A Vehicle OverTurning Model: Forecasting Risk Of Disruption On The UK Road Network During The Winter 2013/2014 Storms

The winter of 2013/2014 was exceptional in terms of the number of storms that passed across the United Kingdom and Europe. The UK National Severe Weather Warning Service (NSWWS) identified 34 wind events and issued 47 warnings ranging from yellow (be aware) through amber (be prepared) to a rarely issued red (take action) warning on 12th February 2014. The storms caused numerous impacts across the UK including fatalities, widespread infrastructure damage and economic consequences. A new tool is currently under development which aims to forecast the impact of high winds on the UK road network. The Vehicle Overturning (VOT) Model uses the high resolution MOGREPS-UK ensemble to generate a probabilistic risk value for likely disruption to the road network based on wind gust speed and direction. This probabilistic hazard value is then combined with vulnerability and exposure values to give an overall risk value termed 'Risk of Disruption' which indicates the severity of road disruption expected should a vehicle overturn. The model has been developed as part of a Hazard Impact Model (HIM) under the auspices of the Natural Hazards Partnership, which is a collaboration between a number of UK agencies including the Cabinet Office. The aim is to produce early warnings for severe events that allows an overall picture of the risk to society, based on probability and impact, to be generated. This presentation will illustrate, using case studies from winter 2013/2014, how the VOT model can improve the understanding of risk on the road network during wind storms. This will better inform the NSWWS of the impacts predicted during a high impact weather event and allow meteorologists to make a more informed decision about the extent and severity of the warning to be issued. Further, the presentation will discuss how the HIM intends to combine hazard impacts in order to better inform decision makers and emergency responders during multiple natural hazard events.