Monitoring and assimilation tests with TROPOMI data in the CAMS system: near-real-time total column ozone

Kurzfassung

The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor (S5P) satellite launched in October 2017 yields a wealth of atmospheric composition data, including retrievals of total column ozone (TCO3) that are provided in near-real time (NRT) and off-line. These NRT TCO3 retrievals (V1.0.0) have been included in the data assimilation system of the Copernicus Atmosphere Monitoring Service (CAMS), and tests to monitor the data and to carry out first assimilation experiments with them have been performed for the period 26 November 2017 to 3 May 2018. TROPOMI was still in its commissioning phase until 24 April 2018. Nevertheless, the results show that, even at this early stage, the TROPOMI TCO3 data generally agree well with the CAMS analysis over large parts of the Globe and also with TCO3 retrievals from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Experiment-2 (GOME-2) that are routinely assimilated by CAMS. However, the TCO3 NRT data from TROPOMI show some retrieval anomalies at high latitudes, at low solar elevations and over snow/ice (e.g. Antarctica) where the differences with the CAMS analysis and the other datasets are larger. These differences come mainly from the surface albedo climatology that is used in the NRT TROPOMI TCO3 retrieval. This climatology has a coarser horizontal resolution than the TROPOMI TCO3 data which leads to problems in areas where there are large changes in reflectivity from pixel to pixel, e.g. pixels covered by snow/ice or not. The assimilation of TROPOMI TCO3 has been tested in the CAMS system for data between 60°N and 60°S and for solar elevations less than 10° and is found to have only little impact on the ozone analysis, because the CAMS analysis is already well constrained by several other ozone retrievals that are routinely assimilated. Variational bias correction is applied to the TROPOMI NRT TCO3 data and successfully corrects for the biases seen in the data. Averaged over the period 26 November 2017 to 3 May 2018, difference between experiments with and without assimilation of TROPOMI data are less than 2% for TCO3 and less than 1% in the vertical for averaged zonal mean O3 mixing ratios. Compared to independent observation (Brewer spectrometers, ozone sondes, IAGOS ozone profiles and GAW surface measurements) the differences between the assimilation run and a run without TROPOMI assimilation are also small. The only noteworthy differences between the experiment with and without assimilation of TROPOMI data are seen compared to IAGOS profiles at West African airports where the assimilation of TROPOMI improves the fit of the CAMS analysis to the independent data. Despite the small impact of TROPOMI TCO3 in the CAMS analysis it will be beneficial to include the TROPOMI TCO3 NRT data actively in the operational NRT CAMS analysis after more tests. This will add some redundancy and resilience in the system and will allow us to use a more robust observation system in case some of the other older instruments, whose retrievals are currently assimilated by CAMS, stop working.