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Simon J. Mason simon@iri.columbia International Research Institute for Climate and Society

Enhancing linkages between climate service providers and users to facilitate climate adaptation and climate risk management. Simon J. Mason simon@iri.columbia.edu International Research Institute for Climate and Society The Earth Institute of Columbia University

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Simon J. Mason simon@iri.columbia International Research Institute for Climate and Society

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  1. Enhancing linkages between climate service providers and users to facilitate climate adaptation and climate risk management Simon J. Mason simon@iri.columbia.edu International Research Institute for Climate and Society The Earth Institute of Columbia University Technical Conference on Changing Climate and Demands for Climate Services for Sustainable Development Antalya, Turkey, 16 – 18 February, 2010

  2. Introduction Promoting the realization of genuine benefit from the application of seasonal climate information requires understanding and addressing the reasons why climate information is currently under-utilized. Addressing only some of those reasons may leave serious bottlenecks.

  3. Uncertain Climate Information • 2.5° 2.5° resolution. • 45% probability of FMA seasonal rainfall total being within the driest third of years from 1971 – 2000. • What is difficult to understand? • terciles? • probabilities? • Will there be flooding in Mbabane over the next few months?

  4. Uncertain Climate Information For the next 3 months, collect all the rainfall over the whole of Swaziland, and Maputo Province (Mozambique), and about 25% of Mpumalanga Province (South Africa); the amount of rainfall we think you will get in 2009 will make it amongst the 10 driest years we measured between 1971 and 2000 (but …

  5. Uncertain Climate Information … the probability is only 45%, so we’re more likely to be wrong than right, and … even if we are right there may be floods because it may rain heavily but not frequently (and there may not be floods even if we’re wrong), and … we might be wrong about the 45%). Consider yourselves forewarned.

  6. Is 50 mm over 6 days a lot of rain? Unclear Weather Information Will there be flooding in Mbabane in the next few days?

  7. Team A scores 320 for 7 in 50 overs in a one-day international. Would you bet on them winning the match?

  8. Lost in translation: forecasts made by forecasters for forecasters. Service provision of forecast is not same as need for information on impacts. Difficult to make decisions even when forecast is clear. Probabilities are not the problem; the forecast is just not relevant. Don’t dumb-down the forecast; forecast something interesting. Making sense of climate information

  9. Climate Information • Climate information is like a hospital gown: one size fits nobody. • Forecasts need to be tailored.

  10. Tailoring requires partnerships • Tailoring requires climate service.

  11. IRI – IFRC Map Room: http://iridl.ldeo.columbia.edu/maproom/.IFRC/.Forecasts/

  12. IRI – IFRC Help Desk What is happening to El Niño? Why should I worry about El Niño? Why should I worry about this El Niño? What should I do about it?

  13. Some users have a good idea of what climate information they need. Some of their questions may be unanswerable. How can we use existing climate information to try to answer these questions? How can we improve existing information to try to answer these questions? Some users do not know what information they need, or even whether they need any information … … and they do not have any of their own impact data to make demonstrating a climate impact very feasible. Making sense of climate information

  14. Temporal information useful for developing seasonal disease calendars for control planning purposes Climate and endemic malaria Unfortunately epidemiological data is very poor in sub-Saharan Africa. In the absence of epidemiological data climate data can be used to help model and map the distribution of disease. Climate suitability for endemic malaria = 18-32ºC + 80mm + RH>60%

  15. Climate and epidemic malaria For epidemics we are less interested in the ‘normal’ – more interested in the ‘abnormal’ ….

  16. 30 year drought >? Impact of climate trends West Africa provides one of the most dramatic examples worldwide of climate variability that has been directly and quantitatively measured [Hulme, 2001].  Changes in malaria < endemicity (Faye et al 1995) > epidemicity (Mouchet et al 1996) Changes in meningitis > epidemic frequency southward extension of ‘Meningitis Belt’ (Molesworth et al 2003) !! Very important consideration when establishing baselines !!

  17. Demands for evidence-based health policy Before using climate information in routine decision making health policy advisors need: • Evidence of the impact of climate variability on their specific outcome of interest, and • Evidence that using climate information is a cost-effective means to improving health outcomes, and • Evidence that the information can be practically useful within their decision frameworks.

  18. Establishing evidence base Malaria incidence inBotswana is strongly related to rainfall variability during the peak rainfall season December – February. NB. Preparation of malaria data.

  19. Demonstrating predictability Forecast (rainfall) DJF Rainfall Composites Observation (rainfall) High Malaria years 88, 89, 93, 96, 97, Low Malaria years 82, 83, 87, 92, 02,

  20. Integrated early warning systems Integrated MEWS gathering cumulative evidence for early and focused epidemic preparedness and response (WHO 2004)…. Flag 1 – Flag 2 – Flag 3

  21. RBM: Southern African Regional MEWS activities Evidence for practical application within a decision making framework (DaSilva, et al. MJ 2004). Evidence for using environmental monitoring (Thomson, et al. AJTMH 2005) Evidence for using seasonal forecasting (Thomson, et al. Nature 2006). Evidence of timing/effectiveness (Worrall, et al. TMIH 2007; Worrall, et al. 2008)

  22. Establish Multi-Agency Climate-Health Working Group - E t h i o p i a - - K e n y a - - M a d a g a s c a r -

  23. Train community of practice… • N e w Y o r k – • - E t h i o p i a - • - K e n y a - • - M a d a g a s c a r -

  24. … and keep them networked … Climate Information for Public Health Action!

  25. …and innovate….. Technology available – but what about the underlying data? NASA-SERVIR (Africa) Google Earth WHO-OpenHealth Cell phone technology (e.g. iPhone and Android)

  26. Conclusions Climate information should attempt to answer questions that users ask, not that climatologists ask. The ability to tailor forecast information to answer users’ questions as closely as possible, provides the basis of any climate service, not the data per se. BUT promoting the capabilities of climate service providers alone will have minimal impact on the application of climate information – the reduction in vulnerability to climate change and variability will be minimal.

  27. Recommendation Any program to promote the development of climate services should be conducted in direct collaboration with programs to promote the demand for such services. For example, WMO capacity building programs (e.g. through CLIPS) should be partnered with WHO programs so that partnerships are developed. Look for opportunities to engage climatologists in user practices rather than trying to engage users into our own agendas.

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