Climate risk modelling provides valuable quantitative data on potential risks at different spatiotemporal scales, but it is essential that these models are evaluated appropriately. In some cases, it may be useful to merge quantitative datasets with qualitative data and local knowledge, to better inform and evaluate climate risk assessments. This interdisciplinary study maps climatic risks relating to health and agriculture that are facing rural Northern Ireland. A large range of quantitative national climate risk modelling results from the OpenCLIM project are scrutinised using local qualitative insights identified during workshops and interviews with farmers and rural care providers. In some cases, the qualitative local knowledge supported the quantitative modelling results, such as (1) highlighting that heat risk can be an issue for health in rural areas as well as urban centres, and (2) precipitation is changing, with increased variability posing challenges to agriculture. In other cases, the local knowledge challenged the national quantitative results. For example, models suggested that (1) potential heat stress impacts will be low, and (2) grass growing conditions will be more favourable, with higher yields as a result of future climatic conditions. In both cases, local knowledge challenged these conclusions, with discomfort and workplace heat stress reported by care staff and recent experience of variable weather having significant impacts on grass growth on farms across the country. Hence, merging even a small amount of qualitative local knowledge with quantitative national modelling projects results in a more holistic understanding of the local climate risk.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)