Distributing and Visualizing Drifter Data in COSMO

Abstract

In the context of the COSMO project (CTM2016-79474-R, MINECO/FEDER,UE), a series of activities are under way to assess the quality of the ocean currents derived by ocean forecast systems. Key elements for these assessments are a set of regular Lagrangian experiments performed by Salvamento Marítimo and the release of 18 surface drifters near Gibraltar Strait during the MEDGIB-II Campaign on January 19, 2018.Timely processing of both Lagrangian data and operational forecasts are required to correctly perform such assessment. The surface drifters use several kinds of transmission technologies, using different datatypes and formats and coming from different data sources. Therefore these different formats and data sources need to be unified and standardized. Among the various possibilities, we decided to use the GeoJSON format. So, to distribute the Lagrangian data from the field experiments a new data distribution system has been developed. This system can download the data from all the transmission data source providers, process and convert them to the GeoJSON format. Moreover, the system allows to access and download the data using a web browser with a low bandwidth consumption. The data is converted to the Keyhole Markup Language (KML) format too and it can be directly viewed in the Earth browsers (e.g. Google Earth).The COSMO-VIEW tool is an interactive GUI programmed in Python. This GUI is able to remotely access ocean predictions provided by Puertos del Estado and SOCIB through OPeNDAP protocol and to launch MOTU queries to the COPERNICUS service to download data from their operational prediction systems. The tool is able to superpose th elatest images of satellite sea surface temperature and the hourly currents from the various HF Radar stations provided by Puertos del Estado and SOCIB as well as to superpose the trajectories of the surface drifters released during the COSMO project (GeoJSON format)and the trajectories simulated by the COSMO Lagrangian Mode