Details of Award
NERC Reference : NE/P020534/1
R and openair training for atmospheric science
Training Grant Award
- Lead Supervisor:
- Professor DC Carslaw, University of York, Chemistry
- Grant held at:
- University of York, Chemistry
- Science Area:
- Atmospheric
- Overall Classification:
- Atmospheric
- ENRIs:
- Environmental Risks and Hazards
- Global Change
- Pollution and Waste
- Science Topics:
- Atmospheric Kinetics
- Troposphere
- Atmospheric composition
- Air pollution
- Boundary Layer Meteorology
- Atmospheric chemistry
- Land - Atmosphere Interactions
- Environment & Health
- Air pollution
- Air pollution
- Pollution
- Abstract:
- This proposal aims to provide training in the rapidly growing area of environmental data analysis. There is a strong need for enhanced data analysis skills for PhD students in the atmospheric sciences in part because the number of data sets is increasing both in amount of data available and complexity. To fully exploit such data and maximise the insights that can be derived from data requires high level data analysis capabilities. This training course will focus on training based on data analysis software called R (a programming language specifically designed for data analysis), and specifically, an R 'package' called openair. The training will be available for up to 20 students and will be hosted at the University of York for 5 days in 2017. The course will be led by x who is the lead developer of the openair package, assisted by y - a mature PhD student at York Chemistry Department with extensive experience in R programming for atmospheric science applications. openair itself is widely used in the atmospheric science community throughout the world. The package is in the top 7% of over 9,500 R packages downloaded worldwide. The paper associated with openair is the highest cited paper in 2012 (Environmental Modelling & Software, impact factor = 4.2) with over 150 citations (WoS). The software is used in a wide variety of settings from urban air pollution research to analysing global trace gas concentrations at remote sites worldwide. The software has been downloaded >55,000 times in the last 4 years.x and y have previously run a successful 3-day R/openair course together at the University of Aarhus in Denmark, following an invitation to do so in 2015. We will use an innovative 'dynamic reporting' technique to deliver course materials where all materials will be provided in a reproducible way. This approach allows the mixing of conventional report text with R scripts where the document is 'run' to produce all the outputs (e.g. figures, tables, statistics). This approach guarantees that all course R scripts and analysis run as exactly intended and can be easily re-created at a later time by all students. Additionally, an R package will be provided to students that will form a lasting, reliable resource of all the data sets, analyses and course manual to the students. Students will also be introduced to a version control system called git and code repository GitHub on the final day to show how robust systems of analysis can be used to improve data analysis reliability and allow sharing with researchers across the world. Previous experience suggests that spending sufficient one to one time with students using their data and working on their problems considerably increases the value of such courses. Day 4 of the training course will focus on providing such support and all solutions will be provided in the course manual that can be accessed by all students using the 'dynamic reporting' approach mentioned above. The course is of sufficient length and depth that it will provide a significant contribution towards PhD study. Feedback from a similar course about 2 years ago was very good and it was clear that students felt they benefitted enormously from attending. Many for example have now used R and openair analysis in their submitted publications and theses. The course has wide benefit beyond academia because R and openair itself is used around the world by both the private and public sectors. The applicant is very aware of need for these skills with his joint position with Ricardo Energy & Environment, which has one of Europe's largest air pollution consultancies. The joint position is also help to running the course, where experience in solving 'real world' data analysis problems will be brought to students' attention.
- NERC Reference:
- NE/P020534/1
- Grant Stage:
- Completed
- Scheme:
- Doctoral Training
- Grant Status:
- Closed
- Programme:
- Advanced Training
This training grant award has a total value of £12,635
FDAB - Financial Details (Award breakdown by headings)
| Total - Other Costs |
|---|
| £12,635 |
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