Developing and improving products derived from radar measurements to support weather services.
Weather radar provide the primary means of measuring the spatial extent and distribution of rainfall over a wide geographical area by observing the atmosphere with high spatial and temporal resolution. The most intense rainfall events are often highly localised and can therefore be missed or under-sampled by rain gauge networks, and whilst these events can be forecast with skill, it is not currently possible to forecast the exact location of their initiation. Radar therefore provides a crucial input to short-range weather forecasts (nowcasts) of precipitation rate, and improves the skill of weather forecasts when it is assimilated into numerical weather prediction models.
The radar products team based in Exeter is responsible for improving the quality and accuracy of surface precipitation rate estimates made from radar. These are available to hydrometeorologists in real-time and contribute to the processes for forecasting and warning of rainfall-driven flooding, amongst many other applications.
- Improving the accuracy of radar precipitation estimates using dual polarisation radar data.
- Development of Odyssey, the OPERA data centre for processing radar data from across Europe, in collaboration with Météo France
- Merging radar precipitation rates and accumulations with other observations such as rain gauges to improve accuracy.
- Development of new products using dual polarisation data, such as a 3D hydrometeor (eg rain, hail, snow, ice crystals) classification and 2D surface precipitation type.
- Developing and using 3D radar products.
- Incorporating scientific developments into the operational data processing system, Radarnet IV, in a robust and timely manner.
- Hydrometeor classification.
- 3D Reflectivity composite development.
- Merging radar rainfall estimates with rain gauges.
- Radar processing software re-engineering.
- Updating our correction for the vertical profile of reflectivity.
Last updated: Aug 5, 2016 9:13 AM