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This chapter summarizes our current knowledge on the mean climatological features ofAmazonia. Significant uncertainties remain in our understanding ofthe complex dynamics of climate and climate variability in that region, which are due, in part, to the lack of observational data. The strong seasonality of the rainfall and the relatively rapid transition between the wet and dry season associated with onset of the rainy season is related to the establishment M the South America Monsoon System (SAMS). The SAMS is controlled by large~scalethermodynamic conditions influenced by the near-equatorial sea surface temperature (SST). It has been suggested that land-surface dryness in the dry season is the main cause of the delay in the onset ofthe subsequent wet season. The 30- to 60-day oscillation is the major mode ofintraseasonal variability. Interannual variability ofthe hydroclimatic system is strongly related to El Niiio-Southern Oscillation. More generally, tropical Pacific and Atlantic SSTs control rainfall variability in Amazonia, and SWAtlantic SST anomalies influence the variability of the South Atlantic Convergence Zone (SACZ). Land surface-atmosphere interactions have been proposed as a possible dynamical mechanism for the unexplained variance at the annual and interannual timescales. At decadal and interdecadal timescales, rainfall variability is related to the Pacific Decadal Oscillation mainly over the southern portions, and linked to the North Atlantic Oscillation. At paleoclimate timescales, there is large uncertainty on major aspects of rainfall variability over tropical South America. For instance, there remains uncertainty on the basic character ofrainfall anomalies over Amazonia, whether drier or wetter, during the Last Glacial Maximum, and paleoclimate reconstructions still suffer from lack of data.

The Amazon plays an important role in the functioning of the Earth’s climate. It acts as one ofthe critical heat sources for the global atmosphere via evaporation of water vapor at the surface and release ofheat in the middle and upper troposphere by latent heat of condensation in tropical convective clouds. Forest evaporation year-round is about 3 to 3.5 mID d-1 . In contrast, for savanna regions bordering the Amazon forest, evaporation is reduced during the dry season because of the limitation of soil moisture. Deforestation causes a large reduction in dry season evaporation. The cloudiness-rainfall regime of the undisturbed forest/is similar to that of a tropical ocean, which led us to call the Amazon Basin a “green ocean.” Biogenic volatile organic compounds are released by the forest into the atmosphere, where some play an important role in providing aerosols and cloudlcondensation nuclei. On the other hand, aerosols emitted by biomass burning may cause reduction of rainfall. Together the chapters in this section reveal a complex mix of interacting processes that acting in concert control the movement and composition of the atmosphere above Amazonia. Each separate study reveals some new insight into one facet, but together they reveal an integrated system in which change in one component will produce impacts in another. The most important message is that deforestation is not just a change in land use, but it impacts the functioning of the Amazonian ecosystem itself. Changes in the evaporation and the chemical composition ofthe atmosphere produce changes in the cloud physics and in the dynamics and thermodynamics of the atmospheric circulation. These, in tum, impact the rainfall and the hydrological cycle.

A bacia Amazônica possui uma gama variada de ecossistemas e grande riqueza de diversidades biológica e étnica. Inclui a maior extensão de foresta tropical da Terra, mais de 5 milhões de km, e responde por aproximadamente um quarto das espécies animais e vegetais do planeta. A precipitação atmosférica anual é de 2.300 mm, em média, e a descarga média do rio Amazonas no oceano Atlântico é de cerca de 220.000 m3/s, o que corresponde a 18% da descarga total de água fresca nos oceanos do mundo.

This chapter contains sections titled: Introduction Warming in Amazonia and observed climate Trens Brief evolution of modeling of climate change in Amazonia: Deforestation and experiments on climate change and Amazonian deforestation Model projections of climate change in the Amazon basin from IPCC AR4 global models Projections of change in hydrology and moisture transport in and out of Amazonia A combination of the increase in greenhouse gas concentrations and land use changes in Amazonia as forcings for climate change Experiences on climate change projections from regional models in Amazonia Uncertainty assessments Dangerous climate change in Amazonia as projected by the UK Met Office Hadley Centre model Effects of aerosols in the projections of future drought events in Amazonia Extreme events in the context of climate change: Is the drought of Amazonia in 2005 an indicator of how extremes will be in a warmer climate? Impacts of changes in climate and hydrology in water resources in Amazonia.

Ecophysiological characteristics of forest and savanna vegetation are compared in an attempt to understand how physiological differences within and between these vegetation types relate to their geographical distributions. A simple ordination first shows that although precipitation exerts a key effect on Amazonian vegetation distributions, soil characteristics are also impmiant. In patiicular, it is found that under similar precipitation regimes, deciduous forests tend to occur on more fertile soils than do cenado vegetation types. A high subsoil clay content is also impmiant in allowing the existence of semievergreen forests at only moderate rainfall. Such observations are consistent with biome specific physiological characteristics. For example, deciduous trees have higher nutrient requirements than do evergreen ones which also tend to have characteristics associated with severe water deficits such as a low specific leaf area. Nutrient contents and photosynthetic rates are lower than for savanna than for forest species with several eco,system characteristics suggesting a primary limitation of nitrogen on savanna productivity. By contrast, phosphorus seems to constrain the productivity of most Amazonian forest types. Differentiation is made between the fast-growing, high-nutrient-requiring forest types of western Amazonia and their counterpatis in eastern Amazonia, which tend to occupy infertile but deeper soils of high water-holding ability. On the basis of observed physiological characteristics of the various vegetation fmills, it is argued that, should Amazonian precipitation decline sharply in the future, the slower growing forests of eastern Amazonia will transform directly into an evergreen cerrado type vegetation but with the more fertile western Amazonian forests being replaced by some form of drought-deciduous vegetation.

The interactions between the Amazonian boundary layer, the surface, atmospheric convection, aerosols, and larger-scale circulations are complex. The field experiments inAmazonia have provided rich insights into the daytime and nighttime boundary layer in different regions and seasons over both forest and pasture and into the coupling between the surface fluxes, the boundary layer, precipitation, and cloud radiative forcing. We discuss the typical diurnal cycle of Amazonian convection, the self-organization into mesoscale systems in different synoptic regimes, and the role offorest and river breeze circulations. We review the coupling between aerosols, smoke, and convection in the dry season; ozone transpOlis by deep convection; and microphysical and electrical impacts on convection.

Desvendando Questões Ambientais com Isótopos Estáveis oferece a universitários, professores e público geral uma visão interessante e reveladora sobre o papel que os isótopos estáveis desempenham em vários campos do conhecimento. Essa é a primeira publicação brasileira sobre o tema; apresenta a metodologia do uso dos isótopos estáveis dos elementos mais comumente utilizados, como: carbono, nitrogênio, oxigênio e hidrogênio, e seus vastos campos de aplicação. Uma potente ferramenta investigativa. Pesquisas em solos, atmosfera, vegetação e nutrição animal são beneficiadas por esta ferramenta, e outras são de interesse amplo da população, como a adulteração de bebidas e alimentos ou a descoberta de que se plantava milho na Amazônia pré-histórica. A grande maioria dos exemplos que permeiam os capítulos deste livro resulta de estudos conduzidos pelo grupo realizados no Brasil. Os autores pertencem a cinco gerações de engenheiros agrônomos pesquisadores do Centro de Energia Nuclear na Agricultura (Cena), órgão de integração da Universidade de São Paulo (USP).

Neste trabalho são avaliadas as tendências dos extremos de temperatura e precipitação nas regiões metropolitanas do Rio de Janeiro (RMRJ) e São Paulo (RMSP) no final do século XXI. Para isso foram utilizadas as simulações de dois modelos regionais climáticos usados no projeto CREAS: RegCM3 e HadRM3P. As simulações foram realizadas para o período de 1961-1990 e para 2071-2100, no cenário futuro A2 de emissão de gases de efeito estufa do IPCC. Os modelos regionais indicam para a região de estudo um aumento da temperatura média anual que pode chegar a 2-3 ºC segundo o modelo RegCM3 e 3-4 ºC segundo o HadRM3P. Os índices extremos de precipitação para a RMRJ indicam um aumento no número de dias secos consecutivos e uma redução no número de dias no ano com precipitação acima de 10 mm. Para essa mesma região, os modelos prevêem um aumento no máximo anual de precipitação acumulada em cinco dias consecutivos e que poderia ocasionar enchentes. As tendências nos índices extremos de temperatura, tanto para RMRJ quanto RMSP, indicam um aumento no número de dias e noites quentes e uma diminuição em dias e noites frias. Esses resultados são consistentes com um clima mais seco que o atual, com altas temperaturas diurnas e noturnas e com chuvas intensas concentradas em períodos curtos.

Several studies have been devoted to dynamic and statistical downscaling for both climate variability and climate change. This paper introduces an application of temporal neural networks for downscaling global climate model output and autocorrelation functions. This method is proposed for downscaling daily precipitation time series for a region in the Amazon Basin. The downscaling models were developed and validated using IPCC AR4 model output and observed daily precipitation. In this paper five AOGCMs for the twentieth century (20C3M) (1970-1999) and three SRES scenarios (A2, A1B, and B1) were used. The performance in downscaling of the temporal neural network was compared to that of an autocorrelation statistical downscaling model with emphasis on its ability to reproduce the observed climate variability and tendency for the period 1970-1999. The model test results indicate that the neural network model significantly outperforms the statistical models for the downscaling of daily precipitation variability.