Assessing the benefits from improved hydromet services Orders of magnitude and future research Stéphane Hallegatte The World Bank, Sustainable Development Network

Disasters and asset losses If warning reduces losses by 10%, and only half of the floods are forecasted, 200m EUR of benefits per year in Europe If warning reduces losses by 50% and 75% of the floods can be forecasted, 1.5b EUR of benefits per year in Europe Idem with windstorm: between 460m and 2.7b in Europe Data from Day (1970) or Carsell et al (2004)

Annual asset losses that could be avoided thanks to EWS GDP (million USD) Potential (European-like) benefits Ratio of current vs potential benefits Estimation of current benefits Benefits from improved services Low estimate Likely estimate Low estimate Likely estimate Low estimate Likely estimate Low income 413, % Lower middle income 4,300, % Upper middle income 15,300, ,54250%2171, ,271 High income 43,000,0001,2177,145100%1,2177,145-- TOTAL 63,013,0001,78410,4701,4598, ,904 Potential benefits, assuming countries have the same potential (wrt GDP) than Europe

Annual asset losses that could be avoided thanks to EWS GDP (million USD) Potential (European-like) benefits Ratio of current vs potential benefits Estimation of current benefits Benefits from improved services Low estimate Likely estimate Low estimate Likely estimate Low estimate Likely estimate Low income 413, % Lower middle income 4,300, % Upper middle income 15,300, ,54250%2171, ,271 High income 43,000,0001,2177,145100%1,2177,145-- TOTAL 63,013,0001,78410,4701,4598, ,904 Broad assumptions about the share of potentials that are realized today

Annual asset losses that could be avoided thanks to EWS GDP (million USD) Potential (European-like) benefits Ratio of current vs potential benefits Estimation of current benefits Benefits from improved services Low estimate Likely estimate Low estimate Likely estimate Low estimate Likely estimate Low income 413, % Lower middle income 4,300, % Upper middle income 15,300, ,54250%2171, ,271 High income 43,000,0001,2177,145100%1,2177,145-- TOTAL 63,013,0001,78410,4701,4598, ,904 Estimates of current benefits in all countries

Annual asset losses that could be avoided thanks to EWS GDP (million USD) Potential (European-like) benefits Ratio of current vs potential benefits Estimation of current benefits Benefits from improved services Low estimate Likely estimate Low estimate Likely estimate Low estimate Likely estimate Low income 413, % Lower middle income 4,300, % Upper middle income 15,300, ,54250%2171, ,271 High income 43,000,0001,2177,145100%1,2177,145-- TOTAL 63,013,0001,78410,4701,4598, ,904 Hydromet services and early warning systems could reduce annual asset losses by between 300 million and 2 billion USD per year in developing countries

Other economic benefits from hydromet information in Europe Benefits from the optimization of economic production Weather sensitive sectors at the global level: – Agriculture, 2,000 billion USD; – Mining and energy, 7,000 billion USD; – Construction, 3,200 billion USD; – Transport, 4,300 billion USD. Total: sensitive sectors create more than 16,000 billion USD per year of added value, i.e. about 25% of world GDP.

Other economic benefits from hydromet information in Europe Examples of optimization of production processes: – Nuclear plants production levels take hours to adjust, and rely on electricity demand forecasts that are weather-dependent; – Some activities in the construction industry are temperature- dependent (e.g., concrete additional ingredients are required if temperature exceeds 32°C); – Farmers base their decisions (e.g., harvesting date, fertilizer application) on weather data and forecasts. – Air traffic and other transports can anticipate perturbations Case studies and national-scale studies in developed countries suggest value added gain from much larger than 1% of sector VA. With 0.1% or 1% gain, total gain from hydromet services in developed countries are between and % of GDP.

Annual economic benefits from hydromet information in developing countries GDP (million USD) Potential (European-like) benefits Ratio of current vs potential benefits Estimation of actual benefits Benefits from improved services Low estimate Likely estimate Low estimate Likely estimate Low estimate Likely estimate Low income 413, ,03310% Lower middle income 4,300,0001,07510,75020%2152, ,600 Upper middle income 15,300,0003,82538,25050%1,91319,1251,91319,125 High income 43,000,00010,750107,500100%10,750107,500-- TOTAL63,013,00015,753157,53312,888128,8782,86528,654

Natural hazards kill on average 43,000 persons per year in developing countries Number of people reported killed by weather-related natural disasters ( ), in developing countries and at the world level. There is no significant trend in these series. Data from EM-DAT: The OFDA/CRED International Disaster Database.

Developed vs. developing countries There is an annual death probability of 7.5 per million due to weather events in developing countries. The annual death probability is 2.2 per million inhabitants in developed countries. Using EWS, we assume that the annual death probability in developing countries could be reduced from 7.5 to 4 per million – Half the current level – Twice the level in developed countries Using Copenhagen Consensus values, it corresponds to an annual benefit of 700 million USD per year or 3.5 billion USD per year. This estimate is conservative, as we do not account for morbidity (injuries and disaster-caused illness)

How to improve hydromet services and EWS ? 1.The local observation system, based on ground, in-situ observations 2.Forecasting capacity, i.e. the translation of low-resolution model forecast into high-resolution forecast 3.Interpretation capacity, to translate model output into actual forecast and warnings 4.Communication tools, to make sure the alert reaches the individuals in charge to implementing prevention measures 5.Users’ decision-making capacities, to make sure warnings are actually used (including for evacuation). Cost (from national scale studies) in 80 developing countries, less than $1 billion per year.

Conclusions Type of benefits Annual benefits (million USD) Annual cost (million USD) Benefit-cost ratio MinimumLikelyMinimumLikely Reduced asset losses from disasters 3002,000 1, Reduced human losses from disasters 7003,500 Other economic benefits 3,00030,000 Total4,00035,500

Areas for future research

What about marginal benefits? Cumulative investment Benefits The problem is the non-convexity of benefits wrt investments To assess whether investments should be increased or decreased, what matters is the marginal benefit (i.e. benefit from one more dollar invested). Easier when assessing existing capability or instrument (example of the METOP system)

What about climate projections? Adaptation requires also anticipation, especially in sectors with long- term investments: – Water management infrastructure (lifetime: up to 200 years); – Energy production and distribution infrastructure (up to 80 years); – Transportation infrastructure (50 to 200 years) ; – Natural disaster protections (50 to 200 years); – Urbanism, housing and architecture (25 to 150 years). These infrastructures represent more than 200% of GDP in developed countries In developing countries, these infrastructures are currently being built and it is urgent to take climate change into account.

IPCC, 2007

What about national security? In the absence of national security considerations, much more cooperation and coordination would be possible.

The best is never to protect: the forecast creates too many false alarms to be useful. Its value is zero The best is to protect all the time: the forecast misses too many events to be useful. Its value is zero The ratio between protection cost and event losses (C/L) Value of the deterministic forecast of temperature anomaly above 8°C, 6 days in advance (144h) during the summer 2003 (850hPa level) FORECAST VALUE (0=climatology; 1=perfect forecast) Link with decision-making Source: ??

Link with decision-making Source: Olivier Mestre (Meteo-France)

The Northridge earthquake in 1994 The Loma Prieta earthquake in 1989 in San Francisco The role of indirect losses

The Northridge earthquake in 1994 Tierney (1997) Giuliano and Golob (1998)

Kroll et al. (1991)

Employment impacts

Model-based assessment of indirect losses Katrina Results from the ARIO model in Louisiana Little or no indirect loss if direct losses are below $50 billion. Indirect losses soar when direct losses exceed $50 billion. Hallegatte(2008)

Conclusions We can claim that hydromet services benefits exceed costs in rich countries We can claim that better hydromet services in developing countries would be cost-efficient (if we can do it) We cannot conclude on the “optimal” budget in rich countries and on the cost-effectiveness of selected investments (except in some cases, see the Metop paper) We have a long way to go to assess the cost-benefit ratio