James works on the development of fast radiative transfer models.
Areas of expertise:
Radiative transfer and the fast model RTTOV
Cloud detection algorithms
James works on the development of the RTTOV fast radiative transfer model which is developed in collaboration with Météo-France and European Centre for Medium-Range Weather Forecasts (ECMWF) as part of the NWP SAF, which is funded by EUMETSAT. For the Met Office and many other users worldwide, the fast model RTTOV plays an important role in assimilating satellite observations for NWP.
James is involved in developing the scientific capabilities of the model, co-ordinating the release of new versions of RTTOV and answering user queries about the software. Among other things James has recently worked on introducing the capability to simulate visible and near-infrared wavelengths for clear-air atmospheric profiles. He is now working to implement simulations for cloud and aerosol profiles at these wavelengths. This capability could allow, for example, cloud properties to be determined more accurately by combining information from visible/near-infrared and thermal infrared channels. Ultimately this could lead to better representation of cloud within NWP models by increasing the scope for assimilating cloud-affected satellite observations.
In the past James has been involved in developing and improving algorithms to identify cloud-contaminated pixels in imagery from the MSG satellites. These geostationary satellites operated by EUMETSAT have been providing high-resolution images over Europe, Africa and the Atlantic every 15 minutes at solar and infrared wavelengths since 2004. Various quantitative imagery products derived from the data provide guidance for forecasters and also form inputs to the Met Office's automated nowcasting systems. In addition to imagery products, the satellite observations in areas of clear-sky are assimilated into the Met Office Unified Model, and work is underway to enable assimilation of radiances in cloudy regions. A fundamental pre-processing step for these activities is the accurate identification of pixels which contain cloud in the Meteosat imagery. James remains responsible for maintaining the cloud detection algorithms.
James joined the Satellite Applications team in 2007 after obtaining an MSc in Remote Sensing and Image Processing from Edinburgh University. As an undergraduate James studied Maths at Cambridge University.
Last updated: Jun 16, 2016 12:08 PM