Articles | Volume 21, issue 11
https://doi.org/10.5194/acp-21-8593-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-8593-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Jun 2021
Research article |
| 08 Jun 2021
| 08 Jun 2021
Restoring the top-of-atmosphere reflectance during solar eclipses: a proof of concept with the UV absorbing aerosol index measured by TROPOMI
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Delft University of Technology, Delft, the Netherlands
Ping Wang
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Piet Stammes
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Related authors
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
Short summary
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.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 18, 73–91, https://doi.org/10.5194/amt-18-73-2025, https://doi.org/10.5194/amt-18-73-2025, 2025
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
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.
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
Short summary
Short summary
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.
Victor J. H. Trees, Ping Wang, Piet Stammes, Lieuwe G. Tilstra, David P. Donovan, and A. Pier Siebesma
Atmos. Meas. Tech., 18, 73–91, https://doi.org/10.5194/amt-18-73-2025, https://doi.org/10.5194/amt-18-73-2025, 2025
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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).
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Adams, C., McLinden, C. A., Strong, K., and Umlenski, V.: Ozone and NO2 variations measured during the 1 August 2008 solar eclipse above Eureka, Canada with a UV-visible spectrometer, J. Geophys. Res.-Atmos., 115, D19310, https://doi.org/10.1029/2010JD014424, 2010. a
Bernhard, G. and Petkov, B.: Measurements of spectral irradiance during the solar eclipse of 21 August 2017: reassessment of the effect of solar limb darkening and of changes in total ozone, Atmos. Chem. Phys., 19, 4703–4719, https://doi.org/10.5194/acp-19-4703-2019, 2019. a, b
Bojkov, R. D.: The ozone variations during the solar eclipse of 20 May 1966, Tellus, 20, 417–421, https://doi.org/10.3402/tellusa.v20i3.10020, 1968. a
Chakrabarty, D., Peshin, S., Srivastav, S., Shah, N., and Pandya, K.: Further evidence of total ozone variation during the solar eclipse of 1995, J. Geophys. Res., 106, 3213–3218, https://doi.org/10.1029/2000JD900522, 2001. a
Chakrabarty, D. K., Shah, N. C., and Pandya, K. V.: Fluctuation in ozone column over Ahmedabad during the solar eclipse of 24 October 1995, Geophys. Res. Lett., 24, 3001–3003, https://doi.org/10.1029/97GL03016, 1997. a
Chauvenet, W.: A manual of spherical and practical astronomy, J. B. Lippincott, Philadelphia, 1863. a
Chitta, L. P., Smitha, H. N., and Solanki, S. K.: Solar Photosphere, Oxford
Research Encyclopedia of Physics, Oxford University Press
Oxford, https://doi.org/10.1093/acrefore/9780190871994.013.26,
2020. a
Copernicus Sentinel-5P: (processed by ESA), TROPOMI level 2 Ultraviolet Aerosol Index products. Version 01. European Space Agency. https://doi.org/10.5270/S5P-0wafvaf (last access: 31 May 2021), 2018.
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
de Haan, J. F., Bosma, P. B., and Hovenier, J. W.: The adding method for multiple scattering calculations of polarized light, Astron. Astrophys., 183, 371–391, 1987. a
Gedzelman, S. D.: Sky color near the horizon during a total solar eclipse, Appl. Optics, 14, 2831–2837, https://doi.org/10.1364/AO.14.002831, 1975. a
Gedzelman, S. D.: Solar eclipse skies and limb reddening, Appl. Optics, 59, F78–F84, https://doi.org/10.1364/AO.396964, 2020. a, b
Gil, M., Puentedura, O., Yela, M., and Cuevas, E.: Behavior of NO2 and O3 columns during the eclipse of February 26, 1998, as measured by visible spectroscopy, J. Geophys. Res., 105, 3583–3593, https://doi.org/10.1029/1999JD900973, 2000. a
Herman, J. R.: The response of stratospheric constituents to a solar eclipse, sunrise, and sunset, J. Geophys. Res.-Oceans, 84, 3701–3710, https://doi.org/10.1029/JC084iC07p03701, 1979. 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, b
Hu, Q., Wang, H., Goloub, P., Li, Z., Veselovskii, I., Podvin, T., Li, K., and Korenskiy, M.: The characterization of Taklamakan dust properties using a multiwavelength Raman polarization lidar in Kashi, China, Atmos. Chem. Phys., 20, 13817–13834, https://doi.org/10.5194/acp-20-13817-2020, 2020. a
Kazantzidis, A., Bais, A. F., Emde, C., Kazadzis, S., and Zerefos, C. S.: Attenuation of global ultraviolet and visible irradiance over Greece during the total solar eclipse of 29 March 2006, Atmos. Chem. Phys., 7, 5959–5969, https://doi.org/10.5194/acp-7-5959-2007, 2007. a
Kemp, J., Henson, G., Steiner, C., Beardsley, I., and Powell, E.: The optical polarization of the Sun, measured at a sensitivity of parts in ten million, Nature, 328, 92, https://doi.org/10.1038/328092a0, 1987. 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
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
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
Mims, F. M. and Mims, E. R.: Fluctuations in column ozone during the total solar eclipse of July 11, 1991, Geophys. Res. Lett., 20, 367–370, https://doi.org/10.1029/93GL00493, 1993. a
Montornès, A., Codina, B., Zack, J. W., and Sola, Y.: Implementation of Bessel's method for solar eclipses prediction in the WRF-ARW model, Atmos. Chem. Phys., 16, 5949–5967, https://doi.org/10.5194/acp-16-5949-2016, 2016. a
Ockenfuß, P., Emde, C., Mayer, B., and Bernhard, G.: Accurate 3-D radiative transfer simulation of spectral solar irradiance during the total solar eclipse of 21 August 2017, Atmos. Chem. Phys., 20, 1961–1976, https://doi.org/10.5194/acp-20-1961-2020, 2020. a, b, c
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
Petrov, M. P. and Alitto, S.: Takla Makan Desert, available at:
https://www.britannica.com/place/Takla-Makan-Desert (last access: 18 May 2021),
2019. a
Pierce, A. K., Slaughter, C. D., and Weinberger, D.: Solar limb darkening in the interval 7404–24 018 Å, II, Sol. Phys., 52, 179–189, https://doi.org/10.1007/BF00935800, 1977. a, b, c
Shaw, G. E.: Sky Brightness and Polarization During the 1973 African Eclipse, Appl. Optics, 14, 388–394, https://doi.org/10.1364/AO.14.000388, 1975. a
Stammes, P.: Spectral radiance modelling in the UV-visible range, in: IRS 2000:
Current Problems in Atmospheric Radiation, edited by: Smith, W. L. and
Timofeyev, Y. M., A. Deepak Publishing, Hampton, Virginia, 385–388, 2001. a
Stein Zweers, D., Apituley, A., and Veefkind, P.: Algorithm theoretical basis
document for the TROPOMI UV Aerosol Index. Doc. No. S5P-KNMI-L2-0008-RP, Issue
1.1, Royal Netherlands Meteorological Institute (KNMI), available at:
http://www.tropomi.eu/sites/default/files/files/S5P-KNMI-L2-0008-RP-TROPOMI_ATBD_UVAI-1.1.0-20180615_signed.pdf
(last access: 14 September 2020), 2018. a
Stenflo, J. O.: Polarization of the Sun's continuous spectrum, Astron. Astrophys., 429, 713–730, https://doi.org/10.1051/0004-6361:20041667, 2005. a, b
Stenflo, J. O. and Keller, C. U.: The second solar spectrum. A new window for diagnostics of the Sun, Astron. Astrophys., 321, 927–934, 1997. 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, b
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
Tuinder, O., de Graaf, M., Tilstra, G., Penning de Vries, M., and
Kooreman, M.: Algorithm theoretical basis document for the NRT, Offline and
Data Record Absorbing Aerosol Index Products. Doc. No. ACSAF/KNMI/ATBD/002,
Issue 2.61, Royal Netherlands Meteorological Institute (KNMI), available at:
https://acsaf.org/docs/atbd/Algorithm_Theoretical_Basis_Document_NAR_NAP_ARS_ARP_Sep_2019.pdf
(last access: 8 October 2020), 2019. a
Waldmeier, M.: Ergebnisse und probleme der sonnenforschung, von
dr. M. Waldmeier mit 102 figuren, Lpz Akademische Verlagsgesellschaft Becker
and Erler, Leipzig, Germany, 1941. a
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
Winkler, P., Kaminski, U., Ohler, U., Riedl, J., Schroers, H., and Anwender, D.: Development of meteorological parameters and total ozone during the total solar eclipse of August 11, 1999, Meteorol. Z., 10, 193–199, https://doi.org/10.1127/0941-2948/2001/0010-0193, 2001. a
Wuebbles, D. and Chang, J. S.: A theoretical study of stratospheric trace species variations during a solar eclipse, Geophys. Res. Lett., 6, 179–182, https://doi.org/10.1029/GL006i003p00179, 1979. a, b
Zerefos, C. S., Balis, D. S., Meleti, C., Bais, A. F., Tourpali, K., Kourtidis, K., Vanicek, K., Cappellani, F., Kaminski, U., Colombo, T., Stübi, R., Manea, L., Formenti, P., and Andreae, M. O.: Changes in surface solar UV irradiances and total ozone during the solar eclipse of August 11, 1999, J. Geophys. Res.-Atmos., 105, 26463–26473, https://doi.org/10.1029/2000JD900412, 2000. a
Short summary
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.
Given the time and location of a point on the Earth's surface, we explain how to compute the...
Altmetrics
Final-revised paper
Preprint