech., 14, 1425–1438, https://doi.org/10.5194/amt-14-1425-2021, https://doi.org/10.5194/amt-14-1425-2021, 2021
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Output from climate chemistry models (CMAM, EMAC, and WACCM) is used to estimate the expected geophysical variability of ozone concentrations between coincident satellite instrument measurement times and geolocations. We use the Canadian ACE-FTS and OSIRIS instruments as a case study. Ensemble mean estimates are used to optimize coincidence criteria between the two instruments, allowing for the use of more coincident profiles while providing an estimate of the geophysical variation.
Shoma Yamanouchi, Camille Viatte, Kimberly Strong, Erik Lutsch, Dylan B. A. Jones, Cathy Clerbaux, Martin Van Damme, Lieven Clarisse, and Pierre-Francois Coheur
Atmos. Meas. Tech., 14, 905–921, https://doi.org/10.5194/amt-14-905-2021, https://doi.org/10.5194/amt-14-905-2021, 2021
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Ammonia (NH3) is a major source of pollution in the air. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 over Toronto, Canada, derived from multiscale datasets are examined. These NH3 datasets were compared to each other and to a model to better understand NH3 variability and to assess model performance.
Frederik Tack, Alexis Merlaud, Marian-Daniel Iordache, Gaia Pinardi, Ermioni Dimitropoulou, Henk Eskes, Bart Bomans, Pepijn Veefkind, and Michel Van Roozendael
Atmos. Meas. Tech., 14, 615–646, https://doi.org/10.5194/amt-14-615-2021, https://doi.org/10.5194/amt-14-615-2021, 2021
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We assess the TROPOMI tropospheric NO2 product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) based on coinciding airborne APEX reference observations (~75 m × 120 m), acquired over polluted regions in Belgium. The TROPOMI NO2 product meets the mission requirements in terms of precision and accuracy. However, we show that TROPOMI is biased low over polluted areas, mainly due to the limited spatial resolution of a priori input for the AMF computation.
Claudia Rivera Cárdenas, Cesar Guarín, Wolfgang Stremme, Martina M. Friedrich, Alejandro Bezanilla, Diana Rivera Ramos, Cristina A. Mendoza-Rodríguez, Michel Grutter, Thomas Blumenstock, and Frank Hase
Atmos. Meas. Tech., 14, 595–613, https://doi.org/10.5194/amt-14-595-2021, https://doi.org/10.5194/amt-14-595-2021, 2021
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
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This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
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