Flux inversion of atmospheric trace gases
Flux inversion is the process through which we locate and quantify the sources and sinks of a gas using measurements of that gas at different points (or along different paths) in space and time. All flux inversion procedures need to take into account meteorology that can be used to predict how gas particles move in the atmosphere when released from a source. At CEI we are working on flux inversion at three scales, which we classify as local, regional, and global.
Statistical learning for ocean engineering
Ocean engineering is a branch of engineering that is concerned with the design, construction, and maintenance of structures and systems in the ocean environment, including ships, offshore platforms, wind turbines, and underwater vehicles. Researchers from CEI have partnered with the University of Western Australia to develop data science methods that facilitate some of the processes, to help make them more environmentally friendly, safe, and viable. Below we discuss two sub-fields: one related to sediment analysis and the other related to wave prediction.
Multivariate stochastic modelling
Multivariate geostatistics is based on modelling all covariances between all possible combinations of two or more variables at any locations in a continuously indexed domain. Multivariate spatial covariance models need to be built with care, since any covariance matrix that is derived from such a model has to be nonnegative-definite. In our research we are trying to find new ways to easily construct valid complex multivariate covariance models. Two such ways that we present below are through conditioning, and through domain warping.