The use of probabilistic weather generator information for climate change adaptation in the UK water sector

Christopher Harris, Andrew Quinn, Jonathan Bridgeman

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


Adapting to climate change in the water sector requires abandoning two crucial assumptions. First, that the climate represented in the instrumental record is representative of the future. Instead, future water resource planning cannot be based on old measurements (or sequences derived from attaching change factors to instrumental data) and it should be recognized that stationarity is no longer viable, and, second, that climate modelling can be expected to give precise and certain predictions of the future. Instead, probabilistic projections of the future that take into account the full range of uncertainty should form the basis of robust climate change adaptation plans.

As a response to the first assumption, it is suggested that stochastic weather generators represent a particularly useful approach to understanding the impacts of future climate change on water resources at a catchment scale, particularly given the recent release of ‘science-hidden’ tools such as the UKCP09 weather generator. With regards to the second assumption, it is suggested that modelling activity should identify the range of plausible futures to develop probabilities of risk, using those robust decision-making techniques which can gauge the performance of potential adaptation strategies.

The best practice for delivering a replicable and practical hydroclimatological impact assessment for UK water resources at a catchment scale is identified, and an hypothetical example is outlined. It is suggested that although augmenting the resilience of water resources to climate change on a catchment scale is dependent on using the correct modelling tools, the robustness of the method with which that information is used to make adaptation decisions is equally as important. Copyright © 2012 Royal Meteorological Society
Original languageEnglish
Pages (from-to)129-140
JournalMeteorological Applications
Issue number2
Early online date19 Jun 2012
Publication statusPublished - Apr 2014


  • statistical downscaling;risk;resilience;water resources;probabilistic decision making;hydroclimatology;uncertainty;water supply and demand


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