1. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276. www.gaia-clim.eu This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276. www.gaia-clim.eu The GAIA-CLIM Virtual Observatory Jörg Schulz With thanks to Bill Bell, Jacques Descloitres, Marie Doutriaux- Boucher, Paul Green, Jean-Christopher Lambert, Arndt Meier, Tony Reale, Kuldar Taveter, Kaalev Tuldar

2. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276. www.gaia-clim.eu Virtual Observatory Develop a sustainable facility that supports Copernicus Services and science to analyse product quality in routine mode. Provision of open access to collocated data and their meta data including all assessed uncertainties; Provision of access to documentation of the data and uncertainty assessment methods, e.g. the traceability chains; Provision of graphical displays of collocation ; Provision of online analysis of collocation data subsample, e.g., spatially, regionally, meteorologically, per satellite, etc.; VO in GAIA-CLIM will be demonstrational, however, its design aims at becoming an operational tool at later stage; Needs to be extendable in terms of reference data and satellite missions.

3. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276. www.gaia-clim.eu Indications from User Survey The most frequent intended application is model evaluation Uncertainties: what and how to be reported needs to be reviewed. Timeliness: Offline or delayed fine for now. However, the design needs to foresee an eventual operational near real time capability. Data format: large agreement for NetCDF4. Flexible forward radiative transfer modelling capability, allowing e.g. to bring radiosonde data into brightness temperature space to compare against Level 1 satellite data. VO Tools: sub-setting by variable, time and location, but also by observing system and by surface type. Online data post-processing: re-gridding to a specified resolution and or time step and average data in space and/or time. At a later stage possibly vertical smoothing. Extraction tools: comparison of collocated data files/specified subsets. At a later stage trend and step-change analysis, stability tests, and anomaly calculations. Visualization tools: graphical maps and time series. Possibly at a later stage plots with comparison statistics. Concise documentation Easy access

4. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276. www.gaia-clim.eu Design of the VO Modular and adaptive – and a bit of pragmatism Take advantage of existing tools, e.g. for co-location and sub-setting (STAMP, ICARE, Felyx, …) Compliant with C3S standard (Copernicus Services) and EUMETSAT standards for operational software Decide on some core features and 3 pilot data sets that are “safe bets” start the development around these add specific plug-ins for emerging needs as necessary involve selected β–users throughout the whole process no general code lock-down planned – the VO will try to accommodate for anticipated progress in the other WPs - but please let us know your plans early.

5. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640276. www.gaia-clim.eu ECV priorities Priorities in terms of ECVs and pilot data sets to be used during development and for showcasing the VO: Temperature profiles (Satellite+GRUAN, possibly ARSA radiosondes from DWD) Humidity – we are looking at 3 distinct and complementing products: Profiles of abs. Humidity (kg/kg) from microwave sounders (183 GHz) versus GRUAN Total column water vapour (TCWV), ARSA radiosonde data base from marc.schroeder@dwd.demarc.schroeder@dwd.de Upper troposphere humidity: relative humidity, 30 years of METEOSAT data Comparison with NWP where possible Aerosols, AOD at 550nm from space and reference data from AERONET and possibly LIDAR (if traceability completed in time) GCOS Greenhouse gases, in particular Ozone. Reference data from Dobson/Brewer ground-based networks. Others reference data to be added depending on level of completeness of traceability within given timeframes (the more the merrier). Priorities in terms of ECVs and pilot data sets to be used during development and for showcasing the VO: Temperature profiles (Satellite+GRUAN, possibly ARSA radiosondes from DWD) Humidity – we are looking at 3 distinct and complementing products: Profiles of abs. Humidity (kg/kg) from microwave sounders (183 GHz) versus GRUAN Total column water vapour (TCWV), ARSA radiosonde data base from marc.schroeder@dwd.demarc.schroeder@dwd.de Upper troposphere humidity: relative humidity, 30 years of METEOSAT data Comparison with NWP where possible Aerosols, AOD at 550nm from space and reference data from AERONET and possibly LIDAR (if traceability completed in time) GCOS Greenhouse gases, in particular Ozone. Reference data from Dobson/Brewer ground-based networks. Others reference data to be added depending on level of completeness of traceability within given timeframes (the more the merrier).