Journal
NATURAL HAZARDS
Volume 70, Issue 1, Pages 767-787Publisher
SPRINGER
DOI: 10.1007/s11069-013-0851-3
Keywords
Extreme weather impacts; Preparedness level; Traffic and supply disruptions; Crisis management; Reputational and business damage; Extreme weather indicators
Funding
- EU
- Research Council of Norway
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Four cases are studied in this assessment of how the harsh 2010 winter weather affected rail freight operations in Norway, Sweden, Switzerland and Poland and also of the reactive behaviour rail managers mobilised to reduce the adverse outcomes. The results are utilised in a fifth case assessing the proportion of freight train delays in Finland during 2008-2010 by modelling the odds for freight train delays as a function of changes in metstates on the Finnish network and weather-induced infrastructure damage. The results show that rail operators were totally unprepared to deal with the powerful and cascading effects of three harsh weather elements-long spells of low temperatures, heavy snowfalls and strong winds-which affected them concurrently and shut down large swathes of European rail infrastructure and train operations. Rail traffic disruptions spread to downstream and upstream segments of logistics channels, causing shippers and logistics operators to move freight away from rail to road transfer. As a result, railways lost market share for high-value container cargo, revenues and long-term business prospects for international freight movement. Analyses of measures employed to mitigate the immediate damage show that managers improvised their ways of handling crises rather than drew on a priori contingency, i.e. fight-back programmes and crisis management skills. Modelling the co-variation between extreme weather and freight train delays in Finland during 2008-2010 revealed that 60 % of late arrivals were related to winter weather. Furthermore, the combined effect of temperatures below -7 degrees C and 10-20 cm changes in snow depth coverage from 1 month to the next explained 62 % of the variation in log odds for freight train delays. Also, it has been shown that changes in the number of days with 10-20 cm snow depth coverage explained 66 % of the variation in late train arrivals, contributing to 626 min or 10.5 additional hours' delay. Changes in the number of days with snowfalls over 5 mm accounted for 77 % variation in late train arrivals, implying that each additional day with this snowfall could contribute to 19.5 h' delay. Finally, the combination of increased mean number of days with 5 mm snowfall and temperature below -20 degrees C explained 79 % of the variation in late arrivals, contributing to 193 min or 3.25 h' delay. All results were significant (p = 0.00).
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