2. I Latin American and the Caribbean Workshop Assesment for Impacts and Adaptation to Climate Change in Multiple Regions and Sectors (AIACC) 27-30 May 2003 Luis Jose Mata l.mata@uni-bonn.de

3. Introduccion to Extreme Events and Climate Change Ier. Taller Latinoamericano y del Caribe (AIACC) San Jose, Costa Rica, Mayo, 2003

4. Luis J. Mata 1 M.Rusticucci 2, S.Solman 3 J. B. Valdés 4 1 Center for Develompment Research, University of Bonn, Germany, l.mata@uni-bonn.de 2 Departamento de Ciencias de la Atmósfera y los Océanos, Universidad de Buenos Aires, Buenos Aires, Argentina, mati@at.fcen.uba.ar 3 CIMA (Centro de Investigaciones del Mar y la Atmosfera) and Departamento de Ciencias de la Atmósfera y los Océanos, Universidad de Buenos Aires, Buenos Aires, Argentina, solman@at1.fcen.uba.ar 4 Dept. of Civil Engineering and SAHRA (Sustainability for Semi-Arid Hydrology and Riparian Areas) Center, The University of Arizona, Tucson, Arizona, jvaldes@u.arizona.edu ZEF

5. Outline (ideas) 1- Some fundamental from IPCC TAR 2- Climate change is not only about changes in average values —in addition to changes in the mean it is very important to examine trends in extreme events. 3- Theoretical view—linear increase in the mean and variability imply a nonlinear increase of climate extremes 4- This theoretic matter is confronted with some observations 5- Adaptation and needs of good forecasting

6. Some fundamental from IPCC TAR and other sources

7. Estimates of confidence in observed and projected change in some extreme events Change in climate phenomenon Confidence in observed changes (latest half of 20th century) Confidence in projected changes (during 21st century) Higher maximum temperatures and more hot days over nearly all land areas LikelyVery Likely Higher minimum temperatures, fewer cold days and frost days over nearly all land areas Very Likely Reduced diurnal temperature range over most land areas Very Likely More intense precipitation events Likely (northern hemisphere, mid latitude areas) Very Likely Increased droughts and floods associated with El Nino event in many regions Likely Source: IPCC, 2001Very Likely (90-99%chance)Likely (66-90% chance) Estimates of confidence in observed and projected change in some extreme events Change in climate phenomenon Confidence in observed changes (latest half of 20th century) Confidence in projected changes (during 21st century) Higher maximum temperatures and more hot days over nearly all land areas LikelyVery Likely Higher minimum temperatures, fewer cold days and frost days over nearly all land areas Very Likely Reduced diurnal temperature range over most land areas Very Likely More intense precipitation events Likely (northern hemisphere, mid latitude areas) Very Likely Increased droughts and floods associated with El Nino event in many regions Likely Source: IPCC, 2001Very Likely (90-99%chance)Likely (66-90% chance)

8. Examples of ENSO impacts on several Latin American Countries Subregion or CountryImpacted Climatological/Hydrological Variable El NinoLa Nina Argentina (Pampas) Increase in precipitation during November- January Decrease in precipitation during October- December Chile and Central Western Argentina Increase in runoffNegative rainfall anomalies ColombiaDecrease in precipitation, soil moisture and river streamflow Heavier precipitation and floods Northern Amazon and Norheast Brazil Decrease in precipitation during rainy season (severe drought in NE Brazil) Increase in precipitation, higher runoff Source: Mata & Campos, 2001

9. TypeDescription Simple extremes Individual local weather variables exceeding critical level on a continuous scale (e.g.,temperature, precipitation) Complex extremes Severe weather associated with particular climatic phenomena, often requiring a critical combination of variables (e.g., tropical cyclones) Unique or singular phenomena A plausible future climatic state with potentially extreme large-scale or global outcomes (e.g., THC) Source: Chapter 1 IPCC, 2001 Typology of Extreme Events

10. Temperature and Precipitation - The increased in temperature is associated with an stronger warming in daily minimum temperatures than maximum (Easterling et al., 1997) - Global precipitation has also increased since the late 19 th century (IPCC, 2001). - Given these increases, it is expected that there would also be increases in extreme events (Mearns et al., 1984)

11. The planet averaged an even 14.0 C between 1961-90. The average temperature in 2002 was about 14.55 the second warmest year on record Global average mean temperature has increased by 0.6± 0.2 ° C since the late 19 th century

12. Climate change is not only about changes in average values—in addition to changes in the mean it is very important to examine trends in extreme events

13. Trends on annual and seasonal (DJF and JJA) rainfall in Corrientes, Argentina

14. Figure 4. Rainfall occurred in Venezuela on December 1999 caused over 30,000 deaths and great economic losses. Heavy Precipitation and landslides Annual maxima 951mm in 1954 LJM,2002 Source: MARN,2000 cumulative daily Was these extreme? Yes!!!—but not implausible given the historical evidence

15. They claim that the 1999 event has a sizeable probability which implies that such an occurence within a reasonably short time horizon could have been anticipated

16. Was the Venezuelan Central Coast December 1999 an unique event? Source: Coles et al, 2003

17. Some other extreme events (e.g., floods)

19. Water Extremes Bonn Flood (Rhein River) Mozambique Flood

20. Location (Continent) Duration (Days) Affected Region (sq km) Damage (USD per Sq. km) C. Europe (Europe) 18 (August) 252.30079.270 S. Russia (Asia) 12 (June) 224.6001.945 W. Venezuela (South America) 11 (July) 224.90013,34 NW China (Asia) 10 (June) 252.0001.587 Source: Darmouth Flood ObservatoryPhoto: C.Stache/AP DRESDEN Some floods in summer (June-August 2002)

21. An increase in mean and variance imply a nonlinear increase in the probability of extremes Theory

22. Mean T 0 ± 1 SD LJM,2002 Threshold New Mean Probability of high extremes Probability of low extremes

24. Observations

25. Figure 5. Annual precipitation PDF at Corrientes, Argentina Annual rainfall in mm D ensity Mean 1902-1944= 1186.95 mm Mean 1945-1999 =1431.00 mm Source: Olga Penalba, personal comunication 2002 LJM,2003

26. Figure 3. Extreme value distributions of maximum flows on Paraná river at Corrientes (1904-1960 and 1961-1997) Source: Valdés, 2002 personal communication

27. Something about adaptation

28. Adaptation can decrease the probability of extremes Threshold Probability of low extremes Probability of high extremes Coping range animation4

29. Adaptation can decrease the probability of extremes Probability of low extremes Probability of high extremes Threshold Adaptation LJM,2002 animation5

30. Due to a good flood forecasting Photo: L.J.Mata,1998 Anticipatory Adaptation

31. Gracias