Articles | Volume 13, issue 8
https://doi.org/10.5194/amt-13-4169-2020
© 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-13-4169-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Total column water vapor retrieval for Global Ozone Monitoring Experience-2 (GOME-2) visible blue observations
Ka Lok Chan
CORRESPONDING AUTHOR
Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
Pieter Valks
Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
Sander Slijkhuis
Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
Claas Köhler
Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
Diego Loyola
Remote Sensing Technology Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany
Related authors
Chengxin Zhang, Xinhan Niu, Hongyu Wu, Zhipeng Ding, Ka Lok Chan, Jhoon Kim, Thomas Wagner, and Cheng Liu
Atmos. Chem. Phys., 25, 759–770, https://doi.org/10.5194/acp-25-759-2025, https://doi.org/10.5194/acp-25-759-2025, 2025
Short summary
Short summary
This research utilizes hourly air pollution observations from the world’s first geostationary satellite to develop a spatiotemporal neural network model for full-coverage surface NO2 pollution prediction over the next 24 hours, achieving outstanding forecasting performance and efficacy. These results highlight the profound impact of geostationary satellite observations in advancing air quality forecasting models, thereby contributing to future models for health exposure to air pollution.
Ka Lok Chan, Pieter Valks, Klaus-Peter Heue, Ronny Lutz, Pascal Hedelt, Diego Loyola, Gaia Pinardi, Michel Van Roozendael, François Hendrick, Thomas Wagner, Vinod Kumar, Alkis Bais, Ankie Piters, Hitoshi Irie, Hisahiro Takashima, Yugo Kanaya, Yongjoo Choi, Kihong Park, Jihyo Chong, Alexander Cede, Udo Frieß, Andreas Richter, Jianzhong Ma, Nuria Benavent, Robert Holla, Oleg Postylyakov, Claudia Rivera Cárdenas, and Mark Wenig
Earth Syst. Sci. Data, 15, 1831–1870, https://doi.org/10.5194/essd-15-1831-2023, https://doi.org/10.5194/essd-15-1831-2023, 2023
Short summary
Short summary
This paper presents the theoretical basis as well as verification and validation of the Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products.
Katerina Garane, Ka Lok Chan, Maria-Elissavet Koukouli, Diego Loyola, and Dimitris Balis
Atmos. Meas. Tech., 16, 57–74, https://doi.org/10.5194/amt-16-57-2023, https://doi.org/10.5194/amt-16-57-2023, 2023
Short summary
Short summary
In this work, 2.5 years of TROPOMI/S5P Total Column Water Vapor (TCWV) observations retrieved from the blue wavelength band are validated against co-located precipitable water measurements from NASA AERONET, which uses Cimel Sun photometers globally. Overall, the TCWV product agrees well on a global scale with the ground-based dataset (Pearson correl. coefficient 0.909) and has a mean relative bias of −2.7 ± 4.9 % with respect to the AERONET observations for moderate albedo and cloudiness.
Gerrit Kuhlmann, Ka Lok Chan, Sebastian Donner, Ying Zhu, Marc Schwaerzel, Steffen Dörner, Jia Chen, Andreas Hueni, Duc Hai Nguyen, Alexander Damm, Annette Schütt, Florian Dietrich, Dominik Brunner, Cheng Liu, Brigitte Buchmann, Thomas Wagner, and Mark Wenig
Atmos. Meas. Tech., 15, 1609–1629, https://doi.org/10.5194/amt-15-1609-2022, https://doi.org/10.5194/amt-15-1609-2022, 2022
Short summary
Short summary
Nitrogen dioxide (NO2) is an air pollutant whose concentration often exceeds air quality guideline values, especially in urban areas. To map the spatial distribution of NO2 in Munich, we conducted the Munich NO2 Imaging Campaign (MuNIC), where NO2 was measured with stationary, mobile, and airborne in situ and remote sensing instruments. The campaign provides a unique dataset that has been used to compare the different instruments and to study the spatial variability of NO2 and its sources.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Ka Lok Chan, Athina Argyrouli, Ronny Lutz, Steffen Beirle, Ehsan Khorsandi, Frank Baier, Vincent Huijnen, Alkiviadis Bais, Sebastian Donner, Steffen Dörner, Myrto Gratsea, François Hendrick, Dimitris Karagkiozidis, Kezia Lange, Ankie J. M. Piters, Julia Remmers, Andreas Richter, Michel Van Roozendael, Thomas Wagner, Mark Wenig, and Diego G. Loyola
Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, https://doi.org/10.5194/amt-14-7297-2021, 2021
Short summary
Short summary
In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented with correction for the dependency of the stratospheric NO2 on the viewing geometry. The AMF calculation is implemented using improved surface albedo, a priori NO2 profiles, and cloud correction. The improved tropospheric NO2 data show good correlations with ground-based MAX-DOAS measurements.
Brian Auffarth, Mark Weber, Alexei Rozanov, Carlo Arosio, John P. Burrows, Melanie Coldewey-Egbers, Sean M. Davis, Doug Degenstein, Kimberlee Dubé, Stacey M. Frith, Lucien Froidevaux, Diego Loyola, Vitali E. Fioletov, Viktoria Sofieva, Ronald van der A, and Jeannette D. Wild
Atmos. Chem. Phys., 26, 13359–13386, https://doi.org/10.5194/acp-26-13359-2026, https://doi.org/10.5194/acp-26-13359-2026, 2026
Short summary
Short summary
This study examines the trends of stratospheric and total ozone between 2000 and 2024, using long-term satellite datasets. Our results show positive trends in the upper stratosphere and a strong ozone recovery in the Southern Hemisphere, while changes in lower altitudes remain mostly small. The total and stratospheric trends show very similar results, indicating that tropospheric ozone contributes little to total column changes, while the stratospheric column is the dominant driver.
Leonardo M. A. Alvarado, Sora Seo, Adrian Doicu, Andreas Richter, and Diego Loyola
EGUsphere, https://doi.org/10.5194/egusphere-2026-4360, https://doi.org/10.5194/egusphere-2026-4360, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Chlorine dioxide reveals the chemistry that destroys ozone in the upper atmosphere, but it is hard to measure from space, especially in the dim light of polar winter. We built a new method to analyse satellite measurements that separates the true signal from instrument noise and gives a trustworthy uncertainty for every observation, without extra corrections. It matches an existing product while being more reliable, supporting operational European monitoring and future missions for other gases.
Francisco J. Pérez-Invernón, Francisco J. Gordillo-Vázquez, Oscar van der Velde, Joan Montanyà, Jesús Alberto López Trujillo, Nicolau Pineda, Diego Loyola, Sora Seo, Christoph Knote, Alexandre O. Fierro, and Heidi Huntrieser
EGUsphere, https://doi.org/10.5194/egusphere-2026-3308, https://doi.org/10.5194/egusphere-2026-3308, 2026
Short summary
Short summary
Lightning is a major source of atmospheric pollutants. This study uses advanced satellite and ground-based data to show how lightning characteristics, such as length, brightness, and duration, affect the production of these pollutants in storms over Spain’s Ebro Valley.
Hongrui Gao, Qin He, Kai Qin, Jhoon Kim, Diego Loyola, Pravash Tiwari, Lingxiao Lu, and Jason Blake Cohen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-443, https://doi.org/10.5194/essd-2026-443, 2026
Revised manuscript under review for ESSD
Short summary
Short summary
There are always gaps in satellite records of air pollution because of factors such as clouds and operating conditions. We used a physics-aware deep learning method, producing a gapless 0.05° hourly dataset of tropospheric nitrogen dioxide over Asian pollution hotspots from 2019 to 2024. The dataset can capture sub-daily changes, revealing how traffic, industry, and clean-air policies shaped pollution, supporting health and environment studies.
Sean Davis, William Ball, Yue Jia, Gabriel Chiodo, Justin Alsing, James Keeble, Hideharu Akiyoshi, Carlo Arosio, Ewa Bednarz, Andreas Chrysanthou, Melanie Coldewey-Egbers, Robert Damadeo, Sandip Dhomse, Mohamadou Diallo, Simone Dietmuller, Roland Eichinger, Stacey Frith, Birgit Hassler, Michaela Hegglin, Daan Hubert, Patrick Jöckel, Béatrice Josse, Natalya Kramarova, Diego Loyola, Eliane Maillard Barras, Marion Marchand, Olaf Morgenstern, David Plummer, Robert Portmann, Karen Rosenlof, Alexei Rozanov, Viktoria Sofieva, Johannes Staehelin, Timofei Sukhodolov, Kleareti Tourpali, Ronald Van der A, H. J. Ray Wang, Krzysztof Wargan, Shingo Watanabe, Mark Weber, Jeannette Wild, Yousuke Yamashita, and Jerry Ziemke
EGUsphere, https://doi.org/10.5194/egusphere-2026-532, https://doi.org/10.5194/egusphere-2026-532, 2026
Short summary
Short summary
This study investigates how tropical ozone levels have changed since 2000 in chemistry climate models and satellite observations to determine how well they agree with one another, and to see if current trends can help predict future levels. At some, satellite records disagree significantly on the magnitude of ozone changes. The study shows a connection between recent ozone trends and future ozone levels, suggesting that satellite measurements could help constrain future ozone changes.
África Barreto, Francisco Quirós, Omaira E. García, Jorge Pereda-de-Pablo, Daniel González-Fernández, Andrés Bedoya-Velásquez, Michael Sicard, Carmen Córdoba-Jabonero, Marco Iarlori, Vincenzo Rizi, Nickolay Krotkov, Simon Carn, Reijo Roininen, Antonio J. Molina-Arias, A. Fernando Almansa, Óscar Álvarez-Losada, Carla Aramo, Juan José Bustos, Romain Ceolato, Adolfo Comerón, Alicia Felpeto, Rosa D. García, Pablo González-Sicilia, Yenny González, Pascal Hedelt, Miguel Hernández, María-Ángeles López-Cayuela, Diego Loyola, Stavros Meletlidis, Constantino Muñoz-Porcar, Ermanno Pietropaolo, Ramón Ramos, Alejandro Rodríguez-Gómez, Roberto Román, Pedro M. Romero-Campos, Martin Stuefer, Carlos Toledano, and Ellsworth J. Welton
Atmos. Meas. Tech., 19, 1385–1406, https://doi.org/10.5194/amt-19-1385-2026, https://doi.org/10.5194/amt-19-1385-2026, 2026
Short summary
Short summary
This manuscript describes the instrumental coverage deployed during the Tajogaite eruption (19 September–25 December 2021) by the Instituto Geográfico Nacional (IGN), the Spanish State Meteorological Agency (AEMET), and other Spanish members of ACTRIS (Aerosol, Clouds and Trace Gases Research Infrastructure) to monitor its atmospheric impact. Two complementary methods provide consistent plume height data for future operational surveillance.
Robert J. D. Spurr, Matt Christi, Nickolay A. Krotkov, Won-Ei Choi, Simon Carn, Can Li, Natalya Kramarova, David Haffner, Eun-Su Yang, Nick Gorkavyi, Alexander Vasilkov, Krzysztof Wargan, Omar Torres, Diego Loyola, Serena Di Pede, J. Pepijn Veefkind, Parker Case, Thomas Schroeder, and Pawan K. Bhartia
Atmos. Meas. Tech., 19, 993–1021, https://doi.org/10.5194/amt-19-993-2026, https://doi.org/10.5194/amt-19-993-2026, 2026
Short summary
Short summary
The submarine eruption of the Hunga volcano released water vapor and sulfur dioxide directly into the stratosphere. The sulfur dioxide formed sulfuric acid aerosols leading to increased scattering of solar ultraviolet radiation (UV), interfering with satellite ozone retrievals. We present a new satellite technique for deriving the amount and height of Hunga aerosols from UV measurements, revealing an unusually low sulfuric acid concentration due to the water-rich conditions in the fresh plume.
Arno Keppens, Daan Hubert, José Granville, Oindrila Nath, Jean-Christopher Lambert, Catherine Wespes, Pierre-François Coheur, Cathy Clerbaux, Anne Boynard, Richard Siddans, Barry Latter, Brian Kerridge, Serena Di Pede, Pepijn Veefkind, Juan Cuesta, Gaelle Dufour, Klaus-Peter Heue, Melanie Coldewey-Egbers, Diego Loyola, Andrea Orfanoz-Cheuquelaf, Swathi Maratt Satheesan, Kai-Uwe Eichmann, Alexei Rozanov, Viktoria F. Sofieva, Jerald R. Ziemke, Antje Inness, Roeland Van Malderen, and Lars Hoffmann
Atmos. Meas. Tech., 18, 6893–6916, https://doi.org/10.5194/amt-18-6893-2025, https://doi.org/10.5194/amt-18-6893-2025, 2025
Short summary
Short summary
The first Tropospheric Ozone Assessment Report (TOAR) encountered discrepancies between several satellite sensors’ estimates of the distribution and change of ozone in the free troposphere. Therefore, contributing to the second TOAR, we harmonise as much as possible the observational perspective of sixteen tropospheric ozone products from satellites. This only partially accounts for the observed discrepancies, with a reduction of 10–40 % of the inter-product dispersion upon harmonisation.
Melanie Coldewey-Egbers, Diego G. Loyola R., Barry Latter, Richard Siddans, Brian Kerridge, Daan Hubert, Michel van Roozendael, and Michael Eisinger
Atmos. Meas. Tech., 18, 5485–5505, https://doi.org/10.5194/amt-18-5485-2025, https://doi.org/10.5194/amt-18-5485-2025, 2025
Short summary
Short summary
The Global Ozone Monitoring Experiment (GOME)-type Ozone Profile Essential Climate Variable (GOP-ECV) data record provides monthly mean ozone profiles with global coverage from 1995 to 2021 at a spatial resolution of 5° × 5°. Measurements from five nadir-viewing satellite sensors are first harmonized and then merged into a coherent record. The long-term stability of the data record is further improved through scaling the profiles using the GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record as a reference.
Carlo Arosio, Viktoria Sofieva, Andrea Orfanoz-Cheuquelaf, Alexei Rozanov, Klaus-Peter Heue, Diego Loyola, Edward Malina, Ryan M. Stauffer, David Tarasick, Roeland Van Malderen, Jerry R. Ziemke, and Mark Weber
Atmos. Meas. Tech., 18, 3247–3265, https://doi.org/10.5194/amt-18-3247-2025, https://doi.org/10.5194/amt-18-3247-2025, 2025
Short summary
Short summary
Tropospheric ozone affects air quality and climate, being a pollutant and a greenhouse gas. We analyze satellite data of tropospheric ozone columns obtained by combining two types of observations: one providing stratospheric and the other 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.
Veronika Gstaiger, Claas Köhler, Philipp Hochstaffl, Martin Bachmann, Raquel de los Reyes, Stefanie Holzwarth, Jiaojiao Tian, Peter Gege, Oliver Paxa, Thomas Krauss, Nina Merkle, and Franz Kurz
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-G-2025, 315–322, https://doi.org/10.5194/isprs-annals-X-G-2025-315-2025, https://doi.org/10.5194/isprs-annals-X-G-2025-315-2025, 2025
Pascal Hedelt, Jens Reichardt, Felix Lauermann, Benjamin Weiß, Nicolas Theys, Alberto Redondas, Africa Barreto, Omaira Garcia, and Diego Loyola
Atmos. Chem. Phys., 25, 1253–1272, https://doi.org/10.5194/acp-25-1253-2025, https://doi.org/10.5194/acp-25-1253-2025, 2025
Short summary
Short summary
The 2021 volcanic eruption of Tajogaite on La Palma is investigated using ground-based and satellite measurements. In addition, the atmospheric transport of the volcanic cloud towards Europe is studied in detail. The amount of SO2 released during the eruption and the height of the volcanic plume are in excellent agreement among the different measurements. Furthermore, volcanic aerosol microphysical properties could be retrieved using a new retrieval approach based on lidar measurements.
Chengxin Zhang, Xinhan Niu, Hongyu Wu, Zhipeng Ding, Ka Lok Chan, Jhoon Kim, Thomas Wagner, and Cheng Liu
Atmos. Chem. Phys., 25, 759–770, https://doi.org/10.5194/acp-25-759-2025, https://doi.org/10.5194/acp-25-759-2025, 2025
Short summary
Short summary
This research utilizes hourly air pollution observations from the world’s first geostationary satellite to develop a spatiotemporal neural network model for full-coverage surface NO2 pollution prediction over the next 24 hours, achieving outstanding forecasting performance and efficacy. These results highlight the profound impact of geostationary satellite observations in advancing air quality forecasting models, thereby contributing to future models for health exposure to air pollution.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech., 17, 6345–6367, https://doi.org/10.5194/amt-17-6345-2024, https://doi.org/10.5194/amt-17-6345-2024, 2024
Short summary
Short summary
This paper describes a new treatment of the spatial misregistration of cloud properties for Sentinel-5 Precursor, when the footprints of different spectral bands are not perfectly aligned. The methodology exploits synergies between spectrometers and imagers, like TROPOMI and VIIRS. The largest improvements have been identified for heterogeneous scenes at cloud edges. This approach is generic and can also be applied to future Sentinel-4 and Sentinel-5 instruments.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
Short summary
Short summary
In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Tim Trent, Marc Schröder, Shu-Peng Ho, Steffen Beirle, Ralf Bennartz, Eva Borbas, Christian Borger, Helene Brogniez, Xavier Calbet, Elisa Castelli, Gilbert P. Compo, Wesley Ebisuzaki, Ulrike Falk, Frank Fell, John Forsythe, Hans Hersbach, Misako Kachi, Shinya Kobayashi, Robert E. Kursinski, Diego Loyola, Zhengzao Luo, Johannes K. Nielsen, Enzo Papandrea, Laurence Picon, Rene Preusker, Anthony Reale, Lei Shi, Laura Slivinski, Joao Teixeira, Tom Vonder Haar, and Thomas Wagner
Atmos. Chem. Phys., 24, 9667–9695, https://doi.org/10.5194/acp-24-9667-2024, https://doi.org/10.5194/acp-24-9667-2024, 2024
Short summary
Short summary
In a warmer future, water vapour will spend more time in the atmosphere, changing global rainfall patterns. In this study, we analysed the performance of 28 water vapour records between 1988 and 2014. We find sensitivity to surface warming generally outside expected ranges, attributed to breakpoints in individual record trends and differing representations of climate variability. The implication is that longer records are required for high confidence in assessing climate trends.
Philipp Hochstaffl, Franz Schreier, Claas Henning Köhler, Andreas Baumgartner, and Daniele Cerra
Atmos. Meas. Tech., 16, 4195–4214, https://doi.org/10.5194/amt-16-4195-2023, https://doi.org/10.5194/amt-16-4195-2023, 2023
Short summary
Short summary
The study examines methane enhancements inferred from hyperspectral imaging observations using different retrieval schemes. One of the core challenges is the high spatial and moderate spectral resolution as it makes separation of spectral variations caused by molecular absorption and surface reflectivity challenging. It was found that localized methane enhancements can be detected and quantified from HySpex airborne observations using various retrieval schemes.
Ka Lok Chan, Pieter Valks, Klaus-Peter Heue, Ronny Lutz, Pascal Hedelt, Diego Loyola, Gaia Pinardi, Michel Van Roozendael, François Hendrick, Thomas Wagner, Vinod Kumar, Alkis Bais, Ankie Piters, Hitoshi Irie, Hisahiro Takashima, Yugo Kanaya, Yongjoo Choi, Kihong Park, Jihyo Chong, Alexander Cede, Udo Frieß, Andreas Richter, Jianzhong Ma, Nuria Benavent, Robert Holla, Oleg Postylyakov, Claudia Rivera Cárdenas, and Mark Wenig
Earth Syst. Sci. Data, 15, 1831–1870, https://doi.org/10.5194/essd-15-1831-2023, https://doi.org/10.5194/essd-15-1831-2023, 2023
Short summary
Short summary
This paper presents the theoretical basis as well as verification and validation of the Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products.
Katerina Garane, Ka Lok Chan, Maria-Elissavet Koukouli, Diego Loyola, and Dimitris Balis
Atmos. Meas. Tech., 16, 57–74, https://doi.org/10.5194/amt-16-57-2023, https://doi.org/10.5194/amt-16-57-2023, 2023
Short summary
Short summary
In this work, 2.5 years of TROPOMI/S5P Total Column Water Vapor (TCWV) observations retrieved from the blue wavelength band are validated against co-located precipitable water measurements from NASA AERONET, which uses Cimel Sun photometers globally. Overall, the TCWV product agrees well on a global scale with the ground-based dataset (Pearson correl. coefficient 0.909) and has a mean relative bias of −2.7 ± 4.9 % with respect to the AERONET observations for moderate albedo and cloudiness.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
Short summary
Short summary
The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
Klaus-Peter Heue, Diego Loyola, Fabian Romahn, Walter Zimmer, Simon Chabrillat, Quentin Errera, Jerry Ziemke, and Natalya Kramarova
Atmos. Meas. Tech., 15, 5563–5579, https://doi.org/10.5194/amt-15-5563-2022, https://doi.org/10.5194/amt-15-5563-2022, 2022
Short summary
Short summary
To retrieve tropospheric ozone column information, we subtract stratospheric column data of BASCOE from TROPOMI/S5P total ozone columns.
The new S5P-BASCOE data agree well with existing tropospheric data like OMPS-MERRA-2. The data are also compared to ozone soundings.
The tropospheric ozone columns show the expected temporal and spatial patterns. We will also apply the algorithm to future UV nadir missions like Sentinel 4 or 5 or to recent and ongoing missions like GOME_2 or OMI.
Pieternel F. Levelt, Deborah C. Stein Zweers, Ilse Aben, Maite Bauwens, Tobias Borsdorff, Isabelle De Smedt, Henk J. Eskes, Christophe Lerot, Diego G. Loyola, Fabian Romahn, Trissevgeni Stavrakou, Nicolas Theys, Michel Van Roozendael, J. Pepijn Veefkind, and Tijl Verhoelst
Atmos. Chem. Phys., 22, 10319–10351, https://doi.org/10.5194/acp-22-10319-2022, https://doi.org/10.5194/acp-22-10319-2022, 2022
Short summary
Short summary
Using the COVID-19 lockdown periods as an example, we show how Sentinel-5P/TROPOMI trace gas data (NO2, SO2, CO, HCHO and CHOCHO) can be used to understand impacts on air quality for regions and cities around the globe. We also provide information for both experienced and inexperienced users about how we created the data using state-of-the-art algorithms, where to get the data, methods taking meteorological and seasonal variability into consideration, and insights for future studies.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Andreas Richter, Pieter Valks, Ramina Alwarda, Kristof Bognar, Udo Frieß, José Granville, Myojeong Gu, Paul Johnston, Cristina Prados-Roman, Richard Querel, Kimberly Strong, Thomas Wagner, Folkard Wittrock, and Margarita Yela Gonzalez
Atmos. Meas. Tech., 15, 3439–3463, https://doi.org/10.5194/amt-15-3439-2022, https://doi.org/10.5194/amt-15-3439-2022, 2022
Short summary
Short summary
We report on the GOME-2A and GOME-2B OClO dataset (2007 to 2016, from the EUMETSAT's AC SAF) validation using data from nine NDACC zenith-scattered-light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Specific sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings and their typical errors. Good agreement is found for both the inter-annual variability and the overall OClO seasonal behavior.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Thilo Erbertseder, Diego Loyola, Pieter Valks, Song Liu, Dale J. Allen, Kenneth E. Pickering, Eric J. Bucsela, Patrick Jöckel, Jos van Geffen, Henk Eskes, Sergio Soler, Francisco J. Gordillo-Vázquez, and Jeff Lapierre
Atmos. Meas. Tech., 15, 3329–3351, https://doi.org/10.5194/amt-15-3329-2022, https://doi.org/10.5194/amt-15-3329-2022, 2022
Short summary
Short summary
Lightning, one of the major sources of nitrogen oxides in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. In this work, we contribute to improving the estimation of lightning-produced nitrogen oxides in the Ebro Valley and the Pyrenees by using two different TROPOMI products and comparing the results.
Mark Weber, Carlo Arosio, Melanie Coldewey-Egbers, Vitali E. Fioletov, Stacey M. Frith, Jeannette D. Wild, Kleareti Tourpali, John P. Burrows, and Diego Loyola
Atmos. Chem. Phys., 22, 6843–6859, https://doi.org/10.5194/acp-22-6843-2022, https://doi.org/10.5194/acp-22-6843-2022, 2022
Short summary
Short summary
Long-term trends in column ozone have been determined from five merged total ozone datasets spanning the period 1978–2020. We show that ozone recovery due to the decline in stratospheric halogens after the 1990s (as regulated by the Montreal Protocol) is evident outside the tropical region and amounts to half a percent per decade. The ozone recovery in the Northern Hemisphere is however compensated for by the negative long-term trend contribution from atmospheric dynamics since the year 2000.
Melanie Coldewey-Egbers, Diego G. Loyola, Christophe Lerot, and Michel Van Roozendael
Atmos. Chem. Phys., 22, 6861–6878, https://doi.org/10.5194/acp-22-6861-2022, https://doi.org/10.5194/acp-22-6861-2022, 2022
Short summary
Short summary
Monitoring the long-term evolution of ozone and the evaluation of trends is essential to assess the efficacy of the Montreal Protocol and its amendments. The first signs of recovery as a consequence of decreasing amounts of ozone-depleting substances have been reported, but the impact needs to be investigated in more detail. In the Southern Hemisphere significant positive trends were found, but in the Northern Hemisphere the expected increase is still not yet visible.
Maria-Elissavet Koukouli, Konstantinos Michailidis, Pascal Hedelt, Isabelle A. Taylor, Antje Inness, Lieven Clarisse, Dimitris Balis, Dmitry Efremenko, Diego Loyola, Roy G. Grainger, and Christian Retscher
Atmos. Chem. Phys., 22, 5665–5683, https://doi.org/10.5194/acp-22-5665-2022, https://doi.org/10.5194/acp-22-5665-2022, 2022
Short summary
Short summary
Volcanic eruptions eject large amounts of ash and trace gases into the atmosphere. The use of space-borne instruments enables the global monitoring of volcanic SO2 emissions in an economical and risk-free manner. The main aim of this paper is to present its extensive verification, accomplished within the ESA S5P+I: SO2LH project, over major recent volcanic eruptions, against collocated space-borne measurements, as well as assess its impact on the forecasts provided by CAMS.
Gerrit Kuhlmann, Ka Lok Chan, Sebastian Donner, Ying Zhu, Marc Schwaerzel, Steffen Dörner, Jia Chen, Andreas Hueni, Duc Hai Nguyen, Alexander Damm, Annette Schütt, Florian Dietrich, Dominik Brunner, Cheng Liu, Brigitte Buchmann, Thomas Wagner, and Mark Wenig
Atmos. Meas. Tech., 15, 1609–1629, https://doi.org/10.5194/amt-15-1609-2022, https://doi.org/10.5194/amt-15-1609-2022, 2022
Short summary
Short summary
Nitrogen dioxide (NO2) is an air pollutant whose concentration often exceeds air quality guideline values, especially in urban areas. To map the spatial distribution of NO2 in Munich, we conducted the Munich NO2 Imaging Campaign (MuNIC), where NO2 was measured with stationary, mobile, and airborne in situ and remote sensing instruments. The campaign provides a unique dataset that has been used to compare the different instruments and to study the spatial variability of NO2 and its sources.
Antje Inness, Melanie Ades, Dimitris Balis, Dmitry Efremenko, Johannes Flemming, Pascal Hedelt, Maria-Elissavet Koukouli, Diego Loyola, and Roberto Ribas
Geosci. Model Dev., 15, 971–994, https://doi.org/10.5194/gmd-15-971-2022, https://doi.org/10.5194/gmd-15-971-2022, 2022
Short summary
Short summary
This paper describes the way that the Copernicus Atmosphere Monitoring Service (CAMS) produces forecasts of volcanic SO2. These forecasts are provided routinely every day. They are created by blending SO2 data from satellite instruments (TROPOMI and GOME-2) with the CAMS model. We show that the quality of the CAMS SO2 forecasts can be improved if additional information about the height of volcanic plumes is provided in the satellite data.
Christophe Lerot, François Hendrick, Michel Van Roozendael, Leonardo M. A. Alvarado, Andreas Richter, Isabelle De Smedt, Nicolas Theys, Jonas Vlietinck, Huan Yu, Jeroen Van Gent, Trissevgeni Stavrakou, Jean-François Müller, Pieter Valks, Diego Loyola, Hitoshi Irie, Vinod Kumar, Thomas Wagner, Stefan F. Schreier, Vinayak Sinha, Ting Wang, Pucai Wang, and Christian Retscher
Atmos. Meas. Tech., 14, 7775–7807, https://doi.org/10.5194/amt-14-7775-2021, https://doi.org/10.5194/amt-14-7775-2021, 2021
Short summary
Short summary
Global measurements of glyoxal tropospheric columns from the satellite instrument TROPOMI are presented. Such measurements can contribute to the estimation of atmospheric emissions of volatile organic compounds. This new glyoxal product has been fully characterized with a comprehensive error budget, with comparison with other satellite data sets as well as with validation based on independent ground-based remote sensing glyoxal observations.
Daan Hubert, Klaus-Peter Heue, Jean-Christopher Lambert, Tijl Verhoelst, Marc Allaart, Steven Compernolle, Patrick D. Cullis, Angelika Dehn, Christian Félix, Bryan J. Johnson, Arno Keppens, Debra E. Kollonige, Christophe Lerot, Diego Loyola, Matakite Maata, Sukarni Mitro, Maznorizan Mohamad, Ankie Piters, Fabian Romahn, Henry B. Selkirk, Francisco R. da Silva, Ryan M. Stauffer, Anne M. Thompson, J. Pepijn Veefkind, Holger Vömel, Jacquelyn C. Witte, and Claus Zehner
Atmos. Meas. Tech., 14, 7405–7433, https://doi.org/10.5194/amt-14-7405-2021, https://doi.org/10.5194/amt-14-7405-2021, 2021
Short summary
Short summary
We assess the first 2 years of TROPOMI tropical tropospheric ozone column data. Comparisons to reference measurements by ozonesonde and satellite sensors show that TROPOMI bias (−0.1 to +2.3 DU) and precision (1.5 to 2.5 DU) meet mission requirements. Potential causes of bias and its spatio-temporal structure are discussed, as well as ways to identify sampling errors. Our analysis of known geophysical patterns demonstrates the improved performance of TROPOMI with respect to its predecessors.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Ka Lok Chan, Athina Argyrouli, Ronny Lutz, Steffen Beirle, Ehsan Khorsandi, Frank Baier, Vincent Huijnen, Alkiviadis Bais, Sebastian Donner, Steffen Dörner, Myrto Gratsea, François Hendrick, Dimitris Karagkiozidis, Kezia Lange, Ankie J. M. Piters, Julia Remmers, Andreas Richter, Michel Van Roozendael, Thomas Wagner, Mark Wenig, and Diego G. Loyola
Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, https://doi.org/10.5194/amt-14-7297-2021, 2021
Short summary
Short summary
In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented with correction for the dependency of the stratospheric NO2 on the viewing geometry. The AMF calculation is implemented using improved surface albedo, a priori NO2 profiles, and cloud correction. The improved tropospheric NO2 data show good correlations with ground-based MAX-DOAS measurements.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
Short summary
Short summary
We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Cited articles
Alexandrov, M. D., Schmid, B., Turner, D. D., Cairns, B., Oinas, V., Lacis, A. A., Gutman, S. I., Westwater, E. R., Smirnov, A., and Eilers, J.: Columnar water vapor retrievals from multifilter rotating shadowband radiometer data, J. Geophys. Res.-Atmos., 114, D02306, https://doi.org/10.1029/2008JD010543, 2009. a, b
Anderson, G. P., Clough, S. A., Kneizys, F., Chetwynd, J. H., and Shettle,
E. P.: AFGL atmospheric constituent profiles (0.120 km), Tech. rep., Air
Force Geophysics Lab Hanscom Afb, MA, 43 pp., 1986. a
Antón, M., Loyola, D., Román, R., and Vömel, H.: Validation of GOME-2/MetOp-A total water vapour column using reference radiosonde data from the GRUAN network, Atmos. Meas. Tech., 8, 1135–1145, https://doi.org/5194/amt-8-1135-2015, 2015. a, b, c, d
Bauer, P. and Schluessel, P.: Rainfall, total water, ice water, and water vapor over sea from polarized microwave simulations and Special Sensor
Microwave/Imager data, J. Geophys. Res.-Atmos., 98,
20 737–20 759, https://doi.org/10.1029/93JD01577, 1993. a
Beirle, S., Lampel, J., Wang, Y., Mies, K., Dörner, S., Grossi, M., Loyola, D., Dehn, A., Danielczok, A., Schröder, M., and Wagner, T.: The ESA GOME-Evolution “Climate” water vapor product: a homogenized time series of H2O columns from GOME, SCIAMACHY, and GOME-2, Earth Syst. Sci. Data, 10, 449–468, https://doi.org/5194/essd-10-449-2018, 2018. a
Bellomo, K., Clement, A., Mauritsen, T., Rädel, G., and Stevens, B.: Simulating the role of subtropical stratocumulus clouds in driving Pacific climate variability, J. Climate, 27, 5119–5131, https://doi.org/10.1175/JCLI-D-13-00548.1, 2014. a
Bhatia, N., Tolpekin, V. A., Reusen, I., Sterckx, S., Biesemans, J.,
and Stein, A.: Sensitivity of reflectance to water vapor and aerosol
optical thickness, IEEE J. Sel. Top. Appl., 8, 3199–3208,
https://doi.org/10.1109/JSTARS.2015.2425954, 2015. a
Bhatia, N., Iordache, M.-D., Stein, A., Reusen, I., and Tolpekin, V. A.:
Propagation of uncertainty in atmospheric parameters to hyperspectral
unmixing, Remote Sens. Environ., 204, 472–484,
https://doi.org/10.1016/j.rse.2017.10.008, 2018. a
Boersma, K. F., Eskes, H. J., and Brinksma, E. J.: Error analysis for
tropospheric NO2 retrieval from space, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2003JD003962, 2004. a, b, c
Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/5194/amt-4-1905-2011, 2011. a, b
Borger, C., Beirle, S., Dörner, S., Sihler, H., and Wagner, T.: Total column water vapour retrieval from S-5P/TROPOMI in the visible blue spectral range, Atmos. Meas. Tech., 13, 2751–2783, https://doi.org/5194/amt-13-2751-2020, 2020. a
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster,
P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh,
S., Sherwood, S., Stevens, B., and Zhang, X.: Chapter 7 – Clouds and Aerosols, in: Climate Change 2013 – The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 571–658, https://doi.org/10.1017/CBO9781107415324.016, 2013. a
Bovensmann, H., Burrows, J., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V., Chance, K., and Goede, A.: SCIAMACHY: Mission objectives and
measurement modes, J. Atmos. Sci., 56, 127–150,
https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999. a
Brion, J., Chakir, A., Charbonnier, J., Daumont, D., Parisse, C., and Malicet, J.: Absorption spectra measurements for the ozone molecule in the 350–830 nm region, J. Atmos. Chem., 30, 291–299,
https://doi.org/10.1023/A:1006036924364, 1998. a, b
Brown, P. T., Li, W., Jiang, J. H., and Su, H.: Unforced surface air
temperature variability and its contrasting relationship with the anomalous
TOA energy flux at local and global spatial scales, J. Climate, 29,
925–940, https://doi.org/10.1175/JCLI-D-15-0384.1, 2016. a
Burrows, J. P., Weber, M., Buchwitz, M., Rozanov, V.,
Ladstätter-Weißenmayer, A., Richter, A., DeBeek, R., Hoogen, R.,
Bramstedt, K., Eichmann, K.-U., et al.: The global ozone monitoring
experiment (GOME): mission concept and first scientific results, J. Atmos. Sci., 56, 151–175,
https://doi.org/10.1175/1520-0469(1999)056<0151:TGOMEG>2.0.CO;2, 1999. a
Chan, K. L., Pöhler, D., Kuhlmann, G., Hartl, A., Platt, U., and Wenig, M. O.: NO2 measurements in Hong Kong using LED based long path differential optical absorption spectroscopy, Atmos. Meas. Tech., 5, 901–912, https://doi.org/5194/amt-5-901-2012, 2012. a
Chance, K. and Kurucz, R.: An improved high-resolution solar reference spectrum for Earth's atmosphere measurements in the ultraviolet, visible, and near infrared, J Quant. Spectrosc. Ra., 111, 1289–1295, https://doi.org/10.1016/j.jqsrt.2010.01.036, 2010. a
Clough, S. A. and Iacono, M. J.: Line-by-line calculation of atmospheric fluxes and cooling rates: 2. Application to carbon dioxide, ozone, methane, nitrous oxide and the halocarbons, J. Geophys. Res.-Atmos., 100, 16519–16535, https://doi.org/10.1029/95JD01386, 1995. a
Colman, R.: A comparison of climate feedbacks in general circulation models,
Clim. Dynam., 20, 865–873, https://doi.org/10.1007/s00382-003-0310-z, 2003. a
De Smedt, I., Theys, N., Yu, H., Danckaert, T., Lerot, C., Compernolle, S., Van Roozendael, M., Richter, A., Hilboll, A., Peters, E., Pedergnana, M., Loyola, D., Beirle, S., Wagner, T., Eskes, H., van Geffen, J., Boersma, K. F., and Veefkind, P.: Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project, Atmos. Meas. Tech., 11, 2395–2426, https://doi.org/5194/amt-11-2395-2018, 2018. a, b, c
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, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: 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, b, c
Durre, I., Vose, R. S., and Wuertz, D. B.: Overview of the integrated global
radiosonde archive, J. Climate, 19, 53–68, https://doi.org/10.1175/JCLI3594.1,
2006. a
Hartmann, D., Klein Tank, A., Rusticucci, M., Alexander, L., Brönnimann,
S., Charabi, Y., Dentener, F., Dlugokencky, E., Easterling, D., Kaplan, A.,
Soden, B., Thorne, P., Wild, M., and Zhai, P.: Observations: Atmosphere and Surface, in Climate Change 2013 – The Physical Science Basis: Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge,
United Kingdom and New York, NY, USA, 159–254, https://doi.org/10.1017/CBO9781107415324.008, 2013. a
Holben, B., Eck, T., Slutsker, I., Tanre, D., Buis, J., Setzer, A., Vermote,
E., Reagan, J., Kaufman, Y., Nakajima, T., Lavenu, F., Jankowiak, I., and
Smirnov, A.: AERONET – A federated instrument network and data archive for
aerosol characterization, Remote Sens. Environ., 66, 1–16,
1998. a
Holben, B. N., Tanre, D., Smirnov, A., Eck, T. F., Slutsker, I., Abuhassan, N.,
Newcomb, W. W., Schafer, J. S., Chatenet, B., Lavenu, F., Kaufman, Y. J.,
Castle, J. V., Setzer, A., Markham, B., Clark, D., Frouin, R., Halthore, R.,
Karneli, A., O'Neill, N. T., Pietras, C., Pinker, R. T., Voss, K., and
Zibordi, G.: An emerging ground-based aerosol climatology: Aerosol optical
depth from AERONET, J. Geophys. Res.-Atmos., 106,
12 067–12 097, https://doi.org/10.1029/2001JD900014, 2001. a
Kalakoski, N., Kujanpää, J., Sofieva, V., Tamminen, J., Grossi, M., and Valks, P.: Validation of GOME-2/Metop total column water vapour with ground-based and in situ measurements, Atmos. Meas. Tech., 9, 1533–1544, https://doi.org/5194/amt-9-1533-2016, 2016. a, b, c
Kaufman, Y. J. and Gao, B. .: Remote sensing of water vapor in the near
IR from EOS/MODIS, IEEE T. Geosci. Remote,
30, 871–884, https://doi.org/10.1109/36.175321, 1992. a
Kiehl, J. T. and Trenberth, K. E.: Earth's annual global mean energy budget,
B. Am. Meteorol. Soc., 78, 197–208,
https://doi.org/10.1175/1520-0477(1997)078<0197:EAGMEB>2.0.CO;2, 1997. a
Klaes, K. D., Cohen, M., Buhler, Y., Schlüssel, P., Munro, R., Luntama,
J.-P., von Engeln, A., Clérigh, E. Ó., Bonekamp, H., Ackermann, J.,
et al.: An introduction to the EUMETSAT polar system, B. Am. Meteorol. Soc., 88, 1085–1096, https://doi.org/10.1175/BAMS-88-7-1085, 2007. a
Krotkov, N. A., Lamsal, L. N., Celarier, E. A., Swartz, W. H., Marchenko, S. V., Bucsela, E. J., Chan, K. L., Wenig, M., and Zara, M.: The version 3 OMI NO2 standard product, Atmos. Meas. Tech., 10, 3133–3149, https://doi.org/5194/amt-10-3133-2017, 2017. a, b
Lampel, J., Pöhler, D., Tschritter, J., Frieß, U., and Platt, U.: On the relative absorption strengths of water vapour in the blue wavelength range, Atmos. Meas. Tech., 8, 4329–4346, https://doi.org/5194/amt-8-4329-2015, 2015. a, b
Levelt, P., Van den Oord, G. H. J., Dobber, M., Malkki, A., Visser, H.,
de Vries, J., Stammes, P., Lundell, J., and Saari, H.: The ozone monitoring
instrument, IEEE T. Geosci. Remote, 44,
1093–1101, https://doi.org/10.1109/TGRS.2006.872333, 2006. a
Li, Z., Fielding, E. J., Cross, P., and Muller, J.-P.: Interferometric
synthetic aperture radar atmospheric correction: medium resolution imaging
spectrometer and advanced synthetic aperture radar integration, Geophys. Res. Lett, 33, L06816, https://doi.org/10.1029/2005GL025299, 2006. a
Liu, S., Valks, P., Pinardi, G., De Smedt, I., Yu, H., Beirle, S., and Richter, A.: An improved total and tropospheric NO2 column retrieval for GOME-2, Atmos. Meas. Tech., 12, 1029–1057, https://doi.org/5194/amt-12-1029-2019, 2019. a
Lorente, A., Boersma, K. F., Stammes, P., Tilstra, L. G., Richter, A., Yu, H., Kharbouche, S., and Muller, J.-P.: The importance of surface reflectance anisotropy for cloud and NO2 retrievals from GOME-2 and OMI, Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/5194/amt-11-4509-2018, 2018. a
Loyola, D. G., Thomas, W., Livschitz, Y., Ruppert, T., Albert, P.,
and Hollmann, R.: Cloud properties derived from GOME/ERS-2 backscatter data for trace gas retrieval, IEEE T. Geosci. Remote, 45, 2747–2758, https://doi.org/10.1109/TGRS.2007.901043, 2007. a
Loyola, D. G., Thomas, W., Spurr, R., and Mayer, B.: Global patterns in
daytime cloud properties derived from GOME backscatter UV-VIS
measurements, Int. J. Remote Sens., 31, 4295–4318,
https://doi.org/10.1080/01431160903246741, 2010. a
Loyola, D. G., Xu, J., Heue, K.-P., and Zimmer, W.: Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements, Atmos. Meas. Tech., 13, 985–999, https://doi.org/5194/amt-13-985-2020, 2020. a
Lutz, R., Loyola, D., Gimeno García, S., and Romahn, F.: OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B, Atmos. Meas. Tech., 9, 2357–2379, https://doi.org/5194/amt-9-2357-2016, 2016. a, b
Martin, R. V., Chance, K., Jacob, D. J., Kurosu, T. P., Spurr, R. J. D.,
Bucsela, E., Gleason, J. F., Palmer, P. I., Bey, I., Fiore, A. M., Li, Q.,
Yantosca, R. M., and Koelemeijer, R. B. A.: An improved retrieval of
tropospheric nitrogen dioxide from GOME, J. Geophys. Res.-Atmos., 107, ACH 9-1–ACH 9-21, https://doi.org/10.1029/2001JD001027, 2002. a
Munro, R., Lang, R., Klaes, D., Poli, G., Retscher, C., Lindstrot, R., Huckle, R., Lacan, A., Grzegorski, M., Holdak, A., Kokhanovsky, A., Livschitz, J., and Eisinger, M.: The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview, Atmos. Meas. Tech., 9, 1279–1301, https://doi.org/5194/amt-9-1279-2016, 2016. a
Noël, S., Buchwitz, M., Bovensmann, H., Hoogen, R., and Burrows, J. P.:
Atmospheric water vapor amounts retrieved from GOME satellite data,
Geophys. Res. Lett, 26, 1841–1844, https://doi.org/10.1029/1999GL900437,
1999. a
Noël, S., Buchwitz, M., and Burrows, J. P.: First retrieval of global water vapour column amounts from SCIAMACHY measurements, Atmos. Chem. Phys., 4, 111–125, https://doi.org/5194/acp-4-111-2004, 2004. a
Palmer, P. I., Jacob, D. J., Chance, K., Martin, R. V., Spurr, R. J. D.,
Kurosu, T. P., Bey, I., Yantosca, R., Fiore, A., and Li, Q.: Air mass factor formulation for spectroscopic measurements from satellites: application to formaldehyde retrievals from the global ozone monitoring experiment, J. Geophys. Res.-Atmos., 106, 14 539–14 550,
https://doi.org/10.1029/2000JD900772, 2001. a
Pérez-Ramírez, D., Whiteman, D. N., Smirnov, A., Lyamani, H., Holben,
B. N., Pinker, R., Andrade, M., and Alados-Arboledas, L.: Evaluation of
AERONET precipitable water vapor versus microwave radiometry, GPS, and
radiosondes at ARM sites, J. Geophys. Res.-Atmos.,
119, 9596–9613, https://doi.org/10.1002/2014JD021730, 2014. a, b, c
Pope, R. M. and Fry, E. S.: Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements, Appl. Optics, 36, 8710–8723,
https://doi.org/10.1364/AO.36.008710, 1997. a, b
Pougatchev, N., August, T., Calbet, X., Hultberg, T., Oduleye, O., Schlüssel, P., Stiller, B., Germain, K. St., and Bingham, G.: IASI temperature and water vapor retrievals – error assessment and validation, Atmos. Chem. Phys., 9, 6453–6458, https://doi.org/5194/acp-9-6453-2009, 2009. a
Richter, A. and Burrows, J.: Tropospheric NO2 from GOME measurements,
Adv. Space Res., 29, 1673–1683,
https://doi.org/10.1016/S0273-1177(02)00100-X, 2002. a
Román, R., Antón, M., Cachorro, V., Loyola, D., de Galisteo, J. O.,
de Frutos, A., and Romero-Campos, P.: Comparison of total water vapor column from GOME-2 on MetOp-A against ground-based GPS measurements at the Iberian Peninsula, Sci. Total Environ., 533, 317–328,
https://doi.org/10.1016/j.scitotenv.2015.06.124, 2015. a, b
Rothman, L., Gordon, I., Barber, R., Dothe, H., Gamache, R., Goldman, A.,
Perevalov, V., Tashkun, S., and Tennyson, J.: HITEMP, the high-temperature molecular spectroscopic database, J Quant. Spectrosc. Ra., 111, 2139–2150, https://doi.org/10.1016/j.jqsrt.2010.05.001, 2010. a, b
Rothman, L. S., Gordon, I. E., Barbe, A., Benner, D. C., Bernath, P. F., Birk, M., Boudon, V., Brown, L. R., Campargue, A., Champion, J. P., Chance, K., Coudert, L. H., Dana, V., Devi, V. M., Fally, S., Flaud, J. M., Gamache,
R. R., Goldman, A., Jacquemart, D., Kleiner, I., Lacome, N., Lafferty, W. J., Mandin, J. Y., Massie, S. T., Mikhailenko, S. N., Miller, C. E.,
Moazzen-Ahmadi, N., Naumenko, O. V., Nikitin, A., Orphal, J., Perevalov,
V. I., Perrin, A., Predoi-Cross, A., Rinsland, C. P., Rotger, M.,
Šimečkovǎ, M., Smith, M. A. H., Sung, K., Tashkun, S. A.,
Tennyson, J., Toth, R. A., Vandaele, A. C., and Auwera, J. V.: The HITRAN
2008 molecular spectroscopic database, J Quant. Spectrosc. Ra., 110, 533–572, https://doi.org/10.1016/j.jqsrt.2009.02.013, 2009. a
Schröder, M., Lockhoff, M., Fell, F., Forsythe, J., Trent, T., Bennartz, R., Borbas, E., Bosilovich, M. G., Castelli, E., Hersbach, H., Kachi, M., Kobayashi, S., Kursinski, E. R., Loyola, D., Mears, C., Preusker, R., Rossow, W. B., and Saha, S.: The GEWEX Water Vapor Assessment archive of water vapour products from satellite observations and reanalyses, Earth Syst. Sci. Data, 10, 1093–1117, https://doi.org/5194/essd-10-1093-2018, 2018. a, b
Soden, B. J. and Held, I. M.: An assessment of climate feedbacks in coupled
ocean–atmosphere models, J. Climate, 19, 3354–3360,
https://doi.org/10.1175/JCLI3799.1, 2006. a
Soden, B. J., Jackson, D. L., Ramaswamy, V., Schwarzkopf, M. D., and Huang, X.: The radiative signature of upper tropospheric moistening, Science, 310,
841–844, https://doi.org/10.1126/science.1115602, 2005. a
Solomon, S., Schmeltekopf, A. L., and Sanders, R. W.: On the interpretation of zenith sky absorption measurements, J. Geophys. Res.-Atmos., 92, 8311–8319, https://doi.org/10.1029/JD092iD07p08311, 1987. a
Spurr, R.: LIDORT and VLIDORT: Linearized pseudo-spherical scalar and vector
discrete ordinate radiative transfer models for use in remote sensing
retrieval problems, in: Light Scattering Reviews 3, edited by: Kokhanovsky, A.A., Springer Praxis Books, Springer, Berlin, Heidelberg, 229–275, https://doi.org/10.1007/978-3-540-48546-9_7, 2008. a
Stutz, J. and Platt, U.: Numerical analysis and estimation of the statistical
error of differential optical absorption spectroscopy measurements with
least-squares methods, Appl. Optics, 35, 6041–6053,
https://doi.org/10.1364/AO.35.006041, 1996. a
Sütterlin, M., Stöckli, R., Schaaf, C. B., and Wunderle, S.: Albedo
climatology for European land surfaces retrieved from AVHRR data
(1990–2014) and its spatial and temporal analysis from green-up to vegetation
senescence, J. Geophys. Res.-Atmos., 121, 8156–8171,
https://doi.org/10.1002/2016JD024933, 2016. a, b
Thalman, R. and Volkamer, R.: Temperature dependent absorption cross-sections
of O2–O2 collision pairs between 340 and 630 nm and at atmospherically
relevant pressure, Phys. Chem. Chem. Phys., 15, 15371–15381,
https://doi.org/10.1039/C3CP50968K, 2013. a, b
Theys, N., De Smedt, I., Yu, H., Danckaert, T., van Gent, J., Hörmann, C., Wagner, T., Hedelt, P., Bauer, H., Romahn, F., Pedergnana, M., Loyola, D., and Van Roozendael, M.: Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis, Atmos. Meas. Tech., 10, 119–153, https://doi.org/5194/amt-10-119-2017, 2017. a, b
Tilstra, L. G., Tuinder, O. N. E., Wang, P., and Stammes, P.: Surface
reflectivity climatologies from UV to NIR determined from Earth observations by GOME-2 and SCIAMACHY, J. Geophys. Res.-Atmos.,
122, 4084–4111, https://doi.org/10.1002/2016JD025940, 2017. a
Trenberth, K. E. and Stepaniak, D. P.: Covariability of components of poleward
atmospheric energy transports on seasonal and interannual timescales, J. Climate, 16, 3691–3705,
https://doi.org/10.1175/1520-0442(2003)016<3691:COCOPA>2.0.CO;2, 2003. a
Valks, P., Pinardi, G., Richter, A., Lambert, J.-C., Hao, N., Loyola, D., Van Roozendael, M., and Emmadi, S.: Operational total and tropospheric NO2 column retrieval for GOME-2, Atmos. Meas. Tech., 4, 1491–1514, https://doi.org/5194/amt-4-1491-2011, 2011. a
Vandaele, A. C., Hermans, C., Fally, S., Carleer, M., Colin, R., Merienne,
M.-F., Jenouvrier, A., and Coquart, B.: High-resolution Fourier transform
measurement of the NO2 visible and near-infrared absorption cross
sections: temperature and pressure effects, J. Geophys. Res., 107,, 4348, https://doi.org/10.1029/2001JD000971, 2002. a, b
Van Malderen, R., Brenot, H., Pottiaux, E., Beirle, S., Hermans, C., De Mazière, M., Wagner, T., De Backer, H., and Bruyninx, C.: A multi-site intercomparison of integrated water vapour observations for climate change analysis, Atmos. Meas. Tech., 7, 2487–2512, https://doi.org/5194/amt-7-2487-2014, 2014. a, b
Van Roozendael, M., Loyola, D., Spurr, R., Balis, D., Lambert, J.-C.,
Livschitz, Y., Valks, P., Ruppert, T., Kenter, P., Fayt, C., and Zehner, C.: Ten years of GOME/ERS-2 total ozone data – the new GOME data processor (GDP) version 4: 1. Algorithm description, J. Geophys. Res., 111, D14311, https://doi.org/10.1029/2005JD006375, 2006. a
Vaquero-Martínez, J., Antón, M., de Galisteo, J. P. O., Cachorro, V. E.,
Álvarez-Zapatero, P., Román, R., Loyola, D., ao Costa, M. J., Wang, H.,
Abad, G. G., and Noël, S.: Inter-comparison of integrated water vapor
from satellite instruments using reference GPS data at the Iberian
Peninsula, Remote Sens. Environ., 204, 729–740,
https://doi.org/10.1016/j.rse.2017.09.028, 2018.
a, b
Veefkind, J., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G.,
Claas, J., Eskes, H., de Haan, J., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R.,
Kruizinga, B., Vink, R., Visser, H., and Levelt, P.: TROPOMI on the ESA
Sentinel-5 Precursor: a GMES mission for global observations of the
atmospheric composition for climate, air quality and ozone layer
applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012. a
Wagner, T., Beirle, S., Grzegorski, M., and Platt, U.: Global trends
(1996–2003) of total column precipitable water observed by Global Ozone
Monitoring Experiment (GOME) on ERS-2 and their relation to near-surface temperature, J. Geophys. Res., 111, D12102,
https://doi.org/10.1029/2005JD006523, 2006. a
Wagner, T., Beirle, S., Sihler, H., and Mies, K.: A feasibility study for the retrieval of the total column precipitable water vapour from satellite observations in the blue spectral range, Atmos. Meas. Tech., 6, 2593–2605, https://doi.org/5194/amt-6-2593-2013, 2013. a, b, c
Wang, H., Souri, A. H., González Abad, G., Liu, X., and Chance, K.: Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications, Atmos. Meas. Tech., 12, 5183–5199, https://doi.org/5194/amt-12-5183-2019, 2019. a
Wang, J. and Zhang, L.: Systematic errors in global radiosonde precipitable
water data from comparisons with ground-based GPS measurements, J. Climate, 21, 2218–2238, https://doi.org/10.1175/2007JCLI1944.1, 2008. a, b
Wenig, M. O., Cede, A. M., Bucsela, E. J., Celarier, E. A., Boersma, K. F.,
Veefkind, J. P., Brinksma, E. J., Gleason, J. F., and Herman, J. R.:
Validation of OMI tropospheric NO2 column densities using direct-Sun
mode Brewer measurements at NASA Goddard Space Flight Center, J. Geophys. Res., 113, D16S45, https://doi.org/10.1029/2007JD008988, 2008. a
Short summary
The paper presents a new water vapor retrieval algorithm in the blue spectral band for the Global Ozone Monitoring Experience-2 (GOME-2) satellite instruments. The new retrieval features a dynamic a priori optimization module, which makes it less dependent on input from chemistry transport models and better suited for climate studies. As the blue band wavelength is available to various satellites, retrieving water vapor in the blue band potentially extends the water vapor climate record.
The paper presents a new water vapor retrieval algorithm in the blue spectral band for the...