Developing and improving techniques for processing satellite imagery data.
This area of research focuses on improving the way we use satellite imagery data for forecasting, NWP (Numerical Weather Prediction), and environmental and climate applications. On one level, this involves the development of value-added image products which help the human forecaster to interpret current weather or environmental situations - for example, images of cloud-top height, fog coverage or ash clouds from a recent volcanic eruption. The image data can also be processed to form data-sets suitable for climate applications - for example, historical sea-surface temperature analyses.
However, an additional use of the imagery data is via assimilation into our NWP models, in order to provide better initial conditions for many of the model variables. One example of this is the assimilation of wind information into the model via Atmospheric Motion Vectors (AMVs), which are derived by tracking features in a sequence of images. Other examples include the assimilation of humidity; aerosol and surface information in cloud-free areas; and improving the models' representation of cloud and humidity when clouds are present in the satellite data.
- To develop and improve the generation of satellite imagery data and products in support of nowcasting and forecasting.
- To improve forecast accuracy through better assimilation of satellite imagery data into the Unified Model.
- To provide guidance on the utilisation of satellite data for climate applications.
- To develop and improve the processing of AMVs for assimilation into the Met Office Numerical Weather Prediction models.
- To improve the use of satellite imagery for the analysis of cloud in the Unified Model and in the Met Office nowcasting systems.
- To extend the assimilation of geostationary satellite radiances to improve cloud, humidity and dynamical information in the Met Office Numerical Weather Prediction models.
- To develop new satellite imagery products in support of nowcasting and environmental monitoring applications.
- Assimilation of satellite land surface products (e.g. snow cover, vegetation) into the Unified Model.
- Processing of satellite sea surface temperature data for inclusion in a climate quality analysis.