An external view of the Met Office building at night.

James Hocking

James works on the development of fast radiative transfer models.

Areas of expertise

  • Radiative transfer

  • The fast radiative transfer model RTTOV

  • Cloud detection algorithms

Publications by James Hocking

Current activities

James works on the development of the RTTOV fast radiative transfer model which is developed in collaboration with Météo-France, DWD 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 a critical role in assimilating satellite observations for NWP, and in numerous other applications including generating simulated satellite imagery, and studies related historical and future sensors.

James coordinates development of the scientific and technical capabilities of the model, carries out testing of the software, maintains much of the documentation, puts together release packages of new versions of RTTOV, and answers user queries about the software. James is involved in development across all aspects of the software, including the implementation of new radiative transfer solvers, improvements to existing solvers, implementation of surface emissivity and reflectance models, creation of scattering optical properties for aerosols and hydrometeors, developments to the gas absorption optical depth parameterisation used within RTTOV, developing the C++ and Python interfaces to RTTOV (a Fortran code), and maintaining and improving the test harness for the software.

James is also the sole developer of the NWP SAF Radiance Simulator (RadSim). This tool provides a user-friendly way to run RTTOV simulations without writing any code. Simulations are configured via a Fortran namelist or are specified on the command line via a Python script. RadSim can ingest NWP model data from various sources (e.g. ECMWF, Met Office UM, DWD ICON, JMA, HARMONIE, NWP SAF profile datasets), carry out spatial and temporal interpolation of the fields to observation locations, and run RTTOV on the resulting atmospheric profiles and associated surface data.

Career background

James joined the Satellite Applications (now Satellite and Surface Assimilation) team in 2007 after obtaining an MSc in Remote Sensing and Image Processing from Edinburgh University. Initially James worked on developing and improving algorithms to identify cloud-contaminated pixels in imagery from the MSG satellites. He has been working on the RTTOV model since 2010. As an undergraduate, James studied Maths at Cambridge University.