Articles | Volume 18, issue 1
https://doi.org/10.5194/amt-18-73-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-73-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cancellation of cloud shadow effects in the absorbing aerosol index retrieval algorithm of TROPOMI
Research & Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Department of Geoscience & Remote Sensing, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, the Netherlands
Ping Wang
Research & Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Piet Stammes
Research & Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Lieuwe G. Tilstra
Research & Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
David P. Donovan
Research & Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA, De Bilt, the Netherlands
Department of Geoscience & Remote Sensing, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, the Netherlands
A. Pier Siebesma
Department of Geoscience & Remote Sensing, Delft University of Technology, Stevinweg 1, 2628 CN, Delft, the Netherlands
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Victor J. H. Trees, Ping Wang, Job I. Wiltink, Piet Stammes, Daphne M. Stam, David P. Donovan, and A. Pier Siebesma
EGUsphere, https://doi.org/10.5194/egusphere-2025-2197, https://doi.org/10.5194/egusphere-2025-2197, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We present MONKI (Monte Carlo KNMI), an efficient and accurate radiative transfer code written in Fortran. MONKI computes total and polarised radiances reflected and transmitted by planetary atmospheres, accounting for polarisation in all scattering orders. MONKI handles both homogeneous atmospheres and 3D cloud structures. MONKI has been validated, and produces reliable results even for planets with optically thick, strongly polarising atmospheres.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
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This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 15, 3121–3140, https://doi.org/10.5194/amt-15-3121-2022, https://doi.org/10.5194/amt-15-3121-2022, 2022
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Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution. These shadows contaminate TROPOMI's air quality measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a satellite spectrometer.
Victor Trees, Ping Wang, and Piet Stammes
Atmos. Chem. Phys., 21, 8593–8614, https://doi.org/10.5194/acp-21-8593-2021, https://doi.org/10.5194/acp-21-8593-2021, 2021
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Given the time and location of a point on the Earth's surface, we explain how to compute the wavelength-dependent obscuration during solar eclipses. We restore the top-of-atmosphere reflectances and the absorbing aerosol index in the partial Moon shadow during the solar eclipses on 26 December 2019 and 21 June 2020 measured by TROPOMI. This correction method resolves eclipse anomalies and allows for study of the effect of solar eclipses on the composition of the Earth's atmosphere from space.
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.
Victor J. H. Trees, Ping Wang, Job I. Wiltink, Piet Stammes, Daphne M. Stam, David P. Donovan, and A. Pier Siebesma
EGUsphere, https://doi.org/10.5194/egusphere-2025-2197, https://doi.org/10.5194/egusphere-2025-2197, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
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We present MONKI (Monte Carlo KNMI), an efficient and accurate radiative transfer code written in Fortran. MONKI computes total and polarised radiances reflected and transmitted by planetary atmospheres, accounting for polarisation in all scattering orders. MONKI handles both homogeneous atmospheres and 3D cloud structures. MONKI has been validated, and produces reliable results even for planets with optically thick, strongly polarising atmospheres.
Martin de Graaf, Maarten Sneep, Mark ter Linden, L. Gijsbert Tilstra, David P. Donovan, Gerd-Jan van Zadelhoff, and J. Pepijn Veefkind
Atmos. Meas. Tech., 18, 2553–2571, https://doi.org/10.5194/amt-18-2553-2025, https://doi.org/10.5194/amt-18-2553-2025, 2025
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The aerosol layer height (ALH) from the TROPOspheric Monitoring Instrument (TROPOMI) has been constantly improved since its release in 2019. Over bright surfaces, fitting the albedo improved the retrieval, as shown for a set of situations, ranging from multiple layers of smoke to thick desert dust plumes and low-altitude industrial pollution. The latest results of the operational ALH are compared to profiles from the ATmospheric LIDar (ATLID) on board the recently launched EarthCARE mission.
Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
Atmos. Meas. Tech., 18, 1961–1979, https://doi.org/10.5194/amt-18-1961-2025, https://doi.org/10.5194/amt-18-1961-2025, 2025
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Long-term records of plant fluorescence offer vital insights into changing vegetation activity. The GOME-2A sensor provides extensive global observations but suffers from calibration and instrument degradation, which affects data consistency. This study presents the SIFTER v3 algorithm, which effectively resolves these issues and includes other improvements, resulting in robust, accurate, and consistent GOME-2A fluorescence measurements from 2007 to 2017.
Peristera Paschou, Nikolaos Siomos, Eleni Marinou, Antonis Gkikas, Samira Moussa Idrissa, Daniel Tetteh Quaye, Désire Degbe Fiogbe Attannon, Kalliopi Artemis Voudouri, Charikleia Meleti, David Patric Donovan, George Georgoussis, Tommaso Parrinello, Thorsten Fehr, Jonas von Bismarck, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2025-1152, https://doi.org/10.5194/egusphere-2025-1152, 2025
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This study presents the results from a validation study on the Level 2A products (aerosol optical properties) of the European Space Agency’s Aeolus mission. Measurements from the eVe lidar, a combined linear/circular polarization and Raman lidar and ESA’s ground reference system, that have been collected during the ASKOS/JATAC campaign are compared with collocated Aeolus Level 2A profiles obtained from the latest version (Baseline 16) of the available SCA, MLE, and AEL-PRO Aeolus algorithms.
Konstantinos Rizos, Emmanouil Proestakis, Thanasis Georgiou, Antonis Gkikas, Eleni Marinou, Peristera Paschou, Kalliopi Artemis Voudouri, Athanasios Tsikerdekis, David Donovan, Gerd-Jan van Zadelhoff, Angela Benedetti, Holger Baars, Athena Augusta Floutsi, Nikos Benas, Martin Stengel, Christian Retscher, Edward Malina, and Vassilis Amiridis
EGUsphere, https://doi.org/10.5194/egusphere-2025-1175, https://doi.org/10.5194/egusphere-2025-1175, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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The Aeolus satellite's lidar system had limitations in detecting certain atmospheric layers and distinguishing between aerosol and cloud types. To improve accuracy, a new dust detection product was developed. By combining data from various sources and validating it with ground-based measurements, this enhanced product performs better than the original. It helps improve dust transport models and weather predictions, making it a valuable tool for atmospheric monitoring and forecasting.
Laura Köhler, Julia Windmiller, Dariusz Baranowski, Michał Brennek, Michał Ciuryło, Lennéa Hayo, Daniel Kȩpski, Stefan Kinne, Beata Latos, Bertrand Lobo, Tobias Marke, Timo Nischik, Daria Paul, Piet Stammes, Artur Szkop, and Olaf Tuinder
Earth Syst. Sci. Data, 17, 633–659, https://doi.org/10.5194/essd-17-633-2025, https://doi.org/10.5194/essd-17-633-2025, 2025
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We present atmospheric and oceanic data from the Atlantic References and Convection ship campaign with the Maria S. Merian from Mindelo to Punta Arenas observed with the integrated ship sensors; humidity and temperature profiler; ceilometer; aerosol instruments (Calitoo, Microtops, and DustTrak); radiosondes; uncrewed aircraft vehicles; and conductivity, temperature, and depth scans. The data include three complete profiles of the Intertropical Convergence Zone and a storm in the South Atlantic.
Lev D. Labzovskii, Gerd-Jan van Zadelhoff, David P. Donovan, Jos de Kloe, L. Gijsbert Tilstra, Ad Stoffelen, Damien Josset, and Piet Stammes
Atmos. Meas. Tech., 17, 7183–7208, https://doi.org/10.5194/amt-17-7183-2024, https://doi.org/10.5194/amt-17-7183-2024, 2024
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The Atmospheric Laser Doppler Instrument (ALADIN) on the Aeolus satellite was the first of its kind to measure high-resolution vertical profiles of aerosols and cloud properties from space. We present an algorithm that produces Aeolus lidar surface returns (LSRs), containing useful information for measuring UV reflectivity. Aeolus LSRs matched well with existing UV reflectivity data from other satellites, like GOME-2 and TROPOMI, and demonstrated excellent sensitivity to modeled snow cover.
Ping Wang, David Patrick Donovan, Gerd-Jan van Zadelhoff, Jos de Kloe, Dorit Huber, and Katja Reissig
Atmos. Meas. Tech., 17, 5935–5955, https://doi.org/10.5194/amt-17-5935-2024, https://doi.org/10.5194/amt-17-5935-2024, 2024
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We describe the new feature mask (AEL-FM) and aerosol profile retrieval (AEL-PRO) algorithms developed for Aeolus lidar and present the evaluation of the Aeolus products using CALIPSO data for dust aerosols over Africa. We have found that Aeolus and CALIPSO show similar aerosol patterns in the collocated orbits and have good agreement for the extinction coefficients for the dust aerosols, especially for the cloud-free scenes. The finding is applicable to Aeolus L2A product Baseline 17.
David Patrick Donovan, Gerd-Jan van Zadelhoff, and Ping Wang
Atmos. Meas. Tech., 17, 5301–5340, https://doi.org/10.5194/amt-17-5301-2024, https://doi.org/10.5194/amt-17-5301-2024, 2024
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ATLID (atmospheric lidar) is the lidar to be flown on the Earth Clouds and Radiation Explorer satellite (EarthCARE). EarthCARE is a joint European–Japanese satellite mission that was launched in May 2024. ATLID is an advanced lidar optimized for cloud and aerosol property profile measurements. This paper describes some of the key novel algorithms being applied to this lidar to retrieve cloud and aerosol properties. Example results based on simulated data are presented and discussed.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Juliëtte C. S. Anema, Klaas Folkert Boersma, Piet Stammes, Gerbrand Koren, William Woodgate, Philipp Köhler, Christian Frankenberg, and Jacqui Stol
Biogeosciences, 21, 2297–2311, https://doi.org/10.5194/bg-21-2297-2024, https://doi.org/10.5194/bg-21-2297-2024, 2024
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To keep the Paris agreement goals within reach, negative emissions are necessary. They can be achieved with mitigation techniques, such as reforestation, which remove CO2 from the atmosphere. While governments have pinned their hopes on them, there is not yet a good set of tools to objectively determine whether negative emissions do what they promise. Here we show how satellite measurements of plant fluorescence are useful in detecting carbon uptake due to reforestation and vegetation regrowth.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
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HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Nicole Docter, Anja Hünerbein, David P. Donovan, Rene Preusker, Jürgen Fischer, Jan Fokke Meirink, Piet Stammes, and Michael Eisinger
Atmos. Meas. Tech., 17, 2507–2519, https://doi.org/10.5194/amt-17-2507-2024, https://doi.org/10.5194/amt-17-2507-2024, 2024
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MSI is the imaging spectrometer on board EarthCARE and will provide across-track information on clouds and aerosol properties. The MSI solar channels exhibit a spectral misalignment effect (SMILE) in the measurements. This paper describes and evaluates how the SMILE will affect the cloud and aerosol retrievals that do not account for it.
Lieuwe G. Tilstra, Martin de Graaf, Victor J. H. Trees, Pavel Litvinov, Oleg Dubovik, and Piet Stammes
Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, https://doi.org/10.5194/amt-17-2235-2024, 2024
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This paper introduces a new surface albedo climatology of directionally dependent Lambertian-equivalent reflectivity (DLER) observed by TROPOMI on the Sentinel-5 Precursor satellite. The database contains monthly fields of DLER for 21 wavelength bands at a relatively high spatial resolution of 0.125 by 0.125 degrees. The anisotropy of the surface reflection is handled by parameterisation of the viewing angle dependence.
Shannon L. Mason, Howard W. Barker, Jason N. S. Cole, Nicole Docter, David P. Donovan, Robin J. Hogan, Anja Hünerbein, Pavlos Kollias, Bernat Puigdomènech Treserras, Zhipeng Qu, Ulla Wandinger, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 17, 875–898, https://doi.org/10.5194/amt-17-875-2024, https://doi.org/10.5194/amt-17-875-2024, 2024
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When the EarthCARE mission enters its operational phase, many retrieval data products will be available, which will overlap both in terms of the measurements they use and the geophysical quantities they report. In this pre-launch study, we use simulated EarthCARE scenes to compare the coverage and performance of many data products from the European Space Agency production model, with the intention of better understanding the relation between products and providing a compact guide to users.
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.
David P. Donovan, Pavlos Kollias, Almudena Velázquez Blázquez, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 5327–5356, https://doi.org/10.5194/amt-16-5327-2023, https://doi.org/10.5194/amt-16-5327-2023, 2023
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The Earth Cloud, Aerosol and Radiation Explorer mission (EarthCARE) is a multi-instrument cloud–aerosol–radiation-oriented satellite for climate and weather applications. For this satellite mission to be successful, the development and implementation of new techniques for turning the measured raw signals into useful data is required. This paper describes how atmospheric model data were used as the basis for creating realistic high-resolution simulated data sets to facilitate this process.
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.
Ulla Wandinger, Moritz Haarig, Holger Baars, David Donovan, and Gerd-Jan van Zadelhoff
Atmos. Meas. Tech., 16, 4031–4052, https://doi.org/10.5194/amt-16-4031-2023, https://doi.org/10.5194/amt-16-4031-2023, 2023
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We introduce the algorithms that have been developed to derive cloud top height and aerosol layer products from observations with the Atmospheric Lidar (ATLID) onboard the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE). The products provide information on the uppermost cloud and geometrical and optical properties of aerosol layers in an atmospheric column. They can be used individually but also serve as input for algorithms that combine observations with EarthCARE’s lidar and imager.
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.
Abdanour Irbah, Julien Delanoë, Gerd-Jan van Zadelhoff, David P. Donovan, Pavlos Kollias, Bernat Puigdomènech Treserras, Shannon Mason, Robin J. Hogan, and Aleksandra Tatarevic
Atmos. Meas. Tech., 16, 2795–2820, https://doi.org/10.5194/amt-16-2795-2023, https://doi.org/10.5194/amt-16-2795-2023, 2023
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The Cloud Profiling Radar (CPR) and ATmospheric LIDar (ATLID) aboard the EarthCARE satellite are used to probe the Earth's atmosphere by measuring cloud and aerosol profiles. ATLID is sensitive to aerosols and small cloud particles and CPR to large ice particles, snowflakes and raindrops. It is the synergy of the measurements of these two instruments that allows a better classification of the atmospheric targets and the description of the associated products, which are the subject of this paper.
Ulla Wandinger, Athena Augusta Floutsi, Holger Baars, Moritz Haarig, Albert Ansmann, Anja Hünerbein, Nicole Docter, David Donovan, Gerd-Jan van Zadelhoff, Shannon Mason, and Jason Cole
Atmos. Meas. Tech., 16, 2485–2510, https://doi.org/10.5194/amt-16-2485-2023, https://doi.org/10.5194/amt-16-2485-2023, 2023
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We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.
Martin de Graaf, Karolina Sarna, Jessica Brown, Elma V. Tenner, Manon Schenkels, and David P. Donovan
Atmos. Chem. Phys., 23, 5373–5391, https://doi.org/10.5194/acp-23-5373-2023, https://doi.org/10.5194/acp-23-5373-2023, 2023
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Clouds over the oceans reflect sunlight and cool the earth. Simultaneous measurements were performed of cloud droplet sizes and smoke particles in and near the cloud base over Ascension Island, a remote island in the Atlantic Ocean, to determine the sensitivity of cloud droplets to smoke from the African continent. The smoke was found to reduce cloud droplet sizes, which makes the cloud droplets more susceptible to evaporation, reducing cloud lifetime.
Congcong Qiao, Song Liu, Juan Huo, Xihan Mu, Ping Wang, Shengjie Jia, Xuehua Fan, and Minzheng Duan
Atmos. Meas. Tech., 16, 1539–1549, https://doi.org/10.5194/amt-16-1539-2023, https://doi.org/10.5194/amt-16-1539-2023, 2023
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We established a spectral-fitting method to derive precipitable water vapor (PWV) and aerosol optical depth based on a strict radiative transfer theory by the spectral measurements of direct sun from EKO MS711 and MS712 spectroradiometers. The retrievals were compared with that of the colocated CE-318 photometer; the results showed a high degree of consistency. In the PWV inversion, a strong water vapor absorption band around 1370 nm is introduced to retrieve PWV in a relatively dry atmosphere.
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.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 15, 3121–3140, https://doi.org/10.5194/amt-15-3121-2022, https://doi.org/10.5194/amt-15-3121-2022, 2022
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Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution. These shadows contaminate TROPOMI's air quality measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a satellite spectrometer.
Wim C. de Rooy, Pier Siebesma, Peter Baas, Geert Lenderink, Stephan R. de Roode, Hylke de Vries, Erik van Meijgaard, Jan Fokke Meirink, Sander Tijm, and Bram van 't Veen
Geosci. Model Dev., 15, 1513–1543, https://doi.org/10.5194/gmd-15-1513-2022, https://doi.org/10.5194/gmd-15-1513-2022, 2022
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This paper describes a comprehensive model update to the boundary layer schemes. Because the involved parameterisations are all built on widely applied frameworks, the here-described modifications are applicable to many NWP and climate models. The model update contains substantial modifications to the cloud, turbulence, and convection schemes and leads to a substantial improvement of several aspects of the model, especially low cloud forecasts.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
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The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Hartwig Deneke, Carola Barrientos-Velasco, Sebastian Bley, Anja Hünerbein, Stephan Lenk, Andreas Macke, Jan Fokke Meirink, Marion Schroedter-Homscheidt, Fabian Senf, Ping Wang, Frank Werner, and Jonas Witthuhn
Atmos. Meas. Tech., 14, 5107–5126, https://doi.org/10.5194/amt-14-5107-2021, https://doi.org/10.5194/amt-14-5107-2021, 2021
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The SEVIRI instrument flown on the European geostationary Meteosat satellites acquires multi-spectral images at a relatively coarse pixel resolution of 3 × 3 km2, but it also has a broadband high-resolution visible channel with 1 × 1 km2 spatial resolution. In this study, the modification of an existing cloud property and solar irradiance retrieval to use this channel to improve the spatial resolution of its output products as well as the resulting benefits for applications are described.
Karolina Sarna, David P. Donovan, and Herman W. J. Russchenberg
Atmos. Meas. Tech., 14, 4959–4970, https://doi.org/10.5194/amt-14-4959-2021, https://doi.org/10.5194/amt-14-4959-2021, 2021
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We show a method for obtaining cloud optical extinction with a lidar system. We use a scheme in which a lidar signal is inverted based on the estimated value of cloud extinction at the far end of the cloud and apply a correction for multiple scattering within the cloud and a range resolution correction. By applying our technique, we show that it is possible to obtain the cloud optical extinction with an error better than 5 % up to 90 m within the cloud.
Victor Trees, Ping Wang, and Piet Stammes
Atmos. Chem. Phys., 21, 8593–8614, https://doi.org/10.5194/acp-21-8593-2021, https://doi.org/10.5194/acp-21-8593-2021, 2021
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Given the time and location of a point on the Earth's surface, we explain how to compute the wavelength-dependent obscuration during solar eclipses. We restore the top-of-atmosphere reflectances and the absorbing aerosol index in the partial Moon shadow during the solar eclipses on 26 December 2019 and 21 June 2020 measured by TROPOMI. This correction method resolves eclipse anomalies and allows for study of the effect of solar eclipses on the composition of the Earth's atmosphere from space.
Steven Compernolle, Athina Argyrouli, Ronny Lutz, Maarten Sneep, Jean-Christopher Lambert, Ann Mari Fjæraa, Daan Hubert, Arno Keppens, Diego Loyola, Ewan O'Connor, Fabian Romahn, Piet Stammes, Tijl Verhoelst, and Ping Wang
Atmos. Meas. Tech., 14, 2451–2476, https://doi.org/10.5194/amt-14-2451-2021, https://doi.org/10.5194/amt-14-2451-2021, 2021
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The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account for cloud interference with the observations, S5P cloud data products (CLOUD OCRA/ROCINN_CAL, OCRA/ROCINN_CRB, and FRESCO) provide vital input: cloud fraction, cloud height, and cloud optical thickness. Here, S5P cloud parameters are validated by comparing with other satellite sensors (VIIRS, MODIS, and OMI) and with ground-based CloudNet data. The agreement depends on product type and cloud height.
Veerle De Bock, Alexander Mangold, L. Gijsbert Tilstra, Olaf N. E. Tuinder, and Andy Delcloo
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-425, https://doi.org/10.5194/amt-2020-425, 2020
Revised manuscript not accepted
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The Absorbing Aerosol Height (AAH) is a new GOME-2 product representing the height of absorbing aerosol layers. In this paper the AAH is validated against the layer height detected by CALIOP. We concluded that the AAH often underestimates the height of volcanic layers, so it should be handled with care when using it for aviation safety purposes. Taking into account the uncertainties, the product can be considered as an important added value for near-real time monitoring of volcanic ash layers.
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, David Donovan, Aleksey Malinka, Jörg Schmidt, Patric Seifert, and Ulla Wandinger
Atmos. Chem. Phys., 20, 15247–15263, https://doi.org/10.5194/acp-20-15247-2020, https://doi.org/10.5194/acp-20-15247-2020, 2020
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A novel lidar method to study cloud microphysical properties (of liquid water clouds) and to study aerosol–cloud interaction (ACI) is developed and presented in this paper. In Part 1, the theoretical framework including an error analysis is given together with an overview of the aerosol information that the same lidar system can obtain. The ACI concept based on aerosol and cloud information is also explained. Applications of the proposed approach to lidar measurements are presented in Part 2.
Cristofer Jimenez, Albert Ansmann, Ronny Engelmann, David Donovan, Aleksey Malinka, Patric Seifert, Robert Wiesen, Martin Radenz, Zhenping Yin, Johannes Bühl, Jörg Schmidt, Boris Barja, and Ulla Wandinger
Atmos. Chem. Phys., 20, 15265–15284, https://doi.org/10.5194/acp-20-15265-2020, https://doi.org/10.5194/acp-20-15265-2020, 2020
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Part 2 presents the application of the dual-FOV polarization lidar technique introduced in Part 1. A lidar system was upgraded with a second polarization telescope, and it was deployed at the southernmost tip of South America. A comparison with alternative remote sensing techniques and the evaluation of the aerosol–cloud–wind relation in a convective boundary layer in pristine marine conditions are presented in two case studies, demonstrating the potential of the approach for ACI studies.
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.
Cited articles
Anderson, G. P.: AFGL Atmospheric Constituent Profiles (0-120km), Tech. Rep. AFGL-TR-86-0110, Air Force Geophys. Lab., Hanscom AFB, MA, 48 pp., 1986. a
Bass, A. M. and Paur, R. J.: The ultraviolet cross-sections of ozone. II. Results and temperature dependence, in: Atmospheric ozone, Proceedings of the Quadrennial, edited by: Zerefos, C. S. and Ghazi, A., 611–616, 1985. a
Beirle, S., Borger, C., Dörner, S., Li, A., Hu, Z., Liu, F., Wang, Y., and Wagner, T.: Pinpointing nitrogen oxide emissions from space, Science Advances, 5, eaax9800, https://doi.org/10.1126/sciadv.aax9800, 2019. a
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov, V. V., Chance, K. V., and Goede, A. P. H.: SCIAMACHY: Mission Objectives and Measurement Modes, J. Atmos. Sci., 56, 127–150, https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999. a
Chandrasekhar, S.: Radiative transfer, Dover Publications, New York, ISBN 10: 0486605906 1960. a
Copernicus Sentinel-5P: TROPOMI Level 2 Ultraviolet Aerosol Index products, Version 01, European Space Agency [data set], https://doi.org/10.5270/S5P-3dgz66p, 2018. a, b
de Graaf, M., Stammes, P., Torres, O., and Koelemeijer, R. B. A.: Absorbing Aerosol Index: Sensitivity analysis, application to GOME and comparison with TOMS, J. Geophys. Res.-Atmos., 110, D01201, https://doi.org/10.1029/2004JD005178, 2005. a, b, c, d
de Rooij, W. A. and van der Stap, C. C. A. H.: Expansion of Mie scattering matrices in generalized spherical functions, Astron. Astrophys., 131, 237–248, 1984. a
Deutschmann, T., Beirle, S., Frieß, U., Grzegorski, M., Kern, C., Kritten, L., Platt, U., Prados-Román, C., Puķī, J., Wagner, T., Werner, B., and Pfeilsticker, K.: The Monte Carlo atmospheric radiative transfer model McArtim: Introduction and validation of Jacobians and 3D features, J. Quant. Spectrosc. Ra., 112, 1119–1137, https://doi.org/10.1016/j.jqsrt.2010.12.009, 2011. a
Georgoulias, A. K., Boersma, K. F., van Vliet, J., Zhang, X., van der A, R., Zanis, P., and de Laat, J.: Detection of NO2 pollution plumes from individual ships with the TROPOMI/S5P satellite sensor, Environ. Res. Lett., 15, 124037, https://doi.org/10.1088/1748-9326/abc445, 2020. a
Hansen, J. E. and Travis, L. D.: Light scattering in planetary atmospheres, Space Sci. Rev., 16, 527–610, https://doi.org/10.1007/BF00168069, 1974. a
Herman, J. R., Bhartia, P. K., Torres, O., Hsu, C., Seftor, C., and Celarier, E.: Global distribution of UV-absorbing aerosols from Nimbus 7/TOMS data, J. Geophys. Res.-Atmos., 102, 16911–16922, https://doi.org/10.1029/96JD03680, 1997. a
Jethva, H., Torres, O., and Ahn, C.: A 12-year long global record of optical depth of absorbing aerosols above the clouds derived from the OMI/OMACA algorithm, Atmos. Meas. Tech., 11, 5837–5864, https://doi.org/10.5194/amt-11-5837-2018, 2018. a
Koelemeijer, R. B. A., Stammes, P., Hovenier, J. W., and de Haan, J. F.: A fast method for retrieval of cloud parameters using oxygen A band measurements from the Global Ozone Monitoring Experiment, J. Geophys. Res., 106, 3475–3490, https://doi.org/10.1029/2000JD900657, 2001. a, b
Kooreman, M. L., Stammes, P., Trees, V., Sneep, M., Tilstra, L. G., de Graaf, M., Stein Zweers, D. C., Wang, P., Tuinder, O. N. E., and Veefkind, J. P.: Effects of clouds on the UV Absorbing Aerosol Index from TROPOMI, Atmos. Meas. Tech., 13, 6407–6426, https://doi.org/10.5194/amt-13-6407-2020, 2020. a, b, c, d
Levelt, P. F., van den Oord, G. H. J., Dobber, M. R., Malkki, A., Visser, H., de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The Ozone Monitoring Instrument, IEEE T. Geosci. Remote, 44, 1093–1101, https://doi.org/10.1109/TGRS.2006.872333, 2006. a
Lorente, A., Boersma, K. F., Eskes, H. J., Veefkind, J. P., van Geffen, J. H. G. M., de Zeeuw, M. B., Denier van der Gon, H. A. C., Beirle, S., and Krol, M. C.: Quantification of nitrogen oxides emissions from build-up of pollution over Paris with TROPOMI, Scientific Reports, 9, 20033, https://doi.org/10.1038/s41598-019-56428-5, 2019. a
Ludewig, A., Kleipool, Q., Bartstra, R., Landzaat, R., Leloux, J., Loots, E., Meijering, P., van der Plas, E., Rozemeijer, N., Vonk, F., and Veefkind, P.: In-flight calibration results of the TROPOMI payload on board the Sentinel-5 Precursor satellite, Atmos. Meas. Tech., 13, 3561–3580, https://doi.org/10.5194/amt-13-3561-2020, 2020. a, b
Marchuk, G. I., Mikhailov, G. A., and Nazaraliev, M. A.: The Monte Carlo methods in atmospheric optics, Springer Berlin, Heidelberg, https://doi.org/10.1007/978-3-540-35237-2, 1980. a
Mayer, B.: Radiative transfer in the cloudy atmosphere, EPJ Web of Conferences, 1, 75–99, https://doi.org/10.1140/epjconf/e2009-00912-1, 2009. a
Munro, R., Lang, R., Klaes, D., Poli, G., Retscher, C., Lindstrot, R., Huckle, R., Lacan, A., Grzegorski, M., Holdak, A., Kokhanovsky, A., Livschitz, J., and Eisinger, M.: The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview, Atmos. Meas. Tech., 9, 1279–1301, https://doi.org/10.5194/amt-9-1279-2016, 2016. a
Nanda, S., de Graaf, M., Veefkind, J. P., ter Linden, M., Sneep, M., de Haan, J., and Levelt, P. F.: A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm, Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019, 2019. a
Pandey, S., Gautam, R., Houweling, S., Denier van der Gon, H., Sadavarte, P., Borsdorff, T., Hasekamp, O., Landgraf, J., Tol, P., van Kempen, T., Hoogeveen, R., van Hees, R., Hamburg, S. P., Maasakkers, J. D., and Aben, I.: Satellite observations reveal extreme methane leakage from a natural gas well blowout, P. Natl. Acad. Sci. USA, 116, 26376–26381, https://doi.org/10.1073/pnas.1908712116, 2019. a
Penning de Vries, M. and Wagner, T.: Modelled and measured effects of clouds on UV Aerosol Indices on a local, regional, and global scale, Atmos. Chem. Phys., 11, 12715–12735, https://doi.org/10.5194/acp-11-12715-2011, 2011. a
Penning de Vries, M. J. M., Beirle, S., and Wagner, T.: UV Aerosol Indices from SCIAMACHY: introducing the SCattering Index (SCI), Atmos. Chem. Phys., 9, 9555–9567, https://doi.org/10.5194/acp-9-9555-2009, 2009. a, b
Sanders, A. F. J., de Haan, J. F., Sneep, M., Apituley, A., Stammes, P., Vieitez, M. O., Tilstra, L. G., Tuinder, O. N. E., Koning, C. E., and Veefkind, J. P.: Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A, Atmos. Meas. Tech., 8, 4947–4977, https://doi.org/10.5194/amt-8-4947-2015, 2015. a
Schneising, O., Buchwitz, M., Reuter, M., Vanselow, S., Bovensmann, H., and Burrows, J. P.: Remote sensing of methane leakage from natural gas and petroleum systems revisited, Atmos. Chem. Phys., 20, 9169–9182, https://doi.org/10.5194/acp-20-9169-2020, 2020. a
Spada, F., Krol, M. C., and Stammes, P.: McSCIA: application of the Equivalence Theorem in a Monte Carlo radiative transfer model for spherical shell atmospheres, Atmos. Chem. Phys., 6, 4823–4842, https://doi.org/10.5194/acp-6-4823-2006, 2006. a
Stam, D. M., de Haan, J. F., Hovenier, J. W., and Stammes, P.: A fast method for simulating observations of polarized light emerging from the atmosphere applied to the oxygen-A band, J. Quant. Spectrosc. Ra., 64, 131–149, https://doi.org/10.1016/S0022-4073(99)00009-6, 2000. a
Stein Zweers, D., Apituley, A., and Veefkind, P.: Algorithm theoretical basis document for the TROPOMI UV Aerosol Index, Document No. S5P-KNMI-L2-0008-RP, Issue 2.1.0, Royal Netherlands Meteorological Institute (KNMI), https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-UV-Aerosol-Index.pdf (last access: 26 December 2024), 2018. a, b
Theys, N., Hedelt, P., De Smedt, I., Lerot, C., Yu, H., Vlietinck, J., Pedergnana, M., Arellano, S., Galle, B., Fernandez, D., Carlito, C. J. M., Barrington, C., Taisne, B., Delgado-Granados, H., Loyola, D., and Van Roozendael, M.: Global monitoring of volcanic SO2 degassing with unprecedented resolution from TROPOMI onboard Sentinel-5 Precursor, Scientific Reports, 9, 2643, https://doi.org/10.1038/s41598-019-39279-y, 2019. a
Tilstra, L. G., de Graaf, M., Wang, P., and Stammes, P.: In-orbit Earth reflectance validation of TROPOMI on board the Sentinel-5 Precursor satellite, Atmos. Meas. Tech., 13, 4479–4497, https://doi.org/10.5194/amt-13-4479-2020, 2020. a
Tilstra, L. G., de Graaf, M., Trees, V. J. H., Litvinov, P., Dubovik, O., and Stammes, P.: A directional surface reflectance climatology determined from TROPOMI observations, Atmos. Meas. Tech., 17, 2235–2256, https://doi.org/10.5194/amt-17-2235-2024, 2024. a
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.: Derivation of aerosol properties from satellite measurements of backscattered ultraviolet radiation: Theoretical basis, J. Geophys. Res.-Atmos., 103, 17099–17110, https://doi.org/10.1029/98JD00900, 1998. a, b
Torres, O., Jethva, H., and Bhartia, P. K.: Retrieval of Aerosol Optical Depth above Clouds from OMI Observations: Sensitivity Analysis and Case Studies, J. Atmos. Sci., 69, 1037–1053, https://doi.org/10.1175/JAS-D-11-0130.1, 2012. a
Torres, O., Bhartia, P. K., Jethva, H., and Ahn, C.: Impact of the ozone monitoring instrument row anomaly on the long-term record of aerosol products, Atmos. Meas. Tech., 11, 2701–2715, https://doi.org/10.5194/amt-11-2701-2018, 2018. a
Trees, V., Wang, P., and Stammes, P.: Restoring the top-of-atmosphere reflectance during solar eclipses: a proof of concept with the UV absorbing aerosol index measured by TROPOMI, Atmos. Chem. Phys., 21, 8593–8614, https://doi.org/10.5194/acp-21-8593-2021, 2021. a
van der A, R., de Laat, J., Eskes, H., and Ding, J.: Connecting the dots: NOx emissions along a West Siberian natural gas pipeline, npj Climate and Atmospheric Science, 3, 16, https://doi.org/10.1038/s41612-020-0119-z, 2020. a
van Geffen, J., Eskes, H., Boersma, K., and Veefkind, J.: TROPOMI ATBD of the total and tropospheric NO2 data products, Document No. S5P-KNMI-L2-0005-RP, Issue 2.2.0, Royal Netherlands Meteorological Institute (KNMI), https://sentinel.esa.int/documents/247904/2476257/Sentinel-5P-TROPOMI-ATBD-NO2-data-products (last access: 18 August 2021), 2021. a
Varon, D. J., McKeever, J., Jervis, D., Maasakkers, J. D., Pandey, S., Houweling, S., Aben, I., Scarpelli, T., and Jacob, D. J.: Satellite Discovery of Anomalously Large Methane Point Sources From Oil/Gas Production, Geophys. Res. Lett., 46, 13507–13516, https://doi.org/10.1029/2019GL083798, 2019. a
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications, Remote Sens. Environ., 120, 70–83, https://doi.org/10.1016/j.rse.2011.09.027, 2012. a, b
Wang, P., Stammes, P., van der A, R., Pinardi, G., and van Roozendael, M.: FRESCO+: an improved O2 A-band cloud retrieval algorithm for tropospheric trace gas retrievals, Atmos. Chem. Phys., 8, 6565–6576, https://doi.org/10.5194/acp-8-6565-2008, 2008. a, b
Short summary
Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements over Europe by TROPOMI. Using a cloud shadow detection algorithm and simulations, we found that the overall effect on the aerosol index is minimal. Interestingly, we found that cloud shadows are significantly bluer than their shadow-free surroundings, but the traditional algorithm already (partly) automatically corrects for this increased blueness.
Our study investigates the impact of cloud shadows on satellite-based aerosol index measurements...