NERC Advanced Training Course – Earth Observations for Weather and Climate Studies
Suitable for postgraduate students and postdocs
Dates of course: 5-9 September 2016
Location: University of Reading, Reading, UK
Web link: Details can be found here<http://www.store.reading.
Earth observation (EO) plays a crucial role in providing weather/climate records, advancing our understanding of the weather and climate systems, and improving model representations. In addition to their unique role in weather/climate science and services, EO data are also a rapidly growing economic area. The course is aimed at PhD students or early career researchers who are working in weather/climate science, and wish to use EO data for understanding atmospheric processes and improving model simulations in a quantitative manner.
This 5-day training course combines lectures, practical sessions, student presentations and group projects. A team of experienced lecturers and researchers at the Department of Meteorology of the University of Reading will deliver morning lectures, introducing students to theoretical principles of satellite-based remote sensing measurements. They will also demonstrate and supervise afternoon practical sessions for students to conduct their group projects. Group projects will be based on well-defined research topics with 2–3 open questions; students will learn to analyse weather/climate model output, and run state-of-the-art radiative transfer models, visualisation tools and advanced satellite simulators in the Reading computing lab.
The objectives of the training course are 1) to review fundamentals of weather, climate and radiative transfer models applied to remote sensing; and 2) to develop knowledge and practical skills for synthesising EO data for emerging weather and climate issues. At the end of the training course, the students will be able to:
• Develop and evaluate retrieval methods for sensing lands/oceans, aerosols, clouds, precipitation, temperature and humidity;
• Evaluate weather/climate model output using radiative transfer models and satellite simulators; and
• Synthesise large EO data sets by using and modifying visualisation tools.
This course focuses on quantitative aspects of extracting information from EO data, and the underpinning physics of this, rather than image interpretation.
How to register:
Please use this web link<http://www.store.reading.