WMO Social and Economic Benefit Studies in WMO region RA VI Adriaan Perrels Vice-chair WG SDP / chair TT-SEB2 Zagreb, Croatia, SEB course – 29.6 –

Contents  RA VI – reported interest in SEB  Conducted SEBs in RA VI  Case study examples  Exploitation and communication  Conclusions 2

3 WMO survey on SEB in RA VI (2011) 25 NMSs responded (out of 50)

Reported reasons for interest in SEB  Justifying public funding 68%  Investment / R&D prioritization 44%  Service development (incl. charging structures) 56%  Many respondents indicated that support was welcome (from the WMO), notably regarding:  Guidance (’how to define / conduct / etc.’)  SEB methods  Experience & information sharing  Funding 4 book TT-SEB / COST

SEB studies in RA VI area (not exhaustive)  UK MetOffice (2007; 2013; 2015)  Russia (2001; NOAA 2006)  Denmark (DMI) (Transport Ministry 2006)  Finland (FMI) (VTT 2007/2008; FMI 2011/2012)  South-East Europe & former CIS (World Bank 2008)  Croatia (HMZ) (VTT/FMI 2008)  MeteoSwiss (INFRAS 2008)  Spain (AEMET) (datos.gob.es 2014) 5

Examples of SEB studies  MeteoSwiss (Frei 2010; Frei et al 2011)  Broad scope, but with emphasis on transport  Benefit transfer by sector and by approach  All weather service providers in Switzerland  FMI (Nurmi et al 2012; Nurmi et al 2013)  Focus on transport  Deep analysis of the value chain  Also tries to account for user cost  UK MetOffice (2013)  (2013) Benefits of high performance computing  Avoided hazard cost; optimal wind power siting 6

Characterizing case studies test footer 7 CharacteristicsSwitzerland Finland UK Purpose(s) Validation of hydro/met-services Validation of investment Commissioned by MeteoSwiss FMI/ VTT (EVASERVE project) ; FMI UK MetOffice Carried out by 1.Internally (pre-study) 2.INFRAS 1. VTT 2. Internally private consultants; universities Funded by MeteoSwiss EVASERVE project / FMI EU EWENT / FMI UK MetOffice Scope First broad brush; later more precise (transport) First quite broad (based on data availability); later more precise (transport) one specific topic – benefits of new super computer (focuses on measurable benefit generation in selected sectors) Costs of SEB study 1.? 2.~ $ ~ 20 person months (around € ) 2.roughly € approx. £ per sector study Estimated (net) benefit ~ $ 240 million/year; costs: ~ $ 83 million/year (incl. private WS) Road: B/C ratio ~10 ~ $ 360 million/year (260?) costs: ~ $ 75 million/year; road: € 36 million ; B/C ratio ~10 ~ £ 2 billion during 5 years; Investment cost: ~ £ 100 million Follow-up Links with / extension to climate services Communication of results More surveys by enduser group MCDA of service development choices Cross institute product development forum Benefit-cost analysis consultancy and studies Communication of results Purchase advice Communication of results and valuation method

Examples of SEB studies – in depth  Switzerland, Finland  Road: maintenance, clearance – cost savings better traffic flow – time savings avoided accidents – avoided cost Challenge is to show the differential effect of a new or improved weather service (as compared to current practice) 8

Tracing information effects test footer 9 Swiss road case (Frei et al 2014) Finnish road case (Nurmi et al 2013)

Examples of SEB studies – in depth UK MetOffice: Benefits of high performance computing:  Higher accuracy / resolution enables further hazard cost reduction through  Emergency services (better anticipation; deployment)  Better located and sized protection  less damage to private and public property  Higher accuracy / resolution enables:  Optimized siting of wind turbines  Benefits are conditional on quality of complimentary models and services 10

The benefits of showing the benefits  Analysis of the value chain not only gives an idea of the current net benefits, but can also show what can be improved in each stage of the value chain  Supports the development of understanding the customer, customer relations, and partnerships  Citizens  Public agencies  Specific sectors (agriculture, transport, energy)  Neighboring NMS’s  … facilitated by good communication 11

Conclusions  Experience with SEB is building up, but by no means common knowledge in RA VI  SEB is not only numerical results, but also a learning process and management tool  SEB comes in many sizes  purpose should drive the ambition level and allocated resources  Re-/deregulation as new motivator  Enhanced sharing of information and experience seems very useful  Value chain as a key concept test footer 12

References  Anderson et al (2015), Valuing Weather and Climate: Economic Assessment of Meteorological and Hydrological Services – case studies 1, 6 and 7  Datos.gob.es (2014), Estudio Sector Infomediario Parte III. Análisis Coste – Beneficio de la información meteorológica infomediario-2014http://datos.gob.es/content/estudios-de-caracterizacion-del-sector- infomediario-2014  Frei, Th., von Grünigen, S. and Willemse, S. (2012), Economic benefit of meteorology in the Swiss road transportation sector, Meteorological Applications  Frei Th. (2010), Economic and social benefits of meteorology and climatology in Switzerland, Meteorological Applications, Vol.17, pp. 39–44.  Leviäkangas, P., (2009), Benefits and value of meteorological information services – the case of the Finnish Meteorological Institute, Meteorological Applications, Vol.16, pp.369–379  Leviäkangas,P., Hautala, R., Räsänen, J., Öörni, R., Sonninen, S., Hekkanen, M., Ohlström, M., Venäläinen, A., and Saku, S. (2007), Benefits of meteorological services in Croatia, VTT Research Notes 2420, Oulu  Met Office UK (2007), The Public Weather Service’s contribution to the UK economy,  Nurmi, P., Perrels, A., Nurmi, V. (2013), Expected impacts and value of improvements in weather forecasting on the road transport sector, Meteorological Applications, Vol.20, pp.217 – 223  Nurmi,V, Perrels, A., Nurmi, P., Seitz, D., Michaelides, S., Athanasatos, S., and Papadakis, M. (2012), Economic value of weather forecasts on transportation – Impacts of weather forecast quality developments to the economic effects of severe weather, EWENT report D

Thank you for your attention Had this information a differential effect?