Modelagem estocástica do índice de radiação ultravioleta na costa leste do nordeste do Brasil

The increase in ultraviolet radiation (UV) at surface, the high incidence of non-melanoma skin cancer (NMSC) in coast of Northeast of Brazil (NEB) and reduction of total ozone were the motivation for the present study. The overall objective was to identify and understand the variability of UV or Index Ultraviolet Radiation (UV Index) in the capitals of the east coast of the NEB and adjust stochastic models to time series of UV index aiming make predictions (interpolations) and forecasts / projections (extrapolations) followed by trend analysis. The methodology consisted of applying multivariate analysis (principal component analysis and cluster analysis), Predictive Mean Matching method for filling gaps in the data, autoregressive distributed lag (ADL) and Mann-Kendal. The modeling via the ADL consisted of parameter estimation, diagnostics, residuals analysis and evaluation of the quality of the predictions and forecasts via mean squared error and Pearson correlation coefficient. The research results indicated that the annual variability of UV in the capital of Rio Grande do Norte (Natal) has a feature in the months of September and October that consisting of a stabilization / reduction of UV index because of the greater annual concentration total ozone. The increased amount of aerosol during this period contributes in lesser intensity for this event. The increased amount of aerosol during this period contributes in lesser intensity for this event. The application of cluster analysis on the east coast of the NEB showed that this event also occurs in the capitals of Paraiba (João Pessoa) and Pernambuco (Recife). Extreme events of UV in NEB were analyzed from the city of Natal and were associated with absence of cloud cover and levels below the annual average of total ozone and did not occurring in the entire region because of the uneven spatial distribution of these variables. The ADL (4, 1) model, adjusted with data of the UV index and total ozone to period 2001-2012 made a the projection / extrapolation for the next 30 years (2013-2043) indicating in end of that period an increase to the UV index of one unit (approximately), case total ozone maintain the downward trend observed in study period

Análise da precipitação no semi-árido potiguar

The semiarid rainfall regime is northeastern Brazil is highly variable. Climate processes associated with rainfall are complex and their effects may represent extreme situations of drought or floods, which can have adverse effects on society and the environment. The regional economy has a significant agricultural component, which is strongly influenced by weather conditions. Maximum precipitation analysis is traditionally performed using the intensity-duration-frequency (IDF) probabilistic approach. Results from such analysis are typically used in engineering projects involving hydraulic structures such as drainage network systems and road structures. On the other hand, precipitation data analysis may require the adoption of some kind of event identification criteria. The minimum inter-event duration (IMEE) is one of the most used criteria. This study aims to analyze the effect of the IMEE on the obtained rain event properties. For this purpose, a nine-year precipitation time series (2002- 2011) was used. This data was obtained from an automatic raingauge station, installed in an environmentally protected area, Ecological Seridó Station. The results showed that adopted IMEE values has an important effect on the number of events, duration, event height, mean rainfall rate and mean inter-event duration. Furthermore, a higher occurrence of extreme events was observed for small IMEE values. Most events showed average rainfall intensity higher than 2 mm.h-1 regardless of IMEE. The storm coefficient of advance was, in most cases, within the first quartile of the event, regardless of the IMEE value. Time series analysis using partial time series made it possible to adjust the IDF equations to local characteristics

Caracterização estatística de processos sísmicos via Distribuição Generalizada de Pareto. Estudo de caso: João Câmara-RN

The work is to make a brief discussion of methods to estimate the parameters of the Generalized Pareto distribution (GPD). Being addressed the following techniques: Moments (moments), Maximum Likelihood (MLE), Biased Probability Weighted Moments (PWMB), Unbiased Probability Weighted Moments (PWMU), Mean Power Density Divergence (MDPD), Median (MED), Pickands (PICKANDS), Maximum Penalized Likelihood (MPLE), Maximum Goodness-of-fit (MGF) and the Maximum Entropy (POME) technique, the focus of this manuscript. By way of illustration adjustments were made for the Generalized Pareto distribution, for a sequence of earthquakes intraplacas which occurred in the city of João Câmara in the northeastern region of Brazil, which was monitored continuously for two years (1987 and 1988). It was found that the MLE and POME were the most efficient methods, giving them basically mean squared errors. Based on the threshold of 1.5 degrees was estimated the seismic risk for the city, and estimated the level of return to earthquakes of intensity 1.5°, 2.0°, 2.5°, 3.0° and the most intense earthquake never registered in the city, which occurred in November 1986 with magnitude of about 5.2º

Dowscaling estocástico para extremos climáticos via interpolação espacial

Present day weather forecast models usually cannot provide realistic descriptions of local and particulary extreme weather conditions. However, for lead times of about a small number of days, they provide reliable forecast of the atmospheric circulation that encompasses the subscale processes leading to extremes. Hence, forecasts of extreme events can only be achieved through a combination of dynamical and statistical analysis methods, where a stable and significant statistical model based on prior physical reasoning establishes posterior statistical-dynamical model between the local extremes and the large scale circulation. Here we present the development and application of such a statistical model calibration on the besis of extreme value theory, in order to derive probabilistic forecast for extreme local temperature. The dowscaling applies to NCEP/NCAR re-analysis, in order to derive estimates of daily temperature at Brazilian northeastern region weather stations

Indicador de vulnerabilidade agropecuária a extremos climáticos para o nordeste do Brasil

The effects of climate change on human societies have become the focus of many researchers for their research. Understanding weather patterns (circulation of the atmosphere, precipitation, temperature) is essences for predicting extreme weather, but analyze how these extreme events act in our society and look for ways to reduce the impact caused by these events is the great challenge. Using a concept very in the humanities and social sciences to understand these impacts and the adaptation of the society's vulnerability. The objective of this work is to develop and apply a methodology for evaluating fining scale and quantify the vulnerability of the Brazilian Northeast to climatic extremes, developing a methodology that combines aspects of vulnerability to drought, as well as socioeconomic and climatic indicators used to assess exposure, ability to adaptation and the sensitivity of geographical microregions of the region. The assessment of the susceptibility or degree of exposure to risk is the regional using the SPI (Standardized Precipitation Index) by the degree of magnitude dried (MD), the rate of precipitation such as PCD (Precipitation Concentration Degree) and PCP (Precipitation Period Concentration) helped characterize and regional climatology, these indices showed satisfactory results in the pilot study of Rio Grande do Norte to assess the degree of exposure to drought. Regarding sensitivity agricultural / livestock multivariate statistical technique to factor analysis showed acceptable results for the proposed model using data for the period 1990-1999 (P1). The application of the analysis of vulnerability considering the adaptive capacity, as the adaptive disability have almost similar results with much of the region's vulnerability to extreme south of Bahia state as a part of the semiarid region has a degree of vulnerability among moderate and mean

Influência de eventos hidrológicos extremos na qualidade da água de reservatórios na região tropical semiárida

Reservoirs are artificial ecosystems, intermediate between rivers and lakes, with diferent morphological and hydrological characteristics that can provide many important benefits to society. However, the use of this water for human consumption, watering livestock, leisure, irrigated agricultural production and pisciculture development, directly influence the increase loading of nutrients to aquatic environments and contribute to acceleration of eutrophication. Furthermore, global climate models are predicting a higher occurrence of extreme events such as floods and severe droughts, which will create hydrological stresses in lakes. In the semiarid northeast we can see the occurrence of these events, the drought of the years 2012, 2013 and 2014 was the worst drought in 60 years, according to the National Water Agency (ANA). Thus, this study aimed to evaluate the quality of the semiarid tropical water sources, identifying temporal patterns in periods with extreme hydrological events (floods and severe droughts). The study results showed that Gargalheiras and Cruzeta reservoirs presented significative changes in the limnological variables between rain and severe drought periods, with better appearance and in the most of the water quality variables in the rainy season and higher nutrientes concentrations and high electrical conductivity values in severe season, indicating decay of its quality. However, we found diferent behaviors between the reservoirs in severe drought. While Gargalheiras showed a typical behavior of the region, with high concentrations of algal biomass, indicating the worsening eutrophication, Cruzeta demonstrated a colapse in the total phytoplankton biomass, evidenced by the decrease in chla concentrations. This fact occurred because the low depth and proximity with the sediment facilited the inorganic solids resuspension and, consequently, resulted in turbid water column and light by limitation. In addition, the different behaviors between the reservoirs indicate that the responses of these environments problems such as extreme events must take into account factors such the region climate, size, depth of the reservoir and the basin characteristics.

Estudo do balanço de umidade por meio de modelos regionais para o clima do passado e do futuro sobre a América do Sul

In the context of climate change over South America (SA) has been observed that the combination of high temperatures and rain more temperatures less rainfall, cause different impacts such as extreme precipitation events, favorable conditions for fires and droughts. As a result, these regions face growing threat of water shortage, local or generalized. Thus, the water availability in Brazil depends largely on the weather and its variations in different time scales. In this sense, the main objective of this research is to study the moisture budget through regional climate models (RCM) from Project Regional Climate Change Assessments for La Plata Basin (CLARIS-LPB) and combine these RCM through two statistical techniques in an attempt to improve prediction on three areas of AS: Amazon (AMZ), Northeast Brazil (NEB) and the Plata Basin (LPB) in past climates (1961-1990) and future (2071-2100). The moisture transport on AS was investigated through the moisture fluxes vertically integrated. The main results showed that the average fluxes of water vapor in the tropics (AMZ and NEB) are higher across the eastern and northern edges, thus indicating that the contributions of the trade winds of the North Atlantic and South are equally important for the entry moisture during the months of JJA and DJF. This configuration was observed in all the models and climates. In comparison climates, it was found that the convergence of the flow of moisture in the past weather was smaller in the future in various regions and seasons. Similarly, the majority of the SPC simulates the future climate, reduced precipitation in tropical regions (AMZ and NEB), and an increase in the LPB region. The second phase of this research was to carry out combination of RCM in more accurately predict precipitation, through the multiple regression techniques for components Main (C.RPC) and convex combination (C.EQM), and then analyze and compare combinations of RCM (ensemble). The results indicated that the combination was better in RPC represent precipitation observed in both climates. Since, in addition to showing values be close to those observed, the technique obtained coefficient of correlation of moderate to strong magnitude in almost every month in different climates and regions, also lower dispersion of data (RMSE). A significant advantage of the combination of methods was the ability to capture extreme events (outliers) for the study regions. In general, it was observed that the wet C.EQM captures more extreme, while C.RPC can capture more extreme dry climates and in the three regions studied.