Numerics Warehouse - Services

By: Numerics Warehouse  05/12/2011
Keywords: renewable energy, modelling, Forecasts

Utilising state of the art modelling techniques, we can offer forecasts and hindcasts for areas of interest worldwide. We have a range of models already prepared for various timeframes and our clients can commission further models for specific regions, conditions and time periods depending on their requirements.

Numerical model products are customised for our ocean energy clients and state authorities to assist at every stage in the development cycle: - conceptual planning, site selection, detailed engineering design and operational aspects - forecasting.

  • Ten year climatologies (1997 to 2007) of wind and wave energy for key areas, including monthly statistics and extremes.
  • A high level visual map based conceptual planning tool to predict the energy output from a mix of a wide range of wave, wind and tidal renewable energy devices.
  • For any location within our high resolution models - automatically generated statistical reports over a ten year period of conditions of weather and waves.
  • Detailed directional wave spectral data, for every 3 hours over ten years at many hundreds of near coastal locations in areas with a good wave energy resource.
  • Boundary, initial and forcing data for very high resolution wave and ocean models. These models can be run by Numerics Warehouse on the clients behalf, or the data can be supplied for the clients own modelling work.
  • Forecasts of waves, weather, currents, tides.

Our broadest scale models cover entire ocean basins from which we extract boundary data for successively higher resolution models - until in coastal locations; we resolve the features required by ocean energy developers. The succession of models used and the climatalogical periods over which the models are run require that we use supercomputers - a proficiency in the use of which we have - so our clients can concentrate on their area of expertise without maintaining a large modelling group.

Keywords: Forecasts, modelling, renewable energy