Validation of Methane and Carbon Monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations
- 1Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
- 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
- 3Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
- 4SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
- 5Institute of Environmental Physics, University of Bremen, Bremen, Germany
- 6European Space Agency, ESA/ESRIN
- 7Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
- 8Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, Munich, Germany
- 9Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
- 10Max Planck Institute for Biogeochemistry, Jena, Germany
- 11Izaña Atmospheric Research Centre (IARC), State Meteorological Agency of Spain (AEMET), Santa Cruz de Tenerife, Spain
- 12Centro de Ciencias de la Atmósfera, Universidad Nacional Autonoma de Mexico, UNAM, Mexico
- 13National Center for Atmospheric Research, Boulder, CO, USA
- 14Finnish Meteorological Institute, FMI, Sodankylä, Finland
- 15NASA Ames Research Center, Moffett Field, CA, USA
- 16LERMA-IPSL, Sorbonne Université, CNRS, Observatoire de Paris, PSL Université, Paris, France
- 17Institut d’Astrophysique et de Géophysique, Université de Liège, Liège, Belgium
- 18Department of Atmospheric Physics, Faculty of Physics, St. Petersburg State University, Saint Petersburg, Russia
- 19Earth and Space Sciences, Chalmers University of Technology, Gothenburg, Sweden
- 20UAR 3365 – OSU Réunion, Université de La Réunion, Saint-Denis, Réunion, France
- 21National Institute for Environmental Studies (NIES), Tsukuba, Japan
- 22Institute for Space-Earth Environmental Research (ISEE), Nagoya University, Japan
- 23National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, New Zealand
- 24Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
- 25Department of Physics, University of Toronto, Toronto, Ontario, Canada
- 26Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
- 27Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
- 28Earth Observation Research Center (EORC), Japan Aerospace Exploration Agency (JAXA), Japan
- 29LAGEO, the Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
- 30University of Chinese Academy of Sciences, Beijing, China
- 31Shanghai Ecological Forecasting and Remote Sensing Center, Shanghai, China
Abstract. The Sentinel-5 Precursor (S5P) mission with the TROPOspheric Monitoring Instrument (TROPOMI) onboard has been measuring solar radiation backscattered by the Earth's atmosphere and its surface since its launch on 13 October 2017. Methane (CH4) and carbon monoxide (CO) data with a spatial resolution (initially 7 x 7 km2, upgraded to 5.5 x 7 km2 on 6th of August 2019) have been retrieved from shortwave infrared (SWIR) and near-infrared (NIR) measurements since the end of November 2017 and made available to the experts for early validation and quality checks before the official product release. In this paper, we present for the first time the S5P CH4 and CO validation results (covering a period from November 2017 to September 2020) using global Total Carbon Column Observing Network (TCCON) and Infrared Working Group of the Network for the Detection of Atmospheric Composition Change (NDACC-IRWG) network data, accounting for a priori alignment and smoothing uncertainties in the validation, and testing the sensitivity of validation results towards the application of advanced co-location criteria.
We found that the required bias (systematic error) of 1.5 % and random error of 1 % for the S5P standard and bias-corrected methane data are met for measurements over land surfaces with pixels having quality assurance (QA) value > 0.5. The systematic difference between the S5P standard XCH4 and TCCON data is on average −0.69 ± 0.73 %. The systematic difference changes to a value of −0.25 ± 0.57 % for the S5P bias-corrected XCH4 data. We found a correlation of above 0.6 for most stations, which is mostly dominated by the seasonal cycle. The contributions of smoothing uncertainty at the individual stations are estimated and found to be dependent on the location. The highest contribution of the smoothing uncertainty is observed for mid-latitude TCCON stations and high latitude stations for NDACC. A seasonal dependency of the relative bias is seen. We observe a high bias during the springtime measurements at high SZA and a decreasing bias with increasing SZA for the rest of the year.
We found that the required bias (systematic error) of 15 % and random error of < 10 % for the S5P carbon monoxide data are met in general for measurements over all surfaces with pixels having quality assurance value of > 0.5. There are a few stations where this is not the case, mostly due to co-location mismatches and the limited availability of co-located data. We compared the S5P XCO data with respect to standard TCCON XCO and unscaled TCCON XCO (without application of the empirical scaling factor) data sets. The systematic difference between the S5P XCO and the TCCON data is on average 9.14 ± 3.33 % (standard TCCON XCO data) and 2.36 ± 3.22 % (unscaled TCCON XCO data). We found that the systematic difference between the S5P CO column and NDACC CO column data (excluding two stations that were obvious outliers) is on average 6.44 ± 3.79 %. We found a correlation of above 0.9 for most TCCON and NDACC stations indicating that the temporal variations in CO column captured by the ground-based instruments are reproduced very similarly by the S5P CO column. The contribution of smoothing uncertainty at the individual stations is estimated and found to be significant. They are found to be dependent on the location with large changes seen for stations located in the Southern Hemisphere as compared to the Northern Hemisphere and at highly polluted stations. A cone co-location criterion, which gives a better match between the ground-based instrument's line-of-sight and satellite pixels, seems to give better results for high latitude stations and stations located close to emission sources. The validation results for the clear-sky and cloud cases of S5P pixels are comparable to the validation results including all pixels with quality assurance value of > 0.5. We observe that the relative bias increases with increasing SZA. We estimated this increase is about 10 % over the complete range of measurement SZAs.
The study shows the high quality of S5P CH4 and CO data by validating the products against reference global TCCON and NDACC stations covering a wide range of latitudinal bands, atmospheric conditions, and surface conditions.
Mahesh Kumar Sha et al.
Mahesh Kumar Sha et al.
Mahesh Kumar Sha et al.
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