Defining climate modelling user needs What is actually required to support impact analysis and adaptation policy development? Rob Swart (Alterra, Netherlands)

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Presentation transcript:

Defining climate modelling user needs What is actually required to support impact analysis and adaptation policy development? Rob Swart (Alterra, Netherlands) and Christian Pagé (CERFACS, France) 2010 AGU Fall Meeting Session on Climate modelling in support of policy decision making: needs and limitations II 15 December 2010

Background IS-ENES: Infrastructure for the European Network for Earth System Modelling Effort to better connect climate and impacts communities since late 90s - with mixed success Questionnaire to users in Europe during summer 2010 and workshop in January 2011 Results support new strategy for European climate modelling groups upcoming years

Global climate modelling Statistical/dynamic downscaling The biophysical impact researchers??? The socio-economic researchers? Practitioners, public/ private decision makers? Who are the users? Water management; Agriculture and forests; Biodiversity/nature protection (terrestrial, freshwater); Coastal areas; Marine (biodiversity) and fisheries; Health (human, animal, plant); Infrastructure (transport, energy, other); Financial instruments and insurance; Urban and other types of spatial planning; Disaster risk reduction.

Two levels of users? Many non-specialized users – need guidance? Many specialized users – need tailoring?

Specify climate data users Account for a diverse group of users –types of sectorial impacts and –roles/functions (from impact modelers to private sector decision makers) –regions with a very different level of knowledge Distinguish between non-specialized and specialized, niche users –data volume –guidance and support provided.

Types of information required by impact communities Derived climate indices, notably indices on extreme events Highest resolution possible, but then how to deal with uncertainties? Full range of scenarios, including outer ends of ranges (worst or best case) Probabilistic scenarios - these have advantages but also serious constraints in terms of their interpretation: to avoid over- interpretation must use with caution and proper guidance Simple post-processing tools, e.g. for simple statistics, data conversions, or visualization 4-5 years? Rotterdam?

Not just data Guidance on how to use and interpret the information with proper account of uncertainties Better integration/harmonization of data sources at different geographic level Specific tailor-made information is required for many specialist applications that cannot be meaningfully addressed in a generic way ???

Easy access Impact and adaptation researchers are not climate modellers: –Interface: design user friendly interfaces –Format: offer a variety of data formats –Barriers: remove institutional or financial constraints –Guidance: provide simple guidance

The broader context Connect communities: the climate modelling and impacts communities should jointly work on developing guidance for impact researchers on how to select and interpret climate scenario output in a way that best matches their needs. Link with other scenarios: coordination with the provision or development of socio-economic scenarios is important.