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Lookup NU author(s): Dr Ben SmithORCiD, Dr Stephen BirkinshawORCiD, Dr Craig Robson
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025 The Author(s)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.
Author(s): Kennedy-Asser AT, Andrews OD, Montgomery J, Jenkins KL, Smith BAH, Lewis E, Birkinshaw SJ, He H, Pywell RF, Brown MJ, Redhead JW, Warren R, Robson C, Smith AJP, Nicholls RJ, Mullan D, McGuire R
Publication type: Article
Publication status: Published
Journal: Climate Risk Management
Year: 2025
Volume: 48
Online publication date: 25/03/2025
Acceptance date: 22/03/2025
Date deposited: 14/04/2025
ISSN (electronic): 2212-0963
Publisher: Elsevier B.V.
URL: https://doi.org/10.1016/j.crm.2025.100702
DOI: 10.1016/j.crm.2025.100702
Data Access Statement: All quantitative OpenCLIM modelling data is available through the DAFNI website (https://www.dafni.ac.uk). Further analysis code including the dairy milk yield calculation is available via GitHub (https://github.com/ATK-A/NI_CRM).
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