Abstract

The Gulf of Finland is an elongated estuary in the north-eastern Baltic Sea. It carries a heavy sea traffic that is a threat to this sensitive sea area. The annual amount of transported oil is presently over 100 Mtons and it is still expected to increase in the future. The Gulf of Finland is relatively small in size while its length is 400 km and the width varies between 48-135 km. In addition to the coastline shared between Finland, Russia and Estonia, the gulf has a large and fragmented archipelago where numerous small islands comprise about 6500 km of shores. Due to complex hydrography it has been seen necessary to apply a high resolution oil spill drift forecast system to the gulf. The OpHespo oil drift forecast system is an internet based tool for oil pollution response authorities around the Gulf of Finland. It is possible to calculate drift forecast up to two days ahead. The drift forecasts are based on four times per day updated wind and current forecasts. The wind forecasts originate from HIRLAM (HIgh Resolution Limited Area Model) run by the Finnish Meteorological Institute. The used HIRLAM model has a horizontal grid resolution of about 9 km that enables it to forecast some of the land-sea interactions having an effect to the wind speed and direction. The current forecasts are computed using a local area hydro-dynamic model. The local model is forced with the HIRLAM wind forecast, and hydro-dynamic boundary conditions at the entrance of the Gulf of Finland are obtained from the Hiromb operational Baltic Sea model. The OpHespo graphical user interface has been developed in close cooperation with the Finnish oil pollution response authorities that ensures a good functionality of the programme related to their tasks. Several workshops and training sessions have been arranged for oil pollution response authorities and meteorologists on duty during 2003-06. The challenge is that the end-users of OpHespo are aware of the added value that the programme gives to oil spill response exercises and planning of response measures. Training in advance contributes also to interpretation the forecast results in a reasonable way and raises up ideas of how to further develop the drift forecast system as specialist of different fields convene.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call