SimCLIM Booth presentation

  • View
    454

  • Download
    0

Embed Size (px)

DESCRIPTION

Overview of SimCLIM Software and CLIMsystems

Text of SimCLIM Booth presentation

  • 1. Bridging the gap between climate change science and action: CLIMsystems and the SimCLIM system

2. Importance and Demand Importance of Climate Change Scenarios for EndUsers: V&A assessment, planning, mitigation,DRR Who practically use the scenarios:Policy makers (Planners), consultants, engineers,researchers . . . What sort of information do they demand:extremes, averages, sea level, temperature,precipitation, wind, vapour pressure, sea surfacetemperature, TC. 3. Examples of adaptationactivities that requireclimate risk information New infrastructure Costbenefit analysis, infrastructure performance and design Resource management Assessment of natural resource availability, status and allocation Retrofit Scoping assessments to identify risks and reduce exposure to extreme events Behavioural Measures that optimize scheduling or performance of existing infrastructure Institutional Regulation, monitoring and reporting Sectoral Economic planning, sector restructuring, guidance and standards, DRR Communication Communicating risks to stakeholders, high-level advocacy and planning, DRR Financial Services to transfer risk, incentives and insurance 4. Part of the next generation 5. Model assessment and inter-comparison This implies caution when interpreting the output from asingle model or a single type of model (e.g. regional climatemodels) and the advantage of including as many differenttypes of downscaling models, global models and emissionscenarios as possible when developing climate-changeprojections at the local scale (Haylock et al 2006) CORDEX: Coordinated Regional Climate DownscalingExperiment (CORDEX) STARDEX: Statistical and Regional dynamical Downscaling ofExtremes for European regions HadEX: Hadley Centre global land-based gridded climateextremes data set 6. Regional/country/local/Climate Change Baseline and Scenarios East TimorMalampa VanuatuBhutan Marshall IslandsEritreaHo Chi Minh CityKorean PeninsulaUsing all available IPCC AR4 Data (all more than 20 GCMs, daily monthly output,Temp, Prec, relative humidity, wind, SST, solar radiation) 7. Co-evolutionary Decision Support Systemfor climate change V&A assessment Speeds up problem solving: With the pre- loaded data and impact models, and the fast analysis functionality and user friendly interface Facilitates interpersonal communication: All groups work with same data, platform and models Promotes learning or training Generates new evidence in support of a decision Encourages exploration and discovery on the part of the decision maker Developed with support from Reveals new approaches to the formulationAPN FAWSIM project (2008-2010) of problems.Bridges scientific community and policy makers 8. TrainingSNC Training VanuatuIMHEN Training Viet NamV & A Training Epi Island SimCLIM Training New Zealand 9. Summary Regional/local climate change uncertainty isconsiderable, inter model variability is the largestcomponent. Multiple model, downscaling method andRCP(SRES) ensemble approach is needed for riskassessment. Rapid scenario production has advantages inimpact and adaptation assessment Direct communication between researchers andend users is crucial for the whole assessmentprocess Hands-on tools are a plausible bridge to end users Thank you