Articles | Volume 16, issue 11
https://doi.org/10.5194/amt-16-2919-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-2919-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Jun 2023
Research article |
| 14 Jun 2023
| 14 Jun 2023
An approach to track instrument calibration and produce consistent products with the version-8 total column ozone algorithm (V8TOZ)
Zhihua Zhang
CORRESPONDING AUTHOR
I. M. System Group Inc. at NOAA, College Park, MD 20740, USA
Jianguo Niu
I. M. System Group Inc. at NOAA, College Park, MD 20740, USA
Lawrence E. Flynn
Center for Satellite Application and Research, NOAA/NESDIS, College
Park, MD 20740, USA
Eric Beach
I. M. System Group Inc. at NOAA, College Park, MD 20740, USA
Trevor Beck
Center for Satellite Application and Research, NOAA/NESDIS, College
Park, MD 20740, USA
Related authors
No articles found.
Irina Petropavlovskikh, Koji Miyagawa, Audra McClure-Beegle, Bryan Johnson, Jeannette Wild, Susan Strahan, Krzysztof Wargan, Richard Querel, Lawrence Flynn, Eric Beach, Gerard Ancellet, and Sophie Godin-Beekmann
Atmos. Meas. Tech., 15, 1849–1870, https://doi.org/10.5194/amt-15-1849-2022, https://doi.org/10.5194/amt-15-1849-2022, 2022
Short summary
Short summary
The Montreal Protocol and its amendments assure the recovery of the stratospheric ozone layer that protects the Earth from harmful ultraviolet radiation. To monitor ozone recovery, multiple satellites and ground-based observational platforms collect ozone data. The changes in instruments can influence the continuation of the ozone data. We discuss a method to remove instrumental artifacts from ozone records to improve the internal consistency among multiple observational records.
Elizabeth C. Weatherhead, Jerald Harder, Eduardo A. Araujo-Pradere, Greg Bodeker, Jason M. English, Lawrence E. Flynn, Stacey M. Frith, Jeffrey K. Lazo, Peter Pilewskie, Mark Weber, and Thomas N. Woods
Atmos. Chem. Phys., 17, 15069–15093, https://doi.org/10.5194/acp-17-15069-2017, https://doi.org/10.5194/acp-17-15069-2017, 2017
Short summary
Short summary
Satellite overlap is often carried out as a check on the stability of the data collected. We looked at how length of overlap influences how much information can be derived from the overlap period. Several results surprised us: the confidence we could have in the matchup of two records was independent of the offset, and understanding of the relative drift between the two satellite data sets improved significantly with 2–3 years of overlap. Sudden jumps could easily be confused with drift.
L. K. Huang, M. T. DeLand, S. L. Taylor, and L. E. Flynn
Atmos. Meas. Tech., 7, 267–278, https://doi.org/10.5194/amt-7-267-2014, https://doi.org/10.5194/amt-7-267-2014, 2014
P. K. Bhartia, R. D. McPeters, L. E. Flynn, S. Taylor, N. A. Kramarova, S. Frith, B. Fisher, and M. DeLand
Atmos. Meas. Tech., 6, 2533–2548, https://doi.org/10.5194/amt-6-2533-2013, https://doi.org/10.5194/amt-6-2533-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Water vapor measurements inside clouds and storms using a differential absorption radar
Evaluation of the first year of Pandora NO2 measurements over Beijing and application to satellite validation
Validation of MUSES NH3 observations from AIRS and CrIS against aircraft measurements from DISCOVER-AQ and a surface network in the Magic Valley
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer
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
Ship- and aircraft-based XCH4 over oceans as new tool for 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
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
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
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
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
Short summary
Short summary
In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
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., 17, 377–395, https://doi.org/10.5194/amt-17-377-2024, https://doi.org/10.5194/amt-17-377-2024, 2024
Short summary
Short summary
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 timescales and how this is affected by wind speed and direction and chemistry.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
Short summary
Short summary
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 differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Alana K. Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew K. Thorpe, and Riley Duren
Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, https://doi.org/10.5194/amt-16-6065-2023, 2023
Short summary
Short summary
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.
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 Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
Short summary
Short summary
We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-144, https://doi.org/10.5194/amt-2023-144, 2023
Revised manuscript accepted for AMT
Short summary
Short summary
Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Bak, J., Liu, X., Kim, J.-H., Haffner, D. P., Chance, K., Yang, K., and Sun, K.: Characterization and correction of OMPS nadir mapper measurements for ozone profile retrievals, Atmos. Meas. Tech., 10, 4373–4388, https://doi.org/10.5194/amt-10-4373-2017, 2017.
Bhartia, P. K. and Wellemeyer, C. G.: TOMS-V8 total ozone algorithm, in: OMI
Algorithm, Theoretical Basis Document Volume II: OMI Ozone Products, edited
by: Bhartia, P. K., NASA Goddard Space Flight Center Greenbelt, Maryland, USA, https://eospso.gsfc.nasa.gov/sites/default/files/atbd/ATBD-OMI-02.pdf (last access: 6 June 2023), 2022.
Bhartia, P. K., McPeters, R. D., Flynn, L. E., Taylor, S., Kramarova, N. A., Frith, S., Fisher, B., and DeLand, M.: Solar Backscatter UV (SBUV) total ozone and profile algorithm, Atmos. Meas. Tech., 6, 2533–2548, https://doi.org/10.5194/amt-6-2533-2013, 2013.
Bodeker, G. E., Scott, J. C., Kreher, K., and McKenzie, R. L.: Global ozone
trends in potential vorticity coordinates using TOMS and GOME intercompared
against the Dobson network: 1978–1998, J. Geophys. Res., 106, 23029–23042,
2001.
Caudill, T. R., Flittner, D. E., Herman, B. M., Torres, O., and McPeters, R.
D.: Evaluation of the Pseudo-spherical Approximation for Backscattered
Ultraviolet Radiances and Ozone Retrieval, J. Geophys. Res., 102,
3881–3890, 1997.
de Graaf, M., Stammes, P., Torres, O., and Koelemeijer, R. B. A.: Absorbing
Aerosol Index: sensitivity analysis, application to GOME and comparison with
TOMS, J. Geophys. Res., 110, D01201, https://doi.org/10.1029/2004JD005178, 2005.
Flynn, L., Long, C., Wu, X., Evans, R., Beck, C. T., Petropavlovskikh, I.,
McConville, G., Yu, W., Z. Zhang, Niu, J., Beach, E., Hao, Y., Pan, C., Sen,
B., Novicki, M., Zhou, S., and Seftor, C.: Performance of the Ozone Mapping
and Profiler Suite (OMPS) products. J. Geophys. Res.-Atmos., 119, 6181–6195, https://doi.org/10.1002/2013JD020467, 2014.
Garane, K., Koukouli, M.-E., Verhoelst, T., Lerot, C., Heue, K.-P., Fioletov, V., Balis, D., Bais, A., Bazureau, A., Dehn, A., Goutail, F., Granville, J., Griffin, D., Hubert, D., Keppens, A., Lambert, J.-C., Loyola, D., McLinden, C., Pazmino, A., Pommereau, J.-P., Redondas, A., Romahn, F., Valks, P., Van Roozendael, M., Xu, J., Zehner, C., Zerefos, C., and Zimmer, W.: TROPOMI/S5P total ozone column data: global ground-based validation and consistency with other satellite missions, Atmos. Meas. Tech., 12, 5263–5287, https://doi.org/10.5194/amt-12-5263-2019, 2019.
Geogdzhayev, I. V. and Marshak, A.: Calibration of the DSCOVR EPIC visible and NIR channels using MODIS Terra and Aqua data and EPIC lunar observations, Atmos. Meas. Tech., 11, 359–368, https://doi.org/10.5194/amt-11-359-2018, 2018.
Haffner, D. P., Kramarova, N. A., Ziemke, J. R., McPeters, R. D., Bhartia,
P. K., Baek, K. H., Labow, G. J., and Frith, S. M.: Error-Uncertainty
Analysis of the TOMS Version 9 Total Ozone Record from the OMI and OMPS
Mapping Instruments, American Geophysical Union, Fall Meeting 2019, 9–13 December 2019, San Francisco, USA, abstract
no. NG21B-0947, https://ui.adsabs.harvard.edu/abs/2019AGUFMNG21B0947H (last access: 9 June 2023), 2019.
Herman, J. R., Bhartia, P. K., Torres, O., Hsu, C., Seftor, C., and
Celarier, E.: Global distribution of UV-absorbing aerosols from Nimbus
7/TOMS data, J. Geophys. Res., 102, 16911–16922, 1997.
Huang, X. and Yang, K.: Algorithm theoretical basis for ozone and sulfur dioxide retrievals from DSCOVR EPIC, Atmos. Meas. Tech., 15, 5877–5915, https://doi.org/10.5194/amt-15-5877-2022, 2022.
Inness, A., Flemming, J., Heue, K.-P., Lerot, C., Loyola, D., Ribas, R., Valks, P., van Roozendael, M., Xu, J., and Zimmer, W.: Monitoring and assimilation tests with TROPOMI data in the CAMS system: near-real-time total column ozone, Atmos. Chem. Phys., 19, 3939–3962, https://doi.org/10.5194/acp-19-3939-2019, 2019.
Jaross, G., Bhartia, P. K., Chen, G., Kowitt, M., Haken, M., Chen, Z., Xu,
P., Warner, J., and Kelly, T.: OMPS Limb Profiler instrument performance
assessment, J. Geophys. Res.-Atmos., 119, 4399–4412, https://doi.org/10.1002/2013JD020482, 2014.
Klenk, K. F., Bhartia, P. K., Fleig, A. J., Kaveeshwar, V. G., McPeters, R.
D., and Smith, P. M.: Total ozone determination from the Backscattered
Ultraviolet (BUV) experiment, J. Appl. Meteorol., 21, 1672–1684, 1982.
Kooreman, M. L., Stammes, P., Trees, V., Sneep, M., Tilstra, L. G., de Graaf, M., Stein Zweers, D. C., Wang, P., Tuinder, O. N. E., and Veefkind, J. P.: Effects of clouds on the UV Absorbing Aerosol Index from TROPOMI, Atmos. Meas. Tech., 13, 6407–6426, https://doi.org/10.5194/amt-13-6407-2020, 2020.
Koukouli, M. E., Balis, D. S., Loyola, D., Valks, P., Zimmer, W., Hao, N., Lambert, J.-C., Van Roozendael, M., Lerot, C., and Spurr, R. J. D.: Geophysical validation and long-term consistency between GOME-2/MetOp-A total ozone column and measurements from the sensors GOME/ERS-2, SCIAMACHY/ENVISAT and OMI/Aura, Atmos. Meas. Tech., 5, 2169–2181, https://doi.org/10.5194/amt-5-2169-2012, 2012.
Kramarova, N. A., Ziemke, J. R., Huang, L.-K., Herman, J. R., Wargan, K.,
Seftor, C. J., Labow, G. J., and Oman, L. D.: Evaluation of Version 3 Total and Tropospheric Ozone Columns from Earth Polychromatic Imaging Camera on Deep Space Climate Observatory for Studying Regional Scale Ozone Variations,
Frontiers in Remote Sensing, 2, 734071, https://doi.org/10.3389/frsen.2021.734071, 2021.
Lindfors, A. V., Kujanpää, J., Kalakoski, N., Heikkilä, A., Lakkala, K., Mielonen, T., Sneep, M., Krotkov, N. A., Arola, A., and Tamminen, J.: The TROPOMI surface UV algorithm, Atmos. Meas. Tech., 11, 997–1008, https://doi.org/10.5194/amt-11-997-2018, 2018.
Lyapustin, A., Go, S., Korkin, S., Wang, Y., Torres, O., Jethva, H., and
Marshak, A.: Retrievals of Aerosol Optical Depth and Spectral Absorption
from DSCOVR EPIC, Frontiers in Remote Sensing, 2, 645794, https://doi.org/10.3389/frsen.2021.645794, 2021.
Marshak, A., Herman, J., Adam, S., Karin, B., Carn, S., Cede,
A., Geogdzhayev, I., Huang, D., Huang, L., Knyazikhin, Y., Kowalewski,
M., Krotkov, N., Lyapustin, A., McPeters, R., Meyer, K. G., Torres, O.,
and Yang, Y.: Earth Observations from DSCOVR EPIC Instrument, B. Am.
Meteorol. Soc., 99, 1829–1850, https://doi.org/10.1175/BAMS-D-17-0223.1, 2018.
McPeters, R., Frith, S., Kramarova, N., Ziemke, J., and Labow, G.: Trend quality ozone from NPP OMPS: the version 2 processing, Atmos. Meas. Tech., 12, 977–985, https://doi.org/10.5194/amt-12-977-2019, 2019.
McPeters, R. D., Bhartia, P. K., Krueger, A. J., Herman, J. R., Schlesinger,
B. M., Wellemeyer, C. G., Seftor, C. J., Jaross, G., Taylor, S. L.,
Swissler, T., Torres, O., Labow, G., Byerly, W., and Cebula, R. P.: Nimbus-7
Total Ozone Mapping Spectrometer (TOMS) Data Products User's Guide, NASA
Reference Publication, USA, 67 pp., https://acd-ext.gsfc.nasa.gov/anonftp/toms/nimbus7/NIMBUS7_USERGUIDE.PDF (last access: 9 June 2023), 1996.
National Oceanic and Atmospheric Administration (NOAA): NOAA Comprehensive Large Array-data Stewardship System (CLASS), National Oceanic and Atmospheric Administration, USA [data set],
https://www.avl.class.noaa.gov/saa/products/search?datatype_family=RPOMPSSDR, last access: 9 June 2023.
Niu, J., Flynn, L. E., Beck, T., Zhang, Z., and Beach, E.: Evaluation and
Improvement of the Near-Real-Time Linear Fit SO2 Retrievals from Suomi NPP Ozone Mapping and Profiler Suite, IEEE T. Geosci. Remote, 59, 101–113, https://doi.org/10.1109/TGRS.2020.2992429, 2020.
Pan, C., Zhou, L., Cao, C., Flynn L., and Kalluri, S.: Spectral Calibration
of NOAA-20 OMPS Sensor Data Record, IGARSS 2019 – 2019 IEEE International
Geoscience and Remote Sensing Symposium, 28 July–2 August 2019, Yokohama, Japan, IEEE, 8999–9001, https://doi.org/10.1109/IGARSS.2019.8898250, 2019.
Seftor, C. J., Jaross, G., Kowitt, M., Haken, M., Li, J., and Flynn,
L. E.: Post-launch performance of the Suomi NPP Ozone Mapping and Profiler
Suite (OMPS) nadir sensors, J. Geophys. Res.-Atmos., 119, 4413–4428,
https://doi.org/10.1002/2013JD020472, 2014.
Torres, O. and Bhartia, P. K.: Impact of tropospheric aerosol absorption on
ozone retrieval from backscattered ultraviolet measurements, J. Geophys.
Res., 104, 21569–21577, 1999.
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.:
Derivation of aerosol properties from satellite measurements of
backscattered ultraviolet radiation: theoretical basis, J. Geophys. Res.,
103, 17099–17110, 1998.
Torres, O., Tanskanen, A., Veihelmann, B., Ahn, C., Braak, R., Bhartia, P.
K., Veefkind, P., and Levelt, P.: Aerosols and surface UV products from
Ozone Monitoring Instrument observations: an overview, J. Geophys. Res.,
112, D24S47, https://doi.org/10.1029/2007JD008809, 2007.
Wellemeyer, C. G., Taylor, S. L., Seftor, C. J., McPeters R. D., and
Bhartia, P. K.: A correction for total ozone mapping spectrometer profile
shape errors at high latitude, J. Geophys. Res., 102, 9029–9038, 1997.
Wu, X., Liu, Q., Zeng, J., Grotenhuis, M., Qian, H., Caponi, M., Flynn, L.,
Jaross, G., Sen, B., Buss, R. H., Johnsen, W., Janz, S., Pan, C., Niu, J.,
Beck, T., Beach, E., Yu, W., Rama Varma Raja, M. K., Stuhmer, D.,
Cumpton, D., Owen, C., and Li, W.-H.: Evaluation of the sensor data record
from the nadir instruments of the Ozone Mapping Profiler Suite (OMPS), J.
Geophys. Res.-Atmos., 119, 6170–6180, https://doi.org/10.1002/2013JD020484, 2014.
Yan, B., Pan, C., Beck, T., Jin, X., Wang, L., Liang, D., Flynn, L., Chen,
J., Huang, J., Buckner, S., Zou, C., Sun, N., Lin, L., Young, A., Zhou, L.,
and Hao, W.: New Reprocessing towards Life-Time Quality-Consistent Suomi NPP
OMPS Nadir Sensor Data Records (SDR): Calibration Improvements and Impact
Assessments on Long-Term Quality Stability of OMPS SDR Data Sets, Remote
Sens., 14, 3125, https://doi.org/10.3390/rs14133125, 2022.
Yang, K., Krotkov, N. A., Krueger, A.J., Carn, S. A., Bhartia, P. K., and
Levelt, P. F.: Improving retrieval of volcanic sulfur dioxide from
backscattered UV satellite observations, Geophys. Res. Lett., 36, L03102,
https://doi.org/10.1029/2008GL036036, 2009.
Zou, C., Zhou, L., Lin, L., Sun, N., Chen, Y., Flynn, L., Zhang, B., Cao,
C., Iturbide-Sanchez, F., Beck, T., Yan, B., Kalluri, S., Bai, Y., Blonski,
S., Choi, T., Divakarla, M., Gu, Y., Hao, X., Li, W., Liang, D., Niu, J.,
Shao, X., Strow, L., Tobin, D., Tremblay, D., Uprety, S., Wang, W., Xu, H.,
Yang, H., and Goldberg, M.: The Reprocessed Suomi NPP Satellite
Observations, Remote Sens, 12, 2891, https://doi.org/10.3390/rs12182891, 2020.
Short summary
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.
This study mainly focused on addressing stability and improvement when using a broadband...
