Ian leads the development and application of location-specific forecasting for industry, specialising in Energy, Retail and Road/Rail.
Ian is a Senior Applied Scientist in the Post-Processing Applications team and develops and delivers products and services to help our industry customers manage the impact of weather and realise weather opportunities in their operations.
Ian routinely works directly with customers in the Energy and Retail sectors to deliver historical data and forecast solutions to meet their specific needs. He also works to maximise the usefulness of Numerical Weather Prediction (NWP) to application in the real world, developing techniques to optimise forecasts using multi-model blending and fully exploiting the range of plausible scenarios offered by a range of NWP solutions.
Ian is currently supporting the migration of our capabilities into cloud-based technologies.
Ian has been working in applied science roles since joining the Met Office in August 1998. This has always involved developing weather forecast capabilities for industry customers, but he has also spent a significant portion of his career developing location-forecasts for our public and media customers.
From 2016 to 2018, Ian was the science lead in a project with National Grid to explore enhancements to short range solar radiation forecasting.
From 2015 he led the scientific development of a platform to deliver both historical and forecast data for locations and regions. This provided customers the ability to set the latest forecast in historical context and identify analogues in their own past data, be that sales, demand, load, footfall, downtime, impact, call volumes, or any other weather-sensitive business metric.
From 2010 Ian was responsible for the creation and development of the Met Office’s first production multi-model optimal blend capability.
Ian graduated with a BSc in Meteorology from the University of Reading.