Oasis being used in international/ community projects. Julie Calkins & Fred Hattermann & Future Danube Team

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1 Oasis being used in international/ community projects Julie Calkins & Fred Hattermann & Future Danube Team 1

2 Why applying OASIS LMF in international projects? There is a growing demand for user oriented climate services ( Climate services ensure that the best available climate science is effectively communicated with agriculture, water, health, and other sectors (-> insurance!), to develop and evaluate adaptation strategies. Easily accessible, timely, and decision-relevant scientific information. ) Huge (public and private) funds are currently allocated to better understand climate (and weather) related hazards and risks Needed is an open source standard for risk assessment that can be used by different sectors OASIS LMF provides tools and utility to all (-> easy to apply software, user support, workshops, community etc.) 2

3 Two examples EU Climate-KIC funded Open access cat-modelling driving adaptation to enable resilience in an uncertain future Set-up of the flood risk model for the Danube started in 2016 Funding for the Danube until end of 2017 EU Horizon 2020 funded Project duration Mai 2017 April 2020 Multi-hazard and multi-risk Strong cooperation with the OASIS consortium OASIS LMF and Genillard & Co are partners Several insurers committed their interest Climate service call 3

4 Programme key elements Working with OASIS since 2011, Flagship status in 2017 How CKIC sees itself - the program acts as a catalyst to accelerate new market development - attract supply, nurture demand, and build the end-user community for both climate risk mitigation and adaptation Support key entities that help set standards and provide the marketplace Demonstrate use of climate risk data and models beyond insurance Support enabling activity: capacity-building and financial innovation 13 innovation projects and a core community of 30 organisations incl NGOs, insurers, research/thinktank, City/local, and start-ups in viz and analytical tools Connections with global policy piece, development/drr actors and CoEs, EC/EUCPM, WB, UN

5 Standards and marketplace Set Standards: Further develop and promote the Oasis Loss Modelling Framework (LMF, to improve pricing of climate risk and open up the black box of catastrophe modelling. Provide a Market place: There is a need for a collaborative market exchange to drive the global market by linking demand for risk analytics, with the supply of open climate risk data and catastrophe models, tools and services. The OASIS Hub is the most prominent example. Building Capacity and Capability: Translation and implementation, developing tools and services to aid standardisation and interoperability.

6 Climate Risk Information Ecosystem The Vision: An open, global, and transparent marketplace for climate risk information Supply Service Provider Market Place Service Provider Demand Academia/Research Data & models marketing Marketplace Biz development (Re)Insurance SMEs Modelling Companies (Re)insurance Public institutions and donors MOOC providers Crowd sourcing E-Marketplace (OASIS Hub) OASIS LMF (Market standard setter ) Analytical tools Other consultant s /services Infrastructure, Agric, Industry Public authorities Health sector public & private Supply chains Climate-KIC (and other funders / multipliers) as convener, enabler and champion

7 : Demonstrate the value of climate risk data In end-user investment, insurance &/or planning decisions Multi-hazard tailored risk models for agric insurance in CEE Agric and E Africa, matching needs re/ins SwissRe, ACHMEA, WTW Cities Health Pluvial flooding risk assessment and adaptation for cities with Vjele, Gothenburg, Paris and responding to SCOR needs Using risk models to improve loss calculations and adaptation planning, with DCLG, health systems actors, EurapCo and cross-cutting effort to foster risk transfer methods and lower the barriers to engagement Capacity-Building New Financial Products Tools for increasing use and usefulness and usability, training for researchers, small insurers cities and utilities Sovereign credit rating, city risk pooling facility

8 Climate Risk Information flagship program We are: An active community of partners in supply/demand around Oasis family Pulling in public funders and research model developers Looking to extend the impact of risk modelling tools to new users/customers Growing our portfolio of projects (upcoming call!) For more information, please get in touch:

9 H2020 Insurance project background 9

10 Future Danube Model: climate service offer Better understanding of hazard and risk under current conditions and in areas which are currently model underdeveloped Better understanding of hazard and risk under future conditions End-user driven: Cooperation with the private (insurance) and public sectors 10

11 Why the Danube? 19 Countries and 83 million people, 4 capitals 2002 floods in Germany, Austria, Czech Republic, Hungary, Moldova, Switzerland, and Slovakia, causing total damages of 16,5 billion Euro (3,400 billion insured losses) and 39 fatalities 2013 floods in Austria, Czech Republic, Germany, Hungary, Poland, Switzerland, causing damages of 12,600 billion Euro (3,100 billion insured losses), and 25 fatalities (NatCatSERVICE, Munich RE)

12 Future Danube: Model suite Imperial College PIK Potsdam GFZ Potsdam DTU Kopenhagen & Additional partners: OASIS LMF Genillard & Co Pannon Pro Budapest Water Works Insurance sector PIK Potsdam

13 Continuous simulation model of flood risk chain Weather Generator Meteorological fields Eco-hydrol. Model: SWIM Bankfull discharge threshold value Routed flow River Network Routing: 1D Channel Network Model dike overtopping discharge Hinterland Inundation: 2D Raster-Based Inertia Model flood maps of max. water levels Flood Loss Model: direct damage to res. buildings 13

14 Modelling concept 14

15 Big data -> condensed information 240,000 years of daily climate and hydrological data ~13,0000 river sections ~200,000 spatial units Robust risk information 15

16 Future Danube: Model suite

17 Input: Realistic daily precipitation generated by weather module (many more events than observed -> rare (extreme) events) JJA precipitation for Upper Danube basin The largest observed event X 30 years of CORDEX data X 10,000 years of IMAGE data These extreme events were never observed, but are possible and cause the huge damages S. Hardwick, Imperial College 17

18 Future Danube: Model suite *

19 River sections and subbasins upper part of the Danube until Budapest Subbasins 13,778 Elements 186,296 PIK Potsdam

20 Change in recurrence of 100 year flood PIK Potsdam

21 Agreement in projections PIK Potsdam

22 Change in flood frequency under CC * increase in intensity (water levels) increase in frequency These statistics are there for each of the ~13,0000 river sections PIK Potsdam 22

23 Change in flood frequency under CC PIK Potsdam 23

24 Spatial change in hydrology PIK Potsdam 24

25 Future Danube: Model suite *

26 Loss estimation Spatially detailed or aggregated risk assessment T0: EUR 744 Mio T1: EUR 641 Mio T2: EUR 281 Mio Partner: GFZ Potsdam 26

27 Pluvial flooding (example: Vienna) Spatially detailed or aggregated risk assessment T0: EUR 744 Mio T1: EUR 641 Mio T2: EUR 281 Mio Partner: Danish Technical University 27

28 Link to OASIS LMF Exposure (Item) Area Peril Dictionary Vulnerability Dictionary Hazard Intensity Bin Dictionary Vulnerability Event Damage Bin Dictionary The resulting flood event set and vulnerability functions provide flood hazard footprints and the vulnerability components as input to the Oasis Loss Model Framework (LMF). 28

29 Take home messages Climate change impacts on large-scale hazard and risk Modular approach for either applying the entire suite to get consistent multi-peril estimates or to plug-in external modules or data within OASIS LMF Open GIS technologies for visualization of results Probabilistic approach as improved basis for informed decision making under uncertainty Tailor made models focusing on user needs and sites Further information: 29

30 Many thanks! Contacts: Julie Calkins, Climate-KIC Fred Hattermann, Potsdam Institute for Climate Impact Research 30

31 Increasing robustness of risk information Uncertainty bounds (in blue) before and after -> decreasing uncertainty 31

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