Impact of Spatio-Climatic Variability on Environment-Hosted Land-based Renewables: Microclimates
Lead Research Organisation:
NERC CEH (Up to 30.11.2019)
Department Name: Shore
Abstract
Many current or projected future land-based renewable energy schemes are highly dependent on very localised climatic conditions, especially in regions of complex terrain. For example, mean wind speed, which is the determining factor in assessing the viability of wind farms, varies considerably over distances no greater than the size of a typical farm. Variations in the productivity of bio-energy crops also occur on similar spatial scales. This localised climatic variation will lead to significant differences in response of the landscape in hosting land-based renewables (LBR) and without better understanding could compromise our ability to deploy LBR to maximise environmental and energy gains. Currently climate prediction models operate at much coarser scales than are required for renewable energy applications. 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, taken from the field of numerical weather prediction, to develop a micro-climate model, which will be able to make climate predictions locally down to scales of less than one kilometre. We will conduct validation experiments for the new model at wind farm and bio-energy crop sites. The model will be applied to the problems of (i) predicting the effect of a wind farm on soil carbon sequestration on an upland site, thus addressing the question of carbon payback time for wind farm schemes and (ii) for predicting local yield variations of bio-energy crops. Extremely high resolution numerical modelling of the effect of wind turbines on each other and on the air-land exchanges will be undertaken using a computational fluid dynamics model (CFD). The project will provide a new tool for climate impact prediction at the local scale and will provide new insight into the detailed physical, bio-physical and geochemical processes affecting the resilience and adaptation of sensitive (often upland) environments when hosting LBR.
Organisations
Publications

Armstrong A
(2014)
Wind farm and solar park effects on plant-soil carbon cycling: uncertain impacts of changes in ground-level microclimate.
in Global change biology

Armstrong A
(2016)
Solar park microclimate and vegetation management effects on grassland carbon cycling
in Environmental Research Letters

Armstrong A
(2015)
Biotic and Abiotic Factors Interact to Regulate Northern Peatland Carbon Cycling
in Ecosystems

Armstrong A
(2016)
Ground-level climate at a peatland wind farm in Scotland is affected by wind turbine operation
in Environmental Research Letters

Gray A
(2013)
Methane indicator values for peatlands: a comparison of species and functional groups.
in Global change biology

Ward S
(2013)
Warming effects on greenhouse gas fluxes in peatlands are modulated by vegetation composition
in Ecology Letters

Whitaker J
(2020)
Plant functional type indirectly affects peatland carbon fluxes and their sensitivity to environmental change
in European Journal of Soil Science
Description | Key findings include the relatively small but significant effect of operational wind turbines on ground level temperature. This effect was not, however, as large as that seen over the year with the different seasons. |
Exploitation Route | Findings will help stakeholders improve siting, design and management of existing and proposed wind farms across UK terrestrial landscapes. |
Sectors | Agriculture Food and Drink Energy Environment |
Description | This research is ongoing (i.e. Knowledge Exchange component). Findings will be used by academics, researchers and educators to examine and understand the effects of turbines on ground level microclimates. |
First Year Of Impact | 2013 |
Sector | Agriculture, Food and Drink,Education,Energy,Environment |