The Value of Climate Services Across Economic and Public Sectors

1. The Value of Climate Services Across Economic and Public Sectors Janet Clements, Water Resources Economist, Stratus Consulting April 8, 2013

2. What I will cover • Literature review • Methodological characteristics of valuation studies: • Type of climate services • Scale of analysis • Ex ante/hypothetical vs. ex post/observed use of climate services • Specification of climate services benefits • Factors influencing value • Challenges in improving valuation studies • Going forward . . . .

3. Literature Review • Process for identifying valuation studies • Weather and climate services terminology • More than 185 studies reviewed • 143 studies assessed values at the sector level • Work products: • Summary matrix of all studies reviewed • Summaries of selected studies • Synthesis Paper

4. Literature Survey: Distribution by Sector

5. Study Characteristics: Geographic Distribution of Studies

6. Value of Climate Services Studies: Applications by Sector Agriculture • Crop management (e.g., input use, timing of planting/harvest, crop selection); Irrigation decisions; Herd management (e.g., when/how many animals to sell); Implications for global trade market Fisheries • Responding to threat of harmful algal blooms (HAB); Harvest management Energy • Planning purchases of gas and electric power; Managing responses in emergency situations; Grid/distribution management; Optimizing reservoir/hydropower operations

7. Applications by Sector (con’t) Transportation • Reducing wait times on runways; Fuel purchasing; Accident reduction; Snow preparation/removal Water Management • Storage/release decisions by reservoir managers; Water pricing/allocation; Water for environmental purposes Tourism/recreation • Marine forecasts/warnings; Event management Disaster management • Hurricane preparedness; Early warning systems

8. Study Characteristics: Forecast Types • In agriculture, water management, and fisheries sectors, almost all the studies considered discrete seasonal forecasts (e.g., ENSO phase forecasts). • In other sectors, the use and valuation of short-term forecasts is more common. • Very few studies of the value of long-term forecasts

9. Study characteristics: Forecast types • Most studies assume a perfect forecast scenario • With a perfect phase forecast, average conditions are typically assumed. • Some value climate services using probability-based or imperfect forecasts. • Imperfect forecasts typically portrayed as capturing some percentage of the value of a perfect forecast (can be small or even zero). • Vary by lead time, weather parameters, specificity

10. Study characteristics: Level of aggregation • In agricultural sector, the most common type of assessment examines value at the crop/enterprise level • Studies at farm level allow land allocation to vary between cropping systems • In sectors other than agriculture, sector and higher levels of aggregation are more common

11. Study characteristics: Ex ante vs. observed studies • Majority of studies include ex ante predictions of value • In agriculture, majority of ex ante studies use crop-growth simulation models as the basis for crop yields under different forecasts • Baseline management decisions typically assume perfect knowledge of historical climate data • Very few based on observed changes in management in response to forecasts • Several studies have used surveys and other techniques to qualitatively assess the use of climate services

12. Study Characteristics: Benefits quantified Mostly financial/economic • $/hectare or $/acre • Avoided revenue losses • Total welfare gains (consumer/producer surplus) • Change in prices (e.g., crops, electricity) • Cost savings • Increased sales/income Environmental/social • Water savings • Reductions in nitrogen applied to crops • Reduced soil erosion • Household willingness to pay for forecasts • Increased recreational fishing days

13. Example Benefit Estimates – Agricultural Studies Regional/National • $1.1 million in annual benefits for Australian farmers in Merredin region with forecasting technology that provides 30% decrease in seasonal uncertainty • $10 million annually for Mexico economy with use of ENSO early warning system by farmers Farm level • $0.44 – 0.85 in willingness-to-pay by households in Zimbabwe for improved seasonal forecasts • $9-35 per acre by adjusting crop mix to ENSO phase in Argentina Sector-level • $36 million in benefits to Canadian hay production with daily precipitation forecast • $1.1 billion in losses to U.S. agriculture from incorrect 2000 drought Global/National • Global annual value of ENSO phase information in agriculture ranges from $399 million to $556 million to $1,390 million. • Global value of climate prediction approximately $900 million Sources: Makaudze, 2005; Jones et. al., 2000; Fox et. al. 1999; Changnon, 2002; Petersen and Fraser, 2001; Adams et. al., 2003; Chen and McCarl, 2000; Chen et. al., 2001; Chen et. al., 2002; Hallstrom, 2004

14. Example Benefit Estimates – Other Sectors Water Up to $11.6 million in annual welfare benefits with perfect ENSO forecasts in the Northern Taiwan regional water market $100-350 million in annual benefits to Georgia in drought years with use of water management strategies based on precipitation index forecast. Energy 100% increase in net weekly income for wind energy producers in Europe with medium-range forecasts $1 to $6.5 billion in decadal hydropower benefits for Ethiopia with perfect ENSO-based precipitation forecast Transportation $11 million in avoided costs of carrying extra fuel for Quantas Airlines in Australia due to improvements in terminal aerodrome forecast information $56.1–60.1 million in avoided costs to Swiss economy with use of weather services in the transportation sector Fisheries $902,000 in average annual total welfare benefits related to Pacific Coho salmon fishery with use of perfect ENSO forecast. Other Households willing to pay $25–41 per year for tropical cyclone service in Australia $468 million in avoided fatalities from Philadelphia’s heat watch/warning system from 1995 - 1998 Roulston et. al. 2003, Block, 2011; Weiher et. al. 2005, Frei et. al., 2012; Costello et. al., 1998; Quiroga et. al., 2011; Steinemann, 2006; Anaman et. al., 1997; Ebit et. al., 2004

15. Valuation Methods • Decision theory • Employed in majority of studies (across all sectors) • Various economic models (utility maximization, avoided costs) • General equilibrium concepts • partial equilibrium, sector, and trade models • Game theory • limited use • Econometric models • Contingent valuation (willingness to pay, WTP) • Benefits transfer • avoided costs, value of statistical life, WTP values

16. Factors influencing the value of forecasts Many factors can lead to under/overestimation of climate services: • Forecast characteristics/quality • Decision-maker characteristics • Decision-maker environment • Constrained management options

17. Going forward . . . . . • Identifying appropriate methods and providing guidance (e.g., benefits transfer potential, valuation issues) • Focusing on specific questions (e.g., funding, prioritization, effectiveness) • Ground-truthing Are we asking questions relevant to users? • Incorporating advanced forecasting techniques/implications of climate change