Climate Projections: From Useful to Usability Richard B. Rood, Maria Carmen Lemos, Donald E. Anderson Richard B. Rood December 15, 2010

Outline Introduction of the problem Literature review Uncertainty fallacy Relevance to providing climate data Lemos and Rood, Wiley Interdisciplinary Reviews, 2010Wiley Interdisciplinary Reviews, 2010

Introduction of the problem Investigate the perceived gap between the production of climate predictions / projections and their use by practitioners, stakeholders, decision makers etc. –Point of View Political scientist and a physical scientist Literature review: Empirical evidence on the use of climate projections. –Seasonal forecasts –Regional Integrated Sciences and Assessments Centers Experiential

Evidence for Lack of Use Failure to develop policy Amplification of the language of uncertainty in political arguments and science research programs Mixed, both good and bad, outcomes from experiences of using climate projections / predictions Misunderstanding and poorly matched expectations of producer and providers Lack of understanding of the scope and methods of use of climate projections / predictions –That is – climate projection information is, indeed, used There is a range of usability: Informs us on better use

Literature Review Based largely on research into the use of seasonal forecasts –For example, choice of seeds for a wet or dry year A definition –Useful / Usefulness: scientist’s perception of user’s needs –Usability: users’ definition of what knowledge can be readily applied to their decision process

Literature Review: Mixed Results Same seasonal forecast –Valuable to resource-rich, market-based irrigated farmer in Australia –No value to subsidence farmer in Africa with no technological alternatives Lemos and Morehouse (Global Environmental Change, 2005) – usable information –“directly reflects expressed constituent needs, should be understandable to users, should be available at the times and places it is needed, and should be accessible through the media available to the user community.”

Literature Review: Uncertainty What is the role of uncertainty in decision making? –Decisions are always made in the presence of uncertainty Physical climate Policy decisions Environmental engineering Land use / Land change / Urbanization Technological capabilities Economic impact Political landscape ---

Role of Uncertainty It is unlikely that a nuance on the quantitative representation of uncertainty is the greatest hindrance to increasing the usability of climate data. More sophisticated algorithms, more complete models of complex systems rarely lead to uncertainty reduction. Focus on, perhaps: –Uncertainty description –Uncertainty quantification –Process based uncertainty analysis

Politics and Uncertainty Amplification of the language of uncertainty in political arguments and science research programs - Selective Doubt Scientific Investigation Produces: Knowledge of Global Warming from Projections Scientific Investigation Produces: Uncertainty of the Knowledge RESPONSES None Mitigation Adaptation

Politics and Uncertainty Uncertainty is a product of scientific investigation. There is always uncertainty. Uncertainty can be and is used to fuel political and advocacy positions

Uncertainty Fallacy Uncertainty fallacy, that is, a belief that the systematic reduction of uncertainty in climate projections is required in order for the projections to be used by decision- makers. –Follows from Review of the use of climate data Role of climate uncertainty relative to other sources of uncertainty Role of uncertainty in political and advocacy arguments

How does this inform providing climate projections? Balanced approach to address all of the elements in the knowledge system –Directly addresses practitioner’s needs –Understandable –Available –Accessible –Process-based translation of imperfect projections Uncertainty description and application –Vetted, evaluated, standardized, documented

Systems Definition: Implementation planning Basic Data Projection Products Application’s Community Tasks Data Formats for Community Remapping, regridding Localization (space and time) Parameters (Penman-Monteith) Indices (e.g. Frich) Ensemble Analysis Information databases Information Portals Tasks Inventory of products Inventory of services Development of experiential base Tasks Inventory of existing activities Partnering of existing activities Re-use and interoperability? Tasks Emergence of analysis approaches Emergence of evaluation approaches Co-generation of solutions Tasks Documentation of end-to-end problem solving Extensibility / Scaling Up Feedback to Basic Data Tasks Interfaces to problem solving knowledge base Process improvement

Some notes from heat wave study Can we do better than just saying that it is going to get hotter? What is value of nuanced calculations of heat extremes and stress? Is it usable information? What is the balance between having to study each case and the ability to aggregate information and develop general strategies? What is the minimal level of complexity that must be accommodated?