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Interações entre Clima e Vegetação na Amazônia: do último período glacial até o clima do futuro Carlos A. Nobre CPTEC/INPE III CONFERÊNCIA CIENTÍFICA DO.

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Apresentação em tema: "Interações entre Clima e Vegetação na Amazônia: do último período glacial até o clima do futuro Carlos A. Nobre CPTEC/INPE III CONFERÊNCIA CIENTÍFICA DO."— Transcrição da apresentação:

1 Interações entre Clima e Vegetação na Amazônia: do último período glacial até o clima do futuro Carlos A. Nobre CPTEC/INPE III CONFERÊNCIA CIENTÍFICA DO LBA Brasília, Julho 2004 Interações entre Clima e Vegetação na Amazônia: do último período glacial até o clima do futuro Carlos A. Nobre CPTEC/INPE III CONFERÊNCIA CIENTÍFICA DO LBA Brasília, Julho 2004

2 Vegetation-Climate Interactions Climate Vegetation Bidirectional on various times scales

3 Atlantic rainforest

4 Map of dry season length (DSL) (data after Sombroek, 2001), expressed as the number of months with <100 mm of rain. Steege et al., Biodiversity and Conservation 12 (in press), © 2003 Kluwer Academic Publishers

5 Sternberg, 2001, Global Ecology & Biogeography, 10, 369–378 Vegetation = f (climate) Climate = f (vegetation) Savanna Forest Simple Model of Biome (Savanna and Tropical Forest)-Climate Equilibrium States

6 Annual precipitation Mean climatic equator Arid Savanna Rainforest Savanna Arid Growing season Growing season length in months Mean annual precipitation in mm South Equator North Latitude A scheme of the relationship between mean annual precipitation and growing season length in tropical climates (from Newman, 1977) Tmean > 24 C 13 C < Tcoldest month < 18 C P (3 driest months) < 50 mm P (6 wettest months) > 600 mm 1000 mm < Pannual < 1500 mm Climatic Conditions for Savannas (Nix (1983)

7 Nobre et al. 1991, J. Climate Modeling Deforestation and Biogeography in Amazonia Current Biomes Post-deforestation 1 Tropical Forest 6 Savanna

8 Geografia Ecologia Modelagem de Distribuição Geográfica de Biomas Área de Ocorrência Algoritmo Variável Ambiental A Variável ambiental B Modelo de Biomas Previsão da Distribuição

9 Five climate parameters drive the potential vegetation model Oyama and Nobre, 2002 Monthly values of precipitation and temperature Water Balance Model Potential Vegetation Model SSiB Biomes

10 Visual Comparison of CPTEC-PBM versus Natural Vegetation Map CPTEC-PBM SiB Biome Classification Oyama and Nobre, % agreement on a global 2 deg x 2 deg grid

11 Visual Comparison of CPTEC-PBM versus Natural Vegetation Map SiB Biome Classification NATURAL VEGETATION POTENTIAL VEGETATION Oyama and Nobre, 2002

12 Searching for Multiple Biome-Climate Equilibria

13 Vegetation = f 1 (climate variables) = f 1 (g 0, g 5, Tc, h, s) g 0 = degree-days above 0 C g 5 = degree-days above 5 C Tc = mean temperature of the coldest month h = aridity index s = sesonality index f 1 is a highly nonlinear function Climate = f 2 (vegetation) = f 2 (AGCM coupled to vegetated land surface scheme) f 2 is also a nonlinear function

14 IC: All land points covered by desert IC: All land points covered by tropical forest I T E R A T I O N S

15 Results of CPTEC-DBM for two different Initial Conditons: all land areas covered by desert (a) and forest (b) Oyama, 2002 Biome-climate equilibrium solution with IC as forest (a) is similar to current natural vegetation (c); when the IC is desert (b), the final equilibrium solution is different for Tropical South America a b c Initial Conditions

16 Oyama and Nobre, 2003 Two Biome-Climate Equilibrium States found for South America! Soil Moisture Rainfall anomalies -- current state (a) -- second state (b)

17 Unconditional probability of a wet day. a) Threshold of 1 mm, b) Weak rainfall (rainy days: 1 mm - 5 mm) and, c) Moderate rainfall (rainy days: 5 mm - 25 mm). The daily data spans 1979 to P > 1 mm1 mm < P < 5 mm 5 mm < P < 25 mm Obregon 2001 Unconditional Probability of a Wet Day

18 Obregon mm < P < 5 mm SACZ Sea Breezes Instability lines Annual Precipitation

19 Sensitivity Analysis to Savannization of Amazonia Resolution: ~ 2ºx2º Control2033All Savanna 2033All Savanna JJA5,4%-21,7% JJAS1,9%-21,9% Dry Season Precipitation* * 12°S-3°N / 50°W-75°W Oliveira et al., 2004

20 Paleovegetation Reconstructions as Validation for the Second Stable Equilibrium?

21 Application of CPTEC-PBM for Past Climate Changes Oyama, 2002 (a)PBM results with uniform cooling of 6 C and drying of 3 mm/day to emulate climate conditions of the LGM (21 ka BP); (b) vegetation reconstruction for LGM; a b

22 Last glacial maximum: GENESIS+IBIS The importance of vegetation feedbacks Reference: Foley, J. A.; Levis, S.; Costa, M. H., Cramer, W.; Pollard, D. 2000: Incorporating dynamic vegetation cover within global climate models. Ecological Applications, v. 10, n. 6, p R = radiation of 21 ka BP, fixed modern vegetation, [CO2] = 180 ppmv RPV = radiation of 21 ka BP + dynamic vegetation + physiology at [CO2] = 180 ppmv Decrease of Amazonia Rainfall!

23 Results for Amazonia

24 What are the likely biome changes in Tropical South America due to Global Warming?

25 Change in Amazon Climate and Hydrology in HadCM3LC Lat: 15 o S - 0 o N Lon: 70 o W - 50 o W Amazon forest die-back! Cox et al., 2000

26 Change in Amazon Carbon Balance in HadCM3LC Lat: 15 o S - 0 o N Lon: 70 o W - 50 o W Amazon forest die-back! Cox et al., 2000

27 Change in Global Climate in HadCM3LC Interactive CO 2 and Dynamic Vegetation 2090s s Cox et al., 2000

28 Geografia Ecologia Análise de Redistribuição de Biomas em face a Mudanças Climáticas Área de Ocorrência Algoritmo Precipitação Temperatura Modelo de Biomas Previsão da Distribuição Projeção de Biomas com Mudança Climática Projeção considerando alterações climáticas

29 A2 High GHG Emissions ScenarioB2 Low GHG Emissions Scenario Temperature Anomalies (deg C) for Nobre et al., 2004

30 A2 High GHG Emissions ScenarioB2 Low GHG Emissions Scenario Precipitation Anomalies (mm/day) for Nobre et al., 2004

31 Projected Biome Distributions for South America for Natural Vegetation A2 High GHG Emissions ScenarioB2 Low GHG Emissions Scenario Nobre et al., 2004

32 Conclusions The future of biome distribution in Amazonia in face of land cover and climate changes Natural ecosystems in Amazonia have been under increasing land use change pressure. Large-scale land cover changes could cause warming and a reduction of rainfall by themselves in Amazonia. The synergistic combination of regional climate changes caused by global warming and land cover change over the next several decades could tip the biome-climate state to a new stable equilibrium with savannization of parts of Amazonia (and desertification of parts of Northeast Brazil).

33 Possible stability landscape for Tropical South America. Valleys (X1, X2 and Y) and hills correspond to stable and unstable equilibrium states, respectively. Arrows represent climate state (depicted as a black circle) perturbations. State X1 refers to present-day stable equilibrium. For small (large) excursions from X1, state X2 (Y) can be found. It is suggested that the new alternative stable equilibrium state found in this work corresponds to X2. Notice that it is necessary to reach X2 before reaching state Y. Resilience Stochastic Perturbations Gradual Perturbations affect Resilience (e.g., deforestation, fragmentation, etc.)

34 Biome-Climate Bi-Stability for the Sahel Current State Second State SCHEFFER EL AL., NATURE | VOL 413 | 11 OCTOBER 2001 The second equilibriun state depend mostly on vegetation (albedo) feedback and secondarily on ocean feedbacks

35 P r : rain P s : snow T: sfc air temperature T s : soil temperature S: soil water storage N: overland snow storage E: evapotranspiration R: runoff M: snowmelt P r : rain P s : snow T: sfc air temperature T s : soil temperature S: soil water storage N: overland snow storage E: evapotranspiration R: runoff M: snowmelt Simple Land Surface Model Oyama and Nobre, 2002


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