Articles | Volume 16, issue 6
https://doi.org/10.5194/amt-16-1461-2023
© 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-16-1461-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Mar 2023
Research article |
| 21 Mar 2023
| 21 Mar 2023
Correcting 3D cloud effects in XCO2 retrievals from the Orbiting Carbon Observatory-2 (OCO-2)
Steffen Mauceri
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Steven Massie
Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO 80303, USA
Sebastian Schmidt
Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO 80303, USA
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William R. Keely, Steffen Mauceri, Sean Crowell, and Christopher W. O'Dell
Atmos. Meas. Tech., 16, 5725–5748, https://doi.org/10.5194/amt-16-5725-2023, https://doi.org/10.5194/amt-16-5725-2023, 2023
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Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
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This paper provides insights into the effects of clouds on Orbiting Carbon Observatory (OCO-2) measurements of CO2. Calculations are carried out that indicate the extent to which this satellite experiment underestimates CO2, due to these cloud effects, as a function of the distance between the surface observation footprint and the nearest cloud. The paper discusses how to lessen the influence of these cloud effects.
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Aerosols are fine particles that are suspended in Earth’s atmosphere. A better understanding of aerosols is important to lower uncertainties in climate predictions. We propose measuring aerosols from satellites and airplanes equipped with hyperspectral cameras using an artificial neural network, a form of machine learning. We applied our neural network to hyperspectral observations from a recent airplane flight over India and find general agreement with independent aerosol measurements.
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Atmos. Meas. Tech., 16, 3609–3630, https://doi.org/10.5194/amt-16-3609-2023, https://doi.org/10.5194/amt-16-3609-2023, 2023
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Atmos. Meas. Tech., 16, 2145–2166, https://doi.org/10.5194/amt-16-2145-2023, https://doi.org/10.5194/amt-16-2145-2023, 2023
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Hong Chen, K. Sebastian Schmidt, Steven T. Massie, Vikas Nataraja, Matthew S. Norgren, Jake J. Gristey, Graham Feingold, Robert E. Holz, and Hironobu Iwabuchi
Atmos. Meas. Tech., 16, 1971–2000, https://doi.org/10.5194/amt-16-1971-2023, https://doi.org/10.5194/amt-16-1971-2023, 2023
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We introduce the Education and Research 3D Radiative Transfer Toolbox (EaR3T) and propose a radiance self-consistency approach for quantifying and mitigating 3D bias in legacy airborne and spaceborne imagery retrievals due to spatially inhomogeneous clouds and surfaces.
Paul A. Barrett, Steven J. Abel, Hugh Coe, Ian Crawford, Amie Dobracki, James Haywood, Steve Howell, Anthony Jones, Justin Langridge, Greg M. McFarquhar, Graeme J. Nott, Hannah Price, Jens Redemann, Yohei Shinozuka, Kate Szpek, Jonathan W. Taylor, Robert Wood, Huihui Wu, Paquita Zuidema, Stéphane Bauguitte, Ryan Bennett, Keith Bower, Hong Chen, Sabrina Cochrane, Michael Cotterell, Nicholas Davies, David Delene, Connor Flynn, Andrew Freedman, Steffen Freitag, Siddhant Gupta, David Noone, Timothy B. Onasch, James Podolske, Michael R. Poellot, Sebastian Schmidt, Stephen Springston, Arthur J. Sedlacek III, Jamie Trembath, Alan Vance, Maria A. Zawadowicz, and Jianhao Zhang
Atmos. Meas. Tech., 15, 6329–6371, https://doi.org/10.5194/amt-15-6329-2022, https://doi.org/10.5194/amt-15-6329-2022, 2022
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To better understand weather and climate, it is vital to go into the field and collect observations. Often measurements take place in isolation, but here we compared data from two aircraft and one ground-based site. This was done in order to understand how well measurements made on one platform compared to those made on another. Whilst this is easy to do in a controlled laboratory setting, it is more challenging in the real world, and so these comparisons are as valuable as they are rare.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
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Dongwei Fu, Larry Di Girolamo, Robert M. Rauber, Greg M. McFarquhar, Stephen W. Nesbitt, Jesse Loveridge, Yulan Hong, Bastiaan van Diedenhoven, Brian Cairns, Mikhail D. Alexandrov, Paul Lawson, Sarah Woods, Simone Tanelli, Sebastian Schmidt, Chris Hostetler, and Amy Jo Scarino
Atmos. Chem. Phys., 22, 8259–8285, https://doi.org/10.5194/acp-22-8259-2022, https://doi.org/10.5194/acp-22-8259-2022, 2022
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Matthew S. Norgren, John Wood, K. Sebastian Schmidt, Bastiaan van Diedenhoven, Snorre A. Stamnes, Luke D. Ziemba, Ewan C. Crosbie, Michael A. Shook, A. Scott Kittelman, Samuel E. LeBlanc, Stephen Broccardo, Steffen Freitag, and Jeffrey S. Reid
Atmos. Meas. Tech., 15, 1373–1394, https://doi.org/10.5194/amt-15-1373-2022, https://doi.org/10.5194/amt-15-1373-2022, 2022
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A new spectral instrument (SPN-S), with the ability to partition solar radiation into direct and diffuse components, is used in airborne settings to study the optical properties of aerosols and cirrus. It is a low-cost and mechanically simple system but has higher measurement uncertainty than existing standards. This challenge is overcome by utilizing the unique measurement capabilities to develop new retrieval techniques. Validation is done with data from two NASA airborne research campaigns.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Michal Segal Rozenhaimer, Meloë Kacenelenbogen, Yohei Shinozuka, Connor Flynn, Rich Ferrare, Sharon Burton, Chris Hostetler, Marc Mallet, and Paquita Zuidema
Atmos. Meas. Tech., 15, 61–77, https://doi.org/10.5194/amt-15-61-2022, https://doi.org/10.5194/amt-15-61-2022, 2022
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This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
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In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Steven T. Massie, Heather Cronk, Aronne Merrelli, Christopher O'Dell, K. Sebastian Schmidt, Hong Chen, and David Baker
Atmos. Meas. Tech., 14, 1475–1499, https://doi.org/10.5194/amt-14-1475-2021, https://doi.org/10.5194/amt-14-1475-2021, 2021
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The OCO-2 science team is working to retrieve CO2 measurements that can be used by the carbon cycle community to calculate regional sources and sinks of CO2. The retrieved data, however, are in need of improvements in accuracy. This paper discusses several ways in which 3D cloud metrics (such as the distance of a measurement to the nearest cloud) can be used to account for cloud effects in the OCO-2 CO2 data files.
Jens Redemann, Robert Wood, Paquita Zuidema, Sarah J. Doherty, Bernadette Luna, Samuel E. LeBlanc, Michael S. Diamond, Yohei Shinozuka, Ian Y. Chang, Rei Ueyama, Leonhard Pfister, Ju-Mee Ryoo, Amie N. Dobracki, Arlindo M. da Silva, Karla M. Longo, Meloë S. Kacenelenbogen, Connor J. Flynn, Kristina Pistone, Nichola M. Knox, Stuart J. Piketh, James M. Haywood, Paola Formenti, Marc Mallet, Philip Stier, Andrew S. Ackerman, Susanne E. Bauer, Ann M. Fridlind, Gregory R. Carmichael, Pablo E. Saide, Gonzalo A. Ferrada, Steven G. Howell, Steffen Freitag, Brian Cairns, Brent N. Holben, Kirk D. Knobelspiesse, Simone Tanelli, Tristan S. L'Ecuyer, Andrew M. Dzambo, Ousmane O. Sy, Greg M. McFarquhar, Michael R. Poellot, Siddhant Gupta, Joseph R. O'Brien, Athanasios Nenes, Mary Kacarab, Jenny P. S. Wong, Jennifer D. Small-Griswold, Kenneth L. Thornhill, David Noone, James R. Podolske, K. Sebastian Schmidt, Peter Pilewskie, Hong Chen, Sabrina P. Cochrane, Arthur J. Sedlacek, Timothy J. Lang, Eric Stith, Michal Segal-Rozenhaimer, Richard A. Ferrare, Sharon P. Burton, Chris A. Hostetler, David J. Diner, Felix C. Seidel, Steven E. Platnick, Jeffrey S. Myers, Kerry G. Meyer, Douglas A. Spangenberg, Hal Maring, and Lan Gao
Atmos. Chem. Phys., 21, 1507–1563, https://doi.org/10.5194/acp-21-1507-2021, https://doi.org/10.5194/acp-21-1507-2021, 2021
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Southern Africa produces significant biomass burning emissions whose impacts on regional and global climate are poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA investigation designed to study the key processes that determine these climate impacts. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project, the dataset it produced, and the most important initial findings.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Amie Dobracki, Paquita Zuidema, Steven Howell, Steffen Freitag, and Sarah Doherty
Atmos. Meas. Tech., 14, 567–593, https://doi.org/10.5194/amt-14-567-2021, https://doi.org/10.5194/amt-14-567-2021, 2021
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Based on observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), this work establishes an observationally driven link from mid-visible aerosol optical depth (AOD) and other scene parameters to broadband shortwave irradiance (and by extension the direct aerosol radiative effect, DARE). The majority of the case-to-case DARE variability within the ORACLES dataset is attributable to the dependence on AOD and scene albedo.
Yohei Shinozuka, Meloë S. Kacenelenbogen, Sharon P. Burton, Steven G. Howell, Paquita Zuidema, Richard A. Ferrare, Samuel E. LeBlanc, Kristina Pistone, Stephen Broccardo, Jens Redemann, K. Sebastian Schmidt, Sabrina P. Cochrane, Marta Fenn, Steffen Freitag, Amie Dobracki, Michal Segal-Rosenheimer, and Connor J. Flynn
Atmos. Chem. Phys., 20, 11275–11285, https://doi.org/10.5194/acp-20-11275-2020, https://doi.org/10.5194/acp-20-11275-2020, 2020
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To help satellite retrieval of aerosols and studies of their radiative effects, we demonstrate that daytime aerosol optical depth over low-level clouds is similar to that in neighboring clear skies at the same heights. Based on recent airborne lidar and sun photometer observations above the southeast Atlantic, the mean AOD difference at 532 nm is between 0 and -0.01, when comparing the cloudy and clear sides of cloud edges, with each up to 20 km wide.
Sabrina P. Cochrane, K. Sebastian Schmidt, Hong Chen, Peter Pilewskie, Scott Kittelman, Jens Redemann, Samuel LeBlanc, Kristina Pistone, Meloë Kacenelenbogen, Michal Segal Rozenhaimer, Yohei Shinozuka, Connor Flynn, Steven Platnick, Kerry Meyer, Rich Ferrare, Sharon Burton, Chris Hostetler, Steven Howell, Steffen Freitag, Amie Dobracki, and Sarah Doherty
Atmos. Meas. Tech., 12, 6505–6528, https://doi.org/10.5194/amt-12-6505-2019, https://doi.org/10.5194/amt-12-6505-2019, 2019
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For two cases from the NASA ORACLES experiments, we retrieve aerosol and cloud properties and calculate a direct aerosol radiative effect (DARE). We investigate the relationship between DARE and the cloud albedo by specifying the albedo for which DARE transitions from a cooling to warming radiative effect. Our new aerosol retrieval algorithm is successful despite complexities associated with scenes that contain aerosols above clouds and decreases the uncertainty on retrieved aerosol parameters.
Steffen Mauceri, Bruce Kindel, Steven Massie, and Peter Pilewskie
Atmos. Meas. Tech., 12, 6017–6036, https://doi.org/10.5194/amt-12-6017-2019, https://doi.org/10.5194/amt-12-6017-2019, 2019
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Aerosols are fine particles that are suspended in Earth’s atmosphere. A better understanding of aerosols is important to lower uncertainties in climate predictions. We propose measuring aerosols from satellites and airplanes equipped with hyperspectral cameras using an artificial neural network, a form of machine learning. We applied our neural network to hyperspectral observations from a recent airplane flight over India and find general agreement with independent aerosol measurements.
Kristina Pistone, Jens Redemann, Sarah Doherty, Paquita Zuidema, Sharon Burton, Brian Cairns, Sabrina Cochrane, Richard Ferrare, Connor Flynn, Steffen Freitag, Steven G. Howell, Meloë Kacenelenbogen, Samuel LeBlanc, Xu Liu, K. Sebastian Schmidt, Arthur J. Sedlacek III, Michal Segal-Rozenhaimer, Yohei Shinozuka, Snorre Stamnes, Bastiaan van Diedenhoven, Gerard Van Harten, and Feng Xu
Atmos. Chem. Phys., 19, 9181–9208, https://doi.org/10.5194/acp-19-9181-2019, https://doi.org/10.5194/acp-19-9181-2019, 2019
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Understanding how smoke particles interact with sunlight is important in calculating their effects on climate, since some smoke is more scattering (cooling) and some is more absorbing (heating). Knowing this proportion is important for both satellite observations and climate models. We measured smoke properties in a recent aircraft-based field campaign off the west coast of Africa and present a comparison of these properties as measured using the six different, independent techniques available.
Marc Mallet, Pierre Nabat, Paquita Zuidema, Jens Redemann, Andrew Mark Sayer, Martin Stengel, Sebastian Schmidt, Sabrina Cochrane, Sharon Burton, Richard Ferrare, Kerry Meyer, Pablo Saide, Hiren Jethva, Omar Torres, Robert Wood, David Saint Martin, Romain Roehrig, Christina Hsu, and Paola Formenti
Atmos. Chem. Phys., 19, 4963–4990, https://doi.org/10.5194/acp-19-4963-2019, https://doi.org/10.5194/acp-19-4963-2019, 2019
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The model is able to represent LWP but not the LCF. AOD is consistent over the continent but also over ocean (ACAOD). Differences are observed in SSA due to the absence of internal mixing in ALADIN-Climate. A significant regional gradient of the forcing at TOA is observed. An intense positive forcing is simulated over Gabon. Results highlight the significant effect of enhanced moisture on BBA extinction. The surface dimming modifies the energy budget.
Rintaro Okamura, Hironobu Iwabuchi, and K. Sebastian Schmidt
Atmos. Meas. Tech., 10, 4747–4759, https://doi.org/10.5194/amt-10-4747-2017, https://doi.org/10.5194/amt-10-4747-2017, 2017
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Three-dimensional (3-D) radiative transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. Multi-pixel, multispectral approaches based on deep learning are proposed for retrieval of cloud optical thickness and droplet effective radius. A feasibility test shows that proposed retrieval methods are effective to obtain accurate cloud properties. Use of the convolutional neural network is effective to reduce 3-D radiative transfer effects.
Shi Song, K. Sebastian Schmidt, Peter Pilewskie, Michael D. King, Andrew K. Heidinger, Andi Walther, Hironobu Iwabuchi, Gala Wind, and Odele M. Coddington
Atmos. Chem. Phys., 16, 13791–13806, https://doi.org/10.5194/acp-16-13791-2016, https://doi.org/10.5194/acp-16-13791-2016, 2016
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The radiative effects of spatially complex cloud fields are notoriously difficult to estimate and are afflicted with errors up to ±50 % of the incident solar radiation. We find that horizontal photon transport, the leading cause for these three-dimensional effects, manifests itself through a spectral fingerprint – a new observable that holds promise for reducing the errors associated with spatial complexity by moving the problem to the spectral dimension.
Steven T. Massie, Julien Delanoë, Charles G. Bardeen, Jonathan H. Jiang, and Lei Huang
Atmos. Chem. Phys., 16, 6091–6105, https://doi.org/10.5194/acp-16-6091-2016, https://doi.org/10.5194/acp-16-6091-2016, 2016
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Changes in cloud vertical structure (i.e. the shape of cloud ice water content (IWC) vertical structure) due to variations in aerosol, observed by three different satellite experiments (MODIS, OMI, and MLS) are calculated in the Tropics during 2007–2010. This topic is of interest because aerosol-cloud interactions are the largest source of uncertainty in climate models. Analysis of the effects of MODIS aerosol, OMI absorptive aerosol, and MLS CO (an absorptive aerosol proxy) upon deep convective
B. C. Kindel, P. Pilewskie, K. S. Schmidt, T. Thornberry, A. Rollins, and T. Bui
Atmos. Meas. Tech., 8, 1147–1156, https://doi.org/10.5194/amt-8-1147-2015, https://doi.org/10.5194/amt-8-1147-2015, 2015
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Measurements of upper tropospheric-lower stratospheric water vapor amounts in the tropics were made using the 1400 and 1900nm water vapor bands present in airborne solar spectral irradiance data. These were validated with radiative transfer modeling using in situ profiles of water vapor, temperature, and pressure. An approach to extending these types of measurements from aircraft altitudes to the top of the atmosphere to infer stratospheric water vapor amount is outlined.
X. Jiang, M. C. Barth, C. Wiedinmyer, and S. T. Massie
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-21383-2013, https://doi.org/10.5194/acpd-13-21383-2013, 2013
Revised manuscript not accepted
H. M. Worden, M. N. Deeter, C. Frankenberg, M. George, F. Nichitiu, J. Worden, I. Aben, K. W. Bowman, C. Clerbaux, P. F. Coheur, A. T. J. de Laat, R. Detweiler, J. R. Drummond, D. P. Edwards, J. C. Gille, D. Hurtmans, M. Luo, S. Martínez-Alonso, S. Massie, G. Pfister, and J. X. Warner
Atmos. Chem. Phys., 13, 837–850, https://doi.org/10.5194/acp-13-837-2013, https://doi.org/10.5194/acp-13-837-2013, 2013
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A retrieval of xCO2 from ground-based mid-infrared NDACC solar absorption spectra and comparison to TCCON
U-Plume: Automated algorithm for plume detection and source quantification by satellite point-source imagers
Optimal estimation retrieval of tropospheric ammonia from the Geostationary Interferometric Infrared Sounder on board FengYun-4B
Stratospheric-trace-gas-profile retrievals from balloon-borne limb imaging of mid-infrared emission spectra
Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder: first result from GIIRS on board FengYun-4B
IMK/IAA MIPAS retrievals version 8: CH4 and N2O
Vertical information of CO from TROPOMI total column measurements in context of the CAMS-IFS data assimilation scheme
Global retrieval of stratospheric and tropospheric BrO columns from OMPS-NM onboard the Suomi-NPP satellite
Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images
Inferring the vertical distribution of CO and CO2 from TCCON total column values using the TARDISS algorithm
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique
Michelson Interferometer for Passive Atmospheric Sounding Institute of Meteorology and Climate Research/Instituto de Astrofísica de Andalucía version 8 retrieval of nitric oxide and lower-thermospheric temperature
Near-real-time detection of unexpected atmospheric events using principal component analysis on the Infrared Atmospheric Sounding Interferometer (IASI) radiances
Differences in MOPITT surface level CO retrievals and trends from Level 2 and Level 3 products in coastal grid boxes
Updated merged SAGE-CCI-OMPS+ dataset for the evaluation of ozone trends in the stratosphere
Accounting for meteorological biases in simulated plumes using smarter metrics
Accounting for surface reflectance spectral features in TROPOMI methane retrievals
Investigation of three-dimensional radiative transfer effects for UV–Vis satellite and ground-based observations of volcanic plumes
Retrievals of precipitable water vapor and aerosol optical depth from direct sun measurements with EKO MS711 and MS712 spectroradiometers
Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm
Version 8 IMK–IAA MIPAS ozone profiles: nominal observation mode
Using portable low-resolution spectrometers to evaluate Total Carbon Column Observing Network (TCCON) biases in North America
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024, https://doi.org/10.5194/amt-17-1941-2024, 2024
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We assimilate different MOPITT CO products to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech., 17, 1891–1911, https://doi.org/10.5194/amt-17-1891-2024, https://doi.org/10.5194/amt-17-1891-2024, 2024
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The new version (V2) of the OMI ozone profile product is introduced to improve retrieval quality and long-term consistency of tropospheric ozone by incorporating the recent collection 4 OMI L1b spectral products and refining radiometric correction, forward model calculation, and a priori ozone data.
Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, Annette Ladstätter-Weißenmayer, John P. Burrows, Anne M. Thompson, Ryan M. Stauffer, and Debra E. Kollonige
Atmos. Meas. Tech., 17, 1791–1809, https://doi.org/10.5194/amt-17-1791-2024, https://doi.org/10.5194/amt-17-1791-2024, 2024
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Valuable information on the tropospheric ozone column (TrOC) can be obtained globally by combining space-borne limb and nadir measurements (limb–nadir matching, LNM). This study describes the retrieval of TrOC from the OMPS instrument (since 2012) using the LNM technique. The OMPS-LNM TrOC was compared with ozonesondes and other satellite measurements, showing a good agreement with a negative bias within 1 to 4 DU. This new dataset is suitable for pollution studies.
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya García-Comas, and Manuel López-Puertas
Atmos. Meas. Tech., 17, 1759–1789, https://doi.org/10.5194/amt-17-1759-2024, https://doi.org/10.5194/amt-17-1759-2024, 2024
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CFC-11, CFC-12, and HCFC-22 contribute to the depletion of ozone and are potent greenhouse gases. They have been banned by the Montreal protocol. With MIPAS on Envisat the atmospheric composition could be observed between 2002 and 2012. We present here the retrieval of their atmospheric distributions for the final data version 8. We characterise the derived data by their error budget and their spatial resolution. An additional representation for direct comparison to models is also provided.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024, https://doi.org/10.5194/amt-17-1375-2024, 2024
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The accuracy of trace gas retrievals from spaceborne observations, like those from the Orbiting Carbon Observatory 2 (OCO-2), are sensitive to the referenced digital elevation model (DEM). Therefore, we evaluate several global DEMs, used in versions 10 and 11 of the OCO-2 retrieval along with the Copernicus DEM. We explore the impacts of changing the DEM on biases in OCO-2-retrieved XCO2 and inferred CO2 fluxes. Our findings led to an update to OCO-2 v11.1 using the Copernicus DEM globally.
Eamon K. Conway, Amir H. Souri, Joshua Benmergui, Kang Sun, Xiong Liu, Carly Staebell, Christopher Chan Miller, Jonathan Franklin, Jenna Samra, Jonas Wilzewski, Sebastien Roche, Bingkun Luo, Apisada Chulakadabba, Maryann Sargent, Jacob Hohl, Bruce Daube, Iouli Gordon, Kelly Chance, and Steven Wofsy
Atmos. Meas. Tech., 17, 1347–1362, https://doi.org/10.5194/amt-17-1347-2024, https://doi.org/10.5194/amt-17-1347-2024, 2024
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The work presented here describes the processes required to convert raw sensor data for the MethaneAIR instrument to geometrically calibrated data. Each algorithm is described in detail. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the EDF. MethaneSAT's goals are to precisely map over 80 % of the production sources of methane emissions from oil and gas fields across the globe to a high degree of accuracy.
Javier Roger, Luis Guanter, Javier Gorroño, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 1333–1346, https://doi.org/10.5194/amt-17-1333-2024, https://doi.org/10.5194/amt-17-1333-2024, 2024
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Methane emissions can be identified using remote sensing, but surface-related structures disturb detection. In this work, a variation of the matched filter method that exploits a large fraction of the near-infrared range (1000–2500 nm) is applied. In comparison to the raw matched filter, it reduces background noise and strongly attenuates the surface-related artifacts, which leads to a greater detection capability. We propose this variation as a standard methodology for methane detection.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
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We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Gregory R. McGarragh, Christopher W. O'Dell, Sean M. R. Crowell, Peter Somkuti, Eric B. Burgh, and Berrien Moore III
Atmos. Meas. Tech., 17, 1091–1121, https://doi.org/10.5194/amt-17-1091-2024, https://doi.org/10.5194/amt-17-1091-2024, 2024
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Carbon dioxide and methane are greenhouse gases that have been rapidly increasing due to human activity since the industrial revolution, leading to global warming and subsequently negative affects on the climate. It is important to measure the concentrations of these gases in order to make climate predictions that drive policy changes to mitigate climate change. GeoCarb aims to measure the concentrations of these gases from space over the Americas at unprecedented spatial and temporal scales.
Jianping Mao, James B. Abshire, S. Randy Kawa, Xiaoli Sun, and Haris Riris
Atmos. Meas. Tech., 17, 1061–1074, https://doi.org/10.5194/amt-17-1061-2024, https://doi.org/10.5194/amt-17-1061-2024, 2024
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NASA Goddard Space Flight Center has developed an integrated-path, differential absorption lidar approach to measure column-averaged atmospheric CO2 (XCO2). We demonstrated the lidar’s capability to measure XCO2 to cloud tops ,as well as to the ground, with the data from the summer 2017 airborne campaign in the US and Canada. This active remote sensing technique can provide all-sky data coverage and high-quality XCO2 measurements for future airborne science campaigns and space missions.
Jong-Uk Park, Hyun-Jae Kim, Jin-Soo Park, Jinsoo Choi, Sang Seo Park, Kangho Bae, Jong-Jae Lee, Chang-Keun Song, Soojin Park, Kyuseok Shim, Yeonsoo Cho, and Sang-Woo Kim
Atmos. Meas. Tech., 17, 197–217, https://doi.org/10.5194/amt-17-197-2024, https://doi.org/10.5194/amt-17-197-2024, 2024
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The high-spatial-resolution NO2 vertical column densities (VCDs) were measured from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas in South Korea with the newly developed versatile NO2 VCD retrieval algorithm apt to be applied to the instruments with volatile optical and radiometric properties. The airborne HIS observations emphasized the intensifying satellite sub-grid variability in NO2 VCDs near the emission sources.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
EGUsphere, https://doi.org/10.5194/egusphere-2023-3047, https://doi.org/10.5194/egusphere-2023-3047, 2023
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Our research, utilizing Gaofen-5b satellite data, detected methane emissions from 32 coal mines and 93 plume events in Shanxi, China, showing significant variability among sources. Emission rates spanned from 857.67 to 14333.02 kg·h-1. This study highlights satellites' capacity to monitor specific methane origins, offering valuable support in reducing greenhouse gas emissions.
William R. Keely, Steffen Mauceri, Sean Crowell, and Christopher W. O'Dell
Atmos. Meas. Tech., 16, 5725–5748, https://doi.org/10.5194/amt-16-5725-2023, https://doi.org/10.5194/amt-16-5725-2023, 2023
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Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
Karl Voglmeier, Voltaire Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-220, https://doi.org/10.5194/amt-2023-220, 2023
Revised manuscript accepted for AMT
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Comparison of total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminate these seasonally varying differences by applying new ozone absorption cross-sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 5609–5645, https://doi.org/10.5194/amt-16-5609-2023, https://doi.org/10.5194/amt-16-5609-2023, 2023
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This paper describes a new version (V8) of ozone data from MIPAS middle-atmosphere spectra. The dataset comprises high-quality ozone profiles from 20 to 100 km, with pole-to-pole latitude coverage for the day- and nighttime, spanning 2005 until 2012. An exhaustive treatment of errors has been performed. Compared to other satellite instruments, MIPAS ozone shows a positive bias of 5 %–8 % below 70 km. In the upper mesosphere, this new version agrees much better than previous ones (within 10 %).
Minqiang Zhou, Bavo Langerock, Mahesh Kumar Sha, Christian Hermans, Nicolas Kumps, Rigel Kivi, Pauli Heikkinen, Christof Petri, Justus Notholt, Huilin Chen, and Martine De Mazière
Atmos. Meas. Tech., 16, 5593–5608, https://doi.org/10.5194/amt-16-5593-2023, https://doi.org/10.5194/amt-16-5593-2023, 2023
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Simon Warnach, Holger Sihler, Christian Borger, Nicole Bobrowski, Steffen Beirle, Ulrich Platt, and Thomas Wagner
Atmos. Meas. Tech., 16, 5537–5573, https://doi.org/10.5194/amt-16-5537-2023, https://doi.org/10.5194/amt-16-5537-2023, 2023
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BrO inside volcanic gas plumes but can be used in combination with SO2 to characterize the volcanic property and its activity state. High-quality satellite observations can provide a global inventory of this important quantity. This paper investigates how to accurately detect BrO inside volcanic plumes from the satellite UV spectrum. A sophisticated novel non-volcanic background correction scheme is presented, and systematic errors including cross-interference with formaldehyde are minimized.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
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Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Lieven Clarisse, Bruno Franco, Martin Van Damme, Tommaso Di Gioacchino, Juliette Hadji-Lazaro, Simon Whitburn, Lara Noppen, Daniel Hurtmans, Cathy Clerbaux, and Pierre Coheur
Atmos. Meas. Tech., 16, 5009–5028, https://doi.org/10.5194/amt-16-5009-2023, https://doi.org/10.5194/amt-16-5009-2023, 2023
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Ammonia is an important atmospheric pollutant. This article presents version 4 of the algorithm which retrieves ammonia abundances from the infrared measurements of the satellite sounder IASI. A measurement operator is introduced that can emulate the measurements (so-called averaging kernels) and measurement uncertainty is better characterized. Several other changes to the product itself are also documented, most of which improve the temporal consistency of the 2007–2022 IASI NH3 dataset.
Vladimir Savastiouk, Henri Diémoz, and C. Thomas McElroy
Atmos. Meas. Tech., 16, 4785–4806, https://doi.org/10.5194/amt-16-4785-2023, https://doi.org/10.5194/amt-16-4785-2023, 2023
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This paper describes a way to significantly improve ozone measurements at low sun elevations and large ozone amounts when using the Brewer ozone spectrophotometer. The proposed algorithm will allow more uniform ozone measurements across the monitoring network. This will contribute to more reliable trend analysis and support the satellite validation. This research contributes to better understanding the physics of the instrument, and the new algorithm is based on this new knowledge.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
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Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and Andre Butz
EGUsphere, https://doi.org/10.5194/egusphere-2023-1857, https://doi.org/10.5194/egusphere-2023-1857, 2023
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
EGUsphere, https://doi.org/10.31223/X53M42, https://doi.org/10.31223/X53M42, 2023
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak, and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 415 +/- 321 t/hr.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-194, https://doi.org/10.5194/amt-2023-194, 2023
Revised manuscript accepted for AMT
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Philipp Hochstaffl, Franz Schreier, Claas Henning Köhler, Andreas Baumgartner, and Daniele Cerra
Atmos. Meas. Tech., 16, 4195–4214, https://doi.org/10.5194/amt-16-4195-2023, https://doi.org/10.5194/amt-16-4195-2023, 2023
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The study examines methane enhancements inferred from hyperspectral imaging observations using different retrieval schemes. One of the core challenges is the high spatial and moderate spectral resolution as it makes separation of spectral variations caused by molecular absorption and surface reflectivity challenging. It was found that localized methane enhancements can be detected and quantified from HySpex airborne observations using various retrieval schemes.
Wenyu Wang, Jian Xu, and Zhenzhan Wang
Atmos. Meas. Tech., 16, 4137–4153, https://doi.org/10.5194/amt-16-4137-2023, https://doi.org/10.5194/amt-16-4137-2023, 2023
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This article presents a study for feasibility analysis of atmospheric wind measurement using a terahertz (THz) passive limb radiometer with high spectral resolution. The simulations show that line-of-sight wind from 40 to 120 km can be obtained better than 10 m s−1 (at most altitudes it is better than 5 m s−1) using the O3, O2, H2O, and OI bands. This study will provide reference for future payload design.
Wei Huang, Lei Liu, Bin Yang, Shuai Hu, Wanying Yang, Zhenfeng Li, Wantong Li, and Xiaofan Yang
Atmos. Meas. Tech., 16, 4101–4114, https://doi.org/10.5194/amt-16-4101-2023, https://doi.org/10.5194/amt-16-4101-2023, 2023
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To improve the retrieval speed of the AERI optimal estimation (AERIoe) method, a fast-retrieval algorithm named Fast AERIoe is proposed on the basis of the findings that the change in Jacobians during the retrieval process had little effect on the performance of AERIoe. The results of the experiment show that the retrieved profiles from Fast AERIoe are comparable to those of AERIoe and that the retrieval speed is significantly improved, with the average retrieval time reduced by 59 %.
Rafaella Chiarella, Matthias Buschmann, Joshua Laughner, Isamu Morino, Justus Notholt, Christof Petri, Geoffrey Toon, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 16, 3987–4007, https://doi.org/10.5194/amt-16-3987-2023, https://doi.org/10.5194/amt-16-3987-2023, 2023
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The goal is to establish a window and strategy for xCO2 retrieval from ground-based Fourier transform spectrometers for NDACC. In the study we describe the spectroscopy of the region, the locations and instruments used, and the methods of calculating the retrieved xCO2. We performed tests to assess the sensitivity to diverse factors and sources of errors while comparing the retrieval to a well-established xCO2 retrieval from TCCON.
Jack Bruno, Dylan Jervis, Daniel Varon, and Daniel Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2023-1343, https://doi.org/10.5194/egusphere-2023-1343, 2023
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Methane is a potent greenhouse gas and a current high priority target for short/mid term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing and the data volume is outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high spatial resolution satellite data.
Zhao-Cheng Zeng, Lu Lee, Chengli Qi, Lieven Clarisse, and Martin Van Damme
Atmos. Meas. Tech., 16, 3693–3713, https://doi.org/10.5194/amt-16-3693-2023, https://doi.org/10.5194/amt-16-3693-2023, 2023
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This study presents an NH3 retrieval algorithm based on the optimal estimation method for the Geostationary Interferometric Infrared Sounder (GIIRS) on board China’s FengYun-4B satellite (FY-4B/GIIRS). Retrieval results demonstrate the capability of FY-4B/GIIRS in capturing the diurnal NH3 changes in East Asia. This operational geostationary observation by FY-4B/GIIRS represents an important advancement over the twice-per-day observations provided by current low-Earth-orbit (LEO) instruments.
Ethan Runge, Jeff Langille, Daniel Zawada, Adam Bourassa, and Doug Degenstein
Atmos. Meas. Tech., 16, 3123–3139, https://doi.org/10.5194/amt-16-3123-2023, https://doi.org/10.5194/amt-16-3123-2023, 2023
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The Limb Imaging Fourier Transform Spectrometer Experiment (LIFE) instrument takes vertical images of limb radiance across a wide mid-infrared spectral band from a stratospheric balloon. Measurements are used to infer vertical-trace-gas-profile retrievals of H2O, O3, HNO3, CH4, and N2O. Nearly time-/space-coincident observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Microwave Limb Sounder (MLS) instruments are compared to the LIFE results.
Zhao-Cheng Zeng, Lu Lee, and Chengli Qi
Atmos. Meas. Tech., 16, 3059–3083, https://doi.org/10.5194/amt-16-3059-2023, https://doi.org/10.5194/amt-16-3059-2023, 2023
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Observations from geostationary orbit provide contiguous coverage with a high temporal resolution, representing an important advancement over current low-Earth-orbit instruments. Using measurements from GIIRS on board China's FengYun satellite, the world’s first geostationary hyperspectral infrared sounder, we showed the first results of diurnal CO in eastern Asia from a geostationary orbit, which will have great potential in improving local and global air quality and climate research.
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya Garcia-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel Lopez-Puertas, and Gabriele P. Stiller
EGUsphere, https://doi.org/10.5194/egusphere-2023-919, https://doi.org/10.5194/egusphere-2023-919, 2023
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument onboard the ENVIronmental SATellite (ENVISAT) during 2002 to 2012. Monitoring of these gases is of scientific interest, because both of them are strong greenhouse gases. We analyse the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Tobias Borsdorff, Teresa Campos, Natalie Kille, Kyle J. Zarzana, Rainer Volkamer, and Jochen Landgraf
Atmos. Meas. Tech., 16, 3027–3038, https://doi.org/10.5194/amt-16-3027-2023, https://doi.org/10.5194/amt-16-3027-2023, 2023
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ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O’Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
EGUsphere, https://doi.org/10.5194/egusphere-2023-1163, https://doi.org/10.5194/egusphere-2023-1163, 2023
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We describe a new bromine monoxide (BrO) product from the OMPS-NM instrument onboard the Suomi-NPP satellite. This product provides global stratospheric and tropospheric columns separately for nearly a decade, a feature that is currently rare in publicly available datasets. Both stratospheric and the tropospheric BrO vertical columns from OMPS-NM demonstrate good agreement with ground-based observations from three stations (Lauder, Utqiag ̇vik, and Harestua).
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca C. Baier, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 2601–2625, https://doi.org/10.5194/amt-16-2601-2023, https://doi.org/10.5194/amt-16-2601-2023, 2023
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We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 1.51 ppb (~ 2 %) for CO and 5.09 ppm (~ 1.25 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
EGUsphere, https://doi.org/10.5194/egusphere-2023-563, https://doi.org/10.5194/egusphere-2023-563, 2023
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Methane is a potent greenhouse gas responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions is an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images, and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Manuel López-Puertas, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, https://doi.org/10.5194/amt-16-2167-2023, 2023
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New global nitric oxide (NO) volume-mixing-ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK-IAA MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on ESA version 8 calibration and were processed using an improved retrieval approach.
Adrien Vu Van, Anne Boynard, Pascal Prunet, Dominique Jolivet, Olivier Lezeaux, Patrice Henry, Claude Camy-Peyret, Lieven Clarisse, Bruno Franco, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 16, 2107–2127, https://doi.org/10.5194/amt-16-2107-2023, https://doi.org/10.5194/amt-16-2107-2023, 2023
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With its near-real-time observations and good horizontal coverage, the Infrared Atmospheric Sounding Interferometer (IASI) instrument can contribute to the monitoring systems for a systematic and continuous detection of exceptional atmospheric events such as fires, anthropogenic pollution episodes, volcanic eruptions, or industrial releases. In this paper, a new approach is described for the detection and characterization of unexpected events in terms of trace gases using IASI radiance spectra.
Ian Ashpole and Aldona Wiacek
Atmos. Meas. Tech., 16, 1923–1949, https://doi.org/10.5194/amt-16-1923-2023, https://doi.org/10.5194/amt-16-1923-2023, 2023
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The MOPITT instrument has been measuring atmospheric carbon monoxide (CO) from space since 2000. Its data products are valuable for CO trend analysis. This paper compares products with different spatial resolutions to identify discrepancies in mean CO amounts and detectable trends for coastal grid boxes. It is found that CO amounts and trends differ significantly between data products for a large number of these grid boxes, essentially due to how the coarser-resolution products are created.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Thomas Wagner, Simon Warnach, Steffen Beirle, Nicole Bobrowski, Adrian Jost, Janis Puķīte, and Nicolas Theys
Atmos. Meas. Tech., 16, 1609–1662, https://doi.org/10.5194/amt-16-1609-2023, https://doi.org/10.5194/amt-16-1609-2023, 2023
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We investigate 3D effects of volcanic plumes on the retrieval results of satellite and ground-based UV–Vis observations. With its small ground pixels of 3.5 x 5.5 km², the TROPOMI instrument can detect much smaller volcanic plumes than previous instruments. At the same time, 3D effects become important. The effect of horizontal photon paths especially can lead to a strong underestimation of the derived plume contents of up to > 50 %, which can be further increased for strong absorbers like SO2.
Congcong Qiao, Song Liu, Juan Huo, Xihan Mu, Ping Wang, Shengjie Jia, Xuehua Fan, and Minzheng Duan
Atmos. Meas. Tech., 16, 1539–1549, https://doi.org/10.5194/amt-16-1539-2023, https://doi.org/10.5194/amt-16-1539-2023, 2023
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We established a spectral-fitting method to derive precipitable water vapor (PWV) and aerosol optical depth based on a strict radiative transfer theory by the spectral measurements of direct sun from EKO MS711 and MS712 spectroradiometers. The retrievals were compared with that of the colocated CE-318 photometer; the results showed a high degree of consistency. In the PWV inversion, a strong water vapor absorption band around 1370 nm is introduced to retrieve PWV in a relatively dry atmosphere.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, https://doi.org/10.5194/amt-16-1443-2023, 2023
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A new ozone data set, derived from radiation measurements of the space-borne instrument MIPAS, is presented. It consists of more than 2 million single ozone profiles from 2002–2012, covering virtually all latitudes and altitudes between 5 and 70 km. Progress in data calibration and processing methods allowed for significant improvement of the data quality, compared to previous data versions. Hence, the data set will help to better understand e.g. the time evolution of ozone in the stratosphere.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
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Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
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Short summary
The Orbiting Carbon Observatory-2 makes space-based measurements of reflected sunlight. Using a retrieval algorithm these measurements are converted to CO2 concentrations in the atmosphere. However, the converted CO2 concentrations contain errors for observations close to clouds. Using a simple machine learning approach, we developed a model to correct these remaining errors. The model is able to reduce errors over land and ocean by 20 % and 40 %, respectively.
The Orbiting Carbon Observatory-2 makes space-based measurements of reflected sunlight. Using a...
