Articles | Volume 13, issue 7
https://doi.org/10.5194/amt-13-4009-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-4009-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jul 2020
Research article |
| 24 Jul 2020
| 24 Jul 2020
On the performance of satellite-based observations of XCO2 in capturing the NOAA Carbon Tracker model and ground-based flask observations over Africa's land mass
Anteneh Getachew Mengistu
CORRESPONDING AUTHOR
Department of Physics, Addis Ababa University, Addis Ababa, Ethiopia
Gizaw Mengistu Tsidu
Department of Physics, Addis Ababa University, Addis Ababa, Ethiopia
Department of Earth and Environment, Botswana International University of Science and Technology, Palapye, Botswana
Related authors
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
Short summary
Short summary
In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Anteneh Getachew Mengistu and Gizaw Mengistu Tsidu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-84, https://doi.org/10.5194/amt-2018-84, 2018
Revised manuscript not accepted
Gezahegn Sufa Daba and Gizaw Mengistu Tsidu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2232, https://doi.org/10.5194/egusphere-2025-2232, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This study investigates non-ideal instrumental effects that could degrade the performance of a high-resolution infrared spectrometer. By using standard gas cell measurement, it identifies key sources of modulation loss and spectral artifacts. The results help improve understanding of instrumental stability and support more accurate use of the spectrometer in long-term scientific applications.
Carlos Alberti, Frank Hase, Matthias Frey, Darko Dubravica, Thomas Blumenstock, Angelika Dehn, Paolo Castracane, Gregor Surawicz, Roland Harig, Bianca C. Baier, Caroline Bès, Jianrong Bi, Hartmut Boesch, André Butz, Zhaonan Cai, Jia Chen, Sean M. Crowell, Nicholas M. Deutscher, Dragos Ene, Jonathan E. Franklin, Omaira García, David Griffith, Bruno Grouiez, Michel Grutter, Abdelhamid Hamdouni, Sander Houweling, Neil Humpage, Nicole Jacobs, Sujong Jeong, Lilian Joly, Nicholas B. Jones, Denis Jouglet, Rigel Kivi, Ralph Kleinschek, Morgan Lopez, Diogo J. Medeiros, Isamu Morino, Nasrin Mostafavipak, Astrid Müller, Hirofumi Ohyama, Paul I. Palmer, Mahesh Pathakoti, David F. Pollard, Uwe Raffalski, Michel Ramonet, Robbie Ramsay, Mahesh Kumar Sha, Kei Shiomi, William Simpson, Wolfgang Stremme, Youwen Sun, Hiroshi Tanimoto, Yao Té, Gizaw Mengistu Tsidu, Voltaire A. Velazco, Felix Vogel, Masataka Watanabe, Chong Wei, Debra Wunch, Marcia Yamasoe, Lu Zhang, and Johannes Orphal
Atmos. Meas. Tech., 15, 2433–2463, https://doi.org/10.5194/amt-15-2433-2022, https://doi.org/10.5194/amt-15-2433-2022, 2022
Short summary
Short summary
Space-borne greenhouse gas missions require ground-based validation networks capable of providing fiducial reference measurements. Here, considerable refinements of the calibration procedures for the COllaborative Carbon Column Observing Network (COCCON) are presented. Laboratory and solar side-by-side procedures for the characterization of the spectrometers have been refined and extended. Revised calibration factors for XCO2, XCO and XCH4 are provided, incorporating 47 new spectrometers.
Anteneh Getachew Mengistu, Gizaw Mengistu Tsidu, Gerbrand Koren, Maurits L. Kooreman, K. Folkert Boersma, Torbern Tagesson, Jonas Ardö, Yann Nouvellon, and Wouter Peters
Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, https://doi.org/10.5194/bg-18-2843-2021, 2021
Short summary
Short summary
In this study, we assess the usefulness of Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval (SIFTER) data from the GOME-2A instrument and near-infrared reflectance of vegetation (NIRv) from MODIS to capture the seasonality and magnitudes of gross primary production (GPP) derived from six eddy-covariance flux towers in Africa in the overlap years between 2007–2014. We also test the robustness of sun-induced fluoresence and NIRv to compare the seasonality of GPP for the major biomes.
Temesgen Yirdaw Berhe, Gizaw Mengistu Tsidu, Thomas Blumenstock, Frank Hase, and Gabriele P. Stiller
Atmos. Meas. Tech., 13, 4079–4096, https://doi.org/10.5194/amt-13-4079-2020, https://doi.org/10.5194/amt-13-4079-2020, 2020
Short summary
Short summary
The retrieved CH4 and N2O VMR and column amounts from Addis Ababa, tropical site, are found to exhibit very good agreement with all coincident satellite observations (MIPAS, MLS, and AIRS). Furthermore, the bias obtained from the comparison is comparable to the precision of FTIR measurement, which allows the use of data in further scientific studies as it represents a unique environment of tropical Africa, a region poorly investigated in the past.
Gizaw Mengistu Tsidu and Mulugeta Melaku Zegeye
Ann. Geophys., 38, 725–748, https://doi.org/10.5194/angeo-38-725-2020, https://doi.org/10.5194/angeo-38-725-2020, 2020
Short summary
Short summary
The performance of the IRI-2016 model in simulating GPS-TEC is assessed based on various statistical tools during two distinct solar activity periods. In particular, the categorical metrics used in the study to assess the performance of the empirical and climatological IRI-2016 model at the margins of the TEC distribution reveal remarkable model skill in simulating the observed tails of the TEC distribution, which is much better than accurately simulating the observed climatology as designed.
Temesgen Yirdaw Berhe, Gizaw Mengistu Tsidu, Thomas Blumenstock, Frank Hase, Thomas von Clarmann, Justus Notholt, and Emmanuel Mahieu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-209, https://doi.org/10.5194/amt-2019-209, 2019
Revised manuscript not accepted
Short summary
Short summary
This study aims to assess the latitudinal variation of MIPAS version
V5R_CH4_220 and V5R_CH4_224 uncertainty. Furthermore, we analyze the relationship between these uncertainties and the variability of water vapor. Mainly, the high uncertainty found in tropics for MIPAS CH4 220 is highly associated with variability of water vapour. However, this effect has been reduced in the new updated MIPAS CH4 224 datasets due to jointly fitted water profile with methane.
Matthias Frey, Mahesh K. Sha, Frank Hase, Matthäus Kiel, Thomas Blumenstock, Roland Harig, Gregor Surawicz, Nicholas M. Deutscher, Kei Shiomi, Jonathan E. Franklin, Hartmut Bösch, Jia Chen, Michel Grutter, Hirofumi Ohyama, Youwen Sun, André Butz, Gizaw Mengistu Tsidu, Dragos Ene, Debra Wunch, Zhensong Cao, Omaira Garcia, Michel Ramonet, Felix Vogel, and Johannes Orphal
Atmos. Meas. Tech., 12, 1513–1530, https://doi.org/10.5194/amt-12-1513-2019, https://doi.org/10.5194/amt-12-1513-2019, 2019
Short summary
Short summary
In a 3.5-year long study, the long-term performance of a mobile EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference spectrometer. We find that the EM27/SUN is stable on timescales of several years, qualifying it for permanent carbon cycle studies.
The performance of an ensemble of 30 EM27/SUN spectrometers was also tested in the framework of the COllaborative Carbon Column Observing Network (COCCON) and found to be very uniform.
Anteneh Getachew Mengistu and Gizaw Mengistu Tsidu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-84, https://doi.org/10.5194/amt-2018-84, 2018
Revised manuscript not accepted
Milkessa Gebeyehu Homa, Gizaw Mengistu Tsidu, and Derese Tekestebrihan Nega
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-133, https://doi.org/10.5194/acp-2017-133, 2017
Revised manuscript not accepted
Short summary
Short summary
This article provides aerosol climatology of Ethiopia for 21 years. The result showed that aerosol loading over the region is steadily increasing in different sizes. The dominant radius of the particulate matters are between 0.452–0.525 μm, & dominated by reflective type aerosol. This influence the solar radiation budget of the earth, which in turn influences the Earth's climate in different ways. Hence, it is the right time to give the right attention to air quality & climate change impacts.
Sabine Barthlott, Matthias Schneider, Frank Hase, Thomas Blumenstock, Matthäus Kiel, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Gizaw Mengistu Tsidu, Samuel Takele Kenea, Michel Grutter, Eddy F. Plaza-Medina, Wolfgang Stremme, Kim Strong, Dan Weaver, Mathias Palm, Thorsten Warneke, Justus Notholt, Emmanuel Mahieu, Christian Servais, Nicholas Jones, David W. T. Griffith, Dan Smale, and John Robinson
Earth Syst. Sci. Data, 9, 15–29, https://doi.org/10.5194/essd-9-15-2017, https://doi.org/10.5194/essd-9-15-2017, 2017
Short summary
Short summary
Tropospheric water vapour isotopologue distributions have been consistently generated and quality-filtered for 12 globally distributed ground-based FTIR sites. The products are provided as two data types. The first type is best-suited for tropospheric water vapour distribution studies. The second type is needed for analysing moisture pathways by means of {H2O,δD}-pair distributions. This paper describes the data types and gives recommendations for their correct usage.
Matthias Schneider, Andreas Wiegele, Sabine Barthlott, Yenny González, Emanuel Christner, Christoph Dyroff, Omaira E. García, Frank Hase, Thomas Blumenstock, Eliezer Sepúlveda, Gizaw Mengistu Tsidu, Samuel Takele Kenea, Sergio Rodríguez, and Javier Andrey
Atmos. Meas. Tech., 9, 2845–2875, https://doi.org/10.5194/amt-9-2845-2016, https://doi.org/10.5194/amt-9-2845-2016, 2016
Short summary
Short summary
Tropospheric {H2O,δD} pairs can be observed by remote sensing techniques, but the data quality strongly depends on a comprehensive consideration of the complex nature and a careful calibration of the remote sensing data pairs. This paper reviews the quality assurance/documentation activities of the MUSICA project and demonstrates that MUSICA’s ground-based FTIR and space-based IASI {H2O,δD} pair products are accurate and can be generated at a global scale with high resolution and for long periods.
G. Mengistu Tsidu, T. Blumenstock, and F. Hase
Atmos. Meas. Tech., 8, 3277–3295, https://doi.org/10.5194/amt-8-3277-2015, https://doi.org/10.5194/amt-8-3277-2015, 2015
Short summary
Short summary
Intercomparison of precipitable water vapour from ERA-Interim, Fourier transform infrared spectrometer, GPS and radiosonde over complex topography of Ethiopia was made for the first time over a data-void region of eastern Africa. The study reveals weakness of ERA-Interim reanalysis in capturing diurnal and to some extent seasonal variabilities. The weakness can be improved through additional data assimilation, adaptation of convection and land surface modules to the reality in the region.
F. Hase, M. Frey, T. Blumenstock, J. Groß, M. Kiel, R. Kohlhepp, G. Mengistu Tsidu, K. Schäfer, M. K. Sha, and J. Orphal
Atmos. Meas. Tech., 8, 3059–3068, https://doi.org/10.5194/amt-8-3059-2015, https://doi.org/10.5194/amt-8-3059-2015, 2015
M. Frey, F. Hase, T. Blumenstock, J. Groß, M. Kiel, G. Mengistu Tsidu, K. Schäfer, M. K. Sha, and J. Orphal
Atmos. Meas. Tech., 8, 3047–3057, https://doi.org/10.5194/amt-8-3047-2015, https://doi.org/10.5194/amt-8-3047-2015, 2015
S. Takele Kenea, G. Mengistu Tsidu, T. Blumenstock, F. Hase, T. von Clarmann, and G. P. Stiller
Atmos. Meas. Tech., 6, 495–509, https://doi.org/10.5194/amt-6-495-2013, https://doi.org/10.5194/amt-6-495-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Advancing CH4 and N2O retrieval strategies for NDACC/IRWG FTIR observations with the support of airborne in situ measurements
Atmospheric horizontal gradients measured with eight co-located GNSS stations and a microwave radiometer
Validation of the version 4.5 MAESTRO ozone and NO2 measurements
Performance assessment of the IASI-O3 KOPRA product for observing midlatitude tropospheric ozone evolution for 15 years: validation with ozone sondes and consistency of the three IASI instruments
Long-term evolution of the calibration constant on a mobile/field campaign water vapour Raman lidar
Benchmarking data-driven inversion methods for the estimation of local CO2 emissions from synthetic satellite images of XCO2 and NO2
Validation of 12 years (2008–2019) of IASI-A CO with IAGOS aircraft observations
Assessment of laboratory O4 absorption cross-sections at 360 nm using atmospheric long-path DOAS observations
Diurnal variations of NO2 tropospheric vertical column density over the Seoul metropolitan area from the Geostationary Environment Monitoring Spectrometer (GEMS): seasonal differences and the influence of the a priori NO2 profile
Inter-comparison of tropospheric ozone column datasets from combined nadir and limb satellite observations
Validation of ACE-FTS version 5.2 ozone data with ozonesonde measurements
Intercomparison of long-term ground-based measurements of total, tropospheric, and stratospheric ozone at Lauder, New Zealand
First evaluation of the GEMS glyoxal products against TROPOMI and ground-based measurements
Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements
Using open-path dual-comb spectroscopy to monitor methane emissions from simulated grazing cattle
Greenhouse gas column observations from a portable spectrometer in Uganda
Independent validation of IASI/MetOp-A LMD and RAL CH4 products using CAMS model, in situ profiles, and ground-based FTIR measurements
Joint spectral retrievals of ozone with Suomi NPP CrIS augmented by S5P/TROPOMI
An evaluation of atmospheric absorption models at millimetre and sub-millimetre wavelengths using airborne observations
Applicability of the inverse dispersion method to measure emissions from animal housings
5 years of Sentinel-5P TROPOMI operational ozone profiling and geophysical validation using ozonesonde and lidar ground-based networks
Using a portable FTIR spectrometer to evaluate the consistency of Total Carbon Column Observing Network (TCCON) measurements on a global scale: the Collaborative Carbon Column Observing Network (COCCON) travel standard
Comparison of the H2O, HDO and δD stratospheric climatologies between the MIPAS-ESA V8, MIPAS-IMK V5 and ACE-FTS V4.1/4.2 satellite datasets
TROPESS-CrIS CO single-pixel vertical profiles: intercomparisons with MOPITT and model simulations for 2020 western US wildfires
TOLNet validation of satellite ozone profiles in the troposphere: impact of retrieval wavelengths
An uncertainty methodology for solar occultation flux measurements: ammonia emissions from livestock production
Validation of Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) chlorodifluoromethane (HCFC-22) in the upper troposphere and lower stratosphere
First validation of high-resolution satellite-derived methane emissions from an active gas leak in the UK
Ship- and aircraft-based XCH4 over oceans as a new tool for satellite validation
Single-blind test of nine methane-sensing satellite systems from three continents
Water vapor measurements inside clouds and storms using a differential absorption radar
Evaluation of the first year of Pandora NO2 measurements over Beijing and application to satellite validation
Validation of MUSES NH3 observations from AIRS and CrIS against aircraft measurements from DISCOVER-AQ and a surface network in the Magic Valley
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer
Evaluation of total ozone measurements from Geostationary Environmental Monitoring Spectrometer (GEMS)
To new heights by flying low: comparison of aircraft vertical NO2 profiles to model simulations and implications for TROPOMI NO2 retrievals
Local comparisons of tropospheric ozone: vertical soundings at two neighbouring stations in southern Bavaria
Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of NO2 and H2CO at Kinshasa and comparisons with TROPOMI observations
Total column ozone trends from the NASA Merged Ozone time series 1979 to 2021 showing latitude-dependent ozone recovery dates (1994 to 1998)
The SPARC water vapour assessment II: biases and drifts of water vapour satellite data records with respect to frost point hygrometer records
Vicarious calibration of the Tropospheric Monitoring Instrument (TROPOMI) short-wave infrared (SWIR) module over the Railroad Valley Playa
First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements
A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases
Evaluating the consistency between OCO-2 and OCO-3 XCO2 estimates derived from the NASA ACOS version 10 retrieval algorithm
OLCI-A/B tandem phase: evaluation of FLuorescence EXplorer (FLEX)-like radiances and estimation of systematic differences between OLCI-A and OLCI-FLEX
Multi-parameter dynamical diagnostics for upper tropospheric and lower stratospheric studies
An approach to track instrument calibration and produce consistent products with the version-8 total column ozone algorithm (V8TOZ)
Satellite remote-sensing capability to assess tropospheric-column ratios of formaldehyde and nitrogen dioxide: case study during the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) field campaign
Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign
Ivan Ortega, James W. Hannigan, Bianca C. Baier, Kathryn McKain, and Dan Smale
Atmos. Meas. Tech., 18, 2353–2371, https://doi.org/10.5194/amt-18-2353-2025, https://doi.org/10.5194/amt-18-2353-2025, 2025
Short summary
Short summary
This study evaluates retrieval strategies for CH4 and N2O using high-resolution FTIR observations from Boulder, Colorado. By comparing results with independent AirCore and aircraft in situ measurements, the analysis validates retrieval accuracy and quantifies uncertainties. The findings highlight the benefits of updated spectroscopy and improved a priori profiles and highlight consistent agreement with in situ data.
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 18, 2069–2082, https://doi.org/10.5194/amt-18-2069-2025, https://doi.org/10.5194/amt-18-2069-2025, 2025
Short summary
Short summary
We analyzed signal delays in the atmosphere, using eight co-located global navigation satellite system (GNSS) stations, and compared linear horizontal gradients with microwave radiometer data. A weak constraint applied when estimating gradients in the GNSS data processing, enhancing short-lived gradient tracking but increasing noise, which can be mitigated by averaging gradients from the eight stations. This approach may enhance GNSS-based atmospheric monitoring for use in weather nowcasting.
Paul S. Jeffery, James R. Drummond, C. Thomas McElroy, Kaley A. Walker, and Jiansheng Zou
Atmos. Meas. Tech., 18, 569–602, https://doi.org/10.5194/amt-18-569-2025, https://doi.org/10.5194/amt-18-569-2025, 2025
Short summary
Short summary
The MAESTRO instrument has been monitoring ozone and NO2 since February 2004. A new version of these data products has recently been released; however, these new products must be validated against other datasets to ensure their validity. This study presents such an assessment, using measurements from 11 satellite instruments to characterize the new MAESTRO products. In the stratosphere, good agreement is found for ozone and acceptable agreement is found for NO2 with these other datasets.
Gaëlle Dufour, Maxim Eremenko, Juan Cuesta, Gérard Ancellet, Michael Gill, Eliane Maillard Barras, and Roeland Van Malderen
EGUsphere, https://doi.org/10.5194/egusphere-2024-4096, https://doi.org/10.5194/egusphere-2024-4096, 2025
Short summary
Short summary
The IASI-O3 KOPRA v3.0 product shows strong consistency (<1 %) for the three IASI instruments. The validation against homogenized ozone sondes reveals an overall good agreement with slight biases (3–6 %) in tropospheric ozone and a possible temporal drift but difficult to assess due to the limited number of sites. No specific trends are estimated for the tropospheric ozone column for 2008–2022, but persistent negative trends are observed in the lower troposphere.
Patrick Chazette, Julien Totems, and Frédéric Laly
EGUsphere, https://doi.org/10.5194/egusphere-2024-3583, https://doi.org/10.5194/egusphere-2024-3583, 2025
Short summary
Short summary
The use of active remote sensing instruments to sample the atmospheric environment requires accurate calibration that is stable over time so that measurements are reproducible. This is the case for measurements of atmospheric water vapour using Raman lidar, which are of growing interest in the context of climate risks such as extreme precipitation. This study addresses this issue. It is based on 6 campaigns spread over a period of 7 years between 2016 and 2022.
Diego Santaren, Janne Hakkarainen, Gerrit Kuhlmann, Erik Koene, Frédéric Chevallier, Iolanda Ialongo, Hannakaisa Lindqvist, Janne Nurmela, Johanna Tamminen, Laia Amorós, Dominik Brunner, and Grégoire Broquet
Atmos. Meas. Tech., 18, 211–239, https://doi.org/10.5194/amt-18-211-2025, https://doi.org/10.5194/amt-18-211-2025, 2025
Short summary
Short summary
This study evaluates data-driven inversion methods for estimating CO2 emissions from local sources, such as power plants and cities, using meteorological data and XCO2 and NO2 satellite images rather than atmospheric transport modeling. We assess and compare the performance of five different methods using simulations of 1 year of satellite images, taken from the upcoming Copernicus CO2 Monitoring Mission, covering 15 power plants and the city of Berlin, Germany.
Brice Barret, Pierre Loicq, Eric Le Flochmoën, Yasmine Bennouna, Juliette Hadji-Lazaro, Daniel Hurtmans, and Bastien Sauvage
Atmos. Meas. Tech., 18, 129–149, https://doi.org/10.5194/amt-18-129-2025, https://doi.org/10.5194/amt-18-129-2025, 2025
Short summary
Short summary
Profiles of carbon monoxide (CO) retrieved from the Infrared Atmospheric Sounding Interferometer (IASI) with the SOftware for a Fast Retrieval of IASI Data (SOFRID) and Fast Optimal Retrievals on Layers for IASI (FORLI) are validated with 8500 observations at 33 airports from the In-service Aircraft for a Global Observing System (IAGOS) for 2008–2019. IASI retrievals underestimate CO, with stronger bias in the middle to upper troposphere for SOFRID and in the lower troposphere for FORLI.
Bianca Lauster, Udo Frieß, Jan-Marcus Nasse, Ulrich Platt, and Thomas Wagner
EGUsphere, https://doi.org/10.5194/egusphere-2024-3881, https://doi.org/10.5194/egusphere-2024-3881, 2025
Short summary
Short summary
Remote sensing measurements of scattered sunlight use the atmospheric absorption of O4 (oxygen dimer) to derive cloud and aerosol properties. However, inconsistencies between measurements and radiative transfer simulations were found recently and, so far, there is no consensus on how to deal with these appropriately. In this study, long-term long-path differential optical absorption spectroscopy (DOAS) observations are analysed and very good agreement with laboratory measurements was found.
Seunghwan Seo, Si-Wan Kim, Kyoung-Min Kim, Andreas Richter, Kezia Lange, John P. Burrows, Junsung Park, Hyunkee Hong, Hanlim Lee, Ukkyo Jeong, Jung-Hun Woo, and Jhoon Kim
Atmos. Meas. Tech., 18, 115–128, https://doi.org/10.5194/amt-18-115-2025, https://doi.org/10.5194/amt-18-115-2025, 2025
Short summary
Short summary
Over the Seoul metropolitan area, tropospheric NO2 vertical column densities from the Geostationary Environment Monitoring Spectrometer show distinct seasonal features. Also, varying a priori data have substantial impacts on the observed NO2 columns. The a priori data from different chemical transport models resulted in differences of up to −18.3 %. Notably, diurnal patterns of observed NO2 columns are similar for all datasets, although their a priori data exhibit contrasting diurnal patterns.
Carlo Arosio, Viktoria Sofieva, Andrea Orfanoz-Cheuquelaf, Alexei Rozanov, Klaus-Peter Heue, Edward Malina, Ryan M. Stauffer, David Tarasick, Roeland Van Malderen, Jerry R. Ziemke, and Mark Weber
EGUsphere, https://doi.org/10.5194/egusphere-2024-3737, https://doi.org/10.5194/egusphere-2024-3737, 2024
Short summary
Short summary
Tropospheric ozone affects air quality and climate, being a pollutant and a greenhouse gas. We analysed satellite data of tropospheric ozone that combine two types of observations: one providing stratospheric ozone and another measuring total ozone. We compare common climatological features and study the influence of the tropopause (troposphere to stratosphere boundary) on the results. We also examine trends over the last 20 years and compare satellite data with ozonesondes to identify drifts.
Jiansheng Zou, Kaley A. Walker, Patrick E. Sheese, Chris D. Boone, Ryan M. Stauffer, Anne M. Thompson, and David W. Tarasick
Atmos. Meas. Tech., 17, 6983–7005, https://doi.org/10.5194/amt-17-6983-2024, https://doi.org/10.5194/amt-17-6983-2024, 2024
Short summary
Short summary
Ozone measurements from the ACE-FTS satellite instrument have been compared to worldwide balloon-borne ozonesonde profiles using pairs of closely spaced profiles and monthly averaged profiles. ACE-FTS typically measures more ozone in the stratosphere by up to 10 %. The long-term stability of the ACE-FTS ozone data is good, exhibiting small (but non-significant) drifts of less than 3 % per decade in the stratosphere. Lower in the profiles, the calculated drifts are larger (up to 10 % per decade).
Robin Björklund, Corinne Vigouroux, Peter Effertz, Omaira E. García, Alex Geddes, James Hannigan, Koji Miyagawa, Michael Kotkamp, Bavo Langerock, Gerald Nedoluha, Ivan Ortega, Irina Petropavlovskikh, Deniz Poyraz, Richard Querel, John Robinson, Hisako Shiona, Dan Smale, Penny Smale, Roeland Van Malderen, and Martine De Mazière
Atmos. Meas. Tech., 17, 6819–6849, https://doi.org/10.5194/amt-17-6819-2024, https://doi.org/10.5194/amt-17-6819-2024, 2024
Short summary
Short summary
Different ground-based ozone measurements from the last 2 decades at Lauder are compared to each other. We want to know why different trends have been observed in the stratosphere. Also, the quality and relevance of tropospheric datasets need to be evaluated. While remaining drifts are still present, our study explains roughly half of the differences in observed trends in previous studies and shows the necessity for continuous review and improvement of the measurements.
Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, Gitaek T. Lee, Sieun D. Lee, Seunga Shin, Dong-Won Lee, Hyunkee Hong, Christophe Lerot, Isabelle De Smedt, Thomas Danckaert, Francois Hendrick, and Hitoshi Irie
Atmos. Meas. Tech., 17, 6369–6384, https://doi.org/10.5194/amt-17-6369-2024, https://doi.org/10.5194/amt-17-6369-2024, 2024
Short summary
Short summary
In this study, we evaluated the GEMS glyoxal products by comparing them with TROPOMI and MAX-DOAS measurements. GEMS and TROPOMI VCDs present similar spatial distributions. Monthly variations in GEMS VCDs and TROPOMI and MAX-DOAS VCDs differ in northeastern Asia, which we attributed to a polluted reference spectrum and high NO2 concentrations. GEMS glyoxal products with unparalleled temporal resolution would enrich our understanding of VOC emissions and diurnal variation.
Kezia Lange, Andreas Richter, Tim Bösch, Bianca Zilker, Miriam Latsch, Lisa K. Behrens, Chisom M. Okafor, Hartmut Bösch, John P. Burrows, Alexis Merlaud, Gaia Pinardi, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Steffen Ziegler, Simona Ripperger-Lukosiunaite, Leon Kuhn, Bianca Lauster, Thomas Wagner, Hyunkee Hong, Donghee Kim, Lim-Seok Chang, Kangho Bae, Chang-Keun Song, Jong-Uk Park, and Hanlim Lee
Atmos. Meas. Tech., 17, 6315–6344, https://doi.org/10.5194/amt-17-6315-2024, https://doi.org/10.5194/amt-17-6315-2024, 2024
Short summary
Short summary
Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation of important air pollutants such as nitrogen dioxide (NO2) over large areas. The South Korean instrument GEMS, launched in February 2020, is the first instrument in geostationary orbit and covers a large part of Asia. Our investigations show the observed diurnal evolution of NO2 at different measurement sites.
Chinthaka Weerasekara, Lindsay C. Morris, Nathan A. Malarich, Fabrizio R. Giorgetta, Daniel I. Herman, Kevin C. Cossel, Nathan R. Newbury, Clenton E. Owensby, Stephen M. Welch, Cosmin Blaga, Brett D. DePaola, Ian Coddington, Brian R. Washburn, and Eduardo A. Santos
Atmos. Meas. Tech., 17, 6107–6117, https://doi.org/10.5194/amt-17-6107-2024, https://doi.org/10.5194/amt-17-6107-2024, 2024
Short summary
Short summary
Most methane emissions during the life cycle of beef cattle occur during the grazing phase. Measuring methane in grazing systems is difficult due to the high mobility and low density of animals. This work investigates if dual-comb spectroscopy can measure methane emissions from small cattle herds. An enhancement of 10 nmol mol-1 methane above the atmospheric background was measured, equivalent to 20 head located 60 m away. The calculated methane flux was within 5 % of the actual release rate.
Neil Humpage, Hartmut Boesch, William Okello, Jia Chen, Florian Dietrich, Mark F. Lunt, Liang Feng, Paul I. Palmer, and Frank Hase
Atmos. Meas. Tech., 17, 5679–5707, https://doi.org/10.5194/amt-17-5679-2024, https://doi.org/10.5194/amt-17-5679-2024, 2024
Short summary
Short summary
We used a Bruker EM27/SUN spectrometer within an automated weatherproof enclosure to measure greenhouse gas column concentrations over a 3-month period in Jinja, Uganda. The portability of the EM27/SUN allows us to evaluate satellite and model data in locations not covered by traditional validation networks. This is of particular value in tropical Africa, where extensive terrestrial ecosystems are a significant store of carbon and play a key role in the atmospheric budgets of CO2 and CH4.
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge
Atmos. Meas. Tech., 17, 5491–5524, https://doi.org/10.5194/amt-17-5491-2024, https://doi.org/10.5194/amt-17-5491-2024, 2024
Short summary
Short summary
The paper discusses two very distinct methane products from the IASI instrument aboard the MetOp-A satellite. One (referred to as LMD NLISv8.3) uses a machine-learning approach, while the other (RALv2.0) uses a more conventional optimal estimation approach. We used a variety of model and independent reference measurement data to assess both products' overall quality, their differences, and specific aspects of each product that would benefit from further analysis by the product development teams.
Edward Malina, Kevin W. Bowman, Valentin Kantchev, Le Kuai, Thomas P. Kurosu, Kazuyuki Miyazaki, Vijay Natraj, Gregory B. Osterman, Fabiano Oyafuso, and Matthew D. Thill
Atmos. Meas. Tech., 17, 5341–5371, https://doi.org/10.5194/amt-17-5341-2024, https://doi.org/10.5194/amt-17-5341-2024, 2024
Short summary
Short summary
Characterizing the distribution of ozone in the atmosphere is a challenging problem, with current Earth observation satellites using either thermal infrared (TIR) or ultraviolet (UV) instruments, sensitive to different portions of the atmosphere, making it difficult to gain a full picture. In this work, we combine measurements from the TIR and UV instruments Suomi NPP CrIS and Sentinel-5P/TROPOMI to improve sensitivity through the whole atmosphere and improve knowledge of ozone distribution.
Stuart Fox, Vinia Mattioli, Emma Turner, Alan Vance, Domenico Cimini, and Donatello Gallucci
Atmos. Meas. Tech., 17, 4957–4978, https://doi.org/10.5194/amt-17-4957-2024, https://doi.org/10.5194/amt-17-4957-2024, 2024
Short summary
Short summary
Airborne observations are used to evaluate two models for absorption and emission by atmospheric gases, including water vapour and oxygen, at microwave and sub-millimetre wavelengths. These models are needed for the Ice Cloud Imager (ICI) on the next generation of European polar-orbiting weather satellites, which measures at frequencies up to 664 GHz. Both models can provide a good match to measurements from airborne radiometers and are sufficiently accurate for use with ICI.
Marcel Bühler, Christoph Häni, Albrecht Neftel, Patrice Bühler, Christof Ammann, and Thomas Kupper
Atmos. Meas. Tech., 17, 4649–4658, https://doi.org/10.5194/amt-17-4649-2024, https://doi.org/10.5194/amt-17-4649-2024, 2024
Short summary
Short summary
Methane was released from an artificial source inside a barn to test the applicability of the inverse dispersion method (IDM). Multiple open-path concentration devices and ultrasonic anemometers were used at the site. It is concluded that, for the present study case, the effect of a building and a tree in the main wind axis led to a systematic underestimation of the IDM-derived emission rate probably due to deviations in the wind field and turbulent dispersion from the ideal assumptions.
Arno Keppens, Serena Di Pede, Daan Hubert, Jean-Christopher Lambert, Pepijn Veefkind, Maarten Sneep, Johan De Haan, Mark ter Linden, Thierry Leblanc, Steven Compernolle, Tijl Verhoelst, José Granville, Oindrila Nath, Ann Mari Fjæraa, Ian Boyd, Sander Niemeijer, Roeland Van Malderen, Herman G. J. Smit, Valentin Duflot, Sophie Godin-Beekmann, Bryan J. Johnson, Wolfgang Steinbrecht, David W. Tarasick, Debra E. Kollonige, Ryan M. Stauffer, Anne M. Thompson, Angelika Dehn, and Claus Zehner
Atmos. Meas. Tech., 17, 3969–3993, https://doi.org/10.5194/amt-17-3969-2024, https://doi.org/10.5194/amt-17-3969-2024, 2024
Short summary
Short summary
The Sentinel-5P satellite operated by the European Space Agency has carried the TROPOspheric Monitoring Instrument (TROPOMI) around the Earth since October 2017. This mission also produces atmospheric ozone profile data which are described in detail for May 2018 to April 2023. Independent validation using ground-based reference measurements demonstrates that the operational ozone profile product mostly fully and at least partially complies with all mission requirements.
Benedikt Herkommer, Carlos Alberti, Paolo Castracane, Jia Chen, Angelika Dehn, Florian Dietrich, Nicholas M. Deutscher, Matthias Max Frey, Jochen Groß, Lawson Gillespie, Frank Hase, Isamu Morino, Nasrin Mostafavi Pak, Brittany Walker, and Debra Wunch
Atmos. Meas. Tech., 17, 3467–3494, https://doi.org/10.5194/amt-17-3467-2024, https://doi.org/10.5194/amt-17-3467-2024, 2024
Short summary
Short summary
The Total Carbon Column Observing Network is a network of ground-based Fourier transform infrared (FTIR) spectrometers used mainly for satellite validation. To ensure the highest-quality validation data, the network needs to be highly consistent. This is a major challenge, which so far is solved by site comparisons with airborne in situ measurements. In this work, we describe the use of a portable FTIR spectrometer as a travel standard for evaluating the consistency of TCCON sites.
Karen De Los Ríos, Paulina Ordoñez, Gabriele P. Stiller, Piera Raspollini, Marco Gai, Kaley A. Walker, Cristina Peña-Ortiz, and Luis Acosta
Atmos. Meas. Tech., 17, 3401–3418, https://doi.org/10.5194/amt-17-3401-2024, https://doi.org/10.5194/amt-17-3401-2024, 2024
Short summary
Short summary
This study examines newer versions of H2O and HDO retrievals from Envisat/MIPAS and SCISAT/ACE-FTS. Results reveal a better agreement in stratospheric H2O profiles than in HDO profiles. The H2O tape recorder signal is consistent across databases, but δD tape recorder composites show differences that impact the interpretation of water vapour transport. These findings enhance the need for intercomparisons to refine our insights.
Ming Luo, Helen M. Worden, Robert D. Field, Kostas Tsigaridis, and Gregory S. Elsaesser
Atmos. Meas. Tech., 17, 2611–2624, https://doi.org/10.5194/amt-17-2611-2024, https://doi.org/10.5194/amt-17-2611-2024, 2024
Short summary
Short summary
The TROPESS CrIS single-pixel CO profile retrievals are compared to the MOPITT CO products in steps of adjusting them to the common a priori assumptions. The two data sets are found to agree within 5 %. We also demonstrated and analyzed the proper steps in evaluating GISS ModelE CO simulations using satellite CO retrieval products for the western US wildfire events in September 2020.
Matthew S. Johnson, Alexei Rozanov, Mark Weber, Nora Mettig, John Sullivan, Michael J. Newchurch, Shi Kuang, Thierry Leblanc, Fernando Chouza, Timothy A. Berkoff, Guillaume Gronoff, Kevin B. Strawbridge, Raul J. Alvarez, Andrew O. Langford, Christoph J. Senff, Guillaume Kirgis, Brandi McCarty, and Larry Twigg
Atmos. Meas. Tech., 17, 2559–2582, https://doi.org/10.5194/amt-17-2559-2024, https://doi.org/10.5194/amt-17-2559-2024, 2024
Short summary
Short summary
Monitoring tropospheric ozone (O3), a harmful pollutant negatively impacting human health, is primarily done using ground-based measurements and ozonesondes. However, these observation types lack the coverage to fully understand tropospheric O3. Satellites can retrieve tropospheric ozone with near-daily global coverage; however, they are known to have biases and errors. This study uses ground-based lidars to validate multiple satellites' ability to observe tropospheric O3.
Johan Mellqvist, Nathalia T. Vechi, Charlotte Scheutz, Marc Durif, Francois Gautier, John Johansson, Jerker Samuelsson, Brian Offerle, and Samuel Brohede
Atmos. Meas. Tech., 17, 2465–2479, https://doi.org/10.5194/amt-17-2465-2024, https://doi.org/10.5194/amt-17-2465-2024, 2024
Short summary
Short summary
The solar occultation flux method retrieves ammonia gas columns from the solar spectrum. Emissions are obtained by multiplying the integrated plume concentration by the wind speed profile. The methodology for uncertainty estimation was established considering an error budget with systematic and random components, resulting in an expanded uncertainty in the range of 20 % to 30 %. The method was validated in a controlled release, and its application was demonstrated in different farms.
Felicia Kolonjari, Patrick E. Sheese, Kaley A. Walker, Chris D. Boone, David A. Plummer, Andreas Engel, Stephen A. Montzka, David E. Oram, Tanja Schuck, Gabriele P. Stiller, and Geoffrey C. Toon
Atmos. Meas. Tech., 17, 2429–2449, https://doi.org/10.5194/amt-17-2429-2024, https://doi.org/10.5194/amt-17-2429-2024, 2024
Short summary
Short summary
The Canadian Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) satellite instrument is currently providing the only vertically resolved chlorodifluoromethane (HCFC-22) measurements from space. This study assesses the most current ACE-FTS HCFC-22 data product in the upper troposphere and lower stratosphere, as well as modelled HCFC-22 from a 39-year run of the Canadian Middle Atmosphere Model (CMAM39) in the same region.
Emily Dowd, Alistair J. Manning, Bryn Orth-Lashley, Marianne Girard, James France, Rebecca E. Fisher, Dave Lowry, Mathias Lanoisellé, Joseph R. Pitt, Kieran M. Stanley, Simon O'Doherty, Dickon Young, Glen Thistlethwaite, Martyn P. Chipperfield, Emanuel Gloor, and Chris Wilson
Atmos. Meas. Tech., 17, 1599–1615, https://doi.org/10.5194/amt-17-1599-2024, https://doi.org/10.5194/amt-17-1599-2024, 2024
Short summary
Short summary
We provide the first validation of the satellite-derived emission estimates using surface-based mobile greenhouse gas surveys of an active gas leak detected near Cheltenham, UK. GHGSat’s emission estimates broadly agree with the surface-based mobile survey and steps were taken to fix the leak, highlighting the importance of satellite data in identifying emissions and helping to reduce our human impact on climate change.
Astrid Müller, Hiroshi Tanimoto, Takafumi Sugita, Prabir K. Patra, Shin-ichiro Nakaoka, Toshinobu Machida, Isamu Morino, André Butz, and Kei Shiomi
Atmos. Meas. Tech., 17, 1297–1316, https://doi.org/10.5194/amt-17-1297-2024, https://doi.org/10.5194/amt-17-1297-2024, 2024
Short summary
Short summary
Satellite CH4 observations with high accuracy are needed to understand changes in atmospheric CH4 concentrations. But over oceans, reference data are limited. We combine various ship and aircraft observations with the help of atmospheric chemistry models to derive observation-based column-averaged mixing ratios of CH4 (obs. XCH4). We discuss three different approaches and demonstrate the applicability of the new reference dataset for carbon cycle studies and satellite evaluation.
Evan D. Sherwin, Sahar H. El Abbadi, Philippine M. Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey S. Rutherford, Yuanlei Chen, and Adam R. Brandt
Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, https://doi.org/10.5194/amt-17-765-2024, 2024
Short summary
Short summary
Countries and companies increasingly rely on a growing fleet of satellites to find large emissions of climate-warming methane, particularly from oil and natural gas systems across the globe. We independently assessed the performance of nine such systems by releasing controlled, undisclosed amounts of methane as satellites passed overhead. The tested systems produced reliable detection and quantification results, including the smallest-ever emission detected from space in such a test.
Luis F. Millán, Matthew D. Lebsock, Ken B. Cooper, Jose V. Siles, Robert Dengler, Raquel Rodriguez Monje, Amin Nehrir, Rory A. Barton-Grimley, James E. Collins, Claire E. Robinson, Kenneth L. Thornhill, and Holger Vömel
Atmos. Meas. Tech., 17, 539–559, https://doi.org/10.5194/amt-17-539-2024, https://doi.org/10.5194/amt-17-539-2024, 2024
Short summary
Short summary
In this study, we describe and validate a new technique in which three radar tones are used to estimate the water vapor inside clouds and precipitation. This instrument flew on board NASA's P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign and the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign.
Ouyang Liu, Zhengqiang Li, Yangyan Lin, Cheng Fan, Ying Zhang, Kaitao Li, Peng Zhang, Yuanyuan Wei, Tianzeng Chen, Jiantao Dong, and Gerrit de Leeuw
Atmos. Meas. Tech., 17, 377–395, https://doi.org/10.5194/amt-17-377-2024, https://doi.org/10.5194/amt-17-377-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NO2) is a trace gas which is important for atmospheric chemistry and may affect human health. To understand processes leading to harmful concentrations, it is important to monitor NO2 concentrations near the surface and higher up. To this end, a Pandora instrument has been installed in Beijing. An overview of the first year of data shows the large variability on diurnal to seasonal timescales and how this is affected by wind speed and direction and chemistry.
Karen E. Cady-Pereira, Xuehui Guo, Rui Wang, April B. Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin Kantchev
Atmos. Meas. Tech., 17, 15–36, https://doi.org/10.5194/amt-17-15-2024, https://doi.org/10.5194/amt-17-15-2024, 2024
Short summary
Short summary
Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large-scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are differences in magnitude, but the satellite data are spatially and temporally well correlated with the in situ data.
Alana K. Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew K. Thorpe, and Riley Duren
Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, https://doi.org/10.5194/amt-16-6065-2023, 2023
Short summary
Short summary
Methane is a powerful greenhouse gas, and a significant portion of methane comes from large individual plumes. Recently, airplane-mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image, there are two widely used approaches. In this study, we assess the performance of both approaches using controlled-release experiments. We also examine the minimum detection limit of the infrared technology.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
Short summary
Short summary
We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Kanghyun Baek, Jae Hwan Kim, Juseon Bak, David P. Haffner, Mina Kang, and Hyunkee Hong
Atmos. Meas. Tech., 16, 5461–5478, https://doi.org/10.5194/amt-16-5461-2023, https://doi.org/10.5194/amt-16-5461-2023, 2023
Short summary
Short summary
The GEMS mission was the first mission of the geostationary satellite constellation for hourly atmospheric composition monitoring. The GEMS ozone measurements were cross-compared to those of Pandora, OMPS, and TROPOMI satellite sensors and excellent agreement was found. GEMS has proven to be a powerful new instrument for monitoring and assessing the diurnal variation in atmospheric ozone. This experience can be used to advance research with future geostationary environmental satellite missions.
Tobias Christoph Valentin Werner Riess, Klaas Folkert Boersma, Ward Van Roy, Jos de Laat, Enrico Dammers, and Jasper van Vliet
Atmos. Meas. Tech., 16, 5287–5304, https://doi.org/10.5194/amt-16-5287-2023, https://doi.org/10.5194/amt-16-5287-2023, 2023
Short summary
Short summary
Satellite retrievals of trace gases require prior knowledge of the vertical distribution of the pollutant, which is usually obtained from models. Using aircraft-measured vertical NO2 profiles over the North Sea in summer 2021, we evaluate the Transport Model 5 profiles used in the TROPOMI NO2 retrieval. We conclude that driven by the low horizontal resolution and the overestimated vertical mixing, resulting NO2 columns are 20 % too low. This has important implications for emission estimates.
Thomas Trickl, Martin Adelwart, Dina Khordakova, Ludwig Ries, Christian Rolf, Michael Sprenger, Wolfgang Steinbrecht, and Hannes Vogelmann
Atmos. Meas. Tech., 16, 5145–5165, https://doi.org/10.5194/amt-16-5145-2023, https://doi.org/10.5194/amt-16-5145-2023, 2023
Short summary
Short summary
Tropospheric ozone have been measured for more than a century. Highly quantitative ozone measurements have been made at monitoring stations. However, deficits have been reported for vertical sounding systems. Here, we report a thorough intercomparison effort between a differential-absorption lidar system and two types of balloon-borne ozone sondes, also using ozone sensors at nearby mountain sites as references. The sondes agree very well with the lidar after offset corrections.
Rodriguez Yombo Phaka, Alexis Merlaud, Gaia Pinardi, Martina M. Friedrich, Michel Van Roozendael, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, François Hendrick, Ermioni Dimitropoulou, Richard Bopili Mbotia Lepiba, Edmond Phuku Phuati, Buenimio Lomami Djibi, Lars Jacobs, Caroline Fayt, Jean-Pierre Mbungu Tsumbu, and Emmanuel Mahieu
Atmos. Meas. Tech., 16, 5029–5050, https://doi.org/10.5194/amt-16-5029-2023, https://doi.org/10.5194/amt-16-5029-2023, 2023
Short summary
Short summary
We present air quality measurements in Kinshasa, Democratic Republic of the Congo, performed with a newly developed instrument which was installed on a roof of the University of Kinshasa in November 2019. The instrument records spectra of the scattered sunlight, from which we derive the abundances of nitrogen dioxide and formaldehyde, two important pollutants. We compare our ground-based measurements with those of the TROPOspheric Monitoring Instrument (TROPOMI).
Jay Herman, Jerald Ziemke, and Richard McPeters
Atmos. Meas. Tech., 16, 4693–4707, https://doi.org/10.5194/amt-16-4693-2023, https://doi.org/10.5194/amt-16-4693-2023, 2023
Short summary
Short summary
Fourier series multivariate linear regression trends (% per decade) in ozone were estimated from the Merged Ozone Data Set (MOD) from 1979 to 2021 in two different regimes, from 1979 to TA (the date when ozone stopped decreasing) and TA to 2021. The derived TA is a latitude-dependent date, ranging from 1994 to 1998. TA(θ) is a marker for photochemistry dynamics models attempting to represent ozone change over the past 42 years.
Michael Kiefer, Dale F. Hurst, Gabriele P. Stiller, Stefan Lossow, Holger Vömel, John Anderson, Faiza Azam, Jean-Loup Bertaux, Laurent Blanot, Klaus Bramstedt, John P. Burrows, Robert Damadeo, Bianca Maria Dinelli, Patrick Eriksson, Maya García-Comas, John C. Gille, Mark Hervig, Yasuko Kasai, Farahnaz Khosrawi, Donal Murtagh, Gerald E. Nedoluha, Stefan Noël, Piera Raspollini, William G. Read, Karen H. Rosenlof, Alexei Rozanov, Christopher E. Sioris, Takafumi Sugita, Thomas von Clarmann, Kaley A. Walker, and Katja Weigel
Atmos. Meas. Tech., 16, 4589–4642, https://doi.org/10.5194/amt-16-4589-2023, https://doi.org/10.5194/amt-16-4589-2023, 2023
Short summary
Short summary
We quantify biases and drifts (and their uncertainties) between the stratospheric water vapor measurement records of 15 satellite-based instruments (SATs, with 31 different retrievals) and balloon-borne frost point hygrometers (FPs) launched at 27 globally distributed stations. These comparisons of measurements during the period 2000–2016 are made using robust, consistent statistical methods. With some exceptions, the biases and drifts determined for most SAT–FP pairs are < 10 % and < 1 % yr−1.
Tim A. van Kempen, Tim J. Rotmans, Richard M. van Hees, Carol Bruegge, Dejian Fu, Ruud Hoogeveen, Thomas J. Pongetti, Robert Rosenberg, and Ilse Aben
Atmos. Meas. Tech., 16, 4507–4527, https://doi.org/10.5194/amt-16-4507-2023, https://doi.org/10.5194/amt-16-4507-2023, 2023
Short summary
Short summary
Validation of satellite measurements is essential for providing reliable and consistent products. In this paper, a validation method for TROPOMI-SWIR (Tropospheric Measurement Instrument in the short-wavelength infrared) is explored. TROPOMI-SWIR has been shown to be exceptionally stable, a necessity to explore the methodology. Railroad Valley, Nevada, is a prime location to perform the necessary measurements to validate the satellite measurements of TROPOMI-SWIR.
Serin Kim, Daewon Kim, Hyunkee Hong, Lim-Seok Chang, Hanlim Lee, Deok-Rae Kim, Donghee Kim, Jeong-Ah Yu, Dongwon Lee, Ukkyo Jeong, Chang-Kuen Song, Sang-Woo Kim, Sang Seo Park, Jhoon Kim, Thomas F. Hanisco, Junsung Park, Wonei Choi, and Kwangyul Lee
Atmos. Meas. Tech., 16, 3959–3972, https://doi.org/10.5194/amt-16-3959-2023, https://doi.org/10.5194/amt-16-3959-2023, 2023
Short summary
Short summary
A first evaluation of the Geostationary Environmental Monitoring Spectrometer (GEMS) NO2 was carried out via comparison with the NO2 data obtained from the ground-based Pandora direct-sun measurements at four sites in Seosan, Republic of Korea. Comparisons between GEMS NO2 and Pandora NO2 were performed according to GEMS cloud fraction. GEMS NO2 showed good agreement with that of Pandora NO2 under less cloudy conditions.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
Short summary
Short summary
We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
Short summary
Short summary
NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Lena Katharina Jänicke, Rene Preusker, Marco Celesti, Marin Tudoroiu, Jürgen Fischer, Dirk Schüttemeyer, and Matthias Drusch
Atmos. Meas. Tech., 16, 3101–3121, https://doi.org/10.5194/amt-16-3101-2023, https://doi.org/10.5194/amt-16-3101-2023, 2023
Short summary
Short summary
To compare two top-of-atmosphere radiances measured by instruments with different spectral characteristics, a transfer function has been developed. It is applied to a tandem data set of Sentinel-3A and B, for which OLCI-B mimicked the ESA’s eighth Earth Explorer FLEX. We found that OLCI-A measured radiances about 2 % brighter than OLCI-FLEX. Only at larger wavelengths were OLCI-A measurements about 5 % darker. The method is thus successful, being sensitive to calibration and processing issues.
Luis F. Millán, Gloria L. Manney, Harald Boenisch, Michaela I. Hegglin, Peter Hoor, Daniel Kunkel, Thierry Leblanc, Irina Petropavlovskikh, Kaley Walker, Krzysztof Wargan, and Andreas Zahn
Atmos. Meas. Tech., 16, 2957–2988, https://doi.org/10.5194/amt-16-2957-2023, https://doi.org/10.5194/amt-16-2957-2023, 2023
Short summary
Short summary
The determination of atmospheric composition trends in the upper troposphere and lower stratosphere (UTLS) is still highly uncertain. We present the creation of dynamical diagnostics to map several ozone datasets (ozonesondes, lidars, aircraft, and satellite measurements) in geophysically based coordinate systems. The diagnostics can also be used to analyze other greenhouse gases relevant to surface climate and UTLS chemistry.
Zhihua Zhang, Jianguo Niu, Lawrence E. Flynn, Eric Beach, and Trevor Beck
Atmos. Meas. Tech., 16, 2919–2941, https://doi.org/10.5194/amt-16-2919-2023, https://doi.org/10.5194/amt-16-2919-2023, 2023
Short summary
Short summary
This study mainly focused on addressing stability and improvement when using a broadband approach, establishing soft-calibration adjustments for both OMPS S-NPP and N20, analyzing error biases based on multi-sensor bias correction, and comparing total column ozone and aerosol index retrievals from NOAA OMPS with those from other products.
Matthew S. Johnson, Amir H. Souri, Sajeev Philip, Rajesh Kumar, Aaron Naeger, Jeffrey Geddes, Laura Judd, Scott Janz, Heesung Chong, and John Sullivan
Atmos. Meas. Tech., 16, 2431–2454, https://doi.org/10.5194/amt-16-2431-2023, https://doi.org/10.5194/amt-16-2431-2023, 2023
Short summary
Short summary
Satellites provide vital information for studying the processes controlling ozone formation. Based on the abundance of particular gases in the atmosphere, ozone formation is sensitive to specific human-induced and natural emission sources. However, errors and biases in satellite retrievals hinder this data source’s application for studying ozone formation sensitivity. We conducted a thorough statistical evaluation of two commonly applied satellites for investigating ozone formation sensitivity.
Kezia Lange, Andreas Richter, Anja Schönhardt, Andreas C. Meier, Tim Bösch, André Seyler, Kai Krause, Lisa K. Behrens, Folkard Wittrock, Alexis Merlaud, Frederik Tack, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Vinod Kumar, Sebastian Donner, Steffen Dörner, Bianca Lauster, Maria Razi, Christian Borger, Katharina Uhlmannsiek, Thomas Wagner, Thomas Ruhtz, Henk Eskes, Birger Bohn, Daniel Santana Diaz, Nader Abuhassan, Dirk Schüttemeyer, and John P. Burrows
Atmos. Meas. Tech., 16, 1357–1389, https://doi.org/10.5194/amt-16-1357-2023, https://doi.org/10.5194/amt-16-1357-2023, 2023
Short summary
Short summary
We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted during the S5P-VAL-DE-Ruhr campaign in the Rhine-Ruhr region. The measurements are used to validate spaceborne NO2 data products from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). Auxiliary data of the TROPOMI NO2 retrieval, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity, and cloud treatment are investigated to evaluate their impact.
Cited articles
Bie, N., Lei, L., Zeng, Z., Cai, B., Yang, S., He, Z., Wu, C., and Nassar, R.: Regional uncertainty of GOSAT XCO2 retrievals in China: quantification and attribution, Atmos. Meas. Tech., 11, 1251–1272, https://doi.org/10.5194/amt-11-1251-2018, 2018. a
Boesch, H., Baker, D., Connor, B., Crisp, D., and Miller, C.: Global
characterization of CO2 column retrievals from shortwave-infrared satellite
observations of the Orbiting Carbon Observatory-2 mission, Remote Sens., 3,
270–304, https://doi.org/10.3390/rs3020270, 2011. a
Carré, F., Hiederer, R., Blujdea, V., and Koeble, R.: Background guide for
the calculation of land carbon stocks in the biofuels sustainability scheme:
drawing on the 2006 IPCC guidelines for national greenhouse gas inventories,
Luxembourg: Joint Research Center, European Commission, EUR, 24573, 34463,
https://doi.org/10.2788/34463, 2010. a
Chatterjee, A., Gierach, M., Sutton, A., Feely, R., Crisp, D., Eldering, A.,
Gunson, M., O'Dell, C., Stephens, B., and Schimel, D.: Influence of El
Niño on atmospheric CO2 over the tropical Pacific Ocean: Findings from
NASA’s OCO-2 mission, Science, 358, eaam5776,
https://doi.org/10.1126/science.aam5776, 2017. a
Chevallier, F.: Impact of correlated observation errors on inverted CO2 surface
fluxes from OCO measurements, Geophys. Res. Lett., 34, L24804,
https://doi.org/10.1029/2007GL030463, 2007. a
Ciais, P., Bombelli, A., Williams, M., Piao, S., Chave, J., Ryan, C., Henry,
M., Brender, P., and Valentini, R.: The carbon balance of Africa: synthesis
of recent research studies, Philos. T. Roy. Soc.
A, 369, 2038–2057,
https://doi.org/10.1098/rsta.2010.0328, 2011. a
Connor, B. J., Boesch, H., Toon, G., Sen, B., Miller, C., and Crisp, D.:
Orbiting Carbon Observatory: Inverse method and prospective error analysis,
J. Geophys. Res.-Atmos., 113, D05305,
https://doi.org/10.1029/2006JD008336, 2008. a, b
Crisp, D., Fisher, B. M., O'Dell, C., Frankenberg, C., Basilio, R., Bösch, H., Brown, L. R., Castano, R., Connor, B., Deutscher, N. M., Eldering, A., Griffith, D., Gunson, M., Kuze, A., Mandrake, L., McDuffie, J., Messerschmidt, J., Miller, C. E., Morino, I., Natraj, V., Notholt, J., O'Brien, D. M., Oyafuso, F., Polonsky, I., Robinson, J., Salawitch, R., Sherlock, V., Smyth, M., Suto, H., Taylor, T. E., Thompson, D. R., Wennberg, P. O., Wunch, D., and Yung, Y. L.: The ACOS CO2 retrieval algorithm – Part II: Global X
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., van de Berg, I., Biblot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M.,
Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart,
F.: The ERA-Interim reanalysis: Configuration and performance of the data
assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, doi:10.1002/qj.828, 2011..: The ERA-Interim
reanalysis: Configuration and performance of the data assimilation system,
Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011. a
Deng, A., Yu, T., Cheng, T., Gu, X., Zheng, F., and Guo, H.: Intercomparison of
Carbon Dioxide Products Retrieved from GOSAT Short-Wavelength Infrared
Spectra for Three Years (2010–2012), Atmosphere, 7, 109,
https://doi.org/10.3390/atmos7090109, 2016a. a, b
Deng, F., Jones, D. B., O'Dell, C. W., Nassar, R., and Parazoo, N. C.:
Combining GOSAT XCO2 observations over land and ocean to improve regional CO2
flux estimates, J. Geophys. Res.-Atmos., 121,
1896–1913, https://doi.org/10.1002/2015JD024157, 2016b. a
Dobler, J. T., Harrison, F. W., Browell, E. V., Lin, B., McGregor, D., Kooi,
S., Choi, Y., and Ismail, S.: Atmospheric CO2 column measurements with an
airborne intensity-modulated continuous wave 1.57 µm fiber laser lidar,
Appl. Optics, 52, 2874–2892, https://doi.org/10.1364/AO.52.002874, 2013. a
Feist, D. G., Arnold, S. G., John, N., and Geibel, M.: TCCON data from
Ascension Island (SH), Release GGG2014R0, TCCON data archive, hosted by:
CaltechDATA, https://doi.org/10.14291/tccon.ggg2014.ascension01.R0/1149285, 2014. a
Frankenberg, C., Kulawik, S. S., Wofsy, S. C., Chevallier, F., Daube, B., Kort, E. A., O'Dell, C., Olsen, E. T., and Osterman, G.: Using airborne HIAPER Pole-to-Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide, Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, 2016. a
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V.,
Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur, R., Strassmann, K., Weaver, A. J. and Yoshikawa, C., and Zeng, N.: Climate–carbon cycle
feedback analysis: results from the C4MIP model intercomparison, J.
Climate, 19, 3337–3353, https://doi.org/10.1175/JCLI3800.1, 2006. a
Hamazaki, T., Kaneko, Y., Kuze, A., and Kondo, K.: Fourier transform
spectrometer for greenhouse gases observing satellite (GOSAT), in: Enabling
sensor and platform technologies for spaceborne remote sensing, 5659,
73–81, International Society for Optics and Photonics,
https://doi.org/10.1117/12.581198, 2005. a
Hao, W. M. and Liu, M.-H.: Spatial and temporal distribution of tropical
biomass burning, Global Biogeochem. Cy., 8, 495–503,
https://doi.org/10.1029/94GB02086, 1994. a, b
Houweling, S., Breon, F.-M., Aben, I., Rödenbeck, C., Gloor, M., Heimann, M., and Ciais, P.: Inverse modeling of CO2 sources and sinks using satellite data: a synthetic inter-comparison of measurement techniques and their performance as a function of space and time, Atmos. Chem. Phys., 4, 523–538, https://doi.org/10.5194/acp-4-523-2004, 2004. a
Hulme, M., Doherty, R., Ngara, T., New, M., and Lister, D.: African climate
change: 1900-2100, Clim. Res., 17, 145–168, https://doi.org/10.3354/cr017145,
2001. a
Hungershoefer, K., Breon, F.-M., Peylin, P., Chevallier, F., Rayner, P., Klonecki, A., Houweling, S., and Marshall, J.: Evaluation of various observing systems for the global monitoring of CO2 surface fluxes, Atmos. Chem. Phys., 10, 10503–10520, https://doi.org/10.5194/acp-10-10503-2010, 2010. a
Idso, C. D., Idso, S. B., and Balling Jr, R. C.: The relationship between
near-surface air temperature over land and the annual amplitude of the
atmosphere’s seasonal CO2 cycle, Environ. Exp. Bot., 41,
31–37, https://doi.org/10.1016/S0098-8472(98)00047-1, 1999. a
Inoue, M., Morino, I., Uchino, O., Miyamoto, Y., Yoshida, Y., Yokota, T., Machida, T., Sawa, Y., Matsueda, H., Sweeney, C., Tans, P. P., Andrews, A. E., Biraud, S. C., Tanaka, T., Kawakami, S., and Patra, P. K.: Validation of XCO2 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data, Atmos. Chem. Phys., 13, 9771–9788, https://doi.org/10.5194/acp-13-9771-2013, 2013. a
Jing, Y., Wang, T., Zhang, P., Chen, L., Xu, N., and Ma, Y.: Global Atmospheric
CO2 Concentrations Simulated by GEOS-Chem: Comparison with GOSAT, Carbon
Tracker and Ground-Based Measurements, Atmosphere, 9, 175,
https://doi.org/10.3390/atmos9050175, 2018. a
Jones, C. D., Collins, M., Cox, P. M., and Spall, S. A.: The carbon cycle
response to ENSO: A coupled climate–carbon cycle model study, J.
Climate, 14, 4113–4129,
https://doi.org/10.1175/1520-0442(2001)014<4113:TCCRTE>2.0.CO;2, 2001. a
Keppel-Aleks, G., Wennberg, P. O., and Schneider, T.: Sources of variations in total column carbon dioxide, Atmos. Chem. Phys., 11, 3581–3593, https://doi.org/10.5194/acp-11-3581-2011, 2011. a
Keppel-Aleks, G., Wennberg, P. O., Washenfelder, R. A., Wunch, D., Schneider, T., Toon, G. C., Andres, R. J., Blavier, J.-F., Connor, B., Davis, K. J., Desai, A. R., Messerschmidt, J., Notholt, J., Roehl, C. M., Sherlock, V., Stephens, B. B., Vay, S. A., and Wofsy, S. C.: The imprint of surface fluxes and transport on variations in total column carbon dioxide, Biogeosciences, 9, 875–891, https://doi.org/10.5194/bg-9-875-2012, 2012. a
Kong, S., Lu, B., Han, B., Bai, Z., Xu, Z., You, Y., Jin, L., Guo, X., and
Wang, R.: Seasonal variation analysis of atmospheric CH4, N2O and CO2 in
Tianjin offshore area, Science China Earth Science, 53, 1205–1215,
https://doi.org/10.1007/s11430-010-3065-5, 2010. a
Krol, M., Houweling, S., Bregman, B., van den Broek, M., Segers, A., van Velthoven, P., Peters, W., Dentener, F., and Bergamaschi, P.: The two-way nested global chemistry-transport zoom model TM5: algorithm and applications, Atmos. Chem. Phys., 5, 417–432, https://doi.org/10.5194/acp-5-417-2005, 2005. a, b
Kulawik, S., Wunch, D., O'Dell, C., Frankenberg, C., Reuter, M., Oda, T., Chevallier, F., Sherlock, V., Buchwitz, M., Osterman, G., Miller, C. E., Wennberg, P. O., Griffith, D., Morino, I., Dubey, M. K., Deutscher, N. M., Notholt, J., Hase, F., Warneke, T., Sussmann, R., Robinson, J., Strong, K., Schneider, M., De Mazière, M., Shiomi, K., Feist, D. G., Iraci, L. T., and Wolf, J.: Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON, Atmos. Meas. Tech., 9, 683–709, https://doi.org/10.5194/amt-9-683-2016, 2016. a, b, c, d
Kuze, A., Suto, H., Nakajima, M., and Hamazaki, T.: Thermal and near infrared
sensor for carbon observation Fourier-transform spectrometer on the
Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl. Optics, 48, 6716–6733, https://doi.org/10.1364/AO.48.006716, 2009. a, b
Lei, L., Guan, X., Zeng, Z., Zhang, B., Ru, F., and Bu, R.: A comparison of
atmospheric CO2 concentration GOSAT-based observations and model simulations,
Science China Earth Sciences, 57, 1393, https://doi.org/10.1007/s11430-013-4807-y,
2014. a
Liang, A., Gong, W., Han, G., and Xiang, C.: Comparison of Satellite-Observed
XCO2 from GOSAT, OCO-2, and Ground-Based TCCON, Remote Sens., 9, 1033,
https://doi.org/10.3390/rs9101033, 2017. a, b
Lindqvist, H., O'Dell, C. W., Basu, S., Boesch, H., Chevallier, F., Deutscher, N., Feng, L., Fisher, B., Hase, F., Inoue, M., Kivi, R., Morino, I., Palmer, P. I., Parker, R., Schneider, M., Sussmann, R., and Yoshida, Y.: Does GOSAT capture the true seasonal cycle of carbon dioxide?, Atmos. Chem. Phys., 15, 13023–13040, https://doi.org/10.5194/acp-15-13023-2015, 2015. a
Liu, L., Zhou, L., Zhang, X., Wen, M., Zhang, F., Yao, B., and Fang, S.: The
characteristics of atmospheric CO2 concentration variation of four national
background stations in China, Sci. China Ser. D, 52,
1857–1863, https://doi.org/10.1007/s11430-009-0143-7, 2009. a
Malhi, Y., Adu-Bredu, S., Asare, R. A., Lewis, S. L., and Mayaux, P.: African
rainforests: past, present and future, Philos. T.
Roy. Soc. B, 368, 20120312,
https://doi.org/10.1098/rstb.2012.0312, 2013. a
Mengistu Tsidu, G.: High-resolution monthly rainfall database for Ethiopia:
Homogenization, reconstruction, and gridding, J. Climate, 25,
8422–8443, https://doi.org/10.1175/JCLI-D-12-00027.1, 2012. a
Mengistu Tsidu, G., Blumenstock, T., and Hase, F.: Observations of precipitable water vapour over complex topography of Ethiopia from ground-based GPS, FTIR, radiosonde and ERA-Interim reanalysis, Atmos. Meas. Tech., 8, 3277–3295, https://doi.org/10.5194/amt-8-3277-2015, 2015. a
Morino, I., Uchino, O., Inoue, M., Yoshida, Y., Yokota, T., Wennberg, P. O., Toon, G. C., Wunch, D., Roehl, C. M., Notholt, J., Warneke, T., Messerschmidt, J., Griffith, D. W. T., Deutscher, N. M., Sherlock, V., Connor, B., Robinson, J., Sussmann, R., and Rettinger, M.: Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra, Atmos. Meas. Tech., 4, 1061–1076, https://doi.org/10.5194/amt-4-1061-2011, 2011. a
Nayak, R. K., Deepthi, E. N., Dadhwal, V. K., Rao, K. H., and Dutt, C. B. S.: Evaluation of NOAA Carbon Tracker Global Carbon Dioxide Products, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 287–290, https://doi.org/10.5194/isprsarchives-XL-8-287-2014, 2014. a, b
NIES GOSAT Project: Summary of the GOSAT Level 2 data Products Validation
Activity, Center for Global Environmental Research, 1–10, 2012. a
O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C., Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J., Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T., Toon, G. C., Wennberg, P. O., and Wunch, D.: The ACOS CO2 retrieval algorithm – Part 1: Description and validation against synthetic observations, Atmos. Meas. Tech., 5, 99–121, https://doi.org/10.5194/amt-5-99-2012, 2012. a, b, c, d, e, f
Olsen, S. C. and Randerson, J. T.: Differences between surface and column
atmospheric CO2 and implications for carbon cycle research, J. Geophys. Res.-Atmos., 109, D02301, https://doi.org/10.1029/2003JD003968, 2004. a
Patra, P. K., Crisp, D., Kaiser, J. W., Wunch, D., Saeki, T., Ichii, K.,
Sekiya, T., Wennberg, P. O., Feist, D. G., Pollard, D. F., Griffith, D. W. T., Velazco, V. A., De Maziere, M, Sha, M. K., Roehl, C., Chatterjee, A., and Ishijima, K.: The
Orbiting Carbon Observatory (OCO-2) tracks 2–3 peta-gram increase in carbon
release to the atmosphere during the 2014–2016 El Niño, Sci.
Rep., 7, 13567, https://doi.org/10.1038/s41598-017-13459-0, 2017. a
Peters, W., Krol, M., Dlugokencky, E., Dentener, F., Bergamaschi, P., Dutton,
G., Velthoven, P. v., Miller, J., Bruhwiler, L., and Tans, P.: Toward
regional-scale modeling using the two-way nested global model TM5:
Characterization of transport using SF6, J. Geophys. Res.-Atmos., 109, D19314, https://doi.org/10.1029/2004JD005020, 2004. a
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J.,
Masarie, K., Miller, J. B., Bruhwiler, L. M., Pétron, G., Hirsch, A. I., Worthy, D. E. J., van der Werf, G. R., Randerson, J. T., Wennberg, P. O., Krol, M. C., and Tans, P. T.: An atmospheric perspective on North American carbon dioxide exchange:
CarbonTracker, P. Natl. Acad. Sci. USA, 104,
18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007. a, b
Rayner, P. and O'Brien, D.: The utility of remotely sensed CO2 concentration
data in surface source inversions, Geophys. Res. Lett., 28,
175–178, https://doi.org/10.1029/2000GL011912, 2001. a
Rodgers, C. D. and Connor, B. J.: Intercomparison of remote sounding
instruments, J. Geophys. Res.-Atmos., 108, 4116,
https://doi.org/10.1029/2002JD002299, 2003. a
Saitoh, N., Imasu, R., Ota, Y., and Niwa, Y.: CO2 retrieval algorithm for the
thermal infrared spectra of the Greenhouse Gases Observing Satellite:
Potential of retrieving CO2 vertical profile from high-resolution FTS sensor,
J. Geophys. Res.-Atmos., 114, D17305,
https://doi.org/10.1029/2008JD011500, 2009. a
Santer, B. D., Painter, J. F., Bonfils, C., Mears, C. A., Solomon, S., Wigley,
T. M., Gleckler, P. J., Schmidt, G. A., Doutriaux, C., Gillett, N. P.,
Taylor, K. E., Thorne, P. W., and Wentz, F. J.: Human and natural influences on the changing thermal structure of the
atmosphere, P. Natl. Acad. Sci. USA, 110,
17235–17240, https://doi.org/10.1073/pnas.1305332110, 2013. a
Stocker, B. D., Roth, R., Joos, F., Spahni, R., Steinacher, M., Zaehle, S.,
Bouwman, L., Xu-Ri, and Prentice, I. C.: Multiple greenhouse-gas feedbacks from
the land biosphere under future climate change scenarios, Nat. Clim.
Change, 3, 666–672, https://doi.org/10.1038/nclimate1864, 2013. a
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192,
https://doi.org/10.1029/2000JD900719, 2001. a
Velazco, V. A., Morino, I., Uchino, O., Deutscher, N. M., Bukosa, B., Belikov,
D. A., Oishi, Y., Nakajima, T. Y., Macatangay, R., Nakatsuru, T., Maksyutov, S., Schwandner, F. M., and Griffith, D. W. T.:
Total carbon column observing network Philippines: Toward quantifying
atmospheric carbon in southeast asia, Climate, Disaster and Development Journal, 2, 1–12, https://doi.org/10.18783/cddj.v002.i02.a01, 2017. a
Williams, C. A., Hanan, N. P., Neff, J. C., Scholes, R. J., Berry, J. A.,
Denning, A. S., and Baker, D. F.: Africa and the global carbon cycle, Carbon balance and management, 2, 3, https://doi.org/10.1186/1750-0680-2-3, 2007. a, b, c
Wunch, D., Wennberg, P. O., Toon, G. C., Connor, B. J., Fisher, B., Osterman, G. B., Frankenberg, C., Mandrake, L., O'Dell, C., Ahonen, P., Biraud, S. C., Castano, R., Cressie, N., Crisp, D., Deutscher, N. M., Eldering, A., Fisher, M. L., Griffith, D. W. T., Gunson, M., Heikkinen, P., Keppel-Aleks, G., Kyrö, E., Lindenmaier, R., Macatangay, R., Mendonca, J., Messerschmidt, J., Miller, C. E., Morino, I., Notholt, J., Oyafuso, F. A., Rettinger, M., Robinson, J., Roehl, C. M., Salawitch, R. J., Sherlock, V., Strong, K., Sussmann, R., Tanaka, T., Thompson, D. R., Uchino, O., Warneke, T., and Wofsy, S. C.: A method for evaluating bias in global measurements of CO2 total columns from space, Atmos. Chem. Phys., 11, 12317–12337, https://doi.org/10.5194/acp-11-12317-2011, 2011. a
Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and
Maksyutov, S.: Global concentrations of CO2 and CH4 retrieved from GOSAT:
First preliminary results, Sola, 5, 160–163, https://doi.org/10.2151/sola.2009-041,
2009.
a, b, c
Yokota, Y., Matsunaga, T., Ohtake, M., Haruyama, J., Nakamura, R., Yamamoto,
S., Ogawa, Y., Morota, T., Honda, C., Saiki, K., Nagasawa, K., Kitazato, K., Sasaki, S., Iwasaki, A., Demura, H., Hirata, N., Hiroi, T., Honda, R., Iijima, Y., and Mizutani, H.: Lunar photometric
properties at wavelengths 0.5–1.6 µm acquired by SELENE Spectral
Profiler and their dependency on local albedo and latitudinal zones, Icarus,
215, 639–660, https://doi.org/10.1016/j.icarus.2011.07.028, 2011. a
Yoshida, Y., Kikuchi, N., Morino, I., Uchino, O., Oshchepkov, S., Bril, A., Saeki, T., Schutgens, N., Toon, G. C., Wunch, D., Roehl, C. M., Wennberg, P. O., Griffith, D. W. T., Deutscher, N. M., Warneke, T., Notholt, J., Robinson, J., Sherlock, V., Connor, B., Rettinger, M., Sussmann, R., Ahonen, P., Heikkinen, P., Kyrö, E., Mendonca, J., Strong, K., Hase, F., Dohe, S., and Yokota, T.: Improvement of the retrieval algorithm for GOSAT SWIR XCO2 and XCH4 and their validation using TCCON data, Atmos. Meas. Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, 2013. a, b
Zhang, L., Jiang, H., and Zhang, X.: Comparison analysis of the global carbon
dioxide concentration column derived from SCIAMACHY, AIRS, and GOSAT with
surface station measurements, Int. J. Remote Sens., 36,
1406–1423, https://doi.org/10.1080/01431161.2015.1009656, 2015. a
Zhou, T., Yi, C., Bakwin, P. S., and Zhu, L.: Links between global CO2
variability and climate anomalies of biomes, Sci. China Ser. D, 51, 740–747, https://doi.org/10.1007/s11430-008-0024-5, 2008. a
Short summary
This paper assesses the performance of observed XCO2 from the GOSAT and OCO-2 satellites in capturing simulated XCO2 from the NOAA Carbon Tracker model over Africa. These satellite observations and Carbon Tracker mixing ratios near the surface are also compared to available in situ CO2 flask data from Assekrem, Algeria; Mt. Kenya; Gobabeb, Namibia; and Cape Town; as well as to data off the coast at Seychelles, Ascension Island, and at Izana, Tenerife.
This paper assesses the performance of observed XCO2 from the GOSAT and OCO-2 satellites in...
