Global methane column-averaged dry air mole fraction (XCH4) from TROPOMI WFM-DOAS, since 2017

Schneising, Oliver; Buchwitz, Michael; Reuter, Maximilian; Bovensmann, Heinrich; Burrows, John P.; Borsdorff, Tobias; Deutscher, Nicholas M.; Feist, Dietrich G.; Griffith, David W. T.; Hase, Frank; Hermans, Christian; Iraci, Laura T.; Kivi, Rigel; Landgraf, Jochen; Morino, Isamu; Notholt, Justus; Petri, Christof; Pollard, David F.; Roche, Sébastien; Shiomi, Kei; Strong, Kimberly; Sussmann, Ralf; Velazco, Voltaire A.; Warneke, Thorsten; and Wunch, Debra

Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and methane (CH4) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which was successfully launched in October 2017, is a spaceborne nadir-viewing imaging spectrometer measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR), combining a high spatial resolution with daily global coverage. These characteristics enable the determination of both gases with an unprecedented level of detail on a global scale, introducing new areas of application. Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH4 are simultaneously retrieved from TROPOMIs radiance measurements in the 2.3µm spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). This algorithm is intended to be used with the operational algorithms for mutual verification and to provide new geophysical insights. We introduce the algorithm in detail, including expected error characteristics based on synthetic data, a machine-learning-based quality filter, and a shallow learning calibration procedure applied in the post-processing of the XCH4 data. The quality of the results based on real TROPOMI data is assessed by validation with ground-based Fourier transform spectrometer (FTS) measurements providing realistic error estimates of the satellite data: the XCO data set is characterised by a random error of 5.1ppb (5.8%) and a systematic error of 1.9ppb (2.1%); the XCH4 data set exhibits a random error of 14.0ppb (0.8%) and a systematic error of 4.3ppb (0.2%). The natural XCO and XCH4 variations are well-captured by the satellite retrievals, which is demonstrated by a high correlation with the validation data (R=0.97 for XCO and R=0.91 for XCH4 based on daily averages).

Citation

Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019.

Contact

Schneising, Oliver

Metadata Access

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Data and Resources

Additional Info

Field Value
Identifier DOI:10.5194/amt-12-6771-2019
Project(s) ESA Climate Change Initiative “Plus” (CCI+)
Institute University of Bremen
Source https://www.iup.uni-bremen.de/carbon_ghg/products/tropomi_wfmd/
Publication Date 2019-12-19
Version v1.8
Product TROPOMI WFM-DOAS (TROPOMI/WFMD) XCH4
Sensor TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel-5 Precursor
Files
  1. Product User Guide (PUG)
  2. Algorithm Theoretical Basis Document (ATBD)
Variables [Units]
  1. orbit_number: Orbit number
  2. scanline: along track dimension index (This dimension variable defines the indices along track)
  3. ground_pixel: across track dimension index (This dimension variable defines the indices across track)
  4. latitude_corners: latitude corners (Corner latitudes of the measurement) [degree_north]
  5. longitude_corners: longitude corners (Corner longitude of the measurement) [degree_east]
  6. altitude: altitude (Average surface altitude) [m]
  7. surface_roughness: surface roughness [m]
  8. apparent_albedo: apparent surface albedo (Retrieved surface albedo at 2313nm)
  9. land_fraction: land fraction (Land fraction of the observed scene in percent) [1e-2]
  10. cloud_parameter: cloud parameter from strong water vapour absorption (Ratio of measured to cloud-free reference radiance for selected strong water vapour lines)
  11. co_column: vertical column of carbon monoxide (Retrieved vertical column amount of carbon monoxide) [mol m-2]
  12. h2o_column: vertical column of water vapour (Retrieved vertical column amount of water vapour) [g cm-2]
  13. h2o_column_uncertainty: 1-sigma uncertainty of the retrieved vertical column of atmospheric water vapour [g cm-2]
  14. satellite_altitude: satellite altitude (Altitude of the spacecraft relative to the WGS84 reference ellipsoid) [m]
  15. satellite_latitude: satellite latitude (Latitude of the spacecraft sub-satellite point on the WGS84 reference ellipsoid) [degrees_north]
  16. satellite_longitude: satellite longitude (Longitude of the spacecraft sub-satellite point on the WGS84 reference ellipsoid) [degrees_east]
Region Global
Spatial Reference EPSG:4326 WGS 84
Spatial Resolution 5.5km x 7km at nadir (typically)
Spatial Coverage Latitude -90.00 to 90.00, Longitude -180.00 to 180.00
Temporal Coverage since 2017-11
Temporal Resolution P1D
Format NetCDF
Is Supplement To

Schneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019.

Related to

Schneising, O., Buchwitz, M., Hachmeister, J., Vanselow, S., Reuter, M., Buschmann, M., Bovensmann, H., and Burrows, J. P.: Advances in retrieving methane and carbon monoxide from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2022-258, in review, 2022.

Schneising, O., Buchwitz, M., Reuter, M., Vanselow, S., Bovensmann, H., and Burrows, J. P.: Remote sensing of methane leakage from natural gas and petroleum systems revisited, Atmos. Chem. Phys., 20, 9169–9182, https://doi.org/10.5194/acp-20-9169-2020, 2020.

Hachmeister, J., Schneising, O., Buchwitz, M., Lorente, A., Borsdorff, T., Burrows, J. P., Notholt, J., and Buschmann, M.: On the influence of underlying elevation data on Sentinel-5 Precursor TROPOMI satellite methane retrievals over Greenland, Atmos. Meas. Tech., 15, 4063–4074, https://doi.org/10.5194/amt-15-4063-2022, 2022.

Dataset extent

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