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. SO 2, GOME-2, SACS, BIRA/DLR/EUMETSAT NO 2, OMI, KNMI/NASA Aerosol Optical Depth, MODIS, NASA SO 2, IASI, Univ. of Brussels/ EUMETSAT Exciting satellite observations

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

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

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 Air-quality ensemble forecasts and (re-)analyses UV index Stratospheric ozone records Monthly methane emissions Global forecasts NO 2 …And many more services. MACC-II Services

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

8. Past & future - O3

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

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

12. SCIAMACHY (SRON)IASI (LMD)GOSAT (NIES) Monitoring of new methane data 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. Observation – model differences Number of observation per 12h

13. Feedback from monitoring SCIAMACHY (assimilated) IASI (monitored) GOSAT (monitored) 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 -34 ppb 0

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.