The post holder will be a member of the Climate Science Research Group, within the Centre for Sustainable Forestry & Climate Change (CSF&CC) – one of two thematic research centres within Forest Research. CSF&CC focuses strongly on applied interdisciplinary research, to provide evidence to underpin sustainable management of Britain’s trees, woods and forests.
The Climate Change Research Group (CCRG) develops scientific understanding and synthesises research into practical advice relating to the management and use of trees and forests in adaptation and mitigation of climate change and the impacts of climate on forest function. The research underpins efforts to reduce risk and improve resilience of the UK forestry sector.
The team comprises fifteen staff in science and technical roles. CCRG researchers focus on assessing resilience and understanding GHG balance of forest systems across two broad thematic work areas: 1) climate mitigation and 2) climate adaptation. The group publishes widely in a range of high impact forest science, environmental and policy related journals. The group is actively involved in UKRI funded science and training of new scientists via PhD’s.
The group is seeking to appoint, on a fixed term basis, a Climate Data Analyst to undertake and support the group's research on the resilience of commercial and native forestry species to future climate change. There will be a focus on applied research, data products and spatial data outputs with web delivery in support of modelling activities and to support to other science groups.
The role will focus on data analyst activities working with UKCP18 climate data to inform forest modelling and decision support. The successful applicant will therefore be proficient in R or similar statistical / modelling packages with experience of the management and analysis of environmental datasets (e.g., historic Met Office data and UKCP18 projections). They will be expected to implement data warehousing and data product delivery, including coding, geospatial tools and integration of tools and data with web portals in line with user requirements and specifications. This might include deriving datasets at different spatial and temporal scales, for example taking daily precipitation data and aligning it to the needs of models that require information as 30-year averages or the derivation of additional climate variables, and the provision of user facing tools to access forest growth models which use data to provide estimates of forest productivity.