On the International Day for Disaster Risk Reduction, we will be hosting speakers that showcase how statisticians are helping to prevent disasters. Our honoured guests will tell us about recent advances in forecasting severe weather and about using extreme value analysis to help tackle emergency gas escapes.
11:45 - 11:55 Login
11:55 - 12:00 Introductions by Chair
12:00 - 13:30 Presentations
Beth Woodhams, School of Earth and Environment, University of Leeds
Despite the devastating impacts of intense rainfall events across the continent, the prediction of severe weather events over Tropical Africa remains a great challenge for weather models and forecasters alike. In this talk, I will discuss the latest generation of numerical weather prediction (NWP) models being used to predict high impact weather over Africa. Although advances are being made, the skill of NWP remains low over the region. The application of nowcasting – using near-real-time observations and forward propagation techniques to predict high-impact events in the next few hours – presents many opportunities for improving disaster risk management and increasing responses to weather hazards across a variety of sectors. As nowcasting products are being made available to African meteorological services through the GCRF African SWIFT project, I will discuss the applications and opportunities provided by these products, and a vision for the future of nowcasting in Africa
Laura Cattle, Northern Gas Networks
Northern Gas Networks is a highly regulated business, which means targets are set for the benefits of customers as well as to ensure high health and safety precautions. One of these measures is to ensure that Northern Gas Networks responds to gas escapes within 1 hour of being informed, on 97% of occasions. Gas escapes vary significantly year to year, as well as having seasonality and links to temperature, meaning time series analysis is used to support this prediction.
Additionally, extreme events such as heavy snow or large bursts can cause widespread events, which require a significant number of resources at the same time. The purpose of this analysis is to understand the number of gas escapes at any given time or area of the network to allow for planning the number of resources required to attend these.
This analysis tries to combine a number of statistical techniques, from time series and regression modelling through to extreme value analysis and uncertainty modelling, to ensure gas escapes do not lead to disastrous consequences.
My background consists of MMath in Mathematics and Statistics at the University of Sheffield followed by joining Northern Gas Networks and a rapid learning curve of applying statistical techniques to real life business problems