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CLIMATE CHANGE RELATED STATISTICS OTHER THAN THOSE RELATED TO GHG INVENTORIES

CLIMATE CHANGE RELATED STATISTICS OTHER THAN THOSE RELATED TO GHG INVENTORIES. Jaroslav MYSIAK Fondazione Eni Enrico Mattei, Euro-Mediterranean Center on Climate Change. Main messages.

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CLIMATE CHANGE RELATED STATISTICS OTHER THAN THOSE RELATED TO GHG INVENTORIES

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  1. CLIMATE CHANGE RELATED STATISTICS OTHER THAN THOSE RELATED TO GHG INVENTORIES Jaroslav MYSIAK Fondazione Eni Enrico Mattei, Euro-Mediterranean Center on Climate Change

  2. Main messages Valuable: The extended participation of NSOs in the knowledge-production for the sake of better understanding of climate risk and adaptation is valuable and welcome, Evil is in the detail: The review of the data needs and opportunities for better data provision is very broad and lacks details about: Economic value of better and more accessible data, How embedded in the National Statistical Systems/Data infrastructure, consideration of subsidiarity principle (keywords update and quality insurance), Priorities: To make a tangible difference, set the priorities, identify the quick gains/practices implementable with low costs and high benefits.

  3. Climate change impact, vulnerability and adaptation - From GHG emissions to specific, spatially explicit impacts, and/or vice-verse, from individual behaviour to (large-scale) pattern of GHG emissions, - A web of interrelated components, some of which are known or knowable, others analysed through experimental design, - Advancement of methods and tools hampered by lack of reliable, sufficiently documented, spatially explicit, and accessible data, - (At least partly) different requirements for slow on-set events compared with extreme meteorological events.

  4. Responding to policies - 2012 UNEP review shed light on the internationally agreed (and for the most part not fulfilled) goals and targets, but for most of them the up-to-date data is not available. - EU 2020 Strategy on the way to low carbon, resource efficient and sustainable economy, and EU environmental and climate change policies contain many (additional) targets. - Unclear terms, lengthily negotiation, retrospective data collection.

  5. Difficulty to align NSS with IPCC IPCC’s (mandated with an assessment not a review of existing knowledge about climate change impacts): confidenceand uncertainty. Uncertainty cascade - dealing with multiple possible pathways, hence a number of assumption Multitude of methodologies, tools and pathways depending on the policies adopted to induce reduction of GHG emission and incentivise private autonomous adaptation

  6. Practical examples Costs of climate extremes Incomplete coverage: Only direct losses are counted for, neglecting the indirect and intangible losses. Only few records equipped with economic estimates. Trend detection:normalisation does not account for risk mitigation (e.g. land use changes, river modification) and governance (e.g. enforcement of building restrictions) (Wider) Impacts of environmental policies Quickly changing environment, monitoring of the deployed tariffs, taxes and transfers: Craftwork: counterfactuals, base-line scenarios Social impact analysis requires information about the users

  7. Flood risk assessment: Learning from the past

  8. Flood risk assessment: Learning from the past

  9. Flood risk assessment Indirect losses 1. General Equilibrium model ICES, refined for Italy ino three geographic macroareas (North, Centre, South). 2. Affected labour and capital obtained from hydrological simulations, statistical bereau census data, municipal level. 3. Different elasticity of substitution – mode variants.

  10. Flood risk assessment Data poor regions On March 31th and April 1st, 2013, Port Luis, the capital of the Republic of Mauritius was hit by torrential rainfall with estima-ted return period > 300 years. Precipita-tion over 3 hours ex-ceeded 150 mm.

  11. Role of the NSS and NSO COLLECTION of data, CERTFICATION insurance, provision of ACCESS Cost arguments, subsidiarity principle Measurable is only what is prescribed Exploitation of data. (Thanks for the facts. Now sell them) Data assimilation

  12. Recognise opportunities More quick gains than access to micro-data: improve access to and demonstrate possible applications of the existing data sets, avoid duplication of data collection (e.g. multiple monitoring of land consumption/soil sealing), assimilate data from other sources, negotiate access to proprietary data. Revision of the existing data collection campaigns, Foresight studies beyond demographic growth land use change, soil sealing, urban sprawl, innovation and technology diffusion (caveats: driven by policy)

  13. Questions ORIGINAL DATA COLLECTION: Knowing what data is or might/will be required and in what detail requires permanent dialog with the users’ communities. Often the indicators of progress towards achieving certain policy goal are negotiated and/or agreed on only successively and major efforts are needed to establish the base year/line conditions. Q: To what extent is it possibly to redesign the existing data collection campaigns to meet the needs of others? Q: How to ensure continuity of data collection and comparability of collected data under changing policy requirements?

  14. Questions (cont.) QUALITY ENSURANCE: NSO are the most authoritative data providers/sources. The multiple users look upon the NSOs for reliable, easily accessible and well documented data sets, often for different purposes. While it is very valuable to extend the NSOs operation so as to provide better information for climate adaptation policies, this should not compromise the quality of the information services provided. Q: Are the NSOs prepared and able to i) certify quality (e.g. consistency and reliability) of data provided by/gained from other organisations, and ii) maintain the data?

  15. Questions (cont.) Q: Are the existing NSOs’ metadata information systems prepared to deal with potentially large data set provided by others? (This does not refer only to the access and storage capacity but also human resources and procedures to describe the content and quality of the data).

  16. Thank you! This research project has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) / grant agreement n° 265213 –Project EPI-WATER “Evaluating Economic Policy Instrument for Sustainable Water Management in Europe”.

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