Dr Paul Abernethy

Paul works to develop statistical techniques that can be used to help improve our forecast accuracy at specific locations.

Current activities

The resolution of the Unified Model places a limit on the accuracy of our forecasts, especially at locations that have characteristics that are not typical of the surrounding area. For example, the site could be located at the bottom of a deep valley, near the coast or on the side of a mountain. Forecasts for such sites will unavoidably contain systematic errors that are related to the site's location. Paul's work develops and applies statistical techniques that aim to minimise these systematic errors and thereby improve the accuracy of our forecasts at these locations. Paul has recently applied these statistical techniques to various resolution configurations of the Unified Model, including the North Atlantic and European model and the United Kingdom Post Processing system. Paul has also studied how these techniques can be applied to

a large number of sites that are used in the Met Office Road Surface Temperature model Met Office Road Surface Temperature which provides data for our OpenRoad product.

Career background

Paul has been a member of the Post Processing team since he joined the Met Office in 2008. Prior to joining the Met Office, Paul completed a PhD in Physics at the Department of Physics at the University of York. For his doctorate, Paul studied the magnetorefractive effect in mixed-valence magnetic oxides, a subject matter far removed from meteorology, which links changes in the reflectivity observed in a material's infra-red spectra to changes in its electrical conductivity when a magnetic field is applied. Prior to this, Paul received a MPhys in Physics and Physics with Astrophysics, also from the University of York.

Last updated: 8 April 2014

About Paul Abernethy

Dr Paul Abernethy

Paul uses statistical techniques to improve forecast accuracy.

Areas of expertise

  • Statistical techniques to improve the forecast accuracy.
  • Post Processing of Numerical Weather Prediction model output.
  • Site-specific forecasting techniques.
  • Customer-specific forecasts.