Articles | Volume 9, issue 12
https://doi.org/10.5194/amt-9-6035-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-6035-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
15 Dec 2016
Research article |
| 15 Dec 2016
Improvements to the OMI O2–O2 operational cloud algorithm and comparisons with ground-based radar–lidar observations
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, the Netherlands
Johan F. de Haan
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Maarten Sneep
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Pieternel F. Levelt
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, the Netherlands
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Atmos. Meas. Tech., 17, 3969–3993, https://doi.org/10.5194/amt-17-3969-2024, https://doi.org/10.5194/amt-17-3969-2024, 2024
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Atmos. Chem. Phys., 24, 4511–4535, https://doi.org/10.5194/acp-24-4511-2024, https://doi.org/10.5194/acp-24-4511-2024, 2024
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Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
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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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Johan F. de Haan, Ping Wang, Maarten Sneep, J. Pepijn Veefkind, and Piet Stammes
Geosci. Model Dev., 15, 7031–7050, https://doi.org/10.5194/gmd-15-7031-2022, https://doi.org/10.5194/gmd-15-7031-2022, 2022
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John T. Sullivan, Arnoud Apituley, Nora Mettig, Karin Kreher, K. Emma Knowland, Marc Allaart, Ankie Piters, Michel Van Roozendael, Pepijn Veefkind, Jerry R. Ziemke, Natalya Kramarova, Mark Weber, Alexei Rozanov, Laurence Twigg, Grant Sumnicht, and Thomas J. McGee
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Atmos. Meas. Tech., 15, 3527–3553, https://doi.org/10.5194/amt-15-3527-2022, https://doi.org/10.5194/amt-15-3527-2022, 2022
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Nora Mettig, Mark Weber, Alexei Rozanov, John P. Burrows, Pepijn Veefkind, Anne M. Thompson, Ryan M. Stauffer, Thierry Leblanc, Gerard Ancellet, Michael J. Newchurch, Shi Kuang, Rigel Kivi, Matthew B. Tully, Roeland Van Malderen, Ankie Piters, Bogumil Kois, René Stübi, and Pavla Skrivankova
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Vertical ozone profiles from combined spectral measurements in the UV and IR spectral ranges were retrieved by using data from TROPOMI/S5P and CrIS/Suomi-NPP. The vertical resolution and accuracy of the ozone profiles are improved by combining both wavelength ranges compared to retrievals limited to UV or IR spectral data only. The advancement of our TOPAS algorithm for combined measurements is required because in the UV-only retrieval the vertical resolution in the troposphere is very limited.
Jos van Geffen, Henk Eskes, Steven Compernolle, Gaia Pinardi, Tijl Verhoelst, Jean-Christopher Lambert, Maarten Sneep, Mark ter Linden, Antje Ludewig, K. Folkert Boersma, and J. Pepijn Veefkind
Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022, https://doi.org/10.5194/amt-15-2037-2022, 2022
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Nitrogen dioxide (NO2) is one of the main data products measured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite. This study describes improvements in the TROPOMI NO2 retrieval leading to version v2.2, operational since 1 July 2021. It compares results with previous versions v1.2–v1.4 and with Ozone Monitoring Instrument (OMI) and ground-based measurements.
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.
Nora Mettig, Mark Weber, Alexei Rozanov, Carlo Arosio, John P. Burrows, Pepijn Veefkind, Anne M. Thompson, Richard Querel, Thierry Leblanc, Sophie Godin-Beekmann, Rigel Kivi, and Matthew B. Tully
Atmos. Meas. Tech., 14, 6057–6082, https://doi.org/10.5194/amt-14-6057-2021, https://doi.org/10.5194/amt-14-6057-2021, 2021
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TROPOMI is a nadir-viewing satellite that has observed global atmospheric trace gases at unprecedented spatial resolution since 2017. The retrieval of ozone profiles with high accuracy has been demonstrated using the TOPAS (Tikhonov regularised Ozone Profile retrievAl with SCIATRAN) algorithm and applying appropriate spectral corrections to TROPOMI UV data. Ozone profiles from TROPOMI were compared to ozonesonde and lidar profiles, showing an agreement to within 5 % in the stratosphere.
Frederik Tack, Alexis Merlaud, Marian-Daniel Iordache, Gaia Pinardi, Ermioni Dimitropoulou, Henk Eskes, Bart Bomans, Pepijn Veefkind, and Michel Van Roozendael
Atmos. Meas. Tech., 14, 615–646, https://doi.org/10.5194/amt-14-615-2021, https://doi.org/10.5194/amt-14-615-2021, 2021
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We assess the TROPOMI tropospheric NO2 product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) based on coinciding airborne APEX reference observations (~75 m × 120 m), acquired over polluted regions in Belgium. The TROPOMI NO2 product meets the mission requirements in terms of precision and accuracy. However, we show that TROPOMI is biased low over polluted areas, mainly due to the limited spatial resolution of a priori input for the AMF computation.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
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This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 21, 597–616, https://doi.org/10.5194/acp-21-597-2021, https://doi.org/10.5194/acp-21-597-2021, 2021
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This paper compares the relative atmospheric enhancements of CO and NO2 measured by the space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in the ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional-scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Maurits L. Kooreman, Piet Stammes, Victor Trees, Maarten Sneep, L. Gijsbert Tilstra, Martin de Graaf, Deborah C. Stein Zweers, Ping Wang, Olaf N. E. Tuinder, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 6407–6426, https://doi.org/10.5194/amt-13-6407-2020, https://doi.org/10.5194/amt-13-6407-2020, 2020
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We investigated the influence of clouds on the Absorbing Aerosol Index (AAI), an indicator of the presence of small particles in the atmosphere. Clouds produce artifacts in AAI calculations on the individual measurement (7 km) scale, which was not seen with previous instruments, as well as on large (1000+ km) scales. To reduce these artefacts, we used three different AAI calculation techniques of varying complexity. We find that the AAI artifacts are reduced when using more complex techniques.
Laura M. Judd, Jassim A. Al-Saadi, James J. Szykman, Lukas C. Valin, Scott J. Janz, Matthew G. Kowalewski, Henk J. Eskes, J. Pepijn Veefkind, Alexander Cede, Moritz Mueller, Manuel Gebetsberger, Robert Swap, R. Bradley Pierce, Caroline R. Nowlan, Gonzalo González Abad, Amin Nehrir, and David Williams
Atmos. Meas. Tech., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, https://doi.org/10.5194/amt-13-6113-2020, 2020
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This paper evaluates Sentinel-5P TROPOMI v1.2 NO2 tropospheric columns over New York City using data from airborne mapping spectrometers and a network of ground-based spectrometers (Pandora) collected in 2018. These evaluations consider impacts due to cloud parameters, a priori profile assumptions, and spatial and temporal variability. Overall, TROPOMI tropospheric NO2 columns appear to have a low bias in this region.
Antje Ludewig, Quintus Kleipool, Rolf Bartstra, Robin Landzaat, Jonatan Leloux, Erwin Loots, Peter Meijering, Emiel van der Plas, Nico Rozemeijer, Frank Vonk, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 3561–3580, https://doi.org/10.5194/amt-13-3561-2020, https://doi.org/10.5194/amt-13-3561-2020, 2020
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After the Sentinel-5 Precursor satellite launch on 13 October 2017, its single payload, the TROPOspheric Monitoring Instrument (TROPOMI), was tested and calibrated extensively. Changes due to ageing of the instrument and new insights have led to updates to the L1b processor and its calibration key data, leading to improvements of the data quality. Regularly scheduled calibration measurements are used in the nominal operations phase (since 30 April 2018) to correct instrument degradation.
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Maarten Sneep, Mark ter Linden, Jiyunting Sun, and Pieternel F. Levelt
Atmos. Meas. Tech., 13, 3043–3059, https://doi.org/10.5194/amt-13-3043-2020, https://doi.org/10.5194/amt-13-3043-2020, 2020
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This paper presents a first validation of the TROPOspheric Monitoring Instrument (TROPOMI) aerosol layer height (ALH) product, which is an estimate of the height of an aerosol layer using a spectrometer on board ESA's Sentinel-5 Precursor satellite mission. Comparison between the TROPOMI ALH product and co-located aerosol extinction heights from the CALIOP instrument on board NASA's CALIPSO mission show good agreement for selected cases over the ocean and large differences over land.
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, https://doi.org/10.5194/amt-13-1427-2020, 2020
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This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Jos van Geffen, K. Folkert Boersma, Henk Eskes, Maarten Sneep, Mark ter Linden, Marina Zara, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, https://doi.org/10.5194/amt-13-1315-2020, 2020
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The Tropospheric Monitoring Instrument (TROPOMI) provides atmospheric trace gase and cloud and aerosol property measurements at unprecedented spatial resolution. This study focusses on the TROPOMI NO2 slant column density (SCD) retrieval: the retrieval method used, the stability of and uncertainties in the SCDs, and a comparison with Ozone Monitoring Instrument (OMI) NO2 SCDs. TROPOMI shows a superior performance compared to OMI/QA4ECV and operates as anticipated from instrument specifications.
Jiyunting Sun, J. Pepijn Veefkind, Peter van Velthoven, L. Gijsbert Tilstra, Julien Chimot, Swadhin Nanda, and Pieternel F. Levelt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-39, https://doi.org/10.5194/acp-2020-39, 2020
Revised manuscript not accepted
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ALH is one of the major concerns in quantifying aerosol absorption from the ultra-violet aerosol index (UVAI). The UVAI has a global daily record since 1978, whereas a corresponding ALH data set is limited. In this paper, we attempt to construct a global long-term ALH data set derived from the MERRA-2 aerosol fields that can be favorable in interpreting aerosol absorption from UVAI. We also give comments on several satellite ALH products in terms of the UVAI altitude dependence.
Samuel Quesada-Ruiz, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, Andrea Piacentini, Mathieu Joly, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Christiaan Plechelmus Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 131–152, https://doi.org/10.5194/amt-13-131-2020, https://doi.org/10.5194/amt-13-131-2020, 2020
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Mark ter Linden, Maarten Sneep, Johan de Haan, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, https://doi.org/10.5194/amt-12-6619-2019, 2019
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This paper discusses a neural network forward model used by the operational aerosol layer height (ALH) retrieval algorithm for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Sentinel-5 Precursor satellite mission. This model replaces online radiative transfer calculations within the oxygen A-band, improving the speed of the algorithm by 3 orders of magnitude. With this advancement in the algorithm's speed, TROPOMI is set to deliver the ALH product operationally.
Jiyunting Sun, Pepijn Veefkind, Swadhin Nanda, Peter van Velthoven, and Pieternel Levelt
Atmos. Meas. Tech., 12, 6319–6340, https://doi.org/10.5194/amt-12-6319-2019, https://doi.org/10.5194/amt-12-6319-2019, 2019
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Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing assessment. This paper presents two methods to retrieve SSA from satellite observations of the near-UV absorbing aerosol index (UVAI). The first is physically based radiative transfer simulations; the second is a statistically based machine learning algorithm. The result of the latter is encouraging. Both methods show that the ALH is necessary to quantitatively interpret aerosol absorption from UVAI.
Renske Timmermans, Arjo Segers, Lyana Curier, Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Henk Eskes, Johan de Haan, Jukka Kujanpää, William Lahoz, Albert Oude Nijhuis, Samuel Quesada-Ruiz, Philippe Ricaud, Pepijn Veefkind, and Martijn Schaap
Atmos. Chem. Phys., 19, 12811–12833, https://doi.org/10.5194/acp-19-12811-2019, https://doi.org/10.5194/acp-19-12811-2019, 2019
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We present an evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for air quality analyses of NO2. For this, synthetic observations for both missions are generated and combined with a chemistry transport model. While hourly Sentinel-4 NO2 observations over Europe benefit modelled NO2 analyses throughout the entire day, daily Sentinel-5P NO2 observations with global coverage show an impact up to 3–6 h after overpass. This supports the need for a combination of missions.
Julien Chimot, J. Pepijn Veefkind, Johan F. de Haan, Piet Stammes, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 491–516, https://doi.org/10.5194/amt-12-491-2019, https://doi.org/10.5194/amt-12-491-2019, 2019
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The reference OMI tropospheric NO2 product was reprocessed by new aerosol correction parameters retrieved from the 477 nm O2–O2 band over eastern China and South America for 2 years. These new parameters are from different and separate algorithms, allowing improved use of the 477 nm O2–O2 band. All the tested approaches improve the aerosol correction in the OMI tropospheric NO2 product. We demonstrate the possibility of applying an explicit aerosol correction based on the 477 nm O2–O2 band.
Quintus Kleipool, Antje Ludewig, Ljubiša Babić, Rolf Bartstra, Remco Braak, Werner Dierssen, Pieter-Jan Dewitte, Pepijn Kenter, Robin Landzaat, Jonatan Leloux, Erwin Loots, Peter Meijering, Emiel van der Plas, Nico Rozemeijer, Dinand Schepers, Daniel Schiavini, Joost Smeets, Giuseppe Vacanti, Frank Vonk, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 6439–6479, https://doi.org/10.5194/amt-11-6439-2018, https://doi.org/10.5194/amt-11-6439-2018, 2018
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This paper reports on the pre-launch calibration of the TROPOMI instrument on board ESA's Sentinel 5P satellite. This calibration is needed to convert the raw instrument digital data to physical quantities like Earth radiance and Sun irradiance. From these quantities atmospheric properties can be derived. The paper shows that the chosen approach to calibration and analysis was successful and that
the achieved accuracy makes high-quality observations of the Earth's atmosphere feasible.
Jiyunting Sun, J. Pepijn Veefkind, Peter van Velthoven, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 5261–5277, https://doi.org/10.5194/amt-11-5261-2018, https://doi.org/10.5194/amt-11-5261-2018, 2018
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Near-UV AAI is a qualitative parameter detecting the elevated absorbing aerosol layer. A long-term AAI record of satellite observations has the potential to quantify aerosol absorption on a global scale. Our study presents the possibility of retrieving single-scattering albedo with OMI-measured AAI. The comparison with AERONET is satisfactory and further research will be on how the aerosol wavelength-dependent refractive index and aerosol profile affect the quantification of aerosol absorption.
Swadhin Nanda, J. Pepijn Veefkind, Martin de Graaf, Maarten Sneep, Piet Stammes, Johan F. de Haan, Abram F. J. Sanders, Arnoud Apituley, Olaf Tuinder, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 3263–3280, https://doi.org/10.5194/amt-11-3263-2018, https://doi.org/10.5194/amt-11-3263-2018, 2018
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An approach to estimate the height of aerosol plumes over land from satellite measurements of the oxygen A band is proposed. The method, termed dynamic scaling, forces the retrieval to use spectral points that contain more height information. The method is tested in a synthetic environment as well as with GOME-2A and GOME-2B measurements of wildfire plumes over Europe, with very encouraging results. This method can be easily applied to other aerosol height algorithms using least squares.
Arve Kylling, Sophie Vandenbussche, Virginie Capelle, Juan Cuesta, Lars Klüser, Luca Lelli, Thomas Popp, Kerstin Stebel, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 2911–2936, https://doi.org/10.5194/amt-11-2911-2018, https://doi.org/10.5194/amt-11-2911-2018, 2018
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The aerosol layer height is one of four aerosol parameters which is needed to enhance our understanding of aerosols' role in the climate system. Both active and passive measurement methods may be used to estimate the aerosol layer height. Aerosol height estimates made from passive infrared and solar satellite sensors measurements are compared with satellite-borne lidar estimates. There is considerable variation between the retrieved dust heights and how they compare with the lidar.
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.
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
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The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Julien Chimot, J. Pepijn Veefkind, Tim Vlemmix, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 2257–2277, https://doi.org/10.5194/amt-11-2257-2018, https://doi.org/10.5194/amt-11-2257-2018, 2018
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Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2–O2 band and its spatial pattern evaluated over selected cloud-free scenes. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in east China shows consistent spatial patterns. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South America and Russia.
Swadhin Nanda, Martin de Graaf, Maarten Sneep, Johan F. de Haan, Piet Stammes, Abram F. J. Sanders, Olaf Tuinder, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 161–175, https://doi.org/10.5194/amt-11-161-2018, https://doi.org/10.5194/amt-11-161-2018, 2018
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Estimating aerosol layer height in the atmosphere from satellite data in the oxygen A band (758–770 nm) over land is challenging over land, since the surface is generally very bright in this wavelength region. This paper discusses an interplay between the surface and the atmosphere in their contributions to the top-of-atmosphere reflectance spectrum and the consequent biases obtained while estimating aerosol layer height, using synthetic data and real data from the GOME-2 satellite instrument.
Tim Vlemmix, Xinrui (Jerry) Ge, Bryan T. G. de Goeij, Len F. van der Wal, Gerard C. J. Otter, Piet Stammes, Ping Wang, Alexis Merlaud, Dirk Schüttemeyer, Andreas C. Meier, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-257, https://doi.org/10.5194/amt-2017-257, 2017
Revised manuscript has not been submitted
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We present a first analysis of UV/VIS spectral measurements obtained with the Spectrolite Breadboard Instrument (developed by TNO, The Netherlands) during the AROMAPEX campaign held in Berlin in April 2016 (campaign supported by ESA and EUFAR). This new sensor was used to measure air pollution in the form of tropospheric NO2 columns. The study focuses specifically on the retrieval of surface reflectances, an important intermediate step towards the final product.
V. M. Erik Schenkeveld, Glen Jaross, Sergey Marchenko, David Haffner, Quintus L. Kleipool, Nico C. Rozemeijer, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 10, 1957–1986, https://doi.org/10.5194/amt-10-1957-2017, https://doi.org/10.5194/amt-10-1957-2017, 2017
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The Ozone Monitoring Instrument (OMI) has been flying on NASA’s EOS Aura satellite since July 15, 2004. It has measured the concentration of trace gasses in the atmosphere, like ozone, NO2 and SO2. This article describes the trend in performance and calibration parameters of OMI during 12 years of flight. The degradation of the CCD detectors, solar diffusers, spectral calibration and row anomaly are shown. The instrument shows overall degradation that is better than expected.
Julien Chimot, J. Pepijn Veefkind, Tim Vlemmix, Johan F. de Haan, Vassilis Amiridis, Emmanouil Proestakis, Eleni Marinou, and Pieternel F. Levelt
Atmos. Meas. Tech., 10, 783–809, https://doi.org/10.5194/amt-10-783-2017, https://doi.org/10.5194/amt-10-783-2017, 2017
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We have developed artificial neural network algorithms to retrieve aerosol layer height from satellite OMI observations of the 477 nm O2–O2 spectral band. Based on 3-year (2005–2007) cloud-free scenes over north-east Asia, the results show uncertainties of 260–800 m when aerosol optical thickness is larger than 1. These algorithms also enable aerosol optical thickness retrievals by exploring the OMI continuum reflectance. These results may be used for future trace gas retrievals from TROPOMI.
Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Philippe Ricaud, William Lahoz, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, https://doi.org/10.5194/acp-17-1081-2017, 2017
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A detailed Observing System Simulation Experiment is performed to quantify the impact of future satellite instrument S-5P carbon monoxide (CO) on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode. S-5P is able to capture the CO from forest fires that occurred in Portugal. Furthermore, our results provide evidence of S-5P CO benefits for monitoring processes contributing to atmospheric pollution.
J. H. G. M. van Geffen, K. F. Boersma, M. Van Roozendael, F. Hendrick, E. Mahieu, I. De Smedt, M. Sneep, and J. P. Veefkind
Atmos. Meas. Tech., 8, 1685–1699, https://doi.org/10.5194/amt-8-1685-2015, https://doi.org/10.5194/amt-8-1685-2015, 2015
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The paper describes improvements to the algorithm for the retrieval of nitrogen dioxide (NO2) concentration from measurements of the Ozone Monitoring Instrument (OMI), launched on board NASA's EOS-Aura satellite in 2004. With these improvements - updates of the wavelength calibration and the reference spectra - the OMI results are consistent with independent NO2 measurements and the overall quality of the spectral fit is improved considerably.
M. Belmonte Rivas, P. Veefkind, F. Boersma, P. Levelt, H. Eskes, and J. Gille
Atmos. Meas. Tech., 7, 2203–2225, https://doi.org/10.5194/amt-7-2203-2014, https://doi.org/10.5194/amt-7-2203-2014, 2014
A. Määttä, M. Laine, J. Tamminen, and J. P. Veefkind
Atmos. Meas. Tech., 7, 1185–1199, https://doi.org/10.5194/amt-7-1185-2014, https://doi.org/10.5194/amt-7-1185-2014, 2014
C. A. McLinden, V. Fioletov, K. F. Boersma, S. K. Kharol, N. Krotkov, L. Lamsal, P. A. Makar, R. V. Martin, J. P. Veefkind, and K. Yang
Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, https://doi.org/10.5194/acp-14-3637-2014, 2014
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.
Mengyao Liu, Ronald van der A, Michiel van Weele, Lotte Bryan, Henk Eskes, Pepijn Veefkind, Yongxue Liu, Xiaojuan Lin, Jos de Laat, and Jieying Ding
Atmos. Meas. Tech., 17, 5261–5277, https://doi.org/10.5194/amt-17-5261-2024, https://doi.org/10.5194/amt-17-5261-2024, 2024
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A new divergence method was developed and applied to estimate methane emissions from TROPOMI observations over the Middle East, where it is typically challenging for a satellite to measure methane due to its complicated orography and surface albedo. Our results show the potential of TROPOMI to quantify methane emissions from various sources rather than big emitters from space after objectively excluding the artifacts in the retrieval.
Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw
EGUsphere, https://doi.org/10.5194/egusphere-2024-2352, https://doi.org/10.5194/egusphere-2024-2352, 2024
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Currently measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver-Julesburg basin where agriculture and methane extraction infrastructure is often co-located.
Arno Keppens, Serena Di Pede, Daan Hubert, Jean-Christopher Lambert, Pepijn Veefkind, Maarten Sneep, Johan De Haan, Mark ter Linden, Thierry Leblanc, Steven Compernolle, Tijl Verhoelst, José Granville, Oindrila Nath, Ann Mari Fjæraa, Ian Boyd, Sander Niemeijer, Roeland Van Malderen, Herman G. J. Smit, Valentin Duflot, Sophie Godin-Beekmann, Bryan J. Johnson, Wolfgang Steinbrecht, David W. Tarasick, Debra E. Kollonige, Ryan M. Stauffer, Anne M. Thompson, Angelika Dehn, and Claus Zehner
Atmos. Meas. Tech., 17, 3969–3993, https://doi.org/10.5194/amt-17-3969-2024, https://doi.org/10.5194/amt-17-3969-2024, 2024
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The Sentinel-5P satellite operated by the European Space Agency has carried the TROPOspheric Monitoring Instrument (TROPOMI) around the Earth since October 2017. This mission also produces atmospheric ozone profile data which are described in detail for May 2018 to April 2023. Independent validation using ground-based reference measurements demonstrates that the operational ozone profile product mostly fully and at least partially complies with all mission requirements.
Yutao Chen, Ronald J. van der A, Jieying Ding, Henk Eskes, Jason E. Williams, Nicolas Theys, Athanasios Tsikerdekis, and Pieternel F. Levelt
EGUsphere, https://doi.org/10.5194/egusphere-2024-1094, https://doi.org/10.5194/egusphere-2024-1094, 2024
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There is a lack of local SO2 top-down emission inventories in India. With the improvement in the divergence method and the derivation of SO2 local lifetime, gridded SO2 emissions over a large area can be estimated efficiently. This method can be applied to any region in the world to derive SO2 emissions. Especially for regions with high latitudes, our methodology has the potential to significantly improve the top-down derivation of SO2 emission estimates.
Adrianus de Laat, Jos van Geffen, Piet Stammes, Ronald van der A, Henk Eskes, and J. Pepijn Veefkind
Atmos. Chem. Phys., 24, 4511–4535, https://doi.org/10.5194/acp-24-4511-2024, https://doi.org/10.5194/acp-24-4511-2024, 2024
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Removal of stratospheric nitrogen oxides is crucial for the formation of the ozone hole. TROPOMI satellite measurements of nitrogen dioxide reveal the presence of a not dissimilar "nitrogen hole" that largely coincides with the ozone hole. Three very distinct regimes were identified: inside and outside the ozone hole and the transition zone in between. Our results introduce a valuable and innovative application highly relevant for Antarctic ozone hole and ozone layer recovery.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Konstantinos Michailidis, Maria-Elissavet Koukouli, Dimitris Balis, J. Pepijn Veefkind, Martin de Graaf, Lucia Mona, Nikolaos Papagianopoulos, Gesolmina Pappalardo, Ioanna Tsikoudi, Vassilis Amiridis, Eleni Marinou, Anna Gialitaki, Rodanthi-Elisavet Mamouri, Argyro Nisantzi, Daniele Bortoli, Maria João Costa, Vanda Salgueiro, Alexandros Papayannis, Maria Mylonaki, Lucas Alados-Arboledas, Salvatore Romano, Maria Rita Perrone, and Holger Baars
Atmos. Chem. Phys., 23, 1919–1940, https://doi.org/10.5194/acp-23-1919-2023, https://doi.org/10.5194/acp-23-1919-2023, 2023
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Comparisons with ground-based correlative lidar measurements constitute a key component in the validation of satellite aerosol products. This paper presents the validation of the TROPOMI aerosol layer height (ALH) product, using archived quality assured ground-based data from lidar stations that belong to the EARLINET network. Comparisons between the TROPOMI ALH and co-located EARLINET measurements show good agreement over the ocean.
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023, https://doi.org/10.5194/gmd-16-509-2023, 2023
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We focus on the challenges associated with comparing atmospheric composition models with satellite products such as tropospheric NO2 columns. The aim is to highlight the methodological difficulties and propose sound ways of doing such comparisons. Building on the comparisons, a new satellite product is proposed and made available, which takes advantage of higher-resolution, regional atmospheric modelling to improve estimates of troposheric NO2 columns over Europe.
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.
Johan F. de Haan, Ping Wang, Maarten Sneep, J. Pepijn Veefkind, and Piet Stammes
Geosci. Model Dev., 15, 7031–7050, https://doi.org/10.5194/gmd-15-7031-2022, https://doi.org/10.5194/gmd-15-7031-2022, 2022
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We present an overview of the DISAMAR radiative transfer code, highlighting the novel semi-analytical derivatives for the doubling–adding formulae and the new DISMAS technique for weak absorbers. DISAMAR includes forward simulations and retrievals for satellite spectral measurements from 270 to 2400 nm to determine instrument specifications for passive remote sensing. It has been used in various Sentinel-4/5P/5 projects and in the TROPOMI aerosol layer height and ozone profile products.
John T. Sullivan, Arnoud Apituley, Nora Mettig, Karin Kreher, K. Emma Knowland, Marc Allaart, Ankie Piters, Michel Van Roozendael, Pepijn Veefkind, Jerry R. Ziemke, Natalya Kramarova, Mark Weber, Alexei Rozanov, Laurence Twigg, Grant Sumnicht, and Thomas J. McGee
Atmos. Chem. Phys., 22, 11137–11153, https://doi.org/10.5194/acp-22-11137-2022, https://doi.org/10.5194/acp-22-11137-2022, 2022
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A TROPOspheric Monitoring Instrument (TROPOMI) validation campaign (TROLIX-19) was held in the Netherlands in September 2019. The research presented here focuses on using ozone lidars from NASA’s Goddard Space Flight Center to better evaluate the characterization of ozone throughout TROLIX-19 as compared to balloon-borne, space-borne and ground-based passive measurements, as well as a global coupled chemistry meteorology model.
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.
Quintus Kleipool, Nico Rozemeijer, Mirna van Hoek, Jonatan Leloux, Erwin Loots, Antje Ludewig, Emiel van der Plas, Daley Adrichem, Raoul Harel, Simon Spronk, Mark ter Linden, Glen Jaross, David Haffner, Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 15, 3527–3553, https://doi.org/10.5194/amt-15-3527-2022, https://doi.org/10.5194/amt-15-3527-2022, 2022
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A new collection-4 dataset for the Ozone Monitoring Instrument (OMI) mission has been established to supersede the current collection-3 level-1b (L1b) data, produced with a newly developed L01b data processor based on the TROPOspheric Monitoring Instrument (TROPOMI) L01b processor. The collection-4 L1b data have a similar output format to the TROPOMI L1b data for easy connection of the data series. Many insights from the TROPOMI algorithms, as well as from OMI collection-3 usage, were included.
Nora Mettig, Mark Weber, Alexei Rozanov, John P. Burrows, Pepijn Veefkind, Anne M. Thompson, Ryan M. Stauffer, Thierry Leblanc, Gerard Ancellet, Michael J. Newchurch, Shi Kuang, Rigel Kivi, Matthew B. Tully, Roeland Van Malderen, Ankie Piters, Bogumil Kois, René Stübi, and Pavla Skrivankova
Atmos. Meas. Tech., 15, 2955–2978, https://doi.org/10.5194/amt-15-2955-2022, https://doi.org/10.5194/amt-15-2955-2022, 2022
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Vertical ozone profiles from combined spectral measurements in the UV and IR spectral ranges were retrieved by using data from TROPOMI/S5P and CrIS/Suomi-NPP. The vertical resolution and accuracy of the ozone profiles are improved by combining both wavelength ranges compared to retrievals limited to UV or IR spectral data only. The advancement of our TOPAS algorithm for combined measurements is required because in the UV-only retrieval the vertical resolution in the troposphere is very limited.
Jos van Geffen, Henk Eskes, Steven Compernolle, Gaia Pinardi, Tijl Verhoelst, Jean-Christopher Lambert, Maarten Sneep, Mark ter Linden, Antje Ludewig, K. Folkert Boersma, and J. Pepijn Veefkind
Atmos. Meas. Tech., 15, 2037–2060, https://doi.org/10.5194/amt-15-2037-2022, https://doi.org/10.5194/amt-15-2037-2022, 2022
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Nitrogen dioxide (NO2) is one of the main data products measured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite. This study describes improvements in the TROPOMI NO2 retrieval leading to version v2.2, operational since 1 July 2021. It compares results with previous versions v1.2–v1.4 and with Ozone Monitoring Instrument (OMI) and ground-based measurements.
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.
Nora Mettig, Mark Weber, Alexei Rozanov, Carlo Arosio, John P. Burrows, Pepijn Veefkind, Anne M. Thompson, Richard Querel, Thierry Leblanc, Sophie Godin-Beekmann, Rigel Kivi, and Matthew B. Tully
Atmos. Meas. Tech., 14, 6057–6082, https://doi.org/10.5194/amt-14-6057-2021, https://doi.org/10.5194/amt-14-6057-2021, 2021
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TROPOMI is a nadir-viewing satellite that has observed global atmospheric trace gases at unprecedented spatial resolution since 2017. The retrieval of ozone profiles with high accuracy has been demonstrated using the TOPAS (Tikhonov regularised Ozone Profile retrievAl with SCIATRAN) algorithm and applying appropriate spectral corrections to TROPOMI UV data. Ozone profiles from TROPOMI were compared to ozonesonde and lidar profiles, showing an agreement to within 5 % in the stratosphere.
Lily N. Zhang, Susan Solomon, Kane A. Stone, Jonathan D. Shanklin, Joshua D. Eveson, Steve Colwell, John P. Burrows, Mark Weber, Pieternel F. Levelt, Natalya A. Kramarova, and David P. Haffner
Atmos. Chem. Phys., 21, 9829–9838, https://doi.org/10.5194/acp-21-9829-2021, https://doi.org/10.5194/acp-21-9829-2021, 2021
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In the 1980s, measurements at the British Antarctic Survey station in Halley, Antarctica, led to the discovery of the ozone hole. The Halley total ozone record continues to be uniquely valuable for studies of long-term changes in Antarctic ozone. Environmental conditions in 2017 forced a temporary cessation of operations, leading to a gap in the historic record. We develop and test a method for filling in the Halley record using satellite data and find evidence to further support ozone recovery.
Frederik Tack, Alexis Merlaud, Marian-Daniel Iordache, Gaia Pinardi, Ermioni Dimitropoulou, Henk Eskes, Bart Bomans, Pepijn Veefkind, and Michel Van Roozendael
Atmos. Meas. Tech., 14, 615–646, https://doi.org/10.5194/amt-14-615-2021, https://doi.org/10.5194/amt-14-615-2021, 2021
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We assess the TROPOMI tropospheric NO2 product (OFFL v1.03.01; 3.5 km × 7 km at nadir observations) based on coinciding airborne APEX reference observations (~75 m × 120 m), acquired over polluted regions in Belgium. The TROPOMI NO2 product meets the mission requirements in terms of precision and accuracy. However, we show that TROPOMI is biased low over polluted areas, mainly due to the limited spatial resolution of a priori input for the AMF computation.
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
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This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Ivar R. van der Velde, Guido R. van der Werf, Sander Houweling, Henk J. Eskes, J. Pepijn Veefkind, Tobias Borsdorff, and Ilse Aben
Atmos. Chem. Phys., 21, 597–616, https://doi.org/10.5194/acp-21-597-2021, https://doi.org/10.5194/acp-21-597-2021, 2021
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This paper compares the relative atmospheric enhancements of CO and NO2 measured by the space-based instrument TROPOMI over different fire-prone ecosystems around the world. We find distinct spatial and temporal patterns in the ΔNO2 / ΔCO ratio that correspond to regional differences in combustion efficiency. This joint analysis provides a better understanding of regional-scale combustion characteristics and can help the fire modeling community to improve existing global emission inventories.
Maurits L. Kooreman, Piet Stammes, Victor Trees, Maarten Sneep, L. Gijsbert Tilstra, Martin de Graaf, Deborah C. Stein Zweers, Ping Wang, Olaf N. E. Tuinder, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 6407–6426, https://doi.org/10.5194/amt-13-6407-2020, https://doi.org/10.5194/amt-13-6407-2020, 2020
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We investigated the influence of clouds on the Absorbing Aerosol Index (AAI), an indicator of the presence of small particles in the atmosphere. Clouds produce artifacts in AAI calculations on the individual measurement (7 km) scale, which was not seen with previous instruments, as well as on large (1000+ km) scales. To reduce these artefacts, we used three different AAI calculation techniques of varying complexity. We find that the AAI artifacts are reduced when using more complex techniques.
Laura M. Judd, Jassim A. Al-Saadi, James J. Szykman, Lukas C. Valin, Scott J. Janz, Matthew G. Kowalewski, Henk J. Eskes, J. Pepijn Veefkind, Alexander Cede, Moritz Mueller, Manuel Gebetsberger, Robert Swap, R. Bradley Pierce, Caroline R. Nowlan, Gonzalo González Abad, Amin Nehrir, and David Williams
Atmos. Meas. Tech., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, https://doi.org/10.5194/amt-13-6113-2020, 2020
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This paper evaluates Sentinel-5P TROPOMI v1.2 NO2 tropospheric columns over New York City using data from airborne mapping spectrometers and a network of ground-based spectrometers (Pandora) collected in 2018. These evaluations consider impacts due to cloud parameters, a priori profile assumptions, and spatial and temporal variability. Overall, TROPOMI tropospheric NO2 columns appear to have a low bias in this region.
Antje Ludewig, Quintus Kleipool, Rolf Bartstra, Robin Landzaat, Jonatan Leloux, Erwin Loots, Peter Meijering, Emiel van der Plas, Nico Rozemeijer, Frank Vonk, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 3561–3580, https://doi.org/10.5194/amt-13-3561-2020, https://doi.org/10.5194/amt-13-3561-2020, 2020
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After the Sentinel-5 Precursor satellite launch on 13 October 2017, its single payload, the TROPOspheric Monitoring Instrument (TROPOMI), was tested and calibrated extensively. Changes due to ageing of the instrument and new insights have led to updates to the L1b processor and its calibration key data, leading to improvements of the data quality. Regularly scheduled calibration measurements are used in the nominal operations phase (since 30 April 2018) to correct instrument degradation.
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Maarten Sneep, Mark ter Linden, Jiyunting Sun, and Pieternel F. Levelt
Atmos. Meas. Tech., 13, 3043–3059, https://doi.org/10.5194/amt-13-3043-2020, https://doi.org/10.5194/amt-13-3043-2020, 2020
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This paper presents a first validation of the TROPOspheric Monitoring Instrument (TROPOMI) aerosol layer height (ALH) product, which is an estimate of the height of an aerosol layer using a spectrometer on board ESA's Sentinel-5 Precursor satellite mission. Comparison between the TROPOMI ALH product and co-located aerosol extinction heights from the CALIOP instrument on board NASA's CALIPSO mission show good agreement for selected cases over the ocean and large differences over land.
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, https://doi.org/10.5194/amt-13-1427-2020, 2020
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This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Jos van Geffen, K. Folkert Boersma, Henk Eskes, Maarten Sneep, Mark ter Linden, Marina Zara, and J. Pepijn Veefkind
Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, https://doi.org/10.5194/amt-13-1315-2020, 2020
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The Tropospheric Monitoring Instrument (TROPOMI) provides atmospheric trace gase and cloud and aerosol property measurements at unprecedented spatial resolution. This study focusses on the TROPOMI NO2 slant column density (SCD) retrieval: the retrieval method used, the stability of and uncertainties in the SCDs, and a comparison with Ozone Monitoring Instrument (OMI) NO2 SCDs. TROPOMI shows a superior performance compared to OMI/QA4ECV and operates as anticipated from instrument specifications.
Jiyunting Sun, J. Pepijn Veefkind, Peter van Velthoven, L. Gijsbert Tilstra, Julien Chimot, Swadhin Nanda, and Pieternel F. Levelt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-39, https://doi.org/10.5194/acp-2020-39, 2020
Revised manuscript not accepted
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ALH is one of the major concerns in quantifying aerosol absorption from the ultra-violet aerosol index (UVAI). The UVAI has a global daily record since 1978, whereas a corresponding ALH data set is limited. In this paper, we attempt to construct a global long-term ALH data set derived from the MERRA-2 aerosol fields that can be favorable in interpreting aerosol absorption from UVAI. We also give comments on several satellite ALH products in terms of the UVAI altitude dependence.
Samuel Quesada-Ruiz, Jean-Luc Attié, William A. Lahoz, Rachid Abida, Philippe Ricaud, Laaziz El Amraoui, Régina Zbinden, Andrea Piacentini, Mathieu Joly, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Christiaan Plechelmus Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Meas. Tech., 13, 131–152, https://doi.org/10.5194/amt-13-131-2020, https://doi.org/10.5194/amt-13-131-2020, 2020
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Mark ter Linden, Maarten Sneep, Johan de Haan, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, https://doi.org/10.5194/amt-12-6619-2019, 2019
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This paper discusses a neural network forward model used by the operational aerosol layer height (ALH) retrieval algorithm for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Sentinel-5 Precursor satellite mission. This model replaces online radiative transfer calculations within the oxygen A-band, improving the speed of the algorithm by 3 orders of magnitude. With this advancement in the algorithm's speed, TROPOMI is set to deliver the ALH product operationally.
Jiyunting Sun, Pepijn Veefkind, Swadhin Nanda, Peter van Velthoven, and Pieternel Levelt
Atmos. Meas. Tech., 12, 6319–6340, https://doi.org/10.5194/amt-12-6319-2019, https://doi.org/10.5194/amt-12-6319-2019, 2019
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Single scattering albedo (SSA) is critical for reducing uncertainties in radiative forcing assessment. This paper presents two methods to retrieve SSA from satellite observations of the near-UV absorbing aerosol index (UVAI). The first is physically based radiative transfer simulations; the second is a statistically based machine learning algorithm. The result of the latter is encouraging. Both methods show that the ALH is necessary to quantitatively interpret aerosol absorption from UVAI.
Renske Timmermans, Arjo Segers, Lyana Curier, Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Henk Eskes, Johan de Haan, Jukka Kujanpää, William Lahoz, Albert Oude Nijhuis, Samuel Quesada-Ruiz, Philippe Ricaud, Pepijn Veefkind, and Martijn Schaap
Atmos. Chem. Phys., 19, 12811–12833, https://doi.org/10.5194/acp-19-12811-2019, https://doi.org/10.5194/acp-19-12811-2019, 2019
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We present an evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for air quality analyses of NO2. For this, synthetic observations for both missions are generated and combined with a chemistry transport model. While hourly Sentinel-4 NO2 observations over Europe benefit modelled NO2 analyses throughout the entire day, daily Sentinel-5P NO2 observations with global coverage show an impact up to 3–6 h after overpass. This supports the need for a combination of missions.
Julien Chimot, J. Pepijn Veefkind, Johan F. de Haan, Piet Stammes, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 491–516, https://doi.org/10.5194/amt-12-491-2019, https://doi.org/10.5194/amt-12-491-2019, 2019
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The reference OMI tropospheric NO2 product was reprocessed by new aerosol correction parameters retrieved from the 477 nm O2–O2 band over eastern China and South America for 2 years. These new parameters are from different and separate algorithms, allowing improved use of the 477 nm O2–O2 band. All the tested approaches improve the aerosol correction in the OMI tropospheric NO2 product. We demonstrate the possibility of applying an explicit aerosol correction based on the 477 nm O2–O2 band.
Quintus Kleipool, Antje Ludewig, Ljubiša Babić, Rolf Bartstra, Remco Braak, Werner Dierssen, Pieter-Jan Dewitte, Pepijn Kenter, Robin Landzaat, Jonatan Leloux, Erwin Loots, Peter Meijering, Emiel van der Plas, Nico Rozemeijer, Dinand Schepers, Daniel Schiavini, Joost Smeets, Giuseppe Vacanti, Frank Vonk, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 6439–6479, https://doi.org/10.5194/amt-11-6439-2018, https://doi.org/10.5194/amt-11-6439-2018, 2018
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This paper reports on the pre-launch calibration of the TROPOMI instrument on board ESA's Sentinel 5P satellite. This calibration is needed to convert the raw instrument digital data to physical quantities like Earth radiance and Sun irradiance. From these quantities atmospheric properties can be derived. The paper shows that the chosen approach to calibration and analysis was successful and that
the achieved accuracy makes high-quality observations of the Earth's atmosphere feasible.
Dejian Fu, Susan S. Kulawik, Kazuyuki Miyazaki, Kevin W. Bowman, John R. Worden, Annmarie Eldering, Nathaniel J. Livesey, Joao Teixeira, Fredrick W. Irion, Robert L. Herman, Gregory B. Osterman, Xiong Liu, Pieternel F. Levelt, Anne M. Thompson, and Ming Luo
Atmos. Meas. Tech., 11, 5587–5605, https://doi.org/10.5194/amt-11-5587-2018, https://doi.org/10.5194/amt-11-5587-2018, 2018
Jiyunting Sun, J. Pepijn Veefkind, Peter van Velthoven, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 5261–5277, https://doi.org/10.5194/amt-11-5261-2018, https://doi.org/10.5194/amt-11-5261-2018, 2018
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Near-UV AAI is a qualitative parameter detecting the elevated absorbing aerosol layer. A long-term AAI record of satellite observations has the potential to quantify aerosol absorption on a global scale. Our study presents the possibility of retrieving single-scattering albedo with OMI-measured AAI. The comparison with AERONET is satisfactory and further research will be on how the aerosol wavelength-dependent refractive index and aerosol profile affect the quantification of aerosol absorption.
Swadhin Nanda, J. Pepijn Veefkind, Martin de Graaf, Maarten Sneep, Piet Stammes, Johan F. de Haan, Abram F. J. Sanders, Arnoud Apituley, Olaf Tuinder, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 3263–3280, https://doi.org/10.5194/amt-11-3263-2018, https://doi.org/10.5194/amt-11-3263-2018, 2018
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An approach to estimate the height of aerosol plumes over land from satellite measurements of the oxygen A band is proposed. The method, termed dynamic scaling, forces the retrieval to use spectral points that contain more height information. The method is tested in a synthetic environment as well as with GOME-2A and GOME-2B measurements of wildfire plumes over Europe, with very encouraging results. This method can be easily applied to other aerosol height algorithms using least squares.
Arve Kylling, Sophie Vandenbussche, Virginie Capelle, Juan Cuesta, Lars Klüser, Luca Lelli, Thomas Popp, Kerstin Stebel, and Pepijn Veefkind
Atmos. Meas. Tech., 11, 2911–2936, https://doi.org/10.5194/amt-11-2911-2018, https://doi.org/10.5194/amt-11-2911-2018, 2018
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The aerosol layer height is one of four aerosol parameters which is needed to enhance our understanding of aerosols' role in the climate system. Both active and passive measurement methods may be used to estimate the aerosol layer height. Aerosol height estimates made from passive infrared and solar satellite sensors measurements are compared with satellite-borne lidar estimates. There is considerable variation between the retrieved dust heights and how they compare with the lidar.
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.
Pieternel F. Levelt, Joanna Joiner, Johanna Tamminen, J. Pepijn Veefkind, Pawan K. Bhartia, Deborah C. Stein Zweers, Bryan N. Duncan, David G. Streets, Henk Eskes, Ronald van der A, Chris McLinden, Vitali Fioletov, Simon Carn, Jos de Laat, Matthew DeLand, Sergey Marchenko, Richard McPeters, Jerald Ziemke, Dejian Fu, Xiong Liu, Kenneth Pickering, Arnoud Apituley, Gonzalo González Abad, Antti Arola, Folkert Boersma, Christopher Chan Miller, Kelly Chance, Martin de Graaf, Janne Hakkarainen, Seppo Hassinen, Iolanda Ialongo, Quintus Kleipool, Nickolay Krotkov, Can Li, Lok Lamsal, Paul Newman, Caroline Nowlan, Raid Suleiman, Lieuwe Gijsbert Tilstra, Omar Torres, Huiqun Wang, and Krzysztof Wargan
Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, https://doi.org/10.5194/acp-18-5699-2018, 2018
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The aim of this paper is to highlight the many successes of the Ozone Monitoring Instrument (OMI) spanning more than 13 years. Data from OMI have been used in a wide range of applications. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. OMI data continue to be used for new research and applications.
Julien Chimot, J. Pepijn Veefkind, Tim Vlemmix, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 2257–2277, https://doi.org/10.5194/amt-11-2257-2018, https://doi.org/10.5194/amt-11-2257-2018, 2018
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Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2–O2 band and its spatial pattern evaluated over selected cloud-free scenes. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in east China shows consistent spatial patterns. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South America and Russia.
Jacob C. A. van Peet, Ronald J. van der A, Hennie M. Kelder, and Pieternel F. Levelt
Atmos. Chem. Phys., 18, 1685–1704, https://doi.org/10.5194/acp-18-1685-2018, https://doi.org/10.5194/acp-18-1685-2018, 2018
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Ozone profiles measured by two satellite instruments (GOME-2A and OMI) have been combined with a chemical transport model using data assimilation. The results give a better insight into the global spatial and temporal ozone distribution than either measurement or model results alone. Validation with independent measurements shows biases varying between -5 % and +10 % between the surface and 100 hPa, while between 100 and 10 hPa the biases vary between -3 % and +3 %.
Swadhin Nanda, Martin de Graaf, Maarten Sneep, Johan F. de Haan, Piet Stammes, Abram F. J. Sanders, Olaf Tuinder, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 11, 161–175, https://doi.org/10.5194/amt-11-161-2018, https://doi.org/10.5194/amt-11-161-2018, 2018
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Estimating aerosol layer height in the atmosphere from satellite data in the oxygen A band (758–770 nm) over land is challenging over land, since the surface is generally very bright in this wavelength region. This paper discusses an interplay between the surface and the atmosphere in their contributions to the top-of-atmosphere reflectance spectrum and the consequent biases obtained while estimating aerosol layer height, using synthetic data and real data from the GOME-2 satellite instrument.
Tim Vlemmix, Xinrui (Jerry) Ge, Bryan T. G. de Goeij, Len F. van der Wal, Gerard C. J. Otter, Piet Stammes, Ping Wang, Alexis Merlaud, Dirk Schüttemeyer, Andreas C. Meier, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-257, https://doi.org/10.5194/amt-2017-257, 2017
Revised manuscript has not been submitted
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We present a first analysis of UV/VIS spectral measurements obtained with the Spectrolite Breadboard Instrument (developed by TNO, The Netherlands) during the AROMAPEX campaign held in Berlin in April 2016 (campaign supported by ESA and EUFAR). This new sensor was used to measure air pollution in the form of tropospheric NO2 columns. The study focuses specifically on the retrieval of surface reflectances, an important intermediate step towards the final product.
Jieying Ding, Kazuyuki Miyazaki, Ronald Johannes van der A, Bas Mijling, Jun-ichi Kurokawa, SeogYeon Cho, Greet Janssens-Maenhout, Qiang Zhang, Fei Liu, and Pieternel Felicitas Levelt
Atmos. Chem. Phys., 17, 10125–10141, https://doi.org/10.5194/acp-17-10125-2017, https://doi.org/10.5194/acp-17-10125-2017, 2017
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To evaluate the quality of the satellite-derived NOx emissions, we compare nine emission inventories of nitrogen oxides including four satellite-derived NOx inventories and bottom-up inventories for East Asia. The temporal and spatial distribution of NOx emissions over East Asia are evaluated. We analyse the differences in satellite-derived emissions from two different inversion methods. The paper ends with recommendations for future improvements of emission estimates.
V. M. Erik Schenkeveld, Glen Jaross, Sergey Marchenko, David Haffner, Quintus L. Kleipool, Nico C. Rozemeijer, J. Pepijn Veefkind, and Pieternel F. Levelt
Atmos. Meas. Tech., 10, 1957–1986, https://doi.org/10.5194/amt-10-1957-2017, https://doi.org/10.5194/amt-10-1957-2017, 2017
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The Ozone Monitoring Instrument (OMI) has been flying on NASA’s EOS Aura satellite since July 15, 2004. It has measured the concentration of trace gasses in the atmosphere, like ozone, NO2 and SO2. This article describes the trend in performance and calibration parameters of OMI during 12 years of flight. The degradation of the CCD detectors, solar diffusers, spectral calibration and row anomaly are shown. The instrument shows overall degradation that is better than expected.
Jieying Ding, Ronald Johannes van der A, Bas Mijling, and Pieternel Felicitas Levelt
Atmos. Meas. Tech., 10, 925–938, https://doi.org/10.5194/amt-10-925-2017, https://doi.org/10.5194/amt-10-925-2017, 2017
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We improve the DECSO algorithm for NOx emission estimates from satellite observations, especially over remote regions. The accuracy is about 20 percent for monthly NOx emissions with a spatial resolution of 0.25 degrees. We are able to distinguish ship emissions below the outflow of NO2 from the mainland of China.
Julien Chimot, J. Pepijn Veefkind, Tim Vlemmix, Johan F. de Haan, Vassilis Amiridis, Emmanouil Proestakis, Eleni Marinou, and Pieternel F. Levelt
Atmos. Meas. Tech., 10, 783–809, https://doi.org/10.5194/amt-10-783-2017, https://doi.org/10.5194/amt-10-783-2017, 2017
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We have developed artificial neural network algorithms to retrieve aerosol layer height from satellite OMI observations of the 477 nm O2–O2 spectral band. Based on 3-year (2005–2007) cloud-free scenes over north-east Asia, the results show uncertainties of 260–800 m when aerosol optical thickness is larger than 1. These algorithms also enable aerosol optical thickness retrievals by exploring the OMI continuum reflectance. These results may be used for future trace gas retrievals from TROPOMI.
Rachid Abida, Jean-Luc Attié, Laaziz El Amraoui, Philippe Ricaud, William Lahoz, Henk Eskes, Arjo Segers, Lyana Curier, Johan de Haan, Jukka Kujanpää, Albert Oude Nijhuis, Johanna Tamminen, Renske Timmermans, and Pepijn Veefkind
Atmos. Chem. Phys., 17, 1081–1103, https://doi.org/10.5194/acp-17-1081-2017, https://doi.org/10.5194/acp-17-1081-2017, 2017
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A detailed Observing System Simulation Experiment is performed to quantify the impact of future satellite instrument S-5P carbon monoxide (CO) on tropospheric analyses and forecasts. We focus on Europe for the period of northern summer 2003, when there was a severe heat wave episode. S-5P is able to capture the CO from forest fires that occurred in Portugal. Furthermore, our results provide evidence of S-5P CO benefits for monitoring processes contributing to atmospheric pollution.
Nickolay A. Krotkov, Chris A. McLinden, Can Li, Lok N. Lamsal, Edward A. Celarier, Sergey V. Marchenko, William H. Swartz, Eric J. Bucsela, Joanna Joiner, Bryan N. Duncan, K. Folkert Boersma, J. Pepijn Veefkind, Pieternel F. Levelt, Vitali E. Fioletov, Russell R. Dickerson, Hao He, Zifeng Lu, and David G. Streets
Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, https://doi.org/10.5194/acp-16-4605-2016, 2016
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We examine changes in SO2 and NO2 over the world's most polluted regions during the first decade of Aura OMI observations. Over the eastern US, both NO2 and SO2 levels decreased by 40 % and 80 %, respectively. OMI confirmed large reductions in SO2 over eastern Europe's largest coal power plants. The North China Plain has the world's most severe SO2 pollution, but a decreasing trend been observed since 2011, with a 50 % reduction in 2012–2014. India's SO2 and NO2 levels are growing at a fast pace.
J. Chimot, T. Vlemmix, J. P. Veefkind, J. F. de Haan, and P. F. Levelt
Atmos. Meas. Tech., 9, 359–382, https://doi.org/10.5194/amt-9-359-2016, https://doi.org/10.5194/amt-9-359-2016, 2016
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The interplay between aerosols and the OMI O2–O2 cloud retrieval algorithm is analysed in detail to evaluate the impacts on the accuracy of the tropospheric NO2 retrievals over cloud-free scenes. Collocated OMI NO2 and MODIS Aqua aerosol products are compared over E China, in industrialized areas; the OMI O2–O2 cloud retrieval algorithm is implemented on synthetic study cases dominated by aerosol particles. The resulting biases highlight the need for an improved aerosol correction.
M. Belmonte Rivas, P. Veefkind, H. Eskes, and P. Levelt
Atmos. Chem. Phys., 15, 13519–13553, https://doi.org/10.5194/acp-15-13519-2015, https://doi.org/10.5194/acp-15-13519-2015, 2015
A. F. J. Sanders, J. F. de Haan, M. Sneep, A. Apituley, P. Stammes, M. O. Vieitez, L. G. Tilstra, O. N. E. Tuinder, C. E. Koning, and J. P. Veefkind
Atmos. Meas. Tech., 8, 4947–4977, https://doi.org/10.5194/amt-8-4947-2015, https://doi.org/10.5194/amt-8-4947-2015, 2015
P. Castellanos, K. F. Boersma, O. Torres, and J. F. de Haan
Atmos. Meas. Tech., 8, 3831–3849, https://doi.org/10.5194/amt-8-3831-2015, https://doi.org/10.5194/amt-8-3831-2015, 2015
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Inaccuracies in the retrieval of NO2 tropospheric columns due to the radiative effects of light-absorbing aerosols are not well understood. Here we explicitly account for the effects of aerosols in the Dutch OMI NO2 (DOMINO) tropospheric AMF calculation by including aerosol observations collocated with OMI pixels. The AMF calculations that included aerosol absorption and scattering were on average 10% higher than traditional AMFs. Errors can reach a factor of 2 for individual pixels.
J. Ding, R. J. van der A, B. Mijling, P. F. Levelt, and N. Hao
Atmos. Chem. Phys., 15, 9399–9412, https://doi.org/10.5194/acp-15-9399-2015, https://doi.org/10.5194/acp-15-9399-2015, 2015
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We derived the NOx emissions from the OMI satellite observations. We find a NOx emission reduction of at least 25% during the Youth Olympic Games in Nanjing in 2014. The emission estimate algorithm has detected an emission reduction of 10% during the Chinese Spring Festival. This paper also shows that the observed concentrations and the derived emissions from space have different patterns that provide complimentary information.
J. H. G. M. van Geffen, K. F. Boersma, M. Van Roozendael, F. Hendrick, E. Mahieu, I. De Smedt, M. Sneep, and J. P. Veefkind
Atmos. Meas. Tech., 8, 1685–1699, https://doi.org/10.5194/amt-8-1685-2015, https://doi.org/10.5194/amt-8-1685-2015, 2015
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The paper describes improvements to the algorithm for the retrieval of nitrogen dioxide (NO2) concentration from measurements of the Ozone Monitoring Instrument (OMI), launched on board NASA's EOS-Aura satellite in 2004. With these improvements - updates of the wavelength calibration and the reference spectra - the OMI results are consistent with independent NO2 measurements and the overall quality of the spectral fit is improved considerably.
T. Vlemmix, F. Hendrick, G. Pinardi, I. De Smedt, C. Fayt, C. Hermans, A. Piters, P. Wang, P. Levelt, and M. Van Roozendael
Atmos. Meas. Tech., 8, 941–963, https://doi.org/10.5194/amt-8-941-2015, https://doi.org/10.5194/amt-8-941-2015, 2015
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Two methods are compared to retrieve aerosols, formaldehyde and nitrogen dioxide in the lower troposphere from ground-based remote sensing observations of scattered sunlight in multiple viewing directions. Observations were done in the Beijing area (2008–2011). The two methods show good agreement with respect to the total amount (vertical column) and reasonable agreement with respect to concentrations near the surface and first-order estimates of the vertical profile shape.
T. Mielonen, J. F. de Haan, J. C. A. van Peet, M. Eremenko, and J. P. Veefkind
Atmos. Meas. Tech., 8, 671–687, https://doi.org/10.5194/amt-8-671-2015, https://doi.org/10.5194/amt-8-671-2015, 2015
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In this paper, we have assessed the sensitivity of the operational Ozone Monitoring Instrument ozone profile retrieval algorithm to a number of a priori and radiative transfer assumptions. We then modified the algorithm to improve the retrieval of tropospheric ozone. We found that the modified retrieval unmasks systematic problems in the radiative transfer/instrument model and is more sensitive to tropospheric ozone variation: it is able to capture the tropospheric ozone morphology better.
M. Belmonte Rivas, P. Veefkind, F. Boersma, P. Levelt, H. Eskes, and J. Gille
Atmos. Meas. Tech., 7, 2203–2225, https://doi.org/10.5194/amt-7-2203-2014, https://doi.org/10.5194/amt-7-2203-2014, 2014
B. Hassler, I. Petropavlovskikh, J. Staehelin, T. August, P. K. Bhartia, C. Clerbaux, D. Degenstein, M. De Mazière, B. M. Dinelli, A. Dudhia, G. Dufour, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, J. Granville, N. R. P. Harris, K. Hoppel, D. Hubert, Y. Kasai, M. J. Kurylo, E. Kyrölä, J.-C. Lambert, P. F. Levelt, C. T. McElroy, R. D. McPeters, R. Munro, H. Nakajima, A. Parrish, P. Raspollini, E. E. Remsberg, K. H. Rosenlof, A. Rozanov, T. Sano, Y. Sasano, M. Shiotani, H. G. J. Smit, G. Stiller, J. Tamminen, D. W. Tarasick, J. Urban, R. J. van der A, J. P. Veefkind, C. Vigouroux, T. von Clarmann, C. von Savigny, K. A. Walker, M. Weber, J. Wild, and J. M. Zawodny
Atmos. Meas. Tech., 7, 1395–1427, https://doi.org/10.5194/amt-7-1395-2014, https://doi.org/10.5194/amt-7-1395-2014, 2014
A. Määttä, M. Laine, J. Tamminen, and J. P. Veefkind
Atmos. Meas. Tech., 7, 1185–1199, https://doi.org/10.5194/amt-7-1185-2014, https://doi.org/10.5194/amt-7-1185-2014, 2014
C. A. McLinden, V. Fioletov, K. F. Boersma, S. K. Kharol, N. Krotkov, L. Lamsal, P. A. Makar, R. V. Martin, J. P. Veefkind, and K. Yang
Atmos. Chem. Phys., 14, 3637–3656, https://doi.org/10.5194/acp-14-3637-2014, https://doi.org/10.5194/acp-14-3637-2014, 2014
J. C. A. van Peet, R. J. van der A, O. N. E. Tuinder, E. Wolfram, J. Salvador, P. F. Levelt, and H. M. Kelder
Atmos. Meas. Tech., 7, 859–876, https://doi.org/10.5194/amt-7-859-2014, https://doi.org/10.5194/amt-7-859-2014, 2014
A. F. J. Sanders and J. F. de Haan
Atmos. Meas. Tech., 6, 2725–2740, https://doi.org/10.5194/amt-6-2725-2013, https://doi.org/10.5194/amt-6-2725-2013, 2013
Related subject area
Subject: Clouds | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
3D cloud masking across a broad swath using multi-angle polarimetry and deep learning
Dual-frequency (Ka-band and G-band) radar estimates of liquid water content profiles in shallow clouds
Retrieval of cloud fraction and optical thickness of liquid water clouds over the ocean from multi-angle polarization observations
Severe-hail detection with C-band dual-polarisation radars using convolutional neural networks
Retrieval of cloud fraction using machine learning algorithms based on FY-4A AGRI observations
PEAKO and peakTree: tools for detecting and interpreting peaks in cloud radar Doppler spectra – capabilities and limitations
An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI
Contrail altitude estimation using GOES-16 ABI data and deep learning
The Ice Cloud Imager: retrieval of frozen water column properties
Supercooled liquid water cloud classification using lidar backscatter peak properties
Marine cloud base height retrieval from MODIS cloud properties using machine learning
How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties
ampycloud: an open-source algorithm to determine cloud base heights and sky coverage fractions from ceilometer data
Retrieving cloud base height and geometric thickness using the oxygen A-band channel of GCOM-C/SGLI
Simulation and detection efficiency analysis for measurements of polar mesospheric clouds using a spaceborne wide-field-of-view ultraviolet imager
The Chalmers Cloud Ice Climatology: retrieval implementation and validation
The algorithm of microphysical-parameter profiles of aerosol and small cloud droplets based on the dual-wavelength lidar data
Bayesian cloud-top phase determination for Meteosat Second Generation
Lidar–radar synergistic method to retrieve ice, supercooled water and mixed-phase cloud properties
Deriving cloud droplet number concentration from surface-based remote sensors with an emphasis on lidar measurements
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Discriminating between "Drizzle or rain" and sea salt aerosols in Cloudnet for measurements over the Barbados Cloud Observatory
JAXA Level 2 cloud and precipitation microphysics retrievals based on EarthCARE CPR, ATLID and MSI
Identification of ice-over-water multilayer clouds using multispectral satellite data in an artificial neural network
A new approach to crystal habit retrieval from far-infrared spectral radiance measurements
Multiple-scattering effects on single-wavelength lidar sounding of multi-layered clouds
Optimal estimation of cloud properties from thermal infrared observations with a combination of deep learning and radiative transfer simulation
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations
Infrared Radiometric Image Classification and Segmentation of Cloud Structure Using Deep-learning Framework for Ground-based Infrared Thermal Camera Observations
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
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization
Particle inertial effects on radar Doppler spectra simulation
Detection of aerosol and cloud features for the EarthCARE atmospheric lidar (ATLID): the ATLID FeatureMask (A-FM) product
A unified synergistic retrieval of clouds, aerosols, and precipitation from EarthCARE: the ACM-CAP product
Incorporating EarthCARE observations into a multi-lidar cloud climate record: the ATLID (Atmospheric Lidar) cloud climate product
Introduction to EarthCARE synthetic data using a global storm-resolving simulation
Validation of a camera-based intra-hour irradiance nowcasting model using synthetic cloud data
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.
Athina Argyrouli, Diego Loyola, Fabian Romahn, Ronny Lutz, Víctor Molina García, Pascal Hedelt, Klaus-Peter Heue, and Richard Siddans
Atmos. Meas. Tech., 17, 6345–6367, https://doi.org/10.5194/amt-17-6345-2024, https://doi.org/10.5194/amt-17-6345-2024, 2024
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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.
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.
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.
Takashi M. Nagao, Kentaroh Suzuki, and Makoto Kuji
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-141, https://doi.org/10.5194/amt-2024-141, 2024
Revised manuscript accepted for AMT
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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 instrument on JAXA’s GCOM-C satellite to estimate CBH together with other cloud properties. This algorithm can provide global distributions of CBH across various cloud types, including liquid, ice, and mixed-phase clouds.
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.
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.
Johanna Roschke, Jonas Witthuhn, Marcus Klingebiel, Moritz Haarig, Andreas Foth, Anton Kötsche, and Heike Kalesse-Los
EGUsphere, https://doi.org/10.5194/egusphere-2024-894, https://doi.org/10.5194/egusphere-2024-894, 2024
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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 the measurements over the Barbados Cloud Observatory (BCO). A first-ever analysis of the Cloudnet product including the new "haze echo" target over two years at the BCO is presented.
Kaori Sato, Hajime Okamoto, Tomoaki Nishizawa, Yoshitaka Jin, Takashi Nakajima, Minrui Wang, Masaki Satoh, Woosub Roh, Hiroshi Ishimoto, and Rei Kudo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-99, https://doi.org/10.5194/amt-2024-99, 2024
Revised manuscript accepted for AMT
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This study introduces the JAXA EarthCARE 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 will be 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.
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.
He Huang, Quan Wang, Chao Liu, and Chen Zhou
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-87, https://doi.org/10.5194/amt-2024-87, 2024
Revised manuscript accepted for AMT
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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 initial guesses, and a radiative transfer model is used to create radiance lookup tables for later iteration processes. The new method combines the advantages of traditional and machine learning algorithms, and is applicable both daytime and nighttime conditions.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-40, https://doi.org/10.5194/amt-2024-40, 2024
Revised manuscript accepted for AMT
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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 measured that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
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.
Jesse Loveridge, Aviad Levis, Larry Di Girolamo, Vadim Holodovsky, Linda Forster, Anthony B. Davis, and Yoav Y. Schechner
Atmos. Meas. Tech., 16, 3931–3957, https://doi.org/10.5194/amt-16-3931-2023, https://doi.org/10.5194/amt-16-3931-2023, 2023
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We test a new method for measuring the 3D spatial variations of water within clouds, using measurements of reflections of the Sun's light observed at multiple angles by satellites. This is a great improvement on older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
Zeen Zhu, Pavlos Kollias, and Fan Yang
Atmos. Meas. Tech., 16, 3727–3737, https://doi.org/10.5194/amt-16-3727-2023, https://doi.org/10.5194/amt-16-3727-2023, 2023
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We show that large rain droplets, with large inertia, are unable to follow the rapid change of velocity field in a turbulent environment. A lack of consideration for this inertial effect leads to an artificial broadening of the Doppler spectrum from the conventional simulator. Based on the physics-based simulation, we propose a new approach to generate the radar Doppler spectra. This simulator provides a valuable tool to decode cloud microphysical and dynamical properties from radar observation.
Gerd-Jan van Zadelhoff, David P. Donovan, and Ping Wang
Atmos. Meas. Tech., 16, 3631–3651, https://doi.org/10.5194/amt-16-3631-2023, https://doi.org/10.5194/amt-16-3631-2023, 2023
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The Earth Clouds, Aerosols and Radiation (EarthCARE) satellite mission features the UV lidar ATLID. The ATLID FeatureMask algorithm provides a high-resolution detection probability mask which is used to guide smoothing strategies within the ATLID profile retrieval algorithm, one step further in the EarthCARE level-2 processing chain, in which the microphysical retrievals and target classification are performed.
Shannon L. Mason, Robin J. Hogan, Alessio Bozzo, and Nicola L. Pounder
Atmos. Meas. Tech., 16, 3459–3486, https://doi.org/10.5194/amt-16-3459-2023, https://doi.org/10.5194/amt-16-3459-2023, 2023
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We present a method for accurately estimating the contents and properties of clouds, snow, rain, and aerosols through the atmosphere, using the combined measurements of the radar, lidar, and radiometer instruments aboard the upcoming EarthCARE satellite, and evaluate the performance of the retrieval, using test scenes simulated from a numerical forecast model. When EarthCARE is in operation, these quantities and their estimated uncertainties will be distributed in a data product called ACM-CAP.
Artem G. Feofilov, Hélène Chepfer, Vincent Noël, and Frederic Szczap
Atmos. Meas. Tech., 16, 3363–3390, https://doi.org/10.5194/amt-16-3363-2023, https://doi.org/10.5194/amt-16-3363-2023, 2023
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The response of clouds to human-induced climate warming remains the largest source of uncertainty in model predictions of climate. We consider cloud retrievals from spaceborne observations, the existing CALIOP lidar and future ATLID lidar; show how they compare for the same scenes; and discuss the advantage of adding a new lidar for detecting cloud changes in the long run. We show that ATLID's advanced technology should allow for better detecting thinner clouds during daytime than before.
Woosub Roh, Masaki Satoh, Tempei Hashino, Shuhei Matsugishi, Tomoe Nasuno, and Takuji Kubota
Atmos. Meas. Tech., 16, 3331–3344, https://doi.org/10.5194/amt-16-3331-2023, https://doi.org/10.5194/amt-16-3331-2023, 2023
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JAXA EarthCARE synthetic data (JAXA L1 data) were compiled using the global storm-resolving model (GSRM) NICAM (Nonhydrostatic ICosahedral
Atmospheric Model) simulation with 3.5 km horizontal resolution and the Joint-Simulator. JAXA L1 data are intended to support the development of JAXA retrieval algorithms for the EarthCARE sensor before launch of the satellite. The expected orbit of EarthCARE and horizontal sampling of each sensor were used to simulate the signals.
Philipp Gregor, Tobias Zinner, Fabian Jakub, and Bernhard Mayer
Atmos. Meas. Tech., 16, 3257–3271, https://doi.org/10.5194/amt-16-3257-2023, https://doi.org/10.5194/amt-16-3257-2023, 2023
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This work introduces MACIN, a model for short-term forecasting of direct irradiance for solar energy applications. MACIN exploits cloud images of multiple cameras to predict irradiance. The model is applied to artificial images of clouds from a weather model. The artificial cloud data allow for a more in-depth evaluation and attribution of errors compared with real data. Good performance of derived cloud information and significant forecast improvements over a baseline forecast were found.
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Short summary
The Ozone Monitoring Instrument (OMI) on board the NASA EOS Aura satellite monitors the concentrations of trace gases. The accuracy of such observations relies partly on information on clouds. The OMI OMCLDO2 product derives the cloud fraction and pressure from the observed radiance in the visible. This paper reports on an improved version of this product. Compared to the previous version, the changes in cloud fraction are very small, but the changes in the cloud pressure can be significant.
The Ozone Monitoring Instrument (OMI) on board the NASA EOS Aura satellite monitors the...
