Issue |
Radioprotection
Volume 51, Number HS1, 2016
Towards a self-sustaining European platform on nuclear and radiological emergency preparedness, response and recovery. Key results of the NERIS-TP European project
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Page(s) | S13 - S16 | |
DOI | https://doi.org/10.1051/radiopro/2016004 | |
Published online | 21 July 2016 |
Article
New functionalities developed in the NERIS-TP project regarding meteorological data used by Decision Support Systems
1 NCSR Demokritos, Institute of Nuclear
and Radiological Sciences and Technology, Energy and Safety, Aghia
Paraskevi, Attiki,
Greece.
2 Ukranian Centre for Environmental and
Water Projects (UCEWP), prosp. Glushkova, 42, Kiev, Ukraine.
3 Institute of Mathematical Machines
& Systems Problems NAS of Ukraine (IMMSP), prosp. Glushkova, 42,
Kiev,
Ukraine.
4 Karlsruher Institut für Technologie
(KIT), Campus Nord, IKET, Bau 433, 76021
Karlsruhe,
Germany.
In this paper a description is given of software tools that have been developed during the NERIS-TP project which provide the capability to users of Decision Support Systems (DSSs), such as JRODOS, to calculate their own prognostic meteorological data with the desired spatial and temporal resolution. These tools increase the flexibility of applying the DSSs for any location on the Earth. This is achieved by downloading freely available global meteorological data and downscaling them using the prognostic meteorological model WRF. The results of WRF and/or global data are uploaded to the DSS to calculate the atmospheric dispersion. The above software tools operate in an automated way, in conjunction with the DSS. In addition, data assimilation methodologies have been integrated into the Meteorological Pre-Processor of JRODOS, to correct previously calculated prognostic data on the basis of locally measured meteorological data. These data assimilation methods were successfully tested and their results increase the accuracy of the prognoses of dispersion models.
Key words: Decision Support Systems / JRODOS / prognostic meteorological data / data assimilation / NERIS-TP
© EDP Sciences 2016
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