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It is well known that land use and land-cover changes (LUCC), particularly deforestation, have the potential to modify the hydrological response. Although those signals are relatively well documented in worldwide microcatchment studies, conflicting results reported in literature indicate that those signals can be sometimes difficult to detect and isolate in basins at larger scales. In order to detect signals in the hydrological response potentially, related to LUCC, streamflow records from Ji-Paran´a Basin located in SW Amazonia are analysed in conjunction with deforestation maps derived from remote sensors. The basin has a drainage area greater than 30 000 km2 and has been through severe LUCC in the last decades. Statistical descriptors of daily streamflow series were correlated with landscape indices using non-parametric methodologies. To take into account scale effects, statistical analyses were repeated in different sub-basins. Results showed that the impact of LUCC on the hydrological response is time lagged at larger scales. The flow paths are clearly affected, depending on basin characteristics such as topography. In general, LUCC impacts lead to higher peak streamflows, the reduction of minimal values and the increment of stormflow. In agreement with previous studies, the detection of signals associated with LUCC was clearly detected at the smallest basin, but proved to be difficult at larger scales, suggesting the existence of non-linear effects, which aggregate across scale compensating small scale effects. Such behaviour indicates a challenge for mathematical models, which are usually developed to represent immediate hydrological response to basin wide LUCC.

A new version of ETA WS (workstation) forecast model destined for long-term climate change simulation (ETA CCS) was designed. Numerous modifications and corrections have been made in the original code of the ETA WS forecast model. As a first step in the ETA CCS validation program, we have integrated the model over South America with a horizontal resolution of 40 km for the period 1960-1990. We forced it at its lateral boundaries by the outputs of HadAM3P, which provides a simulation of modern climate with a resolution of about 150 km. The climate ETA model was run on the supercomputer SX-6. Here, we present and compare the output fields of the ETA model and HadAM3P and analyze the geopotential, temperature, and wind fields of both models. For evaluating the similarities of the model outputs, we used a Fourier analysis of time series, the consistency index from linear regression coefficients, the time mean and space mean models’ arithmetic difference and root mean square difference. The results of the study demonstrate that there are no significant differences in behavior and spatial arrangement of large-scale structures of the two models. In addition, the regional model characteristics do not have major positive or negative trends during the integration in relation to the global model. Our analysis shows that the descriptions of large-scale climate structures by these two models are consistent. This means that the ETA CCS model can be used for downscaling HadAM3P output fields. Our proposed technique can be used to evaluate the consistency of any regional model and its driving global model.

This study shows the results from a regional climate simulation of the present-day climate, corresponding to the period 1961-1970 over South America, using the regional Eta Model nested within the HadAM3P model from the UK Hadley Centre. The simulation analysis is focused on assessing the capability of the nested regional model in representing spatial patterns of seasonal mean climate and the annual cycle of precipitation and temperature. The goals of this 10-year run for South America are to verify if the Eta Model can be used in climate-change scenarios and to verify if this model has the ability to generate added value for the South American continent. The Eta Model was chosen because there are few investigations using the Eta Model for long integrations over South America and because the vertical coordinate system used in this model is recommended for use over South America due to the presence of the Andes range. In the present 10-year simulation, the regional model reproduced many of the South American mesoscale climate features and together added new value to the driver model. Value was also added to the driver model by reducing seasonal biases in austral winter relative to austral summer. The regional model also exhibits better performance in the representation of low-level circulation, such as the topographically induced northwesterly flux.

A melhor ferramenta para projetar cenários prováveis de alterações climáticas para o futuro são os modelos matemáticos do sistema climático global (MCG), que levam em conta de forma quantitativa (numérica) o comportamento dos compartimentos climáticos (atmosfera, oceanos, criosfera (áreas com gelo e neve), vegetação, ciclos biogeoquímicos, etc.) e de suas interações. Esses modelos permitem que se simulem prováveis cenários de evolução do clima para vários cenários de emissões dos Gases de Efeito Estufa (GEE). Porém, há duas grandes fontes de incertezas ao utilizar estes modelos. A primeira, é que não sabemos precisamente a trajetória futura das emissões dos GEE e de aerossóis atmosféricos, que depende de decisões humanas sobre o caminho socioeconômico-ambiental desejado e que venha a ser efetivamente implementado. A segunda fonte de incerteza advém do fato que os modelos matemáticos são representações imperfeitas da natureza e diferentes modelos climáticos diferem substancialmente em suas projeções para o clima do futuro, dado o mesmo cenário de evolução das concentrações de GEE e de aerossóis na atmosfera. A maneira de abordar essas duas incertezas é utilizar vários cenários de emissões de GEE e diferentes modelos climáticos.

Earth system science addresses natural and human-driven processes affecting the evolution and ultimately the habitability of the planet. We must recognize that the Earth system encompasses interactions among the atmosphere, ocean, ice, land, biochemistry, and humanity. Humanity has advertent- ly and inadvertently perturbed the entire system, with both positive and negative consequences. Thus, the accelerated development of a monitoring and predic- tion system that integrates physical, biogeochemical, and societal processes is essential if we are to provide quantitative information that can initiate and guide the mitigation of, and adaptation to, future changes in the Earth system. This paper illustrates the crucial role of the biosphere in a complex, integrated Earth system prediction framework. As noted in Shapiro et al. (2010), effectively predicting the evolution of the full Earth system in a way that embraces the next frontier of so- cioeconomic and environmental applications demands international commitment and coordination.

A climatology of extratropical cyclones is presented. Extratropical cyclones, their main characteristics and their predominant tracks, as well as their interannual variability affect weather in South America. For that purpose, a storm-track database has been compiled by applying a cyclone tracking scherme to 6-hourly sea level pressure fields, available from National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis II, for the 1979-2003 period. The spatial distribution of the cyclogenesis frequency shows two main centres, one around northern Argentina, Uruguay and Southern Brazil in all seasons, and the other near to the North Antartic Peninsula. The lifetime of extratropical cyclones in the South American sector exhibits small seasonality, being typically of the order of 3.0 days during most of the year, and slighty higher (3.5 days) in austral summer. The distance travelled by the cyclones formed in the South American sector tends to be smaller than the total paths found in other areas of Southern Hemisphere. A K-mean clustering techniques is used to summarize the analysis of the 25-yr climatology of cyclones tracks. Three clusters werw found; one storm-track cluster in northeast Argentina; a second one west of the Andes Cordillera, and a third cluster located to the north of Antartica Peninsula (around Weddell Sea). The influence of the AAO in the variability of extratropical cyclones is explored, and some signals of the impacts of the variability of the AAO can be observed in the position of the extratropical cyclones around 40ºS, while the impacts on the intensity is detected around 55ºS.

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.

We propose to compare avoided emissions from ethanol use in Brazil with emissions caused by the use of fossil fuel, and by land use changes, specifically Amazon deforestation. The avoided emissions of CO2 in Brazil due to ethanol use in 2008 ranged from approximately 9 to 12 TgCyr1. These values are an order of magnitude higher than the amount of carbon that could be potentially sequestered in soils if sugarcane cultivation in Brazil switches completely to mechanized harvesting, and two orders of magnitude higher than the carbon emissions in soils cultivated with sugarcane and that undergo harvest with burning. In relation to fossil fuel emissions, ethanol avoided emissions are equivalent to 2030% of the carbon emissions associated with the use of gasoline and diesel in the transportation sector, and to approximately 10% of the total use of fossil fuel in the country. When compared with the carbon emissions from Amazon deforestation ethanol avoided emissions are again one order of magnitude lower. We conclude that ethanol avoided emissions are relatively important within the transport sector, but are still incipient if compared with the emissions from total fossil fuel combustion and emissions from deforestation indicating that climate mitigation efforts in Brazil needs to focus outside of biofuel production. Consequently, we suggest that Brazil develop equally strong actions towards increased energy efficiency use in the country and, more importantly to drastically reduce carbon emissions associated with Amazon deforestation.

A carga do nitrogênio em rios é cada vez mais controlada por atividades humanas independentemente da escala espacial, do clima, ou da região geográfica. Consequentemente, esforços de modelagem que predizem exportação de nitrogênio usam atributos que refletem atividades humanas, tais quais, densidade populacional, uso do solo, urbanização e saneamento ambiental. Estes modelos têm aumentado significativamente nosso entendimento sobre as fontes e destino do nitrogênio adicionado ao sistema terrestre e transportado aos sistemas aquáticos, especialmente em países desenvolvidos localizados no Hemisfério Norte. Entretanto, a maioria da população mundial vive em países em desenvolvimento dos trópicos, onde os efeitos das atividades humanas sobre a carga de nitrogênio nos rios são pobremente entendidos. Em um esforço para aumentar nossa compreensão sobre este fenômeno, comparamos a distribuição de nitrogênio dissolvido em 32 rios brasileiros, drenando duas regiões contrastantes em termos de desenvolvimento econômico rios do Estado de São Paulo e da região Amazônica. Nossos dados incluem nitrogênio em duas formas dissolvidas: inorgânica (NID) e orgânica (NOD). Os resultados mostraram que, em ambas as áreas de estudo, a concentração de nitrogênio decresceu com o volume de água dos rios e as concentrações mais elevadas foram encontradas na região economicamente mais desenvolvida. A correlação entre as concentrações e fluxos de nitrogênio com parâmetros demográficos tais quais densidade de população demonstraram que o fluxo de nitrogênio aumenta somente após a densidade populacional atingir 10 indivíduos por km2.

For a better comprehension of the atmospheric chemical and radiative properties, it is necessary to understand the behaviour of trace gases and aerosols; some of these gas types have not been deeply studied. Sulphur dioxide (SO2) is found in the troposphere, as a result of both natural and anthropogenic emissions. To study the behaviour of this gas in the Antarctic continent, the data collected by the Brewer Spectrophotometer installed in the Brazilian Antarctic Station Comandante Ferraz (62° 05 S and 58° 24 W) was used. With this ground-based instrument, the total column of SO2 was measured from the beginning of springtime, to the start of summer, during the years 2003 to 2009. It was possible to observe that the total columns of SO2 did not show any di erences in the time of the development of the ozone hole, as compared to other periods. e main sources of anthropogenic SO2 pollution in this region are the generation of energy, the operations with ships, and the burning of garbage, being a punctual impact. e natural generation of SO2 in this region is mainly related to the conversion of DMS (dimethyl sul de) emitted by the ocean. In a few days, the SO2 total column exceeded the values considered normal for remote regions (>2UD), and these high concentrations must have their sources identi ed and monitored.

Projections of changes in climate extremes are critical to assessing the potential impacts of climate change on human and natural systems. Therefore, especial care should be put on the validation of those extremes derived for present climate in both spatial and temporal variability. We analyze historical simulations of three such indicators as derived from seven GCMs contributing to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4) for the XX century. Our focus is on the consensus in the geographical and temporal variability of temperature and rainfall extreme trends between observations and the GCMs, in terms of direction and significance of the changes at the scale of South America south of 10 oS. The climate extremes described by the 3 indices include warm nights, heavy rainfall amounts and dry spells. The observed historical trends in extremes generally agree with previous observational studies that used other indicators of extremes, and the favorable comparison in the warm nights and extreme rainfall in some regions provides a basic sense of reliability for the GCM simulations. For any specific temperature index, minor differences appear in the spatial distribution of the changes across models in some regions, while substantial differences appear in regions in interior tropical and subtropical South America. The differences are in the relative magnitude of the trends. Consensus and significance are less strong when regional patterns are considered, with the exception of the La Plata Basin, where observed and simulated trends in warm nights and extreme rainfall are evident. This analysis provides a first overview of simulated trends in extremes for present climates, and further work is focused on projected changes in climate extremes from the IPCC-AR4 models.