Technical Bulletins

GOME-2 newsletter #37 May 2015–April 2016

The GOME-2 newsletter provides information about the latest developments concerning the GOME-2 instruments and level 1 product status, as part of the EUMETSAT Polar System (EPS).

GOME-2 Newsletter 37 Fig 1

The Global Ozone Monitoring Experiment–2 (GOME-2) is an optical spectrometer on the Metop satellites.

It is used to get a detailed picture of the total atmospheric content of ozone and the vertical ozone profile in the atmosphere.

You find further details on the GOME-2 page.

Posts from the last six newsletters can be found in this section. Older newsletters can be viewed in the Newsletter Archive (PDF, 8 MB)

PMAp version 2 — AOD over land update released

EUMETSAT released a major update of the Polar Multi-Sensor Aerosol properties (PMAp) product on 17 March 2016. The new release extends the coverage of the previous Aerosol Optical Depth (AOD) product, which was restricted to water surfaces. Now, this AOD product has global coverage, even for solar zenith angles lower than 70 degrees, and includes AOD over almost all land surface types, including desert areas, but excluding surfaces with snow/ice cover. This updated product also contains a realistic AOD error estimate.

The update uses a new netCDF4 data model, which significantly improves the organisation of the data-fields and their structures, and also provides additional parameters. The parameter-naming scheme has been changed to allow compatibility with future mission-naming conventions used for EUMETSAT Polar System-Second Generation (EPS-SG) missions. Complete details are in the updated PMAp user guide (PDF, 870 KB).

The PMAp retrieval algorithm relies on the GOME-2 instrument Polarisation Measurement Device (PMD) observations, and makes use of the unique polarisation-sensitive information it provides. This information also includes sub-pixel resolution information from the AVHRR imager, as well as thermal infrared information from the IASI instrument on the EPS mission.

Figure 1 (top right, click to see full image) shows the PMAp-derived AOD values from both Metop-A and Metop-B satellites, using level-1b data from GOME-2 PMD and AVHRR measurements.

Changes to the retrieval algorithm related to Version 1 of the PMAp product are detailed in the latest version of the Polar Multi-Sensor Aerosol Product: Algorithm Theoretical Basis Document (PDF, 1 MB). Further information can also be found in the PMAp Factsheet (PDF, 659 KB), the updated PMAp validation report for version 2 (PDF, 3 MB) and other relevant documentation on the Technical Documents page.

Instructions on accessing the data, can be found in the PMAp entry in the Product Navigator.

The GOME-2 degradation model for the preparation of GOME-2 level-1C data

The latest version of the GOME-2 degradation model (v.1.0.C) for both Metop-A (M02) and Metop-B (M01) data is available for testing at on our ftp server at:

This version is based on GOME-2 level-1B data generated during the time span of 25/01/2007–31/12/2015 for Metop-A. For Metop-B data, the degradation correction coefficients provided by the model are based on the time span 01/12/2012–31/12/2015. Both models now include an extended model forecast time span that covers data from 01/01/2016–21/12/2016, based on one year of forecast base time, taken from 2015.

The GOME-2 degradation model (v.1.0.C) coefficients, therefore, provide the capability to correct GOME-2 data until the end of 2016. Thus removing potential issues originating from differences in the degradation of the solar path and the earthshine path.

The model assumes a moderate variation of the amount of radiance degradation in the spectral domain. But it is capable of removing significant spectral structures introduced partly by the changing spectral interference patterns of contamination layers on the entrance scan mirror and partly by the solar diffuser systems.

The model provides degradation coefficients for all detector pixels (including the two PMD channels), and separately for the earthshine and solar paths. It also provides a set of coefficients for 24 viewing angle addresses to compensate for the effect of viewing angle differences in the observed differential degradation. Using this technique, the degradation correction can also be separately carried out for solar or earthshine radiances.

Application of version 1.0.C GOME-2 degradation coefficients

To apply the model degradation coefficients is a straightforward process and is detailed in the README file provided with the data on the FTP server. The correction is done by applying this set of equations:

Earthcorr = (Earth — cStray,1,2(v,t,ch=1)) / cEarth (l,v,t)
SMRcorr = SMRNewAIRR / cSMR (l,t)


v is viewing angle
t is Day (Julian date with pivot date 0000-00-00)
l is wavelength (detector pixel)

Since all three dimensions (v, t, and l) are static reference grids, the coefficients have to be interpolated from their fixed grid domains–both in wavelength and viewing angles to the grids actually used in the level-1B data, and for each application.

Note: The set of SMR degradation coefficients (cSMR (l,t)) apply only to in-flight solar-diffuser (AIRR)-calibrated SMR spectra provided with the data in the FTP repository (see the README file on the ftp server).

See the README file for v. 1.0.C for complete specifications and examples instructions for this calculation.

Initial validation: a graphic illustration

Figure 2
Figure 2: GOME-2 signals for the Sun (top), Earthshine (middle), and Reflectance (bottom panel) values at 320 nm (channel 2).

Figure 2 shows the modelled degradation at one wavelength (at 320 nm) and for one viewing angle (v=17 @ close to nadir).

The panels show Solar, Earthshine and Reflectance signals (in red, green and blue plots) over their full model fits (solid black lines) and their temporal degradation coefficients identified as Fit, Trend, and Trend I/I in the plot legends below.

The model applies multiple splines to the in-flight AIRR-calibrated solar signal and excludes instrument anomaly-related outliers. It applies a linear combination of trigonometric functions, together with various polynomial and step-function fittings for the reflectance data.

The reflectance data takes atmospheric seasonal variations into account.

The earthshine model and degradation coefficients are effectively derived by combining the results of the solar model and the reflectance model.

Model input earthshine data is screened for cloud and collected over the Libyan Desert, where surface albedo-related temporal variations are known to be small. Comparisons with degradation coefficients derived from Pacific data screened for clouds have produced the same results.

Figure 3
Figure 3: Reflectivity degradation model coefficients 1.0.C for GOME-2 Metop-A normalised to 25 January 2007.

Figure 3 shows the ratio of Solar path divided by Earthshine path degradation coefficients (cEarth (l,1,t)/cSMR (l,t)) of Metop-A for the most eastward-looking viewing angle (v=1) and for all wavelengths of at least l.0 up to 31 December 2015, as well as for the extended forecast until end 2016. This ratio effectively corrects GOME-2 level-1B reflectance values to level-1C data.

The vertical axis covers all wavelengths from 240 to 780 nm.

The left panel shows the time-series based on level-1B data from the Libyan desert region ending 31 December 2015.

The right panel is the same but extends the model range until end 2016 using polynomial extensions with a forecast base time of one year, 2015.

Note: The model does not correct for the initial degradation condition at the beginning of the time series, which is 25 January 2007 for Metop-A and 1 December 2012 for Metop-B. Therefore, the correction may introduce an offset in the corrected level-1c data. This offset is expected to be static. The impact of this offset on the level-2 retrieval data quality may vary from retrieval to retrieval.

Figure 4: Differences between GOME-2-derived total ozone column (TO3) GDOAS retrievals based,
Figure 5: Relative differences between WOUDC ozone-sonde in-situ measurements and GOME-2 derived total ozone columns (TO3) for one day per month.

Figure 4 shows a time series of total column ozone (TO3) differences relative to January 2017, derived for one day per month over the full Metop-A period, and based on uncorrected level-1B data and corrected level-1C data. The top panel shows absolute differences and the bottom panel relative differences.

The retrieval is carried out with the EUMETSAT in-house suite of GDOAS retrieval monitoring tools. The latter are used for the purpose of monitoring of level-1B data quality and do not necessarily provide the most accurate product quality in absolute terms. For high-quality total column retrievals, see the official operational AC SAF products on the AC SAF website. However, the GDOAS monitoring tools should provide acceptable relative stability.

Figure 5 shows the relative differences between WOUDC ozone-sonde in-situ measurements and GOME-2 derived total ozone columns (TO3) for one day per month. The latter are based on uncorrected level-1B data (blue line) and degradation corrected level-1C data (green line) using the GOME-2 degradation model version 1.0.C.

It shows that the TO3 time series becomes significantly more stable when based on level-1C data corrected for degradation. This result is confirmed by comparison to ozone sonde data from the WOUDC (World Ozone and Ultraviolet Radiation Data Centre) network. With respect to the sonde data, the offset may be a result of both the GDOAS (GOME total ozone DOAS product) retrieval accuracy limitations and the impact of the initial degradation as discussed above.

Disclaimer: EUMETSAT encourages the testing of GOME-2 degradation model v. 1.0.C coefficients by interested users. However, the degradation model data we provide on model data is still only in demonstration status. We welcome feedback on any issues–technical issues as well as quality issues–you have when testing the data. Send an e-mail to EUMETSAT:

Known deficiencies: The region between 283 nm and 300 nm is difficult to model because of the very steep gradients introduced by the ozone absorption involved. Use the data in this region only with additional precautions for potential deficiencies in the degradation coefficients provided here.

Last Updated:  Thursday, 02 March 2017