1. The Role of Tropical Forests in the Regional and Global Hydroclimate Roni Avissar W.H. Gardner Professor and Chair Department of Civil & Environmental Engineering Duke University and R. Ramos da Silva, D. Werth, S. Badya Roy Duke University May 10, 2005

2. 8 9 10 11 12 13 65 64 63 62 61 60 65 60 8 13 9.5 10.5 63 62 Our overall objective is to understand the impact of land-cover change on the local, regional, and global hydroclimate. Porto Velho Cuiaba

3. 8 9 10 11 12 13 65 64 63 62 61 60 65 60 8 13 9.5 10.5 63 62 Porto Velho Cuiaba

5. Low Pressure High Pressure Low Density

6. Low Pressure High Pressure

7. Low Pressure

9. w (m/s) at 3 p.m., 500 m Clouds at 3 p.m. (from GOES)

11. We use the data collected during the joint “Wet Atmospheric Mesoscale Campaign – TRMM validation (WetAMC – TRMM),” in January – February 1999. 65 64 63 62 61 60 8 9 10 11 12 13

12. 8 9 10 11 12 13 65 64 63 62 61 60

13. RAMS (400 m)S-POL (4 km) Average Precipitation Rate (mm/hr)

14. a & e – February 4, 1999 b & f – February 6, 1999 c & g – February 14, 1999 d & h – February 23, 1999 S-POL RH testSoil Moisture testGrid Size testControl

15. 36% increase in the daily mean accumulation! Current deforestation pattern 10.76 mm (daily mean accumulation) No deforestation 7.94 mm (daily mean accumulation)

20. Soares Filho & Nepstad 2004

21. Forest Cerrado 2001 2050 2030 Amazon Basin Landscape Scenarios Final

22. A typical Global Climate Model (GCM) grid

23. 36% increase in the daily mean accumulation! Current deforestation pattern 10.76 mm (daily mean accumulation) No deforestation 7.94 mm (daily mean accumulation) Current deforestation pattern 6.75 mm (daily mean accumulation) A Global Climate Model (GCM) assumes flat terrain and homogeneous land cover With the GCM, 15% decrease in the daily mean accumulation!

24. RAMS OBSERVATIONS

26. 199819992000 Total – C 2051 - C 2031 – C

29. Five ensembles of six, 12-year realizations were performed with the NASA-GISS GCM (with imposed monthly mean sea- surface temperatures): 1.Control – land-cover in early 70’s, before intensive deforestation started (Matthews, 1983); 2.Amazonian deforestation; 3.Central African deforestation; 4.South-Eastern Asian deforestation; 5.All three tropical regions deforested simultaneously (i.e., “total” deforestation). Control case is compared to Cases (2) – (5). Each grid point is tested for monthly, ensemble mean, statistically significant difference in precipitation.

30. Amazonia vs Control PRECIPITATION [mm/day]

31. Africa vs Control PRECIPITATION [mm/day]

32. S.E. Asia vs Control

33. Total vs Control

36. The Luni-Solar Oscillation (LSO) affects tides, which affect SSTs and, as a result, the amount of water evaporated from the ocean that is then advected into the basin, where it precipitates.

37. The atmospheric boundary layer is significantly affected by landscape structure. Frequently, landscape heterogeneity created by land use generates horizontal pressure gradients strong enough to create and sustain organized mesoscale circulations, which can trigger thunderstorm activity. In tropical regions, this happens in all seasons; l Tropical deforestation significantly affects the regional hydroclimatology of these regions and, to a lesser but still quite significant degree, the mid-latitude hydroclimatology (e.g., the US Midwest and the Arabian Peninsula). Among tropical regions, the Amazon Basin seems to have the largest impact, probably due to the fact that its dry season lasts longer and is dryer than in Central Africa and South- East Asia; l Simultaneous deforestation of Amazonia, Central Africa and South-East Asia has a cumulative impact in a few regions (notably, in the Arabian Peninsula) and synergistic impact in others (including in the US by shifting the main impact to California); l Convective activity is one of the key factors that triggers teleconnections between tropical regions and higher latitudes but our GCMs do not account for (mesoscale) landscape-generated convection. Clearly, this limits our capability to estimate the real magnitude of teleconnections between tropical rainforests and the rest of the world; l Inter-decadal variability is associated with the LSO, which is a deterministic, very predictable signal. Thus, it improves the predictability of the Amazonian hydroclimate system and it should be included in new earth system models. Conclusions