Use of advanced data/computational science techniques to improve and intergrate site-specific weather forecasts to support Shell's global operations
Lead Research Organisation:
Imperial College London
Department Name: Earth Science and Engineering
Abstract
The overall aim of this research project will be to investigate how weather forecasting models can be improved and interegrated to support decision-making in a variety of Shell's global operations, including Global Commercials, Trading & Supply and New Energies (Renewable Power and e-mobility).
The underlying forecasting frameworks will be WRF (Weather Research and Forecasting Model) which is currently used by Shell to provide high-resolution, site-specific forecasts, as well as Imperial College's next-generation Gusto model, which used advanced discretisation methods on flexible meshes and it built using the highly scalable Firedrake code generation framework.
The underlying forecasting frameworks will be WRF (Weather Research and Forecasting Model) which is currently used by Shell to provide high-resolution, site-specific forecasts, as well as Imperial College's next-generation Gusto model, which used advanced discretisation methods on flexible meshes and it built using the highly scalable Firedrake code generation framework.
People |
ORCID iD |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/V519534/1 | 30/09/2020 | 29/09/2026 | |||
| 2625241 | Studentship | EP/V519534/1 | 30/09/2020 | 31/03/2024 |