Articles | Volume 10, issue 3
https://doi.org/10.5194/amt-10-939-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-10-939-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Characterization of the OCO-2 instrument line shape functions using on-orbit solar measurements
Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA, USA
Xiong Liu
Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA, USA
Caroline R. Nowlan
Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA, USA
Zhaonan Cai
Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA, USA
Kelly Chance
Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA, USA
Christian Frankenberg
Division of Geological and Planetary Science, California Institute of Technology, Pasadena, CA, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Richard A. M. Lee
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Randy Pollock
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Robert Rosenberg
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
David Crisp
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
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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.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
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In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
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.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
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Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Rui Wang, Da Pan, Xuehui Guo, Kang Sun, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, Cathy Clerbaux, Melissa Puchalski, and Mark A. Zondlo
Atmos. Chem. Phys., 23, 13217–13234, https://doi.org/10.5194/acp-23-13217-2023, https://doi.org/10.5194/acp-23-13217-2023, 2023
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Ammonia (NH3) is a key precursor for fine particulate matter (PM2.5) and a primary form of reactive nitrogen, yet it has sparse ground measurements. We perform the first comprehensive comparison between ground observations and satellite retrievals in the US, demonstrating that satellite NH3 data can help fill spatial gaps in the current ground monitoring networks. Trend analyses using both datasets highlight increasing NH3 trends across the US, including the NH3 hotspots and urban areas.
Chantelle R. Lonsdale and Kang Sun
Atmos. Chem. Phys., 23, 8727–8748, https://doi.org/10.5194/acp-23-8727-2023, https://doi.org/10.5194/acp-23-8727-2023, 2023
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The COVID-19 pandemic, which was caused by the SARS-CoV-2 virus, emerged in 2019, and its still evolving variants have resulted in unprecedented shifts in human activities and anthropogenic emissions into the Earth's atmosphere. We present monthly nitrogen oxide emissions over three major continents from May 2018 to January 2023 to capture variations before and after the COVID-19 pandemic. We focus on a diverse collection of 54 cities to quantify the post-COVID-19 perturbations.
Huiqun Wang, Gonzalo González Abad, Chris Chan Miller, Hyeong-Ahn Kwon, Caroline R. Nowlan, Zolal Ayazpour, Heesung Chong, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Kang Sun, Robert Spurr, and Robert J. Hargreaves
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-66, https://doi.org/10.5194/amt-2023-66, 2023
Preprint withdrawn
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A pipeline for retrieving Total Column Water Vapor from satellite blue spectra is developed. New constraints are considered. Water-leaving radiance is important over the oceans. Results agree with reference datasets well under clear conditions. Due to high sensitivity to clouds, strict data filtering criteria are required. All-sky retrievals can be corrected using machine learning. GPS stations’ representation errors follow a power law relationship with grid resolutions.
Zolal Ayazpour, Shiqi Tao, Dan Li, Amy Jo Scarino, Ralph E. Kuehn, and Kang Sun
Atmos. Meas. Tech., 16, 563–580, https://doi.org/10.5194/amt-16-563-2023, https://doi.org/10.5194/amt-16-563-2023, 2023
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Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLHs used in atmospheric models are often inaccurate. Using PBLH observations from the Aircraft Meteorological DAta Relay (AMDAR), we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US that shows a better agreement with reference PBLH observations than commonly used PBLH products.
Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy
Atmos. Meas. Tech., 15, 3721–3745, https://doi.org/10.5194/amt-15-3721-2022, https://doi.org/10.5194/amt-15-3721-2022, 2022
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This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO2 in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
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The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
Kang Sun, Lingbo Li, Shruti Jagini, and Dan Li
Atmos. Chem. Phys., 21, 13311–13332, https://doi.org/10.5194/acp-21-13311-2021, https://doi.org/10.5194/acp-21-13311-2021, 2021
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We bridge the gap between satellite column observations and emissions by accounting for the dynamic lifetime of pollutants due to wind dispersion and the chemical lifetime due to chemical reactions. Applying it to the Po Valley air basin, we derive the monthly emissions of nitrogen oxides using satellite nitrogen dioxide observations. We further quantify the COVID-19-driven decline of emissions and estimate a 22 % decrease in nitrogen oxide emissions due to the pandemic in 2020.
Carly Staebell, Kang Sun, Jenna Samra, Jonathan Franklin, Christopher Chan Miller, Xiong Liu, Eamon Conway, Kelly Chance, Scott Milligan, and Steven Wofsy
Atmos. Meas. Tech., 14, 3737–3753, https://doi.org/10.5194/amt-14-3737-2021, https://doi.org/10.5194/amt-14-3737-2021, 2021
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Given the high global warming potential of CH4, the identification and subsequent reduction of anthropogenic CH4 emissions presents a significant opportunity for climate change mitigation. Satellites are an integral piece of this puzzle, providing data to quantify emissions at a variety of spatial scales. This work presents the spectral calibration of MethaneAIR, the airborne instrument used as a test bed for the forthcoming MethaneSAT satellite.
Juseon Bak, Xiong Liu, Kang Sun, Kelly Chance, and Jae-Hwan Kim
Atmos. Meas. Tech., 12, 3777–3788, https://doi.org/10.5194/amt-12-3777-2019, https://doi.org/10.5194/amt-12-3777-2019, 2019
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This work improves OMI ozone profile retrievals by accounting for spectral fit residuals caused by slit function errors as a pseudo absorber in the optimal-estimation-based spectral fitting process.
Kang Sun, Lei Zhu, Karen Cady-Pereira, Christopher Chan Miller, Kelly Chance, Lieven Clarisse, Pierre-François Coheur, Gonzalo González Abad, Guanyu Huang, Xiong Liu, Martin Van Damme, Kai Yang, and Mark Zondlo
Atmos. Meas. Tech., 11, 6679–6701, https://doi.org/10.5194/amt-11-6679-2018, https://doi.org/10.5194/amt-11-6679-2018, 2018
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An agile, physics-based approach is developed to oversample irregular satellite observations to a high-resolution common grid. Instead of assuming each sounding as a point or a polygon as in previous methods, the proposed physical oversampling represents soundings as distributions of sensitivity on the ground. This sensitivity distribution can be determined by the spatial response function of each satellite sensor, parameterized as generalized 2-D super Gaussian functions.
Juseon Bak, Xiong Liu, Jae-Hwan Kim, David P. Haffner, Kelly Chance, Kai Yang, and Kang Sun
Atmos. Meas. Tech., 10, 4373–4388, https://doi.org/10.5194/amt-10-4373-2017, https://doi.org/10.5194/amt-10-4373-2017, 2017
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This paper verifies and corrects the Ozone Mapping and Profiler Suite (OMPS) nadir mapper (NM) level 1B v2.0 measurements to retrieve reliable ozone profile and tropospheric ozone using an optimal estimation inversion with the fitting window of 302.5–340 nm. We apply "soft calibration" and "common mode correction" to OMPS radiances to eliminate systematic errors in the fitting residuals and derive random-noise measurement errors accounting for both OMPS radiances and forward model calculation.
Kang Sun, Xiong Liu, Guanyu Huang, Gonzalo González Abad, Zhaonan Cai, Kelly Chance, and Kai Yang
Atmos. Meas. Tech., 10, 3677–3695, https://doi.org/10.5194/amt-10-3677-2017, https://doi.org/10.5194/amt-10-3677-2017, 2017
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This study derives on-orbit slit functions from the OMI irradiance spectra. The results differ from the widely used preflight slit functions. The on-orbit changes of OMI slit functions are insignificant over time after accounting for the solar activity. Applying the derived on-orbit slit functions to ozone-profile retrieval shows substantial improvements over the preflight slit functions based on comparisons with ozonesonde validations.
David Crisp, Harold R. Pollock, Robert Rosenberg, Lars Chapsky, Richard A. M. Lee, Fabiano A. Oyafuso, Christian Frankenberg, Christopher W. O'Dell, Carol J. Bruegge, Gary B. Doran, Annmarie Eldering, Brendan M. Fisher, Dejian Fu, Michael R. Gunson, Lukas Mandrake, Gregory B. Osterman, Florian M. Schwandner, Kang Sun, Tommy E. Taylor, Paul O. Wennberg, and Debra Wunch
Atmos. Meas. Tech., 10, 59–81, https://doi.org/10.5194/amt-10-59-2017, https://doi.org/10.5194/amt-10-59-2017, 2017
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The Orbiting Carbon Observatory-2 carries and points a three-channel imaging grating spectrometer designed to collect high-resolution spectra of reflected sunlight within the molecular oxygen A-band at 0.765 microns and the carbon dioxide bands at 1.61 and 2.06 microns. Here, we describe the OCO-2 instrument, its data products, and its performance during its first 18 months in orbit.
Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Jianxiong Sheng, Kang Sun, Xiong Liu, Kelly Chance, Ilse Aben, Jason McKeever, and Christian Frankenberg
Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, https://doi.org/10.5194/acp-16-14371-2016, 2016
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Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned to launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify methane emissions from the global scale down to the scale of point sources.
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.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
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In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
Yitong Yao, Philippe Ciais, Emilie Joetzjer, Wei Li, Lei Zhu, Yujie Wang, Christian Frankenberg, and Nicolas Viovy
Earth Syst. Dynam., 15, 763–778, https://doi.org/10.5194/esd-15-763-2024, https://doi.org/10.5194/esd-15-763-2024, 2024
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Elevated CO2 concentration (eCO2) is critical for shaping the future path of forest carbon uptake, while uncertainties remain about concurrent carbon loss. Here, we found that eCO2 might amplify competition-induced carbon loss, while the extent of drought-induced carbon loss hinges on the balance between heightened biomass density and water-saving benefits. This is the first time that such carbon loss responses to ongoing climate change have been quantified separately over the Amazon rainforest.
Tianlang Zhao, Jingqiu Mao, Zolal Ayazpour, Gonzalo González Abad, Caroline R. Nowlan, and Yiqi Zheng
Atmos. Chem. Phys., 24, 6105–6121, https://doi.org/10.5194/acp-24-6105-2024, https://doi.org/10.5194/acp-24-6105-2024, 2024
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HCHO variability is a key tracer in understanding VOC emissions in response to climate change. We investigate the role of methane oxidation and biogenic and wildfire emissions in HCHO interannual variability over northern high latitudes in summer, emphasizing wildfires as a key driver of HCHO interannual variability in Alaska, Siberia and northern Canada using satellite HCHO and SIF retrievals and then GEOS-Chem model. We show SIF is a tool to understand biogenic HCHO variability in this region.
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).
Juliëtte C. S. Anema, Klaas Folkert Boersma, Piet Stammes, Gerbrand Koren, William Woodgate, Philipp Köhler, Christian Frankenberg, and Jacqui Stol
Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
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To keep the Paris agreement goals within reach, negative emissions are necessary. They can be achieved with mitigation techniques, such as reforestation, which remove CO2 from the atmosphere. While governments have pinned their hopes on them, there is not yet a good set of tools to objectively determine whether negative emissions do what they promise. Here we show how satellite measurements of plant fluorescence are useful in detecting carbon uptake due to reforestation and vegetation regrowth.
Jin Liao, Glenn M. Wolfe, Alex E. Kotsakis, Julie M. Nicely, Jason M. St. Clair, Thomas F. Hanisco, Gonzalo Gonzalez Abad, Caroline R. Nowlan, Zolal Ayazpour, Isabelle De Smedt, Eric C. Apel, and Rebecca S. Hornbrook
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-72, https://doi.org/10.5194/amt-2024-72, 2024
Revised manuscript accepted for AMT
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Validation of satellite HCHO over the remote marine regions is relatively few and modeled HCHO in these regions is usually added as a global satellite HCHO background. This paper intercompares three satellite HCHO retrievals and validates them against in situ observations from the NASA ATom mission. All retrievals are correlated with ATom integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. A persistent low bias is found in all retrievals at high latitudes.
Russell Doughty, Yujie Wang, Jennifer Johnson, Nicholas Parazoo, Troy Magney, Zoe Pierrat, Xiangming Xiao, Luis Guanter, Philipp Köhler, Christian Frankenberg, Peter Somkuti, Shuang Ma, Yuanwei Qin, Sean Crowell, and Berrien Moore III
EGUsphere, https://doi.org/10.22541/essoar.168167172.20799710/v1, https://doi.org/10.22541/essoar.168167172.20799710/v1, 2024
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Here we present a novel model of global photosynthesis, ChloFluo, which uses spaceborne chlorophyll fluorescence to estimate the amount of photosynthetically active radiation absorbed by chlorophyll. Potential uses of our model are to advance our understanding of the timing and magnitude of photosynthesis, its effect on atmospheric carbon dioxide fluxes, and vegetation response to climate events and change.
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.
Ke Liu, Yujie Wang, Troy S. Magney, and Christian Frankenberg
Biogeosciences, 21, 1501–1516, https://doi.org/10.5194/bg-21-1501-2024, https://doi.org/10.5194/bg-21-1501-2024, 2024
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Stomata are pores on leaves that regulate gas exchange between plants and the atmosphere. Existing land models unrealistically assume stomata can jump between steady states when the environment changes. We implemented dynamic modeling to predict gradual stomatal responses at different scales. Results suggested that considering this effect on plant behavior patterns in diurnal cycles was important. Our framework also simplified simulations and can contribute to further efficiency improvements.
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.
Haklim Choi, Xiong Liu, Ukkyo Jeong, Heesung Chong, Jhoon Kim, Myung Hwan Ahn, Dai Ho Ko, Dong-Won Lee, Kyung-Jung Moon, and Kwang-Mog Lee
Atmos. Meas. Tech., 17, 145–164, https://doi.org/10.5194/amt-17-145-2024, https://doi.org/10.5194/amt-17-145-2024, 2024
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GEMS is the first geostationary satellite to measure the UV--Vis region, and this paper reports the polarization characteristics of GEMS and an algorithm. We develop a polarization correction algorithm optimized for GEMS based on a look-up-table approach that simultaneously considers the polarization of incoming light and polarization sensitivity characteristics of the instrument. Pre-launch polarization error was adjusted close to zero across the spectral range after polarization correction.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
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Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
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We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Geosci. Model Dev., 16, 6337–6354, https://doi.org/10.5194/gmd-16-6337-2023, https://doi.org/10.5194/gmd-16-6337-2023, 2023
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A single ozone (O3) tracer mode was developed in this work to build the capability of the GEOS-Chem model for rapid O3 simulation. It is combined with OMI and surface O3 observations to investigate the changes in tropospheric O3 in China in 2015–2020. The assimilations indicate rapid surface O3 increases that are underestimated by the a priori simulations. We find stronger increases in tropospheric O3 columns over polluted areas and a large discrepancy by assimilating different observations.
Rui Wang, Da Pan, Xuehui Guo, Kang Sun, Lieven Clarisse, Martin Van Damme, Pierre-François Coheur, Cathy Clerbaux, Melissa Puchalski, and Mark A. Zondlo
Atmos. Chem. Phys., 23, 13217–13234, https://doi.org/10.5194/acp-23-13217-2023, https://doi.org/10.5194/acp-23-13217-2023, 2023
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Ammonia (NH3) is a key precursor for fine particulate matter (PM2.5) and a primary form of reactive nitrogen, yet it has sparse ground measurements. We perform the first comprehensive comparison between ground observations and satellite retrievals in the US, demonstrating that satellite NH3 data can help fill spatial gaps in the current ground monitoring networks. Trend analyses using both datasets highlight increasing NH3 trends across the US, including the NH3 hotspots and urban areas.
Tim A. van Kempen, Tim J. Rotmans, Richard M. van Hees, Carol Bruegge, Dejian Fu, Ruud Hoogeveen, Thomas J. Pongetti, Robert Rosenberg, and Ilse Aben
Atmos. Meas. Tech., 16, 4507–4527, https://doi.org/10.5194/amt-16-4507-2023, https://doi.org/10.5194/amt-16-4507-2023, 2023
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Validation of satellite measurements is essential for providing reliable and consistent products. In this paper, a validation method for TROPOMI-SWIR (Tropospheric Measurement Instrument in the short-wavelength infrared) is explored. TROPOMI-SWIR has been shown to be exceptionally stable, a necessity to explore the methodology. Railroad Valley, Nevada, is a prime location to perform the necessary measurements to validate the satellite measurements of TROPOMI-SWIR.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Atmos. Chem. Phys., 23, 9745–9763, https://doi.org/10.5194/acp-23-9745-2023, https://doi.org/10.5194/acp-23-9745-2023, 2023
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Ozone Monitoring Instrument (OMI) and surface O3 observations are used to investigate the changes in tropospheric O3 in the USA and Europe in 2005–2020. The surface-based assimilations show limited changes in surface and tropospheric column O3. The OMI-based assimilations show larger decreases in tropospheric O3 columns in 2010–2014, related to a decline in free-tropospheric NO2. Analysis suggests limited impacts of local emissions decline on tropospheric O3 over the USA and Europe in 2005–2020.
Chantelle R. Lonsdale and Kang Sun
Atmos. Chem. Phys., 23, 8727–8748, https://doi.org/10.5194/acp-23-8727-2023, https://doi.org/10.5194/acp-23-8727-2023, 2023
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The COVID-19 pandemic, which was caused by the SARS-CoV-2 virus, emerged in 2019, and its still evolving variants have resulted in unprecedented shifts in human activities and anthropogenic emissions into the Earth's atmosphere. We present monthly nitrogen oxide emissions over three major continents from May 2018 to January 2023 to capture variations before and after the COVID-19 pandemic. We focus on a diverse collection of 54 cities to quantify the post-COVID-19 perturbations.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Huiqun Wang, Gonzalo González Abad, Chris Chan Miller, Hyeong-Ahn Kwon, Caroline R. Nowlan, Zolal Ayazpour, Heesung Chong, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Kang Sun, Robert Spurr, and Robert J. Hargreaves
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-66, https://doi.org/10.5194/amt-2023-66, 2023
Preprint withdrawn
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A pipeline for retrieving Total Column Water Vapor from satellite blue spectra is developed. New constraints are considered. Water-leaving radiance is important over the oceans. Results agree with reference datasets well under clear conditions. Due to high sensitivity to clouds, strict data filtering criteria are required. All-sky retrievals can be corrected using machine learning. GPS stations’ representation errors follow a power law relationship with grid resolutions.
Vincent Humphrey and Christian Frankenberg
Biogeosciences, 20, 1789–1811, https://doi.org/10.5194/bg-20-1789-2023, https://doi.org/10.5194/bg-20-1789-2023, 2023
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Microwave satellites can be used to monitor how vegetation biomass changes over time or how droughts affect the world's forests. However, such satellite data are still difficult to validate and interpret because of a lack of comparable field observations. Here, we present a remote sensing technique that uses the Global Navigation Satellite System (GNSS) as a makeshift radar, making it possible to observe canopy transmissivity at any existing environmental research site in a cost-efficient way.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Amir H. Souri, Matthew S. Johnson, Glenn M. Wolfe, James H. Crawford, Alan Fried, Armin Wisthaler, William H. Brune, Donald R. Blake, Andrew J. Weinheimer, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Corinne Vigouroux, Bavo Langerock, Sungyeon Choi, Lok Lamsal, Lei Zhu, Shuai Sun, Ronald C. Cohen, Kyung-Eun Min, Changmin Cho, Sajeev Philip, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 23, 1963–1986, https://doi.org/10.5194/acp-23-1963-2023, https://doi.org/10.5194/acp-23-1963-2023, 2023
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We have rigorously characterized different sources of error in satellite-based HCHO / NO2 tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.
Zolal Ayazpour, Shiqi Tao, Dan Li, Amy Jo Scarino, Ralph E. Kuehn, and Kang Sun
Atmos. Meas. Tech., 16, 563–580, https://doi.org/10.5194/amt-16-563-2023, https://doi.org/10.5194/amt-16-563-2023, 2023
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Accurate knowledge of the planetary boundary layer height (PBLH) is essential to study air pollution. However, PBLH observations are sparse in space and time, and PBLHs used in atmospheric models are often inaccurate. Using PBLH observations from the Aircraft Meteorological DAta Relay (AMDAR), we present a machine learning framework to produce a spatially complete PBLH product over the contiguous US that shows a better agreement with reference PBLH observations than commonly used PBLH products.
Emily Bell, Christopher W. O'Dell, Thomas E. Taylor, Aronne Merrelli, Robert R. Nelson, Matthäus Kiel, Annmarie Eldering, Robert Rosenberg, and Brendan Fisher
Atmos. Meas. Tech., 16, 109–133, https://doi.org/10.5194/amt-16-109-2023, https://doi.org/10.5194/amt-16-109-2023, 2023
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A small percentage of data from the Orbiting Carbon Observatory-3 (OCO-3) instrument has been shown to have a geometry-related bias in the earliest public data release. This work shows that the bias is due to a complex interplay of aerosols and viewing geometry and is largely mitigated in the latest data version through improved bias correction and quality filtering.
Juseon Bak, Eun-Ji Song, Hyo-Jung Lee, Xiong Liu, Ja-Ho Koo, Joowan Kim, Wonbae Jeon, Jae-Hwan Kim, and Cheol-Hee Kim
Atmos. Chem. Phys., 22, 14177–14187, https://doi.org/10.5194/acp-22-14177-2022, https://doi.org/10.5194/acp-22-14177-2022, 2022
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Our study investigates the temporal variations of ozone profiles at Pohang in the Korean Peninsula from multiple ozone products. We discuss the quantitative relationships between daily surface measurements and key meteorological variables, different seasonality of ozone between the troposphere and stratosphere, and interannual changes in the lower tropospheric ozone, linked by the weather pattern driven by the East Asian summer monsoon.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Yujie Wang and Christian Frankenberg
Biogeosciences, 19, 4705–4714, https://doi.org/10.5194/bg-19-4705-2022, https://doi.org/10.5194/bg-19-4705-2022, 2022
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Plant hydraulics is often misrepresented in topical research. We highlight the commonly seen ambiguities and/or mistakes, with equations and figures to help visualize the potential biases. We recommend careful thinking when using or modifying existing plant hydraulic terms, methods, and models.
Yujie Wang and Christian Frankenberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-172, https://doi.org/10.5194/bg-2022-172, 2022
Revised manuscript not accepted
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Leaf light absorption coefficient is often not measured along with leaf gas exchange, but assumed to be constant. This potentially causes biases in estimated photosynthetic capacity and modeled photosynthetic rates. We explored how leaf light absorption features and light source may impact the photosynthesis modeling, and found that the biases are dependent of model assumptions. Researchers need to be more cautious with these inaccurate assumptions in photosynthesis models.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy
Atmos. Meas. Tech., 15, 3721–3745, https://doi.org/10.5194/amt-15-3721-2022, https://doi.org/10.5194/amt-15-3721-2022, 2022
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This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO2 in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.
Tianlang Zhao, Jingqiu Mao, William R. Simpson, Isabelle De Smedt, Lei Zhu, Thomas F. Hanisco, Glenn M. Wolfe, Jason M. St. Clair, Gonzalo González Abad, Caroline R. Nowlan, Barbara Barletta, Simone Meinardi, Donald R. Blake, Eric C. Apel, and Rebecca S. Hornbrook
Atmos. Chem. Phys., 22, 7163–7178, https://doi.org/10.5194/acp-22-7163-2022, https://doi.org/10.5194/acp-22-7163-2022, 2022
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Monitoring formaldehyde (HCHO) can help us understand Arctic vegetation change. Here, we compare satellite data and model and show that Alaska summertime HCHO is largely dominated by a background from methane oxidation during mild wildfire years and is dominated by wildfire (largely from direct emission of fire) during strong fire years. Consequently, it is challenging to use satellite HCHO to study vegetation change in the Arctic region.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
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This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Russell Doughty, Thomas P. Kurosu, Nicholas Parazoo, Philipp Köhler, Yujie Wang, Ying Sun, and Christian Frankenberg
Earth Syst. Sci. Data, 14, 1513–1529, https://doi.org/10.5194/essd-14-1513-2022, https://doi.org/10.5194/essd-14-1513-2022, 2022
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We describe and compare solar-induced chlorophyll fluorescence data produced by NASA from the Greenhouse Gases Observing Satellite (GOSAT) and the Orbiting Carbon Observatory-2 (OCO-2) and OCO-3 platforms.
Johannes Gensheimer, Alexander J. Turner, Philipp Köhler, Christian Frankenberg, and Jia Chen
Biogeosciences, 19, 1777–1793, https://doi.org/10.5194/bg-19-1777-2022, https://doi.org/10.5194/bg-19-1777-2022, 2022
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We develop a convolutional neural network, named SIFnet, that increases the spatial resolution of SIF from TROPOMI by a factor of 10 to a spatial resolution of 0.005°. SIFnet utilizes coarse SIF observations, together with a broad range of high-resolution auxiliary data. The insights gained from interpretable machine learning techniques allow us to make quantitative claims about the relationships between SIF and other common parameters related to photosynthesis.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
Atmos. Chem. Phys., 22, 1097–1130, https://doi.org/10.5194/acp-22-1097-2022, https://doi.org/10.5194/acp-22-1097-2022, 2022
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Satellite CO2 observations are constantly improved. We study an ensemble of different atmospheric models (inversions) from 2015 to 2018 using separate ground-based data or two versions of the OCO-2 satellite. Our study aims to determine if different satellite data corrections can yield different estimates of carbon cycle flux. A difference in the carbon budget between the two versions is found over tropical Africa, which seems to show the impact of corrections applied in satellite data.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
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The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
Yujie Wang and Christian Frankenberg
Biogeosciences, 19, 29–45, https://doi.org/10.5194/bg-19-29-2022, https://doi.org/10.5194/bg-19-29-2022, 2022
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Modeling vegetation canopy is important in predicting whether the land remains a carbon sink to mitigate climate change in the near future. Vegetation canopy model complexity, however, impacts the model-predicted carbon and water fluxes as well as canopy fluorescence, even if the same suite of model inputs is used. Given the biases caused by canopy model complexity, we recommend not misusing parameters inverted using different models or assumptions.
Alexander J. Turner, Philipp Köhler, Troy S. Magney, Christian Frankenberg, Inez Fung, and Ronald C. Cohen
Biogeosciences, 18, 6579–6588, https://doi.org/10.5194/bg-18-6579-2021, https://doi.org/10.5194/bg-18-6579-2021, 2021
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This work builds a high-resolution estimate (500 m) of gross primary productivity (GPP) over the US using satellite measurements of solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI) between 2018 and 2020. We identify ecosystem-specific scaling factors for estimating gross primary productivity (GPP) from TROPOMI SIF. Extreme precipitation events drive four regional GPP anomalies that account for 28 % of year-to-year GPP differences across the US.
Siraput Jongaramrungruang, Georgios Matheou, Andrew K. Thorpe, Zhao-Cheng Zeng, and Christian Frankenberg
Atmos. Meas. Tech., 14, 7999–8017, https://doi.org/10.5194/amt-14-7999-2021, https://doi.org/10.5194/amt-14-7999-2021, 2021
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This study shows how precision error and bias in column methane retrieval change with different instrument specifications and the impact of spectrally complex surface albedos on retrievals. We show how surface interferences can be mitigated with an optimal spectral resolution and a higher polynomial degree in a retrieval process. The findings can inform future satellite instrument designs to have robust observations capable of separating real CH4 plume enhancements from surface interferences.
Amir H. Souri, Kelly Chance, Juseon Bak, Caroline R. Nowlan, Gonzalo González Abad, Yeonjin Jung, David C. Wong, Jingqiu Mao, and Xiong Liu
Atmos. Chem. Phys., 21, 18227–18245, https://doi.org/10.5194/acp-21-18227-2021, https://doi.org/10.5194/acp-21-18227-2021, 2021
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The global pandemic is believed to have an impact on emissions of air pollutants such as nitrogen dioxide (NO2) and formaldehyde (HCHO). This study quantifies the changes in the amount of NOx and VOC emissions via state-of-the-art inverse modeling technique using satellite observations during the lockdown 2020 with respect to a baseline over Europe, which in turn, it permits unraveling atmospheric processes being responsible for ozone formation in a less cloudy month.
Luis Guanter, Cédric Bacour, Andreas Schneider, Ilse Aben, Tim A. van Kempen, Fabienne Maignan, Christian Retscher, Philipp Köhler, Christian Frankenberg, Joanna Joiner, and Yongguang Zhang
Earth Syst. Sci. Data, 13, 5423–5440, https://doi.org/10.5194/essd-13-5423-2021, https://doi.org/10.5194/essd-13-5423-2021, 2021
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Sun-induced chlorophyll fluorescence (SIF) is an electromagnetic signal emitted by plants in the red and far-red parts of the spectrum. It has a functional link to photosynthesis and can be measured by satellite instruments, which makes it an important variable for the remote monitoring of the photosynthetic activity of vegetation ecosystems around the world. In this contribution we present a SIF dataset derived from the new Sentinel-5P TROPOMI missions.
Yujie Wang, Philipp Köhler, Liyin He, Russell Doughty, Renato K. Braghiere, Jeffrey D. Wood, and Christian Frankenberg
Geosci. Model Dev., 14, 6741–6763, https://doi.org/10.5194/gmd-14-6741-2021, https://doi.org/10.5194/gmd-14-6741-2021, 2021
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We present the first step in testing a new land model as part of a new Earth system model. Our model links plant hydraulics, stomatal optimization theory, and a comprehensive canopy radiation scheme. We compared model-predicted carbon and water fluxes to flux tower observations and model-predicted sun-induced chlorophyll fluorescence to satellite retrievals. Our model quantitatively predicted the carbon and water fluxes as well as the canopy fluorescence yield.
Kang Sun, Lingbo Li, Shruti Jagini, and Dan Li
Atmos. Chem. Phys., 21, 13311–13332, https://doi.org/10.5194/acp-21-13311-2021, https://doi.org/10.5194/acp-21-13311-2021, 2021
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We bridge the gap between satellite column observations and emissions by accounting for the dynamic lifetime of pollutants due to wind dispersion and the chemical lifetime due to chemical reactions. Applying it to the Po Valley air basin, we derive the monthly emissions of nitrogen oxides using satellite nitrogen dioxide observations. We further quantify the COVID-19-driven decline of emissions and estimate a 22 % decrease in nitrogen oxide emissions due to the pandemic in 2020.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Jianfeng Li, Yuhang Wang, Ruixiong Zhang, Charles Smeltzer, Andrew Weinheimer, Jay Herman, K. Folkert Boersma, Edward A. Celarier, Russell W. Long, James J. Szykman, Ruben Delgado, Anne M. Thompson, Travis N. Knepp, Lok N. Lamsal, Scott J. Janz, Matthew G. Kowalewski, Xiong Liu, and Caroline R. Nowlan
Atmos. Chem. Phys., 21, 11133–11160, https://doi.org/10.5194/acp-21-11133-2021, https://doi.org/10.5194/acp-21-11133-2021, 2021
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Comprehensive evaluations of simulated diurnal cycles of NO2 and NOy concentrations, vertical profiles, and tropospheric vertical column densities at two different resolutions with various measurements during the DISCOVER-AQ 2011 campaign show potential distribution biases of NOx emissions in the National Emissions Inventory 2011 at both 36 and 4 km resolutions, providing another possible explanation for the overestimation of model results.
Wenfu Tang, David P. Edwards, Louisa K. Emmons, Helen M. Worden, Laura M. Judd, Lok N. Lamsal, Jassim A. Al-Saadi, Scott J. Janz, James H. Crawford, Merritt N. Deeter, Gabriele Pfister, Rebecca R. Buchholz, Benjamin Gaubert, and Caroline R. Nowlan
Atmos. Meas. Tech., 14, 4639–4655, https://doi.org/10.5194/amt-14-4639-2021, https://doi.org/10.5194/amt-14-4639-2021, 2021
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We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability within satellite pixels over urban regions. The sub-grid variability within satellite pixels increases with increasing satellite pixel sizes. Temporal variability within satellite pixels decreases with increasing satellite pixel sizes. This work is particularly relevant and useful for future satellite design, satellite data interpretation, and point-grid data comparisons.
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Toshinobu Machida, Shin-ichiro Nakaoka, Prabir K. Patra, Joshua Laughner, and David Crisp
Atmos. Chem. Phys., 21, 8255–8271, https://doi.org/10.5194/acp-21-8255-2021, https://doi.org/10.5194/acp-21-8255-2021, 2021
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Over oceans, high uncertainties in satellite CO2 retrievals exist due to limited reference data. We combine commercial ship and aircraft observations and, with the aid of model calculations, obtain column-averaged mixing ratios of CO2 (XCO2) data over the Pacific Ocean. This new dataset has great potential as a robust reference for XCO2 measured from space and can help to better understand changes in the carbon cycle in response to climate change using satellite observations.
Carly Staebell, Kang Sun, Jenna Samra, Jonathan Franklin, Christopher Chan Miller, Xiong Liu, Eamon Conway, Kelly Chance, Scott Milligan, and Steven Wofsy
Atmos. Meas. Tech., 14, 3737–3753, https://doi.org/10.5194/amt-14-3737-2021, https://doi.org/10.5194/amt-14-3737-2021, 2021
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Given the high global warming potential of CH4, the identification and subsequent reduction of anthropogenic CH4 emissions presents a significant opportunity for climate change mitigation. Satellites are an integral piece of this puzzle, providing data to quantify emissions at a variety of spatial scales. This work presents the spectral calibration of MethaneAIR, the airborne instrument used as a test bed for the forthcoming MethaneSAT satellite.
Juseon Bak, Xiong Liu, Robert Spurr, Kai Yang, Caroline R. Nowlan, Christopher Chan Miller, Gonzalo Gonzalez Abad, and Kelly Chance
Atmos. Meas. Tech., 14, 2659–2672, https://doi.org/10.5194/amt-14-2659-2021, https://doi.org/10.5194/amt-14-2659-2021, 2021
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We apply a principal component analysis (PCA)-based approach combined with lookup tables (LUTs) of corrections to accelerate the VLIDORT radiative transfer (RT) model used in the retrieval of ozone profiles from backscattered ultraviolet (UV) measurements by the Ozone Monitoring Instrument (OMI).
Michael Buchwitz, Maximilian Reuter, Stefan Noël, Klaus Bramstedt, Oliver Schneising, Michael Hilker, Blanca Fuentes Andrade, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Hartmut Boesch, Lianghai Wu, Jochen Landgraf, Ilse Aben, Christian Retscher, Christopher W. O'Dell, and David Crisp
Atmos. Meas. Tech., 14, 2141–2166, https://doi.org/10.5194/amt-14-2141-2021, https://doi.org/10.5194/amt-14-2141-2021, 2021
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The COVID-19 pandemic resulted in reduced anthropogenic carbon dioxide (CO2) emissions during 2020 in large parts of the world. We have used a small ensemble of satellite retrievals of column-averaged CO2 (XCO2) to find out if a regional-scale reduction of atmospheric CO2 can be detected from space. We focus on East China and show that it is challenging to reliably detect and to accurately quantify the emission reduction, which only results in regional XCO2 reductions of about 0.1–0.2 ppm.
Jakob Borchardt, Konstantin Gerilowski, Sven Krautwurst, Heinrich Bovensmann, Andrew K. Thorpe, David R. Thompson, Christian Frankenberg, Charles E. Miller, Riley M. Duren, and John Philip Burrows
Atmos. Meas. Tech., 14, 1267–1291, https://doi.org/10.5194/amt-14-1267-2021, https://doi.org/10.5194/amt-14-1267-2021, 2021
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The AVIRIS-NG hyperspectral imager has been used successfully to identify and quantify anthropogenic methane sources utilizing different retrieval and inversion methods. Here, we examine the adaption and application of the WFM-DOAS algorithm to AVIRIS-NG measurements to retrieve local methane column enhancements, compare the results with other retrievals, and quantify the uncertainties resulting from the retrieval method. Additionally, we estimate emissions from five detected methane plumes.
Robert R. Nelson, Annmarie Eldering, David Crisp, Aronne J. Merrelli, and Christopher W. O'Dell
Atmos. Meas. Tech., 13, 6889–6899, https://doi.org/10.5194/amt-13-6889-2020, https://doi.org/10.5194/amt-13-6889-2020, 2020
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Measurements of surface wind speed over oceans are scientifically useful. Here we show that the Orbiting Carbon Observatory-2 (OCO-2), originally designed to measure carbon dioxide using reflected sunlight, can also accurately and precisely measure wind speed. OCO-2's high spatial resolution means that it can observe close to coastlines and therefore be used to study coastal wind processes and inform related economic sectors.
Laura M. Judd, Jassim A. Al-Saadi, James J. Szykman, Lukas C. Valin, Scott J. Janz, Matthew G. Kowalewski, Henk J. Eskes, J. Pepijn Veefkind, Alexander Cede, Moritz Mueller, Manuel Gebetsberger, Robert Swap, R. Bradley Pierce, Caroline R. Nowlan, Gonzalo González Abad, Amin Nehrir, and David Williams
Atmos. Meas. Tech., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, https://doi.org/10.5194/amt-13-6113-2020, 2020
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This paper evaluates Sentinel-5P TROPOMI v1.2 NO2 tropospheric columns over New York City using data from airborne mapping spectrometers and a network of ground-based spectrometers (Pandora) collected in 2018. These evaluations consider impacts due to cloud parameters, a priori profile assumptions, and spatial and temporal variability. Overall, TROPOMI tropospheric NO2 columns appear to have a low bias in this region.
Juseon Bak, Xiong Liu, Manfred Birk, Georg Wagner, Iouli E. Gordon, and Kelly Chance
Atmos. Meas. Tech., 13, 5845–5854, https://doi.org/10.5194/amt-13-5845-2020, https://doi.org/10.5194/amt-13-5845-2020, 2020
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This paper evaluates different sets of high-resolution ozone absorption cross-section data for use in atmospheric ozone profile measurements in the Hartley and Huggins bands with a particular focus on BDM 1995 (Daumont et al. 1992; Brion et al., 1993; Malicet et al., 1995) currently used in our retrievals and a new laboratory dataset by Birk and Wagner (BW) (2018).
Lei Zhu, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Kelly Chance, Eric C. Apel, Joshua P. DiGangi, Alan Fried, Thomas F. Hanisco, Rebecca S. Hornbrook, Lu Hu, Jennifer Kaiser, Frank N. Keutsch, Wade Permar, Jason M. St. Clair, and Glenn M. Wolfe
Atmos. Chem. Phys., 20, 12329–12345, https://doi.org/10.5194/acp-20-12329-2020, https://doi.org/10.5194/acp-20-12329-2020, 2020
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We develop a validation platform for satellite HCHO retrievals using in situ observations from 12 aircraft campaigns. The platform offers an alternative way to quickly assess systematic biases in HCHO satellite products over large domains and long periods, facilitating optimization of retrieval settings and the minimization of retrieval biases. Application to the NASA operational HCHO product indicates that relative biases range from −44.5 % to +112.1 % depending on locations and seasons.
Rui Cheng, Troy S. Magney, Debsunder Dutta, David R. Bowling, Barry A. Logan, Sean P. Burns, Peter D. Blanken, Katja Grossmann, Sophia Lopez, Andrew D. Richardson, Jochen Stutz, and Christian Frankenberg
Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, https://doi.org/10.5194/bg-17-4523-2020, 2020
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We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
Xiao Lu, Lin Zhang, Tongwen Wu, Michael S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, and Min Wei
Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, https://doi.org/10.5194/gmd-13-3817-2020, 2020
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This study presents the development and evaluation of a new climate chemistry model, BCC-GEOS-Chem v1.0, which couples the GEOS-Chem chemical transport model as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model. A 3-year (2012–2014) simulation of BCC-GEOS-Chem v1.0 shows that the model captures well the spatiotemporal distributions of tropospheric ozone, other gaseous pollutants, and aerosols.
Eamon K. Conway, Iouli E. Gordon, Jonathan Tennyson, Oleg L. Polyansky, Sergei N. Yurchenko, and Kelly Chance
Atmos. Chem. Phys., 20, 10015–10027, https://doi.org/10.5194/acp-20-10015-2020, https://doi.org/10.5194/acp-20-10015-2020, 2020
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Water vapour has a complex spectrum and absorbs from the microwave to the near-UV where it dissociates. There is limited knowledge of the absorption features in the near-UV, and there is a large disagreement for the available models and experiments. We created a new ab initio model that is in good agreement with observation at 363 nm. At lower wavelengths, our calculations suggest that the latest experiments overestimate absorption. This has implications for trace gas retrievals in the near-UV.
Amir H. Souri, Caroline R. Nowlan, Gonzalo González Abad, Lei Zhu, Donald R. Blake, Alan Fried, Andrew J. Weinheimer, Armin Wisthaler, Jung-Hun Woo, Qiang Zhang, Christopher E. Chan Miller, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 20, 9837–9854, https://doi.org/10.5194/acp-20-9837-2020, https://doi.org/10.5194/acp-20-9837-2020, 2020
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For the first time, we provide a joint nonlinear optimal estimate of NOx and NMVOC emissions during the KORUS-AQ campaign by simultaneously incorporating SAO's new product of HCHO columns from OMPS and OMI tropospheric NO2 columns into a regional model. Results demonstrate a promising improvement in the performance of the model in terms of HCHO and NO2 concentrations, which in turn enables us to quantify the impact of the emission changes on different pathways of ozone formation and loss.
Nicholas C. Parazoo, Troy Magney, Alex Norton, Brett Raczka, Cédric Bacour, Fabienne Maignan, Ian Baker, Yongguang Zhang, Bo Qiu, Mingjie Shi, Natasha MacBean, Dave R. Bowling, Sean P. Burns, Peter D. Blanken, Jochen Stutz, Katja Grossmann, and Christian Frankenberg
Biogeosciences, 17, 3733–3755, https://doi.org/10.5194/bg-17-3733-2020, https://doi.org/10.5194/bg-17-3733-2020, 2020
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Satellite measurements of solar-induced chlorophyll fluorescence (SIF) provide a global measure of photosynthetic change. This enables scientists to better track carbon cycle responses to environmental change and tune biochemical processes in vegetation models for an improved simulation of future change. We use tower-instrumented SIF measurements and controlled model experiments to assess the state of the art in terrestrial biosphere SIF modeling and find a wide range of sensitivities to light.
Marielle Saunois, Ann R. Stavert, Ben Poulter, Philippe Bousquet, Josep G. Canadell, Robert B. Jackson, Peter A. Raymond, Edward J. Dlugokencky, Sander Houweling, Prabir K. Patra, Philippe Ciais, Vivek K. Arora, David Bastviken, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Kimberly M. Carlson, Mark Carrol, Simona Castaldi, Naveen Chandra, Cyril Crevoisier, Patrick M. Crill, Kristofer Covey, Charles L. Curry, Giuseppe Etiope, Christian Frankenberg, Nicola Gedney, Michaela I. Hegglin, Lena Höglund-Isaksson, Gustaf Hugelius, Misa Ishizawa, Akihiko Ito, Greet Janssens-Maenhout, Katherine M. Jensen, Fortunat Joos, Thomas Kleinen, Paul B. Krummel, Ray L. Langenfelds, Goulven G. Laruelle, Licheng Liu, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Joe McNorton, Paul A. Miller, Joe R. Melton, Isamu Morino, Jurek Müller, Fabiola Murguia-Flores, Vaishali Naik, Yosuke Niwa, Sergio Noce, Simon O'Doherty, Robert J. Parker, Changhui Peng, Shushi Peng, Glen P. Peters, Catherine Prigent, Ronald Prinn, Michel Ramonet, Pierre Regnier, William J. Riley, Judith A. Rosentreter, Arjo Segers, Isobel J. Simpson, Hao Shi, Steven J. Smith, L. Paul Steele, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Francesco N. Tubiello, Aki Tsuruta, Nicolas Viovy, Apostolos Voulgarakis, Thomas S. Weber, Michiel van Weele, Guido R. van der Werf, Ray F. Weiss, Doug Worthy, Debra Wunch, Yi Yin, Yukio Yoshida, Wenxin Zhang, Zhen Zhang, Yuanhong Zhao, Bo Zheng, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Earth Syst. Sci. Data, 12, 1561–1623, https://doi.org/10.5194/essd-12-1561-2020, https://doi.org/10.5194/essd-12-1561-2020, 2020
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Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. We have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. This is the second version of the review dedicated to the decadal methane budget, integrating results of top-down and bottom-up estimates.
Gregory Duveiller, Federico Filipponi, Sophia Walther, Philipp Köhler, Christian Frankenberg, Luis Guanter, and Alessandro Cescatti
Earth Syst. Sci. Data, 12, 1101–1116, https://doi.org/10.5194/essd-12-1101-2020, https://doi.org/10.5194/essd-12-1101-2020, 2020
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Sun-induced chlorophyll fluorescence is a valuable indicator of vegetation productivity, but our capacity to measure it from space using satellite remote techniques has been hampered by a lack of spatial detail. Based on prior knowledge of how ecosystems should respond to growing conditions in some modelling along with ancillary satellite observations, we provide here a new enhanced dataset with higher spatial resolution that better represents the spatial patterns of vegetation growth over land.
Maximilian Reuter, Michael Buchwitz, Oliver Schneising, Stefan Noël, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Antonio Di Noia, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Lianghai Wu, Otto P. Hasekamp, Ilse Aben, Akihiko Kuze, Hiroshi Suto, Kei Shiomi, Yukio Yoshida, Isamu Morino, David Crisp, Christopher W. O'Dell, Justus Notholt, Christof Petri, Thorsten Warneke, Voltaire A. Velazco, Nicholas M. Deutscher, David W. T. Griffith, Rigel Kivi, David F. Pollard, Frank Hase, Ralf Sussmann, Yao V. Té, Kimberly Strong, Sébastien Roche, Mahesh K. Sha, Martine De Mazière, Dietrich G. Feist, Laura T. Iraci, Coleen M. Roehl, Christian Retscher, and Dinand Schepers
Atmos. Meas. Tech., 13, 789–819, https://doi.org/10.5194/amt-13-789-2020, https://doi.org/10.5194/amt-13-789-2020, 2020
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We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
Alexander J. Turner, Philipp Köhler, Troy S. Magney, Christian Frankenberg, Inez Fung, and Ronald C. Cohen
Biogeosciences, 17, 405–422, https://doi.org/10.5194/bg-17-405-2020, https://doi.org/10.5194/bg-17-405-2020, 2020
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We present the highest resolution solar-induced chlorophyll fluorescence (SIF) dataset from satellite measurements, providing previously unobservable phenomena related to plant photosynthesis. We find a strong correspondence between TROPOMI SIF and AmeriFlux GPP. We then observe a double peak in the seasonality of California's photosynthesis, not seen by traditional vegetation indices (e.g., MODIS). This is further corroborated by EOF/PC analysis.
Siraput Jongaramrungruang, Christian Frankenberg, Georgios Matheou, Andrew K. Thorpe, David R. Thompson, Le Kuai, and Riley M. Duren
Atmos. Meas. Tech., 12, 6667–6681, https://doi.org/10.5194/amt-12-6667-2019, https://doi.org/10.5194/amt-12-6667-2019, 2019
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This paper demonstrates the use of high-resolution 2-D plume imagery from airborne remote sensing retrievals to quantify methane point-source emissions. It shows significant improvements on the flux estimates without the need for direct wind speed measurements. This paves the way for enhanced flux estimates in future field campaign and space-based observations to better understand the magnitude and distribution of various point sources of methane.
Susan S. Kulawik, Sean Crowell, David Baker, Junjie Liu, Kathryn McKain, Colm Sweeney, Sebastien C. Biraud, Steve Wofsy, Christopher W. O'Dell, Paul O. Wennberg, Debra Wunch, Coleen M. Roehl, Nicholas M. Deutscher, Matthäus Kiel, David W. T. Griffith, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Mazière, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, Dave F. Pollard, Isamu Morino, Osamu Uchino, Frank Hase, Dietrich G. Feist, Sébastien Roche, Kimberly Strong, Rigel Kivi, Laura Iraci, Kei Shiomi, Manvendra K. Dubey, Eliezer Sepulveda, Omaira Elena Garcia Rodriguez, Yao Té, Pascal Jeseck, Pauli Heikkinen, Edward J. Dlugokencky, Michael R. Gunson, Annmarie Eldering, David Crisp, Brendan Fisher, and Gregory B. Osterman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-257, https://doi.org/10.5194/amt-2019-257, 2019
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This paper provides a benchmark of OCO-2 v8 and ACOS-GOSAT v7.3 XCO2 and lowermost tropospheric (LMT) errors. The paper focuses on the systematic errors and subtracts out validation, co-location, and random errors, looks at the correlation scale-length (spatially and temporally) of systematic errors, finding that the scale lengths are similar to bias correction scale-lengths. The assimilates of the bias correction term is used to place an error on fluxes estimates.
Daniel H. Cusworth, Daniel J. Jacob, Daniel J. Varon, Christopher Chan Miller, Xiong Liu, Kelly Chance, Andrew K. Thorpe, Riley M. Duren, Charles E. Miller, David R. Thompson, Christian Frankenberg, Luis Guanter, and Cynthia A. Randles
Atmos. Meas. Tech., 12, 5655–5668, https://doi.org/10.5194/amt-12-5655-2019, https://doi.org/10.5194/amt-12-5655-2019, 2019
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We examine the potential for global detection of methane plumes from individual point sources with the new generation of spaceborne imaging spectrometers scheduled for launch in 2019–2025. We perform methane retrievals on simulated scenes with varying surfaces and atmospheric methane concentrations. Our results suggest that imaging spectrometers in space could play a transformative role in the future for quantifying methane emissions from point sources on a global scale.
Juseon Bak, Kang-Hyeon Baek, Jae-Hwan Kim, Xiong Liu, Jhoon Kim, and Kelly Chance
Atmos. Meas. Tech., 12, 5201–5215, https://doi.org/10.5194/amt-12-5201-2019, https://doi.org/10.5194/amt-12-5201-2019, 2019
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GEMS will be launched in late 2019 on board the GeoKOMPSAT (Geostationary Korea Multi-Purpose Satellite) to measure O3, NO2, SO2, H2CO, CHOCHO, and aerosols in East Asia. To support the development of the GEMS ozone profile algorithm, we perform the cross-evaluation of simulated GEMS ozone profile retrievals based on optimal estimation and ozonesonde measurements within the GEMS domain.
Huiqun Wang, Amir Hossein Souri, Gonzalo González Abad, Xiong Liu, and Kelly Chance
Atmos. Meas. Tech., 12, 5183–5199, https://doi.org/10.5194/amt-12-5183-2019, https://doi.org/10.5194/amt-12-5183-2019, 2019
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Total column water vapor (TCWV) is retrieved from the spectra obtained by the Ozone Monitoring Instrument (OMI). Data filtering criteria are recommended. The OMI data generally compare well with reference datasets over both land and the oceans. The data are useful for a variety of applications spanning a range of spatial and temporal scales, such as atmospheric rivers, corn sweat and El Niño.
Kai Yang and Xiong Liu
Atmos. Meas. Tech., 12, 4745–4778, https://doi.org/10.5194/amt-12-4745-2019, https://doi.org/10.5194/amt-12-4745-2019, 2019
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We constructed total-ozone-dependent and tropopause-dependent climatologies from MERRA-2 ozone data to describe the dynamic variations in the ozone profile in response to changing meteorological conditions. The new climatologies contain the first quantitative characterization of ozone profile covariances, which facilitate a new approach to improve ozone profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions of the covariance matrices.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
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Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Juseon Bak, Xiong Liu, Kang Sun, Kelly Chance, and Jae-Hwan Kim
Atmos. Meas. Tech., 12, 3777–3788, https://doi.org/10.5194/amt-12-3777-2019, https://doi.org/10.5194/amt-12-3777-2019, 2019
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This work improves OMI ozone profile retrievals by accounting for spectral fit residuals caused by slit function errors as a pseudo absorber in the optimal-estimation-based spectral fitting process.
Hyeong-Ahn Kwon, Rokjin J. Park, Gonzalo González Abad, Kelly Chance, Thomas P. Kurosu, Jhoon Kim, Isabelle De Smedt, Michel Van Roozendael, Enno Peters, and John Burrows
Atmos. Meas. Tech., 12, 3551–3571, https://doi.org/10.5194/amt-12-3551-2019, https://doi.org/10.5194/amt-12-3551-2019, 2019
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The Geostationary Environment Monitoring Spectrometer (GEMS) will be launched by South Korea in 2019, and it will measure radiances ranging from 300 to 500 nm every hour with a fine spatial resolution of 7 km x 8 km over Seoul in South Korea to monitor column concentrations of air pollutants including O3, NO2, SO2, and HCHO, as well as aerosol optical properties. This paper describes a GEMS formaldehyde retrieval algorithm including a number of sensitivity tests for algorithm evaluation.
Lu Shen, Daniel J. Jacob, Xiong Liu, Guanyu Huang, Ke Li, Hong Liao, and Tao Wang
Atmos. Chem. Phys., 19, 6551–6560, https://doi.org/10.5194/acp-19-6551-2019, https://doi.org/10.5194/acp-19-6551-2019, 2019
Raid M. Suleiman, Kelly Chance, Xiong Liu, Gonzalo González Abad, Thomas P. Kurosu, Francois Hendrick, and Nicolas Theys
Atmos. Meas. Tech., 12, 2067–2084, https://doi.org/10.5194/amt-12-2067-2019, https://doi.org/10.5194/amt-12-2067-2019, 2019
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This paper presents the retrieval algorithm for the operational OMBRO data product and shows comparisons with correlative measurements and retrieval results. We highlight the physics of the retrieval. We compare the OMBRO products with other satellite and in situ measurements of BrO and illustrate the quality of the product on a global scale. We study OMBRO enhancements in volcanic plumes and over salt lakes. We also discuss the shortcomings and future updates of the OMBRO product.
Jin Liao, Thomas F. Hanisco, Glenn M. Wolfe, Jason St. Clair, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Alan Fried, Eloise A. Marais, Gonzalo Gonzalez Abad, Kelly Chance, Hiren T. Jethva, Thomas B. Ryerson, Carsten Warneke, and Armin Wisthaler
Atmos. Chem. Phys., 19, 2765–2785, https://doi.org/10.5194/acp-19-2765-2019, https://doi.org/10.5194/acp-19-2765-2019, 2019
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Organic aerosol (OA) intimately links natural and anthropogenic emissions with air quality and climate. Direct OA measurements from space are currently not possible. This paper describes a new method to estimate OA by combining satellite HCHO and in situ OA and HCHO. The OA estimate is validated with the ground network. This new method has a potential for mapping observation-based global OA estimate.
Debsunder Dutta, David S. Schimel, Ying Sun, Christiaan van der Tol, and Christian Frankenberg
Biogeosciences, 16, 77–103, https://doi.org/10.5194/bg-16-77-2019, https://doi.org/10.5194/bg-16-77-2019, 2019
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Canopy structural and leaf photosynthesis parameterizations are often fixed over time in Earth system models and represent large sources of uncertainty in predictions of carbon and water fluxes. We develop a moving window nonlinear optimal parameter inversion framework using constraining flux and satellite reflectance observations. The results demonstrate the applicability of the approach for error reduction and capturing the seasonal variability of key ecosystem parameters.
Kang Sun, Lei Zhu, Karen Cady-Pereira, Christopher Chan Miller, Kelly Chance, Lieven Clarisse, Pierre-François Coheur, Gonzalo González Abad, Guanyu Huang, Xiong Liu, Martin Van Damme, Kai Yang, and Mark Zondlo
Atmos. Meas. Tech., 11, 6679–6701, https://doi.org/10.5194/amt-11-6679-2018, https://doi.org/10.5194/amt-11-6679-2018, 2018
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An agile, physics-based approach is developed to oversample irregular satellite observations to a high-resolution common grid. Instead of assuming each sounding as a point or a polygon as in previous methods, the proposed physical oversampling represents soundings as distributions of sensitivity on the ground. This sensitivity distribution can be determined by the spatial response function of each satellite sensor, parameterized as generalized 2-D super Gaussian functions.
Christopher W. O'Dell, Annmarie Eldering, Paul O. Wennberg, David Crisp, Michael R. Gunson, Brendan Fisher, Christian Frankenberg, Matthäus Kiel, Hannakaisa Lindqvist, Lukas Mandrake, Aronne Merrelli, Vijay Natraj, Robert R. Nelson, Gregory B. Osterman, Vivienne H. Payne, Thomas E. Taylor, Debra Wunch, Brian J. Drouin, Fabiano Oyafuso, Albert Chang, James McDuffie, Michael Smyth, David F. Baker, Sourish Basu, Frédéric Chevallier, Sean M. R. Crowell, Liang Feng, Paul I. Palmer, Mavendra Dubey, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Isamu Morino, Justus Notholt, Hirofumi Ohyama, Christof Petri, Coleen M. Roehl, Mahesh K. Sha, Kimberly Strong, Ralf Sussmann, Yao Te, Osamu Uchino, and Voltaire A. Velazco
Atmos. Meas. Tech., 11, 6539–6576, https://doi.org/10.5194/amt-11-6539-2018, https://doi.org/10.5194/amt-11-6539-2018, 2018
Michael Buchwitz, Maximilian Reuter, Oliver Schneising, Stefan Noël, Bettina Gier, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Jasdeep Anand, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Akihiko Kuze, Hiroshi Suto, Yukio Yoshida, David Crisp, and Christopher O'Dell
Atmos. Chem. Phys., 18, 17355–17370, https://doi.org/10.5194/acp-18-17355-2018, https://doi.org/10.5194/acp-18-17355-2018, 2018
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We present a new satellite data set of column-averaged mixing ratios of carbon dioxide (CO2), which covers the time period 2003 to 2016. We used this data set to compute annual mean atmospheric CO2 growth rates. We show that the growth rate is highest during 2015 and 2016 despite nearly constant CO2 emissions from fossil fuel burning in recent years. The high growth rates are attributed to year 2015-2016 El Nino episodes. We present correlations with fossil fuel emissions and ENSO indices.
Caroline R. Nowlan, Xiong Liu, Scott J. Janz, Matthew G. Kowalewski, Kelly Chance, Melanie B. Follette-Cook, Alan Fried, Gonzalo González Abad, Jay R. Herman, Laura M. Judd, Hyeong-Ahn Kwon, Christopher P. Loughner, Kenneth E. Pickering, Dirk Richter, Elena Spinei, James Walega, Petter Weibring, and Andrew J. Weinheimer
Atmos. Meas. Tech., 11, 5941–5964, https://doi.org/10.5194/amt-11-5941-2018, https://doi.org/10.5194/amt-11-5941-2018, 2018
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The GEO-CAPE Airborne Simulator (GCAS) was developed in support of future air quality and ocean color geostationary satellite missions. GCAS flew in its first field campaign on NASA's King Air B-200 aircraft during DISCOVER-AQ Texas in 2013. In this paper, we determine nitrogen dioxide and formaldehyde columns over Houston from the GCAS air quality sensor and compare those results with measurements made from ground-based Pandora spectrometers and in situ airborne instruments.
Hansen Cao, Tzung-May Fu, Lin Zhang, Daven K. Henze, Christopher Chan Miller, Christophe Lerot, Gonzalo González Abad, Isabelle De Smedt, Qiang Zhang, Michel van Roozendael, François Hendrick, Kelly Chance, Jie Li, Junyu Zheng, and Yuanhong Zhao
Atmos. Chem. Phys., 18, 15017–15046, https://doi.org/10.5194/acp-18-15017-2018, https://doi.org/10.5194/acp-18-15017-2018, 2018
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Our top-down estimates for annual total Chinese NMVOC emissions was 30.7 to 49.5 Tg y−1, including 16.4 to 23.6 Tg y−1 from anthropogenic sources, 12.2 to 22.8 Tg y−1 from biogenic sources, and 2.08 to 3.13 Tg y−1 from biomass burning. Our four inversions consistently showed that the emissions of Chinese anthropogenic NMVOC precursors of glyoxal were larger than the a priori estimates. The glyoxal and formaldehyde constraints helped distinguish the NMVOC species from different sources.
Dejian Fu, Susan S. Kulawik, Kazuyuki Miyazaki, Kevin W. Bowman, John R. Worden, Annmarie Eldering, Nathaniel J. Livesey, Joao Teixeira, Fredrick W. Irion, Robert L. Herman, Gregory B. Osterman, Xiong Liu, Pieternel F. Levelt, Anne M. Thompson, and Ming Luo
Atmos. Meas. Tech., 11, 5587–5605, https://doi.org/10.5194/amt-11-5587-2018, https://doi.org/10.5194/amt-11-5587-2018, 2018
Jiali Luo, Laura L. Pan, Shawn B. Honomichl, John W. Bergman, William J. Randel, Gene Francis, Cathy Clerbaux, Maya George, Xiong Liu, and Wenshou Tian
Atmos. Chem. Phys., 18, 12511–12530, https://doi.org/10.5194/acp-18-12511-2018, https://doi.org/10.5194/acp-18-12511-2018, 2018
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We analyze upper tropospheric CO and O3 using satellite data from limb-viewing (MLS) and nadir-viewing (IASI and OMI) sensors, together with dynamical variables, to examine how the two types of data complement each other in representing the chemical variability associated with the day-to-day dynamical variability in the Asian summer monsoon anticyclone. The results provide new observational evidence of eddy shedding in upper tropospheric CO distribution.
Janne Hakkarainen, Iolanda Ialongo, Shamil Maksyutov, and David Crisp
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-649, https://doi.org/10.5194/acp-2018-649, 2018
Revised manuscript not accepted
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We provide a global (60° S–60° N) view of the XCO2 anomalies, indicators of CO2 emissions to and removal from the atmosphere, and study their annual variations and seasonal patterns. We see that positive anomalies correspond to the emissions from fossil fuel combustion over the major industrial areas as well as biomass burning during different fire seasons. The largest negative anomalies correspond to the growing seasons in the middle latitudes. The results are achieved using NASA's OCO-2 data.
Matthew S. Johnson, Xiong Liu, Peter Zoogman, John Sullivan, Michael J. Newchurch, Shi Kuang, Thierry Leblanc, and Thomas McGee
Atmos. Meas. Tech., 11, 3457–3477, https://doi.org/10.5194/amt-11-3457-2018, https://doi.org/10.5194/amt-11-3457-2018, 2018
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This research was conducted to determine the impact of multiple a priori ozone (O3) profile products on Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite retrievals. It was determined that non-climatological model predictions, in particular those from a chemical transport model, when applied as the a priori profile improved the accuracy of TEMPO tropospheric O3 retrievals in comparison to the TB-Clim product that is currently suggested for use in the TEMPO retrieval algorithm.
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
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The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Xiao Lu, Lin Zhang, Xiong Liu, Meng Gao, Yuanhong Zhao, and Jingyuan Shao
Atmos. Chem. Phys., 18, 3101–3118, https://doi.org/10.5194/acp-18-3101-2018, https://doi.org/10.5194/acp-18-3101-2018, 2018
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Deteriorating tropospheric ozone pollution over India may not only affect local human health and vegetation but also perturb global ozone distribution. This study analyzes the processes controlling lower tropospheric ozone over India using OMI satellite observations (2006–2014) and model simulations (1990–2010). We show that the South Asian monsoon largely controls the seasonal cycle and interannual variability of Indian lower tropospheric ozone via changes in ozone production and transport.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, and Zhaonan Cai
Atmos. Meas. Tech., 11, 17–32, https://doi.org/10.5194/amt-11-17-2018, https://doi.org/10.5194/amt-11-17-2018, 2018
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In this paper, we focus on the validation of OMI ozone (PROFOZ) product in the stratosphere using MLS ozone observations. This paper, with its companion paper focusing on the validation in the troposphere by using global ozonesonde observations, provides us with a comprehensive understanding of the data quality of OMI PROFOZ product and impacts of the “row anomaly”.
Juseon Bak, Xiong Liu, Jae-Hwan Kim, David P. Haffner, Kelly Chance, Kai Yang, and Kang Sun
Atmos. Meas. Tech., 10, 4373–4388, https://doi.org/10.5194/amt-10-4373-2017, https://doi.org/10.5194/amt-10-4373-2017, 2017
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This paper verifies and corrects the Ozone Mapping and Profiler Suite (OMPS) nadir mapper (NM) level 1B v2.0 measurements to retrieve reliable ozone profile and tropospheric ozone using an optimal estimation inversion with the fitting window of 302.5–340 nm. We apply "soft calibration" and "common mode correction" to OMPS radiances to eliminate systematic errors in the fitting residuals and derive random-noise measurement errors accounting for both OMPS radiances and forward model calculation.
Andrew K. Thorpe, Christian Frankenberg, David R. Thompson, Riley M. Duren, Andrew D. Aubrey, Brian D. Bue, Robert O. Green, Konstantin Gerilowski, Thomas Krings, Jakob Borchardt, Eric A. Kort, Colm Sweeney, Stephen Conley, Dar A. Roberts, and Philip E. Dennison
Atmos. Meas. Tech., 10, 3833–3850, https://doi.org/10.5194/amt-10-3833-2017, https://doi.org/10.5194/amt-10-3833-2017, 2017
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At local scales emissions of methane (CH4) and carbon dioxide (CO2) are highly uncertain. The AVIRIS-NG imaging spectrometer maps large regions and generates high-spatial-resolution CH4 and CO2 concentration maps from anthropogenic and natural sources. Examples include CH4 from a processing plant, tank, pipeline leak, seep, mine vent shafts, and CO2 from power plants. This demonstrates a greenhouse gas monitoring capability that targets the two dominant anthropogenic climate-forcing agents.
Kang Sun, Xiong Liu, Guanyu Huang, Gonzalo González Abad, Zhaonan Cai, Kelly Chance, and Kai Yang
Atmos. Meas. Tech., 10, 3677–3695, https://doi.org/10.5194/amt-10-3677-2017, https://doi.org/10.5194/amt-10-3677-2017, 2017
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This study derives on-orbit slit functions from the OMI irradiance spectra. The results differ from the widely used preflight slit functions. The on-orbit changes of OMI slit functions are insignificant over time after accounting for the solar activity. Applying the derived on-orbit slit functions to ozone-profile retrieval shows substantial improvements over the preflight slit functions based on comparisons with ozonesonde validations.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Ray Weiss, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
John R. Worden, Gary Doran, Susan Kulawik, Annmarie Eldering, David Crisp, Christian Frankenberg, Chris O'Dell, and Kevin Bowman
Atmos. Meas. Tech., 10, 2759–2771, https://doi.org/10.5194/amt-10-2759-2017, https://doi.org/10.5194/amt-10-2759-2017, 2017
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This paper evaluates the uncertainties of the total column carbon dioxide (XCO2) measurements from the NASA OCO-2 instrument by comparing observed variations in small geographical regions to the calculated uncertainties of the data within this region. In general we find that the reported XCO2 precision is related to that expected from the XCO2 radiance noise. However, the reported accuracy is at least smaller than the actual accuracy by a factor of 2–4.
Christopher Chan Miller, Daniel J. Jacob, Eloise A. Marais, Karen Yu, Katherine R. Travis, Patrick S. Kim, Jenny A. Fisher, Lei Zhu, Glenn M. Wolfe, Thomas F. Hanisco, Frank N. Keutsch, Jennifer Kaiser, Kyung-Eun Min, Steven S. Brown, Rebecca A. Washenfelder, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 17, 8725–8738, https://doi.org/10.5194/acp-17-8725-2017, https://doi.org/10.5194/acp-17-8725-2017, 2017
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The use of satellite glyoxal observations for estimating isoprene emissions has been limited by knowledge of the glyoxal yield from isoprene. We use SENEX aircraft observations over the southeast US to evaluate glyoxal yields from isoprene in a 3-D atmospheric model. The SENEX observations support a pathway for glyoxal formation in pristine regions that we propose here, which may have implications for improving isoprene emissions estimates from upcoming high-resolution geostationary satellites.
Guanyu Huang, Xiong Liu, Kelly Chance, Kai Yang, Pawan K. Bhartia, Zhaonan Cai, Marc Allaart, Gérard Ancellet, Bertrand Calpini, Gerrie J. R. Coetzee, Emilio Cuevas-Agulló, Manuel Cupeiro, Hugo De Backer, Manvendra K. Dubey, Henry E. Fuelberg, Masatomo Fujiwara, Sophie Godin-Beekmann, Tristan J. Hall, Bryan Johnson, Everette Joseph, Rigel Kivi, Bogumil Kois, Ninong Komala, Gert König-Langlo, Giovanni Laneve, Thierry Leblanc, Marion Marchand, Kenneth R. Minschwaner, Gary Morris, Michael J. Newchurch, Shin-Ya Ogino, Nozomu Ohkawara, Ankie J. M. Piters, Françoise Posny, Richard Querel, Rinus Scheele, Frank J. Schmidlin, Russell C. Schnell, Otto Schrems, Henry Selkirk, Masato Shiotani, Pavla Skrivánková, René Stübi, Ghassan Taha, David W. Tarasick, Anne M. Thompson, Valérie Thouret, Matthew B. Tully, Roeland Van Malderen, Holger Vömel, Peter von der Gathen, Jacquelyn C. Witte, and Margarita Yela
Atmos. Meas. Tech., 10, 2455–2475, https://doi.org/10.5194/amt-10-2455-2017, https://doi.org/10.5194/amt-10-2455-2017, 2017
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It is essential to understand the data quality of +10-year OMI ozone product and impacts of the “row anomaly” (RA). We validate the OMI Ozone Profile (PROFOZ) product from Oct 2004 to Dec 2014 against ozonesonde observations globally. Generally, OMI has good agreement with ozonesondes. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability.
Hyun-Deok Choi, Hongyu Liu, James H. Crawford, David B. Considine, Dale J. Allen, Bryan N. Duncan, Larry W. Horowitz, Jose M. Rodriguez, Susan E. Strahan, Lin Zhang, Xiong Liu, Megan R. Damon, and Stephen D. Steenrod
Atmos. Chem. Phys., 17, 8429–8452, https://doi.org/10.5194/acp-17-8429-2017, https://doi.org/10.5194/acp-17-8429-2017, 2017
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We evaluate global ozone–carbon monoxide (O3–CO) correlations in a chemistry and transport model during July–August with TES-Aura satellite observations and examine the sensitivity of model simulations to input meteorological data and emissions. Results show that O3–CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.
Debra Wunch, Paul O. Wennberg, Gregory Osterman, Brendan Fisher, Bret Naylor, Coleen M. Roehl, Christopher O'Dell, Lukas Mandrake, Camille Viatte, Matthäus Kiel, David W. T. Griffith, Nicholas M. Deutscher, Voltaire A. Velazco, Justus Notholt, Thorsten Warneke, Christof Petri, Martine De Maziere, Mahesh K. Sha, Ralf Sussmann, Markus Rettinger, David Pollard, John Robinson, Isamu Morino, Osamu Uchino, Frank Hase, Thomas Blumenstock, Dietrich G. Feist, Sabrina G. Arnold, Kimberly Strong, Joseph Mendonca, Rigel Kivi, Pauli Heikkinen, Laura Iraci, James Podolske, Patrick W. Hillyard, Shuji Kawakami, Manvendra K. Dubey, Harrison A. Parker, Eliezer Sepulveda, Omaira E. García, Yao Te, Pascal Jeseck, Michael R. Gunson, David Crisp, and Annmarie Eldering
Atmos. Meas. Tech., 10, 2209–2238, https://doi.org/10.5194/amt-10-2209-2017, https://doi.org/10.5194/amt-10-2209-2017, 2017
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This paper describes the comparisons between NASA's Orbiting Carbon Observatory (OCO-2) column-averaged dry-air mole fractions of CO2 with its primary ground-based validation network, the Total Carbon Column Observing Network (TCCON). The paper shows that while the standard bias correction reduces much of the spurious variability in the satellite measurements, residual biases remain.
Michael Buchwitz, Oliver Schneising, Maximilian Reuter, Jens Heymann, Sven Krautwurst, Heinrich Bovensmann, John P. Burrows, Hartmut Boesch, Robert J. Parker, Peter Somkuti, Rob G. Detmers, Otto P. Hasekamp, Ilse Aben, André Butz, Christian Frankenberg, and Alexander J. Turner
Atmos. Chem. Phys., 17, 5751–5774, https://doi.org/10.5194/acp-17-5751-2017, https://doi.org/10.5194/acp-17-5751-2017, 2017
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Methane is an important greenhouse gas and increasing atmospheric concentrations result in global warming. We present a simple method to derive annual methane emission estimates of methane hotspot areas from satellite data. We present results for four source areas. We found that our estimates are in good agreement with other studies/data sets for the Four Corners region in the USA and for Azerbaijan but we also found higher emissions for parts of California and Turkmenistan.
Hyeong-Ahn Kwon, Rokjin J. Park, Jaein I. Jeong, Seungun Lee, Gonzalo González Abad, Thomas P. Kurosu, Paul I. Palmer, and Kelly Chance
Atmos. Chem. Phys., 17, 4673–4686, https://doi.org/10.5194/acp-17-4673-2017, https://doi.org/10.5194/acp-17-4673-2017, 2017
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A geostationary satellite can measure daytime hourly HCHO columns. Atmospheric conditions such as synoptic meteorology and the presence of other gases and aerosols may affect HCHO measurements. We examine the effects of their temporal variation on the HCHO measurement of a geostationary satellite in East Asia. We find that the hourly variation of other species could be important. Especially the inclusion of hourly aerosol variation in the retrieval could lead to improving HCHO measurements.
Annmarie Eldering, Chris W. O'Dell, Paul O. Wennberg, David Crisp, Michael R. Gunson, Camille Viatte, Charles Avis, Amy Braverman, Rebecca Castano, Albert Chang, Lars Chapsky, Cecilia Cheng, Brian Connor, Lan Dang, Gary Doran, Brendan Fisher, Christian Frankenberg, Dejian Fu, Robert Granat, Jonathan Hobbs, Richard A. M. Lee, Lukas Mandrake, James McDuffie, Charles E. Miller, Vicky Myers, Vijay Natraj, Denis O'Brien, Gregory B. Osterman, Fabiano Oyafuso, Vivienne H. Payne, Harold R. Pollock, Igor Polonsky, Coleen M. Roehl, Robert Rosenberg, Florian Schwandner, Mike Smyth, Vivian Tang, Thomas E. Taylor, Cathy To, Debra Wunch, and Jan Yoshimizu
Atmos. Meas. Tech., 10, 549–563, https://doi.org/10.5194/amt-10-549-2017, https://doi.org/10.5194/amt-10-549-2017, 2017
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This paper describes the measurements of atmospheric carbon dioxide collected in the first 18 months of the satellite mission known as the Orbiting Carbon Observatory-2 (OCO-2). The paper shows maps of the carbon dioxide data, data density, and other data fields that illustrate the data quality. This mission has collected a more precise, more dense dataset of carbon dioxide then we have ever had previously.
David Crisp, Harold R. Pollock, Robert Rosenberg, Lars Chapsky, Richard A. M. Lee, Fabiano A. Oyafuso, Christian Frankenberg, Christopher W. O'Dell, Carol J. Bruegge, Gary B. Doran, Annmarie Eldering, Brendan M. Fisher, Dejian Fu, Michael R. Gunson, Lukas Mandrake, Gregory B. Osterman, Florian M. Schwandner, Kang Sun, Tommy E. Taylor, Paul O. Wennberg, and Debra Wunch
Atmos. Meas. Tech., 10, 59–81, https://doi.org/10.5194/amt-10-59-2017, https://doi.org/10.5194/amt-10-59-2017, 2017
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The Orbiting Carbon Observatory-2 carries and points a three-channel imaging grating spectrometer designed to collect high-resolution spectra of reflected sunlight within the molecular oxygen A-band at 0.765 microns and the carbon dioxide bands at 1.61 and 2.06 microns. Here, we describe the OCO-2 instrument, its data products, and its performance during its first 18 months in orbit.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Jianxiong Sheng, Kang Sun, Xiong Liu, Kelly Chance, Ilse Aben, Jason McKeever, and Christian Frankenberg
Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, https://doi.org/10.5194/acp-16-14371-2016, 2016
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Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned to launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify methane emissions from the global scale down to the scale of point sources.
Lei Zhu, Daniel J. Jacob, Patrick S. Kim, Jenny A. Fisher, Karen Yu, Katherine R. Travis, Loretta J. Mickley, Robert M. Yantosca, Melissa P. Sulprizio, Isabelle De Smedt, Gonzalo González Abad, Kelly Chance, Can Li, Richard Ferrare, Alan Fried, Johnathan W. Hair, Thomas F. Hanisco, Dirk Richter, Amy Jo Scarino, James Walega, Petter Weibring, and Glenn M. Wolfe
Atmos. Chem. Phys., 16, 13477–13490, https://doi.org/10.5194/acp-16-13477-2016, https://doi.org/10.5194/acp-16-13477-2016, 2016
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HCHO column data are widely used as a proxy for VOCs emissions, but validation of the data has been extremely limited. We use accurate aircraft observations to validate and intercompare 6 HCHO retrievals with GEOS-Chem as the intercomparison platform. Retrievals are interconsistent in spatial variability over the SE US and in daily variability, but are biased low by 20–51 %. Our work supports the use of HCHO column as a quantitative proxy for isoprene emission after correction of the low bias.
Brian Connor, Hartmut Bösch, James McDuffie, Tommy Taylor, Dejian Fu, Christian Frankenberg, Chris O'Dell, Vivienne H. Payne, Michael Gunson, Randy Pollock, Jonathan Hobbs, Fabiano Oyafuso, and Yibo Jiang
Atmos. Meas. Tech., 9, 5227–5238, https://doi.org/10.5194/amt-9-5227-2016, https://doi.org/10.5194/amt-9-5227-2016, 2016
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We present an analysis of uncertainties in global measurements of the column-averaged dry-air mole fraction of CO2 (XCO2) by the satellite OCO-2. The analysis is based on our best estimates for uncertainties in the OCO-2 operational algorithm and its inputs. From these results we estimate the "variable error", which differs between soundings, to infer the error in the difference of XCO2 between any two soundings. Variable errors are usually < 1 ppm over ocean and ~ 0.5–2 ppm over land.
Zeli Tan, Qianlai Zhuang, Daven K. Henze, Christian Frankenberg, Ed Dlugokencky, Colm Sweeney, Alexander J. Turner, Motoki Sasakawa, and Toshinobu Machida
Atmos. Chem. Phys., 16, 12649–12666, https://doi.org/10.5194/acp-16-12649-2016, https://doi.org/10.5194/acp-16-12649-2016, 2016
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Methane emissions from the pan-Arctic could be important in understanding the global carbon cycle but are still poorly constrained to date. This study demonstrated that satellite retrievals can be used to reduce the uncertainty of the estimates of these emissions. We also provided additional evidence for the existence of large methane emissions from pan-Arctic lakes in the Siberian yedoma permafrost region. We found that biogeochemical models should be improved for better estimates.
Huiqun Wang, Gonzalo Gonzalez Abad, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 16, 11379–11393, https://doi.org/10.5194/acp-16-11379-2016, https://doi.org/10.5194/acp-16-11379-2016, 2016
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Water vapor is highly important. The OMI total column water vapor product retrieved using SAO's version 1.0 algorithm agrees well with other reference products over the land but has a low bias over the ocean. The updated OMI water vapor product retrieved using SAO's version 2.1 algorithm largely eliminates the low bias over the ocean, improving the land/ocean consistency and the overall data quality. This dataset can benefit a variety of scientific studies and practical applications.
Juseon Bak, Xiong Liu, Jae H. Kim, Matthew T. Deland, and Kelly Chance
Atmos. Meas. Tech., 9, 4521–4531, https://doi.org/10.5194/amt-9-4521-2016, https://doi.org/10.5194/amt-9-4521-2016, 2016
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The main focus of this paper is improving an error of OMI nadir ozone profile retrievals due to the presence of polar mesospheric clouds (PMCs), consisting of small light-scattering particles at an altitude of 80–85 km. This error is shown to be systematic bias from ~ −2 at 2 hPa to ~ −20 % at 0.5 hPa and significantly correlated with brightness of PMCs. We reduce this interference of PMCs on ozone retrievals by including the PMC optical depth in the forward-model calculation and retrieval.
Remco A. Scheepmaker, Joost aan de Brugh, Haili Hu, Tobias Borsdorff, Christian Frankenberg, Camille Risi, Otto Hasekamp, Ilse Aben, and Jochen Landgraf
Atmos. Meas. Tech., 9, 3921–3937, https://doi.org/10.5194/amt-9-3921-2016, https://doi.org/10.5194/amt-9-3921-2016, 2016
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We have developed an algorithm to measure HDO (heavy water) in the atmosphere using the TROPOMI satellite instrument, scheduled for launch in 2016. Giving an insight in the history of water vapour, these measurements will help to better understand the water cycle and its role in climate change. We use realistic measurement simulations to describe the performance of the algorithm, and show that TROPOMI will greatly improve and extend the HDO datasets from the previous SCIAMACHY and GOSAT missions.
Gonzalo González Abad, Alexander Vasilkov, Colin Seftor, Xiong Liu, and Kelly Chance
Atmos. Meas. Tech., 9, 2797–2812, https://doi.org/10.5194/amt-9-2797-2016, https://doi.org/10.5194/amt-9-2797-2016, 2016
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The multi-spectral possibilities of the OMPS Nadir Mapper instrument are exploited here to perform formaldehyde retrievals. Orbiting the Earth at 824 km, OMPS observes the atmosphere in a time frame similar to instruments belonging to NASA's A-Train constellation, 01:30. We show that OMPS is well suited to measure formaldehyde despite its spectral resolution of 1nm. The comparison of OMPS retrievals with OMI products show good temporal correlation.
Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
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We use observations from the HIAPER Pole-to-Pole Observations (HIPPO) flights from January 2009 through September 2011 to validate CO2 measurements from satellites (GOSAT, TES, AIRS) and atmospheric inversion models (CarbonTracker CT2013B, MACC v13r1).
Caroline R. Nowlan, Xiong Liu, James W. Leitch, Kelly Chance, Gonzalo González Abad, Cheng Liu, Peter Zoogman, Joshua Cole, Thomas Delker, William Good, Frank Murcray, Lyle Ruppert, Daniel Soo, Melanie B. Follette-Cook, Scott J. Janz, Matthew G. Kowalewski, Christopher P. Loughner, Kenneth E. Pickering, Jay R. Herman, Melinda R. Beaver, Russell W. Long, James J. Szykman, Laura M. Judd, Paul Kelley, Winston T. Luke, Xinrong Ren, and Jassim A. Al-Saadi
Atmos. Meas. Tech., 9, 2647–2668, https://doi.org/10.5194/amt-9-2647-2016, https://doi.org/10.5194/amt-9-2647-2016, 2016
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The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument is a remote sensing airborne instrument developed in support of future air quality satellite missions that will operate from geostationary orbit. GeoTASO flew in its first intensive field campaign during the DISCOVER-AQ 2013 Earth Venture Mission over Houston, Texas. This paper introduces the instrument and data analysis, and presents GeoTASO's first observations of NO2 at 250 m x 250 m spatial resolution.
Glynn C. Hulley, Riley M. Duren, Francesca M. Hopkins, Simon J. Hook, Nick Vance, Pierre Guillevic, William R. Johnson, Bjorn T. Eng, Jonathan M. Mihaly, Veljko M. Jovanovic, Seth L. Chazanoff, Zak K. Staniszewski, Le Kuai, John Worden, Christian Frankenberg, Gerardo Rivera, Andrew D. Aubrey, Charles E. Miller, Nabin K. Malakar, Juan M. Sánchez Tomás, and Kendall T. Holmes
Atmos. Meas. Tech., 9, 2393–2408, https://doi.org/10.5194/amt-9-2393-2016, https://doi.org/10.5194/amt-9-2393-2016, 2016
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Using data from a new airborne Hyperspectral Thermal Emission Spectrometer (HyTES) instrument, we present a technique for the detection and wide-area mapping of emission plumes of methane and other atmospheric trace gas species over challenging and diverse environmental conditions with high spatial resolution, that permits direct attribution to sources in complex environments.
Christopher Chan Miller, Daniel J. Jacob, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 16, 4631–4639, https://doi.org/10.5194/acp-16-4631-2016, https://doi.org/10.5194/acp-16-4631-2016, 2016
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Volatile organic compounds (VOCs) are important precursors for photochemical smog.
Glyoxal is an organic compound produced in the atmosphere from reactions of larger VOCs. OMI satellite observations of glyoxal show a large hotspot over the Pearl River delta. The hotspot can be explained by industrial paint and solvent emissions of aromatic VOCs. Our work shows OMI observations are consistent with current VOC emissions estimates, whereas previous work has suggested large underestimates.
Thomas E. Taylor, Christopher W. O'Dell, Christian Frankenberg, Philip T. Partain, Heather Q. Cronk, Andrey Savtchenko, Robert R. Nelson, Emily J. Rosenthal, Albert Y. Chang, Brenden Fisher, Gregory B. Osterman, Randy H. Pollock, David Crisp, Annmarie Eldering, and Michael R. Gunson
Atmos. Meas. Tech., 9, 973–989, https://doi.org/10.5194/amt-9-973-2016, https://doi.org/10.5194/amt-9-973-2016, 2016
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NASA's Orbiting Carbon Observatory-2 (OCO-2) is providing approximately 1 million soundings per day of the total column of carbon dioxide (XCO2). The retrieval of XCO2 can only be performed for soundings sufficiently free of cloud and aerosol. This work highlights comparisons of OCO-2 cloud screening algorithms to the MODIS cloud mask product. We find agreement approximately 85 % of the time with some significant spatial and small seasonal dependencies.
Susan Kulawik, Debra Wunch, Christopher O'Dell, Christian Frankenberg, Maximilian Reuter, Tomohiro Oda, Frederic Chevallier, Vanessa Sherlock, Michael Buchwitz, Greg Osterman, Charles E. Miller, Paul O. Wennberg, David Griffith, Isamu Morino, Manvendra K. Dubey, Nicholas M. Deutscher, Justus Notholt, Frank Hase, Thorsten Warneke, Ralf Sussmann, John Robinson, Kimberly Strong, Matthias Schneider, Martine De Mazière, Kei Shiomi, Dietrich G. Feist, Laura T. Iraci, and Joyce Wolf
Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, https://doi.org/10.5194/amt-9-683-2016, 2016
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To accurately estimate source and sink locations of carbon dioxide, systematic errors in satellite measurements and models must be characterized. This paper examines two satellite data sets (GOSAT, launched 2009, and SCIAMACHY, launched 2002), and two models (CarbonTracker and MACC) vs. the TCCON CO2 validation data set. We assess biases and errors by season and latitude, satellite performance under averaging, and diurnal variability. Our findings are useful for assimilation of satellite data.
U. Jeong, J. Kim, C. Ahn, O. Torres, X. Liu, P. K. Bhartia, R. J. D. Spurr, D. Haffner, K. Chance, and B. N. Holben
Atmos. Chem. Phys., 16, 177–193, https://doi.org/10.5194/acp-16-177-2016, https://doi.org/10.5194/acp-16-177-2016, 2016
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An aerosol retrieval and error analysis algorithm using OMI measurements based on an optimal-estimation method was developed in this study. The aerosol retrievals were validated using the DRAGON campaign products. The estimated errors of the retrievals represented the actual biases between retrieval and AERONET measurements well. The retrievals, with their estimated uncertainties, are expected to be valuable for relevant studies, such as trace gas retrieval and data assimilation.
D. R. Thompson, I. Leifer, H. Bovensmann, M. Eastwood, M. Fladeland, C. Frankenberg, K. Gerilowski, R. O. Green, S. Kratwurst, T. Krings, B. Luna, and A. K. Thorpe
Atmos. Meas. Tech., 8, 4383–4397, https://doi.org/10.5194/amt-8-4383-2015, https://doi.org/10.5194/amt-8-4383-2015, 2015
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We discuss principles for real-time infrared spectral signature detection and measurement, and report performance onboard the NASA Airborne Visible Infrared Spectrometer - Next Generation (AVIRIS-NG). We describe a case study of the NASA/ESA CO2 and MEthane eXperiment (COMEX), a multi-platform campaign to measure CH4 plumes released from anthropogenic sources including oil and gas infrastructure. AVIRIS-NG successfully detected CH4 plumes in concert with other in situ and remote instruments.
J. Bak, X. Liu, J. H. Kim, M. T. Deland, and K. Chance
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-25907-2015, https://doi.org/10.5194/acpd-15-25907-2015, 2015
Revised manuscript not accepted
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This work demonstrated the interference of tenuous PMCs on OMI ozone profile retrievals above 6hPa. The presence of PMCs leads to the systematic biases of -2% at 2hPa and -20% at 0.5hPa in OMI retrievals, which are significantly correlated with brightness of PMCs. We perform simultaneous retrievals of PMC optical depth with ozone using optimal estimation technique, to reduce the interference on ozone profile retrievals. As a result, the negative OMI biases are reduced to within ±10%.
S. Hayashida, X. Liu, A. Ono, K. Yang, and K. Chance
Atmos. Chem. Phys., 15, 9865–9881, https://doi.org/10.5194/acp-15-9865-2015, https://doi.org/10.5194/acp-15-9865-2015, 2015
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The lower tropospheric ozone distribution maps were first obtained from the recent retrieval products of the Ozone Monitoring Instrument (OMI) onboard the Earth Observing System (EOS) Aura satellite. We found significant enhancement of ozone in the lower troposphere over central and eastern China (CEC), with Shandong Province as its center, and most notable in June in any given year. Similar seasonal variations were observed throughout the 9-year OMI measurement period of 2005 to 2013.
J. R. Worden, A. J. Turner, A. Bloom, S. S. Kulawik, J. Liu, M. Lee, R. Weidner, K. Bowman, C. Frankenberg, R. Parker, and V. H. Payne
Atmos. Meas. Tech., 8, 3433–3445, https://doi.org/10.5194/amt-8-3433-2015, https://doi.org/10.5194/amt-8-3433-2015, 2015
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Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Aura Tropospheric Emission Spectrometer (TES) and XCH4 (dry-mole air fraction of methane) from the Greenhouse Gases Observing Satellite - Thermal And Near-infrared for carbon Observation (GOSAT TANSO).
E. N. Koffi, P. J. Rayner, A. J. Norton, C. Frankenberg, and M. Scholze
Biogeosciences, 12, 4067–4084, https://doi.org/10.5194/bg-12-4067-2015, https://doi.org/10.5194/bg-12-4067-2015, 2015
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We investigate the utility of satellite measurements of solar-induced chlorophyll fluorescence (SIF) in constraining gross primary productivity (GPP). We simulate SIF with the biosphere model BETHY coupled with the fluorescence model SCOPE. The model simulates well the patterns of SIF. SIF is sensitive to leaf chlorophyll and incoming radiation but not to the key physiological parameter Vcmax controlling GPP. Thus, further model development is necessary before SIF can be used to constrain GPP.
R. A. Scheepmaker, C. Frankenberg, N. M. Deutscher, M. Schneider, S. Barthlott, T. Blumenstock, O. E. Garcia, F. Hase, N. Jones, E. Mahieu, J. Notholt, V. Velazco, J. Landgraf, and I. Aben
Atmos. Meas. Tech., 8, 1799–1818, https://doi.org/10.5194/amt-8-1799-2015, https://doi.org/10.5194/amt-8-1799-2015, 2015
L. Guanter, I. Aben, P. Tol, J. M. Krijger, A. Hollstein, P. Köhler, A. Damm, J. Joiner, C. Frankenberg, and J. Landgraf
Atmos. Meas. Tech., 8, 1337–1352, https://doi.org/10.5194/amt-8-1337-2015, https://doi.org/10.5194/amt-8-1337-2015, 2015
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This paper investigates the potential of the upcoming TROPOspheric Monitoring Instrument (TROPOMI) instrument for the retrieval of the chlorophyll fluorescence signal emitted in the 650–850nm spectral range by the photosynthetic machinery of green plants. We find that TROPOMI will allow substantial improvements in the space monitoring of fluorescence with respect to current spaceborne instruments such as GOME-2 and SCIAMACHY.
C. Liu, X. Liu, M. G. Kowalewski, S. J. Janz, G. González Abad, K. E. Pickering, K. Chance, and L. N. Lamsal
Atmos. Meas. Tech., 8, 751–759, https://doi.org/10.5194/amt-8-751-2015, https://doi.org/10.5194/amt-8-751-2015, 2015
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We characterize the wavelengths and slit functions of Airborne Compact Atmospheric Mapper (ACAM) measurements in ~304--500 nm through the cross-correlation technique. It is necessary to account for atmospheric gas absorption and the ring effect. The derived broadened Gaussian slit functions agree very well with laboratory measurements. Trace gas retrieval comparisons demonstrate that the cross-correlation technique can be reliably used to characterize slit functions.
J. Bak, X. Liu, J. H. Kim, K. Chance, and D. P. Haffner
Atmos. Chem. Phys., 15, 667–683, https://doi.org/10.5194/acp-15-667-2015, https://doi.org/10.5194/acp-15-667-2015, 2015
C. Frankenberg, R. Pollock, R. A. M. Lee, R. Rosenberg, J.-F. Blavier, D. Crisp, C. W. O'Dell, G. B. Osterman, C. Roehl, P. O. Wennberg, and D. Wunch
Atmos. Meas. Tech., 8, 301–313, https://doi.org/10.5194/amt-8-301-2015, https://doi.org/10.5194/amt-8-301-2015, 2015
M. Alexe, P. Bergamaschi, A. Segers, R. Detmers, A. Butz, O. Hasekamp, S. Guerlet, R. Parker, H. Boesch, C. Frankenberg, R. A. Scheepmaker, E. Dlugokencky, C. Sweeney, S. C. Wofsy, and E. A. Kort
Atmos. Chem. Phys., 15, 113–133, https://doi.org/10.5194/acp-15-113-2015, https://doi.org/10.5194/acp-15-113-2015, 2015
G. González Abad, X. Liu, K. Chance, H. Wang, T. P. Kurosu, and R. Suleiman
Atmos. Meas. Tech., 8, 19–32, https://doi.org/10.5194/amt-8-19-2015, https://doi.org/10.5194/amt-8-19-2015, 2015
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We present and discuss the Smithsonian Astrophysical Observatory (SAO) formaldehyde retrieval algorithm for the Ozone Monitoring Instrument (OMI), which is the operational retrieval for NASA OMI H2CO.
C. Chan Miller, G. Gonzalez Abad, H. Wang, X. Liu, T. Kurosu, D. J. Jacob, and K. Chance
Atmos. Meas. Tech., 7, 3891–3907, https://doi.org/10.5194/amt-7-3891-2014, https://doi.org/10.5194/amt-7-3891-2014, 2014
V. Gryazin, C. Risi, J. Jouzel, N. Kurita, J. Worden, C. Frankenberg, V. Bastrikov, K. Gribanov, and O. Stukova
Atmos. Chem. Phys., 14, 9807–9830, https://doi.org/10.5194/acp-14-9807-2014, https://doi.org/10.5194/acp-14-9807-2014, 2014
E. A. Marais, D. J. Jacob, A. Guenther, K. Chance, T. P. Kurosu, J. G. Murphy, C. E. Reeves, and H. O. T. Pye
Atmos. Chem. Phys., 14, 7693–7703, https://doi.org/10.5194/acp-14-7693-2014, https://doi.org/10.5194/acp-14-7693-2014, 2014
E. Hache, J.-L. Attié, C. Tourneur, P. Ricaud, L. Coret, W. A. Lahoz, L. El Amraoui, B. Josse, P. Hamer, J. Warner, X. Liu, K. Chance, M. Höpfner, R. Spurr, V. Natraj, S. Kulawik, A. Eldering, and J. Orphal
Atmos. Meas. Tech., 7, 2185–2201, https://doi.org/10.5194/amt-7-2185-2014, https://doi.org/10.5194/amt-7-2185-2014, 2014
H. Wang, X. Liu, K. Chance, G. González Abad, and C. Chan Miller
Atmos. Meas. Tech., 7, 1901–1913, https://doi.org/10.5194/amt-7-1901-2014, https://doi.org/10.5194/amt-7-1901-2014, 2014
P. Zoogman, D. J. Jacob, K. Chance, X. Liu, M. Lin, A. Fiore, and K. Travis
Atmos. Chem. Phys., 14, 6261–6271, https://doi.org/10.5194/acp-14-6261-2014, https://doi.org/10.5194/acp-14-6261-2014, 2014
S. Massart, A. Agusti-Panareda, I. Aben, A. Butz, F. Chevallier, C. Crevoisier, R. Engelen, C. Frankenberg, and O. Hasekamp
Atmos. Chem. Phys., 14, 6139–6158, https://doi.org/10.5194/acp-14-6139-2014, https://doi.org/10.5194/acp-14-6139-2014, 2014
B. Dils, M. Buchwitz, M. Reuter, O. Schneising, H. Boesch, R. Parker, S. Guerlet, I. Aben, T. Blumenstock, J. P. Burrows, A. Butz, N. M. Deutscher, C. Frankenberg, F. Hase, O. P. Hasekamp, J. Heymann, M. De Mazière, J. Notholt, R. Sussmann, T. Warneke, D. Griffith, V. Sherlock, and D. Wunch
Atmos. Meas. Tech., 7, 1723–1744, https://doi.org/10.5194/amt-7-1723-2014, https://doi.org/10.5194/amt-7-1723-2014, 2014
S. Houweling, M. Krol, P. Bergamaschi, C. Frankenberg, E. J. Dlugokencky, I. Morino, J. Notholt, V. Sherlock, D. Wunch, V. Beck, C. Gerbig, H. Chen, E. A. Kort, T. Röckmann, and I. Aben
Atmos. Chem. Phys., 14, 3991–4012, https://doi.org/10.5194/acp-14-3991-2014, https://doi.org/10.5194/acp-14-3991-2014, 2014
C. Liu, S. Beirle, T. Butler, P. Hoor, C. Frankenberg, P. Jöckel, M. Penning de Vries, U. Platt, A. Pozzer, M. G. Lawrence, J. Lelieveld, H. Tost, and T. Wagner
Atmos. Chem. Phys., 14, 1717–1732, https://doi.org/10.5194/acp-14-1717-2014, https://doi.org/10.5194/acp-14-1717-2014, 2014
A. K. Thorpe, C. Frankenberg, and D. A. Roberts
Atmos. Meas. Tech., 7, 491–506, https://doi.org/10.5194/amt-7-491-2014, https://doi.org/10.5194/amt-7-491-2014, 2014
G. Liu, J. Liu, D. W. Tarasick, V. E. Fioletov, J. J. Jin, O. Moeini, X. Liu, C. E. Sioris, and M. Osman
Atmos. Chem. Phys., 13, 10659–10675, https://doi.org/10.5194/acp-13-10659-2013, https://doi.org/10.5194/acp-13-10659-2013, 2013
J. Joiner, L. Guanter, R. Lindstrot, M. Voigt, A. P. Vasilkov, E. M. Middleton, K. F. Huemmrich, Y. Yoshida, and C. Frankenberg
Atmos. Meas. Tech., 6, 2803–2823, https://doi.org/10.5194/amt-6-2803-2013, https://doi.org/10.5194/amt-6-2803-2013, 2013
L. Mandrake, C. Frankenberg, C. W. O'Dell, G. Osterman, P. Wennberg, and D. Wunch
Atmos. Meas. Tech., 6, 2851–2864, https://doi.org/10.5194/amt-6-2851-2013, https://doi.org/10.5194/amt-6-2851-2013, 2013
J. P. Parrella, K. Chance, R. J. Salawitch, T. Canty, M. Dorf, and K. Pfeilsticker
Atmos. Meas. Tech., 6, 2549–2561, https://doi.org/10.5194/amt-6-2549-2013, https://doi.org/10.5194/amt-6-2549-2013, 2013
J. Cuesta, M. Eremenko, X. Liu, G. Dufour, Z. Cai, M. Höpfner, T. von Clarmann, P. Sellitto, G. Foret, B. Gaubert, M. Beekmann, J. Orphal, K. Chance, R. Spurr, and J.-M. Flaud
Atmos. Chem. Phys., 13, 9675–9693, https://doi.org/10.5194/acp-13-9675-2013, https://doi.org/10.5194/acp-13-9675-2013, 2013
P. S. Kim, D. J. Jacob, X. Liu, J. X. Warner, K. Yang, K. Chance, V. Thouret, and P. Nedelec
Atmos. Chem. Phys., 13, 9321–9335, https://doi.org/10.5194/acp-13-9321-2013, https://doi.org/10.5194/acp-13-9321-2013, 2013
J. Bak, X. Liu, J. C. Wei, L. L. Pan, K. Chance, and J. H. Kim
Atmos. Meas. Tech., 6, 2239–2254, https://doi.org/10.5194/amt-6-2239-2013, https://doi.org/10.5194/amt-6-2239-2013, 2013
R. A. Scheepmaker, C. Frankenberg, A. Galli, A. Butz, H. Schrijver, N. M. Deutscher, D. Wunch, T. Warneke, S. Fally, and I. Aben
Atmos. Meas. Tech., 6, 879–894, https://doi.org/10.5194/amt-6-879-2013, https://doi.org/10.5194/amt-6-879-2013, 2013
J. Worden, K. Wecht, C. Frankenberg, M. Alvarado, K. Bowman, E. Kort, S. Kulawik, M. Lee, V. Payne, and H. Worden
Atmos. Chem. Phys., 13, 3679–3692, https://doi.org/10.5194/acp-13-3679-2013, https://doi.org/10.5194/acp-13-3679-2013, 2013
D. Fu, J. R. Worden, X. Liu, S. S. Kulawik, K. W. Bowman, and V. Natraj
Atmos. Chem. Phys., 13, 3445–3462, https://doi.org/10.5194/acp-13-3445-2013, https://doi.org/10.5194/acp-13-3445-2013, 2013
C. Frankenberg, D. Wunch, G. Toon, C. Risi, R. Scheepmaker, J.-E. Lee, P. Wennberg, and J. Worden
Atmos. Meas. Tech., 6, 263–274, https://doi.org/10.5194/amt-6-263-2013, https://doi.org/10.5194/amt-6-263-2013, 2013
J. Bak, J. H. Kim, X. Liu, K. Chance, and J. Kim
Atmos. Meas. Tech., 6, 239–249, https://doi.org/10.5194/amt-6-239-2013, https://doi.org/10.5194/amt-6-239-2013, 2013
H. M. Worden, M. N. Deeter, C. Frankenberg, M. George, F. Nichitiu, J. Worden, I. Aben, K. W. Bowman, C. Clerbaux, P. F. Coheur, A. T. J. de Laat, R. Detweiler, J. R. Drummond, D. P. Edwards, J. C. Gille, D. Hurtmans, M. Luo, S. Martínez-Alonso, S. Massie, G. Pfister, and J. X. Warner
Atmos. Chem. Phys., 13, 837–850, https://doi.org/10.5194/acp-13-837-2013, https://doi.org/10.5194/acp-13-837-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields
Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China
Can the remote sensing of combustion phase improve estimates of landscape fire smoke emission rate and composition?
Tropospheric NO2 retrieval algorithm for geostationary satellite instruments: applications to GEMS
Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean
Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements
Merging TEMPEST microwave and GOES-16 geostationary IR soundings for improved water vapor profiles
Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission
Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection
Assessment of the contribution of the Meteosat Third Generation Infrared Sounder (MTG-IRS) for the characterisation of ozone over Europe
Assessing the potential of free-tropospheric water vapour isotopologue satellite observations for improving the analyses of convective events
Current potential of CH4 emission estimates using TROPOMI in the Middle East
A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument
Developments on a 22GHz Microwave Radiometer and Reprocessing of 13-Year Time Series for Water Vapour Studies
Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks
Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
A new method for estimating megacity NOx emissions and lifetimes from satellite observations
Accounting for the effect of aerosols in GHGSat methane retrieval
NitroNet – A deep-learning NO2 profile retrieval prototype for the TROPOMI satellite instrument
A survey of methane point source emissions from coal mines in Shanxi province of China using AHSI on board Gaofen-5B
Global retrieval of stratospheric and tropospheric BrO columns from the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on board the Suomi-NPP satellite
IMK–IAA MIPAS retrieval version 8: CH4 and N2O
Report on Landsat 8 and Sentinel-2B observations of the Nord Stream 2 pipeline methane leak
U-Plume: automated algorithm for plume detection and source quantification by satellite point-source imagers
CH4Net: a deep learning model for monitoring methane super-emitters with Sentinel-2 imagery
Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates
Quantitative imaging of carbon dioxide plumes using a ground-based shortwave infrared spectral camera
The transition to new ozone absorption cross sections for Dobson and Brewer total ozone measurements
Advantages of assimilating multispectral satellite retrievals of atmospheric composition: a demonstration using MOPITT carbon monoxide products
An improved OMI ozone profile research product version 2.0 with collection 4 L1b data and algorithm updates
Tropospheric ozone column dataset from OMPS-LP/OMPS-NM limb–nadir matching
Version 8 IMK/IAA MIPAS measurements of CFC-11, CFC-12, and HCFC-22
The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product
Level0 to Level1B processor for MethaneAIR
Exploiting the entire near-infrared spectral range to improve the detection of methane plumes with high-resolution imaging spectrometers
The differences between remote sensing and in situ air pollutants measurements over the Canadian Oil Sands
A method for estimating localized CO2 emissions from co-located satellite XCO2 and NO2 images
The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty
Airborne lidar measurements of atmospheric CO2 column concentrations to cloud tops made during the 2017 ASCENDS/ABoVE campaign
Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources
A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10
MIPAS ozone retrieval version 8: middle-atmosphere measurements
Atmospheric N2O and CH4 total columns retrieved from low-resolution Fourier transform infrared (FTIR) spectra (Bruker VERTEX 70) in the mid-infrared region
A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations
Estimation of anthropogenic and volcanic SO2 emissions from satellite data in the presence of snow/ice on the ground
The IASI NH3 version 4 product: averaging kernels and improved consistency
A physically based correction for stray light in Brewer spectrophotometer data analysis
Optimal selection of satellite XCO2 images over cities for urban CO2 emission monitoring using a global adaptive-mesh model
A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm
Swathi Maratt Satheesan, Kai-Uwe Eichmann, John P. Burrows, Mark Weber, Ryan Stauffer, Anne M. Thompson, and Debra Kollonige
Atmos. Meas. Tech., 17, 6459–6484, https://doi.org/10.5194/amt-17-6459-2024, https://doi.org/10.5194/amt-17-6459-2024, 2024
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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.
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.
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.
Alistair Bell, Eric Sauvageat, Gunter Stober, Klemens Hocke, and Axel Murk
EGUsphere, https://doi.org/10.5194/egusphere-2024-2474, https://doi.org/10.5194/egusphere-2024-2474, 2024
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Hardware and software developments have been made on a 22 GHz microwave radiometer for the measurement of middle atmosphere water vapour near Bern, Switzerland. Previous measurements dating back to 2010 have been re-calibrated and an improved optimal estimation retrieval performed on these measurements, giving a 13 year long dataset. Measurements made with new and improved instrumental hardware are used to correct previous measurements, which show better agreement than the non-corrected dataset.
Maximilian Reuter, Michael Hilker, Stefan Noël, Antonio Di Noia, Michael Weimer, Oliver Schneising, Michael Buchwitz, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2365, https://doi.org/10.5194/egusphere-2024-2365, 2024
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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.
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.
Leon Kuhn, Steffen Beirle, Sergey Osipov, Andrea Pozzer, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2024-1196, https://doi.org/10.5194/egusphere-2024-1196, 2024
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This paper presents a new machine-learning model, which allows to compute NO2 concentration profiles from satellite observations. The neural network was trained on synthetic data from the regional chemistry and transport model WRF-Chem. It is the first model of this kind. We present a thorough model validation study, including different seasons and regions of the world.
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.
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.
Xiaoyi Zhao, Vitali Fioletov, Debora Griffin, Chris McLinden, Ralf Staebler, Cristian Mihele, Kevin Strawbridge, Jonathan Davies, Ihab Abboud, Sum Chi Lee, Alexander Cede, Martin Tiefengraber, and Robert Swap
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-27, https://doi.org/10.5194/amt-2024-27, 2024
Revised manuscript accepted for AMT
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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 the meteorological conditions (wind directions, speed, and boundary layer conditions) will strongly affect the agreement between the two measurements.
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.
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.
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.
Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-199, https://doi.org/10.5194/amt-2023-199, 2023
Revised manuscript accepted for AMT
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We study the capacity of XCO2 space-borne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods, and objective criteria for image selection. Wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias on the emission estimation of -7 % of the emissions and a spread of 56 %. Other images give a bias of -31 % and a spread of 99 %.
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.
Cited articles
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Short summary
Accurately characterizing the instrument line shape (ILS) of the Orbiting Carbon Observatory-2 (OCO-2) is challenging and highly important due to its high spectral resolution and requirement for retrieval accuracy. Measured ILS during preflight experiments has been used in the OCO-2 CO2 retrieval. This study derives the on-orbit ILS of OCO-2 using its solar measurements and answers the questions whether on-orbit ILS has changed compared to preflight and whether it varies during the mission.
Accurately characterizing the instrument line shape (ILS) of the Orbiting Carbon Observatory-2...