Seasonal early warning and climate risk management: Preparedness and adaptation

1. Seasonal early warning and climate risk management: Preparedness and adaptation Roger S. Pulwarty Director, Climate and Societal Interactions Division and National Integrated Drought Information System NOAA W. Baethgen, G. Galu, W. Thiaw, N. Trotz. L. Nurse, M. van Aalst………

2. “This IPCC report addresses, for the first time, how integrating expertise in climate science, hazards and disaster risk management, and adaptation can inform, help to reduce and manage the risks of extreme events and disastersin a changing climate” 2012 IPCC Special Report on Managing the Risksof Extreme Events and Disasters to Advance Climate Change Adaptation

3. The Romans clearly ignored the AD 350 IPCC and AD 300 UNIDSR Reports (50th edition-2012) Source: InfoRoma, 2004. www.inforoma.it DEFERRED MAINTENANCE?

4. Observed Physical System Changes-What is in the data? Air Temperature Near Surface (Troposphere) Glaciers (Glacier Mass Balance) Specific Humidity 3 Datasets 7 Datasets 4 Datasets Temperature Over Oceans Snow Cover (March-April, Northern Hemisphere) 5 Datasets 2 Datasets Sea-Surface Temperature Sea Level 7 Datasets 7 Datasets Ocean Heat Content Land Surface Air Temperature Over Land Sea-ice 5 Datasets 3 Datasets 7 Datasets 4

5. Weather-Climatea continuum and a deficit Climate spans an enormous range of time and space scales Impacts result from a number of complex variables 30DAYS 1SEASON Heat Waves Floods Storm Track Variations Madden-Julian Oscillation El Niño-Southern Oscillation++++++ Decadal Variability Solar Variability Deep Ocean Circulation Greenhouse Gases 3YEARS 10YEARS 30YEARS 100YEARS SHORT-TERM INTERANNUAL DECADE-TO-CENTURY 5

6. Where does climate variability come from? • NAO • TAV • Easterly Waves • ENSO • AMO

7. Whence does climate variability arise? PDO AMO ENSO

8. Climate Risk Management (CRM) is a term is used for a large and growing body of work, bridging the climate change adaptation, disaster managementand development sectors, amongst many others Image- S.Zebiak

9. The WMO on Climate Risk Management based on the guidance from the Symposium on CRM proposes a definition of CRM as “a systematic and coordinated process in which climate information is used to reduce the risks associated with climate variability and change, and to take advantage of opportunities, in order to improve the resilience of social, economic and environmental systems”

10. Yes-But Let’s Not Wait Too Long ! photo courtesy K. Dixon, NOAA GFDL

11. The solution space

12. Formalized Early Warning Systems • A repertoire of actions A = {a1, a2, ..., aA} that constitute agents practical behavior as shared knowledge between observers • A set of world states S = {s1, s2, ..., sS} can be used to evaluate local background and broader contexts • A set of outcomes Oa = {oa1 , oa2 , ..., oaA} indicating the state as it is assumed to be after the execution an action • A prediction function that expresses an observer’s hypotheses that, given at an instant t, n observed evidences for actions in An, with the context in S, a certain action will be performed by an observed agent at t + t0, with the respective outcome in Oa and a probability in the distribution P

13. Regional Scale Decadal Predictions ? Western Africa : Annual-Mean Temperature Southern Africa : Annual-Mean Temperature Climate Change Projections cannot deliver predictions of decadal variability

14. Source: CPC Prediction Branch

15. Science and Policy: Information Chains Knowledge “Translation”, “Tailoring” (Boundary Organizations) • Knowledge • Application • Operation • Policy Knowledge Generation New Research Questions New Knowledge Demands Here are the main Challenges: Need a “new type” of Scientist (integrator, interpreter, entrepreneur) Example: Information Chain in Disaster Risk Management Climate Information and Products for Disasters National Emergency System Climate Information Products Climate Science Local Implementation When the Chains are not present: Create them the solution is not to “skip links”, but to create the links When Chains are established and strong we do not need to “market”

17. CRM: Manage the Entire Range of VARIABILITY Probability (Density) HARDSHIP e.g., Drought CRISIS e.g., Mitch Climate related Outcome (e.g., food production)

18. Also Critical For Development: Risk aversion reduces Technology Adoption Effect on Natural Resources “Poverty Traps” CRM: Manage the Entire Range of Risks Probability (Density) HARDSHIP e.g., Drought MISSED OPPORTUNITIES CRISIS e.g., Mitch Climate related Outcome (e.g., food production------security) Weather Index Insurance

19. Decision Support Framework Assessing Consequences

20. 2010/11 rainfall compared to historical totals since 1950/51 in select pastoral areas of Kenya and Ethiopia Declaration of 60-year’s Worst Drought Source: FEWS NET/USGS and FEWS NET/NOAA Graphics: FEWS NET

21. Time-line between Early Warning & Famine Declaration 2010/11: Genesis of A Drought Crisis Food Security Outlooks , Updates & Briefings FEWS NET & Partners La-Nina Declared WMO/GHACOF Updates Peak Impacts/Massive Response Warning  Onset  International Media, UN Declaration of Famine Massive Humanitarian Response 1-year from Early Warning to Emergency Response?

22. Model agreement/convergence? Observational agreement

23. Food Security Outlook Scenario Approach A dynamic Early Warning Tool for Contingency & Response Planning A tool for communicating uncertainties….

24. Before making forecasts: • Meet with recipients or representatives to determine which measures they would find most useful • Independently analyze the problems that stakeholders face in order to obtain a complementary perspective • Empirically test formats for communication in order to ensure that stakeholders understand the information as intended • Seek users explicit agreement on appropriate formats. • Develop seasonal decision calendars cooperatively with stakeholders to determine key entry points for different kinds of information R.S. Pulwarty, S. Olanrewaju and P. Zorba 2008 Communicating Agroclimatological Information, including Forecasts, for Agricultural Decisions. WMO/CAgM Guide to Agricultural Meteorological Practices (GAMP)

25. While making forecasts: Make the nature of links to decision calendars and the forecast as explicit as possible, including alternate possible outcomes Document the assumptions underlying forecasts including how changes seasonal development would change the forecast (how is the forecast verifying?) When evaluating use: Conduct post-season farmer workshops (also during if possible) Review what was predicted and what assumptions were made Construct explanations not only for what actually happened but what could have happened as a way of retrieving uncertainties at the time of predictions Evaluate what new was learned about the process producing the event predicted as well as the event itself

26. Early Warning Information Systems - Architecture: How would this have helped in previous decisions EW(I)S Research & Monitoring Management Capacity Coordination Decision Support Tools Services/product Delivery Regional, National, Local Institutions

27. Recognize “communication” as necessary but insufficient Broad societal processes that create dynamic pressures and unsafe conditions are not easy to change, yet are fundamental to human vulnerability Social process(es) of risk communication are more than “one-way” AND more than “two-way” The “push” supply of new information by would-be providers of information/technology , and the “pull” demand for new information from would-be learners is never linear More challenging is an understanding the socialization of lessons learned by particular individuals and organizations through their own, direct trial and error experiences

28. Impediments to the flow of knowledge among existing components • Policies and practices that can give rise to failures of the component parts working as a system • Opportunities for and constraints to learning and institutional innovation Mapping decision making processes and climate information entry points

29. Improving the linkages between information and decision-making-key considerations • What is the quality of information available to decision-makers at all levels? • What factors influence whether or not such information will be used? • What factors influence whether risk communications are trusted? • What governance structures may facilitate better decision-making practice? • How can information systems be adapted to the different levels of decision makers?

30. Thank you

31. Thank You!

32. CRM: Manage the Entire Range of VARIABILITY Probability (Density) Climate related Outcome (e.g., food production)

33. Monthly of Precipitation None of the Years behaves like the long term mean Probability of a Year being “Average” = ZERO Still, Planning is based on “AVERAGE” year Can we use something with Probability > 0 ? Seasonal Climate Forecasts (likelihood of “Drier”, “Wetter”)

34. Climate Information Services GFCS, CMO/CIMH, NMHS, NOAA MONITORING/RESEARCH DEVELOPMENT AND ENGAGEMENT (data analysis, products) PROTOTYPING (applying scenarios etc.) DELIVERY, EVALUATION. Scientific Knowledge development and Management Impacts Assessment and Decision support tools Capacity and Coordination: Products and Services + =

35. Assessing Drought Early Warning Systems –WMO, NIDIS, UNISDR International Drought Information Systems (November, 2011 National Drought Policy 2013)

36. Climate Change Scenarios: Using Climate Models (GCMs) Complex models that simulate physical processes in the atmosphere, oceans and land Key Input: GHG emissions Assumptions on: (e.g., in 2080-2100) Technologies? Energy Sources? Deforestation Rates? UNCERTAINTY (Scenarios IPCC) e.g. communications 1970’s’