Climatic Change

, Volume 71, Issue 1–2, pp 9–41 | Cite as

A Regional, Multi-Sectoral And Integrated Assessment Of The Impacts Of Climate And Socio-Economic Change In The Uk

Part I. Methodology
  • I. P. HolmanEmail author
  • M. D. A. Rounsevell
  • S. Shackley
  • P. A. Harrison
  • R. J. Nicholls
  • P. M. Berry
  • E. Audsley


Policy makers and stakeholders are increasingly demanding impact assessments which produce policy-relevant guidance on the local impacts of global climate change. The ‘Regional Climate Change Impact and Response Studies in East Anglia and North West England’ (RegIS) study developed a methodology for stakeholder-led, regional climate change impact assessment that explicitly evaluated local and regional (sub-national) scale impacts and adaptation options, and cross-sectoral interactions between four major sectors driving landscape change (agriculture, biodiversity, coasts and floodplains and water resources). The ‘Drivers-Pressure-State-Impact-Response’ (DPSIR) approach provided a structure for linking the modelling and scenario techniques. A 5 × 5 km grid was chosen for numerical modelling input (climate and socio-economic scenarios) and output, as a compromise between the climate scenario resolution (10 × 10 km) and the detailed spatial resolution output desired by stakeholders. Fundamental methodological issues have been raised by RegIS which reflect the difficulty of multi-sectoral modelling studies at local scales. In particular, the role of scenarios, error propagation in linked models, model validity, transparency and transportability as well as the use of integrated assessment to evaluate adaptation options to climate change are examined. Integrated assessments will provide new insights which will compliment those derived by more detailed sectoral assessments.


Impact Assessment Climate Scenario Landscape Change Integrate Assessment Adaptation Option 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • I. P. Holman
    • 1
    Email author
  • M. D. A. Rounsevell
    • 2
  • S. Shackley
    • 3
  • P. A. Harrison
    • 4
  • R. J. Nicholls
    • 5
  • P. M. Berry
    • 4
  • E. Audsley
    • 6
  1. 1.Institute of Water and EnvironmentCranfield UniversityU.K.
  2. 2.Université catholique de LouvainBelgium
  3. 3.Tyndall Centre for Climate Change ResearchUniversity of ManchesterU.K.
  4. 4.Environmental Change InstituteUniversity of OxfordU.K.
  5. 5.School of Civil Engineering and the EnvironmentUniversity of SouthamptonU.K.
  6. 6.Silsoe Research InstituteU.K.

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