Climate Change: Why Worry?

1. Climate Change: Why Worry? Anji Seth, University of Connecticut Primer Seminario de Investigación SANREM CRSP: Adaptación al Cambio en los Andes. La Paz, 24-28 Abril, 2006 Puerto Pérez

2. F.A.Q. • How do we know climate is changing? • Doesn’t climate change naturally? • So what’s the deal with Global Warming? • Can’t we wait to see what happens? • Warmer temperatures would be kind of nice…? Puerto Pérez

3. How do we know climate is changing? Puerto Pérez

4. Austria Puerto Pérez

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8. FIGURE [reprinted from Mann et al, 2003, Eos, (C) American Geophysical Union]. Comparison of proxy-based Northern Hemisphere (NH) temperature reconstructions (Jones et al., 1998; Mann et al., 1999; Crowley and Lowery, 2000) Puerto Pérez

9. Doesn’t climate change naturally? Puerto Pérez

10. Yes! Puerto Pérez

11. So what’s the deal with global warming? Puerto Pérez

12. Carbon Cycle Basics Natural sources Natural sinks Human sources Puerto Pérez

13. Carbon Cycle Basics CO2 sources atmospheric CO2 CO2 sinks Puerto Pérez

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16. Can we wait to see, before taking action? 3 surprises Puerto Pérez

17. Surprise 1: Exponential increase CO2 sources atmospheric CO2 CO2 sinks Puerto Pérez

18. 2050 500 450 400 2006 350 Puerto Pérez

19. Surprise 2: Feedbacks CO2 sources Feedbacks in the system amplify the temperature response atmospheric CO2 temperature CO2 sinks Puerto Pérez

20. Surprise 3: Delayed response CO2 sources .75oC in pipeline based on CO2 now in the atmosphere atmospheric CO2 temperature CO2 sinks Puerto Pérez

21. Warmer temperatures would be kind of nice, wouldn’t they? Puerto Pérez

22. Figure 9.5: (a) The time evolution of the globally averaged temperature change relative to the years (1961 to 1990) of the DDC simulations (IS92a). G: greenhouse gas only (top), GS: greenhouse gas and sulphate aerosols (bottom). The observed temperature change (Jones, 1994) is indicated by the black line. (Unit: °C). (b) The time evolution of the globally averaged precipitation change relative to the years (1961 to 1990) of the DDC simulations. GHG: greenhouse gas only (top), GS: greenhouse gas and sulphate aerosols (bottom). (Unit: %). Puerto Pérez

23. Mean Seasonal Cycle Puerto Pérez

24. Mean Seasonal Cycle: 69W, 15S Temp Prec Frost Freq Wet Day Freq Puerto Pérez

25. Mean Seasonal Cycle: 67W, 22S Temp Prec Frost Freq Wet Day Freq Puerto Pérez

26. El Niño, Cold Pacific Events Puerto Pérez

27. Summer Rainfall, Lake Increment Garreaud & Aceituno (1999) CRU gridded Precipitation data (Dec-Feb) Lake level at Puno (Dec-Feb) Puerto Pérez

28. Altiplano Precipitation Variability Garreaud & Aceituno (2001) Puerto Pérez

29. Precipitation Trends in Andes Vuille et al (2003) Station Precipitation data trends Trends by altitude Puerto Pérez

30. Temperature Trends in Andes Vuille et al (2003) Station, gridded Temperature data Variability, trends Model simulated Temperature Variability, trends Puerto Pérez

31. Does RegCM3 add value when downscaling ECHAM4.5 for South America? (Sub-seasonal statistics) Sara Rauscher (ICTP, Trieste) Anji Seth (U Connecticut, Storrs) Brant Liebmann (NOAA/CDC, Boulder) Suzana Camargo & Joshua Qian (IRI, NY) . Puerto Pérez

32. Daily Precipitation Frequency N. Amz S. Amz Mon SE NE Regional model is as good or better that GCM in all but the N. Amazon region where a substantial dry bias is evident Observed NN-RegCM EC-RegCM ECHAM (Rauscher et al. 2006) Puerto Pérez

33. Monsoon Rainy Season withdrawal Improved in RegCM3 March Monsoon precipitation correlation with SSTa Monsoon onset And withdrawal dates (Rauscher et al. 2006) Puerto Pérez

34. Northeast Dry Spells Regional model improves the dry spell frequency in Northeast Brazil, especially during El Niño years. (Rauscher et al. 2006) Puerto Pérez

35. South American Monsoon Precipitation and Moisture Flux in the SRES A2 Scenario Maisa Rojas (U Chile, Santiago) Anji Seth (U Connecticut, Storrs) Sara Rauscher (ICTP, Trieste) Acknowledgement: IPCC AR4 Modeling Groups and WG I for coordinating, archiving and making accessible the model integrations. Puerto Pérez

36. 1970-2000 Monthly Precipitation Monsoon: models capture the annual cycle. Amazon: models simulate spurious semi-annual cycle, and delay/underestimate observed late summer (JFM) maximum. Southeast: models underestimate summer rains (NDJF), reduce the amplitude of the annual cycle. Puerto Pérez

37. 1970-2000 Monthly Moisture Flux Div. (Vertically Integrated) Amazon: simulated semi- annual cycle in moisture flux divergence compared with annual cycle in reanalysis. Monsoon: moisture flux convergence increases during onset of rains (SON) and levels off until end of rains (Mar). Models capture this. Southeast: convergence is strong in summer (DJF) and weaker rest of year. Only 2 of 6 models simulate this. Puerto Pérez

38. (2070-2100)-(1970-2000) Monthly Precipitation Monsoon: Little agreement among models during rainy season (NDJFM). Drier early rainy season (SON), wetter late rainy season (JFM)? Amazon: Little agreement among models during onset of rains (SON). Most models suggest increased precipitation during middle/late rainy season (DJFM). Southeast: General model agreement towards increased precipitation, especially in spring (OND). Puerto Pérez

39. (2070-2100)-(1970-2000) Mon. Moist. Flx. Divg. (Vertically Integrated) Amazon: model agreement increased convergence during middle/end of rainy season (DJFM). Monsoon: Increased divergence in early rainy season (SON) and some agreement for increased convergence during the middle/end of rainy season (JFM). Southeast: model agreement in enhanced moisture flux convergence, especially in spring (OND). Puerto Pérez

40. Summary: South American Monsoon, SRES A2 • Amazon: • Models simulate semi-annual, low amplitude, delayed rains. • There is little model agreement in precipitation change during rainy season onset (SON), due to delayed onset in simulations? • 5 of 6 models suggest increased precipitation during the • middle/late rainy season (DJFM) which is primary season in models. • Monsoon: • The annual cycle is well simulated. • There is little model agreement in precipitation change during the rainy season (Dec-Feb). • Possible shift in the timing of the rainy season (?), with drier conditions early and wetter conditions later, is consistent with projected changes in moisture flux convergence. • Southeast: • Models underestimate summer precipitation (NDJF). • Models show general agreement towards increased precipitation, especially in spring (OND). • Consistent with observed trend (Liebmann et al, JCL, 2004) Puerto Pérez

41. Discussion: Wetter spring in Southeast & drier spring in Monsoon? Although the results in the Monsoon region are more uncertain than those in the Southeast, there is some suggestion in the models towards drier early season and wetter late season in the monsoon region. The projected increase in precipitation in the Southeast is supported by model agreement and observed recent trends (Liebmann et al, JCL 2004). The difference between Monsoon and Southeast regions in spring could imply a southward shift in the SACZ during early season (OND) (see Nogues-Paegle and Mo, JCL, 1997), and is perhaps related to strengthening of the Atlantic subtropical high. We do see a strengthening of the high in the model runs (not shown), which would have implications for moisture transport flux convergence into the Southeast. Moisture flux convergence changes seen here are consistent with this hypothesis. Puerto Pérez