3A.1
The Met Office NWP system - status and longer term plans

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Monday, 3 February 2014: 4:00 PM
Room C201 (The Georgia World Congress Center )
Gilbert Brunet, Met Office, Exeter, United Kingdom

Seamless modelling and prediction across a range of timescales has been at the heart of the Met Office strategy for weather and climate prediction since 1990. The Met Office Unified Model forms the core of this capability. The seamless approach has delivered a number of benefits, including increased efficiency in model development and science. This presentation will provide an update of the Met Office NWP system, highlighting recent progress and outlining future plans.

The London 2012 Olympic and Paralympic Games provided an excellent high profile opportunity to develop and showcase new applications in our weather forecasting capability. This led to a couple of significant milestones in the delivery of new capability within the seamless modelling context. The Nowcasting Demonstration project developed new capability to run an hourly-cycling NWP system, combining a 1.5km resoulution version of the Unified Model over southern England and 4D-Var data assimilation. Ultimately we hope to replace extrapolation-based nowcasting techniques with such an NWP-based system.

The Met Office also showcased a high resolution (2.2km) ensemble configuration over the UK for the first time. This now means we have probabilistic forecasting capability across all timescales within our operational systems, and a truly seamless approach. Analysis, validation and communication of high resolution ensemble forecasts presents several challenges to overcome, which will be discussed.

Our forecasting systems and science are continually developed and evolve to take advantage of improved understanding and increasing computing power, and to meet our users' requirements. We will discuss our priorities for future development. This includes acceleration of our efforts in regional coupled prediction to provide a more integrated approach to forecasting and a more complete prediction of out complex and interdependent environment.