Community Research and Development Information Service - CORDIS


During emergency situations, following both nuclear and chemical atmospheric emissions, source term parameters such as locality, intensity, duration and height must be identified immediately and simultaneously to estimate the long range transport (LRT) of the cloud. The advantage of using real-time monitoring data for updating the predictions of LRT models has been demonstrated previously using an approach based on the idea that a monitoring network can characterise cloud evolution completely, and on the fact that the major source of uncertainties in LRT models lies in the wind field and precipitation field forecasting errors. When the network observations are available, a function describing that field is fitted to it and is used as an area source for generating new predictions on the cloud evolution. LRT model results may also be fitted in this way, allowing improvement in the LRT model used by LORAN without adversely affecting its calculation time or portability. Improvements to the LORAN procedure are described, together with some of the factors on which the success of LORAN depends.

Additional information

Authors: DE CORT M, JRC Ispra (IT);GRAZIANI G, JRC Ispra (IT);GALMARINI S, Instituut voor Marien en Atmosferisch Onderzoek Universiteit Utrecht (NL);GRIPPA G, MAIND Srl, Milano (IT)
Bibliographic Reference: Paper presented: Computer Support for Environmental Impact Assessment - CSEIA 93, Como (IT), October 6-8, 1993
Availability: Available from (1) as Paper EN 37810 ORA
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