Articles | Volume 17, issue 21
https://doi.org/10.5194/amt-17-6345-2024
© Author(s) 2024. 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-17-6345-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Oct 2024
Research article |
| 30 Oct 2024
| 30 Oct 2024
An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI
Athina Argyrouli
Chair of Remote Sensing Technology, School of Engineering and Design, Technical University of Munich (TUM), Munich, Germany
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
Diego Loyola
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
Fabian Romahn
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
Víctor Molina García
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
Pascal Hedelt
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
Klaus-Peter Heue
German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Wessling, Germany
Richard Siddans
Rutherford Appleton Laboratory (RAL), Chilton OX11 0QX, United Kingdom
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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
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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.
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
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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.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Athina Argyrouli, Ronny Lutz, L. Gijsbert Tilstra, Vincent Huijnen, François Hendrick, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 755–787, https://doi.org/10.5194/amt-13-755-2020, https://doi.org/10.5194/amt-13-755-2020, 2020
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This paper presents an improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations that are
performed with a more accurate knowledge of surface albedo, the a priori NO2 profile, and cloud and aerosol corrections.
Diego G. Loyola, Sebastián Gimeno García, Ronny Lutz, Athina Argyrouli, Fabian Romahn, Robert J. D. Spurr, Mattia Pedergnana, Adrian Doicu, Víctor Molina García, and Olena Schüssler
Atmos. Meas. Tech., 11, 409–427, https://doi.org/10.5194/amt-11-409-2018, https://doi.org/10.5194/amt-11-409-2018, 2018
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In this paper we present the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) mission: OCRA (Optical Cloud Recognition Algorithm) retrieves the cloud fraction using measurements in the UV–VIS spectral regions, and ROCINN (Retrieval of Cloud Information using Neural Networks) retrieves the cloud top height and optical thickness using measurements in and around the oxygen A-band in the NIR.
Sanjeevani Panditharatne, Helen Brindley, Caroline Cox, Rui Song, Richard Siddans, Richard Bantges, Jonathan Murray, Stuart Fox, and Cathryn Fox
EGUsphere, https://doi.org/10.5194/egusphere-2025-647, https://doi.org/10.5194/egusphere-2025-647, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Upwelling radiation with wavelengths between 15 and 100 microns is theorised to be highly sensitive to the properties of ice clouds, particularly the shape of the ice crystals. We exploit this sensitivity and perform the first retrieval of ice cloud properties using these wavelengths from an observation taken on an aircraft and evaluate it against measurements of the cloud’s properties.
Shihan Sun, Paul I. Palmer, Richard Siddans, Brian J. Kerridge, Lucy Ventress, Achim Edtbauer, Akima Ringsdorf, Eva Y. Pfannerstill, and Jonathan Williams
EGUsphere, https://doi.org/10.5194/egusphere-2025-778, https://doi.org/10.5194/egusphere-2025-778, 2025
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Isoprene released by plants can impact atmospheric chemistry and climate. The Amazon rainforest is a major source of isoprene. We derived isoprene emissions using satellite retrievals of isoprene columns and a chemical transport model. We evaluated our isoprene emission estimates using ground-based isoprene observations and satellite retrievals of formaldehyde. We found that using satellite retrievals of isoprene can help better understand isoprene emissions over the Amazon.
Sanjeevani Panditharatne, Helen Brindley, Caroline Cox, Richard Siddans, Jonathan Murray, Laura Warwick, and Stuart Fox
Atmos. Meas. Tech., 18, 717–735, https://doi.org/10.5194/amt-18-717-2025, https://doi.org/10.5194/amt-18-717-2025, 2025
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Observations from the upcoming European Space Agency’s Far-Infrared Outgoing Radiation Understanding and Monitoring (FORUM) satellite are theorised to be highly sensitive to distributions of water vapour within Earth’s atmosphere. We exploit this sensitivity and extend the Infrared Microwave Sounding retrieval scheme for use on observations from FORUM. This scheme is evaluated on both simulated and observed measurements and shows good agreement with references of the atmospheric state.
Melanie Coldewey-Egbers, Diego G. Loyola, Barry Latter, Richard Siddans, Brian Kerridge, Daan Hubert, Michel van Roozendael, and Michael Eisinger
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-196, https://doi.org/10.5194/amt-2024-196, 2025
Preprint under review for AMT
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The 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°x5°. 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 of the profiles using as a reference the GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-3746, https://doi.org/10.5194/egusphere-2024-3746, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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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.
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
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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.
Julia Bruckert, Simran Chopra, Richard Siddans, Charlotte Wedler, and Gholam Ali Hoshyaripour
EGUsphere, https://doi.org/10.5194/egusphere-2024-4062, https://doi.org/10.5194/egusphere-2024-4062, 2025
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The 2022 Hunga eruption emitted about 150 Tg water vapor into the stratosphere. Here, we show that the water vapor injection not only accelerates SO2 oxidation and sulfate production but also increases the aging of ash (coating of ash by sulfate). Our study shows that aerosol aging alone does not explain the rapid loss of ash after the Hunga eruption as observed by satellite instruments. However, some ash might be masked in the observation due to the strong coating.
Carlo Arosio, Viktoria Sofieva, Andrea Orfanoz-Cheuquelaf, Alexei Rozanov, Klaus-Peter Heue, Edward Malina, Ryan M. Stauffer, David Tarasick, Roeland Van Malderen, Jerry R. Ziemke, and Mark Weber
EGUsphere, https://doi.org/10.5194/egusphere-2024-3737, https://doi.org/10.5194/egusphere-2024-3737, 2024
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Tropospheric ozone affects air quality and climate, being a pollutant and a greenhouse gas. We analysed satellite data of tropospheric ozone that combine two types of observations: one providing stratospheric ozone and another measuring total ozone. We compare common climatological features and study the influence of the tropopause (troposphere to stratosphere boundary) on the results. We also examine trends over the last 20 years and compare satellite data with ozonesondes to identify drifts.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-3717, https://doi.org/10.5194/egusphere-2024-3717, 2024
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Tropospheric ozone (O3) is a harmful secondary atmospheric pollutant and an important greenhouse gas. Here, we present an in-depth analysis of lower-tropospheric sub-column O3 (LTCO3, surface – 6 km) records from three satellite products produced by the Rutherford Appleton Laboratory (RAL) over Europe between 1996 and 2017. Overall, we detect moderate negative trends in the satellite records, but corresponding model simulations and ozonesonde measurements show negligible trends.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Chris Wilson, Brian J. Kerridge, Richard Siddans, David P. Moore, Lucy J. Ventress, Emily Dowd, Wuhu Feng, Martyn P. Chipperfield, and John J. Remedios
Atmos. Chem. Phys., 24, 10639–10653, https://doi.org/10.5194/acp-24-10639-2024, https://doi.org/10.5194/acp-24-10639-2024, 2024
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The leaks from the Nord Stream gas pipelines in September 2022 released a large amount of methane (CH4) into the atmosphere. We provide observational data from a satellite instrument that shows a large CH4 plume over the North Sea off the coast of Scandinavia. We use this together with atmospheric models to quantify the CH4 leaked into the atmosphere from the pipelines. We find that 219–427 Gg CH4 was emitted, making this the largest individual fossil-fuel-related CH4 leak on record.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Wuhu Feng, and Martyn P. Chipperfield
EGUsphere, https://doi.org/10.5194/egusphere-2024-2736, https://doi.org/10.5194/egusphere-2024-2736, 2024
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Globally, lockdowns were implemented to limit the spread of COVID-19, leading to a decrease in emissions of key air pollutants. Here, we use novel satellite data and a chemistry model to investigate the impact of the pandemic on tropospheric ozone (O3), a key pollutant, in 2020. Overall, we found substantial decreases of up to 20 %, 2/3s of which came from emission reductions while 1/3 was due to a decrease in the stratospheric ozone flux into the troposphere.
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge
Atmos. Meas. Tech., 17, 5491–5524, https://doi.org/10.5194/amt-17-5491-2024, https://doi.org/10.5194/amt-17-5491-2024, 2024
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The paper discusses two very distinct methane products from the IASI instrument aboard the MetOp-A satellite. One (referred to as LMD NLISv8.3) uses a machine-learning approach, while the other (RALv2.0) uses a more conventional optimal estimation approach. We used a variety of model and independent reference measurement data to assess both products' overall quality, their differences, and specific aspects of each product that would benefit from further analysis by the product development teams.
Audrey Gaudel, Ilann Bourgeois, Meng Li, Kai-Lan Chang, Jerald Ziemke, Bastien Sauvage, Ryan M. Stauffer, Anne M. Thompson, Debra E. Kollonige, Nadia Smith, Daan Hubert, Arno Keppens, Juan Cuesta, Klaus-Peter Heue, Pepijn Veefkind, Kenneth Aikin, Jeff Peischl, Chelsea R. Thompson, Thomas B. Ryerson, Gregory J. Frost, Brian C. McDonald, and Owen R. Cooper
Atmos. Chem. Phys., 24, 9975–10000, https://doi.org/10.5194/acp-24-9975-2024, https://doi.org/10.5194/acp-24-9975-2024, 2024
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The study examines tropical tropospheric ozone changes. In situ data from 1994–2019 display increased ozone, notably over India, Southeast Asia, and Malaysia and Indonesia. Sparse in situ data limit trend detection for the 15-year period. In situ and satellite data, with limited sampling, struggle to consistently detect trends. Continuous observations are vital over the tropical Pacific Ocean, Indian Ocean, western Africa, and South Asia for accurate ozone trend estimation in these regions.
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
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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.
Richard J. Pope, Fiona M. O'Connor, Mohit Dalvi, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Brice Barret, Eric Le Flochmoen, Anne Boynard, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, Catherine Wespes, and Richard Rigby
Atmos. Chem. Phys., 24, 9177–9195, https://doi.org/10.5194/acp-24-9177-2024, https://doi.org/10.5194/acp-24-9177-2024, 2024
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Ozone is a potent air pollutant in the lower troposphere, with adverse impacts on human health. Satellite records of tropospheric ozone currently show large-scale inconsistencies in long-term trends. Our detailed study of the potential factors (e.g. satellite errors, where the satellite can observe ozone) potentially driving these inconsistencies found that, in North America, Europe, and East Asia, the underlying trends are typically small with large uncertainties.
Richard J. Pope, Alexandru Rap, Matilda A. Pimlott, Brice Barret, Eric Le Flochmoen, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Anne Boynard, Christian Retscher, Wuhu Feng, Richard Rigby, Sandip S. Dhomse, Catherine Wespes, and Martyn P. Chipperfield
Atmos. Chem. Phys., 24, 3613–3626, https://doi.org/10.5194/acp-24-3613-2024, https://doi.org/10.5194/acp-24-3613-2024, 2024
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Tropospheric ozone is an important short-lived climate forcer which influences the incoming solar short-wave radiation and the outgoing long-wave radiation in the atmosphere (8–15 km) where the balance between the two yields a net positive (i.e. warming) effect at the surface. Overall, we find that the tropospheric ozone radiative effect ranges between 1.21 and 1.26 W m−2 with a negligible trend (2008–2017), suggesting that tropospheric ozone influences on climate have remained stable with time.
Richard J. Pope, Brian J. Kerridge, Richard Siddans, Barry G. Latter, Martyn P. Chipperfield, Wuhu Feng, Matilda A. Pimlott, Sandip S. Dhomse, Christian Retscher, and Richard Rigby
Atmos. Chem. Phys., 23, 14933–14947, https://doi.org/10.5194/acp-23-14933-2023, https://doi.org/10.5194/acp-23-14933-2023, 2023
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Ozone is a potent air pollutant, and we present the first study to investigate long-term changes in lower tropospheric column ozone (LTCO3) from space. We have constructed a merged LTCO3 dataset from GOME-1, SCIAMACHY and OMI between 1996 and 2017. Comparing LTCO3 between the 1996–2000 and 2013–2017 5-year averages, we find significant positive increases in the tropics/sub-tropics, while in the northern mid-latitudes, we find small-scale differences.
Elisa Carboni, Gareth E. Thomas, Richard Siddans, and Brian Kerridge
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-232, https://doi.org/10.5194/amt-2023-232, 2023
Revised manuscript not accepted
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We analyzed different satellite datasets of cloud properties with a new approach to quantify and interpret their interannual variability based on singular vector decomposition (SVD). The spatial pattern and its temporal evolution are strikingly similar for all the satellite datasets and follow the El Nino Southern Oscillation. The SVD approach reported here has potential for application to satellite data sets and to evaluate consistency between models and observations.
Richard J. Pope, Brian J. Kerridge, Martyn P. Chipperfield, Richard Siddans, Barry G. Latter, Lucy J. Ventress, Matilda A. Pimlott, Wuhu Feng, Edward Comyn-Platt, Garry D. Hayman, Stephen R. Arnold, and Ailish M. Graham
Atmos. Chem. Phys., 23, 13235–13253, https://doi.org/10.5194/acp-23-13235-2023, https://doi.org/10.5194/acp-23-13235-2023, 2023
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In the summer of 2018, Europe experienced several persistent large-scale ozone (O3) pollution episodes. Satellite tropospheric O3 and surface O3 data recorded substantial enhancements in 2018 relative to other years. Targeted model simulations showed that meteorological processes and emissions controlled the elevated surface O3, while mid-tropospheric O3 enhancements were dominated by stratospheric O3 intrusion and advection of North Atlantic O3-rich air masses into Europe.
Maria Rosa Russo, Brian John Kerridge, Nathan Luke Abraham, James Keeble, Barry Graham Latter, Richard Siddans, James Weber, Paul Thomas Griffiths, John Adrian Pyle, and Alexander Thomas Archibald
Atmos. Chem. Phys., 23, 6169–6196, https://doi.org/10.5194/acp-23-6169-2023, https://doi.org/10.5194/acp-23-6169-2023, 2023
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Tropospheric ozone is an important component of the Earth system as it can affect both climate and air quality. In this work we use observed tropospheric ozone derived from satellite observations and compare it to tropospheric ozone from model simulations. Our aim is to investigate recent changes (2005–2018) in tropospheric ozone in the North Atlantic region and to understand what factors are driving such changes.
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
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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.
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
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Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
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
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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.
Bernard Legras, Clair Duchamp, Pasquale Sellitto, Aurélien Podglajen, Elisa Carboni, Richard Siddans, Jens-Uwe Grooß, Sergey Khaykin, and Felix Ploeger
Atmos. Chem. Phys., 22, 14957–14970, https://doi.org/10.5194/acp-22-14957-2022, https://doi.org/10.5194/acp-22-14957-2022, 2022
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The long-duration atmospheric impact of the Tonga eruption in January 2022 is a plume of water and sulfate aerosols in the stratosphere that persisted for more than 6 months. We study this evolution using several satellite instruments and analyse the unusual behaviour of this plume as sulfates and water first moved down rapidly and then separated into two layers. We also report the self-organization in compact and long-lived patches.
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
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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
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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.
Matilda A. Pimlott, Richard J. Pope, Brian J. Kerridge, Barry G. Latter, Diane S. Knappett, Dwayne E. Heard, Lucy J. Ventress, Richard Siddans, Wuhu Feng, and Martyn P. Chipperfield
Atmos. Chem. Phys., 22, 10467–10488, https://doi.org/10.5194/acp-22-10467-2022, https://doi.org/10.5194/acp-22-10467-2022, 2022
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We present a new method to derive global information of the hydroxyl radical (OH), an important atmospheric oxidant. OH controls the lifetime of trace gases important to air quality and climate. We use satellite observations of ozone, carbon monoxide, methane and water vapour in a simple expression to derive OH around 3–4 km altitude. The derived OH compares well to model and aircraft OH data. We then apply the method to 10 years of satellite data to study the inter-annual variability of OH.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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
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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
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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
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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
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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.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
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The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
Isabelle De Smedt, Gaia Pinardi, Corinne Vigouroux, Steven Compernolle, Alkis Bais, Nuria Benavent, Folkert Boersma, Ka-Lok Chan, Sebastian Donner, Kai-Uwe Eichmann, Pascal Hedelt, François Hendrick, Hitoshi Irie, Vinod Kumar, Jean-Christopher Lambert, Bavo Langerock, Christophe Lerot, Cheng Liu, Diego Loyola, Ankie Piters, Andreas Richter, Claudia Rivera Cárdenas, Fabian Romahn, Robert George Ryan, Vinayak Sinha, Nicolas Theys, Jonas Vlietinck, Thomas Wagner, Ting Wang, Huan Yu, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 12561–12593, https://doi.org/10.5194/acp-21-12561-2021, https://doi.org/10.5194/acp-21-12561-2021, 2021
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This paper assess the performances of the TROPOMI formaldehyde observations compared to its predecessor OMI at different spatial and temporal scales. We also use a global network of MAX-DOAS instruments to validate both satellite datasets for a large range of HCHO columns. The precision obtained with daily TROPOMI observations is comparable to monthly OMI observations. We present clear detection of weak HCHO column enhancements related to shipping emissions in the Indian Ocean.
Nikita M. Fedkin, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr
Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, https://doi.org/10.5194/amt-14-3673-2021, 2021
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This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.
Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola
Atmos. Meas. Tech., 14, 2993–3002, https://doi.org/10.5194/amt-14-2993-2021, https://doi.org/10.5194/amt-14-2993-2021, 2021
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Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Margaret R. Marvin, Paul I. Palmer, Barry G. Latter, Richard Siddans, Brian J. Kerridge, Mohd Talib Latif, and Md Firoz Khan
Atmos. Chem. Phys., 21, 1917–1935, https://doi.org/10.5194/acp-21-1917-2021, https://doi.org/10.5194/acp-21-1917-2021, 2021
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We use an atmospheric chemistry model in combination with satellite and surface observations to investigate how biomass burning affects tropospheric ozone over Southeast Asia during its fire seasons. We find that nitrogen oxides from biomass burning were responsible for about 30 % of the regional ozone formation potential, and we estimate that ozone from biomass burning caused more than 400 excess premature deaths in Southeast Asia during the peak burning months of March and September 2014.
Martin Dameris, Diego G. Loyola, Matthias Nützel, Melanie Coldewey-Egbers, Christophe Lerot, Fabian Romahn, and Michel van Roozendael
Atmos. Chem. Phys., 21, 617–633, https://doi.org/10.5194/acp-21-617-2021, https://doi.org/10.5194/acp-21-617-2021, 2021
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Record low ozone values were observed in March 2020. Dynamical and chemical circumstances leading to low ozone values in spring 2020 are discussed and are compared to similar dynamical conditions in the Northern Hemisphere in 1996/1997 and 2010/2011. 2019/2020 showed an unusual persistent polar vortex with low stratospheric temperatures, which were permanently below 195 K at 50 hPa. This enabled enhanced formation of polar stratospheric clouds and a subsequent clear reduction of total ozone.
Omar Torres, Hiren Jethva, Changwoo Ahn, Glen Jaross, and Diego G. Loyola
Atmos. Meas. Tech., 13, 6789–6806, https://doi.org/10.5194/amt-13-6789-2020, https://doi.org/10.5194/amt-13-6789-2020, 2020
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TROPOMI measures the quantity of small suspended particles (aerosols). We describe initial results of aerosol measurements using a NASA algorithm that retrieves the UV aerosol index, aerosol optical depth, and single-scattering albedo. An evaluation of derived products using sun-photometer observations shows close agreement. We also use these results to discuss important biomass burning and wildfire events around the world that got the attention of scientists and news media alike.
Ka Lok Chan, Pieter Valks, Sander Slijkhuis, Claas Köhler, and Diego Loyola
Atmos. Meas. Tech., 13, 4169–4193, https://doi.org/10.5194/amt-13-4169-2020, https://doi.org/10.5194/amt-13-4169-2020, 2020
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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.
Corinne Vigouroux, Bavo Langerock, Carlos Augusto Bauer Aquino, Thomas Blumenstock, Zhibin Cheng, Martine De Mazière, Isabelle De Smedt, Michel Grutter, James W. Hannigan, Nicholas Jones, Rigel Kivi, Diego Loyola, Erik Lutsch, Emmanuel Mahieu, Maria Makarova, Jean-Marc Metzger, Isamu Morino, Isao Murata, Tomoo Nagahama, Justus Notholt, Ivan Ortega, Mathias Palm, Gaia Pinardi, Amelie Röhling, Dan Smale, Wolfgang Stremme, Kim Strong, Ralf Sussmann, Yao Té, Michel van Roozendael, Pucai Wang, and Holger Winkler
Atmos. Meas. Tech., 13, 3751–3767, https://doi.org/10.5194/amt-13-3751-2020, https://doi.org/10.5194/amt-13-3751-2020, 2020
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We validate the TROPOMI HCHO product with ground-based FTIR (Fourier-transform infrared) measurements from 25 stations. We find that TROPOMI overestimates HCHO under clean conditions, while it underestimates it at high HCHO levels. Both TROPOMI precision and accuracy reach the pre-launch requirements, and its precision can even be 2 times better. The observed TROPOMI seasonal variability is in agreement with the FTIR data. The TROPOMI random uncertainty and data filtering should be refined.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nicolas Theys, Diego G. Loyola, Pascal Hedelt, Nickolay A. Krotkov, and Can Li
Atmos. Chem. Phys., 20, 5591–5607, https://doi.org/10.5194/acp-20-5591-2020, https://doi.org/10.5194/acp-20-5591-2020, 2020
Zhuoru Wang, Ka Lok Chan, Klaus-Peter Heue, Adrian Doicu, Thomas Wagner, Robert Holla, and Matthias Wiegner
Atmos. Meas. Tech., 13, 1835–1866, https://doi.org/10.5194/amt-13-1835-2020, https://doi.org/10.5194/amt-13-1835-2020, 2020
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We present a new aerosol profile retrieval algorithm for MAX-DOAS measurements at high-altitude sites and applied to the MAX-DOAS measurements at UFS. The retrieval algorithm is based on a O4 DSCD lookup table which is dedicated to high-altitude MAX-DOAS measurements. The comparison of retrieved aerosol optical depths (AODs) to sun photometer observations shows good agreement with a correlation coefficient (R) of 0.733 and 0.798 at 360 and 477 nm, respectively.
Melanie Coldewey-Egbers, Diego G. Loyola, Gordon Labow, and Stacey M. Frith
Atmos. Meas. Tech., 13, 1633–1654, https://doi.org/10.5194/amt-13-1633-2020, https://doi.org/10.5194/amt-13-1633-2020, 2020
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We compare total ozone columns from the satellite-based GOME-type Total Ozone Essential Climate Variable record and the adjusted Modern Era Retrospective Analysis for Research and Applications version 2 reanalysis during their overlap period from 1995 to 2018. Ozone columns and anomalies show a very good agreement in terms of spatial and temporal patterns. In the tropics the interannual variability is assessed by means of an EOF analysis and both data records show a remarkable consistency.
Diego G. Loyola, Jian Xu, Klaus-Peter Heue, and Walter Zimmer
Atmos. Meas. Tech., 13, 985–999, https://doi.org/10.5194/amt-13-985-2020, https://doi.org/10.5194/amt-13-985-2020, 2020
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In this paper we present a novel algorithm for the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) from UVN sensors based on the full-physics inverse learning machine (FP_ILM) retrieval.
The GE_LER retrieval is optimized for the trace gas retrievals using the DOAS technique and the large amount of data of TROPOMI on board the EU/ESA Sentinel-5 Precursor mission.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Athina Argyrouli, Ronny Lutz, L. Gijsbert Tilstra, Vincent Huijnen, François Hendrick, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 755–787, https://doi.org/10.5194/amt-13-755-2020, https://doi.org/10.5194/amt-13-755-2020, 2020
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This paper presents an improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations that are
performed with a more accurate knowledge of surface albedo, the a priori NO2 profile, and cloud and aerosol corrections.
Pascal Hedelt, Dmitry S. Efremenko, Diego G. Loyola, Robert Spurr, and Lieven Clarisse
Atmos. Meas. Tech., 12, 5503–5517, https://doi.org/10.5194/amt-12-5503-2019, https://doi.org/10.5194/amt-12-5503-2019, 2019
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Sulfur dioxide (SO2) emitted during volcanic eruptions poses not only a major threat to local populations, air quality, and aviation but also has an impact on the climate. The satellite-based detection of the SO2 plume is easy; however, it requires exact knowledge of the SO2 layer height. This paper presents a new method for the extremely fast and accurate determination of the layer height, which is essential in volcanic plume forecasts and the exact determination of the SO2 density.
Pasquale Sellitto, Henda Guermazi, Elisa Carboni, Richard Siddans, and Mike Burton
Atmos. Meas. Tech., 12, 5381–5389, https://doi.org/10.5194/amt-12-5381-2019, https://doi.org/10.5194/amt-12-5381-2019, 2019
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Volcanoes release complex plumes of gas and particles. Volcanic gases, like SO2, can additionally condense, once released, to form particles, sulphate aerosol (SA). Observing simultaneously SO2+SA is important: their proportion provides information on the internal state of volcanoes, and can be used to predict plumes' atmospheric evolution and their environmental and climatic impacts. We developed a new method to observe simultaneously, for the first time, SO2+SA using infrared remote sensing.
Katerina Garane, Maria-Elissavet Koukouli, Tijl Verhoelst, Christophe Lerot, Klaus-Peter Heue, Vitali Fioletov, Dimitrios Balis, Alkiviadis Bais, Ariane Bazureau, Angelika Dehn, Florence Goutail, Jose Granville, Debora Griffin, Daan Hubert, Arno Keppens, Jean-Christopher Lambert, Diego Loyola, Chris McLinden, Andrea Pazmino, Jean-Pierre Pommereau, Alberto Redondas, Fabian Romahn, Pieter Valks, Michel Van Roozendael, Jian Xu, Claus Zehner, Christos Zerefos, and Walter Zimmer
Atmos. Meas. Tech., 12, 5263–5287, https://doi.org/10.5194/amt-12-5263-2019, https://doi.org/10.5194/amt-12-5263-2019, 2019
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The Sentinel-5 Precursor TROPOMI near real time (NRTI) and offline (OFFL) total ozone column (TOC) products are validated against direct-sun and twilight zenith-sky ground-based TOC measurements and other already known spaceborne sensors. The results show that the TROPOMI TOC measurements are in very good agreement with the ground-based measurements and satellite sensor measurements and that they are well within the product requirements.
Ka Lok Chan, Zhuoru Wang, Aijun Ding, Klaus-Peter Heue, Yicheng Shen, Jing Wang, Feng Zhang, Yining Shi, Nan Hao, and Mark Wenig
Atmos. Chem. Phys., 19, 10051–10071, https://doi.org/10.5194/acp-19-10051-2019, https://doi.org/10.5194/acp-19-10051-2019, 2019
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The paper presents long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a MAX-DOAS instrument. The measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO are used to validate OMI satellite observations and to investigate the influences of region transport of air pollutants on the air quality in Nanjing.
Matthew J. Rowlinson, Alexandru Rap, Stephen R. Arnold, Richard J. Pope, Martyn P. Chipperfield, Joe McNorton, Piers Forster, Hamish Gordon, Kirsty J. Pringle, Wuhu Feng, Brian J. Kerridge, Barry L. Latter, and Richard Siddans
Atmos. Chem. Phys., 19, 8669–8686, https://doi.org/10.5194/acp-19-8669-2019, https://doi.org/10.5194/acp-19-8669-2019, 2019
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Wildfires and meteorology have a substantial effect on atmospheric concentrations of greenhouse gases such as methane and ozone. During the 1997 El Niño event, unusually large fire emissions indirectly increased global methane through carbon monoxide emission, which decreased the oxidation capacity of the atmosphere. There were also large regional changes to tropospheric ozone concentrations, but contrasting effects of fire and meteorology resulted in a small change to global radiative forcing.
Antje Inness, Johannes Flemming, Klaus-Peter Heue, Christophe Lerot, Diego Loyola, Roberto Ribas, Pieter Valks, Michel van Roozendael, Jian Xu, and Walter Zimmer
Atmos. Chem. Phys., 19, 3939–3962, https://doi.org/10.5194/acp-19-3939-2019, https://doi.org/10.5194/acp-19-3939-2019, 2019
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This paper documents the use of total column ozone data from the TROPOMI satellite in the global forecasting system of the Copernicus Atmosphere Monitoring Service (CAMS). The data are of good quality over large parts of the globe but have some issues at high latitudes, at low solar elevations and over snow/ice. Assimilating the data in the CAMS system has a small positive impact, especially in the tropical troposphere.
Kostas Eleftheratos, Christos S. Zerefos, Dimitris S. Balis, Maria-Elissavet Koukouli, John Kapsomenakis, Diego G. Loyola, Pieter Valks, Melanie Coldewey-Egbers, Christophe Lerot, Stacey M. Frith, Amund S. Haslerud, Ivar S. A. Isaksen, and Seppo Hassinen
Atmos. Meas. Tech., 12, 987–1011, https://doi.org/10.5194/amt-12-987-2019, https://doi.org/10.5194/amt-12-987-2019, 2019
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We examine the ability of GOME-2A total ozone data to capture variability related to known natural oscillations, such as the QBO, ENSO and NAO, with respect to other satellite datasets, ground-based data, and chemical transport model simulations. The analysis is based on the GOME-2 satellite total ozone columns for the period 2007–2016 which form part of the operational EUMETSAT AC SAF GOME-2 MetOp A GDP4.8 latest data product.
Melanie Coldewey-Egbers, Sander Slijkhuis, Bernd Aberle, Diego Loyola, and Angelika Dehn
Atmos. Meas. Tech., 11, 5237–5259, https://doi.org/10.5194/amt-11-5237-2018, https://doi.org/10.5194/amt-11-5237-2018, 2018
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We present a detailed analysis of the long-term performance of the Global Ozone Monitoring Experiment (GOME) on-board ERS-2, which provided measurements of atmospheric constituents for the 16-year period from 1995 to 2011. By means of various in-flight calibration parameters, we monitor the behavior and stability during the entire mission. Furthermore, we introduce the new homogenized level 1 product generated using the recently developed GOME Data Processor Version 5.1.
Anne Boynard, Daniel Hurtmans, Katerina Garane, Florence Goutail, Juliette Hadji-Lazaro, Maria Elissavet Koukouli, Catherine Wespes, Corinne Vigouroux, Arno Keppens, Jean-Pierre Pommereau, Andrea Pazmino, Dimitris Balis, Diego Loyola, Pieter Valks, Ralf Sussmann, Dan Smale, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 11, 5125–5152, https://doi.org/10.5194/amt-11-5125-2018, https://doi.org/10.5194/amt-11-5125-2018, 2018
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In this paper, we perform a comprehensive validation of the IASI/Metop ozone data using independent observations (satellite, ground-based and ozonesonde). The quality of the IASI total and tropospheric ozone columns in terms of bias and long-term stability is generally good. Compared with ozonesonde data, IASI overestimates (underestimates) the ozone abundance in the stratosphere (troposphere). A negative drift in tropospheric ozone is observed, which is not well understood at this point.
Paul I. Palmer, Simon O'Doherty, Grant Allen, Keith Bower, Hartmut Bösch, Martyn P. Chipperfield, Sarah Connors, Sandip Dhomse, Liang Feng, Douglas P. Finch, Martin W. Gallagher, Emanuel Gloor, Siegfried Gonzi, Neil R. P. Harris, Carole Helfter, Neil Humpage, Brian Kerridge, Diane Knappett, Roderic L. Jones, Michael Le Breton, Mark F. Lunt, Alistair J. Manning, Stephan Matthiesen, Jennifer B. A. Muller, Neil Mullinger, Eiko Nemitz, Sebastian O'Shea, Robert J. Parker, Carl J. Percival, Joseph Pitt, Stuart N. Riddick, Matthew Rigby, Harjinder Sembhi, Richard Siddans, Robert L. Skelton, Paul Smith, Hannah Sonderfeld, Kieran Stanley, Ann R. Stavert, Angelina Wenger, Emily White, Christopher Wilson, and Dickon Young
Atmos. Chem. Phys., 18, 11753–11777, https://doi.org/10.5194/acp-18-11753-2018, https://doi.org/10.5194/acp-18-11753-2018, 2018
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This paper provides an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) experiment. GAUGE was designed to quantify nationwide GHG emissions of the UK, bringing together measurements and atmospheric transport models. This novel experiment is the first of its kind. We anticipate it will inform the blueprint for countries that are building a measurement infrastructure in preparation for global stocktakes, which are a key part of the Paris Agreement.
Elpida Leventidou, Mark Weber, Kai-Uwe Eichmann, John P. Burrows, Klaus-Peter Heue, Anne M. Thompson, and Bryan J. Johnson
Atmos. Chem. Phys., 18, 9189–9205, https://doi.org/10.5194/acp-18-9189-2018, https://doi.org/10.5194/acp-18-9189-2018, 2018
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Three individual tropical tropospheric ozone (TTCO) datasets (1996–2015) retrieved with the convective-cloud differential method (Leventidou et al., 2016) have been harmonised in order to study the global and regional TTCO trends. The trends range between −4 to 4 DU per decade testing six different merging scenarios. No trend has been found for the global tropics using the preferred scenario. It is concluded that harmonisation is one of the major sources of uncertainty in the trend estimates.
Arno Keppens, Jean-Christopher Lambert, José Granville, Daan Hubert, Tijl Verhoelst, Steven Compernolle, Barry Latter, Brian Kerridge, Richard Siddans, Anne Boynard, Juliette Hadji-Lazaro, Cathy Clerbaux, Catherine Wespes, Daniel R. Hurtmans, Pierre-François Coheur, Jacob C. A. van Peet, Ronald J van der A, Katerina Garane, Maria Elissavet Koukouli, Dimitris S. Balis, Andy Delcloo, Rigel Kivi, Réné Stübi, Sophie Godin-Beekmann, Michel Van Roozendael, and Claus Zehner
Atmos. Meas. Tech., 11, 3769–3800, https://doi.org/10.5194/amt-11-3769-2018, https://doi.org/10.5194/amt-11-3769-2018, 2018
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This work, performed at the Royal Belgian Institute for Space Aeronomy and the second in a series of four Ozone_cci papers, reports for the first time on data content studies, information content studies, and comparisons with co-located ground-based reference observations for all 13 nadir ozone profile data products that are part of the Climate Research Data Package (CRDP) on atmospheric ozone of the European Space Agency's Climate Change Initiative.
Richard J. Pope, Martyn P. Chipperfield, Stephen R. Arnold, Norbert Glatthor, Wuhu Feng, Sandip S. Dhomse, Brian J. Kerridge, Barry G. Latter, and Richard Siddans
Atmos. Chem. Phys., 18, 8389–8408, https://doi.org/10.5194/acp-18-8389-2018, https://doi.org/10.5194/acp-18-8389-2018, 2018
Marc Schröder, Maarit Lockhoff, Frank Fell, John Forsythe, Tim Trent, Ralf Bennartz, Eva Borbas, Michael G. Bosilovich, Elisa Castelli, Hans Hersbach, Misako Kachi, Shinya Kobayashi, E. Robert Kursinski, Diego Loyola, Carl Mears, Rene Preusker, William B. Rossow, and Suranjana Saha
Earth Syst. Sci. Data, 10, 1093–1117, https://doi.org/10.5194/essd-10-1093-2018, https://doi.org/10.5194/essd-10-1093-2018, 2018
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This publication presents results achieved within the GEWEX Water Vapor Assessment (G-VAP). An overview of available water vapour data records based on satellite observations and reanalysis is given. If a minimum temporal coverage of 10 years is applied, 22 data records remain. These form the G-VAP data archive, which contains total column water vapour, specific humidity profiles and temperature profiles. The G-VAP data archive is designed to ease intercomparison and climate model evaluation.
Stephen Broccardo, Klaus-Peter Heue, David Walter, Christian Meyer, Alexander Kokhanovsky, Ronald van der A, Stuart Piketh, Kristy Langerman, and Ulrich Platt
Atmos. Meas. Tech., 11, 2797–2819, https://doi.org/10.5194/amt-11-2797-2018, https://doi.org/10.5194/amt-11-2797-2018, 2018
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Measurements of nitrogen dioxide, known to originate from industrial and automotive combustion sources, have been made from space for two decades. Successive generations of instrument bring improvements in ground-pixel resolution; however features in the atmosphere are known to be smaller than what the satellites can resolve. Measurements of urban and industrial areas using a high-resolution airborne instrument allow the impact of the satellite's relatively low resolution to be evaluated.
J. Xu, K.-P. Heue, M. Coldewey-Egbers, F. Romahn, A. Doicu, and D. Loyola
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1995–1998, https://doi.org/10.5194/isprs-archives-XLII-3-1995-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1995-2018, 2018
Isabelle De Smedt, Nicolas Theys, Huan Yu, Thomas Danckaert, Christophe Lerot, Steven Compernolle, Michel Van Roozendael, Andreas Richter, Andreas Hilboll, Enno Peters, Mattia Pedergnana, Diego Loyola, Steffen Beirle, Thomas Wagner, Henk Eskes, Jos van Geffen, Klaas Folkert Boersma, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 2395–2426, https://doi.org/10.5194/amt-11-2395-2018, https://doi.org/10.5194/amt-11-2395-2018, 2018
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This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the TROPOMI/Sentinel-5 Precursor operational processor, and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted.
Steffen Beirle, Johannes Lampel, Yang Wang, Kornelia Mies, Steffen Dörner, Margherita Grossi, Diego Loyola, Angelika Dehn, Anja Danielczok, Marc Schröder, and Thomas Wagner
Earth Syst. Sci. Data, 10, 449–468, https://doi.org/10.5194/essd-10-449-2018, https://doi.org/10.5194/essd-10-449-2018, 2018
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We present time series of the global distribution of water vapor over more than 2 decades based on satellite measurements from different sensors. A particular focus is the consistency amongst the different sensors to avoid jumps from one instrument to another. This is reached by applying robust and simple retrieval settings consistently. The resulting
Climateproduct allows the study of the temporal evolution of water vapor over the last 20 years on a global scale.
Katerina Garane, Christophe Lerot, Melanie Coldewey-Egbers, Tijl Verhoelst, Maria Elissavet Koukouli, Irene Zyrichidou, Dimitris S. Balis, Thomas Danckaert, Florence Goutail, Jose Granville, Daan Hubert, Arno Keppens, Jean-Christopher Lambert, Diego Loyola, Jean-Pierre Pommereau, Michel Van Roozendael, and Claus Zehner
Atmos. Meas. Tech., 11, 1385–1402, https://doi.org/10.5194/amt-11-1385-2018, https://doi.org/10.5194/amt-11-1385-2018, 2018
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The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a level-3 data record, which combines individual sensor products into one single cohesive record covering the 22-year period from 1995 to 2017, generated in the frame of the European Space Agency's Climate Change Initiative Phase II. The exceptional quality of the level-3 GTO-ECV v3 TOC record temporal stability satisfies well the requirements for the total ozone measurement decadal stability of between 1 and 3 %.
Mark Weber, Melanie Coldewey-Egbers, Vitali E. Fioletov, Stacey M. Frith, Jeannette D. Wild, John P. Burrows, Craig S. Long, and Diego Loyola
Atmos. Chem. Phys., 18, 2097–2117, https://doi.org/10.5194/acp-18-2097-2018, https://doi.org/10.5194/acp-18-2097-2018, 2018
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This paper commemorates the 30-year anniversary of the initial signing of the Montreal Protocol (MP) on substances that deplete the ozone layer. The MP is so far successful in reducing ozone-depleting substances, and total ozone decline was successfully stopped by the late 1990s. Total ozone levels have been mostly stable since then. In some regions, barely significant upward trends are observed that suggest an emergence into the expected ozone recovery phase.
Diego G. Loyola, Sebastián Gimeno García, Ronny Lutz, Athina Argyrouli, Fabian Romahn, Robert J. D. Spurr, Mattia Pedergnana, Adrian Doicu, Víctor Molina García, and Olena Schüssler
Atmos. Meas. Tech., 11, 409–427, https://doi.org/10.5194/amt-11-409-2018, https://doi.org/10.5194/amt-11-409-2018, 2018
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In this paper we present the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) mission: OCRA (Optical Cloud Recognition Algorithm) retrieves the cloud fraction using measurements in the UV–VIS spectral regions, and ROCINN (Retrieval of Cloud Information using Neural Networks) retrieves the cloud top height and optical thickness using measurements in and around the oxygen A-band in the NIR.
Richard Siddans, Diane Knappett, Brian Kerridge, Alison Waterfall, Jane Hurley, Barry Latter, Hartmut Boesch, and Robert Parker
Atmos. Meas. Tech., 10, 4135–4164, https://doi.org/10.5194/amt-10-4135-2017, https://doi.org/10.5194/amt-10-4135-2017, 2017
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This paper describes an algorithm to infer the global atmospheric distribution of the greenhouse gas methane, from measurements made by the infrared, nadir-viewing spectrometer IASI, on board the MetOp polar orbiting satellites. The algorithm has been applied to 9 years of data. Results are presented and validated by comparison to independent measurements.
Sarah A. Monks, Stephen R. Arnold, Michael J. Hollaway, Richard J. Pope, Chris Wilson, Wuhu Feng, Kathryn M. Emmerson, Brian J. Kerridge, Barry L. Latter, Georgina M. Miles, Richard Siddans, and Martyn P. Chipperfield
Geosci. Model Dev., 10, 3025–3057, https://doi.org/10.5194/gmd-10-3025-2017, https://doi.org/10.5194/gmd-10-3025-2017, 2017
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The TOMCAT chemical transport model has been updated with the chemical degradation of ethene, propene, toluene, butane and monoterpenes. The tropospheric chemical mechanism is documented and the model is evaluated against surface, balloon, aircraft and satellite data. The model is generally able to capture the main spatial and seasonal features of carbon monoxide, ozone, volatile organic compounds and reactive nitrogen. However,
some model biases are found that require further investigation.
Georgina M. Miles, Richard Siddans, Roy G. Grainger, Alfred J. Prata, Bradford Fisher, and Nickolay Krotkov
Atmos. Meas. Tech., 10, 2687–2702, https://doi.org/10.5194/amt-10-2687-2017, https://doi.org/10.5194/amt-10-2687-2017, 2017
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Volcanic eruptions are important in the way they perturb the climate and help us understand atmospheric processes. We show a new method to measure the SO2 released by explosive volcanic eruptions using the HIRS/2 satellite instrument, which measured atmospheric temperature and H2O. We apply the technique to the 1991 eruption of Cerro Hudson and show it is possible to detect SO2 with a good degree of accuracy. This method and instrument can potentially generate a climate-significant record.
Nicolas Theys, Isabelle De Smedt, Huan Yu, Thomas Danckaert, Jeroen van Gent, Christoph Hörmann, Thomas Wagner, Pascal Hedelt, Heiko Bauer, Fabian Romahn, Mattia Pedergnana, Diego Loyola, and Michel Van Roozendael
Atmos. Meas. Tech., 10, 119–153, https://doi.org/10.5194/amt-10-119-2017, https://doi.org/10.5194/amt-10-119-2017, 2017
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This paper provides a thorough description of the algorithm to retrieve SO2 columns from TROPOMI/Sentinel-5 Precursor measurements. The different algorithmic steps including error analysis are detailed. Scientific verification of the algorithm and validation needs are also discussed.
Klaus-Peter Heue, Melanie Coldewey-Egbers, Andy Delcloo, Christophe Lerot, Diego Loyola, Pieter Valks, and Michel van Roozendael
Atmos. Meas. Tech., 9, 5037–5051, https://doi.org/10.5194/amt-9-5037-2016, https://doi.org/10.5194/amt-9-5037-2016, 2016
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The tropical tropospheric column ozone (TCO) from 5 GOME-type satellite instruments were harmonised to get a consistent time series of tropospheric ozone for 20 years. The time series showed a global ozone trend below 10 km of 0.7 DU per decade. Also the regional trends were analysed and trends up to 1.8 DU per decade or decreases as low as 0.8 DU per decade were observed. The TCO will be part of the operation product for Tropomi/S5P and thereby extended for at least 7 years.
Anne Boynard, Daniel Hurtmans, Mariliza E. Koukouli, Florence Goutail, Jérôme Bureau, Sarah Safieddine, Christophe Lerot, Juliette Hadji-Lazaro, Catherine Wespes, Jean-Pierre Pommereau, Andrea Pazmino, Irene Zyrichidou, Dimitris Balis, Alain Barbe, Semen N. Mikhailenko, Diego Loyola, Pieter Valks, Michel Van Roozendael, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 9, 4327–4353, https://doi.org/10.5194/amt-9-4327-2016, https://doi.org/10.5194/amt-9-4327-2016, 2016
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Seven years of O3 observations retrieved from IASI/MetOp satellite instruments are validated with independent data (UV satellite and ground-based data along with ozonesonde profiles). Overall IASI overestimates the total ozone columns (TOC) by 2–7 % depending on the latitude. The assessment of an updated version of the IASI O3 retrieval sofware shows a correction of ~ 4 % in the IASI TOC product, bringing the overall global bias with UV ground-based and satellite data to ~ 1–2 % on average.
Ronny Lutz, Diego Loyola, Sebastián Gimeno García, and Fabian Romahn
Atmos. Meas. Tech., 9, 2357–2379, https://doi.org/10.5194/amt-9-2357-2016, https://doi.org/10.5194/amt-9-2357-2016, 2016
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This paper presents a method for determining global cloud cover by analyzing satellite data. Knowledge of cloud coverage is not only important for climate studies but also provides valuable information in the monitoring of atmospheric trace gases. The research presented here is embedded in an operational chain, which allows us to derive the cloud-cover information in near real time, i.e., only hours after sensing by the satellite.
S. Hassinen, D. Balis, H. Bauer, M. Begoin, A. Delcloo, K. Eleftheratos, S. Gimeno Garcia, J. Granville, M. Grossi, N. Hao, P. Hedelt, F. Hendrick, M. Hess, K.-P. Heue, J. Hovila, H. Jønch-Sørensen, N. Kalakoski, A. Kauppi, S. Kiemle, L. Kins, M. E. Koukouli, J. Kujanpää, J.-C. Lambert, R. Lang, C. Lerot, D. Loyola, M. Pedergnana, G. Pinardi, F. Romahn, M. van Roozendael, R. Lutz, I. De Smedt, P. Stammes, W. Steinbrecht, J. Tamminen, N. Theys, L. G. Tilstra, O. N. E. Tuinder, P. Valks, C. Zerefos, W. Zimmer, and I. Zyrichidou
Atmos. Meas. Tech., 9, 383–407, https://doi.org/10.5194/amt-9-383-2016, https://doi.org/10.5194/amt-9-383-2016, 2016
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The three GOME-2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007–2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. The GOME-2 products (ozone, trace gases, aerosols and UV radiation) are important for ozone chemistry, air quality studies, climate modeling, policy monitoring and hazard warnings. The processing and dissemination is done by EUMETSAT O3M SAF project.
M. Coldewey-Egbers, D. G. Loyola, M. Koukouli, D. Balis, J.-C. Lambert, T. Verhoelst, J. Granville, M. van Roozendael, C. Lerot, R. Spurr, S. M. Frith, and C. Zehner
Atmos. Meas. Tech., 8, 3923–3940, https://doi.org/10.5194/amt-8-3923-2015, https://doi.org/10.5194/amt-8-3923-2015, 2015
A. Keppens, J.-C. Lambert, J. Granville, G. Miles, R. Siddans, J. C. A. van Peet, R. J. van der A, D. Hubert, T. Verhoelst, A. Delcloo, S. Godin-Beekmann, R. Kivi, R. Stübi, and C. Zehner
Atmos. Meas. Tech., 8, 2093–2120, https://doi.org/10.5194/amt-8-2093-2015, https://doi.org/10.5194/amt-8-2093-2015, 2015
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This work thoroughly discusses a methodology, as summarized in a flowchart, for the round-robin evaluation and geophysical validation of nadir ozone profile retrievals and applies the proposed best practice to a pair of optimal-estimation algorithms run on exactly the same level-1 radiance measurements. The quality assessment combines data set content studies, information content studies, and comparisons with ground-based reference measurements.
M. Antón, D. Loyola, R. Román, and H. Vömel
Atmos. Meas. Tech., 8, 1135–1145, https://doi.org/10.5194/amt-8-1135-2015, https://doi.org/10.5194/amt-8-1135-2015, 2015
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The main goal of this article was to validate the total water vapour column (TWVC) measured by the Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensor highly accurate sounding measurements. The smallest relative differences found in this satellite-sounding comparison (below 10%) were achieved for those cloud-free cases with satellite SZA below 50º which can be considered as a good result for satellite retrievals.
M. Grossi, P. Valks, D. Loyola, B. Aberle, S. Slijkhuis, T. Wagner, S. Beirle, and R. Lang
Atmos. Meas. Tech., 8, 1111–1133, https://doi.org/10.5194/amt-8-1111-2015, https://doi.org/10.5194/amt-8-1111-2015, 2015
G. M. Miles, R. Siddans, B. J. Kerridge, B. G. Latter, and N. A. D. Richards
Atmos. Meas. Tech., 8, 385–398, https://doi.org/10.5194/amt-8-385-2015, https://doi.org/10.5194/amt-8-385-2015, 2015
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This work provides a description and validation of significantly updated algorithm for the retrieval of atmospheric ozone profiles, with a focus on the sensitivity to ozone in the lower troposphere. The satellite-derived ozone profiles are validated against ozonesondes globally, and achieves an average bias of 6% in the lower troposphere. The global distribution is also compared to the ozone distribution from a chemistry transport model, with an average agreement of less than 2 Dobson units.
N. Hao, M. E. Koukouli, A. Inness, P. Valks, D. G. Loyola, W. Zimmer, D. S. Balis, I. Zyrichidou, M. Van Roozendael, C. Lerot, and R. J. D. Spurr
Atmos. Meas. Tech., 7, 2937–2951, https://doi.org/10.5194/amt-7-2937-2014, https://doi.org/10.5194/amt-7-2937-2014, 2014
P. Valks, N. Hao, S. Gimeno Garcia, D. Loyola, M. Dameris, P. Jöckel, and A. Delcloo
Atmos. Meas. Tech., 7, 2513–2530, https://doi.org/10.5194/amt-7-2513-2014, https://doi.org/10.5194/amt-7-2513-2014, 2014
K.-P. Heue, H. Riede, D. Walter, C. A. M. Brenninkmeijer, T. Wagner, U. Frieß, U. Platt, A. Zahn, G. Stratmann, and H. Ziereis
Atmos. Chem. Phys., 14, 6621–6642, https://doi.org/10.5194/acp-14-6621-2014, https://doi.org/10.5194/acp-14-6621-2014, 2014
E. W. Chiou, P. K. Bhartia, R. D. McPeters, D. G. Loyola, M. Coldewey-Egbers, V. E. Fioletov, M. Van Roozendael, R. Spurr, C. Lerot, and S. M. Frith
Atmos. Meas. Tech., 7, 1681–1692, https://doi.org/10.5194/amt-7-1681-2014, https://doi.org/10.5194/amt-7-1681-2014, 2014
H. Brenot, N. Theys, L. Clarisse, J. van Geffen, J. van Gent, M. Van Roozendael, R. van der A, D. Hurtmans, P.-F. Coheur, C. Clerbaux, P. Valks, P. Hedelt, F. Prata, O. Rasson, K. Sievers, and C. Zehner
Nat. Hazards Earth Syst. Sci., 14, 1099–1123, https://doi.org/10.5194/nhess-14-1099-2014, https://doi.org/10.5194/nhess-14-1099-2014, 2014
E. Castelli, B. M. Dinelli, S. Del Bianco, D. Gerber, B. P. Moyna, R. Siddans, B. J. Kerridge, and U. Cortesi
Atmos. Meas. Tech., 6, 2683–2701, https://doi.org/10.5194/amt-6-2683-2013, https://doi.org/10.5194/amt-6-2683-2013, 2013
T. Holzer-Popp, G. de Leeuw, J. Griesfeller, D. Martynenko, L. Klüser, S. Bevan, W. Davies, F. Ducos, J. L. Deuzé, R. G. Graigner, A. Heckel, W. von Hoyningen-Hüne, P. Kolmonen, P. Litvinov, P. North, C. A. Poulsen, D. Ramon, R. Siddans, L. Sogacheva, D. Tanre, G. E. Thomas, M. Vountas, J. Descloitres, J. Griesfeller, S. Kinne, M. Schulz, and S. Pinnock
Atmos. Meas. Tech., 6, 1919–1957, https://doi.org/10.5194/amt-6-1919-2013, https://doi.org/10.5194/amt-6-1919-2013, 2013
N. A. D. Richards, S. R. Arnold, M. P. Chipperfield, G. Miles, A. Rap, R. Siddans, S. A. Monks, and M. J. Hollaway
Atmos. Chem. Phys., 13, 2331–2345, https://doi.org/10.5194/acp-13-2331-2013, https://doi.org/10.5194/acp-13-2331-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements
Determination of the vertical distribution of in-cloud particle shape using SLDR-mode 35 GHz scanning cloud radar
Artificial intelligence (AI)-derived 3D cloud tomography from geostationary 2D satellite data
The EarthCARE mission: science data processing chain overview
Cloud optical and physical properties retrieval from EarthCARE multi-spectral imager: the M-COP products
Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products
Raman lidar-derived optical and microphysical properties of ice crystals within thin Arctic clouds during PARCS campaign
Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements
Deep convective cloud system size and structure across the global tropics and subtropics
A neural-network-based method for generating synthetic 1.6 µm near-infrared satellite images
Numerical model generation of test frames for pre-launch studies of EarthCARE's retrieval algorithms and data management system
Segmentation of polarimetric radar imagery using statistical texture
Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives
Min Deng, Scott E. Giangrande, Michael P. Jensen, Karen Johnson, Christopher R. Williams, Jennifer M. Comstock, Ya-Chien Feng, Alyssa Matthews, Iosif A. Lindenmaier, Timothy G. Wendler, Marquette Rocque, Aifang Zhou, Zeen Zhu, Edward Luke, and Die Wang
Atmos. Meas. Tech., 18, 1641–1657, https://doi.org/10.5194/amt-18-1641-2025, https://doi.org/10.5194/amt-18-1641-2025, 2025
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A relative calibration technique is developed for the cloud radar by monitoring the intercept of the wet-radome attenuation log-linear behavior as a function of rainfall rates in light and moderate rain conditions. This resulting reflectivity offset during the recent field campaign is compared favorably with the traditional disdrometer comparison near the rain onset, while it also demonstrates similar trends with respect to collocated and independently calibrated reference radars.
Yuli Liu and Ian Stuart Adams
Atmos. Meas. Tech., 18, 1659–1674, https://doi.org/10.5194/amt-18-1659-2025, https://doi.org/10.5194/amt-18-1659-2025, 2025
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This paper presents our latest development in tomographic reconstruction algorithms that use multi-angle (sub)millimeter-wave brightness temperature to reconstruct the spatial distribution of ice clouds. Compared to nadir-only retrievals, the tomography technique provides a detailed reconstruction of ice clouds’ inner structure with high spatial resolution and significantly improves retrieval accuracy. Also, the technique effectively increases detection sensitivity for small ice cloud particles.
Alexander Myagkov, Tatiana Nomokonova, and Michael Frech
Atmos. Meas. Tech., 18, 1621–1640, https://doi.org/10.5194/amt-18-1621-2025, https://doi.org/10.5194/amt-18-1621-2025, 2025
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The study examines the use of the spheroidal shape approximation for calculating cloud radar observables in rain and identifies some limitations. To address these, it introduces the empirical scattering model (ESM) based on high-quality Doppler spectra from a 94 GHz radar. The ESM offers improved accuracy and directly incorporates natural rain's microphysical effects. This new model can enhance retrieval and calibration methods, benefiting cloud radar polarimetry experts and scattering modelers.
Kaori Sato, Hajime Okamoto, Tomoaki Nishizawa, Yoshitaka Jin, Takashi Y. Nakajima, Minrui Wang, Masaki Satoh, Woosub Roh, Hiroshi Ishimoto, and Rei Kudo
Atmos. Meas. Tech., 18, 1325–1338, https://doi.org/10.5194/amt-18-1325-2025, https://doi.org/10.5194/amt-18-1325-2025, 2025
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This study introduces the JAXA EarthCARE Level 2 (L2) cloud product using satellite observations and simulated EarthCARE data. The outputs from the product feature a 3D global view of the dominant ice habit categories and corresponding microphysics. Habit and size distribution transitions from cloud to precipitation are quantified by the L2 cloud algorithms. With Doppler data, the products can be beneficial for further understanding of the coupling of cloud microphysics, radiation, and dynamics.
Ho Yi Lydia Mak and Christine Unal
Atmos. Meas. Tech., 18, 1209–1242, https://doi.org/10.5194/amt-18-1209-2025, https://doi.org/10.5194/amt-18-1209-2025, 2025
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The dynamics of thunderclouds are studied using cloud radar. Supercooled liquid water and conical graupel are likely present, while chain-like ice crystals may occur at cloud top. Ice crystals are vertically aligned seconds before lightning and resume their usual horizontal alignment afterwards in some cases. Updrafts and downdrafts are found near cloud core and edges respectively. Turbulence is strong. Radar measurement modes that are more suited for investigating thunderstorms are recommended.
Takashi M. Nagao, Kentaroh Suzuki, and Makoto Kuji
Atmos. Meas. Tech., 18, 773–792, https://doi.org/10.5194/amt-18-773-2025, https://doi.org/10.5194/amt-18-773-2025, 2025
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In satellite remote sensing, estimating cloud-base height (CBH) is more challenging than estimating cloud-top height because the cloud base is obscured by the cloud itself. We developed an algorithm using the specific channel (known as the oxygen A-band channel) of the SGLI on JAXA’s GCOM-C satellite to estimate CBHs together with other cloud properties. This algorithm can provide global distributions of CBH across various cloud types, including liquid, ice, and mixed-phase clouds.
Johanna Roschke, Jonas Witthuhn, Marcus Klingebiel, Moritz Haarig, Andreas Foth, Anton Kötsche, and Heike Kalesse-Los
Atmos. Meas. Tech., 18, 487–508, https://doi.org/10.5194/amt-18-487-2025, https://doi.org/10.5194/amt-18-487-2025, 2025
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We present a technique to discriminate between the Cloudnet target classification of "drizzle or rain" and sea salt aerosols that is applicable to marine Cloudnet sites. The method is crucial for investigating the occurrence of precipitation and significantly improves the Cloudnet target classification scheme for measurements over the Barbados Cloud Observatory (BCO). A first-ever analysis of the Cloudnet product including the new "haze echo" target over 2 years at the BCO is presented.
Andrzej Zbigniew Kotarba and Izabela Wojciechowska
EGUsphere, https://doi.org/10.5194/egusphere-2024-3693, https://doi.org/10.5194/egusphere-2024-3693, 2025
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The research investigates methods for detecting deep convective clouds (DCCs) using satellite infrared data, essential for understanding long-term climate trends. By validating three popular detection methods against lidar-radar data, it found moderate accuracy (below 75 %), emphasizing the importance of fine-tuning thresholds regionally. The study discovers how small threshold changes significantly affect climatology of severe storms.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 18, 73–91, https://doi.org/10.5194/amt-18-73-2025, https://doi.org/10.5194/amt-18-73-2025, 2025
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Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements over Europe by TROPOMI. Using a cloud shadow detection algorithm and simulations, we found that the overall effect on the aerosol index is minimal. Interestingly, we found that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech., 17, 7129–7141, https://doi.org/10.5194/amt-17-7129-2024, https://doi.org/10.5194/amt-17-7129-2024, 2024
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This study introduces a cloud property retrieval method which integrates traditional radiative transfer simulations with a machine learning method. Retrievals from a machine learning algorithm are used to provide a priori states, and a radiative transfer model is used to create lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and it is applicable to both daytime and nighttime conditions.
Sean R. Foley, Kirk D. Knobelspiesse, Andrew M. Sayer, Meng Gao, James Hays, and Judy Hoffman
Atmos. Meas. Tech., 17, 7027–7047, https://doi.org/10.5194/amt-17-7027-2024, https://doi.org/10.5194/amt-17-7027-2024, 2024
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Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.
Juan M. Socuellamos, Raquel Rodriguez Monje, Matthew D. Lebsock, Ken B. Cooper, and Pavlos Kollias
Atmos. Meas. Tech., 17, 6965–6981, https://doi.org/10.5194/amt-17-6965-2024, https://doi.org/10.5194/amt-17-6965-2024, 2024
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This article presents a novel technique to estimate liquid water content (LWC) profiles in shallow warm clouds using a pair of collocated Ka-band (35 GHz) and G-band (239 GHz) radars. We demonstrate that the use of a G-band radar allows retrieving the LWC with 3 times better accuracy than previous works reported in the literature, providing improved ability to understand the vertical profile of LWC and characterize microphysical and dynamical processes more precisely in shallow clouds.
Claudia Emde, Veronika Pörtge, Mihail Manev, and Bernhard Mayer
Atmos. Meas. Tech., 17, 6769–6789, https://doi.org/10.5194/amt-17-6769-2024, https://doi.org/10.5194/amt-17-6769-2024, 2024
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We introduce an innovative method to retrieve the cloud fraction and optical thickness of liquid water clouds over the ocean based on polarimetry. This is well suited for satellite observations providing multi-angle polarization measurements. Cloud fraction and cloud optical thickness can be derived from measurements at two viewing angles: one within the cloudbow and one in the sun glint region.
Vincent Forcadell, Clotilde Augros, Olivier Caumont, Kévin Dedieu, Maxandre Ouradou, Cloé David, Jordi Figueras i Ventura, Olivier Laurantin, and Hassan Al-Sakka
Atmos. Meas. Tech., 17, 6707–6734, https://doi.org/10.5194/amt-17-6707-2024, https://doi.org/10.5194/amt-17-6707-2024, 2024
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This study demonstrates the potential of enhancing severe-hail detection through the application of convolutional neural networks (CNNs) to dual-polarization radar data. It is shown that current methods can be calibrated to significantly enhance their performance for severe-hail detection. This study establishes the foundation for the solution of a more complex problem: the estimation of the maximum size of hailstones on the ground using deep learning applied to radar data.
Jinyi Xia and Li Guan
Atmos. Meas. Tech., 17, 6697–6706, https://doi.org/10.5194/amt-17-6697-2024, https://doi.org/10.5194/amt-17-6697-2024, 2024
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This study presents a method for estimating cloud cover from FY-4A AGRI observations using random forest (RF) and multilayer perceptron (MLP) algorithms. The results demonstrate excellent performance in distinguishing clear-sky scenes and reducing errors in cloud cover estimation. It shows significant improvements compared to existing methods.
Teresa Vogl, Martin Radenz, Fabiola Ramelli, Rosa Gierens, and Heike Kalesse-Los
Atmos. Meas. Tech., 17, 6547–6568, https://doi.org/10.5194/amt-17-6547-2024, https://doi.org/10.5194/amt-17-6547-2024, 2024
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In this study, we present a toolkit of two Python algorithms to extract information from Doppler spectra measured by ground-based cloud radars. In these Doppler spectra, several peaks can be formed due to populations of droplets/ice particles with different fall velocities coexisting in the same measurement time and height. The two algorithms can detect peaks and assign them to certain particle types, such as small cloud droplets or fast-falling ice particles like graupel.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
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Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Eleanor May, Bengt Rydberg, Inderpreet Kaur, Vinia Mattioli, Hanna Hallborn, and Patrick Eriksson
Atmos. Meas. Tech., 17, 5957–5987, https://doi.org/10.5194/amt-17-5957-2024, https://doi.org/10.5194/amt-17-5957-2024, 2024
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The upcoming Ice Cloud Imager (ICI) mission is set to improve measurements of atmospheric ice through passive microwave and sub-millimetre wave observations. In this study, we perform detailed simulations of ICI observations. Machine learning is used to characterise the atmospheric ice present for a given simulated observation. This study acts as a final pre-launch assessment of ICI's capability to measure atmospheric ice, providing valuable information to climate and weather applications.
Luke Edgar Whitehead, Adrian James McDonald, and Adrien Guyot
Atmos. Meas. Tech., 17, 5765–5784, https://doi.org/10.5194/amt-17-5765-2024, https://doi.org/10.5194/amt-17-5765-2024, 2024
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Supercooled liquid water cloud is important to represent in weather and climate models, particularly in the Southern Hemisphere. Previous work has developed a new machine learning method for measuring supercooled liquid water in Antarctic clouds using simple lidar observations. We evaluate this technique using a lidar dataset from Christchurch, New Zealand, and develop an updated algorithm for accurate supercooled liquid water detection at mid-latitudes.
Julien Lenhardt, Johannes Quaas, and Dino Sejdinovic
Atmos. Meas. Tech., 17, 5655–5677, https://doi.org/10.5194/amt-17-5655-2024, https://doi.org/10.5194/amt-17-5655-2024, 2024
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Clouds play a key role in the regulation of the Earth's climate. Aspects like the height of their base are of essential interest to quantify their radiative effects but remain difficult to derive from satellite data. In this study, we combine observations from the surface and satellite retrievals of cloud properties to build a robust and accurate method to retrieve the cloud base height, based on a computer vision model and ordinal regression.
Johanna Mayer, Bernhard Mayer, Luca Bugliaro, Ralf Meerkötter, and Christiane Voigt
Atmos. Meas. Tech., 17, 5161–5185, https://doi.org/10.5194/amt-17-5161-2024, https://doi.org/10.5194/amt-17-5161-2024, 2024
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This study uses radiative transfer calculations to characterize the relation of two satellite channel combinations (namely infrared window brightness temperature differences – BTDs – of SEVIRI) to the thermodynamic cloud phase. A sensitivity analysis reveals the complex interplay of cloud parameters and their contribution to the observed phase dependence of BTDs. This knowledge helps to design optimal cloud-phase retrievals and to understand their potential and limitations.
Howard W. Barker, Jason N. S. Cole, Najda Villefranque, Zhipeng Qu, Almudena Velázquez Blázquez, Carlos Domenech, Shannon L. Mason, and Robin J. Hogan
EGUsphere, https://doi.org/10.5194/egusphere-2024-1651, https://doi.org/10.5194/egusphere-2024-1651, 2024
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Measurements made by three instruments aboard EarthCARE are used to retrieve estimates of cloud and aerosol properties. A radiative closure assessment of these retrievals is performed by the ACMB-DF processor. Radiative transfer models acting on retrieved information produce broadband radiances commensurate with measurements made by EarthCARE’s broadband radiometer. Measured and modelled radiances for small domains are compared and the likelihood of them differing by 10 W/m2 defines the closure.
Frédéric P. A. Vogt, Loris Foresti, Daniel Regenass, Sophie Réthoré, Néstor Tarin Burriel, Mervyn Bibby, Przemysław Juda, Simone Balmelli, Tobias Hanselmann, Pieter du Preez, and Dirk Furrer
Atmos. Meas. Tech., 17, 4891–4914, https://doi.org/10.5194/amt-17-4891-2024, https://doi.org/10.5194/amt-17-4891-2024, 2024
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ampycloud is a new algorithm developed at MeteoSwiss to characterize the height and sky coverage fraction of cloud layers above aerodromes via ceilometer data. This algorithm was devised as part of a larger effort to fully automate the creation of meteorological aerodrome reports (METARs) at Swiss civil airports. The ampycloud algorithm is implemented as a Python package that is made publicly available to the community under the 3-Clause BSD license.
Ke Ren, Haiyang Gao, Shuqi Niu, Shaoyang Sun, Leilei Kou, Yanqing Xie, Liguo Zhang, and Lingbing Bu
Atmos. Meas. Tech., 17, 4825–4842, https://doi.org/10.5194/amt-17-4825-2024, https://doi.org/10.5194/amt-17-4825-2024, 2024
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Ultraviolet imaging technology has significantly advanced the research and development of polar mesospheric clouds (PMCs). In this study, we proposed the wide-field-of-view ultraviolet imager (WFUI) and built a forward model to evaluate the detection capability and efficiency. The results demonstrate that the WFUI performs well in PMC detection and has high detection efficiency. The relationship between ice water content and detection efficiency follows an exponential function distribution.
Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson
Atmos. Meas. Tech., 17, 4337–4368, https://doi.org/10.5194/amt-17-4337-2024, https://doi.org/10.5194/amt-17-4337-2024, 2024
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The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.
Huige Di, Xinhong Wang, Ning Chen, Jing Guo, Wenhui Xin, Shichun Li, Yan Guo, Qing Yan, Yufeng Wang, and Dengxin Hua
Atmos. Meas. Tech., 17, 4183–4196, https://doi.org/10.5194/amt-17-4183-2024, https://doi.org/10.5194/amt-17-4183-2024, 2024
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This study proposes an inversion method for atmospheric-aerosol or cloud microphysical parameters based on dual-wavelength lidar data. It is suitable for the inversion of uniformly mixed and single-property aerosol layers or small cloud droplets. For aerosol particles, the inversion range that this algorithm can achieve is 0.3–1.7 μm. For cloud droplets, it is 1.0–10 μm. This algorithm can quickly obtain the microphysical parameters of atmospheric particles and has better robustness.
Johanna Mayer, Luca Bugliaro, Bernhard Mayer, Dennis Piontek, and Christiane Voigt
Atmos. Meas. Tech., 17, 4015–4039, https://doi.org/10.5194/amt-17-4015-2024, https://doi.org/10.5194/amt-17-4015-2024, 2024
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ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI) is a method to detect clouds and their thermodynamic phase with a geostationary satellite, distinguishing between clear sky and ice, mixed-phase, supercooled and warm liquid clouds. It uses a Bayesian approach based on the lidar–radar product DARDAR. The method allows studying cloud phases, especially mixed-phase and supercooled clouds, rarely observed from geostationary satellites. This can be used for comparison with climate models.
Yu-Wen Chen, K. Sebastian Schmidt, Hong Chen, Steven T. Massie, Susan S. Kulawik, and Hironobu Iwabuchi
EGUsphere, https://doi.org/10.5194/egusphere-2024-1936, https://doi.org/10.5194/egusphere-2024-1936, 2024
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Retrievals of CO2 column-averaged dry air mole fractions from space can be done with spaceborne spectrometers such as OCO-2. Clouds in the vicinity of a footprint lead to spectral perturbations that bias those retrievals well beyond the required accuracy for global assessments of CO2 sources and sinks. This paper presents two physics-based mitigation techniques for these biases based on accompanying imagery, which can be used operationally.
Clémantyne Aubry, Julien Delanoë, Silke Groß, Florian Ewald, Frédéric Tridon, Olivier Jourdan, and Guillaume Mioche
Atmos. Meas. Tech., 17, 3863–3881, https://doi.org/10.5194/amt-17-3863-2024, https://doi.org/10.5194/amt-17-3863-2024, 2024
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Radar–lidar synergy is used to retrieve ice, supercooled water and mixed-phase cloud properties, making the most of the radar sensitivity to ice crystals and the lidar sensitivity to supercooled droplets. A first analysis of the output of the algorithm run on the satellite data is compared with in situ data during an airborne Arctic field campaign, giving a mean percent error of 49 % for liquid water content and 75 % for ice water content.
Gerald G. Mace
Atmos. Meas. Tech., 17, 3679–3695, https://doi.org/10.5194/amt-17-3679-2024, https://doi.org/10.5194/amt-17-3679-2024, 2024
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The number of cloud droplets per unit volume, Nd, in a cloud is important for understanding aerosol–cloud interaction. In this study, we develop techniques to derive cloud droplet number concentration from lidar measurements combined with other remote sensing measurements such as cloud radar and microwave radiometers. We show that deriving Nd is very uncertain, although a synergistic algorithm seems to produce useful characterizations of Nd and effective particle size.
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, https://doi.org/10.5194/amt-17-3583-2024, 2024
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This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
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Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Gianluca Di Natale, Marco Ridolfi, and Luca Palchetti
Atmos. Meas. Tech., 17, 3171–3186, https://doi.org/10.5194/amt-17-3171-2024, https://doi.org/10.5194/amt-17-3171-2024, 2024
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This work aims to define a new approach to retrieve the distribution of the main ice crystal shapes occurring inside ice and cirrus clouds from infrared spectral measurements. The capability of retrieving these shapes of the ice crystals from satellites will allow us to extend the currently available climatologies to be used as physical constraints in general circulation models. This could could allow us to improve their accuracy and prediction performance.
Valery Shcherbakov, Frédéric Szczap, Guillaume Mioche, and Céline Cornet
Atmos. Meas. Tech., 17, 3011–3028, https://doi.org/10.5194/amt-17-3011-2024, https://doi.org/10.5194/amt-17-3011-2024, 2024
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We performed Monte Carlo simulations of single-wavelength lidar signals from multi-layered clouds with special attention focused on the multiple-scattering (MS) effect in regions of the cloud-free molecular atmosphere. The MS effect on lidar signals always decreases with the increasing distance from the cloud far edge. The decrease is the direct consequence of the fact that the forward peak of particle phase functions is much larger than the receiver field of view.
Babak Jahani, Steffen Karalus, Julia Fuchs, Tobias Zech, Marina Zara, and Jan Cermak
EGUsphere, https://doi.org/10.5194/egusphere-2023-2885, https://doi.org/10.5194/egusphere-2023-2885, 2024
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Fog and low stratus (FLS) are both persistent clouds close to the Earth’s surface. In the context of photovoltaic power production, FLS is particularly important, as FLS, impact large regions simultaneously, making regional power grid balancing hard. This study introduces a new machine leanring based algorithm developed for the MSG geostationary satellites that can provide a coherent and detailed view of FLS development over large areas over the 24 H day cycle.
Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, and Matthias Tesche
Atmos. Meas. Tech., 17, 1739–1757, https://doi.org/10.5194/amt-17-1739-2024, https://doi.org/10.5194/amt-17-1739-2024, 2024
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We present a novel method for studying aerosol–cloud interactions. It combines cloud-relevant aerosol concentrations from polar-orbiting lidar observations with the development of individual clouds from geostationary observations. Application to 1 year of data gives first results on the impact of aerosols on the concentration and size of cloud droplets and on cloud phase in the regime of heterogeneous ice formation. The method could enable the systematic investigation of warm and cold clouds.
Kélian Sommer, Wassim Kabalan, and Romain Brunet
EGUsphere, https://doi.org/10.5194/egusphere-2024-101, https://doi.org/10.5194/egusphere-2024-101, 2024
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Our research introduces a novel deep-learning approach for classifying and segmenting ground-based infrared thermal images, a crucial step in cloud monitoring. Tests on self-captured data showcase its excellent accuracy in distinguishing image types and in structure segmentation. With potential applications in astronomical observations, our work pioneers a robust solution for ground-based sky quality assessment, promising advancements in the photometric observations experiments.
Cristina Gil-Díaz, Michäel Sicard, Adolfo Comerón, Daniel Camilo Fortunato dos Santos Oliveira, Constantino Muñoz-Porcar, Alejandro Rodríguez-Gómez, Jasper R. Lewis, Ellsworth J. Welton, and Simone Lolli
Atmos. Meas. Tech., 17, 1197–1216, https://doi.org/10.5194/amt-17-1197-2024, https://doi.org/10.5194/amt-17-1197-2024, 2024
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In this paper, a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. The cloud optical depth, effective column lidar ratio and linear cloud depolarisation ratio have been calculated by a new approach to the two-way transmittance method, which is valid for both ground-based and spaceborne lidar systems. Their associated errors are also provided.
Audrey Teisseire, Patric Seifert, Alexander Myagkov, Johannes Bühl, and Martin Radenz
Atmos. Meas. Tech., 17, 999–1016, https://doi.org/10.5194/amt-17-999-2024, https://doi.org/10.5194/amt-17-999-2024, 2024
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The vertical distribution of particle shape (VDPS) method, introduced in this study, aids in characterizing the density-weighted shape of cloud particles from scanning slanted linear depolarization ratio (SLDR)-mode cloud radar observations. The VDPS approach represents a new, versatile way to study microphysical processes by combining a spheroidal scattering model with real measurements of SLDR.
Sarah Brüning, Stefan Niebler, and Holger Tost
Atmos. Meas. Tech., 17, 961–978, https://doi.org/10.5194/amt-17-961-2024, https://doi.org/10.5194/amt-17-961-2024, 2024
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We apply the Res-UNet to derive a comprehensive 3D cloud tomography from 2D satellite data over heterogeneous landscapes. We combine observational data from passive and active remote sensing sensors by an automated matching algorithm. These data are fed into a neural network to predict cloud reflectivities on the whole satellite domain between 2.4 and 24 km height. With an average RMSE of 2.99 dBZ, we contribute to closing data gaps in the representation of clouds in observational data.
Michael Eisinger, Fabien Marnas, Kotska Wallace, Takuji Kubota, Nobuhiro Tomiyama, Yuichi Ohno, Toshiyuki Tanaka, Eichi Tomita, Tobias Wehr, and Dirk Bernaerts
Atmos. Meas. Tech., 17, 839–862, https://doi.org/10.5194/amt-17-839-2024, https://doi.org/10.5194/amt-17-839-2024, 2024
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The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) is an ESA–JAXA satellite mission to be launched in 2024. We presented an overview of the EarthCARE processors' development, with processors developed by teams in Europe, Japan, and Canada. EarthCARE will allow scientists to evaluate the representation of cloud, aerosol, precipitation, and radiative flux in weather forecast and climate models, with the objective to better understand cloud processes and improve weather and climate models.
Anja Hünerbein, Sebastian Bley, Hartwig Deneke, Jan Fokke Meirink, Gerd-Jan van Zadelhoff, and Andi Walther
Atmos. Meas. Tech., 17, 261–276, https://doi.org/10.5194/amt-17-261-2024, https://doi.org/10.5194/amt-17-261-2024, 2024
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The ESA cloud, aerosol and radiation mission EarthCARE will provide active profiling and passive imaging measurements from a single satellite platform. The passive multi-spectral imager (MSI) will add information in the across-track direction. We present the cloud optical and physical properties algorithm, which combines the visible to infrared MSI channels to determine the cloud top pressure, optical thickness, particle size and water path.
Moritz Haarig, Anja Hünerbein, Ulla Wandinger, Nicole Docter, Sebastian Bley, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5953–5975, https://doi.org/10.5194/amt-16-5953-2023, https://doi.org/10.5194/amt-16-5953-2023, 2023
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The atmospheric lidar (ATLID) and Multi-Spectral Imager (MSI) will be carried by the EarthCARE satellite. The synergistic ATLID–MSI Column Products (AM-COL) algorithm described in the paper combines the strengths of ATLID in vertically resolved profiles of aerosol and clouds (e.g., cloud top height) with the strengths of MSI in observing the complete scene beside the satellite track and in extending the lidar information to the swath. The algorithm is validated against simulated test scenes.
Patrick Chazette and Jean-Christophe Raut
Atmos. Meas. Tech., 16, 5847–5861, https://doi.org/10.5194/amt-16-5847-2023, https://doi.org/10.5194/amt-16-5847-2023, 2023
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The vertical profiles of the effective radii of ice crystals and ice water content in Arctic semi-transparent stratiform clouds were assessed using quantitative ground-based lidar measurements. The field campaign was part of the Pollution in the ARCtic System (PARCS) project which took place from 13 to 26 May 2016 in Hammerfest (70° 39′ 48″ N, 23° 41′ 00″ E). We show that under certain cloud conditions, lidar measurement combined with a dedicated algorithmic approach is an efficient tool.
Damao Zhang, Andrew M. Vogelmann, Fan Yang, Edward Luke, Pavlos Kollias, Zhien Wang, Peng Wu, William I. Gustafson Jr., Fan Mei, Susanne Glienke, Jason Tomlinson, and Neel Desai
Atmos. Meas. Tech., 16, 5827–5846, https://doi.org/10.5194/amt-16-5827-2023, https://doi.org/10.5194/amt-16-5827-2023, 2023
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Cloud droplet number concentration can be retrieved from remote sensing measurements. Aircraft measurements are used to validate four ground-based retrievals of cloud droplet number concentration. We demonstrate that retrieved cloud droplet number concentrations align well with aircraft measurements for overcast clouds, but they may substantially differ for broken clouds. The ensemble of various retrievals can help quantify retrieval uncertainties and identify reliable retrieval scenarios.
Eric M. Wilcox, Tianle Yuan, and Hua Song
Atmos. Meas. Tech., 16, 5387–5401, https://doi.org/10.5194/amt-16-5387-2023, https://doi.org/10.5194/amt-16-5387-2023, 2023
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A new database is constructed from over 20 years of satellite records that comprises millions of deep convective clouds and spans the global tropics and subtropics. The database is a collection of clouds ranging from isolated cells to giant cloud systems. The cloud database provides a means of empirically studying the factors that determine the spatial structure and coverage of convective cloud systems, which are strongly related to the overall radiative forcing by cloud systems.
Florian Baur, Leonhard Scheck, Christina Stumpf, Christina Köpken-Watts, and Roland Potthast
Atmos. Meas. Tech., 16, 5305–5326, https://doi.org/10.5194/amt-16-5305-2023, https://doi.org/10.5194/amt-16-5305-2023, 2023
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Near-infrared satellite images have information on clouds that is complementary to what is available from the visible and infrared parts of the spectrum. Using this information for data assimilation and model evaluation requires a fast, accurate forward operator to compute synthetic images from numerical weather prediction model output. We discuss a novel, neural-network-based approach for the 1.6 µm near-infrared channel that is suitable for this purpose and also works for other solar channels.
Zhipeng Qu, David P. Donovan, Howard W. Barker, Jason N. S. Cole, Mark W. Shephard, and Vincent Huijnen
Atmos. Meas. Tech., 16, 4927–4946, https://doi.org/10.5194/amt-16-4927-2023, https://doi.org/10.5194/amt-16-4927-2023, 2023
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The EarthCARE satellite mission Level 2 algorithm development requires realistic 3D cloud and aerosol scenes along the satellite orbits. One of the best ways to produce these scenes is to use a high-resolution numerical weather prediction model to simulate atmospheric conditions at 250 m horizontal resolution. This paper describes the production and validation of three EarthCARE test scenes.
Adrien Guyot, Jordan P. Brook, Alain Protat, Kathryn Turner, Joshua Soderholm, Nicholas F. McCarthy, and Hamish McGowan
Atmos. Meas. Tech., 16, 4571–4588, https://doi.org/10.5194/amt-16-4571-2023, https://doi.org/10.5194/amt-16-4571-2023, 2023
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We propose a new method that should facilitate the use of weather radars to study wildfires. It is important to be able to identify the particles emitted by wildfires on radar, but it is difficult because there are many other echoes on radar like clear air, the ground, sea clutter, and precipitation. We came up with a two-step process to classify these echoes. Our method is accurate and can be used by fire departments in emergencies or by scientists for research.
Hadrien Verbois, Yves-Marie Saint-Drenan, Vadim Becquet, Benoit Gschwind, and Philippe Blanc
Atmos. Meas. Tech., 16, 4165–4181, https://doi.org/10.5194/amt-16-4165-2023, https://doi.org/10.5194/amt-16-4165-2023, 2023
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Solar surface irradiance (SSI) estimations inferred from satellite images are essential to gain a comprehensive understanding of the solar resource, which is crucial in many fields. This study examines the recent data-driven methods for inferring SSI from satellite images and explores their strengths and weaknesses. The results suggest that while these methods show great promise, they sometimes dramatically underperform and should probably be used in conjunction with physical approaches.
Cited articles
Atkinson, J.: Sister Satellites, Briefly Separated, Working Together Again, https://www.nasa.gov/feature/langley/sister-satellites-briefly-separated-working-together-again (last access: 13 March 2023), 2018. a
Bohren, C. F. and Huffman, D. R.: Absorption and scattering by small particles, Wiley, NY, 530 pp., https://doi.org/10.1002/9783527618156, 1983. a
Cahalan, R. F., Ridgway, W., Wiscombe, W. J., Gollmer, S., and Harshvardhan: Independent Pixel and Monte Carlo Estimates of Stratocumulus Albedo, J. Atmos. Sci., 51, 3776–3790, https://doi.org/10.1175/1520-0469(1994)051<3776:IPAMCE>2.0.CO;2, 1994. a
Chambers, L. H., Wielicki, B. A., and Evans, K. F.: Accuracy of the independent pixel approximation for satellite estimates of oceanic boundary layer cloud optical depth, J. Geophys. Res.-Atmos., 102, 1779–1794, https://doi.org/10.1029/96JD02995, 1997. a
Compernolle, S., Argyrouli, A., Lutz, R., Sneep, M., Lambert, J.-C., Fjæraa, A. M., Hubert, D., Keppens, A., Loyola, D., O'Connor, E., Romahn, F., Stammes, P., Verhoelst, T., and Wang, P.: Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O2–O2, MODIS, and Suomi-NPP VIIRS, Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, 2021. a
Copernicus: Copernicus Data Space Ecosystem on Earth, Copernicus, https://dataspace.copernicus.eu/, 2024. a
Cox, C. S. and Munk, W. H.: Measurement of the Roughness of the Sea Surface from Photographs of the Sun’s Glitter, J. Opt. Soc. Am., 44, 838–850, 1954. 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/10.5194/amt-11-2395-2018, 2018. a
Heidinger, A. and Straka, W.: Algorithm Theoretical Basis Document For NOAA Enterprise Cloud Mask, Version1.2, https://www.star.nesdis.noaa.gov/goesr/documents/ATBDs/Enterprise/ATBD_Enterprise_Cloud_Mask_v1.2_2020_10_01.pdf (last access: 22 October 2024), 2020. a
Heidinger, A., Li, Y., and Wanzong, S.: Algorithm Theoretical Basis Document For Enterprise AWG Cloud Height Algorithm (ACHA), Version 3.4, https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_EPS_Cloud_ACHA_v3.4.pdf (last access: 22 October 2024), 2020. a
Heidinger, A. K., Evan, A. T., Foster, M. J., and Walther, A.: A Naive Bayesian Cloud-Detection Scheme Derived from CALIPSO and Applied within PATMOS-x, J. Appl. Meteorol. Climatol., 51, 1129–1144, https://doi.org/10.1175/JAMC-D-11-02.1, 2012. a
Heue, K.-P., Eichmann, K., and Valks, P.: TROPOMI/S5P ATBD of tropospheric ozone data products, Tech. Rep. S5P-L2-IUP-ATBD-400C, issue 1.6, Deutsches Zentrum fur Luft- und Raumfahrt e.V. in der Helmholtz Gemeinschaft and Institute for Environmental Physics (IUP), https://sentinels.copernicus.eu/documents/247904/2476257/Sentinel-5P-ATBD-TROPOMI-Tropospheric-Ozone/d2106102-b5c3-4d28-b752-026e3448aab2?version=1.2 (last access: 22 October 2024), 2018. a
King, M. D.: Determination of the Scaled Optical Thickness of Clouds from Reflected Solar Radiation Measurements, J. Atmos. Sci., 44, 1734–1751, https://doi.org/10.1175/1520-0469(1987)044<1734:DOTSOT>2.0.CO;2, 1987. a
Kleipool, Q., Ludewig, A., Babić, L., Bartstra, R., Braak, R., Dierssen, W., Dewitte, P.-J., Kenter, P., Landzaat, R., Leloux, J., Loots, E., Meijering, P., van der Plas, E., Rozemeijer, N., Schepers, D., Schiavini, D., Smeets, J., Vacanti, G., Vonk, F., and Veefkind, P.: Pre-launch calibration results of the TROPOMI payload on-board the Sentinel-5 Precursor satellite, Atmos. Meas. Tech., 11, 6439–6479, https://doi.org/10.5194/amt-11-6439-2018, 2018. a
KNMI: S5P/TROPOMI Algorithm theoretical basis document for the TROPOMI L01b data processor, S5P-KNMI-L01B-0009- SD, issue 10.0.0, https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-Level-1B-ATBD (last access: 22 October 2024), 2022. a
Kokhanovsky, A. A. and Mayer, B.: Light reflection and transmission by non-absorbing turbid slabs: simple approximations, J. Opt. A, 5, 43–46, https://doi.org/10.1088/1464-4258/5/1/306, 2003. a, b
Latsch, M., Richter, A., Eskes, H., Sneep, M., Wang, P., Veefkind, P., Lutz, R., Loyola, D., Argyrouli, A., Valks, P., Wagner, T., Sihler, H., van Roozendael, M., Theys, N., Yu, H., Siddans, R., and Burrows, J. P.: Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals, Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, 2022. a
Liu, C.-Y., Chiu, C.-H., Lin, P.-H., and Min, M.: Comparison of cloud-top property retrievals from Advanced Himawari Imager, MODIS, CloudSat/CPR, CALIPSO/CALIOP, and radiosonde, J. Geophys. Res.-Atmos., 125, e2020JD032683, https://doi.org/10.1029/2020JD032683, 2020. a
Liu, S., Valks, P., Pinardi, G., Xu, J., Chan, K. L., Argyrouli, A., Lutz, R., Beirle, S., Khorsandi, E., Baier, F., Huijnen, V., Bais, A., Donner, S., Dörner, S., Gratsea, M., Hendrick, F., Karagkiozidis, D., Lange, K., Piters, A. J. M., Remmers, J., Richter, A., Van Roozendael, M., Wagner, T., Wenig, M., and Loyola, D. G.: An improved TROPOMI tropospheric NO2 research product over Europe, Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, 2021. a
Loyola, D.: Methodologies for solving Satellite Remote Sensing Problems using Neuro Computing Techniques, Ph.D. thesis, Technische Universität München, verlag Dr. Hut, ISBN 978-3-8439-1068-2, 2013. a
Loyola, D. G.: Automatic cloud analysis from polar-orbiting satellites using neural network and data fusion techniques, in: IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium, Vol. 4, 2530–2533 pp., https://doi.org/10.1109/IGARSS.2004.1369811, 2004. 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., Pedergnana, M., and Gimeno García, S.: Smart sampling and incremental function learning for very large high dimensional data, Neural Netw., 78, 75–87, https://doi.org/10.1016/j.neunet.2015.09.001, special Issue on “Neural Network Learning in Big Data”, 2016. a
Loyola, D. G., Gimeno García, S., Lutz, R., Argyrouli, A., Romahn, F., Spurr, R. J. D., Pedergnana, M., Doicu, A., Molina García, V., and Schüssler, O.: The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor, Atmos. Meas. Tech., 11, 409–427, https://doi.org/10.5194/amt-11-409-2018, 2018. a, b
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/10.5194/amt-9-2357-2016, 2016. a, b
Molina García, V.: Retrieval of cloud properties from EPIC/DSCOVR, Ph.D. thesis, Technische Universität München, https://mediatum.ub.tum.de/node?id=1662361 (last access: 22 October 2024), 2022. a
Nakajima, T. and King, M. D.: Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. I – Theory, J. Atmos. Sci., 47, 1878–1893, https://doi.org/10.1175/1520-0469(1990)047<1878:DOTOTA>2.0.CO;2, 1990a. a
Nakajima, T. and King, M. D.: Asymptotic theory for optically thick layers: application to the discrete ordinates method, Appl. Opt., 31, 7669–7683, https://doi.org/10.1364/AO.31.007669, 1990b. a
NASA/LARC/SD/ASDC: CALIPSO Lidar Level 2 5 km Cloud Layer, V4-20 [data set], https://doi.org/10.5067/CALIOP/CALIPSO/LID_L2_05KMCLAY-STANDARD-V4-20, 2018. a
Rodgers, C. D.: Inverse Methods for Atmospheric Sounding: Theory and Practice, Vol. 2 of, Atmospheric, Oceanic and Planetary Physics, World Scientific, https://doi.org/10.1142/3171, 2000. a
Schuessler, O., Loyola, D. G., Doicu, A., and Spurr, R. J. D.: Information Content in the Oxygen A-Band for the Retrieval of Macrophysical Cloud Parameters, IEEE Trans. Geosci. Remote Sens., 52, 3246–3255, https://doi.org/10.1109/TGRS.2013.2271986, 2014. a
Spurr, R. J. D.: VLIDORT: A linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media, J. Quant. Spectrosc. Ra., 102, 316–342, https://doi.org/10.1016/j.jqsrt.2006.05.005, 2006. a
Spurr, R. J. D., Loyola, D., Heue, K.-P., Van Roozendael, M., and Lerot, C.: S5P/TROPOMI Total Ozone ATBD, Tech. Rep. S5P-L2-DLR-ATBD-400A, issue 2.4, Deutsches Zentrum fur Luft- und Raumfahrt e.V. in der Helmholtz Gemeinschaft and Royal Belgian Institute for Space Aeronomy (BIRA-IASB), https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-Total-Ozone (last access: 22 October 2024), 2022. a
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/10.5194/amt-10-119-2017, 2017. a
Van de Hulst, H. C.: Light scattering by small particles, Wiley, NY, 1957. a
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
Walther, A. and Heidinger, A. K.: Implementation of the Daytime Cloud Optical and Microphysical Properties Algorithm (DCOMP) in PATMOS-x, J. Appl. Meteorol. Climatol., 51, 1371–1390, https://doi.org/10.1175/JAMC-D-11-0108.1, 2012. a
Walther, A. and Straka, W.: Algorithm Theoretical Basis Document For Daytime Cloud Optical and Microphysical Properties (DCOMP), Version 1.2, https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_EPS_Cloud_DCOMP_v1.2.pdf (last access: 22 October 2024), 2020. a
Winker, D., Pelon, J., and Mccormick, M.: The CALIPSO mission: Spaceborne lidar for observation of aerosols and clouds, Proc. SPIE-Int. Soc. Opt. Eng., 4893, 1–11, https://doi.org/10.1117/12.466539, 2003. a
Winker, D., Hunt, W., and Hostetler, C.: Status and performance of the CALIOP lidar, P. SPIE – The International Society for Optical Engineering, 5575, 8–15 pp., https://doi.org/10.1117/12.571955, 2004. a
Winker, D. M., Hunt, W. H., and McGill, M. J.: Initial performance assessment of CALIOP, Geophys. Res. Lett., 34, 19, https://doi.org/10.1029/2007GL030135, 2007. a
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.
This paper describes a new treatment of the spatial misregistration of cloud properties for...
