Assimilation of surface-based observations
Improving the impact of surface-based observations in our global and regional Numerical Weather Prediction (NWP) systems.
This area of research focuses on improving and developing the assimilation of a wide range of surface-based observations into both the global and UK regional Met Office Numerical Weather Prediction (NWP) models. Improving the assimilation quality in this way enables us to obtain the best possible estimate of the current state of the atmosphere and thus improve the accuracy of our weather forecasts. The data we consider include surface observations over both land and oceans, upper-air observations such as those obtained by radiosondes and aircraft, and surface-based remotely sensed observations from instruments such as weather radar. Liaison with partners including other national meteorological services and the academic community is an important part of this work.
- Improve forecast accuracy through better assimilation of surface-based observations into the Unified Model.
- Contribute to defining future surface-based observation network to meet the needs of NWP.
- Improving the use of radiosonde data by accounting for the horizontal drift of sondes in the atmosphere.
- Improving the use of weather radar in NWP through direct assimilation of radar reflectivity in four-dimensional variational data assimilation (4DVar).
- Improving the impact of surface-based observations by accounting for correlated observation errors.
- Preparing for and developing next generation observation processing systems.