Articles | Volume 13, issue 9
https://doi.org/10.5194/amt-13-4619-2020
© Author(s) 2020. 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-13-4619-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Aug 2020
Research article |
| 31 Aug 2020
| 31 Aug 2020
Establishment of AIRS climate-level radiometric stability using radiance anomaly retrievals of minor gases and sea surface temperature
Department of Physics and JCET, University of Maryland Baltimore County, Baltimore, MD, USA
Sergio DeSouza-Machado
Department of Physics and JCET, University of Maryland Baltimore County, Baltimore, MD, USA
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Sergio DeSouza-Machado, L. Larrabee Strow, Howard Motteler, and Scott Hannon
Atmos. Meas. Tech., 13, 323–339, https://doi.org/10.5194/amt-13-323-2020, https://doi.org/10.5194/amt-13-323-2020, 2020
Short summary
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The current instruments being used for weather forecasting and climate require accurate radiative transfer codes to process the acquired data. In addition the codes are becoming more realistic, as they can now account for the effects of cloud and aerosols, rather than only simulating radiances for a clear sky. We describe a fast, accurate, and general purpose code that we have developed to help model data from these instruments.
Sergio DeSouza-Machado, L. Larrabee Strow, Andrew Tangborn, Xianglei Huang, Xiuhong Chen, Xu Liu, Wan Wu, and Qiguang Yang
Atmos. Meas. Tech., 11, 529–550, https://doi.org/10.5194/amt-11-529-2018, https://doi.org/10.5194/amt-11-529-2018, 2018
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Thermodynamic fields retrieved from orbiting infrared sounders use a
derived set of measurements as their starting point, rather than the
actual observations. This leads to problems with noise and
sampling. We have developed a fast accurate model with a simple
vertical representation of clouds in the atmosphere for use in
retrievals, which allows us to use all the actual low-noise
measurements at full resolution. These should eventually help produce
more accurate weather forecasts.
Dejian Fu, Kevin W. Bowman, Helen M. Worden, Vijay Natraj, John R. Worden, Shanshan Yu, Pepijn Veefkind, Ilse Aben, Jochen Landgraf, Larrabee Strow, and Yong Han
Atmos. Meas. Tech., 9, 2567–2579, https://doi.org/10.5194/amt-9-2567-2016, https://doi.org/10.5194/amt-9-2567-2016, 2016
Juying X. Warner, Zigang Wei, L. Larrabee Strow, Russell R. Dickerson, and John B. Nowak
Atmos. Chem. Phys., 16, 5467–5479, https://doi.org/10.5194/acp-16-5467-2016, https://doi.org/10.5194/acp-16-5467-2016, 2016
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We present the global distributions of tropospheric ammonia observed by the satellite sensor AIRS from September 2002 through August 2015. The AIRS instrument captures the ammonia concentrations emitted from the anthropogenic (agricultural) source regions where a summer maximum and secondary spring maximum are observable, and the high ammonia concentrations from episodic biomass burning events.
S. DeSouza-Machado, L. Strow, E. Maddy, O. Torres, G. Thomas, D. Grainger, and A. Robinson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-443-2015, https://doi.org/10.5194/amtd-8-443-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
The Atmospheric Infrared Sounder (AIRS) and the Moderate Resolution
Imaging Spectroradiometer (MODIS) are instruments on the 1.30 pm polar
orbiting Aqua spacecraft. We describe a daytime estimation of dust and
volcanic ash layer heights, using a retrieval algorithm that uses the
information in the AIRS L1B thermal infrared data, constrained by the
MODIS L2 aerosol optical depths. CALIOP aerosol centroid heights are
used for dust height comparisons, as are AATSR volcanic plume heights.
A. Tangborn, L. L. Strow, B. Imbiriba, L. Ott, and S. Pawson
Atmos. Chem. Phys., 13, 4487–4500, https://doi.org/10.5194/acp-13-4487-2013, https://doi.org/10.5194/acp-13-4487-2013, 2013
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169, https://doi.org/10.5194/egusphere-2025-169, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Satellites have observed earth's emission of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about the earth and atmosphere. We present a tool that runs alongside global climate models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Xavier Calbet, Cintia Carbajal Henken, Sergio DeSouza-Machado, Bomin Sun, and Tony Reale
Atmos. Meas. Tech., 15, 7105–7118, https://doi.org/10.5194/amt-15-7105-2022, https://doi.org/10.5194/amt-15-7105-2022, 2022
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Water vapor concentration in the atmosphere at small scales (< 6 km) is considered. The measurements show Gaussian random field behavior following Kolmogorov's theory of turbulence two-thirds law. These properties can be useful when estimating the water vapor variability within a given observed satellite scene or when different water vapor measurements have to be merged consistently.
Sergio DeSouza-Machado, L. Larrabee Strow, Howard Motteler, and Scott Hannon
Atmos. Meas. Tech., 13, 323–339, https://doi.org/10.5194/amt-13-323-2020, https://doi.org/10.5194/amt-13-323-2020, 2020
Short summary
Short summary
The current instruments being used for weather forecasting and climate require accurate radiative transfer codes to process the acquired data. In addition the codes are becoming more realistic, as they can now account for the effects of cloud and aerosols, rather than only simulating radiances for a clear sky. We describe a fast, accurate, and general purpose code that we have developed to help model data from these instruments.
Xavier Calbet, Niobe Peinado-Galan, Sergio DeSouza-Machado, Emil Robert Kursinski, Pedro Oria, Dale Ward, Angel Otarola, Pilar Rípodas, and Rigel Kivi
Atmos. Meas. Tech., 11, 6409–6417, https://doi.org/10.5194/amt-11-6409-2018, https://doi.org/10.5194/amt-11-6409-2018, 2018
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The hypothesis whether turbulence within the passive microwave sounders field of view can cause significant biases in radiative transfer modelling at the 183 GHz water vapour absorption band is tested. It is shown that this effect can cause significant biases, which can match the observed ones by Brogniez et al. (2016). They can be explained by locating intense turbulence in the high troposphere, such as the one present in clear air turbulence, cumulus clouds or storms.
Sergio DeSouza-Machado, L. Larrabee Strow, Andrew Tangborn, Xianglei Huang, Xiuhong Chen, Xu Liu, Wan Wu, and Qiguang Yang
Atmos. Meas. Tech., 11, 529–550, https://doi.org/10.5194/amt-11-529-2018, https://doi.org/10.5194/amt-11-529-2018, 2018
Short summary
Short summary
Thermodynamic fields retrieved from orbiting infrared sounders use a
derived set of measurements as their starting point, rather than the
actual observations. This leads to problems with noise and
sampling. We have developed a fast accurate model with a simple
vertical representation of clouds in the atmosphere for use in
retrievals, which allows us to use all the actual low-noise
measurements at full resolution. These should eventually help produce
more accurate weather forecasts.
Dejian Fu, Kevin W. Bowman, Helen M. Worden, Vijay Natraj, John R. Worden, Shanshan Yu, Pepijn Veefkind, Ilse Aben, Jochen Landgraf, Larrabee Strow, and Yong Han
Atmos. Meas. Tech., 9, 2567–2579, https://doi.org/10.5194/amt-9-2567-2016, https://doi.org/10.5194/amt-9-2567-2016, 2016
Juying X. Warner, Zigang Wei, L. Larrabee Strow, Russell R. Dickerson, and John B. Nowak
Atmos. Chem. Phys., 16, 5467–5479, https://doi.org/10.5194/acp-16-5467-2016, https://doi.org/10.5194/acp-16-5467-2016, 2016
Short summary
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We present the global distributions of tropospheric ammonia observed by the satellite sensor AIRS from September 2002 through August 2015. The AIRS instrument captures the ammonia concentrations emitted from the anthropogenic (agricultural) source regions where a summer maximum and secondary spring maximum are observable, and the high ammonia concentrations from episodic biomass burning events.
S. DeSouza-Machado, L. Strow, E. Maddy, O. Torres, G. Thomas, D. Grainger, and A. Robinson
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-443-2015, https://doi.org/10.5194/amtd-8-443-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
The Atmospheric Infrared Sounder (AIRS) and the Moderate Resolution
Imaging Spectroradiometer (MODIS) are instruments on the 1.30 pm polar
orbiting Aqua spacecraft. We describe a daytime estimation of dust and
volcanic ash layer heights, using a retrieval algorithm that uses the
information in the AIRS L1B thermal infrared data, constrained by the
MODIS L2 aerosol optical depths. CALIOP aerosol centroid heights are
used for dust height comparisons, as are AATSR volcanic plume heights.
A. Tangborn, L. L. Strow, B. Imbiriba, L. Ott, and S. Pawson
Atmos. Chem. Phys., 13, 4487–4500, https://doi.org/10.5194/acp-13-4487-2013, https://doi.org/10.5194/acp-13-4487-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Carbon dioxide (CO2) and methane (CH4) are the main anthropogenic greenhouse gases. The European Copernicus CO2 monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.
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This study explores differences between remote sensing and in situ instruments in terms of their vertical, horizontal, and temporal sampling differences. Understanding and resolving these differences are critical for future analyses linking satellite, ground-based remote sensing, and in situ observations in air quality monitoring. It shows that the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
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Atmos. Meas. Tech., 17, 6485–6516, https://doi.org/10.5194/amt-17-6485-2024, https://doi.org/10.5194/amt-17-6485-2024, 2024
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This paper presents a new machine learning model that allows us to compute NO2 concentration profiles from satellite observations. A neural network was trained on synthetic data from the regional chemistry and transport model WRF-Chem. This is the first model of its kind. We present a thorough model validation study, covering various seasons and regions of the world.
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
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CHORA, an advanced cloud convective differential technique, enhances the accuracy of tropospheric-ozone retrievals. Unlike the traditional Pacific cloud reference sector scheme, CHORA introduces a local-cloud reference sector and an alternative approach (CLCT) for precision. Analysing monthly averaged TROPOMI data from 2018 to 2022 and validating with SHADOZ ozonesonde data, CLCT outperforms other methods and so is the preferred choice, especially in future geostationary satellite missions.
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-182, https://doi.org/10.5194/amt-2024-182, 2024
Revised manuscript accepted for AMT
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We developed an advanced POMINO algorithm for global retrieval of TROPOMI HCHO and NO2 VCDs with much improved consistency. Sensitivity tests demonstrate the complexity and non-linear interactions of auxiliary parameters in the AMF calculation. An improved agreement is found with measurements from a global ground-based instrument network. The POMINO retrieval provides a useful source of information for studies combining HCHO and NO2.
Minqiang Zhou, Pucai Wang, Bart Dils, Bavo Langerock, Geoff Toon, Christian Hermans, Weidong Nan, Qun Cheng, and Martine De Mazière
Atmos. Meas. Tech., 17, 6385–6396, https://doi.org/10.5194/amt-17-6385-2024, https://doi.org/10.5194/amt-17-6385-2024, 2024
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Solar absorption spectra near 2967 cm−1 recorded by a ground-based FTIR with a high spectral resolution of 0.0035 cm-1 are applied to retrieve C3H8 columns for the first time in Xianghe, China, within the NDACC-IRWG. The mean and standard deviation of the C3H8 columns are 1.80 ± 0.81 (1σ) × 1015 molec. cm-2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R = 0.84) and C2H2 (R = 0.79), as well as between C3H8 and CO (R = 0.72).
Farrer Owsley-Brown, Martin J. Wooster, Mark J. Grosvenor, and Yanan Liu
Atmos. Meas. Tech., 17, 6247–6264, https://doi.org/10.5194/amt-17-6247-2024, https://doi.org/10.5194/amt-17-6247-2024, 2024
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Landscape fires produce vast amounts of smoke, affecting the atmosphere locally and globally. Whether a fire is flaming or smouldering strongly impacts the rate at which smoke is produced as well as its composition. This study tested two methods to determine these combustion phases in laboratory fires and compared them to the smoke emitted. One of these methods improved estimates of smoke emission significantly. This suggests potential for improvement in global emission estimates.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Theodore K. Koenig, François Hendrick, Douglas Kinnison, Christopher F. Lee, Michel Van Roozendael, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5911–5934, https://doi.org/10.5194/amt-17-5911-2024, https://doi.org/10.5194/amt-17-5911-2024, 2024
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Atmospheric bromine destroys ozone, impacts oxidation capacity, and oxidizes mercury into its toxic form. We constrain bromine by remote sensing of BrO from a mountaintop. Previous measurements retrieved two to three pieces of information vertically; we apply new methods to get five and a half vertically and two more in time. We compare with aircraft measurements to validate the methods and look at variations in BrO over the Pacific.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
Frank Hase, Paolo Castracane, Angelika Dehn, Omaira Elena García, David W. T. Griffith, Lukas Heizmann, Nicholas B. Jones, Tomi Karppinen, Rigel Kivi, Martine de Mazière, Justus Notholt, and Mahesh Kumar Sha
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-140, https://doi.org/10.5194/amt-2024-140, 2024
Revised manuscript accepted for AMT
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The primary measurement result delivered by a Fourier Transform spectrometer is an interferogram, and the spectrum required for further analysis needs to be calculated from the interferogram by a Fourier analysis. The paper deals with technical aspects of this process and shows how the reconstruction of the spectrum can be optimized.
Edward Malina, Jure Brence, Jennifer Adams, Jovan Tanevski, Sašo Džeroski, Valentin Kantchev, and Kevin W. Bowman
EGUsphere, https://doi.org/10.5194/egusphere-2024-2392, https://doi.org/10.5194/egusphere-2024-2392, 2024
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The large fleet of Earth Observation satellites in orbit currently generate huge volumes of data, requiring significant computational resources to process in a timely manner. We present a method for predicting poor quality measurements using machine learning. We find that machine learning methods can accurately predict poor quality measurements, and remove them from the processing change, saving time and computational resources.
Chia-Pang Kuo and Christian Kummerow
Atmos. Meas. Tech., 17, 5637–5653, https://doi.org/10.5194/amt-17-5637-2024, https://doi.org/10.5194/amt-17-5637-2024, 2024
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A small satellite about the size of a shoe box, named TEMPEST, carries only a microwave sensor and is designed to measure the water cycle of the Earth from space in an economical way compared with traditional satellites, which have additional infrared sensors. To overcome the limitation, extra infrared signals from GOES-R ABI are combined with TEMPEST microwave measurements. Compared with ground observations, improved humidity information is extracted from the merged TEMPEST and ABI signals.
Christopher Chan Miller, Sébastien Roche, Jonas S. Wilzewski, Xiong Liu, Kelly Chance, Amir H. Souri, Eamon Conway, Bingkun Luo, Jenna Samra, Jacob Hawthorne, Kang Sun, Carly Staebell, Apisada Chulakadabba, Maryann Sargent, Joshua S. Benmergui, Jonathan E. Franklin, Bruce C. Daube, Yang Li, Joshua L. Laughner, Bianca C. Baier, Ritesh Gautam, Mark Omara, and Steven C. Wofsy
Atmos. Meas. Tech., 17, 5429–5454, https://doi.org/10.5194/amt-17-5429-2024, https://doi.org/10.5194/amt-17-5429-2024, 2024
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MethaneSAT is an upcoming satellite mission designed to monitor methane emissions from the oil and gas (O&G) industry globally. Here, we present observations from the first flight campaign of MethaneAIR, a MethaneSAT-like instrument mounted on an aircraft. MethaneAIR can map methane with high precision and accuracy over a typically sized oil and gas basin (~200 km2) in a single flight. This paper demonstrates the capability of the upcoming satellite to routinely track global O&G emissions.
Matthieu Dogniaux and Cyril Crevoisier
Atmos. Meas. Tech., 17, 5373–5396, https://doi.org/10.5194/amt-17-5373-2024, https://doi.org/10.5194/amt-17-5373-2024, 2024
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Many CO2-observing satellite concepts, with very different design choices and trade-offs, are expected to be put into orbit during the upcoming decade. This work uses numerical simulations to explore the impact of critical design parameters on the performance of upcoming CO2-observing satellite concepts.
Francesca Vittorioso, Vincent Guidard, and Nadia Fourrié
Atmos. Meas. Tech., 17, 5279–5299, https://doi.org/10.5194/amt-17-5279-2024, https://doi.org/10.5194/amt-17-5279-2024, 2024
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The future Meteosat Third Generation Infrared Sounder (MTG-IRS) will represent a major innovation for the monitoring of the chemical state of the atmosphere. MTG-IRS will have the advantage of being based on a geostationary platform and acquiring data with a high temporal frequency. This work aims to evaluate its potential impact over Europe within a chemical transport model (MOCAGE). The results indicate that the assimilation of these data always has a positive impact on ozone analysis.
Matthias Schneider, Kinya Toride, Farahnaz Khosrawi, Frank Hase, Benjamin Ertl, Christopher J. Diekmann, and Kei Yoshimura
Atmos. Meas. Tech., 17, 5243–5259, https://doi.org/10.5194/amt-17-5243-2024, https://doi.org/10.5194/amt-17-5243-2024, 2024
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Despite its importance for extreme weather and climate feedbacks, atmospheric convection is not well constrained. This study assesses the potential of novel tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events. We find that the impact of the isotopologues is small for stable atmospheric conditions but significant for unstable conditions, which have the strongest societal impacts (e.g. storms and flooding).
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
Atmos. Meas. Tech., 17, 5261–5277, https://doi.org/10.5194/amt-17-5261-2024, https://doi.org/10.5194/amt-17-5261-2024, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where it is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
EGUsphere, https://doi.org/10.5194/egusphere-2024-2352, https://doi.org/10.5194/egusphere-2024-2352, 2024
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Currently measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver-Julesburg basin where agriculture and methane extraction infrastructure is often co-located.
Tannaz H. Mohammadloo, Matthew Jones, Bas van de Kerkhof, Kyle Dawson, Brendan James Smith, Stephen Conley, Abigail Corbett, and Rutger IJzermans
EGUsphere, https://doi.org/10.5194/egusphere-2024-1175, https://doi.org/10.5194/egusphere-2024-1175, 2024
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Methane is a potent greenhouse gas. Trustable detection and quantification of methane emissions at facility level is critical to identify the largest sources, and to prioritize them for repair. We provide a systematic analysis of the uncertainty in drone-based methane emission surveys, based on theoretical considerations and historical data sets. We provide guidelines to industry on how to avoid or minimize potential errors in drone-based measurements for methane emission quantification.
Xianzhong Duan, Ming Chang, Guotong Wu, Suping Situ, Shengjie Zhu, Qi Zhang, Yibo Huangfu, Weiwen Wang, Weihua Chen, Bin Yuan, and Xuemei Wang
Atmos. Meas. Tech., 17, 4065–4079, https://doi.org/10.5194/amt-17-4065-2024, https://doi.org/10.5194/amt-17-4065-2024, 2024
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Accurately estimating biogenic volatile organic compound (BVOC) emissions in forest ecosystems has been challenging. This research presents a framework that utilizes drone-based lidar, photogrammetry, and image recognition technologies to identify plant species and estimate BVOC emissions. The largest cumulative isoprene emissions were found in the Myrtaceae family, while those of monoterpenes were from the Rubiaceae family.
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, https://doi.org/10.5194/amt-17-3949-2024, 2024
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This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Steffen Beirle and Thomas Wagner
Atmos. Meas. Tech., 17, 3439–3453, https://doi.org/10.5194/amt-17-3439-2024, https://doi.org/10.5194/amt-17-3439-2024, 2024
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We present a new method for estimating emissions and lifetimes for nitrogen oxides emitted from large cities by using satellite NO2 observations combined with wind fields. The estimate is based on the simultaneous evaluation of the downwind plumes for opposing wind directions. This allows us to derive seasonal mean emissions and lifetimes for 100 cities around the globe.
Qiurun Yu, Dylan Jervis, and Yi Huang
Atmos. Meas. Tech., 17, 3347–3366, https://doi.org/10.5194/amt-17-3347-2024, https://doi.org/10.5194/amt-17-3347-2024, 2024
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This study estimated the effects of aerosols on GHGSat satellite methane retrieval and investigated the performance of simultaneously retrieving aerosol and methane information using a multi-angle viewing method. Results suggested that the performance of GHGSat methane retrieval improved when aerosols were considered, and the multi-angle viewing method is insensitive to the satellite angle setting. This performance assessment is useful for improving future GHGSat-like instruments.
Zhonghua He, Ling Gao, Miao Liang, and Zhao-Cheng Zeng
Atmos. Meas. Tech., 17, 2937–2956, https://doi.org/10.5194/amt-17-2937-2024, https://doi.org/10.5194/amt-17-2937-2024, 2024
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Using Gaofen-5B satellite data, this study detected 93 methane plume events from 32 coal mines in Shanxi, China, with emission rates spanning from 761.78 ± 185.00 to 12729.12 ± 4658.13 kg h-1, showing significant variability among sources. This study highlights Gaofen-5B’s capacity for monitoring large methane point sources, offering valuable support in reducing greenhouse gas emissions.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 17, 2849–2871, https://doi.org/10.5194/amt-17-2849-2024, https://doi.org/10.5194/amt-17-2849-2024, 2024
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument on board the Environmental Satellite (Envisat) during 2002 to 2012. Monitoring of these gases is of scientific interest because both of them are strong greenhouse gases. We analyze the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
Atmos. Meas. Tech., 17, 2583–2593, https://doi.org/10.5194/amt-17-2583-2024, https://doi.org/10.5194/amt-17-2583-2024, 2024
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Methane is a potent greenhouse gas that has been responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions comprise an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech., 17, 2317–2334, https://doi.org/10.5194/amt-17-2317-2024, https://doi.org/10.5194/amt-17-2317-2024, 2024
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and André Butz
Atmos. Meas. Tech., 17, 2257–2275, https://doi.org/10.5194/amt-17-2257-2024, https://doi.org/10.5194/amt-17-2257-2024, 2024
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Karl Voglmeier, Voltaire A. Velazco, Luca Egli, Julian Gröbner, Alberto Redondas, and Wolfgang Steinbrecht
Atmos. Meas. Tech., 17, 2277–2294, https://doi.org/10.5194/amt-17-2277-2024, https://doi.org/10.5194/amt-17-2277-2024, 2024
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Comparison between total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminates these seasonally varying differences by applying new ozone absorption cross sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
Jihanne El Haouari, Jean-Michel Gaucel, Christelle Pittet, Jean-Yves Tourneret, and Herwig Wendt
EGUsphere, https://doi.org/10.48550/arXiv.2404.05298, https://doi.org/10.48550/arXiv.2404.05298, 2024
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This paper explores new techniques based on sparse representations for estimating the spectral response functions of high-resolution spectrometers. The method is highly competitive with commonly used parametric models yielding more accurate estimates while accounting for wavelength dependence. The resulting normalized estimation errors of the spectrometer spectral responses are less than 1 %, which will allow better quantification of trace gas concentrations at the Earth surface.
Richard Eastes, J. Scott Evans, Quan Gan, Bill McClintock, and Jerry Lumpe
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-52, https://doi.org/10.5194/amt-2024-52, 2024
Revised manuscript accepted for AMT
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The temperature is essential to understanding the thermosphere. Most temperature measurements have indirect or had large uncertainties, especially in the lower-middle thermosphere where data are rarely available. Since October 2018 NASA’s GOLD mission has produced disk images of neutral temperatures near 160 km at locations over the Americas and Atlantic Ocean. This paper discusses both temperature retrieval techniques and issues in interpreting GOLD’s images of temperatures.
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.
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Short summary
The NASA AIRS satellite instrument has measured the infrared emission of the Earth continuously since 2002. If AIRS measurements are stable, these radiances can provide globally consistent multi-decadal trends of important climate variables, including the Earth's surface temperature, and the atmospheric temperature and humidity vs. height. Using the sensitivity of the AIRS radiances to well-known carbon dioxide trends, we show that AIRS is stable to 0.02 K per decade, well below climate trends.
The NASA AIRS satellite instrument has measured the infrared emission of the Earth continuously...
