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Reviewing the 2013-2014 UK winter storms

Waves breaking over the sea wall at Exmouth on 6 January 2014. Photo taken by Paul J Martin.

February 2015 - One year on from a period of remarkable storms and flooding in the UK during winter 2013-2014, three new peer-reviewed articles have recently been published which provide more in-depth assessments of the conditions and the performance of our operational forecast modelling systems.

A special issue of the Weather journal published by the Royal Meteorological Society brings together a collection of articles describing the storms of winter 2013/2014. Mike Kendon and Mark McCarthy from the Met Office National Climate Information Centre have reviewed the weather events of the winter and describe climatological features, particularly rainfall and storminess in the context of long-term historical records.

Rainfall anomalies for winter 2013/2014 using the 1981–2010 long-term average. (a) December 2013, (b) January 2014, (c) February 2014, (d) winter 2013/2014. From Kendon and McCarthy 2015.

A key feature of the winter, as this collection of articles illustrates, was the multiple range of impacts experienced as a result of the storms - fluvial flooding, groundwater flooding, coastal flooding, land-slips, wide-spread power cuts and damage to infrastructure. A new article in the same issue of Weather by Andrew Sibley, Dave Cox and Helen Titley (of the Met Office Hazard Centre, Flood Forecasting Centre and Weather Impacts teams respectively) looks at coastal flooding from the North Sea storm surge in early December and subsequent flooding to the west and south coasts of England and Wales.

The hydrological response for both river flows and groundwater, in the context of long-term records held by the National Hydrological Monitoring Programme, are discussed in an accompanying article by Katie Muchan and colleagues at the Centre for Ecology and Hydrology. Together, these articles provide a link from the weather events of the winter to consequences in terms of flooding for inland and coastal communities.

The Met Office was at the heart of the government response to the storms, providing advice on weather impacts through the National Severe Weather Warning Service and Civil Contingency Advisors. The Flood Forecasting Centre, a partnership between the Met Office and Environment Agency, provided regional-scale guidance on flood risk to national and local authorities, while the Environment Agency issued a significant number of flood warnings to the public and stakeholders. Information on other hazards, for instance landslips, was provided through the British Geological Survey and Natural Hazard Partnership. Atmosphere-ocean-wave-tidal-surge models, developed by the Met Office, National Oceanography Centre and other partners, were used to predict coastal flooding. Together, these advanced warnings helped authorities, business and individuals to be better prepared to take mitigating actions.

Ensemble tidal surge graphs for Lowestoft (left) and North Shields (right). Top is the forecast from 0600 UTC 1 December 2013, bottom 0000 UTC 5 December 2013. See paper by Sibley et. al. 2015 for more information.

A new review article written by Huw Lewis and 15 other Met Office co-authors from across Science and Operational teams reviews the observational and modelling toolkit available to the operational meteorologists during winter 2013-14, and assesses its performance. This article features in a special issue of Meteorological Applications on high resolution precipitation, also published by the Royal Meteorological Society. Latest results demonstrated that the suite of global and high resolution UK numerical weather prediction models provided excellent guidance during the period, supported by high-resolution observations networks, such as weather radar. The paper discusses a number of future research directions and challenges to improve our capability which we are actively pursuing. This includes accelerating progress towards understanding the value that might be delivered through more UK Environmental Prediction.

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