Articles | Volume 14, issue 3
https://doi.org/10.5194/amt-14-2451-2021
© 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-14-2451-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Mar 2021
Research article |
| 31 Mar 2021
| 31 Mar 2021
Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O2–O2, MODIS, and Suomi-NPP VIIRS
Steven Compernolle
CORRESPONDING AUTHOR
Atmospheric Data Synergies, Atmospheric Reactive Gases, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Uccle (Brussels), Belgium
Athina Argyrouli
TUM Department of Civil, Geo and Environmental Engineering, Chair of Remote Sensing Technology, Technical University of Munich, Munich, Germany
Atmospheric Processors, Remote Sensing Technology Institute, German Aerospace Center (DLR), Münchener Straße 20, 82234 Weßling, Germany
Ronny Lutz
Atmospheric Processors, Remote Sensing Technology Institute, German Aerospace Center (DLR), Münchener Straße 20, 82234 Weßling, Germany
Maarten Sneep
Research and Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3730 AE De Bilt, the Netherlands
Jean-Christopher Lambert
Atmospheric Data Synergies, Atmospheric Reactive Gases, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Uccle (Brussels), Belgium
Ann Mari Fjæraa
Atmospheric and Climate Research, Norsk Institutt for Luftforskning (NILU), Instituttveien 18, 2007 Kjeller, Norway
Daan Hubert
Atmospheric Data Synergies, Atmospheric Reactive Gases, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Uccle (Brussels), Belgium
Arno Keppens
Atmospheric Data Synergies, Atmospheric Reactive Gases, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Uccle (Brussels), Belgium
Diego Loyola
Atmospheric Processors, Remote Sensing Technology Institute, German Aerospace Center (DLR), Münchener Straße 20, 82234 Weßling, Germany
Ewan O'Connor
Finnish Meteorological Institute (FMI), Helsinki, Finland
Department of Meteorology, University of Reading, Whiteknights, P.O. Box 217, Reading, Berkshire RG6 6AH, United Kingdom
Fabian Romahn
Atmospheric Processors, Remote Sensing Technology Institute, German Aerospace Center (DLR), Münchener Straße 20, 82234 Weßling, Germany
Piet Stammes
Research and Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3730 AE De Bilt, the Netherlands
Tijl Verhoelst
Atmospheric Data Synergies, Atmospheric Reactive Gases, Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Ringlaan 3, 1180 Uccle (Brussels), Belgium
Ping Wang
Research and Development Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3730 AE De Bilt, the Netherlands
Viewed
Total article views: 3,781 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Jun 2020)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 2,585 | 1,124 | 72 | 3,781 | 317 | 97 | 84 |
- HTML: 2,585
- PDF: 1,124
- XML: 72
- Total: 3,781
- Supplement: 317
- BibTeX: 97
- EndNote: 84
Total article views: 2,726 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 31 Mar 2021)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 2,090 | 576 | 60 | 2,726 | 166 | 72 | 66 |
- HTML: 2,090
- PDF: 576
- XML: 60
- Total: 2,726
- Supplement: 166
- BibTeX: 72
- EndNote: 66
Total article views: 1,055 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Jun 2020)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 495 | 548 | 12 | 1,055 | 151 | 25 | 18 |
- HTML: 495
- PDF: 548
- XML: 12
- Total: 1,055
- Supplement: 151
- BibTeX: 25
- EndNote: 18
Viewed (geographical distribution)
Total article views: 3,781 (including HTML, PDF, and XML)
Thereof 3,590 with geography defined
and 191 with unknown origin.
Total article views: 2,726 (including HTML, PDF, and XML)
Thereof 2,640 with geography defined
and 86 with unknown origin.
Total article views: 1,055 (including HTML, PDF, and XML)
Thereof 950 with geography defined
and 105 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
29 citations as recorded by crossref.
- Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products M. Haarig et al. 10.5194/amt-16-5953-2023
- Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign K. Lange et al. 10.5194/amt-16-1357-2023
- Temporal assessment of air quality in major cities in Nigeria using satellite data K. Mahmud et al. 10.1016/j.aeaoa.2023.100227
- A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band W. Wang et al. 10.1016/j.rse.2024.114267
- TROPOMI tropospheric ozone column data: geophysical assessment and comparison to ozonesondes, GOME-2B and OMI D. Hubert et al. 10.5194/amt-14-7405-2021
- The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission A. Sayer et al. 10.5194/amt-16-969-2023
- Improved catalog of NOx point source emissions (version 2) S. Beirle et al. 10.5194/essd-15-3051-2023
- A Cloud Identification Method Based on Spectral and Textural Characteristics of Oxygen A Band in TROPOMI Imagery Z. Guo et al. 10.1109/TGRS.2023.3336655
- Satellite derived SO2 emissions from the relatively low-intensity, effusive 2021 eruption of Fagradalsfjall, Iceland B. Esse et al. 10.1016/j.epsl.2023.118325
- A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations S. Warnach et al. 10.5194/amt-16-5537-2023
- Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons J. Park et al. 10.1080/15481603.2022.2026640
- Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic K. Vinjamuri et al. 10.5194/amt-16-2903-2023
- Estimating Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation H. Jethva et al. 10.1029/2022EA002354
- Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data J. van Geffen et al. 10.5194/amt-15-2037-2022
- An improved TROPOMI tropospheric NO2 research product over Europe S. Liu et al. 10.5194/amt-14-7297-2021
- Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals M. Latsch et al. 10.5194/amt-15-6257-2022
- Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields S. Maratt Satheesan et al. 10.5194/amt-17-6459-2024
- First results of cloud retrieval from the Geostationary Environmental Monitoring Spectrometer B. Kim et al. 10.5194/amt-17-453-2024
- Aerosol Parameters Retrieval From TROPOMI/S5P Using Physics-Based Neural Networks L. Rao et al. 10.1109/JSTARS.2022.3196843
- A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources N. Theys et al. 10.5194/acp-21-16727-2021
- Horizontal distribution of tropospheric NO2 and aerosols derived by dual-scan multi-wavelength multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in Uccle, Belgium E. Dimitropoulou et al. 10.5194/amt-15-4503-2022
- Potential of TROPOMI for understanding spatio-temporal variations in surface NO2 and their dependencies upon land use over the Iberian Peninsula H. Petetin et al. 10.5194/acp-23-3905-2023
- Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements I. De Smedt et al. 10.5194/acp-21-12561-2021
- An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI A. Argyrouli et al. 10.5194/amt-17-6345-2024
- Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI S. Beirle et al. 10.5194/essd-13-2995-2021
- Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks T. Verhoelst et al. 10.5194/amt-14-481-2021
- Nitrogen dioxide reductions from satellite and surface observations during COVID-19 mitigation in Rome (Italy) C. Bassani et al. 10.1007/s11356-020-12141-9
- New observations of NO2 in the upper troposphere from TROPOMI E. Marais et al. 10.5194/amt-14-2389-2021
- Nitrogen dioxide decline and rebound observed by GOME-2 and TROPOMI during COVID-19 pandemic S. Liu et al. 10.1007/s11869-021-01046-2
25 citations as recorded by crossref.
- Cloud top heights and aerosol columnar properties from combined EarthCARE lidar and imager observations: the AM-CTH and AM-ACD products M. Haarig et al. 10.5194/amt-16-5953-2023
- Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign K. Lange et al. 10.5194/amt-16-1357-2023
- Temporal assessment of air quality in major cities in Nigeria using satellite data K. Mahmud et al. 10.1016/j.aeaoa.2023.100227
- A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band W. Wang et al. 10.1016/j.rse.2024.114267
- TROPOMI tropospheric ozone column data: geophysical assessment and comparison to ozonesondes, GOME-2B and OMI D. Hubert et al. 10.5194/amt-14-7405-2021
- The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission A. Sayer et al. 10.5194/amt-16-969-2023
- Improved catalog of NOx point source emissions (version 2) S. Beirle et al. 10.5194/essd-15-3051-2023
- A Cloud Identification Method Based on Spectral and Textural Characteristics of Oxygen A Band in TROPOMI Imagery Z. Guo et al. 10.1109/TGRS.2023.3336655
- Satellite derived SO2 emissions from the relatively low-intensity, effusive 2021 eruption of Fagradalsfjall, Iceland B. Esse et al. 10.1016/j.epsl.2023.118325
- A new accurate retrieval algorithm of bromine monoxide columns inside minor volcanic plumes from Sentinel-5P TROPOMI observations S. Warnach et al. 10.5194/amt-16-5537-2023
- Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons J. Park et al. 10.1080/15481603.2022.2026640
- Validation of the Cloud_CCI (Cloud Climate Change Initiative) cloud products in the Arctic K. Vinjamuri et al. 10.5194/amt-16-2903-2023
- Estimating Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation H. Jethva et al. 10.1029/2022EA002354
- Sentinel-5P TROPOMI NO2 retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data J. van Geffen et al. 10.5194/amt-15-2037-2022
- An improved TROPOMI tropospheric NO2 research product over Europe S. Liu et al. 10.5194/amt-14-7297-2021
- Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals M. Latsch et al. 10.5194/amt-15-6257-2022
- Improved convective cloud differential (CCD) tropospheric ozone from S5P-TROPOMI satellite data using local cloud fields S. Maratt Satheesan et al. 10.5194/amt-17-6459-2024
- First results of cloud retrieval from the Geostationary Environmental Monitoring Spectrometer B. Kim et al. 10.5194/amt-17-453-2024
- Aerosol Parameters Retrieval From TROPOMI/S5P Using Physics-Based Neural Networks L. Rao et al. 10.1109/JSTARS.2022.3196843
- A sulfur dioxide Covariance-Based Retrieval Algorithm (COBRA): application to TROPOMI reveals new emission sources N. Theys et al. 10.5194/acp-21-16727-2021
- Horizontal distribution of tropospheric NO2 and aerosols derived by dual-scan multi-wavelength multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements in Uccle, Belgium E. Dimitropoulou et al. 10.5194/amt-15-4503-2022
- Potential of TROPOMI for understanding spatio-temporal variations in surface NO2 and their dependencies upon land use over the Iberian Peninsula H. Petetin et al. 10.5194/acp-23-3905-2023
- Comparative assessment of TROPOMI and OMI formaldehyde observations and validation against MAX-DOAS network column measurements I. De Smedt et al. 10.5194/acp-21-12561-2021
- An advanced spatial coregistration of cloud properties for the atmospheric Sentinel missions: application to TROPOMI A. Argyrouli et al. 10.5194/amt-17-6345-2024
- Catalog of NOx emissions from point sources as derived from the divergence of the NO2 flux for TROPOMI S. Beirle et al. 10.5194/essd-13-2995-2021
4 citations as recorded by crossref.
- Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks T. Verhoelst et al. 10.5194/amt-14-481-2021
- Nitrogen dioxide reductions from satellite and surface observations during COVID-19 mitigation in Rome (Italy) C. Bassani et al. 10.1007/s11356-020-12141-9
- New observations of NO2 in the upper troposphere from TROPOMI E. Marais et al. 10.5194/amt-14-2389-2021
- Nitrogen dioxide decline and rebound observed by GOME-2 and TROPOMI during COVID-19 pandemic S. Liu et al. 10.1007/s11869-021-01046-2
Latest update: 04 Feb 2025
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.
The high-resolution satellite Sentinel-5p TROPOMI observes several atmospheric gases. To account...
