3d mappingof existingobservingcapabilities in the frame of ... · 3d mappingof...
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3D mapping of existing observing capabilitiesin the frame of GAIA-CLIM H2020 projectE.Tramutola,F.Madonna,M.Rosoldi,F.AmatoandtheGAIA-CLIMtask1.2Team
ConsiglioNazionaledelleRicerche,IstitutodiMetodologieperl’AnalisiAmbientale(CNR-IMAA),85050,TitoScalo,Potenza,Italy
The project GAIA-CLIM
The aim of the Gap Analysis for Integrated Atmospheric ECV CLImate Monitoring (GAIA-CLIM) project is to improve our ability touse ground-based and sub-orbital observations to characterize satellite observations for a number of atmospheric EssentialClimate Variables (ECVs). The key outcomes will be a “Virtual Observatory” (VO) facility of co-locations and their uncertainties anda report on gaps in capabilities or understanding, which shall be used to inform subsequent Horizon 2020 activities.
In particular, Work Package 1 (WP1) of the GAIA-CLIM project is devoted to the geographical mapping of existing non-satellitemeasurement capabilities for a number of ECVs in the atmospheric, oceanic and terrestrial domains.The work carried out within WP1 has allowed to provide the users with an up-to-date geographical identification, at the Europeanand global scales, of current surface-based, balloon-based and oceanic (floats) observing capabilities on an ECV by ECV basis forseveral parameters which can be obtained using space-based observations from past, present and planned satellite missions.
Metadata collectionHaving alighted on a set of metadata schema to follow, a consistent collection of discovery metadata has been provided into acommon structure and will be made available to users through the GAIA-CLIM VO in 2018.Metadata can be interactively visualized through a 3D Graphical User Interface.The metadataset includes 54 plausible networks and 2 aircraft permanent infrastructures for EO Characterization in the context ofGAIA-CLIM currently operating on different spatial domains and measuring different ECVs using one or more measurementtechniques.Each classified network has in addition been assessed for suitability against metrological criteria to identify those with a level ofmaturity which enables closure on a comparison with satellite measurements.
NETWORK NUM STATIONSACTRIS 71AD-Net 20
AERONET 1248AGAGE 12AMeDAS 948ARGO 3917ARM 15BSRN 64
CAPMoN 31CARSNET 50CASTNET 100CAWNET 20CREST 4EANET 42Earlinet 27EMEP 245EPA 2166ESRL 200EUREF 265
EuroSkyRad 13Fluxnet 587
GAW GALION 74GAW PFR 29GPS-Met 618GRUAN 17
GSN 848GUAN 171ICOS 29IDAF 10IGS 428
IMPROVE 194LALINET-ALINE 10
MESONET 138MPLNET 15MWRnet 81NDACC 73
NPS 113RAOB 1483RBSN 5392
Scripps CO2 13SHADOZ 19SKYNET 24SMEAR 5
SUOMINET 940SURFRAD 8TCCON 27TOLNET 5USCRN 139WOUDC 351
Tool 3DThe metadata GUI is based on Cesium, a virtual globe freeware and open source written in Javascript. It allows users to apply different filters to the data displayed onthe globe, selecting data per ECV, network, measurementstype and level of maturity. Filtering is operated with a query to GeoServer web application through the WFS interface on a data layer configured on our DB Postgres withPostGIS extension; filters set on the GUI areexpressed using ECQL (Extended Common Query Language).
The GUI allows to visualize in real-time the current non-satellite observing capabilities along with the satellite platforms measuring the same ECVs. Satellite groundtrack and footprint of the instruments on board can be alsovisualized.
This work contributes to improve metadata and web map services and to facilitate users’ experience in the spatio-temporal analysis of Earth Observation data.
ECV NUMAEROSOL 3689
CARBON DIOXIDE 825CARBON MONOXIDE 560
METHANE 244NITROGEN DIOXIDE 569
NOX 31OZONE 2077
TEMPERATURE 7088TEMPERATURE, SALINITY 3917
WATER VAPOR 6016
ECV FEATURETYPE NUMAEROSOL column 1439AEROSOL profile 152AEROSOL surface 2115AEROSOL tower 20
CARBON DIOXIDE column 27CARBON DIOXIDE profile 33CARBON DIOXIDE surface 177CARBON DIOXIDE tower 609
CARBON MONOXIDE column 43CARBON MONOXIDE profile 51CARBON MONOXIDE surface 484CARBON MONOXIDE tower 20
METHANE column 43METHANE profile 51METHANE surface 168METHANE tower 11
NITROGEN DIOXIDE column 38NITROGEN DIOXIDE profile 38NITROGEN DIOXIDE surface 531NITROGEN DIOXIDE tower 2
NOX surface 31OZONE aircraft 15OZONE column 421OZONE profile 241OZONE surface 1552OZONE tower 2
TEMPERATURE profile 1563TEMPERATURE surface 6727TEMPERATURE tower 3
TEMPERATURE,SALINITY profile 3917WATER VAPOR column 3582WATER VAPOR profile 1559WATER VAPOR surface 344WATER VAPOR tower 590
Application Desktop
gaiaclimservice{RESTful web service}
Software architecture
EGU2017-16935
This project has received funding fromthe European Union’s Horizon 2020research and innovation programmeunder grant agreement No 640276.
http://150.145.73.221/Cesium/Apps/GaiaClimTool 3D site:
www.gaia-clim.euGaia-Clim site:
CNR-IMAA Atmospheric Observatory (CIAO) site:www.ciao.imaa.cnr.it
Acknowledgements
We gratefully acknowledge all the PIs and data manager of the measurements networks who facilitated out work to deal with the maturity matrix assessment of each ofthese components of the global observing system. In non-alphabetical order: A. Shimizu (NIES), M. Fujiwara (JMA), M. Palecki (NOAA), S. Lolli (NASAJCET),T. Leblanc(NASA-JPL), M. Campanelli (ISAC-CNR), A. Thompson (NOAA), V. Estelles (CSIC), R. Dirksen(DWD), A. Comeron (Univ. Politecnica de Catalunya), M. Fujiwara (HokkaidoUniversity), D. Sisterson (DOEARM,US), T. Eck (NASA-GSFC).We also acknowledge the requirements of the BING maps add-in, its use ofis done in agreement to the terms and conditions and privacy statement.