The TOAR database and its interfaces

The foundation of the IntelliAQ project is the TOAR database, the world’s largest collection of surface observation data of ozone, ozone precursor gases, meteorological variables, selected tracers for pollution source attributions, and selected results from numerical models of the atmospheric dynamic and chemical composition. Most of these data constitute timeseries of measurements at specific point locations, the “stations”. Various researchers directly submit their data to the TOAR data centre, where they are reformatted, quality controlled, and inserted to the TOAR database. If requested by the data submitters, the reformatted and augmented files from these direct submissions will also be published in a FAIR data service, including a doi for reference in journal publications, presentations, and elsewhere. However, the majority of data in the TOAR database is not “primary data”, but a copy of data from other databases and repositories.

Particular strengths of this globally harmonized database are a unified access to the data and the application of consistent statistical methods everywhere, which make the results comparable.
The data and metrics are made available via a graphical web interface (for documentation see: https://join.fz-juelich.de/static/documentation/JOIN_FAQ.pdf ), a REST service (for documentation see: https://join.fz-juelich.de/services/rest/surfacedata/ ) and as aggregated products on PANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.876108 ). A Collection of software tools to facilitate access to and processing of data can be found in the Gitlab-Repository https://jugit.fz-juelich.de/m.schultz/toar-public-utilities.

Figure 2:The JOIN Web-Interface to TOAR data showing ozone data from one station over a time span of 23 years
Figure 2:The JOIN Web-Interface to TOAR data showing ozone data from one station over a time span of 23 years
Figure 3:REST API, available parameters for surfacedataFigure 4: REST API, queries for detailed information

GeoDataServices

Figure 1: Europe’s nighttime light brightness as exemplary illustration of GeoDataServices’ underlying high resolution data (own graph). Image and Data is processed by NOAA’s National Geophysical Data Center and collected by the US Air Force Weather Agency.

With GeoDataServices (Schultz, M.G. et.al., 2018), we enable an automated and flexible characterisation of an arbitrary point location using high resolution data. These services are accessible through a standardised REST API and can therefore easily be used by both human and machine. In the current version, GeoDataServices includes geographical information on topography and dominant land surface covers, anthropogenic data about urbanisation (human settlements, built-up areas, nighttime light brightness, population density and streets) and agriculture yields (rice and wheat), climatological and environmental data as NOx emissions and climatic zones. Combining this data, GeoDataServices can characterise any point location and therefore enables users to compare locations in a personalised -use case driven- way. For this personalisation, each query needs to be specified with a radius around the point location, in which a given statistical aggregation function is applied. Beside this personalised information preparation, the GeoDataServices are also included in the TOAR database metadata creation. GeoDataServices is currently under development and not yet accessible for the public. However, interested people are encouraged to contact us for more insight into GeoDataServices.

Reference: Schultz, Martin G., et al. “A web service architecture for objective station classification purposes.” 2018 IEEE 14th International Conference on e-Science (e-Science). IEEE, 2018.

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