Impacts of spatio-climatic variability on environment-hosted land-based renewables: Micro-climates

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Currently climate prediction models operate at much coarser scales than are required for renewable energy applications. Variations in the productivity of bio-energy crops, however, occur on the spatial scales of a catchment. The required downscaling of climate data is achieved using a variety of empirical techniques, the reliability of which decreases as the complexity of the terrain increases. In this project, we will use newly emerging techniques of very high resolution nested numerical modelling to develop a micro-climate model, which will be able to make predictions locally down to scales of less than one kilometre. Our (RES) objectives are [OBJ5.2] To quantify the effect of down-scaled meteorological data in complex terrain on crop development, growth, yield and harvestability (e.g. damage)?; and [OBJ6] To evaluate and cross-validate two different modelling approaches accommodating terrain effects on micro-meteorological bio-renewables from biological resources. In collaboration with the consortium partners we will conduct validation experiments for the new model-derived input data at [wind farm and] bio-energy crop sites and predict local yield variations of yield of bioenergy crops using an implicit and explicit approach to account for climatic variability.

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