Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4219-2021
© 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/amt-14-4219-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface measured by the GOME-2 satellite instruments
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Olaf N. E. Tuinder
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Ping Wang
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Piet Stammes
CORRESPONDING AUTHOR
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
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Konstantinos Michailidis, Maria-Elissavet Koukouli, Nikolaos Siomos, Dimitris Balis, Olaf Tuinder, L. Gijsbert Tilstra, Lucia Mona, Gelsomina Pappalardo, and Daniele Bortoli
Atmos. Chem. Phys., 21, 3193–3213, https://doi.org/10.5194/acp-21-3193-2021, https://doi.org/10.5194/acp-21-3193-2021, 2021
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The aim of this study is to investigate the potential of the GOME-2 instrument aboard the MetOp-A, MetOp-B and MetOp-C platforms to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based data from lidar stations available from the EARLINET database. We show that for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation.
Lieuwe G. Tilstra, Martin de Graaf, Ping Wang, and Piet Stammes
Atmos. Meas. Tech., 13, 4479–4497, https://doi.org/10.5194/amt-13-4479-2020, https://doi.org/10.5194/amt-13-4479-2020, 2020
Short summary
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The goal of the study was to determine the accuracy of the radiometric calibration of the TROPOMI instrument on board the Sentinel-5 Precursor satellite in flight. The Earth reflectances were compared to radiative transfer calculations. We report calibration accuracies and errors for 21 selected wavelength bands between 328 and 2314 nm, located in TROPOMI spectral bands 3–7. The reported numbers can be used to perform corrections that will benefit the retrievals of many atmospheric properties.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
Short summary
Short summary
With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Martin de Graaf, Ruben Schulte, Fanny Peers, Fabien Waquet, L. Gijsbert Tilstra, and Piet Stammes
Atmos. Chem. Phys., 20, 6707–6723, https://doi.org/10.5194/acp-20-6707-2020, https://doi.org/10.5194/acp-20-6707-2020, 2020
Short summary
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The radiative effect from smoke by wildfires has been found to be much stronger than models predict. The effect is complex; smoke generally cools the climate system by reflecting sunlight but strongly warms the system when it is found over a bright cloud deck. In this paper three different satellite datasets are compared and all three confirm the strong warming of African smoke over the cloud deck in the south-east Atlantic. The intercomparison reduces the uncertainties in the observations.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Athina Argyrouli, Ronny Lutz, L. Gijsbert Tilstra, Vincent Huijnen, François Hendrick, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 755–787, https://doi.org/10.5194/amt-13-755-2020, https://doi.org/10.5194/amt-13-755-2020, 2020
Short summary
Short summary
This paper presents an improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations that are
performed with a more accurate knowledge of surface albedo, the a priori NO2 profile, and cloud and aerosol corrections.
Martin de Graaf, L. Gijsbert Tilstra, and Piet Stammes
Atmos. Meas. Tech., 12, 5119–5135, https://doi.org/10.5194/amt-12-5119-2019, https://doi.org/10.5194/amt-12-5119-2019, 2019
Short summary
Short summary
A new algorithm is described, which was used to derive direct radiative effects of aerosols above clouds. These effects are among the largest uncertainties in global climate model simulations, and observations are needed to constrain these simulations. A recently developed method was applied to a combination of satellite reflectance measurements to cover the entire shortwave (solar) spectrum. Radiative effects of aerosols over the south-east Atlantic are presented, where the effects are largest.
Alba Lorente, K. Folkert Boersma, Piet Stammes, L. Gijsbert Tilstra, Andreas Richter, Huan Yu, Said Kharbouche, and Jan-Peter Muller
Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, https://doi.org/10.5194/amt-11-4509-2018, 2018
Short summary
Short summary
Light reflected by Earth’s surface is different in each direction: it appears brighter or darker in certain viewing directions. Currently this effect is not accounted for in satellite retrievals; thus surface reflectance climatologies and cloud fractions show an east-west bias across orbits (GOME2,OMI). The effect for NO2 measurements in partly cloudy scenes is substantial. We recommend that this effect in UV/Vis sensors coherently accounted for, and will be especially beneficial for TROPOMI.
Martin de Graaf, Holger Sihler, Lieuwe G. Tilstra, and Piet Stammes
Atmos. Meas. Tech., 9, 3607–3618, https://doi.org/10.5194/amt-9-3607-2016, https://doi.org/10.5194/amt-9-3607-2016, 2016
Short summary
Short summary
The shapes and sizes of the FoV from the OMI satellite instrument were determined with extensive lab tests but never verified after launch. Here, collocated measurements from MODIS, flying in formation, were used to find the most optimal shape of the OMI FoV. This shape is not quadrangular, as suggested by the provided corner coordinates of a pixel, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels.
W. Hewson, M. P. Barkley, G. Gonzalez Abad, H. Bösch, T. Kurosu, R. Spurr, and L. G. Tilstra
Atmos. Meas. Tech., 8, 4055–4074, https://doi.org/10.5194/amt-8-4055-2015, https://doi.org/10.5194/amt-8-4055-2015, 2015
Short summary
Short summary
This work presents the air mass factor (AMF) algorithm in use at the University of Leicester, which introduces scene-specific variables into a per-observation full radiative transfer AMF calculation, including increasing spatial resolution of key environmental parameter databases, input variable area weighting, instrument-specific scattering weight calculation, and inclusion of an ozone vertical profile climatology.
M. J. M. Penning de Vries, S. Beirle, C. Hörmann, J. W. Kaiser, P. Stammes, L. G. Tilstra, O. N. E. Tuinder, and T. Wagner
Atmos. Chem. Phys., 15, 10597–10618, https://doi.org/10.5194/acp-15-10597-2015, https://doi.org/10.5194/acp-15-10597-2015, 2015
A. Castagna, H. Evangelista, L. G. Tilstra, and R. Kerr
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-11671-2014, https://doi.org/10.5194/bgd-11-11671-2014, 2014
Revised manuscript not accepted
L. G. Tilstra, R. Lang, R. Munro, I. Aben, and P. Stammes
Atmos. Meas. Tech., 7, 2047–2059, https://doi.org/10.5194/amt-7-2047-2014, https://doi.org/10.5194/amt-7-2047-2014, 2014
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
Short summary
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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.
Konstantinos Michailidis, Maria-Elissavet Koukouli, Nikolaos Siomos, Dimitris Balis, Olaf Tuinder, L. Gijsbert Tilstra, Lucia Mona, Gelsomina Pappalardo, and Daniele Bortoli
Atmos. Chem. Phys., 21, 3193–3213, https://doi.org/10.5194/acp-21-3193-2021, https://doi.org/10.5194/acp-21-3193-2021, 2021
Short summary
Short summary
The aim of this study is to investigate the potential of the GOME-2 instrument aboard the MetOp-A, MetOp-B and MetOp-C platforms to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based data from lidar stations available from the EARLINET database. We show that for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation.
Lieuwe G. Tilstra, Martin de Graaf, Ping Wang, and Piet Stammes
Atmos. Meas. Tech., 13, 4479–4497, https://doi.org/10.5194/amt-13-4479-2020, https://doi.org/10.5194/amt-13-4479-2020, 2020
Short summary
Short summary
The goal of the study was to determine the accuracy of the radiometric calibration of the TROPOMI instrument on board the Sentinel-5 Precursor satellite in flight. The Earth reflectances were compared to radiative transfer calculations. We report calibration accuracies and errors for 21 selected wavelength bands between 328 and 2314 nm, located in TROPOMI spectral bands 3–7. The reported numbers can be used to perform corrections that will benefit the retrievals of many atmospheric properties.
Erik van Schaik, Maurits L. Kooreman, Piet Stammes, L. Gijsbert Tilstra, Olaf N. E. Tuinder, Abram F. J. Sanders, Willem W. Verstraeten, Rüdiger Lang, Alessandra Cacciari, Joanna Joiner, Wouter Peters, and K. Folkert Boersma
Atmos. Meas. Tech., 13, 4295–4315, https://doi.org/10.5194/amt-13-4295-2020, https://doi.org/10.5194/amt-13-4295-2020, 2020
Short summary
Short summary
With our improved algorithm we have generated a stable, long-term dataset of fluorescence measurements from the GOME-2A satellite instrument. In this study we determined a correction for the degradation of GOME-2A in orbit and applied this correction along with other improvements to our SIFTER v2 retrieval algorithm. The result is a coherent dataset of daily and monthly averaged fluorescence values for the period 2007–2018 to track worldwide changes in photosynthetic activity by vegetation.
Martin de Graaf, Ruben Schulte, Fanny Peers, Fabien Waquet, L. Gijsbert Tilstra, and Piet Stammes
Atmos. Chem. Phys., 20, 6707–6723, https://doi.org/10.5194/acp-20-6707-2020, https://doi.org/10.5194/acp-20-6707-2020, 2020
Short summary
Short summary
The radiative effect from smoke by wildfires has been found to be much stronger than models predict. The effect is complex; smoke generally cools the climate system by reflecting sunlight but strongly warms the system when it is found over a bright cloud deck. In this paper three different satellite datasets are compared and all three confirm the strong warming of African smoke over the cloud deck in the south-east Atlantic. The intercomparison reduces the uncertainties in the observations.
Adrianus de Laat, Margarita Vazquez-Navarro, Nicolas Theys, and Piet Stammes
Nat. Hazards Earth Syst. Sci., 20, 1203–1217, https://doi.org/10.5194/nhess-20-1203-2020, https://doi.org/10.5194/nhess-20-1203-2020, 2020
Short summary
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TROPOMI satellite measurements can accurately determine the height of thick volcanic ash clouds from a short-lived volcanic eruption of the Sinabung volcano in Indonesia. Standard geostationary satellite detection of volcanic ash was limited due to the presence of water and ice in the upper parts of volcanic ash clouds, a known issue. The TROPOMI satellite measurements do not suffer from this limitation, hence providing information where standard geostationary volcanic ash detection is limited.
Ping Wang, Ankie Piters, Jos van Geffen, Olaf Tuinder, Piet Stammes, and Stefan Kinne
Atmos. Meas. Tech., 13, 1413–1426, https://doi.org/10.5194/amt-13-1413-2020, https://doi.org/10.5194/amt-13-1413-2020, 2020
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The comparison of shipborne MAX-DOAS and TROPOMI NO2 products is important for the evaluation of the TROPOMI products. The ship cruises were mainly over remote oceans, thus we only measured background tropospheric NO2. Stratospheric NO2 was measured more accurately because there was almost no contamination from tropospheric NO2. We found that the TROPOMI stratospheric NO2 vertical column densities were slightly higher than the MAX-DOAS measurements.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Athina Argyrouli, Ronny Lutz, L. Gijsbert Tilstra, Vincent Huijnen, François Hendrick, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 755–787, https://doi.org/10.5194/amt-13-755-2020, https://doi.org/10.5194/amt-13-755-2020, 2020
Short summary
Short summary
This paper presents an improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations that are
performed with a more accurate knowledge of surface albedo, the a priori NO2 profile, and cloud and aerosol corrections.
Martin de Graaf, L. Gijsbert Tilstra, and Piet Stammes
Atmos. Meas. Tech., 12, 5119–5135, https://doi.org/10.5194/amt-12-5119-2019, https://doi.org/10.5194/amt-12-5119-2019, 2019
Short summary
Short summary
A new algorithm is described, which was used to derive direct radiative effects of aerosols above clouds. These effects are among the largest uncertainties in global climate model simulations, and observations are needed to constrain these simulations. A recently developed method was applied to a combination of satellite reflectance measurements to cover the entire shortwave (solar) spectrum. Radiative effects of aerosols over the south-east Atlantic are presented, where the effects are largest.
Nikos Benas, Jan Fokke Meirink, Martin Stengel, and Piet Stammes
Atmos. Meas. Tech., 12, 2863–2879, https://doi.org/10.5194/amt-12-2863-2019, https://doi.org/10.5194/amt-12-2863-2019, 2019
Short summary
Short summary
Cloud glory and bow phenomena cause irregularities in satellite-based retrievals of cloud optical and microphysical properties. Here we combine two geostationary satellites over the same areas to analyze retrievals under those conditions. Results show a high sensitivity of retrievals to the assumed width of the cloud droplet size distribution and provide insights into possible improvements in satellite retrievals by appropriately adjusting this assumed parameter.
Aristeidis K. Georgoulias, Ronald J. van der A, Piet Stammes, K. Folkert Boersma, and Henk J. Eskes
Atmos. Chem. Phys., 19, 6269–6294, https://doi.org/10.5194/acp-19-6269-2019, https://doi.org/10.5194/acp-19-6269-2019, 2019
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In this paper, a ∼21-year self-consistent global dataset from four different satellite sensors is compiled for the first time to study the long-term tropospheric NO2 patterns and trends. A novel method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe during the last 2 decades.
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.
Alba Lorente, K. Folkert Boersma, Piet Stammes, L. Gijsbert Tilstra, Andreas Richter, Huan Yu, Said Kharbouche, and Jan-Peter Muller
Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, https://doi.org/10.5194/amt-11-4509-2018, 2018
Short summary
Short summary
Light reflected by Earth’s surface is different in each direction: it appears brighter or darker in certain viewing directions. Currently this effect is not accounted for in satellite retrievals; thus surface reflectance climatologies and cloud fractions show an east-west bias across orbits (GOME2,OMI). The effect for NO2 measurements in partly cloudy scenes is substantial. We recommend that this effect in UV/Vis sensors coherently accounted for, and will be especially beneficial for TROPOMI.
Nikos Benas, Jan Fokke Meirink, Karl-Göran Karlsson, Martin Stengel, and Piet Stammes
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-554, https://doi.org/10.5194/acp-2018-554, 2018
Preprint withdrawn
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In this study we analyse aerosol and cloud changes over South China and investigate their possible interactions. The results show decreasing aerosol loads and increasing liquid clouds. Further analysis of these changes based on various satellite data sets show consistency with the aerosol semi-direct effect, whereby less absorbing aerosols in the cloud layer would lead to an overall decrease in evaporation of cloud droplets, thus increasing cloud amount and cover.
Sweta Shah, Olaf N. E. Tuinder, Jacob C. A. van Peet, Adrianus T. J. de Laat, and Piet Stammes
Atmos. Meas. Tech., 11, 2345–2360, https://doi.org/10.5194/amt-11-2345-2018, https://doi.org/10.5194/amt-11-2345-2018, 2018
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The depletion of the Antarctic ozone layer and its changing vertical distribution have been monitored closely by satellites in the past decades ever since the Antarctic
ozone holewas discovered in the 1980s. We study and assess the quality of the ozone profiles using SCIAMACHY ultraviolet data and compare them against the ozone sondes.
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.
Alba Lorente, K. Folkert Boersma, Huan Yu, Steffen Dörner, Andreas Hilboll, Andreas Richter, Mengyao Liu, Lok N. Lamsal, Michael Barkley, Isabelle De Smedt, Michel Van Roozendael, Yang Wang, Thomas Wagner, Steffen Beirle, Jin-Tai Lin, Nickolay Krotkov, Piet Stammes, Ping Wang, Henk J. Eskes, and Maarten Krol
Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, https://doi.org/10.5194/amt-10-759-2017, 2017
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Choices and assumptions made to represent the state of the atmosphere introduce an uncertainty of 42 % in the air mass factor calculation in trace gas satellite retrievals in polluted regions. The AMF strongly depends on the choice of a priori trace gas profile, surface albedo data set and the correction method to account for clouds and aerosols. We call for well-designed validation exercises focusing on situations when AMF structural uncertainty has the highest impact on satellite retrievals.
Martin de Graaf, Holger Sihler, Lieuwe G. Tilstra, and Piet Stammes
Atmos. Meas. Tech., 9, 3607–3618, https://doi.org/10.5194/amt-9-3607-2016, https://doi.org/10.5194/amt-9-3607-2016, 2016
Short summary
Short summary
The shapes and sizes of the FoV from the OMI satellite instrument were determined with extensive lab tests but never verified after launch. Here, collocated measurements from MODIS, flying in formation, were used to find the most optimal shape of the OMI FoV. This shape is not quadrangular, as suggested by the provided corner coordinates of a pixel, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels.
W. Hewson, M. P. Barkley, G. Gonzalez Abad, H. Bösch, T. Kurosu, R. Spurr, and L. G. Tilstra
Atmos. Meas. Tech., 8, 4055–4074, https://doi.org/10.5194/amt-8-4055-2015, https://doi.org/10.5194/amt-8-4055-2015, 2015
Short summary
Short summary
This work presents the air mass factor (AMF) algorithm in use at the University of Leicester, which introduces scene-specific variables into a per-observation full radiative transfer AMF calculation, including increasing spatial resolution of key environmental parameter databases, input variable area weighting, instrument-specific scattering weight calculation, and inclusion of an ozone vertical profile climatology.
M. J. M. Penning de Vries, S. Beirle, C. Hörmann, J. W. Kaiser, P. Stammes, L. G. Tilstra, O. N. E. Tuinder, and T. Wagner
Atmos. Chem. Phys., 15, 10597–10618, https://doi.org/10.5194/acp-15-10597-2015, https://doi.org/10.5194/acp-15-10597-2015, 2015
A. Castagna, H. Evangelista, L. G. Tilstra, and R. Kerr
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-11671-2014, https://doi.org/10.5194/bgd-11-11671-2014, 2014
Revised manuscript not accepted
L. G. Tilstra, R. Lang, R. Munro, I. Aben, and P. Stammes
Atmos. Meas. Tech., 7, 2047–2059, https://doi.org/10.5194/amt-7-2047-2014, https://doi.org/10.5194/amt-7-2047-2014, 2014
P. Wang and P. Stammes
Atmos. Meas. Tech., 7, 1331–1350, https://doi.org/10.5194/amt-7-1331-2014, https://doi.org/10.5194/amt-7-1331-2014, 2014
J.-T. Lin, R. V. Martin, K. F. Boersma, M. Sneep, P. Stammes, R. Spurr, P. Wang, M. Van Roozendael, K. Clémer, and H. Irie
Atmos. Chem. Phys., 14, 1441–1461, https://doi.org/10.5194/acp-14-1441-2014, https://doi.org/10.5194/acp-14-1441-2014, 2014
J. F. Meirink, R. A. Roebeling, and P. Stammes
Atmos. Meas. Tech., 6, 2495–2508, https://doi.org/10.5194/amt-6-2495-2013, https://doi.org/10.5194/amt-6-2495-2013, 2013
Related subject area
Subject: Gases | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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Retrieval of atmospheric CFC-11 and CFC-12 from high-resolution FTIR observations at Hefei and comparisons with other independent datasets
Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements
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DARCLOS: a cloud shadow detection algorithm for TROPOMI
Combined UV and IR ozone profile retrieval from TROPOMI and CrIS measurements
Improved ozone monitoring by ground-based FTIR spectrometry
On the consistency of methane retrievals using the Total Carbon Column Observing Network (TCCON) and multiple spectroscopic databases
The MOPITT Version 9 CO product: sampling enhancements and validation
Retrieving H2O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI)
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Manuel López-Puertas, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, https://doi.org/10.5194/amt-16-2167-2023, 2023
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New global nitric oxide (NO) volume-mixing-ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK-IAA MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on ESA version 8 calibration and were processed using an improved retrieval approach.
Adrien Vu Van, Anne Boynard, Pascal Prunet, Dominique Jolivet, Olivier Lezeaux, Patrice Henry, Claude Camy-Peyret, Lieven Clarisse, Bruno Franco, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 16, 2107–2127, https://doi.org/10.5194/amt-16-2107-2023, https://doi.org/10.5194/amt-16-2107-2023, 2023
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With its near-real-time observations and good horizontal coverage, the Infrared Atmospheric Sounding Interferometer (IASI) instrument can contribute to the monitoring systems for a systematic and continuous detection of exceptional atmospheric events such as fires, anthropogenic pollution episodes, volcanic eruptions, or industrial releases. In this paper, a new approach is described for the detection and characterization of unexpected events in terms of trace gases using IASI radiance spectra.
Ian Ashpole and Aldona Wiacek
Atmos. Meas. Tech., 16, 1923–1949, https://doi.org/10.5194/amt-16-1923-2023, https://doi.org/10.5194/amt-16-1923-2023, 2023
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The MOPITT instrument has been measuring atmospheric carbon monoxide (CO) from space since 2000. Its data products are valuable for CO trend analysis. This paper compares products with different spatial resolutions to identify discrepancies in mean CO amounts and detectable trends for coastal grid boxes. It is found that CO amounts and trends differ significantly between data products for a large number of these grid boxes, essentially due to how the coarser-resolution products are created.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Thomas Wagner, Simon Warnach, Steffen Beirle, Nicole Bobrowski, Adrian Jost, Janis Puķīte, and Nicolas Theys
Atmos. Meas. Tech., 16, 1609–1662, https://doi.org/10.5194/amt-16-1609-2023, https://doi.org/10.5194/amt-16-1609-2023, 2023
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We investigate 3D effects of volcanic plumes on the retrieval results of satellite and ground-based UV–Vis observations. With its small ground pixels of 3.5 x 5.5 km², the TROPOMI instrument can detect much smaller volcanic plumes than previous instruments. At the same time, 3D effects become important. The effect of horizontal photon paths especially can lead to a strong underestimation of the derived plume contents of up to > 50 %, which can be further increased for strong absorbers like SO2.
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.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Steffen Mauceri, Steven Massie, and Sebastian Schmidt
Atmos. Meas. Tech., 16, 1461–1476, https://doi.org/10.5194/amt-16-1461-2023, https://doi.org/10.5194/amt-16-1461-2023, 2023
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The Orbiting Carbon Observatory-2 makes space-based measurements of reflected sunlight. Using a retrieval algorithm these measurements are converted to CO2 concentrations in the atmosphere. However, the converted CO2 concentrations contain errors for observations close to clouds. Using a simple machine learning approach, we developed a model to correct these remaining errors. The model is able to reduce errors over land and ocean by 20 % and 40 %, respectively.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, https://doi.org/10.5194/amt-16-1443-2023, 2023
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A new ozone data set, derived from radiation measurements of the space-borne instrument MIPAS, is presented. It consists of more than 2 million single ozone profiles from 2002–2012, covering virtually all latitudes and altitudes between 5 and 70 km. Progress in data calibration and processing methods allowed for significant improvement of the data quality, compared to previous data versions. Hence, the data set will help to better understand e.g. the time evolution of ozone in the stratosphere.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
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Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
Joshua L. Laughner, Sébastien Roche, Matthäus Kiel, Geoffrey C. Toon, Debra Wunch, Bianca C. Baier, Sébastien Biraud, Huilin Chen, Rigel Kivi, Thomas Laemmel, Kathryn McKain, Pierre-Yves Quéhé, Constantina Rousogenous, Britton B. Stephens, Kaley Walker, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 1121–1146, https://doi.org/10.5194/amt-16-1121-2023, https://doi.org/10.5194/amt-16-1121-2023, 2023
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Observations using sunlight to measure surface-to-space total column of greenhouse gases in the atmosphere need an initial guess of the vertical distribution of those gases to start from. We have developed an approach to provide those initial guess profiles that uses readily available meteorological data as input. This lets us make these guesses without simulating them with a global model. The profiles generated this way match independent observations well.
Gyo-Hwang Choo, Kyunghwa Lee, Hyunkee Hong, Ukkyo Jeong, Wonei Choi, and Scott J. Janz
Atmos. Meas. Tech., 16, 625–644, https://doi.org/10.5194/amt-16-625-2023, https://doi.org/10.5194/amt-16-625-2023, 2023
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This study discusses the morning and afternoon distribution of NO2 emissions in large cities and industrial areas in South Korea, one of the largest NO2 emitters around the world, using GeoTASO, an airborne remote sensing instrument developed to support geostationary satellite missions. NO2 measurements from GeoTASO were compared with those from ground-based remote sensing instruments including Pandora and in situ sensors.
Oliver Schneising, Michael Buchwitz, Jonas Hachmeister, Steffen Vanselow, Maximilian Reuter, Matthias Buschmann, Heinrich Bovensmann, and John P. Burrows
Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, https://doi.org/10.5194/amt-16-669-2023, 2023
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Methane and carbon monoxide are important constituents of the atmosphere in the context of climate change and air pollution. We present the latest advances in the TROPOMI/WFMD algorithm to simultaneously retrieve atmospheric methane and carbon monoxide abundances from space. The changes in the latest product version are described in detail, and the resulting improvements are demonstrated. An overview of the products is provided including a discussion of annual increases and validation results.
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023, https://doi.org/10.5194/amt-16-481-2023, 2023
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Nitrogen dioxide (NO2) is an important trace gas for both air quality and climate. NO2 affects satellite ocean color products. A new ocean color instrument – OCI (Ocean Color Instrument) – will be launched in 2024 on a NASA satellite. We show that it will be possible to measure NO2 from OCI even though it was not designed for this. The techniques developed here, based on machine learning, can also be applied to instruments already in space to speed up algorithms and reduce the effects of noise.
Minqiang Zhou, Bavo Langerock, Pucai Wang, Corinne Vigouroux, Qichen Ni, Christian Hermans, Bart Dils, Nicolas Kumps, Weidong Nan, and Martine De Mazière
Atmos. Meas. Tech., 16, 273–293, https://doi.org/10.5194/amt-16-273-2023, https://doi.org/10.5194/amt-16-273-2023, 2023
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The ground-based FTIR measurements at Xianghe provide carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) total columns between June 2018 and November 2021. The retrieval strategies, information, and uncertainties of these five important trace gases are presented and discussed. This study provides insight into the time series, variations, and correlations of these five species in northern China.
Zhan Zhang, Evan D. Sherwin, Daniel J. Varon, and Adam R. Brandt
Atmos. Meas. Tech., 15, 7155–7169, https://doi.org/10.5194/amt-15-7155-2022, https://doi.org/10.5194/amt-15-7155-2022, 2022
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This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval algorithm, and the method was calibrated by data from a controlled release test. To our knowledge, this is the first study that validates the performance of a Sentinel-2 methane detection algorithm by calibration with a ground-truth testing. It illustrates the potential for additional validation with systematic future experiments wherein algorithms can be tuned to meet different detection expectations.
Simone Ceccherini, Nicola Zoppetti, and Bruno Carli
Atmos. Meas. Tech., 15, 7039–7048, https://doi.org/10.5194/amt-15-7039-2022, https://doi.org/10.5194/amt-15-7039-2022, 2022
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A new formula of the complete data fusion that, differently from the original one, does not contain matrices that can be singular is discussed. We show that the new formula is a generalization of the original one and analytically and numerically, using a real IASI ozone measurement, derive the errors made with the old formula when the generalized inverse of singular matrices is used. An operational version of the new formula that includes interpolation and coincidence errors is also provided.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca Baier, and Paul O. Wennberg
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-322, https://doi.org/10.5194/amt-2022-322, 2022
Revised manuscript accepted for AMT
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We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 0.857 ppb (~1 %) for CO and 3.55 ppm (~0.8 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science
Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Bernd Funke, Michael Kiefer, Anne Kleinert, Gabriele P. Stiller, Andrea Linden, and Sylvia Kellmann
Atmos. Meas. Tech., 15, 6991–7018, https://doi.org/10.5194/amt-15-6991-2022, https://doi.org/10.5194/amt-15-6991-2022, 2022
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Errors of profiles of temperature and mixing ratios retrieved from spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding are estimated. All known and quantified sources of uncertainty are considered. Some ongoing uncertaities contribute to both the random and to the systematic errors. In some cases, one source of uncertainty propagates onto the error budget via multiple pathways. Problems arise when the correlations of errors to be propagated are unknown.
Marco Ridolfi, Cecilia Tirelli, Simone Ceccherini, Claudio Belotti, Ugo Cortesi, and Luca Palchetti
Atmos. Meas. Tech., 15, 6723–6737, https://doi.org/10.5194/amt-15-6723-2022, https://doi.org/10.5194/amt-15-6723-2022, 2022
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Synergistic retrieval (SR) and complete data fusion (CDF) methods exploit the complementarity of coinciding remote-sensing measurements. We assess the performance of the SR and CDF methods on the basis of synthetic measurements of the FORUM and IASI-NG missions. In the case of perfectly matching measurements, SR and CDF results differ by less than 1 / 10 of the error due to measurement noise. In the case of a realistic mismatch, the two methods show differences in the order of their error bars.
Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, Minqiang Zhou, Martine De Mazière, Emmanuel Mahieu, Irene Pardo Cantos, Jamal Makkor, and Alexander Polyakov
Atmos. Meas. Tech., 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022, https://doi.org/10.5194/amt-15-6739-2022, 2022
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CFC-11 and CFC-12, which are classified as ozone-depleting substances, also have high global warming potentials. This paper describes obtaining the CFC-11 and CFC-12 total columns from the solar spectra based on ground-based Fourier transform infrared spectroscopy at Hefei, China. The seasonal variation and annual trend of the two gases are analyzed, and then the data are compared with other independent datasets.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, Andre Butz, Otto P. Hasekamp, Lianghai Wu, and Jochen Landgraf
Atmos. Meas. Tech., 15, 6585–6603, https://doi.org/10.5194/amt-15-6585-2022, https://doi.org/10.5194/amt-15-6585-2022, 2022
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The TROPOspheric Monitoring Instrument (TROPOMI) performs observations over ocean in every orbit, enhancing the monitoring capabilities of methane from space. In the sun glint geometry the mirror-like reflection at the water surface provides a signal that is high enough to retrieve methane with high accuracy and precision. We present 4 years of methane concentrations over the ocean, and we assess its quality. We also show the importance of ocean observations to quantify total CH4 emissions.
Eric Sauvageat, Eliane Maillard Barras, Klemens Hocke, Alexander Haefele, and Axel Murk
Atmos. Meas. Tech., 15, 6395–6417, https://doi.org/10.5194/amt-15-6395-2022, https://doi.org/10.5194/amt-15-6395-2022, 2022
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We present new harmonized ozone time series from two ground-based microwave radiometers in Switzerland. The new series consist of hourly ozone profiles in the middle atmosphere (~ 20–70 km) from 2009 until 2021. Cross-validation of the new data series shows the benefit of the harmonization process compared to the previous versions. Comparisons with collocated satellite observations is used to further validate these time series for long-term ozone monitoring over central Europe.
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien Hubert Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
EGUsphere, https://doi.org/10.5194/egusphere-2022-924, https://doi.org/10.5194/egusphere-2022-924, 2022
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and are prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far lower errors.
Carlo Arosio, Alexei Rozanov, Victor Gorshelev, Alexandra Laeng, and John P. Burrows
Atmos. Meas. Tech., 15, 5949–5967, https://doi.org/10.5194/amt-15-5949-2022, https://doi.org/10.5194/amt-15-5949-2022, 2022
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This paper characterizes the uncertainties affecting the ozone profiles retrieved at the University of Bremen through OMPS limb satellite observations. An accurate knowledge of the uncertainties is relevant for the validation of the product and to correctly interpret the retrieval results. We investigate several sources of uncertainties, estimate a total random and systematic component, and verify the consistency of the combined OMPS-MLS total uncertainty.
Xinzhou Huang and Kai Yang
Atmos. Meas. Tech., 15, 5877–5915, https://doi.org/10.5194/amt-15-5877-2022, https://doi.org/10.5194/amt-15-5877-2022, 2022
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This paper describes the algorithm for O3 and SO2 retrievals from DSCOVR EPIC. Algorithm advances, including the improved O3 profile representation and the regulated direct fitting inversion technique, improve the accuracy of O3 and SO2 from the multi-channel measurements of DSCOVR EPIC. A thorough error analysis is provided to quantify O3 and SO2 retrieval uncertainties due to various error sources and simplified algorithm physics treatments.
Huan Yu, Claudia Emde, Arve Kylling, Ben Veihelmann, Bernhard Mayer, Kerstin Stebel, and Michel Van Roozendael
Atmos. Meas. Tech., 15, 5743–5768, https://doi.org/10.5194/amt-15-5743-2022, https://doi.org/10.5194/amt-15-5743-2022, 2022
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In this study, we have investigated the impact of 3D clouds on the tropospheric NO2 retrieval from UV–visible sensors. We applied standard NO2 retrieval methods including cloud corrections to synthetic data generated by the 3D radiative transfer model. A sensitivity study was done for synthetic data, and dependencies on various parameters were investigated. Possible mitigation strategies were investigated and compared based on 3D simulations and observed data.
Klaus-Peter Heue, Diego Loyola, Fabian Romahn, Walter Zimmer, Simon Chabrillat, Quentin Errera, Jerry Ziemke, and Natalya Kramarova
Atmos. Meas. Tech., 15, 5563–5579, https://doi.org/10.5194/amt-15-5563-2022, https://doi.org/10.5194/amt-15-5563-2022, 2022
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To retrieve tropospheric ozone column information, we subtract stratospheric column data of BASCOE from TROPOMI/S5P total ozone columns.
The new S5P-BASCOE data agree well with existing tropospheric data like OMPS-MERRA-2. The data are also compared to ozone soundings.
The tropospheric ozone columns show the expected temporal and spatial patterns. We will also apply the algorithm to future UV nadir missions like Sentinel 4 or 5 or to recent and ongoing missions like GOME_2 or OMI.
Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 15, 5497–5514, https://doi.org/10.5194/amt-15-5497-2022, https://doi.org/10.5194/amt-15-5497-2022, 2022
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Satellite observations provide information on the sources of SO2, an important pollutant that affects both air quality and climate. However, these observations suffer from relatively poor data quality due to weak signals of SO2. Here, we use a machine learning technique to analyze satellite SO2 observations in order to reduce the noise and artifacts over relatively clean areas while keeping the signals near pollution sources. This leads to significant improvement in satellite SO2 data.
Elise Potier, Grégoire Broquet, Yilong Wang, Diego Santaren, Antoine Berchet, Isabelle Pison, Julia Marshall, Philippe Ciais, François-Marie Bréon, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5261–5288, https://doi.org/10.5194/amt-15-5261-2022, https://doi.org/10.5194/amt-15-5261-2022, 2022
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Atmospheric inversion at local–regional scales over Europe and pseudo-data assimilation are used to evaluate how CO2 and 14CO2 ground-based measurement networks could complement satellite CO2 imagers to monitor fossil fuel (FF) CO2 emissions. This combination significantly improves precision in the FF emission estimates in areas with a dense network but does not strongly support the separation of the FF from the biogenic signals or the spatio-temporal extrapolation of the satellite information.
François-Marie Bréon, Leslie David, Pierre Chatelanaz, and Frédéric Chevallier
Atmos. Meas. Tech., 15, 5219–5234, https://doi.org/10.5194/amt-15-5219-2022, https://doi.org/10.5194/amt-15-5219-2022, 2022
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The estimate of atmospheric CO2 from space measurement is difficult. Current methods are based on a detailed description of the atmospheric radiative transfer. These are affected by significant biases and errors and are very computer intensive. Instead we have proposed using a neural network approach. A first attempt led to confusing results. Here we provide an interpretation for these results and describe a new version that leads to high-quality estimates.
Matthieu Dogniaux, Cyril Crevoisier, Silvère Gousset, Étienne Le Coarer, Yann Ferrec, Laurence Croizé, Lianghai Wu, Otto Hasekamp, Bojan Sic, and Laure Brooker
Atmos. Meas. Tech., 15, 4835–4858, https://doi.org/10.5194/amt-15-4835-2022, https://doi.org/10.5194/amt-15-4835-2022, 2022
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The Space Carbon Observatory (SCARBO) concept proposes a constellation of small satellites that would carry a miniaturized Fabry–Pérot imaging interferometer named NanoCarb and an aerosol instrument named SPEXone. In this work, we assess the performance of this concept for the retrieval of the total weighted columns of CO2 and CH4 and show the interest of adding the SPEXone aerosol instrument to improve the CO2 and CH4 column retrieval.
Nicolas Theys, Christophe Lerot, Hugues Brenot, Jeroen van Gent, Isabelle De Smedt, Lieven Clarisse, Mike Burton, Matthew Varnam, Catherine Hayer, Benjamin Esse, and Michel Van Roozendael
Atmos. Meas. Tech., 15, 4801–4817, https://doi.org/10.5194/amt-15-4801-2022, https://doi.org/10.5194/amt-15-4801-2022, 2022
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Sulfur dioxide plume height after a volcanic eruption is an important piece of information for many different scientific studies and applications. Satellite UV retrievals are useful in this respect, but available algorithms have shown so far limited sensitivity to SO2 height. Here we present a new technique to improve the retrieval of SO2 plume height for SO2 columns as low as 5 DU. We demonstrate the algorithm using TROPOMI measurements and compare with other height estimates.
Omaira E. García, Esther Sanromá, Frank Hase, Matthias Schneider, Sergio Fabián León-Luis, Thomas Blumenstock, Eliezer Sepúlveda, Carlos Torres, Natalia Prats, Alberto Redondas, and Virgilio Carreño
Atmos. Meas. Tech., 15, 4547–4567, https://doi.org/10.5194/amt-15-4547-2022, https://doi.org/10.5194/amt-15-4547-2022, 2022
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Retrieving high-precision concentrations of atmospheric trace gases from FTIR (Fourier transform infrared) spectrometry requires a precise knowledge of the instrumental performance. In this context, this paper examines the impact on the ozone (O3) retrievals of several approaches used to characterise the instrumental line shape (ILS) function of ground-based FTIR spectrometers within NDACC (Network for the Detection of Atmospheric Composition Change).
Matthias Schneider, Benjamin Ertl, Qiansi Tu, Christopher J. Diekmann, Farahnaz Khosrawi, Amelie N. Röhling, Frank Hase, Darko Dubravica, Omaira E. García, Eliezer Sepúlveda, Tobias Borsdorff, Jochen Landgraf, Alba Lorente, André Butz, Huilin Chen, Rigel Kivi, Thomas Laemmel, Michel Ramonet, Cyril Crevoisier, Jérome Pernin, Martin Steinbacher, Frank Meinhardt, Kimberly Strong, Debra Wunch, Thorsten Warneke, Coleen Roehl, Paul O. Wennberg, Isamu Morino, Laura T. Iraci, Kei Shiomi, Nicholas M. Deutscher, David W. T. Griffith, Voltaire A. Velazco, and David F. Pollard
Atmos. Meas. Tech., 15, 4339–4371, https://doi.org/10.5194/amt-15-4339-2022, https://doi.org/10.5194/amt-15-4339-2022, 2022
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We present a computationally very efficient method for the synergetic use of level 2 remote-sensing data products. We apply the method to IASI vertical profile and TROPOMI total column space-borne methane observations and thus gain sensitivity for the tropospheric methane partial columns, which is not achievable by the individual use of TROPOMI and IASI. These synergetic effects are evaluated theoretically and empirically by inter-comparisons to independent references of TCCON, AirCore, and GAW.
Simone Ceccherini
Atmos. Meas. Tech., 15, 4407–4410, https://doi.org/10.5194/amt-15-4407-2022, https://doi.org/10.5194/amt-15-4407-2022, 2022
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The equivalence between the data fusion performed using the Kalman filter and the Complete Data Fusion has been proved, and a generalization of the Complete Data Fusion formula, that is valid also in the case that the noise error covariance matrices of the fused products are singular, is derived. The two methods are also equivalent to the measurement–space–solution data fusion method, and for moderately nonlinear problems, the three methods are all equivalent to the simultaneous retrieval.
Kang Sun, Mahdi Yousefi, Christopher Chan Miller, Kelly Chance, Gonzalo González Abad, Iouli E. Gordon, Xiong Liu, Ewan O'Sullivan, Christopher E. Sioris, and Steven C. Wofsy
Atmos. Meas. Tech., 15, 3721–3745, https://doi.org/10.5194/amt-15-3721-2022, https://doi.org/10.5194/amt-15-3721-2022, 2022
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This study of upper atmospheric airglow from oxygen is motivated by the need to measure oxygen simultaneously with methane and CO2 in satellite remote sensing. We provide an accurate understanding of the spatial, temporal, and spectral distribution of airglow emissions, which will help in the satellite remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.
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.
Arve Kylling, Claudia Emde, Huan Yu, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer
Atmos. Meas. Tech., 15, 3481–3495, https://doi.org/10.5194/amt-15-3481-2022, https://doi.org/10.5194/amt-15-3481-2022, 2022
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Atmospheric trace gases such as nitrogen dioxide (NO2) may be measured by satellite instruments sensitive to solar ultraviolet–visible radiation reflected from Earth and its atmosphere. For a single pixel, clouds in neighbouring pixels may affect the radiation and hence the retrieved trace gas amount. We found that for a solar zenith angle less than about 40° this cloud-related NO2 bias is typically below 10 %, while for larger solar zenith angles the NO2 bias is on the order of tens of percent.
Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, Oliver Schneising, Heinrich Bovensmann, John P. Burrows, Antonio Di Noia, Robert J. Parker, Hiroshi Suto, Yukio Yoshida, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, Christof Petri, David F. Pollard, Markus Rettinger, Coleen Roehl, Constantina Rousogenous, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, and Thorsten Warneke
Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, https://doi.org/10.5194/amt-15-3401-2022, 2022
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We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
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We present tropospheric ozone column datasets that have been created using combinations of total ozone column from OMI and TROPOMI with stratospheric ozone column datasets from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The main results are (i) several methodological developments, (ii) new tropospheric ozone column datasets from OMI and TROPOMI, and (iii) a new high-resolution dataset of ozone profiles from limb satellite instruments.
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.
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.
Omaira Elena García, Esther Sanromá, Matthias Schneider, Frank Hase, Sergio Fabián León-Luis, Thomas Blumenstock, Eliezer Sepúlveda, Alberto Redondas, Virgilio Carreño, Carlos Torres, and Natalia Prats
Atmos. Meas. Tech., 15, 2557–2577, https://doi.org/10.5194/amt-15-2557-2022, https://doi.org/10.5194/amt-15-2557-2022, 2022
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Accurate observations of atmospheric ozone (O3) are essential to monitor in detail its key role in atmospheric chemistry. In this context, this paper has assessed the effect of using different retrieval strategies on the quality of O3 products from ground-based NDACC FTIR (Fourier transform infrared) spectrometry, with the aim of providing an improved O3 retrieval that could be applied at any NDACC FTIR station.
Edward Malina, Ben Veihelmann, Matthias Buschmann, Nicholas M. Deutscher, Dietrich G. Feist, and Isamu Morino
Atmos. Meas. Tech., 15, 2377–2406, https://doi.org/10.5194/amt-15-2377-2022, https://doi.org/10.5194/amt-15-2377-2022, 2022
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Methane retrievals from remote sensing instruments are fundamentally based on spectroscopic parameters, which indicate spectral-line positions, and their characteristics. These parameters are stored in several databases that vary in their make-up. Here we assess how concentrations of methane isotopologues measured from the same Total Carbon Column Observing Network (TCCON) instruments vary across a range of spectral windows using different spectroscopic databases and comment on the implications.
Merritt Deeter, Gene Francis, John Gille, Debbie Mao, Sara Martínez-Alonso, Helen Worden, Dan Ziskin, James Drummond, Róisín Commane, Glenn Diskin, and Kathryn McKain
Atmos. Meas. Tech., 15, 2325–2344, https://doi.org/10.5194/amt-15-2325-2022, https://doi.org/10.5194/amt-15-2325-2022, 2022
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The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument uses remote sensing to obtain retrievals (measurements) of carbon monoxide (CO) in the atmosphere. This paper describes the latest MOPITT data product, Version 9. Globally, the number of daytime MOPITT retrievals over land has increased by 30 %–40 % compared to the previous product. The reported improvements in the MOPITT product should benefit a wide variety of applications including studies of pollution sources.
Andreas Schneider, Tobias Borsdorff, Joost aan de Brugh, Alba Lorente, Franziska Aemisegger, David Noone, Dean Henze, Rigel Kivi, and Jochen Landgraf
Atmos. Meas. Tech., 15, 2251–2275, https://doi.org/10.5194/amt-15-2251-2022, https://doi.org/10.5194/amt-15-2251-2022, 2022
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This paper presents an extended H₂O/HDO total column dataset from short-wave infrared measurements by TROPOMI including cloudy and clear-sky scenes. Coverage is tremendously increased compared to previous TROPOMI HDO datasets. The new dataset is validated against recent ground-based FTIR measurements from TCCON and against aircraft measurements over the ocean. The use of the new dataset is demonstrated with a case study of a cold air outbreak in January 2020.
Cited articles
Akima, H.: A new method of interpolation and smooth curve fitting based on local procedures, J. ACM, 17, 589–602, https://doi.org/10.1145/321607.321609, 1970. a
Anderson, G. P., Clough, S. A., Kneizys, F. X., Chetwynd, J. H., and Shettle, E. P.: AFGL Atmospheric Constituent Profiles (0–120 km), Environ. Res. Pap. 954, Rep. AFGL-TR-86-0110, Air Force Geophys. Lab., Hanscom AFB, MA, 1986. a
Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/10.5194/amt-4-1905-2011, 2011. a
Bucsela, E. J., Krotkov, N. A., Celarier, E. A., Lamsal, L. N., Swartz, W. H., Bhartia, P. K., Boersma, K. F., Veefkind, J. P., Gleason, J. F., and Pickering, K. E.: A new stratospheric and tropospheric NO2 retrieval algorithm for nadir-viewing satellite instruments: applications to OMI, Atmos. Meas. Tech., 6, 2607–2626, https://doi.org/10.5194/amt-6-2607-2013, 2013. a
Burrows, J. P., Weber, M., Buchwitz, M., Rozanov, V., Ladstätter-Weißenmayer, A., Richter, A., de Beek, R., Hoogen, R., Bramstedt, K., Eichman, K.-U., Eisinger, M., and Perner, D.: The Global Ozone Monitoring Experiment (GOME): Mission concept and first scientific results, J. Atmos. Sci., 56, 151–175, 1999. a
Cai, Z., Liu, Y., Liu, X., Chance, K., Nowlan, C. R., Lang, R., Munro, R., and Suleiman, R.: Characterization and correction of Global Ozone Monitoring Experiment 2 ultraviolet measurements and application to ozone profile retrievals, J. Geophys. Res., 117, D07305, https://doi.org/10.1029/2011JD017096, 2012. a
Chance, K. V. and Spurr, R. J. D.:Ring effect studies: Rayleigh scattering, including molecular parameters for rotational Raman scattering, and the Fraunhofer spectrum, Appl. Opt. 36, 5224–5230, https://doi.org/10.1364/AO.36.005224, 1997. a
Chandrasekhar, S.: Radiative Transfer, Dover Publications, Mineola, New York, 1960. 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
De Smedt, I., Stavrakou, T., Hendrick, F., Danckaert, T., Vlemmix, T., Pinardi, G., Theys, N., Lerot, C., Gielen, C., Vigouroux, C., Hermans, C., Fayt, C., Veefkind, P., Müller, J.-F., and Van Roozendael, M.: Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations, Atmos. Chem. Phys., 15, 12519–12545, https://doi.org/10.5194/acp-15-12519-2015, 2015. a
Desmons, M., Wang, P., Stammes, P., and Tilstra, L. G.: FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2, Atmos. Meas. Tech., 12, 2485–2498, https://doi.org/10.5194/amt-12-2485-2019, 2019. a
Fasnacht, Z., Vasilkov, A., Haffner, D., Qin, W., Joiner, J., Krotkov, N., Sayer, A. M., and Spurr, R.: A geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 2: Evaluation over open ocean, Atmos. Meas. Tech., 12, 6749–6769, https://doi.org/10.5194/amt-12-6749-2019, 2019. a, b
Gao, F., Schaaf, C. B., Strahler, A. H., Roesch, A., Lucht, W., and Dickinson, R.: MODIS bidirectional reflectance distribution function and albedo Climate Modeling Grid products and the variability of albedo for major global vegetation types, J. Geophys. Res., 110, D01104, https://doi.org/10.1029/2004JD005190, 2005. a
Hassinen, S., Balis, D., Bauer, H., Begoin, M., Delcloo, A., Eleftheratos, K., Gimeno Garcia, S., Granville, J., Grossi, M., Hao, N., Hedelt, P., Hendrick, F., Hess, M., Heue, K.-P., Hovila, J., Jønch-Sørensen, H., Kalakoski, N., Kauppi, A., Kiemle, S., Kins, L., Koukouli, M. E., Kujanpää, J., Lambert, J.-C., Lang, R., Lerot, C., Loyola, D., Pedergnana, M., Pinardi, G., Romahn, F., van Roozendael, M., Lutz, R., De Smedt, I., Stammes, P., Steinbrecht, W., Tamminen, J., Theys, N., Tilstra, L. G., Tuinder, O. N. E., Valks, P., Zerefos, C., Zimmer, W., and Zyrichidou, I.: Overview of the O3M SAF GOME-2 operational atmospheric composition and UV radiation data products and data availability, Atmos. Meas. Tech., 9, 383–407, https://doi.org/10.5194/amt-9-383-2016, 2016. a
Hewson, W., Barkley, M. P., Gonzalez Abad, G., Bösch, H., Kurosu, T., Spurr, R., and Tilstra, L. G.: Development and characterisation of a state-of-the-art GOME-2 formaldehyde air-mass factor algorithm, Atmos. Meas. Tech., 8, 4055–4074, https://doi.org/10.5194/amt-8-4055-2015, 2015. a
Hovenier, J. W., van der Mee, C., and Domke, H.: Transfer of Polarized Light in Planetary Atmospheres, Basic Concepts and Practical Methods, Kluwer Academic Publishers, Dordrecht, the Netherlands, 258 pp., 2004. a
Latter, B., Lang, R., and Munro, R.: Cross-comparison of GOME-2, AVHRR and AATSR reflectance, GSICS Quarterly, 5, 3, https://doi.org/10.7289/V5P848V3, 2011. a
Lelli, L., Kokhanovsky, A. A., Rozanov, V. V., Vountas, M., Sayer, A. M., and Burrows, J. P.: Seven years of global retrieval of cloud properties using space-borne data of GOME, Atmos. Meas. Tech., 5, 1551–1570, https://doi.org/10.5194/amt-5-1551-2012, 2012. a
Li, X. and Strahler, A. H.: Geometric-optical bidirectional reflectance modeling of a conifer forest canopy, IEEE T. Geosci. Remote, GE-24, 906–919, https://doi.org/10.1109/TGRS.1986.289706, 1986. a
Liu, S., Valks, P., Pinardi, G., Xu, J., Argyrouli, A., Lutz, R., Tilstra, L. G., Huijnen, V., Hendrick, F., and Van Roozendael, M.: An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2), Atmos. Meas. Tech., 13, 755–787, https://doi.org/10.5194/amt-13-755-2020, 2020. a, b
Lorente, A., Boersma, K. F., Stammes, P., Tilstra, L. G., Richter, A., Yu, H., Kharbouche, S., and Muller, J.-P.: The importance of surface reflectance anisotropy for cloud and NO2 retrievals from GOME-2 and OMI, Atmos. Meas. Tech., 11, 4509–4529, https://doi.org/10.5194/amt-11-4509-2018, 2018. a, b, c, d, e, f, g, h
Loyola, D. G., Xu, J., Heue, K.-P., and Zimmer, W.: Applying FP_ILM to the retrieval of geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) daily maps from UVN satellite measurements, Atmos. Meas. Tech., 13, 985–999, https://doi.org/10.5194/amt-13-985-2020, 2020. a
Matthews, E.: Global vegetation and land use: New high-resolution data bases for climate studies, J. Clim. Appl. Meteorol., 22, 474–487, https://doi.org/10.1175/1520-0450(1983)022<0474:GVALUN>2.0.CO;2, 1983. a
Michalsky, J. J.: The Astronomical Almanac's algorithm for approximate solar position (1950–2050), Sol. Energy, 40, 227–235, 1988. 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
Qin, W., Fasnacht, Z., Haffner, D., Vasilkov, A., Joiner, J., Krotkov, N., Fisher, B., and Spurr, R.: A geometry-dependent surface Lambertian-equivalent reflectivity product for UV–Vis retrievals – Part 1: Evaluation over land surfaces using measurements from OMI at 466 nm, Atmos. Meas. Tech., 12, 3997–4017, https://doi.org/10.5194/amt-12-3997-2019, 2019. a
Roujean, J.-L., Leroy, M., and Deschamps, P.-Y.: A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data, J. Geophys. Res., 97, 20455–20468, https://doi.org/10.1029/92JD01411, 1992. a
Schaepman-Strub, G., Schaepman, M. E., Painter, T. H., Dangel, S., and Martonchik, J. V.: Reflectance quantities in optical remote sensing–definitions and case studies, Remote Sens. Environ., 103, 27–42, https://doi.org/10.1016/j.rse.2006.03.002, 2006. a, b
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
Strahler, A. H, Lucht, W., Schaaf, C. B., Tsang, T., Gao, F., Li, X., Muller, J.-P., Lewis, P., and Barnsley, M. J.: MODIS BRDF/Albedo Product: Algorithm Theoretical Basis Document, MODIS Science Team, Issue 5.0, April, available at: https://modis.gsfc.nasa.gov/data/atbd/atbd_mod09.pdf (last access: 4 June 2021), 1999. a, b, c, d
TEMIS: GOME-2 surface LER database description, available at: https://www.temis.nl/surface/albedo/gome2_ler.php, last access: 4 June 2021. a
Tilstra, L. G., van Soest, G., and Stammes, P.: Method for in-flight satellite calibration in the ultraviolet using radiative transfer calculations, with application to Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), J. Geophys. Res., 110, D18311, https://doi.org/10.1029/2005JD005853, 2005. a
Tilstra, L. G., de Graaf, M., Aben, I., and Stammes, P.: In-flight degradation correction of SCIAMACHY UV reflectances and Absorbing Aerosol Index, J. Geophys. Res., 117, D06209, https://doi.org/10.1029/2011JD016957, 2012. a
Tilstra, L. G., Lang, R., Munro, R., Aben, I., and Stammes, P.: Contiguous polarisation spectra of the Earth from 300 to 850 nm measured by GOME-2 onboard MetOp-A, Atmos. Meas. Tech., 7, 2047–2059, https://doi.org/10.5194/amt-7-2047-2014, 2014. a
van de Hulst, H. C.: Light Scattering by Small Particles, Dover Publications, Mineola, New York, 1981. a
Vasilkov, A., Qin, W., Krotkov, N., Lamsal, L., Spurr, R., Haffner, D., Joiner, J., Yang, E.-S., and Marchenko, S.: Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms, Atmos. Meas. Tech., 10, 333–349, https://doi.org/10.5194/amt-10-333-2017, 2017. a
Veefkind, J. P., de Haan, J. F., Sneep, M., and Levelt, P. F.: Improvements to the OMI O2–O2 operational cloud algorithm and comparisons with ground-based radar–lidar observations, Atmos. Meas. Tech., 9, 6035–6049, https://doi.org/10.5194/amt-9-6035-2016, 2016. a
Wanner, W., Li, X., and Strahler, A. H.: On the derivation of kernels for kernel-driven models of bidirectional reflectance, J. Geophys. Res., 100, 21077–21089, https://doi.org/10.1029/95JD02371, 1995. a
Wessel, P. and Smith, W. H. F.: A global, self-consistent, hierarchical, high-resolution shoreline database, J. Geophys. Res., 101, 8741–8743, https://doi.org/10.1029/96JB00104, 1996. a
Wu, X., Liu, Q., Zeng, J., Grotenhuis, M., Qian, H., Caponi, M., Flynn, L., Jaross, G., Sen, B., Buss Jr., R. H., Johnsen, W., Janz, S., Pan, C., Niu, J., Beck, T., Beach, E., Yu, W., Raja, M. K. R. V, Stuhmer, D., Cumpton, D., Owen, C., and Li, W.-H.: Evaluation of the Sensor Data Record from the nadir instruments of the Ozone Mapping Profiler Suite (OMPS), J. Geophys. Res. Atmos., 119, 6170–6180, https://doi.org/10.1002/2013JD020484, 2014. a
Short summary
In this paper we introduce the new concept of directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface retrieved from satellite observations. We apply this concept to data of the GOME-2 satellite instruments to create a global database of the reflectivity of the Earth's surface, providing surface DLER for 26 wavelength bands between 328 and 772 nm as a function of the satellite viewing angle via a second-degree polynomial parameterisation.
In this paper we introduce the new concept of directionally dependent Lambertian-equivalent...