Vulnerability and Adaptation Assessments Hands-On Training Workshop

1. Vulnerability and Adaptation Assessments Hands-On Training Workshop Developing Baseline Socioeconomic Scenarios for Climate Change Vulnerability and Adaptation Assessment

2. What are baseline socioeconomic scenarios? Four steps for developing socioeconomic scenarios Structured examples Overview

3. It can be very complicated to create detailed and comprehensive socioeconomic and environmental scenarios There may be greater uncertainties about future socioeconomic conditions than about climate change Try not to get bogged down in this exercise The best thing to get out of this is identification of variables that can substantially affect vulnerability to climate change A Note Before We Begin

4. Baseline scenarios estimate changes in socioeconomic and environmental conditions absent climate change Socioeconomic conditions determine key aspects of vulnerability and adaptive capacity to climate changes Object is to construct plausible reference points to understand how vulnerability may change It is not to predict future socioeconomic conditions What Are BaselineSocioeconomic Scenarios?

5. Country Adults AdultRate % Women Children AIDS DeathsAmong Adultsand Children Orphans due to AIDS Angola 220,000 3.9 130,000 23,000 21,000 110,000 Benin 62,000 1.9 35,000 5,700 5.800 34,000 Botswana 330,000 37.3 190,000 25,000 33,000 120,000 Burkina Faso 270,000 4.2 150,000 31,000 29,000 260,000 Burundi 220,000 6.0 130,000 27,000 25,000 200,000 Cameroon 520,000 6.9 290,000 43,000 49,000 240,000 Central African Republic 240,000 13.5 130,000 21,000 23,000 110,000 Surprises Are PossibleHIV/AIDS Cases (Avert.org)

6. Step 1: Analyze vulnerability of current socioeconomic and natural conditions to future climate change Step 2: Identify at least one key indicator for each sector being assessed Step 3: Use or develop a baseline scenario approximately 25 years into the future Step 4: Use or develop a baseline scenario 50 to 100 years into the future General Approach

7. Most straightforward baseline scenario is to use today’s conditions. Why? Today’s conditions are known Easier to communicate about today’s conditions than hypothetical future This is a starting point Can compare to vulnerabilities with hypothetical scenarios to identify variables which most affect vulnerability Current conditions will change Step 1: Analyze Vulnerability of Current Conditions to Climate Change

8. Indicators Good general proxy for the sector’s health and condition Is closely related to vulnerability of the sector More or less of the indicator is correlated with more or less vulnerability in the sector Enable link to change in larger socioeconomic variables such as population or income to change in sector Step 2: Identify Key Sectors and Indicators and Examine Current Conditions

9. Examples Agriculture sector Food security Import and food aid share Water sector Water use intensity Percent of population served by water treatment plants Examples of Indicators

10. Example Indicators for the Water Sector Water

11. Indicators Should be Quantifiable

12. Forecasting socioeconomic conditions beyond ~25 years has much uncertainty ~25 years consistent with many planning horizons Nothing magic about 25 years; could be a longer or shorter period Step 3: Develop ~25 Year Baseline Scenario

13. Use government or other scenarios if available Can they be used to estimate how indicator variables have changed? Can use other countries as analogue Develop own scenarios Developing Baseline Scenarios

14. Example of Using National Planning Documents to Develop Scenarios Tunisia’s Economic Development Plan

15. Increase trade liberalization Continue privatization of production in competitive sectors Increase economic growth to 6% Improve capital and human resources Annual population growth of 1.6% Annual per capita income growth of 4.3% Economic Goals Identified in Tunisia’s Economic Development Plan

16. Increase production (4.3% annual growth) and diversity Improve food security Increase export income Mobilize water resources Increase storage capacity Improve efficiency and reuse of water Tunisian Agriculture Goals

17. Define relevant analytic timeframe (e.g., 2030) Annual rates of change for Crop yield Arable acreage Irrigated acreage Water use intensity (e.g., m3/ha) Socioeconomics (e.g., population and GDP) World commodity prices (e.g., from U.S. BLS) Developing a Baseline for Agriculture

18. Using Analogue Countries to Estimate Change in Indicators

19. Baselines for Bangladesh

20. Vulnerability Indicators

21. Estimate total population and workforce population change Workforce will be needed to help estimate economic growth Use UN population projections because they give estimate by age group Project working age population, e.g., 20 to 65 http://esa.un.org/unup/ An Approach for Creating a 25 Year Baseline Scenario: 1

22. Estimate change in labor productivity Obtain data from national projections The Handbook includes regional productivity projections from Mini-Cam Multiply % change in labor productivity by % change in the workforce to estimate change in national income; e.g., if the workforce grows by 3% per year and productivity grows by 1%: Multiply 1.03  1.01 to get 1.04; 4% rate of economic growth Multiply, do not add, the percentages. This becomes important over many years An Approach for Creating a 25 Year Baseline Scenario: 2

23. Relate the change in economic growth (or other variable such as population) to the indicator variable There may or may not be a direct relationship between economic growth or population and the indicator variable Judgment may be required An Approach for Creating a 25 Year Baseline Scenario: 3

24. Developing a long-term baseline scenario can be desirable if the analysis of vulnerability and adaptation will go out the same length of time Socioeconomic scenarios developed for such long time periods have very high uncertainty There is very uncertainty about key variables such as population growth, productivity, technology, tastes Step 4 (Optional): Develop 50-100 Year Baseline Scenario

25. IPCC Special Report on Emission Scenarios (SRES) estimates global population, economic activity, and emissions of greenhouse gases out to 2100 Divides world up into very large regions Some cover more than one continent An Approach for 50-100 Year Baseline: Use IPCC SRES Scenarios

26. IPCC SRES aims for an internally consistent framework and assumptions relating to various factors including: GHG emissions Socioeconomic conditions Climate conditions Each storyline describes a global paradigm based on: Prevalent social characteristics and attitudes Global relationships among economic growth, industrialization, global and regional trade, social attitudes, and environmental conditions SRES Scenarios

27. Internal consistency requires that relationships among variables such as emissions, economic activity, and global trade be plausibly maintained: For example, high population growth rates may not be consistent with high rates of per capita income increases Storylines are used to estimate patterns and changes in socioeconomic indicators such as: Population growth Economic growth and industrialization Environmental resource use and conditions SRES Scenarios (continued)

28. SRES Scenarios (continued) • Four poles along two major axes • Economic vs. environment • Global vs. regional • Combinations of these four poles give rise to four primary storylines • A1 – Economic growth and liberal globalization • A2 – Economic growth with greater regional focus • B1 – Environmentally sensitive with strong global relationships • B2 – Environmentally sensitive with highly regional focus

29. Global Population Growth Across the Scenarios

30. Storylines should in most cases be consistent with national and regional scale trends, unless there is clear indication that the exposure unit will develop in a manner that runs counter to such trends Project teams will then need to make projections about how indicators could change in the future under the alternative storylines Developing Country-Level SRES Storylines

31. Scenario data are limited on national and subnational scales National level, downscaled data are available for population and income projections With appropriate caveats, downscaled SRES data can be used to examine changes in specified indicators Qualitative assessment is important Expert judgment and stakeholder input are especially relevant here SRES Storyline Data

32. Country level population data are available on the CIESIN web site SRES Country-Level Data

33. Example, method, and tables are drawn from Malone et al. (2004) Numerical example is illustrative of a quantitative approach Analogous methods may be applied to other indicators Try not to be mechanical in application May need to use some imagination Qualitative and narrative approaches should also be used where appropriate and necessary Brief Example for a Developing Country

34. SRES Percentage Changes in Africa and Latin America Populations from 1990

35. SRES Percentage Changes in GDP for Africa and Latin America from 1990

36. Step 1: Use SRES scenarios to develop estimates of population and GDP percentage changes from base year (e.g., 1990). Step 2: Estimate percentage changes in total food consumption from base year. This is likely to follow population changes, but may be adjusted up or down to reflect anticipated improvements or decreases in overall diet and nutrition. Step 3: Estimate total cereal needs in thousands of metric tons. WRI (2000) reports, by country, the “average production of cereals” and the “net cereal imports and food aid as a percent of total cereal consumption.” Together, these two measures can be used to estimate total cereal needs. Steps for Scenario Development (steps 1-3)

37. Downscaled to Country-Level Example: Estimated Basic Food Demand: SRES A2 Scenario (steps 1-3)

38. Step 4: Estimate import and food aid shares. Food imports begin at 43% for African Country 1 as reported in WRI (2000) for 1995. One way to proceed is to choose a target import share for 2100 that is consistent with the relevant SRES storyline. Step 5. Estimate in-country production. This estimate is calculated by subtracting from 1 the import share calculated in Step 4. This gives the share of total cereal needs that is met by in-country production. This number is then multiplied by estimated total cereal needs to give the estimated level of agricultural production implied by the scenario. Step 6. Estimate crop yields and percentage changes. Cereal crop yields are estimated based on required in-country production and assume that planted area is constant. Steps for Scenario Development (steps 4-6)

39. Downscaled to Country-Level Example: Estimated Basic Food Demand: SRES A2 Scenario (steps 4-6)

40. Developing century-long scenarios can result in fantastic results If the analysis does not have to go so far out into future, then only go as far as needed e.g., 30 or 50 years Tradeoff with examining longer-term climate change Timeline

41. Remember that creating baseline scenarios is not an end in itself The purpose is to understand how vulnerability can change Most desirable outcome is to identify variables that can substantially change vulnerability Examine sensitivity to change in those variables Concluding Thoughts

42. Identifying key variables can be useful for policy making Don’t get consumed by baseline scenarios Even a relatively simple comparison of vulnerabilities using no change in socioeconomic conditions and a scenario going out a few decades can provide insights on which variables have a particularly large effect on vulnerability Concluding Thoughts (continued)