Details of Award
NERC Reference : NE/N008359/1
Evaluation of 3D dual-polarised radar-based hydrometeor classification algorithms over the UK
Training Grant Award
- Lead Supervisor:
- Dr RR Neely, University of Leeds, School of Earth and Environment
- Grant held at:
- University of Leeds, School of Earth and Environment
- Science Area:
- Atmospheric
- Freshwater
- Overall Classification:
- Atmospheric
- ENRIs:
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Science Topics:
- Weather prediction
- Boundary Layer Meteorology
- Weather forecasting
- Tropospheric Processes
- Weather forecasting
- Water In The Atmosphere
- Regional & Extreme Weather
- Warning systems
- Weather forecasting
- Technol. for Environ. Appl.
- Radar observation
- Abstract:
- Accurate forecasting of hazardous and high impact weather such as snow and ice is absolutely essential for the National Severe Weather Warning Service (NSWWS) in terms of safety of life. In addition, marginal rain/snow events, which can have a particularly high impact on the transport sector, for example: airport and rail operators, as well as those responsible for gritting our roads. One of the greatest challenges to operational meteorologists is when the freezing level of the atmosphere is close to the surface because this condition leads to uncertainties in precipitation type. An accurate radar hydrometeor type (i.e. rain, snow, hail, etc.) classification product is absolutely essential in helping to identify subtle changes and trends in these marginal rain/snow situations, particularly if this source of information suggests a divergence from model expectations. Extrapolating such trends in radar observations provides meteorologists with important information that leads to producing increased warning times for emergency response teams and other customer groups to take mitigating action. Current hydrometeor type products rely on weather forecast data as conventional (single-polarisation) radar measurements contain limited information on the phase of precipitation. Due to this reliance on secondary information, the skill of the existing Met Office radar hydrometeor type product is greatly impacted by the forecast errors. The Met Office and Environment Agency are upgrading the weather radars in the UK network to dual-polarisation. Unlike single polarisation radar, dual-polarisation allows the size, shape, and orientation of targets within the radar sampling volume to be measured due to the differences these physical parameters have on the scattering of the two perpendicularly transmitted polarization planes. The information that can be inferred from the dual-polarimetric radar variables includes size, shape, composition, and orientation of hydrometeors in storms. A classification of hydrometeor type can be derived from these measurements at a resolution < 1 km, with less reliance on, and fewer errors from weather models. Many recent studies have also shown that this type of information is essential for evaluating model cloud schemes for wintertime conditions and cold cloud processes where differentiating between supercooled liquid drops and types of frozen hydrometeors is key. Though much work has been done in this field, large uncertainties remain in the use of polarimetric radar to identify particles and a focused analysis of the novel observations over the UK is needed. Thus, the goal of this PhD is to improve the ability of weather radars to accurately make quantitative estimates of precipitation by classifying the observed hydrometeor types using the novel data provided by dual-polarisation observations. This aligns directly with a major Public Weather Service project to look at ways of enhancing our nowcasting (i.e. short-term weather forecasting) capability and the newly created Innovation and Application team in the Met Office operations centre will be involved in optimising the use of new sources of observational data to support this project.
- NERC Reference:
- NE/N008359/1
- Grant Stage:
- Completed
- Scheme:
- DTG - directed
- Grant Status:
- Closed
- Programme:
- Industrial CASE
This training grant award has a total value of £86,776
FDAB - Financial Details (Award breakdown by headings)
| Total - Fees | Total - Student Stipend | Total - RTSG |
|---|---|---|
| £16,957 | £58,822 | £11,000 |
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