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Harpham, Quillon
(2019).
DOI: https://doi.org/10.21954/ou.ro.0000f53f
Abstract
The aim of this research is to facilitate the interaction of data between different environmental numerical models and between numerical models and observed data sources, thereby giving rise to more accurate simulations involving a variety of environmental phenomena. The thesis includes ten publications. The first gives an overall context to the field of integrated environmental modelling, which seeks increased interoperability and extensibility between numerical models and data sources. This is followed by a series of four papers introducing and discussing associated enabling technologies: the development of a web portal for the display and comparison of model and in-situ marine data; the FluidEarth 2 implementation of the OpenMI 2.0 standard passing data between models in spatio-temporal structures aggregated from lower level component parts; an extension of the ISO19115 metadata standard to provide aspects related to model coupling; and the Model MAP – a set of necessary concepts for numerical models to be coupled together. These technologies are then applied in a series of papers describing the DRIHM e-Infrastructure for research into hydro-meteorology. These papers focus on the meteorological aspects; the user interface; the back-end computing infrastructures; and two key integrating technologies with an applied example. The final paper gives another example of the use of spatio-temporal feature type structures as part of a new numerical modelling technology.
Overall, this series of papers points towards a structured representation of the data supporting environmental numerical models in terms of the underlying spatio-temporal characteristics. This suggests the adoption of a new vocabulary for describing these characteristics. Adoption of this vocabulary and new representation of environmental modelled data will speed the uptake of coupling strategies and create demand for established and new standards to support integrated environmental modelling.