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Dinâmica do Clima e Mudanças Climáticas sobre o Nordeste do Brasil Paulo Nobre INPE ANA-CGEE Debate Clima e Água no Nordeste Brasilia, 14 August 2008 Outline of this talk • The mean climate • Mechanisms of climate variability • Seasonal predictability & predictions • Impacts of global climate change • What is next?... Annual Mean Precipitation (mm/day) Base period: 1961-90 Data source: East Anglia C.R.U. NORDESTE CLIMATE REGIMES 200 mm 0 5N 100 mm 0 00 J M M J S N QUIXERAMOBIM 100 mm 300 mm 50S 200 mm J M M J S Q N REMANSO O 100S 100 mm R J M M J S N OLINDA S 150S C 300 mm Feb-Apr May-Jun Nov-Jan 200 mm 200 mm 100 mm 100 mm 200S J J M M J S N M M J S N SALVADOR CAETITE 250S 550W 500W 450W 400W 350W 300W 250W From Kousky et al. (1980) SAMS CLIMATE VARIABILITY & CONVERGENCE ZONES ITCZ SITCZ SA CZ From: Grodsky and Carton (2002) The Equatorial Pacific Influence ENSO Cold ENSO Warm The Tropical Atlantic Influence (A) A 200N WARMER SST ITCZ 00 DRY COOLER SST A 200S SSTA Meridional Gradient (B) A 200N COOLER SST 00 ITCZ WET WARMER SST 200S A 800W 600W 400W 200W 00 200E Adapted from: C. A. Nobre and L. C. B. Molion (1988) Wet /Dry Eastern Nordeste: Wet/Dry ocean -atmosphere characteristics ocean-atmosphere Wet 200N Cooler SST 00 Warmer SST 200S A 200N Dry Warmer SST 00 Cooler SST 200S A 800W 600W 400W 200W 00 200E Adapted from: Rao and Lima (1991) ATLANTIC ITCZ POSITION AND OLR ANOMALY CORRELATION MAM CPTEC AGCM T062L28 ANOMALY CORRELATION TAUY RAINFALL poucas evidências de mudanças na amplitude do fenômeno ENSO nos próximos 100 anos. Porém, há possibilidades de uma intensificação dos extremos de secas e enchentes que ocorrem durante eventos quentes de El Niño. Amazon Deforestation Simulations Precipitation Departures AGCM CGCM Nobre et al. (2008, in prep.) Amazon Deforestation and ENSO variability Nobre et al. (2008, submitted) Global Mean Temperature Change Annual Mean Tmax Vitória de Santo Antão, PE Projeções aumento na temperatura do ar ate 2100 em relação a 1980-99. IPCC WG 1 Chapter 10 Figure 3.2: Examples of current vulnerabilities of freshwater resources and their management; in the background, a water stress map based on the 2005 version of WaterGAP (Alcamo et al., 2003a). Figure 3.4: Ensemble mean change in annual runoff, in percent, by 2050 under the SRES A1B emissions scenario, based on an ensemble of 12 climate models (Milly et al., 2005). change of annual runoff Figure 3.8: Illustrative map of future climate change impacts on freshwater which are a threat to the sustainable development of the affected regions. 1: Bobba et al. (2000), 2: Barnett et al. (2004), 3: Döll and Flörke (2005), 4: Mirza et al. (2003) 5: Lehner et al. (2005a) 6: Kistemann et al. (2002). Background map: Ensemble mean change of annual runoff, in percent, between present (1981-2000) and 2081-2100 for the SRES A1B emissions scenario (Nohara et al., 2006). Impactos Severos nos Recursos Hídricos do Nordeste. Tendência a “aridização” da região semi-árida do Nordeste até final do Século XXI Balanço Hídrico-Nordeste 1961-1990 2071-2100 Maior Déficit Hídrico no Nordeste: Vulnerabilidade na agricultura! Impacts due to altered frequencies and intensities of extreme weather, climate, and sea level events are very likely to change Rainfall anomalies (mm/day) (Annual) [(2071-2100)- (1961-90)] Seco Seco Seco Seco B2 B2 A2 A2 Temperature anomalies (C) Annual [(2071-2100)- (1961-90)] Quente Quente B2 B2 A2 A2 Warm nights index (TN90) [(2071-2100)- (1961-90)] HadRM3 1961-90 2071-2100, B2 2071-2100, A2 OBSV Increase in the frequency of warm nights until 2100 Increase in the frequency of warm nights during 19612000 Intense rainfall index ( R10) [(2071-2100)- (1961-90)] HadRM3 1961-90 2071-2100, B2 2071-2100, A2 OBSV Increase in the frequency of intense rainfall events until 2100 Increase in the frequency of intense rainfall events during 1961-2000 Consecutive dry days index (CDD) [(2071-2100)- (1961-90)] HadRM3 1961-90 2071-2100, B2 2071-2100, A2 OBSV Increase in the frequency of consecutive dry days until 2100 Reduction in the frequency of consecutive dry days during 1961-2000 The aggregated CCI (Climate Change index) on a grid basis for South America, for the 2071-2100 period in relation to 1961-90. (Baettig et al. 2007). Regions more vulnerable to Climate Change The CCI indicates that climate will change most strongly relative to today’s natural variability in the tropics. The high CCI-values in the tropics are caused by precipitation changes but also seasonal temperature events. Concerning strong temperature changes, it has to be noted that in the tropics the hot temperature indicator responds more strongly to absolute changes in mean than elsewhere, because natural temperature variability is much smaller in the tropics than in higher latitudes. According to the CCI, climate is expected to change more strongly relative to today’s natural variability in these more vulnerable countries than in many countries with a high HDI and thus lower vulnerability. Arctic Sea Ice Extent 2007 2005 Cenários IPCC Aquecimento Global Temperatura Média Global A2 Extensão Gelo Marinho Ártico, Cenário A2 CO2 de Origem Fóssil & Intensidade do Uso de Carbono Emissões estão seguindo o cenário de mais altas emissões Raupach et al. (2007) HadCM3 Change in Carbon Content Carbon Cycle Effects on Carbon and Temperature Changes A2: 2-4 C warmer, 15-20% less rainfall. B2: 1-3 C warmer, 10-15 % less rainfall Possible impacts: •High frequency of dry spells and evaporation rates and low soil moisture levels affecting levels of channels and reservoirs. •Losses in natural ecosystems caatinga. •Tendency towards aridization and desertification in the semiarid region. •Water scarsity. •Waves of climate refugees migrating towards large cities agravating social problems. •Impacts on human health Sources: INPE, MMAPROBIO, EMBRAPA, CEPAGRI Summary of climate change scenarios for the end of the XXI Century and possible impacts over Nordeste Brazil CPTEC ’s Climate Forecast CPTEC’s Coupled Suite Goal Coupled Forecast Data Assimilation Health Model AGCM AGCM 6 Regional hourly Model Atmos OBS T-S Hydrology Model Atmos FCST daily/hourly Wave Model SST daily OGCM OGCM IC Crop Model SFC fluxes The REGIS study (an UK experience that can serve as a paradigm for Brazil) UKCIP is involved in developing an innovative methodology for undertaking the type of cross-sectorial research that climate change necessitates. This is being implemented through a major commitment of resources in the REGIS study in North West England and East Anglia. The study aims to improve our understanding of the linkages between water resources, agriculture, biodiversity and coastal/river defence. PIRATA SWE data collection