Publicações

A confiabilidade da estimativa e da variabilidade do vento num local ou região de interesse é essencial, principalmente para empreendimentos de energia eólica. Atualmente o mapeamento de áreas com elevado potencial para a exploração comercial pode ser realizado com o uso de modelos atmosféricos que demandam um investimento relativamente baixo. Porém para realizar as simulações com modelos atmosféricos de mesoescala são necessários determinar os domínios (grades) do modelo que podem variar de alguns poucos km a dezenas de km. Com o objetivo de auxiliar na determinação destes domínios será utilizada a técnica de análise de agrupamento (Cluster Analysis) nas séries de dados observados nas estações meteorológicas automáticas do Instituto Nacional de Meteorologia (INMET) para o nordeste do Brasil. Esta classificação consiste em determinar o nível de similaridade ou dissimilaridade entre indivíduos aplicando uma função de agrupamento a uma determinada variável. Está análise tem como principal objetivo determinar regiões com padrões de intensidade do vento semelhante dentro do domínio do estudo, e assim facilitar a localização das grades nas simulações dos modelos, evitando grades que possuam pontos com diferentes padrões de vento. Foram utilizados dados horários de velocidade do vento a 10 m de altura de 121 estações meteorológicas automáticas, no período de janeiro de 2005 a dezembro de 2013. Os resultados obtidos confirmaram que há regiões com diferentes padrões de vento no nordeste, que necessitam configurações de grade distintas e parametrizações físicas adequadas aos fenômenos meteorológicos observados em cada região.

This study evaluates the use of tiles to estimate the effects of surface heterogeneities in simulations of local climate in a landscape-fragmented region of Amazonia. Three experiments using the Eta/Noah-MP model were designed as follows: two experiments with a spatial resolution of 5 km with and without the use of the tile approach. The third experiment used a finer spatial resolution of 2 km without the use of the tile approach (high-resolution experiment). Simulations were carried out for the rainy and dry seasons, which correspond to the months of March and September 2003, respectively. In general, the magnitude of surface fluxes is significantly affected by the introduction of tiles. In the dry season, the use of tiles in the simulation increases the magnitude of precipitation (about 7 mm day−1), skin temperature (about 4 °C), sensible heat flux (about 80 W m−2) and surface albedo (about 0.7). It reduces the latent heat flux (about 30 W m−2) and net radiation (about 40 W m−2). On the other hand, in the rainy season, the model produces excessive precipitation. This may have partly masked the signs of the land fragmentation impact. The tile experiment generates a warmer and drier boundary layer during the dry season. The impact of the surface heterogeneity representation is higher in the dry season than in the rainy season. The results suggest that the degree of impact of the subgrid process representation on the local climate is related to the spatial scale of the fragmentation. The use of the tile approach improves the representation of the effects of landscape heterogeneity on the spatial distribution of surface flux variability in fragmented areas. Comparison against measured data from flux towers in the region show that the model can simulate diurnal and seasonal variations in the local fluxes, despite the biases.

This work studied the behavior and seasonality of evapotranspiration influenced by biotic and abiotic factors through analysis of diurnal variation of aerodynamic resistance (ra), stomatal resistance (rs) and decoupling factor (Ω). This index was proposed by Jarvis and McNaughton (1986) as an indicative of the control of these resistances on the evapotranspiration of vegetation. Selection of representative data from wet and dry seasons from a primary forest in Central Amazonia and a primary forest and a pasture sites in Southwestern Amazonia had shown that: (i) ra is about 20 s.m-1 in both forests in both seasons, and ranges from 70 to 100 s.m-1 in the pasture site; (ii) rs varies both throughout the day and seasonally, with medians increasing from 40 in the morning, to 150 s.m-1 in late afternoon, in the wet season in the forests and from 50 to 160 s.m-1 in the pasture. These values increase in the dry season, with the forests rs ranging from 50 up to 500 s.m-1 and pasture rs starting from 140 s.m-1 and reaching up to more than 1800 s.m-1 in the dry afternoons; (iii) Ω ranges from 0.5 to 0.8 during the wet season, and reduces to values below 0.5 in the afternoons during the dry season, indicating that, although a strong influence of net radiation in the evaporative loss is present, to a large extent the evapotranspiration fluxes are coupled to the biotic control of stomatal closure in the vegetation, especially in the pasture and during dry periods.

Wetlands are the largest global source of atmospheric methane (CH4) 1 , a potent greenhouse gas. However, methane emission inventories from the Amazon floodplain2,3 , the largest natural geographic source of CH4 in the tropics, consistently underestimate the atmospheric burden of CH4 determined via remote sensing and inversion modelling4,5 , pointing to a major gap in our understanding of the contribution of these ecosystems to CH4 emissions. Here we report CH4 fluxes from the stems of 2,357 individual Amazonian floodplain trees from 13 locations across the central Amazon basin. We find that escape of soil gas through wetland trees is the dominant source of regional CH4 emissions. Methane fluxes from Amazon tree stems were up to 200 times larger than emissions reported for temperate wet forests6 and tropical peat swamp forests7 , representing the largest non-ebullitive wetland fluxes observed. Emissions from trees had an average stable carbon isotope value (δ13C) of −66.2±6.4 per mil, consistent with a soil biogenic origin. We estimate that floodplain trees emit 15.1±1.8 to 21.2±2.5 teragrams of CH4 a year, in addition to the 20.5 ± 5.3 teragrams a year emitted regionally from other sources. Furthermore, we provide a topdown regional estimate of CH4 emissions of 42.7±5.6 teragrams of CH4 a year for the Amazon basin, based on regular vertical lowertroposphere CH4 profiles covering the period 20102013. We find close agreement between our top-down and combined bottom-up estimates, indicating that large CH4 emissions from trees adapted to permanent or seasonal inundation can account for the emission source that is required to close the Amazon CH4 budget. Our findings demonstrate the importance of tree stem surfaces in mediating approximately half of all wetland CH4 emissions in the Amazon floodplain, a region that represents up to one-third of the global wetland CH4 source when trees are combined with other emission sources.

Visando a previsão hidrológica de eventos extremos, serão apresentados neste trabalho resultados obtidos com a aplicação do modelo hidrológico distribuído MHD-INPE para eventos extremos ocorridos em São Luís do Paraitinga, SP. As previsões meteorológicas foram obtidas através do modelo atmosférico Eta-INPE, considerando altas resoluções espaciais (1 e 5 km). Os resultados indicam que a maior resolução das previsões meteorológicas resultam em precipitações mais intensas. Consequentemente, o modelo hidrológico tende a prever maiores níveis para o rio. Esse comportamento aumenta a assertividade de eventos acima do limiar de alerta, sendo assim, adequado para a previsão de eventos extremos, visto que tais eventos normalmente são consequentes de chuvas intensas e localizadas.

Natural disasters and finding suitable areas to dispose of municipal solid waste (MSW) are two major global challenges, both of which have several influences in the water resources and are related to climatic change, especially in developing countries like Brazil. Currently the risk of natural disasters is not utilized in the process of locating areas to dispose of MSW. This study, using geographic information system (GIS), analyzed spatially the susceptibility for landslide and flooding hazards in MSW disposal sites in São Paulo state, Brazil. The results showed that more than 90% of sanitary and ditch landfills are located in null, very low and low hazard classes (P0, P1 and P2). However, in this remaining 10% of landfills we still have approximately 55% of the total municipal solid waste disposed into susceptible areas with middle, high and very high hazard classes (P3, P4 and P5). This shows that São Paulo MSW disposal sites need more attention and control to prevent the occurrence of landslide/flooding and consequently the mitigation of environmental, economic and social impacts. In addition, the use of GIS is proved to be an appropriate tool to carry out this type of analysis, so we recommend that the risk of natural disasters should be taken into consideration in the process of finding landfill areas. Mainly, because, there is a tendency for extreme weather events to increase causing more flood and landslide events and consequently contributing to water scarcity and water degradation.

The large excess of solid waste generated in cities is a result of population growth and economic development. Properly managing this municipal solid waste (MSW) is a challenge, mainly in underdeveloped and developing countries where financial concerns are an added problem. From the environmental point of view, a major issue is properly disposing MSW taking into consideration a wide range of factors, and working with different spatial data. In this study, we used geographic information system (GIS) to perform multi-criteria decision analysis (MCDA) conducted by analytical hierarchy process (AHP). The development of the environmental impact susceptibility model (EISM) for municipal solid waste disposal sites (MSWDS) applied to the state of São Paulo, Brazil considered factors such as geology, pedology, geomorphology, water resources, and climate represented by fifteen associated sub-factors. The results indicated that more than 82% of São Paulos territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 18% of the state land area, 85 landfills are located in areas with high and very high environmental impact susceptibility categories. These results are alarming because these 85 landfills receive approximately 17,886 tons of MSW on a daily basis, which corresponds to 46% of all municipal solid waste disposed in São Paulo state. Therefore, decision makers, urban planners and policymakers could use the findings of the EISM towards mitigating the environmental impacts caused by MSWDS.

In this study the climatology of ionospheric scintillations and the zonal drift velocities of scintillationproducing irregularities are depicted for a station located under the southern crest of the equatorial ionization anomaly. Then, the α−µ ionospheric fading model is used for the firstand second-order statistical characterization of amplitude scintillations. In the statistical analyzes, data are used from single-frequency GPS receivers acquired during ∼ 17 years (September 1997November 2014) at Cachoeira Paulista (22.4◦ S; 45.0◦ W), Brazil. The results reveal that the nocturnal occurrence of scintillations follows the seasonal distribution of plasma bubble irregularities observed in the longitudinal sector of eastern South America. In addition to the solar cycle dependence, the results suggest that the occurrence climatology of scintillations is also modulated by the secular variation in the dip latitude of Cachoeira Paulista, since the maximum occurrence of scintillations during the peak of solar cycle 24 was ∼ 20 % lower than that observed during the maximum of solar cycle 23. The dynamics of the irregularities throughout a solar cycle, as investigated from the estimates of the mean zonal drift velocities, presented a good correlation with the EUV and F10.7 cm solar fluxes. Meanwhile, the seasonal behavior showed that the magnitude of the zonal drift velocities is larger during the December solstice months than during the equinoxes. In terms of modeling, the results for the α − µ distribution fit quite well with the experimental data and with the temporal characteristics of fading events independently of the solar activity level.

Every year, a dense smoke haze covers a large portion of South America originating from fires in the Amazon Basin and central parts of Brazil during the dry biomass burning season between August and October. Over a large portion of South America, the average aerosol optical depth at 550 nm exceeds 1.0 during the fire season, while the background value during the rainy season is below 0.2. Biomass burning aerosol particles increase scattering and absorption of the incident solar radiation. The regional-scale aerosol layer reduces the amount of solar energy reaching the surface, cools the near-surface air, and increases the diffuse radiation fraction over a large disturbed area of the Amazon rainforest. These factors affect the energy and CO2 fluxes at the surface. In this work, we applied a fully integrated atmospheric model to assess the impact of biomass burning aerosols in CO2 fluxes in the Amazon region during 2010. We address the effects of the attenuation of global solar radiation and the enhancement of the diffuse solar radiation flux inside the vegetation canopy. Our results indicate that biomass burning aerosols led to increases of about 27% in the gross primary productivity of Amazonia and 10% in plant respiration as well as a decline in soil respiration of 3 %. Consequently, in our model Amazonia became a net carbon sink; net ecosystem exchange during September 2010 dropped from C101 to 104 TgC when the aerosol effects are considered, mainly due to the aerosol diffuse radiation effect. For the forest biome, our results point to a dominance of the diffuse radiation effect on CO2 fluxes, reaching a balance of 50-50% between the diffuse and direct aerosol effects for high aerosol loads. For C3 grasses and savanna (cerrado), as expected, the contribution of the diffuse radiation effect is much lower, tending to zero with the increase in aerosol load. Taking all biomes together, our model shows the Amazon during the dry season, in the presence of high biomass burning aerosol loads, changing from being a source to being a sink of CO2 to the atmosphere.