Data science techniques within environmental and earth sciences drive studies from the molecular to global scale. Better understanding the history, future and present challenges facing our planet - including our role in that evolution - requires techniques that probe fundamental hypotheses. These can provide new insights into key drivers of change. Environmental science is a highly multi-disciplinary field. As such, technologies we require are both responsive to developments from specific fields, such as mathematics or computer science, and developed in response to new experimental and/or modelling facilities. More generally these techniques bridge work from both experimental facilities and modelling facilities.
The Centre for Atmospheric Sciences studies processes important to climate change and air quality in the troposphere and lower stratosphere – the lowest 20 km of the Earth’s atmosphere. Data on the physical and chemical state of the atmosphere is collected from a wide range of research platforms. These cover instruments that probe the properties of individual molecules, through to models of meteorology and chemical weather across the world. Their research ethos relies on using data across a range of scales to improve their understanding of how the atmosphere evolves and impacts our lives. The Centre is part of the successful School of Earth, Atmospheric and Environmental Sciences. It frequently collaborates with institutions such as DEFRA, DSTL, Manchester City Council and the NCAS.
Models Developed by CAS:
The chemistry if the atmosphere is complex. UManSysProp connects chemo-informatics and data science applications. The software enables people to integrate with the latest chemical models of the atmosphere that can predict the occurrence of many millions of molecules. Extracting relevant information from these mechanisms requires the use of automated procedures, for which the UManSysProp suite was built.
Predicting how the climate or air-quality might respond in the future requires the use of models that capture the current state of the art knowledge on chemical and physical processes that occur in the atmosphere. The ManUniCast portal provides a general overview of the model system used, which in this instance provides a basic teaching tool to understand the type of data that is used to underpin our understanding
David's research interests focus on building computational models of atmospheric aerosol particles for use in interpretation of measured properties and as sub models for incorporation into climate change models. This broad classification masks a hierarchy of models and techniques with greatly varying complexity and range of applicability. In addition, the research area is highly multi-disciplinary, covering: Physics, Chemistry, Numerical methods and Computational Science.
The research carried out as part of his role can spill out into areas that might be considered ‘tangential’, such as Informatics. Atmospheric aerosol particles could potentially be comprised of millions of different chemical species. Manually predicting all of the relevant properties of such species, or their behaviour in mixtures, would be impossible. For this, he built software (UManSysProp) based on open-source informatics developments that allow the predictions to be automated.
Gordon is a Professor of Atmospheric Multiphase Processes, his main research interests focus on the processes playing a role in the formation and transformation of atmospheric aerosol, with particular emphasis on their interactions with trace gases and clouds. The processes modifying aerosol composition and size are responsible for the changes in properties that impact on their climatic impacts. Quantification of these processes is of critical importance to reduction in the uncertainty in the aerosol impacts on climate.
Researchers in his group participate in modelling, field and chamber experiment activities. Using a range of detailed process models to investigate aerosol properties and transformations in photochemical chamber and field experiments.