management of local environmental quality or for example water savings due to more efficient irrigation. Social benefits comprise reduced losses of lives, injuries or illnesses but also increased psychosocial well-being.

Different techniques can be used to assign values to the benefits produced by improved weather information (WMO et al 2015):

- Non-market valuation techniques like stated or revealed preference methods.

- Economic modeling methods requiring significant amounts of detailed data and knowledge about the sectors where benefits are assessed, as well as substantial statistical expertise.

- Avoided-costs assessment, which is easier to implement than other options but only considers part of the benefits of improved forecasting. Additional economic benefits such as increased production due to forecasting are ignored.

- Benefits can also be assessed by transferring the results of existing benefit studies to the context being analyzed. This method is the least resource intensive but is also less robust.

None of the methods described is able to assess the full benefits of weather forecasting, as some benefits simply cannot be expressed quantitatively. Complementary quantitative and qualitative assessments can produce a more complete understanding (WMO et al 2015). However, it is often difficult to include qualitatively assessed benefits in a benefit-cost analysis; they are therefore not considered in this analysis.

# 3.3.1 Global benefits transfer

As conducting a comprehensive analysis of the socioeconomic benefits is outside the scope of this research, the data used to estimate the benefits are calculated based on the methods and assumptions used by Hallegatte (2012) on the worldwide socioeconomic benefits of improved early warning systems. Using the benefit transfer approach, the data from Hallegatte (2012) is converted and adapted to measure the additional benefits created by improved weather forecasting in LICs resulting from the provision of global forecasting products.

Hallegatte (2012) analyzes three types of benefits of improved forecasting and early warning: reduced asset losses, reduced human losses and improved economic productivity. In a first step, he uses data from studies on Europe, the OFDA/CRED International Disaster Database (CRED 2015) and the Copenhagen Consensus on Human Life’s definition estimation of life value (DALY – Value of Disability Adjusted Life Year; Copenhagen Consensus Center 2015) to estimate the benefits of forecasting and early warning in the three benefit categories in Europe.

Hallegatte (2012) then uses a benefit transfer approach to apply these estimates to LICs and MICs; the benefit of forecasting in Europe in percentage of gross domestic product (GDP) corresponds to the potential total benefit of European forecasting quality in LICs and MICs:

- The reduction in asset losses due to increased forecasting quality is estimated to be between 0.0003 and 0.017 percent of GDP. From that it is inferred that improving forecasting services to European standards would lead to avoided asset losses between US$ 300 million and 2 billion per year in LICs and MICs.

- Using data on fatalities due to weather disasters from the OFCA/CRED EM-DAT database, the average annual risk of death due to extreme weather in LICs and MICs is 7.5 per million. After

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