Coordinator : M. De Mazière BIRA-IASB n ors.aeronomie.be

1. Demonstration Network Of ground-based Remote Sensing observations in support of the GMES Atmospheric Service Coordinator: M. De Mazière BIRA-IASB nors.aeronomie.be

2. Context • European Initiative Global Monitoring for Environment and Security (GMES)  6 thematicareas - atmosphere - land - ocean - security - emergencies - climate Supportedby ESA and EU sinceearly2000

3. Context • A number of ESA and EU projects have been funded in preparation of the operationalGMES AtmosphereService (GAS): In particular the EU projects MACC and MACC-II : Monitoring Atmospheric Composition and Climate, is the current pre-operational atmospheric service of the European GMES programme. www.gmes-atmosphere.eu MACC combines state-of-the-art atmospheric modelling with Earth observation data to provide information services covering European Air Quality, Global Atmospheric Composition, Climate, and UV and Solar Energy. Overall Objectiveof NORS Perform the required research and developments to optimize the NDACC data and data products for the purpose of supporting the quality assessments of the future GAS.

4. NORS NORS is a demonstration project • target NORS data products • tropospheric and stratospheric ozone columns and vertical profiles up to 70 km altitude; • tropospheric and stratospheric NO2 columns and profiles; • lower tropospheric profiles of NO2, HCHO, aerosol extinction; • tropospheric and stratospheric columns of CO • tropospheric and stratospheric columns of CH4 • 4 NDACC techniques: LIDAR, MW, FTIR, UV-VIS DOAS and MAXDOAS • 4 NDACC pilot stations

5. NORS pilot stations Partners: BIRA-IASB, EMPA, INTA, UBern, KIT, CNRS, Ubremen, Ulg, MPIC, UH, S&T 3 out of 4 are also TCCON sites

6. NORS objectives • Rapid data delivery to NDACC with a delay of maximum 1 month (WP3); • Promote NORS data as validation data within GAS: provide an extensive characterisation of targeted NDACC data and user documentation (WP 4); • to investigate the integration of ground-based data products from various sources (ground-based in-situ surface and remote-sensing data, and satellite data) • to provide ground-based measurement time series back to 2003 in support of the re-analysis products of GAS.

7. NORS objectives • to develop and implement a web-based application for validation of MACCII products using the NORS data products. • Capacity building (WP 10): • To ‘export’ project achievements to whole NDACC community • To support the extension of NDACC to stations outside Western Europe, namely in the tropics, in China, Latin America, Africa and Eastern Europe

8. Status of the NORS project • Start Nov. 1, 2011 • Duration: 33 months • KO meeting, Brussels, Dec. 14, 2011 • Alreadyachieved: • NORS website nors.aeronomie.be • Decision about data format: NORS sticks to GEOMS data format • Rapid data delivery systems are set up • Data willbesubmittedto NDACC database, in a separate directory for “NRT” data • User requirements are formulated for the NORS validation server • Validation Server Design Document willbedelivered < July 10. • Goodcommunicationwith the MACC-II project and MACC-II VAL

9. Overview validation server Some things have to be decided by UVVIS WG

10. Questionstothisgroup • RelatedtoURD • Colocation criteria for ‘validation’ • Effectiveairmasslocation of a DOAS/MAXDOAS observation • Whatexactlytocompare ? • ….. • RelatedtoWPs 3 and 4 • Format issues and user guide of the data • Harmonisationandcharacterisation of products • Comparisonsbetween UVVIS and FTIR data for NO2 and HCHO • …..

11. Invitationtothisgroup Cf. WP10 All NDACC teams willingtocontributedata tothe data stream and the validation of the MACC-II products are welcome, providedthat data are submittedrapidly, in GEOMS HDF format andfollowing the guidelinesthatwillbediscussed in this WG oncethe system is up and running (month 18 – 21 of the project  April – July 2013)

13. Description of the validation server • NORS target species: e.g. O3total column at LA.REUNION • MACC-II model: extract O3 data at LA.REUNION… generatedevery 6hours • How tocompare the data? 6h Time MACC output • temporal co-location measurements <-> model data

14. Choose a ‘characteristic time window’ forevery NORS product. Temporal co-location 6h 6h Time MACC output • Windowshouldnotbebiggerthan 6h 1 measurement -> 1 MACC output • FTIR productschoosewindows = 6h `

15. For every measurement, calculate the location of the effective airmass Interpolate the four surrounding MACC-II model data to this effective airmass location: Spatial co-location for every measurement -> a unique corresponding (interpolated) MACC data point.

16. The MACC-II data is smoothedwith the averagingkernel of the NORS measurement Thenstatisticscanbecalculated (mean bias, modifiednormalizedmean bias, …) Comparison of columns Verticalgrid

17. The MACC-II data is smoothed with the averaging kernel of the NORS measurement To compare partial columns, regrid to a vertical grid on which the retrieved profile has about 1 DOF between two boundaries Comparison of profiles 1 DOF • This grid will depend on the instrument (and location). Every instrument should provide its `preferred’ vertical grid.

18. Determine the unit DOF grid • Subgrid of grid in GEOMS data • v=diagonal vector of (averaged) averaging kernel

19. Summarizing for FTIR • For FTIR products: time between MACC outputs = 6h = characteristic time • Calculation of effective airmass location with raytrace tool (based on fastcode) + interpolation • Definition of the ‘preferred vertical grid’. For current NORS FTIR data providers: send the midpoint heights and height indices to bavo.langerock@aeronomie.be