Claire works with the aviation industry to provide weather data analysis to aid the safety and efficiency of aviation operations.
Areas of expertise
- Machine Learning
Claire is a senior scientist within the aviation team, undertaking data analysis and scientific research to better understand and improve how meteorological data is used within the aviation industry. In January 2019 she started a part-time PhD, investigating machine learning methods to improve convective nowcasting and its applications to the aviation industry.
As part of her work in the Aviation Applications team, Claire has worked on the World Area Forecast System (WAFS) upgrades, including the development of automated Significant Weather charts and the implementation and assessment of the improved Graphical Turbulence Guidance (GTG) turbulence forecast system, working in collaboration with WAFS partners in the USA. She also delivers shorter-term consultancy projects to the aviation industry, using both model and observational datasets to provide bespoke analyses to customers.
Claire joined the Met Office in 2012 in the climate science group, before moving on to the aviation team in August 2013. Whilst in climate science she was involved in consultancy-based projects, researching and communicating climate impacts specific to customers across various sectors, ranging from the utilities industry to environmental organisations.
In 2021-2022 Claire managed the Met Office's Nowcasting R&D team (as maternity cover), coordinating scientific effort in developing and improving our national nowcasting capability. This team seeks to improve the use of observations for nowcasting and situational awareness, with a current focus on convection.
Prior to joining the Met Office, Claire obtained a BSc joint honours in Geography and Mathematics at the University of St Andrews (2011) before going on to complete an MSc in Atmosphere, Oceans and Climate at the University of Reading (2012).