1. 7 June 2016Puerto Pérez1 Climate Change: Why Worry? Primer Seminario de Investigación SANREM CRSP: Adaptación al Cambio en los Andes. La Paz, 24-28 Abril, 2006 Anji Seth, University of Connecticut

2. 7 June 2016Puerto Pérez2 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…?  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…?

3. 7 June 2016Puerto Pérez3 How do we know climate is changing?

4. 7 June 2016Puerto Pérez4 Austria

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8. 7 June 2016Puerto Pérez8 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)

9. 7 June 2016Puerto Pérez9 Doesn’t climate change naturally?

10. 7 June 2016Puerto Pérez10 Yes!

11. 7 June 2016Puerto Pérez11 So what’s the deal with global warming?

12. 7 June 2016Puerto Pérez12 Carbon Cycle Basics Natural sources Natural sinks Human sources

13. 7 June 2016Puerto Pérez13 Carbon Cycle Basics CO 2 sources CO 2 sinks atmospheric CO 2

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16. 7 June 2016Puerto Pérez16 Can we wait to see, before taking action? 3 surprises

17. 7 June 2016Puerto Pérez17 Surprise 1: Exponential increase CO 2 sources CO 2 sinks atmospheric CO 2

18. 7 June 2016Puerto Pérez18 350 400 450 500 2006 2050

19. 7 June 2016Puerto Pérez19 Surprise 2: Feedbacks CO 2 sources CO 2 sinks atmospheric CO 2 temperature Feedbacks in the system amplify the temperature response

20. 7 June 2016Puerto Pérez20 Surprise 3: Delayed response CO 2 sources CO 2 sinks atmospheric CO 2 temperature.75 o C in pipeline based on CO 2 now in the atmosphere

21. 7 June 2016Puerto Pérez21 Warmer temperatures would be kind of nice, wouldn’t they?

22. 7 June 2016Puerto Pérez22 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: %).

23. 7 June 2016Puerto Pérez23 Mean Seasonal Cycle

24. 7 June 2016Puerto Pérez24 Mean Seasonal Cycle: 69W, 15S Prec Temp Wet Day Freq Frost Freq

25. 7 June 2016Puerto Pérez25 Mean Seasonal Cycle: 67W, 22S Prec Temp Wet Day Freq Frost Freq

26. 7 June 2016Puerto Pérez26 El Niño, Cold Pacific Events

27. 7 June 2016Puerto Pérez27 Summer Rainfall, Lake Increment Garreaud & Aceituno (1999) CRU gridded Precipitation data (Dec-Feb) Lake level at Puno (Dec-Feb)

28. 7 June 2016Puerto Pérez28 Altiplano Precipitation Variability Garreaud & Aceituno (2001)

29. 7 June 2016Puerto Pérez29 Precipitation Trends in Andes Vuille et al (2003) Station Precipitation data trends Trends by altitude

30. 7 June 2016Puerto Pérez30 Temperature Trends in Andes Vuille et al (2003) Station, gridded Temperature data Variability, trends Model simulated Temperature Variability, trends

31. 7 June 2016Puerto Pérez31 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).

32. 7 June 2016Puerto Pérez32 (Rauscher et al. 2006) Daily Precipitation Frequency N. Amz S. Amz Mon SE NE Observed NN-RegCM EC-RegCM ECHAM Regional model is as good or better that GCM in all but the N. Amazon region where a substantial dry bias is evident

33. 7 June 2016Puerto Pérez33 (Rauscher et al. 2006) Monsoon Rainy Season withdrawal Improved in RegCM3 Monsoon onset And withdrawal dates March Monsoon precipitation correlation with SSTa

34. 7 June 2016Puerto Pérez34 (Rauscher et al. 2006) Northeast Dry Spells Regional model improves the dry spell frequency in Northeast Brazil, especially during El Niño years.

35. 7 June 2016Puerto Pérez35 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.

36. 7 June 2016Puerto Pérez36 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. 1970-2000 Monthly Precipitation

37. 7 June 2016Puerto Pérez37 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.

38. 7 June 2016Puerto Pérez38 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). (2070-2100)-(1970-2000) Monthly Precipitation

39. 7 June 2016Puerto Pérez39 (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).

40. 7 June 2016Puerto Pérez40 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)

41. 7 June 2016Puerto Pérez41 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.