Publicações

High-speed video records of two bipolar cloud-to-ground flashes were analyzed in detail. They both began with a single positive return stroke that was followed by more than one subsequent weak negative stroke. Due to the elevated cloud base height of its parent thunderstorm, the preparatory processes of each subsequent negative stroke were documented optically below cloud base. In the first event (Case 1) it was observed that all four subsequent negative strokes were initiated by recoil leaders that retraced one horizontal channel segment previously ionized by the positive leader. Those recoil leaders connected to the original vertical channel segment and propagated toward ground, producing four subsequent strokes that had the same ground contact point as the original positive discharge. The second event (Case 2), in contrast, presented 15 subsequent strokes that were initiated by recoil leaders that did not reach the original channel of the positive stroke. They diverged vertically toward ground, making contact approximately 11 km away from the original positive strike point. These results constitute the first optical evidence that both single- and multiple-channel bipolar flashes occur as a consequence of recoil leader activity in the branches of the initial positive return stroke. For both events their total channel length increased continuously at a rate of the order of 104 m s-1, comparable to speeds reported for typical positive leaders. Key Points Inception of subsequent strokes of natural bipolar cloud-to-ground flashes First report of inception mechanism of negative phase of bipolar CG flashes High-speed camera and multiple LLS study of bipolar CG flashes.

Operational records of power outages of the electric energy distribution systems in eastern Amazonia presented a large number of events attributed to lightning strikes, during the 2006 to 2009 period. The regional electricity concessionary data were compared to actual lightning observations made by SIPAMs LDN system, over two areas where operational sub systems of transmission lines are installed. Statistical relations were drawn between the monthly lightning occurrence density and the number of power outages of the electric systems for both areas studied. The results showed that, although with some delays between these variables peaks, the number of power disruptions has a tendency to follow the behavior of the lightning occurrence densities variations. The numerical correlations were positive and may be useful to the transmission lines maintenance crews at least for the Belém-Castanhal electricity distribution sub system. Evidence was found, that the SSTs over certain areas of the Pacific and Atlantic Oceans, influence convection over the area of interest, and may help to prognosticate the periods of intense electric storms, requiring repair readiness for the regional electric systems.

O Índice de Precipitação Normalizada (SPI) é utilizado para quantificar o déficit e/ou excesso de precipitação nas múltiplas escalas de tempo. Ele tem se mostrado bastante útil no monitoramento da precipitação, principalmente pela sua flexibilidade, simplicidade de cálculo e interpretação. Desta forma este estudo tem como objetivo quantificar os eventos extremos secos e chuvosos na cidade de Belém-PA nas escalas de tempo de 3, 6 e 12 meses por meio do SPI. Para isto, utilizaram-se dados mensais de precipitação provenientes da estação meteorológicas de superfície do INMET no período de 1980-2011. Os resultados mostraram que a escala de tempo do SPI é inversamente proporcional à frequência dos eventos de chuva e seca. Os SPIs 3, 6 e 12 mostraram mais eventos secos do que chuvosos para a cidade e a maioria dos eventos de chuva e seca estavam associados, principalmente, ao fenômeno ENOS. ABSTRACT: The Standardized Precipitation Index (SPI) is used to quantify the deficit/ excess rainfall at multiple time scales. It has been very useful in monitoring of precipitation, mainly because of its flexibility, ease of calculation and interpretation. Thus this study aims to quantify the extreme wet and dry events in the city of Belém-PA in time scales of 3, 6 and 12 months by SPI. For this, we used monthly precipitation data from meteorological station at the INMET in the period 1980-2011. The results show that the timescale of the SPI is inversely proportional to the frequency of rain and dry events. The SPIs 3.6 and 12 showed driest events that rainy events to the city and most of the rainfall and drought events were associated, mainly, with the ENSO phenomenon.

O método da Análise Fatorial em Componentes Principais e dos Agrupamentos Hierárquicos foram utilizados para determinar os padrões principais de variabilidade temporal e espacial, assim como identificação dos grupos homogêneos, da precipitação no Estado do Pará. Para isso utilizaram-se dados mensais de 72 postos pluviométricos distribuídos no Estado do Pará. As três primeiras Componentes Principais explicaram 92,91% da variância total dos dados mensais de precipitação. O Primeiro padrão espacial definiu áreas de chuva que são influenciadas pela atuação da Zona de Convergência Intertropical (ZCIT). O segundo padrão espacial está associado a sistemas transientes ou até mesmo da Zona de Convergência do Atlântico Sul que favorecem as chuvas na região no final da primavera e no início do verão austral. Já o terceiro padrão espacial evidencia a influência da atuação da ZCIT, das linhas de instabilidade e da convecção local. Identificaram-se e caracterizaram-se três regiões homogêneas (RH-1, RH-2 e RH-3) em relação à variabilidade sazonal de precipitação no Estado do Pará. A RH-1 ocupa as porções noroeste-nordeste do Estado com maior volume pluviométrico, a RH-2 está situada na região central do Pará e a RH-3 localizada no sudoeste-sudeste do Estado com menor índice pluviométrico.

Today, the volume of data generated in almost all disciplines, particularly in meteorology and climate science, is dramatically increasing. Among the challenges generated by this data deluge is the development of efficient knowledge discovery strategies. Here, we show that statistical and computational tools used to analyze large data sets of genome-wide studies can be fruitfully applied to a climatic context. Although not as powerful as some techniques already in use by climatologists, these tools are simple and robust, and can easily be adapted to detect early warning signals for extreme events like droughts or be used to filter large data sets before applying other more advanced and computationally expensive methods. We test this approach in our investigation of the causes of the Amazon droughts of 2005 and 2010. Our results highlight the major role played in these extreme events by the warming of the seas surface temperature, mainly in the tropical North Atlantic. Our findings are in agreement with several analyses published in the literature. The main message we convey is that free and open-source data mining and visualization techniques routinely used in genetic studies can be useful in helping scientists to extract knowledge from large climatic data sets, particularly in regions of the world that are vulnerable to climate change but where the availability of technical expertise is critically scarce.

Numerical studies on impacts of landscape fragmentation due to land use and land cover change (LUCC) on precipitation fields over the Ji-Paraná basin in the Amazon region are carried out using atmospheric Eta model. Experiments consider historical data about LUCC over the basin from 1978 to 2000 and compare simulations under LUCC conditions with simulations under pristine conditions. In agreement with previous observational studies, model results do not show statistically significant impacts on precipitation in the region. Results indicate that variability in precipitation in this region is mainly controlled by large-scale atmospheric characteristics and soil moisture conditions. However, some limitations are identified in the model simulations, mainly associated to the diurnal cycle of precipitation.

Observational data obtained at two wind towers located at the Alagoas State (Northeast of Brazil – NEB) were used to evaluate the influence of horizontal grid setup on the reliability of wind estimates provided by the numerical weather prediction model BRAMS. Statistical analysis were performed to evaluate the model skill in reproducing the temporal evolution, frequency distribution and the mean daily cycle of the wind observations in both locations. The study was performed for the two typical climate seasons: the rainy (May/2008) and the dry one (November/2008). The results demonstrated that the deviations of wind estimates gets lower if the horizontal grid resolution is increased from 8 km to 2 km. No results improvement occurred when using horizontal grid resolution higher than 2 km. The confiability on wind speed estimates were higher at Girau do Ponciano (GRP), located in the continental area where the sea breeze is less important to the atmospheric dynamic. The results demonstrate that wind data observations play an important role in defining the best configuration and parameterization model to better estimates the availability of wind energy on a specific region, particularly for NEB.

In this report monthly thunderstorm days (TD) in 14 large cities of Brazil from 1951 to 2010 are compared with data obtained in the first part of the 20th century in the same cities and correlated with sea surface temperature (SST) of the equatorial Pacific Ocean and Tropical Atlantic Ocean. On average over all cities, 77 TD are reported each year after 1951, against 43 TD in the first part of the 20th century, an increase of 79%. The increase seems to be related to increase in the urbanization in these cities, and not to global warming. A comparative analysis of TD for the whole country with El NiñoSouthern Oscillation (ENSO) events suggests that the tendency for El Niño to increase the thunderstorm activity is evident in the South (only in the Spring/Summer), Southeast, Northeast and North (only in the Fall/Winter) regions. Regarding the Tropical Atlantic Ocean SST, a similar analysis using the Tropical South Atlantic (TSA) and Tropical North Atlantic (TNA) indices suggests that no significant differences exist between the thunderstorm activity for the two extreme positive and negative TSA conditions in the South and Southeast regions, while in the Northeast and North regions there is a significant increase in the thunderstorm activity during extreme positive TSA. Differently, only in the Northeast region there is a significant influence of TNA on thunderstorm activity. The influence is such that the thunderstorm activity is larger for the extreme negative TNA than for extreme positive TNA. All significant changes were quantified and significant variations were observed. For all parameters investigated (ENSO, TSA and TNA) the Northeast region showed the most significant changes.

The performance of seven regional climate models in simulating the radiation and heat fluxes at the surface over South America (SA) is evaluated. Sources of uncertainty and errors are identified. All simulations have been performed in the context of the CLARIS-LPB Project for the period 1990-2008 and are compared with the GEWEX-SRB, CRU, and GLDAS2 dataset and NCEP-NOAA reanalysis. Results showed that most of the models overestimate the net surface short-wave radiation over tropical SA and La Plata Basin and underestimate it over oceanic regions. Errors in the short-wave radiation are mainly associated with uncertainties in the representation of surface albedo and cloud fraction. For the net surface long-wave radiation, model biases are diverse. However, the ensemble mean showed a good agreement with the GEWEX-SRB dataset due to the compensation of individual model biases. Errors in the net surface long-wave radiation can be explained, in a large proportion, by errors in cloud fraction. For some particular models, errors in temperature also contribute to errors in the net long-wave radiation. Analysis of the annual cycle of each component of the energy budget indicates that the RCMs reproduce generally well the main characteristics of the short- and long-wave radiations in terms of timing and amplitude. However, a large spread among models over tropical SA is apparent. The annual cycle of the sensible heat flux showed a strong overestimation in comparison with the reanalysis and GLDAS2 dataset. For the latent heat flux, strong differences between the reanalysis and GLDAS2 are calculated particularly over tropical SA.

Much research has been devoted to understanding the complexity of biogeochemical and physical processes responsible for the greenhouse gas (GHG) emissions from hydropower reservoirs. Spatial complexity and heterogeneity of GHG emission may be observed in these systems because it is dependent on flooded biomass, river inflow, primary production and dam operation. In this study, we investigate the relationships between waterair CO2 fluxes and phytoplanktonic biomass in Funil Reservoir, an old and stratified tropical reservoir, where intense phytoplankton blooms and low partial pressure of CO2 (pCO2) are observed. Our results showed that Funil Reservoir sea sonal and spatial variability of chlorophyll concentration (Chl) and pCO2 is more related to changes in river inflow over the year than environmental factor such as air temperature and solar radiation. Field data and hydrodynamic simulations reveal that the river inflow contributes to increased heterogeneity in dry season due to the variation of reservoir retention time and river temperature. Contradictory conclusion can be drawn if temporal data collected only near the dam is considered instead of spatial data to represent CO2 fluxes in whole reservoir. The average CO2 fluxes was −17.6 and 22.1 mmolm−2 d−2 considering data collected near the dam and spatial data, respectively, in periods of low retention time. In this case, the lack of spatial information can change completely the role of Funil Reservoir regarding GHG emissions. Our results support the idea that Funil Reservoir is a dynamic system where the hydrodynamics represented by changes in river inflow and retention time is potentially more important force driving both Chl and pCO2 spatial variability than in-system ecological factors.

Strategies for mitigating global climate change require accurate estimates of the emissions of greenhouse gases (GHGs). A strong consensus in the global scientific community states that efforts to control climate change require stabilization of the atmospheric concentration of GHGs (as per a recent compilation; (IPCC 2013)). Estimates of the amounts of carbon dioxide and other GHGs emitted to the atmosphere, as well as the amounts absorbed by terrestrial and aquatic systems, are crucial for planning, analyzing, validating and at global scale verifying mitigation efforts and for analyzing scenarios of future emissions. The magnitude and distribution of current emissions and the path of future emissions are both of considerable importance. It is critical that we have estimates of emissions and that we acknowledge and deal with the uncertainty in our best estimates. The range of issues that derive from uncertainty in emissions estimates was the subject of the 3rd International Uncertainty Workshop held in Lviv, Ukraine, 2010, and is the subject of this special issue.

We investigated spatial-temporal variability and long-term trends of rainfall over the Metropolitan Area of São Paulo (MASP). Due to a lack of continuous and consistent rainfall observations in the MASP, a database for the spatial analysis was created from a composite of 94 stations, with daily rainfall data for 1973-1997, plus data from the University of São Paulo’s Institute of Geophysics and Astronomy (IAG/USP) station for 1933-2011, as the base of the long-term variability analysis. It is shown that the seasonal and interannual rainfall variability result from underlying local influences and remote large-scale atmospheric dynamics. These effects appear to be more complex during the austral spring and fall seasons, and seem to determine the duration of the rainy period over the MASP. The intraseasonal (30-60 d) oscillation of rainfall does not exhibit any long-term modulation; interannual rainfall variability for 1975-1990 appears modulated by the El Niño-Southern Oscillation (ENSO) scale (2-8 yr). Nonetheless, there exists statistical evidence that the rainfall climate over the MASP had an abrupt change at the end of the 1950s, but the global climatic change that occurred in the middle of the 1970s is not evident. The progressive increase in the frequency of rainy days and total daily rainfall throughout the period of analysis are prominent factors in the trend of annual and seasonal rainfall. Furthermore, rainfall variability over the MASP may be modulated by the Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and ENSO at seasonal scales, altering the normal progression of the seasonal rainfall cycle, while at interannual scales, each one of these patterns drives the rainfall variability, mainly when each pattern reaches its extreme value.