Articles | Volume 14, issue 2
https://doi.org/10.5194/amt-14-1167-2021
© Author(s) 2021. 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-14-1167-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Feb 2021
Research article |
| 15 Feb 2021
| 15 Feb 2021
Anthropogenic CO2 monitoring satellite mission: the need for multi-angle polarimetric observations
Stephanie P. Rusli
CORRESPONDING AUTHOR
SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA Utrecht, the Netherlands
Otto Hasekamp
SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA Utrecht, the Netherlands
Joost aan de Brugh
SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA Utrecht, the Netherlands
Guangliang Fu
SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA Utrecht, the Netherlands
Yasjka Meijer
European Space Agency, Keplerlaan 1, 2201 AZ Noordwijk, the Netherlands
Jochen Landgraf
SRON Netherlands Institute for Space Research, Sorbonnelaan 2, 3584 CA Utrecht, the Netherlands
Related authors
No articles found.
Yusuf A. Bhatti, Duncan Watson-Parris, Leighton A. Regayre, Hailing Jia, David Neubauer, Ulas Im, Carl Svenhag, Nick Schutgens, Athanasios Tsikerdekis, Athanasios Nenes, Muhammed Irfan, Bastiaan van Diedenhoven, Ardit Arifi, Guangliang Fu, and Otto P. Hasekamp
Atmos. Chem. Phys., 26, 269–293, https://doi.org/10.5194/acp-26-269-2026, https://doi.org/10.5194/acp-26-269-2026, 2026
Short summary
Short summary
Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and using machine learning to emulate millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.
Mari C. Martinez-Velarte, Jochen Landgraf, Ben Veihelmann, Bernd Sierk, and Tobias Borsdorff
EGUsphere, https://doi.org/10.5194/egusphere-2025-6328, https://doi.org/10.5194/egusphere-2025-6328, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Launched in August 2025, Sentinel-5 provides daily CH4 and CO retrievals and is sensitive to CO2. Its SWIR MCT detectors exhibit persistence effects causing scene-dependent biases. This study quantifies these biases for CH4, CO, CO2, and the CH4/CO2 proxy using RemoTeC over regions with high radiance variability. Typical biases are small (<0.34 %), but outliers reach 1.59–4.01 %. Targeted post-filtering can reduce outliers and meet mission performance.
Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff
Atmos. Meas. Tech., 18, 6093–6123, https://doi.org/10.5194/amt-18-6093-2025, https://doi.org/10.5194/amt-18-6093-2025, 2025
Short summary
Short summary
The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.
Zihao Yuan, Guangliang Fu, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 18, 5415–5434, https://doi.org/10.5194/amt-18-5415-2025, https://doi.org/10.5194/amt-18-5415-2025, 2025
Short summary
Short summary
This work develops an Neural-Network-based above cloud aerosol (ACA) detection and retrieval scheme for multi-angular polarimetric (MAP) instruments. On one year of the retrieval, the retrieved aerosol properties (aerosol optical thickness, AOT, Angstrom Exponent, AE, and Single Scattering Albedo, SSA) agree well with adjacent clear-sky aerosol retrievals. The seasonal global pattern of ACA events and above cloud AOT are also within expectation.
Harikrishnan Charuvil Asokan, Jochen Landgraf, Pepijn Veefkind, Stijn Dellaert, and André Butz
Atmos. Meas. Tech., 18, 5247–5264, https://doi.org/10.5194/amt-18-5247-2025, https://doi.org/10.5194/amt-18-5247-2025, 2025
Short summary
Short summary
Greenhouse gases like CO2 and CH4 drive climate change. Satellites enable monitoring of these emissions from space. Our simulations show that the upcoming Twin ANthropogenic Greenhouse gas Observers (TANGO) mission can detect about 500 targets per 4 d cycle under clear skies, but cloud cover reduces detection. Integrating cloud forecasts into TANGO’s manoeuvering boosts detection, highlighting its potential for improving global emission monitoring.
Michael Weimer, Michael Hilker, Stefan Noël, Max Reuter, Michael Buchwitz, Blanca Fuentes Andrade, Rüdiger Lang, Bernd Sierk, Yasjka Meijer, Heinrich Bovensmann, John P. Burrows, and Hartmut Bösch
Atmos. Meas. Tech., 18, 3321–3340, https://doi.org/10.5194/amt-18-3321-2025, https://doi.org/10.5194/amt-18-3321-2025, 2025
Short summary
Short summary
Optical detectors have a maximum signal (saturation). Exceedance means that the measurement has to be discarded. We investigate where saturation will occur for the future European satellite mission dedicated to CO2 monitoring (CO2M) and strategies to avoid saturation. Saturation impacts coverage and precision, both of which are important for estimation of local CO2 emissions. We find that taking two pictures per sampling should be sufficient to avoid saturation for CO2M, with some impact on CO2 precision.
Zihao Yuan, Guangliang Fu, Bastiaan van Diedenhoven, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp
Atmos. Meas. Tech., 17, 2595–2610, https://doi.org/10.5194/amt-17-2595-2024, https://doi.org/10.5194/amt-17-2595-2024, 2024
Short summary
Short summary
Currently, aerosol properties from spaceborne multi-angle polarimeter (MAP) instruments can only be retrieved in cloud-free areas or in areas where an aerosol layer is located above a cloud. Therefore, it is important to be able to identify cloud-free pixels for which an aerosol retrieval algorithm can provide meaningful output. The developed neural network cloud screening demonstrates that cloud masking for MAP aerosol retrieval can be based on the MAP measurements themselves.
Otto Hasekamp, Pavel Litvinov, Guangliang Fu, Cheng Chen, and Oleg Dubovik
Atmos. Meas. Tech., 17, 1497–1525, https://doi.org/10.5194/amt-17-1497-2024, https://doi.org/10.5194/amt-17-1497-2024, 2024
Short summary
Short summary
Aerosols are particles in the atmosphere that cool the climate by reflecting and absorbing sunlight (direct effect) and changing cloud properties (indirect effect). The scale of aerosol cooling is uncertain, hampering accurate climate predictions. We compare two algorithms for the retrieval of aerosol properties from multi-angle polarimetric measurements: Generalized Retrieval of Atmosphere and Surface Properties (GRASP) and Remote sensing of Trace gas and Aerosol Products (RemoTAP).
Zihan Zhang, Guangliang Fu, and Otto Hasekamp
Atmos. Meas. Tech., 16, 6051–6063, https://doi.org/10.5194/amt-16-6051-2023, https://doi.org/10.5194/amt-16-6051-2023, 2023
Short summary
Short summary
In order to conduct accurate aerosol retrieval over snow, the Remote Sensing of Trace Gases and Aerosol Products (RemoTAP) algorithm is extended with a bi-directional reflection distribution function for snow surfaces. The experiments with both synthetic and real data show that the extended RemoTAP maintains capability for snow-free pixels and has obvious advantages in accuracy and the fraction of successful retrievals for retrieval over snow, especially over surfaces with snow cover > 75 %.
Meng Gao, Bryan A. Franz, Peng-Wang Zhai, Kirk Knobelspiesse, Andrew M. Sayer, Xiaoguang Xu, J. Vanderlei Martins, Brian Cairns, Patricia Castellanos, Guangliang Fu, Neranga Hannadige, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Frederick Patt, Anin Puthukkudy, and P. Jeremy Werdell
Atmos. Meas. Tech., 16, 5863–5881, https://doi.org/10.5194/amt-16-5863-2023, https://doi.org/10.5194/amt-16-5863-2023, 2023
Short summary
Short summary
This study evaluated the retrievability and uncertainty of aerosol and ocean properties from PACE's HARP2 instrument using enhanced neural network models with the FastMAPOL algorithm. A cascading retrieval method is developed to improve retrieval performance. A global set of simulated HARP2 data is generated and used for uncertainty evaluations. The performance assessment demonstrates that the FastMAPOL algorithm is a viable approach for operational application to HARP2 data after PACE launch.
Athanasios Tsikerdekis, Otto P. Hasekamp, Nick A. J. Schutgens, and Qirui Zhong
Atmos. Chem. Phys., 23, 9495–9524, https://doi.org/10.5194/acp-23-9495-2023, https://doi.org/10.5194/acp-23-9495-2023, 2023
Short summary
Short summary
Aerosols are tiny particles of different substances (species) that can be emitted into the atmosphere by natural processes or by anthropogenic activities. However, the actual aerosol emission amount per species is highly uncertain. Thus in this work we correct the aerosol emissions used to drive a global aerosol–climate model using satellite observations through a process called data assimilation. These more accurate aerosol emissions can lead to a more accurate weather and climate prediction.
Manu Goudar, Juliëtte C. S. Anema, Rajesh Kumar, Tobias Borsdorff, and Jochen Landgraf
Geosci. Model Dev., 16, 4835–4852, https://doi.org/10.5194/gmd-16-4835-2023, https://doi.org/10.5194/gmd-16-4835-2023, 2023
Short summary
Short summary
A framework was developed to automatically detect plumes and compute emission estimates with cross-sectional flux method (CFM) for biomass burning events in TROPOMI CO datasets using Visible Infrared Imaging Radiometer Suite active fire data. The emissions were more reliable when changing plume height in downwind direction was used instead of constant injection height. The CFM had uncertainty even when the meteorological conditions were accurate; thus there is a need for better inversion models.
Tobias Borsdorff, Teresa Campos, Natalie Kille, Kyle J. Zarzana, Rainer Volkamer, and Jochen Landgraf
Atmos. Meas. Tech., 16, 3027–3038, https://doi.org/10.5194/amt-16-3027-2023, https://doi.org/10.5194/amt-16-3027-2023, 2023
Short summary
Short summary
ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
Edward Gryspeerdt, Adam C. Povey, Roy G. Grainger, Otto Hasekamp, N. Christina Hsu, Jane P. Mulcahy, Andrew M. Sayer, and Armin Sorooshian
Atmos. Chem. Phys., 23, 4115–4122, https://doi.org/10.5194/acp-23-4115-2023, https://doi.org/10.5194/acp-23-4115-2023, 2023
Short summary
Short summary
The impact of aerosols on clouds is one of the largest uncertainties in the human forcing of the climate. Aerosol can increase the concentrations of droplets in clouds, but observational and model studies produce widely varying estimates of this effect. We show that these estimates can be reconciled if only polluted clouds are studied, but this is insufficient to constrain the climate impact of aerosol. The uncertainty in aerosol impact on clouds is currently driven by cases with little aerosol.
Anna Agustí-Panareda, Jérôme Barré, Sébastien Massart, Antje Inness, Ilse Aben, Melanie Ades, Bianca C. Baier, Gianpaolo Balsamo, Tobias Borsdorff, Nicolas Bousserez, Souhail Boussetta, Michael Buchwitz, Luca Cantarello, Cyril Crevoisier, Richard Engelen, Henk Eskes, Johannes Flemming, Sébastien Garrigues, Otto Hasekamp, Vincent Huijnen, Luke Jones, Zak Kipling, Bavo Langerock, Joe McNorton, Nicolas Meilhac, Stefan Noël, Mark Parrington, Vincent-Henri Peuch, Michel Ramonet, Miha Razinger, Maximilian Reuter, Roberto Ribas, Martin Suttie, Colm Sweeney, Jérôme Tarniewicz, and Lianghai Wu
Atmos. Chem. Phys., 23, 3829–3859, https://doi.org/10.5194/acp-23-3829-2023, https://doi.org/10.5194/acp-23-3829-2023, 2023
Short summary
Short summary
We present a global dataset of atmospheric CO2 and CH4, the two most important human-made greenhouse gases, which covers almost 2 decades (2003–2020). It is produced by combining satellite data of CO2 and CH4 with a weather and air composition prediction model, and it has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. This dataset can be used for scientific studies in the field of climate change and the global carbon cycle.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
Short summary
Short summary
In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Bastiaan van Diedenhoven, Otto P. Hasekamp, Brian Cairns, Gregory L. Schuster, Snorre Stamnes, Michael Shook, and Luke Ziemba
Atmos. Meas. Tech., 15, 7411–7434, https://doi.org/10.5194/amt-15-7411-2022, https://doi.org/10.5194/amt-15-7411-2022, 2022
Short summary
Short summary
The strong variability in the chemistry of atmospheric particulate matter affects the amount of water aerosols absorb and their effect on climate. We present a remote sensing method to determine the amount of water in particulate matter. Its application to airborne instruments indicates that the observed aerosols have rather low water contents and low fractions of soluble particles. Future satellites will be able to yield global aerosol water uptake data.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
Short summary
Short summary
The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Antje Inness, Ilse Aben, Melanie Ades, Tobias Borsdorff, Johannes Flemming, Luke Jones, Jochen Landgraf, Bavo Langerock, Philippe Nedelec, Mark Parrington, and Roberto Ribas
Atmos. Chem. Phys., 22, 14355–14376, https://doi.org/10.5194/acp-22-14355-2022, https://doi.org/10.5194/acp-22-14355-2022, 2022
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service (CAMS) provides daily global air quality forecasts to users worldwide. One of the species of interest is carbon monoxide (CO), an important trace gas in the atmosphere with anthropogenic and natural sources, produced by incomplete combustion, for example, by wildfires. This paper looks at how well CAMS can model CO in the atmosphere and shows that the fields can be improved when blending CO data from the TROPOMI instrument with the CAMS model.
Matthieu Dogniaux, Cyril Crevoisier, Silvère Gousset, Étienne Le Coarer, Yann Ferrec, Laurence Croizé, Lianghai Wu, Otto Hasekamp, Bojan Sic, and Laure Brooker
Atmos. Meas. Tech., 15, 4835–4858, https://doi.org/10.5194/amt-15-4835-2022, https://doi.org/10.5194/amt-15-4835-2022, 2022
Short summary
Short summary
The Space Carbon Observatory (SCARBO) concept proposes a constellation of small satellites that would carry a miniaturized Fabry–Pérot imaging interferometer named NanoCarb and an aerosol instrument named SPEXone. In this work, we assess the performance of this concept for the retrieval of the total weighted columns of CO2 and CH4 and show the interest of adding the SPEXone aerosol instrument to improve the CO2 and CH4 column retrieval.
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022, https://doi.org/10.5194/amt-15-4859-2022, 2022
Short summary
Short summary
In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
Short summary
Short summary
We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Athanasios Tsikerdekis, Nick A. J. Schutgens, Guangliang Fu, and Otto P. Hasekamp
Geosci. Model Dev., 15, 3253–3279, https://doi.org/10.5194/gmd-15-3253-2022, https://doi.org/10.5194/gmd-15-3253-2022, 2022
Short summary
Short summary
In our study we quantify the ability of the future satellite sensor SPEXone, part of the NASA PACE mission, to estimate aerosol emissions. The sensor will be able to retrieve accurate information of aerosol light extinction and most importantly light absorption. We simulate SPEXone spatial coverage and combine it with an aerosol model. We found that SPEXone will be able to estimate species-specific (e.g. dust, sea salt, organic or black carbon, sulfates) aerosol emissions very accurately.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
Short summary
Short summary
This paper presents an extended H₂O/HDO total column dataset from short-wave infrared measurements by TROPOMI including cloudy and clear-sky scenes. Coverage is tremendously increased compared to previous TROPOMI HDO datasets. The new dataset is validated against recent ground-based FTIR measurements from TCCON and against aircraft measurements over the ocean. The use of the new dataset is demonstrated with a case study of a cold air outbreak in January 2020.
Meloë S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, and Gregory L. Schuster
Atmos. Chem. Phys., 22, 3713–3742, https://doi.org/10.5194/acp-22-3713-2022, https://doi.org/10.5194/acp-22-3713-2022, 2022
Short summary
Short summary
The impact of aerosols on Earth's radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study assesses how much aerosol optical properties can tell us about aerosol composition.
Tyler Wizenberg, Kimberly Strong, Kaley Walker, Erik Lutsch, Tobias Borsdorff, and Jochen Landgraf
Atmos. Meas. Tech., 14, 7707–7728, https://doi.org/10.5194/amt-14-7707-2021, https://doi.org/10.5194/amt-14-7707-2021, 2021
Short summary
Short summary
CO is an important atmospheric gas that influences both air quality and the climate. Here, we compare CO measurements from TROPOMI with those from ACE-FTS and an Arctic ground-based FTS at Eureka, Nunavut, to further characterize the accuracy of TROPOMI measurements. CO columns from the instruments agree well but show larger differences at high latitudes. Despite this, the results fall within the TROPOMI accuracy target, indicating good data quality at high latitudes.
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021, https://doi.org/10.5194/amt-14-6249-2021, 2021
Short summary
Short summary
This paper presents, for the first time, Sentinel-5 Precursor methane and carbon monoxide validation results covering a period from November 2017 to September 2020. For this study, we used global TCCON and NDACC-IRWG network data covering a wide range of atmospheric and surface conditions across different terrains. We also show the influence of a priori alignment, smoothing uncertainties and the sensitivity of the validation results towards the application of advanced co-location criteria.
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771, https://doi.org/10.5194/amt-14-4755-2021, https://doi.org/10.5194/amt-14-4755-2021, 2021
Short summary
Short summary
In this study, we present results from aerosol retrievals using both synthetic and real lidar datasets, including measurements from the ACEPOL (Aerosol Characterization from Polarimeter and Lidar) campaign, a combined initiative between NASA and SRON (the Netherlands Institute for Space Research). Aerosol microphysical retrievals were performed using the High Spectral Resolution Lidar-2 (HSRL-2) setup, alongside several others, with the ACEPOL retrievals also compared to polarimeter retrievals.
Meng Gao, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, Richard Ferrare, Joel Gales, Otto Hasekamp, Yongxiang Hu, Amir Ibrahim, Brent McBride, Anin Puthukkudy, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 14, 4083–4110, https://doi.org/10.5194/amt-14-4083-2021, https://doi.org/10.5194/amt-14-4083-2021, 2021
Short summary
Short summary
Multi-angle polarimetric measurements can retrieve accurate aerosol properties over complex atmosphere and ocean systems; however, most retrieval algorithms require high computational costs. We propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems and then conduct simultaneous aerosol and ocean color retrievals on AirHARP measurements. The computational acceleration is 103 times with CPU or 104 times with GPU.
Nick Schutgens, Oleg Dubovik, Otto Hasekamp, Omar Torres, Hiren Jethva, Peter J. T. Leonard, Pavel Litvinov, Jens Redemann, Yohei Shinozuka, Gerrit de Leeuw, Stefan Kinne, Thomas Popp, Michael Schulz, and Philip Stier
Atmos. Chem. Phys., 21, 6895–6917, https://doi.org/10.5194/acp-21-6895-2021, https://doi.org/10.5194/acp-21-6895-2021, 2021
Short summary
Short summary
Absorptive aerosol has a potentially large impact on climate change. We evaluate and intercompare four global satellite datasets of absorptive aerosol optical depth (AAOD) and single-scattering albedo (SSA). We show that these datasets show reasonable correlations with the AErosol RObotic NETwork (AERONET) reference, although significant biases remain. In a follow-up paper we show that these observations nevertheless can be used for model evaluation.
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
Short summary
Short summary
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.
Athanasios Tsikerdekis, Nick A. J. Schutgens, and Otto P. Hasekamp
Atmos. Chem. Phys., 21, 2637–2674, https://doi.org/10.5194/acp-21-2637-2021, https://doi.org/10.5194/acp-21-2637-2021, 2021
Short summary
Short summary
Accurate representation of aerosols in the atmosphere is hard to achieve due to their complex microphysical and optical properties and uncertain emissions. In our work, we employ a data assimilation method which integrates model simulations with satellite observation related to the amount, size and the light absorption of aerosol. The use of these observations in an experiment improves aerosol representation and it is recommended for utilization in future data assimilation practices.
Marvin Knapp, Ralph Kleinschek, Frank Hase, Anna Agustí-Panareda, Antje Inness, Jérôme Barré, Jochen Landgraf, Tobias Borsdorff, Stefan Kinne, and André Butz
Earth Syst. Sci. Data, 13, 199–211, https://doi.org/10.5194/essd-13-199-2021, https://doi.org/10.5194/essd-13-199-2021, 2021
Short summary
Short summary
We developed a shipborne variant of a remote sensing spectrometer for direct sunlight measurements of column-averaged atmospheric mixing ratios of carbon dioxide, methane, and carbon monoxide. The instrument was deployed on the research vessel Sonne during a longitudinal transect over the Pacific during June 2019. The campaign yielded more than 32 000 observations which compare excellently to atmospheric composition data from a state-of-the-art model (CAMS) and satellite observations (TROPOMI).
Alba Lorente, Tobias Borsdorff, Andre Butz, Otto Hasekamp, Joost aan de Brugh, Andreas Schneider, Lianghai Wu, Frank Hase, Rigel Kivi, Debra Wunch, David F. Pollard, Kei Shiomi, Nicholas M. Deutscher, Voltaire A. Velazco, Coleen M. Roehl, Paul O. Wennberg, Thorsten Warneke, and Jochen Landgraf
Atmos. Meas. Tech., 14, 665–684, https://doi.org/10.5194/amt-14-665-2021, https://doi.org/10.5194/amt-14-665-2021, 2021
Short summary
Short summary
TROPOMI aboard Sentinel-5P satellite provides methane (CH4) measurements with exceptional temporal and spatial resolution. The study describes a series of improvements developed to retrieve CH4 from TROPOMI. The updated CH4 product features (among others) a more accurate a posteriori correction derived independently of any reference data. The validation of the improved data product shows good agreement with ground-based and satellite measurements, which highlights the quality of the TROPOMI CH4.
Cited articles
Aben, I., Hasekamp, O., and Hartmann, W.: Uncertainties in the space-based measurements of CO2 columns due to scattering in the Earth's atmosphere, J. Quant. Spectrosc. Radiat. Transfer, 104, 450–459, https://doi.org/10.1016/j.jqsrt.2006.09.013, 2007. a
Basilio, R. R., Bennett, M. W., Eldering, A., Lawson, P. R., and Rosenberg, R. A.: Orbiting Carbon Observatory-3 (OCO-3), remote sensing from the International Space Station (ISS), in: Sensors, Systems, and Next-Generation Satellites XXIII, edited by Neeck, S. P., Martimort, P., and Kimura, T., Int. Soc. Opt. Phot. (SPIE), Strasbourg, France, 42–55, 2019. a
Bucholtz, A.: Rayleigh-Scattering calculations for the terrestrial atmosphere, Appl. Opt., 35, 2765–2773, 1995. a
Butz, A., Hasekamp, O. P., Frankenberg, C., Vidot, J., and Aben, I.: CH4 retrievals from space-based solar backscatter measurements: Performance evaluation against simulated aerosol and cirrus loaded scenes, J. Geophys. Res., 115, D24 302, https://doi.org/10.1029/2010JD014514, 2010. a, b
Butz, A., Guerlet, S., Hasekamp, O., Schepers, D., Galli, A., Aben, I., Frankenberg, C., Hartmann, J. M., Tran, H., Kuze, A., Keppel-Aleks, G., Toon, G., Wunch, D., Wennberg, P., Deutscher, N., Griffith, D., Macatangay, R., Messerschmidt, J., Notholt, J., and Warneke, T.: Toward accurate CO2 and CH4 observations from GOSAT, Geophys. Res. Lett., 38, L14812, https://doi.org/10.1029/2011GL047888, 2011. a
Ciais, P., Dolman, A. J., Bombelli, A., Duren, R., Peregon, A., Rayner, P. J., Miller, C., Gobron, N., Kinderman, G., Marland, G., Gruber, N., Chevallier, F., Andres, R. J., Balsamo, G., Bopp, L., Bréon, F.-M., Broquet, G., Dargaville, R., Battin, T. J., Borges, A., Bovensmann, H., Buchwitz, M., Butler, J., Canadell, J. G., Cook, R. B., DeFries, R., Engelen, R., Gurney, K. R., Heinze, C., Heimann, M., Held, A., Henry, M., Law, B., Luyssaert, S., Miller, J., Moriyama, T., Moulin, C., Myneni, R. B., Nussli, C., Obersteiner, M., Ojima, D., Pan, Y., Paris, J.-D., Piao, S. L., Poulter, B., Plummer, S., Quegan, S., Raymond, P., Reichstein, M., Rivier, L., Sabine, C., Schimel, D., Tarasova, O., Valentini, R., Wang, R., van der Werf, G., Wickland, D., Williams, M., and Zehner, C.: Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system, Biogeosciences, 11, 3547–3602, https://doi.org/10.5194/bg-11-3547-2014, 2014. a
Crisp, D., Meijer, Y., Munro, R., Bowman, K., Chatterjee, A., Baker, D., Chevallier, F., Nassar, R., Palmer, P., Agusti-Panareda, A., Al-Saadi, J., Ariel, Y., Basu, S., Bergamaschi, P., Boesch, H., Bousquet, P., Bovensmann, H., Bréon, F.-M., Brunner, D., Buchwitz, M., Buisson, F., Burrows, J., Butz, A., Ciais, P., Clerbaux, C., Counet, P., Crevoisier, C., Crowell, S., DeCola, P., Deniel, C., Dowell, M., Eckman, R., Edwards, D., Ehret, G., Eldering, A., Engelen, R., Fisher, B., Germain, S., Hakkarainen, J., Hilsenrath, E., Holmlund, K., Houweling, S., Hu, H., Jacob, D., Janssens-Maenhout, G., Jones, D., Jouglet, D., Kataoka, F., Kiel, M., Kulawik, S., Kuze, A., Lachance, R., Lang, R., Landgraf, J., Liu, J., Liu, Y., Maksyutov, S., Matsunaga, T., McKeever, J., Moore, B., Nakajima, M., Natraj, V., Nelson, R., Niwa, Y., Oda, T., O'Dell, C., Ott, L., Patra, P., Pawson, S., Payne, V., Pinty, B., Polavarapu, S., Retscher, C., Rosenberg, R., Schuh, A., Schwandner, F., Shiomi, K., Su, W., Tamminen, J., Taylor, T., Veefkind, P., Veihelmann, B., Wofsy, S., Worden, J., Wunch, D., Yang, D., Zhang, P., and Zehner, C.: A Constellation Architecture for Monitoring CArbon Dioxide and Methane from Space, Report, Committee on Earth Observation Satellites (CEOS), 2018. a
Deschamps, P. Y., Breon, F. M., Leroy, M., Podaire, A., Bricaud, A., Buriez, J. C., and Seze, G.: The POLDER mission: instrument characteristics and scientific objectives, IEEE Trans. Geosci. Remote Sens., 32, 598–615, https://doi.org/10.1109/36.297978, 1994. a
Diner, D. J., Boland, S. W., Brauer, M., Bruegge, C., Burke, K. A., Chipman, R., Di Girolamo, L., Garay, M. J., Hasheminassab, S., Hyer, E., Jerrett, M., Jovanovic, V., Kalashnikova, O. V., Liu, Y., Lyapustin, A. I., Martin, R. V., Nastan, A., Ostro, B. D., Ritz, B., Schwartz, J., Wang, J., and Xu, F.: Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA, J. Appl. Remote Sens, 12, 042603, https://doi.org/10.1117/1.JRS.12.042603, 2018. a
Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., MuñOz, O., Veihelmann, B., van der Zande, W. J., Leon, J.-F., Sorokin, M., and Slutsker, I.: Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust, J. Geophys. Res., 111, D11 208, https://doi.org/10.1029/2005JD006619, 2006. a, b
Dubovik, O., Li, Z., Mishchenko, M. I., Tanré, D., Karol, Y., Bojkov, B., Cairns, B., Diner, D. J., Espinosa, W. R., Goloub, P., Gu, X., Hasekamp, O., Hong, J., Hou, W., Knobelspiesse, K. D., Landgraf, J., Li, L., Litvinov, P., Liu, Y., Lopatin, A., Marbach, T., Maring, H., Martins, V., Meijer, Y., Milinevsky, G., Mukai, S., Parol, F., Qiao, Y., Remer, L., Rietjens, J., Sano, I., Stammes, P., Stamnes, S., Sun, X., Tabary, P., Travis, L. D., Waquet, F., Xu, F., Yan, C., and Yin, D.: Polarimetric remote sensing of atmospheric aerosols: Instruments, methodologies, results, and perspectives, J. Quant. Spectrosc. Radiat. Transfer, 224, 474–511, https://doi.org/10.1016/j.jqsrt.2018.11.024, 2019. a
Fougnie, B., Marbach, T., Lacan, A., Lang, R., Schlüssel, P., Poli, G., Munro, R., and Couto, A. B.: The multi-viewing multi-channel multi-polarisation imager – Overview of the 3MI polarimetric mission for aerosol and cloud characterization, J. Quant. Spectrosc. Radiat. Transf., 219, 23–32, https://doi.org/10.1016/j.jqsrt.2018.07.008, 2018. a, b, c
Frankenberg, C., Hasekamp, O., O'Dell, C., Sanghavi, S., Butz, A., and Worden, J.: Aerosol information content analysis of multi-angle high spectral resolution measurements and its benefit for high accuracy greenhouse gas retrievals, Atmos. Meas. Tech., 5, 1809–1821, https://doi.org/10.5194/amt-5-1809-2012, 2012. a, b
Fu, G. and Hasekamp, O.: Retrieval of aerosol microphysical and optical properties over land using a multimode approach, Atmos. Meas. Tech., 11, 6627–6650, https://doi.org/10.5194/amt-11-6627-2018, 2018. a, b
Fu, G., Hasekamp, O., Rietjens, J., Smit, M., Di Noia, A., Cairns, B., Wasilewski, A., Diner, D., Seidel, F., Xu, F., Knobelspiesse, K., Gao, M., da Silva, A., Burton, S., Hostetler, C., Hair, J., and Ferrare, R.: Aerosol retrievals from different polarimeters during the ACEPOL campaign using a common retrieval algorithm, Atmos. Meas. Tech., 13, 553–573, https://doi.org/10.5194/amt-13-553-2020, 2020. a, b
Guerlet, S., Butz, A., Schepers, D., Basu, S., Hasekamp, O. P., Kuze, A., Yokota, T., Blavier, J.-F., Deutscher, N. M., Griffith, D. W. T., Hase, F., Kyro, E., Morino, I., Sherlock, V., Sussmann, R., Galli, A., and Aben, I.: Impact of aerosol and thin cirrus on retrieving and validating XCO2 from GOSAT shortwave infrared measurements, J. Geophys. Res., 118, 4887–4905, https://doi.org/10.1002/jgrd.50332, 2013. a, b
Hasekamp, O. and Landgraf, J.: A linearized vector radiative transfer model for atmospheric trace gas retrieval, J. Quant. Spectrosc. Radiat. Transfer, 75, 221–238, 2002. a
Hasekamp, O. P. and Butz, A.: Efficient calculation of intensity and polarization spectra in vertically inhomogeneous scattering and absorbing atmospheres, J. Geophys. Res., 113, D20 309, https://doi.org/10.1029/2008JD010379, 2008. a
Hasekamp, O. P. and Landgraf, J.: Linearization of vector radiative transfer with respect to aerosol properties and its use in satellite remote sensing, J. Geophys. Res., 110, D04 203, https://doi.org/10.1029/2004JD005260, 2005. a
Hasekamp, O. P. and Landgraf, J.: Retrieval of aerosol properties over land surfaces: capabilities of multiple-viewing-angle intensity and polarization measurements, Appl. Opt., 46, 3332–3344, https://doi.org/10.1364/AO.46.003332, 2007. a, b, c
Hasekamp, O. P., Litvinov, P., and Butz, A.: Aerosol properties over the ocean from PARASOL multiangle photopolarimetric measurements, J. Geophys. Res.-Atmos., 116, D14204, https://doi.org/10.1029/2010JD015469, 2011. a, b
Hasekamp, O. P., Fu, G., Rusli, S. P., Wu, L., Di Noia, A., Brugh, J. a. d., Landgraf, J., Martijn Smit, J., Rietjens, J., and van Amerongen, A.: Aerosol measurements by SPEXone on the NASA PACE mission: expected retrieval capabilities, J. Quant. Spectrosc. Radiat. Transfer, 227, 170–184, https://doi.org/10.1016/j.jqsrt.2019.02.006, 2019. a, b, c
Hobbs, J. M., Drouin, B. J., Oyafuso, F., Payne, V. H., Gunson, M. R., McDuffie, J., and Mlawer, E. J.: Spectroscopic uncertainty impacts on OCO-2/3 retrievals of XCO2, J. Quant. Spectrosc. Radiat. Transfer, 257, 107360, https://doi.org/10.1016/j.jqsrt.2020.107360, 2020. a
Houweling, S., Hartmann, W., Aben, I., Schrijver, H., Skidmore, J., Roelofs, G.-J., and Breon, F.-M.: Evidence of systematic errors in SCIAMACHY-observed CO2 due to aerosols, Atmos. Chem. Phys., 5, 3003–3013, https://doi.org/10.5194/acp-5-3003-2005, 2005. a
Hu, H., Hasekamp, O., Butz, A., Galli, A., Landgraf, J., Aan de Brugh, J., Borsdorff, T., Scheepmaker, R., and Aben, I.: The operational methane retrieval algorithm for TROPOMI, Atmos. Meas. Tech., 9, 5423–5440, https://doi.org/10.5194/amt-9-5423-2016, 2016. a, b
Jung, Y., Kim, J., Kim, W., Boesch, H., Lee, H., Cho, C., and Goo, T.-Y.: Impact of Aerosol Property on the Accuracy of a CO2 Retrieval Algorithm from Satellite Remote Sensing, Remote Sens., 8, 322, https://doi.org/10.3390/rs8040322, 2016. a
Kuang, Z., Margolis, J., Toon, G., Crisp, D., and Yung, Y.: Spaceborne measurements of atmospheric CO2 by high-resolution NIR spectrometry of reflected sunlight: An introductory study, Geophys. Res. Lett., 29, 1716, https://doi.org/10.1029/2001GL014298, 2002. a, b
Kuhlmann, G., Broquet, G., Marshall, J., Clément, V., Löscher, A., Meijer, Y., and Brunner, D.: Detectability of CO2 emission plumes of cities and power plants with the Copernicus Anthropogenic CO2 Monitoring (CO2M) mission, Atmos. Meas. Tech., 12, 6695–6719, https://doi.org/10.5194/amt-12-6695-2019, 2019. a
Landgraf, J., Hasekamp, O., Box, M., and Trautmann, T.: A Linearized Radiative Transfer Model Using the Analytical Perturbation Approach, J. Geophys. Res., 106, 27291–27305, 2001. a
Litvinov, P., Hasekamp, O., and Cairns, B.: Models for surface reflection of radiance and polarized radiance: Comparison with airborne multi-angle photopolarimetric measurements and implications for modeling top-of-atmosphere measurements, Remote Sens. Environ., 115, 781–792, https://doi.org/10.1016/j.rse.2010.11.005, 2011. a
Maignan, F., Bréon, F.-M., Fédèle, E., and Bouvier, M.: Polarized reflectances of natural surfaces: Spaceborne measurements and analytical modeling, Remote Sens. Environ., 113, 2642–2650, https://doi.org/10.1016/j.rse.2009.07.022, 2009. a
Martins, J. V., Fernandez-Borda, R., McBride, B., Remer, L., and Barbosa, H. M. J.: The Harp hyperangular imaging polarimeter and the need for small satellite payloads with high science payoff for earth science remote sensing, IEEE Int. Geosci. Remote Sens Symposium, Valencia, 6304–6307, 2018. a
Meijer, Y., Boesch, H., Bombelli, A., Brunner, D., Buchwitz, M., Ciais, P., Crips, D., Engenlen, R., Holmlund, K., Houweling, S., Janssens-Maenhout, G., Marshall, J., Nakajima, M., Pinty, B., Scholze, M., Bezy, J. L., Drinkwater, M. R., Fehr, T., Fernandez, V., Loescher, A., Nett, H., Sierk, B., Dubovik, O., Landgraf, J., Lang, R., Lindqvist, H., Tamminen, J., and Veefkind, P.: Copernicus CO2 Monitoring Mission Requirements Document, Earth Miss. Sci. Div., European Space Agency (ESA), Noordwijk, 2019. a
Miller, C. E., Brown, L. R., Toth, R. A., Benner, D. C., and Devi, V. M.: Spectroscopic challenges for high accuracy retrievals of atmospheric CO2 and the Orbiting Carbon Observatory (OCO) experiment, C. R. Phys., 6, 876–887, https://doi.org/10.1016/j.crhy.2005.09.005, 2005. a
Mishchenko, M. I., Geogdzhayev, I. V., Cairns, B., Rossow, W. B., and Lacis, A. A.: Aerosol retrievals over the ocean by use of channels 1 and 2 AVHRR data: sensitivity analysis and preliminary results, Appl. Opt., 38, 7325–7341, https://doi.org/10.1364/AO.38.007325, 1999. 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
Nelson, R. R. and O'Dell, C. W.: The impact of improved aerosol priors on near-infrared measurements of carbon dioxide, Atmos. Meas. Tech., 12, 1495–1512, https://doi.org/10.5194/amt-12-1495-2019, 2019. a
Oshchepkov, S., Bril, A., and Yokota, T.: PPDF-based method to account for atmospheric light scattering in observations of carbon dioxide from space, J. Geophys. Res., 113, D23 210, https://doi.org/10.1029/2008JD010061, 2008. a
Phillips, P.: A technique for the numerical solution of certain integral equations of the first kind, J. Ass. Comput. Mat., 9, 84–97, 1962. a
Pinty, B., Janssens-Maenhout, G., Dowell, M., Zunker, H., Brunhes, T., Ciais, P., Dee, D., van der Gon, H. D., Dolman, H., Drinkwater, M., Engelen, R., Heimann, M., Holmlund, K., Husband, R., Kentarchos, A., Meijer, Y., Palmer, P., and Scholze, M.: An Operational Anthropogenic CO2 Emissions Monitoring & Verification Support capacity – Baseline Requirements, Model Components and Functional Architecture, European Commission Joint Research Centre, Brussels, https://doi.org/10.2760/39384, 2017. a, b, c
Reuter, M., Buchwitz, M., Schneising, O., Noël, S., Bovensmann, H., and Burrows, J.: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering–Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sens., 9, 1102, https://doi.org/10.3390/rs9111102, 2017. a
Rietjens, J. H. H., Smit, M., van Harten, G., Di Noia, A., Hasekamp, O. P., de Boer, J., Volten, H., Snik, F., and Keller, C. U.: Accurate spectrally modulating polarimeters for atmospheric aerosol characterization, in: Proceedings of the SPIE, vol. 9613 of Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 9–13 August 2015, San Diego, California, United States, SPIE, p. 96130S, https://doi.org/10.1117/12.2188024, 2015. a
Rothman, L., Gordon, I., Barbe, A., and et al.: The HITRAN 2008 molecular spectroscopic database, J. Quant. Spectrosc. Radiat. Transfer, 110, 533–572, 2009. a
Scheepmaker, R. A., Frankenberg, C., Galli, A., Butz, A., Schrijver, H., Deutscher, N. M., Wunch, D., Warneke, T., Fally, S., and Aben, I.: Improved water vapour spectroscopy in the 4174–4300 cm−1 region and its impact on SCIAMACHY HDO/H2O measurements, Atmos. Meas. Tech., 6, 879–894, https://doi.org/10.5194/amt-6-879-2013, 2013. a
Shettle, E. P. and Fenn, R. W.: Models for aerosols of the lower atmosphere and the effects of the humidity variations on their optical properties, Envir. Res. Pap. 676 AFGL-TR-79-0214, Air Force Geophys. Lab. (OP), Hanscom, Massachusetts, 1979. a
Snik, F., Karalidi, T., and Keller, C. U.: Spectral modulation for full linear polarimetry, Appl. Opt., 48, 1337–1346, https://doi.org/10.1364/AO.48.001337, 2009. a
Tanré, D., Bréon, F. M., Deuzé, J. L., Dubovik, O., Ducos, F., François, P., Goloub, P., Herman, M., Lifermann, A., and Waquet, F.: Remote sensing of aerosols by using polarized, directional and spectral measurements within the A-Train: the PARASOL mission, Atmos. Meas. Tech., 4, 1383–1395, https://doi.org/10.5194/amt-4-1383-2011, 2011. a
Tikhonov, A.: On the solution of incorrectly stated problems and a method of regularization, Dokl. Acad. Nauk SSSR, 151, 501–504, 1963. a
Tran, H., Boulet, C., and Hartmann, J.-M.: Line mixing and collision-induced absorption by oxygen in the A band: Laboratory measurements, model, and tools for atmospheric spectra computations, J. Geophys. Res., 111, D15210, https://doi.org/10.1029/2005JD006869, 2006. a
Wanner, W., Li, X., and Strahler, A. H.: On the derivation of kernels for kernel-driven models of bidirectional reflectance, J. Geophys. Res., 100, 21077–21089, https://doi.org/10.1029/95JD02371, 1995. a
Wu, L., Hasekamp, O., van Diedenhoven, B., and Cairns, B.: Aerosol retrieval from multiangle, multispectral photopolarimetric measurements: importance of spectral range and angular resolution, Atmos. Meas. Tech., 8, 2625–2638, https://doi.org/10.5194/amt-8-2625-2015, 2015. a
Wu, L., Hasekamp, O., van Diedenhoven, B., Cairns, B., Yorks, J. E., and Chowdhary, J.: Passive remote sensing of aerosol layer height using near-UV multiangle polarization measurements, Geophys. Res. Lett., 43, 8783–8790, https://doi.org/10.1002/2016GL069848, 2016. a
Wu, L., Hasekamp, O., Hu, H., Landgraf, J., Butz, A., aan de Brugh, J., Aben, I., Pollard, D. F., Griffith, D. W. T., Feist, D. G., Koshelev, D., Hase, F., Toon, G. C., Ohyama, H., Morino, I., Notholt, J., Shiomi, K., Iraci, L., Schneider, M., de Mazière, M., Sussmann, R., Kivi, R., Warneke, T., Goo, T.-Y., and Té, Y.: Carbon dioxide retrieval from OCO-2 satellite observations using the RemoTeC algorithm and validation with TCCON measurements, Atmos. Meas. Tech., 11, 3111–3130, https://doi.org/10.5194/amt-11-3111-2018, 2018. a
Wu, L., Hasekamp, O., Hu, H., aan de Brugh, J., Landgraf, J., Butz, A., and Aben, I.: Full-physics carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite by only using the 2.06 µm band, Atmos. Meas. Tech., 12, 6049–6058, https://doi.org/10.5194/amt-12-6049-2019, 2019. a, b
Wu, L., aan de Brugh, J., Meijer, Y., Sierk, B., Hasekamp, O., Butz, A., and Landgraf, J.: XCO2 observations using satellite measurements with moderate spectral resolution: investigation using GOSAT and OCO-2 measurements, Atmos. Meas. Tech., 13, 713–729, https://doi.org/10.5194/amt-13-713-2020, 2020.
a, b
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
Xu, F., van Harten, G., Diner, D. J., Kalashnikova, O. V., Seidel, F. C., Bruegge, C. J., and Dubovik, O.: Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager, J. Geophys. Res.-Atmos., 122, 7004–7026, https://doi.org/10.1002/2017JD026776, 2017. a
Short summary
This study investigates the added value of multi-angle polarimeter (MAP) measurements for XCO2 retrievals, particularly in the context of the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) mission. In this paper, we derive the required MAP instrument specification, and we demonstrate that MAP observations significantly improve the retrieval performance and are needed to meet the XCO2 precision and accuracy requirements of the CO2M mission.
This study investigates the added value of multi-angle polarimeter (MAP) measurements for XCO2...
