The use of Sentinel satellite data in the MACC-II GMES pre-operational atmosphere service

1. The use of Sentinel satellite data in the MACC-II GMES pre-operational atmosphere service • R. Engelen, V.-H. Peuch, and the MACC-II team

2. Exciting satellite observations SO2, IASI, Univ. of Brussels/ EUMETSAT SO2, GOME-2, SACS, BIRA/DLR/EUMETSAT Aerosol Optical Depth, MODIS, NASA NO2, OMI, KNMI/NASA

3. Total ozone observations Satellite observations of atmospheric composition are getting better in terms of accuracy and spatial resolution.

4. Synthesis of model and observations Combining observations with models provides significant added value, when we want to forecast the evolution of pollution events for the next few days. 1-day model forecast observations Improved model emissions Using data assimilation (Huijnen et al., 2012)

5. MACC is a component of Europe’s Global Monitoring for Environment and Security (GMES) initiative which provides services for atmosphere, land, ocean, emergency response and security The atmospheric programme comprises developing operational space-based observation of constituents (Sentinels) strengthening the provision of in situ observations (GISC) developing and operating associated data and information services (MACC-II)

6. http://www.gmes-atmosphere.eu MACC-II Services NO2 Air-quality ensemble forecasts and (re-)analyses Stratospheric ozone records UV index Global forecasts Monthly methane emissions …And many more services.

7. What observations do we use Ozone Near-real-time observations for a 12-hour period SCIA SBUV/2 NOAA-17 SBUV/2 NOAA-18 CO MOPITT IASI OMI MLS SO2 NO2 OMI GOME-2 OMI SCIA GOME-2

8. Past & future - O3

9. Past & future - CO Thermal infrared radiances UV/VIS total column

10. MACC ↔ Data Providers • MACC uses a wide variety of satellite and in-situ data to monitor the composition of the atmosphere • MACC also uses the many observations to provide realistic initial conditions for its 5-day forecasts of atmospheric pollution and air quality • MACC can interact with data providers to provide valuable feedback during the development of retrieval products as well as during the operational phase

11. Planned → passive → active The global system produces daily plots of observation-model difference statistics passive active Time series and geographical plots are generated to monitor the input data, but also to provide feedback to data providers. From planned to active for MOPITT CO observations

12. Monitoring of new methane data Observation – model differences Number of observation per 12h GOSAT (NIES) IASI (LMD) SCIAMACHY (SRON) In the MACC delayed (6 months behind) greenhouse monitoring, observations from new satellites (GOSAT, IASI) are being monitored, while the model is being constrained by SCIAMACHY observations. This monitoring provides valuable feedback to the data providers. Any problems can be detected early on and improvements to the algorithms can then be implemented and tested.

13. Feedback from monitoring ppb Monthly mean observation – model differences for methane provide insight in the geographical patterns of systematic errors. Anomalies can easily be identified allowing more detailed assessment in the underlying causes (model and observations). 38 0 -34 SCIAMACHY (assimilated) GOSAT (monitored) IASI (monitored)

14. Summary • MACC-II provides added value products by merging models with satellite and in-situ observations • Assimilating a wide variety of observations allows the production of better forecasts • New satellite observations can be tested at a very early stage to provide valuable feedback to data providers • The Sentinel missions will provide very important observations, which are crucial considering the slowly aging observation network we currently use.