O presente estudo busca contribuir para a compreensão dos impactos das
mudanças climáticas na região Semiárida do Brasil e como isso afeta a
vegetação e outros aspectos ambientais, pois ao entender melhor essa relação,
será possível compreender como os ecossistemas respondem às mudanças
climáticas e, assim, tomar medidas mais informadas para mitigar seus
impactos. Tendo como objetivo analisar a associação entre os índices de
extremos climáticos por meio de componentes principais e o índice de
vegetação por diferença normalizada (NDVI) na região Semiárida do Brasil
(SAB). Os dados climáticos utilizados foram fornecidos por Xavier et al. (2022)
e as variáveis utilizadas no presente estudo são precipitação, temperatura
máxima e mínima. Os dados de NDVI foram coletados pelo sensor MODIS a
bordo dos satélites TERRA/AQUA da NASA. A análise foi realizada
primordialmente pela caracterização dos períodos chuvoso e seco. Uma vez
determinados esses períodos, foi feita a análise das tendências dos índices
das componentes principais, a fim de calcular a correlação cruzada entre as
componentes nos locais onde houve tendências. Posteriormente, calculada a
correlação cruzada, com o objetivo de verificar a associação entre as
componentes principais de extremos climáticos e o NDVI. No intuito de
compreender como esses fatores interagem e se influenciam mutuamente. A
componente principal (PC1), revela informações sobre as variações a extremos
de temperatura e frequência de dias quentes. Em relação com o NDVI sugere
que as condições climáticas de temperatura, especialmente durante a noite,
desempenham um papel significativo na relação entre tais extremos e o NDVI,
seja no período seco ou chuvoso.

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Fire is an essential element for the conservation and diversity of many ecosystems. However, human activities that use fire have caused changes in the frequency and severity of vegetation fires, even affecting ecosystems not adapted to fire. The terrestrial biomes of Northeast Brazil are vulnerable to fire, exhibiting different degrees of dependence and resistance to it. This study aims to compare the detection of burned areas by the MCD64A1 and MapBiomas products, and the detection of hotspots by the MOD14A2 and MYD14A2 products, from the MODIS instruments aboard NASA's AQUA and TERRA satellites. The products were evaluated across different biomes in Northeast Brazil to identify patterns, trends, and determining factors of fire events. Burned area data from the MCD64A1 and MapBiomas products were obtained for the period from 2001 to 2022, and hotspot data from the MOD14A2 and MYD14A2 products from 2003 to 2022. The analysis of these products was conducted using descriptive and multivariate methods. The results reveal that the MCD64A1 and MapBiomas products show differences in the estimation of burned areas, with significant correlation in some biomes, such as the Caatinga and Cerrado, although they present variations in the amount of burned area detected. Furthermore, the MOD14A2 and MYD14A2 products provided consistent detection of hotspots throughout the studied period, reflecting seasonal and annual variations. Each biome displayed distinct particularities in fire activity patterns, mainly correlated with climatic factors such as the occurrence of El Niño and La Niña events, and associated with anthropogenic activities such as deforestation and the use of fire for pasture clearing. Additionally, other factors influence the accuracy of burned area detection by satellites, such as vegetation, the extent of the fires, and the type and amount of fuel. The analyzed products proved to be valuable tools for monitoring burned areas and hotspots in the biomes of Northeast Brazil, and given the variability in detections observed between different products, further studies are needed to understand how these products behave in each biome, considering the particularities of each one.

This study aimed to analyze daily wind speed data in Brazil collected from 1961 to 2020 to assess changes in two 30-year climatological normals, referred to as P1 and P2. The analysis was conducted through 54 meteorological stations managed by INMET, utilizing missing data filled with the bootstrap expectation maximization algorithm. Imputing 10% of the data was identified as the most reliable, showing low Root Mean Square Error (RMSE) values, values close to 1 for DP, and r values exceeding 0.93, indicating the effectiveness of this method in reconstructing historical wind speed data in Brazil. The study included the application of statistical tests, such as the Mann-Kendall test to detect linear trends and the Sen slope test to quantify trend intensity. During the P2 period, positive trends were observed in the Amazon basin and the semi-arid region, while negative trends were highlighted along the coast and in the Southeast region. Average wind speeds during P1 were higher than those in P2, revealing variations over the years. Comparison of the climatological normals P1 and P2 revealed significant positive trends in some regions during P2, with an increase in the average monthly variation of up to 0.85 m/s. The average slopes of significant trends were -1 and 1 ms-1 decade-1 for all analyzed periods. These results indicated high wind magnitudes, with Maximum Power Density (PD) of 778.08 Wm-2 for the NEB region, 170.90 Wm-2 for the SUB region, and 401.67 Wm-2 for the SUB. These findings have the potential to enhance the optimization of renewable wind energy generation in Brazil. Additionally, two databases, onshore and offshore, were used to evaluate wind potential. The onshore database consisted of hourly wind speed information collected at automatic stations in 2019, located near wind parks. The offshore database was obtained from a buoy offshore, Fortaleza, located on the coast of Ceará, near an offshore wind farm projected by the company Totalenergies Petróleo & Gás Brasil. The hybrid approach (SARIMA+GRU) proved superior to individual algorithms in generating wind speed and offshore wind potential forecasts. The Monte Carlo method was used to build prediction confidence intervals, and the prediction gain percentage reached up to 95% compared to individual models. The studied region has a total estimated technical potential of 2766 GW, and the analysis revealed that a single park with 200 turbines can meet the entire NEB region's demand, equivalent to 229% more than the region's demand. These results highlight the significant wind potential in the region, contributing to future renewable energy projects.

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The study of the wind potential presents a significant importance in relation to the estimation of electricity production, helping companies that intend to invest in wind energy to choose the most appropriate location for the best use of this type of energy resource. In addition, the electrical energy from these large wind turbines can be used for the production of hydrogen. The study aims to use stochastic modeling to forecast wind speed, temperature and relative humidity with short and long term time series, in order to analyze the wind potential for five cities in the coastal region of the Northeast and estimate the production of hydrogen for the ammonia-based nitrogen fertilizer market. The wind speed data comes from five meteorological stations of the National Institute of Meteorology (INMET), which uses an anemometer with a height of 10 m. These stations are located in Northeastern Brazil: Fortaleza, Natal, São Luís, Recife, and Aracaju. These weather stations have periods of approximately 30 years, initially using monthly data. The analysis, modeling, simulation and forecasting with atmospheric variables are part of the study of energy potential, as it allows a better understanding of the nature of data variability, including seasonality, trend and randomness, and can detect small variations. For the analysis of climatological data, the complete time series without a time interval is often used. This implies that regardless of the size of the series, it is not appropriate to have missing data and it is necessary to use the data imputation technique. In this study, missing value imputation was evaluated by including a structural time series model. The wind speed, temperature, and relative humidity data from these coastal cities went through data analysis methods. These methods are composed of the data that will be modeled and the observed data. These will be compared with each other. In addition, the climatological data used in this study have undergone residual tests, accuracy tests, and forecasts and estimates for hydrogen production will be made from the hybrid forecast results. The project aims to contribute to the private wind energy sector, with the availability of a tool that helps investors in this area to choose the most appropriate location for the best use of this type of energy resource.

From this research, it is proposed to characterize the microphysical parameters of clouds that generate extreme precipitation events over the East Coast of the Northeast Region of Brazil (CLNEB), by seasonal period, between the years 1998 to 2014. The objective was to characterize the parameters: Integrated Rainwater Content – RWP (kg/m²), Integrated Ice Content – IWP (kg/m²), Surface Precipitation Rate – SP (mm/h), derived from the 2ACLIM product (Microwave Imager – MI sensor), Freezing Level Height – FH (m), Precipitation Rate (mm/h) and Rainfall Type, from the 2APR product (Precipitation Radar – PR sensor), data from the Tropical Rainfall satellite Measuring Mission (TRMM). To analyze these microphysical parameters, statistical methods and measurements were used, such as mean, standard deviation, analysis of variance (ANOVA) and non-parametric tests by Kruskal-Wallis and Dunn. Finally, a conceptual model was presented to characterize the microphysics of clouds that generate extreme precipitation in this locality. The main results showed that the seasonal periods from December to February and from March to May, in both products, presented higher amounts of estimated rainfall for the clouds that generate extreme precipitation over the CLNEB. The height of the freezing level ranged from 4400 to 5150 meters in relation to the altitude of the 0º C isotherm. However, it was found that there was no difference between the pairs of averages for this parameter between the seasonal periods from June to August and from September to November on CLNEB (p-value > 0.05). It was observed that the extreme precipitation of the CLNEB comes from severe convective clouds (71.36%) and stratiform clouds (28.64%), both cold clouds.

Savanna ecosystems in semi-arid regions play a crucial role in global water and carbon cycles. Many researchers have investigated the hydrometeorological effects on carbon exchange and water use efficiency in these ecosystems, which play a key role in the global water and carbon cycle. These are highly sensitive to seasonal and interannual climate variations. Despite its importance, few studies investigate the relationship between carbon flux and water use efficiency in savannas. Therefore, in this study, we will describe 4 years (2010-2013) of data covering carbon and water fluxes in two areas of tropical savannas with different rainfall characteristics. The objective is to analyze the hydrometeorological effects on the water use efficiency of tropical savannas under different climatic seasonalities at different time scales. The increase in the frequency and severity of droughts is expected to have a profound impact on ecosystem structures and functionality, showing us results that differ from one habitat to another.

The Urban Heat Island phenomenon occurs mainly in cities with a high degree of urbanization, and is directly related to the accelerated and disorganized urban growth resulting from the occupation and transformation of the natural environment without any adequate planning. In this context, this work was carried out with the objective of analyzing and identifying the phenomenon heat islands in the urban areas of the city of Salvador-BA, from the digital images generated by the operational sensor Land Imager–OLI and Thermal Infrared Sensor–TIRS on board the Landsat8 satellite for selected dates in the period from 2013 to 2022. Thus, from the image processing maps of surface temperature and NDVI were generated for the city of Salvador, and six neighborhoods were selected for analysis of surface heat islands: Cassange (rural reference); Center; Business; Grande do Retiro Farm; Platform and New Brasilia. Therefore, the results showed an inverse pattern of the NDVI with respect to surface temperature. The heat islands were more intense in neighborhoods formed by areas of greater urban density and population density, with little or no presence of green areas. It is concluded that the areas with vegetation cover low temperatures are observed due to the shading produced by the trees. This demonstrates how these central urban areas are the most affected by the intensification of the heat island phenomenon, while at the same time confirming the significant role of green areas in urban centers.

Carbon exchange in forested areas, quantified by Net Ecosystem Exchange (NEE) and associated with phenological satellite measurements, plays an important role in understanding biosphere-atmosphere interactions in Amazonia, considering the accelerated deforestation in recent years. Using data from flux measurements tower in the Caxiuanã-PA(2005-2008), climatic data, CO2 exchange estimated by eddy covariance and satellite vegetation indices (MODIS), this work aimed to describe the energy flux, climatic and carbon cycle patterns of the site, correlating its gross primary productivity with satellite vegetation indices. The results found were: i) marked seasonality of climatic variables and energy fluxes, with evapotranspiration and air temperature at the site following the annual march of solar radiation and precipitation; ii) energy fluxes in phase and dependent on the available energy; iii) the site as a carbon sink, varying the intensity according to the site's annual water availability; iv) low correlation between productivity data and vegetation indices, corroborating literature data on these variables in this type of environment. The results show the importance of preserving this type of environment for the global climatic balance and the need to improve satellite estimates for this region.

Due to its aggressive and devastating characteristics, lightning constituted in the history of humanity the central observations point of several scientific communities around the world, causing the evolution of scientific knowledge about the phenomenon. However, our ability to represent its spatial and temporal variability, as well as your relationship with other environmental characteristics, remains a key challenge. It is estimated that about 60-75 million lightning strikes occur annually, which are responsible for the death of approximately 132 people every year in Brazil. The Northeast region of Brazil (NEB) concentrates 18% of all deaths across the entire national territory, and if we consider the population of the different regions, the state of Piauí had the highest mortality rate in the region (1.8 deaths per million ); this value being much higher than the national rate (0.8) and NEB (0.5). In this sense, the present work proposed to evaluate the occurrence of lightning in the Northeast region of Brazil, characterizing its relationship with the microphysics of clouds and natural disasters. Within this scope, data from two different orbital platforms were used: i) from the Tropical Rainfall Measuring Mission (TRMM), data from the Lightning Imaging Sensor (LIS), TRMM Microwave Imager (TMI) and Precipitation Radar (PR) sensors were used. The first provides data on the lightning occurrence throughout the Earth's tropical zone and the last two provide information on the clouds microphysical characteristics and estimation of the precipitation rate; ii) from the Geostationary Operational Environmental Satellite (GOES-16), data from the Geostationary Lightning Mapper (GLM) sensors on the occurrence and location of lightning and Advanced Baseline Imager (ABI) were used, a 16-channel sensor, 2 of which are visible , 4 in the near infrared and 10 in the infrared. First, the TRMM data were analyzed in order to seek to establish a relationship between the lightning occurrence and the clouds microphysical characteristics (ice water path, rain water path, freezing height level, convective precipitation and surface precipitation), comparing them according to lightning occurrence classes, spatial location and atmospheric profiles. Subsequently, a distribution of the lightning measured by the GLM was carried out, in order to understand its spatial and temporal variability. Finally, we also evaluate the relationship between the lightning parameters and the occurrence of natural disasters in the NEB. The states of Maranhão, Piauí and Bahia concentrate the regions with the highest lightning density. A higher occurrence lightning is associated with higher values of ice water path (> 38.9 kg.m⁻²), rain water path (>2 kg.m⁻²), convective precipitation (>5 mm.h^{− 1}) and surface precipitation (>7 mm.h⁻¹), in addition to slightly higher freezing height level values. Regions with high lightning density, on average, do not have lightning with large area, energy and duration. The Intertropical Convergence Zone, in addition to being important for precipitation, is also a system that generates a significant amount of lightning, being commonly related to natural disasters in coverage area. It is expected that, with the establishment of the sites and periods of greater occurrences and the characteristics of lightning, as well as the definition of the participation of each microphysical variable studied in the lightning occurrence, the understanding regarding the phenomenon can increase, in addition to the decrease in fatalities associated with him.

Land use in the Seridó river basin is the main factor in the intensification of desertification in this region, whose phenomenon interferes with the hydrology of the basin. Among its effects on the soil are the low quality and the change in the availability of water resources. The objective of this study was to evaluate the impacts of desertification on the hydrological response and on the water balance of the Seridó river basin, using hydrological modeling. The hydrological model used was SWAT, which proved to be an effective tool, as it satisfactorily simulated the seasonality of the monthly flow (Q) in four tributary sub-basins of the Seridó River, simulating the observed flow variance by more than 60%. In the evaluation of the dexterity of the model, it was observed that the simulation of the Q with greater dexterity were those equal to or less than Q5% (maximum flows) and the PBIAS (RMSE) of the simulated flow was ~ 30% (8.3 m³.s-1 ) and 50% (11.8 m³.s-1) for the calibration and model validation periods, respectively. To assess desertification, two land use and land cover scenarios (LULC, Land Use and Land Cover) were developed for the hydrographic basin: the control scenario, where the vegetation cover of the basin was that observed in 1985; and the desertification scenario, where desert areas were included from 1985 to 2019. The historical and gradual advance of the desert (15.39% of the basin area) altered the annual water balance, increasing the total runoff (Qtot ) by 6.95%, due to the significant increase in surface runoff (Qsurf), which increased by 12.08%. This change altered the maximum flow regime associated with floods, which were considerably increased in the desertification scenario. In annual mean absolute terms, the changes were 14 mm.month-1 and +11 mm.month-1 in the wet season, respectively. On the other hand, subsurface runoff (Qlat) decreased by 15.34% in relation to the annual balance, although it increased by 1.5 mm.month-1 in the rainy season. The annual evapotranspiration (ET) () reduced by 4.18%, which corresponded to -5 (-2) mm.month-1 in the rainy (dry) season. The same impact occurred with soil water content (SW) and percolation (Wperc). In these components, the average annual reductions were 3.79% and 1.96%, -45 mm.month-1 and -4 mm.month-1 in the rainy season, respectively. In spatial terms, with desertification ET, SW, Wperc (Qtot, Qsurf and Qlat), were significantly reduced (increased) in the central-west region of the basin. Studies using remote surface sensing confirm that desertification in the semi-arid region of northeastern Brazil has been installed and has progressed annually, at least since the 1980s. Studies evaluating the hydrological effects caused by this process in the theoretical sphere are rare, or inexistent, that is, hydrological modeling. This study contributes in this direction, and in general, we observed that desertification increased the extremes of maximum flow, while it deteriorated the hydrological conditions, locally and in the areas adjacent to the desert regions, with the reduction of the water content in the soil and the percolation. As a result, the maintenance of natural and agricultural ecosystems will be harmed, as they will have a lower supply of water for the ET, and reduced percolation, unbalance the groundwater system.

The diurnal rainfall variability has a spatial behavior that strongly depends on surface conditions and is related to variations in local circulations, topography and contrast in land cover and use. Understanding and simulating the daily rainfall cycle in a region is important for weather forecasting and for evaluating the efficiency of dynamic climate system models. Few studies have investigated the behavior of the diurnal precipitation cycle in the NEB region and, knowing that the evaluation of the diurnal precipitation cycle is an important test for the consistency analysis of a regional dynamic model, the objective of this project is to analyze the characteristics of the diurnal cycle of precipitation over NEB from the perspective of in situ observations and with regional dynamic modelling. The simulations will be carried out with the Regional Climate Model version 4.6 (RegCM4.6) in different periods. For the evaluation of the simulations, 6 years will be chosen (2008 to 2014). For the treatment of wet processes, the model considers two cumulus parameterization schemes (Grell and Kain-Fritsch). The validation of the simulation data in relation to the observed data will be done through statistical tests such as: ANOVA, Mean Absolute Error (MAE) and Root Square Error (RMSE). Precipitation observations will be obtained from 76 automatic stations, managed by the National Institute of Meteorology (INMET). From this study, we intend to answer questions about the reliability of the model and adequately represent the day cycle in the NEB, as well as the variability of the diurnal cycle in different subregions of the NEB.

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A Bomb Cyclone (BC) is an Extratropical Cyclone (EC) that presents a rapid pressure decay in the center of the system in the order of 1 hPa per hour for 24 hours. This system has gained popularity in recent years as it poses serious threats to the safety of maritime transport, fishing, maritime operations and other activities in coastal regions and the recent impacts on the population. Therefore, the purpose of this study is to analyze the physical, dynamic and phase characteristics of BC in the Southern Hemisphere through a robust climatology from 1979 to 2020. In addition, the existence of a trend in the number of BC over time and the influence of Systems Frontals (SF) in Natural Disasters (DN) in Southern Brazil. It is expected that the results can serve as a basis for improving services such as numerical simulations and be used as prognostics to assist in risk management with a set of preventive and mitigating actions in order to minimize the impact of these systems suffered by the population. Reanalyzed data from the ERA5 set from the Europe Center for Medium-Range Weather Forecasts (ECMWF) were used, with a spatial resolution of 0.125°x0.125° and 2.5°x2.5° and a temporal resolution of 6 hours in the period from 1979 to 2019, natural disaster data kindly provided by the National Center for Monitoring and Alerts for Natural Disasters (Cemaden) from 2016 to 2020, daily accumulated precipitation data, estimated from the Integrated Multi-satellite Retrievals for GPM (IMERG) algorithm (version 5) of the mission of the Global Precipitation Measurement (GPM) 0.25°x0.25° from 2016 to 2020 and surface synoptic charts from the Weather Prediction Center for Climatic Studies/National Institute for Space Research (CPTEC/INPE) at the four main synoptic times (00, 06 , 12 and 18 UTC) from 2016 to 2020. For the detection and tracking of BC, a cyclone tracking scheme was used in pressure level fields at mean sea level every six hours. To evaluate the three-dimensional structure of cyclones, the Cyclone Phase Diagram (CPS) was used. Student's t-test, Shapiro-Wilk, Mann-Kendall, Pettit and Sen's estimation tests were used to determine the existence, magnitude and break point of the trend in the BC time series. The total number of BC was 587, with the highest occurrence (44.2%) in winter and the lowest (6.1%) in summer. The spatial density of BC in the HS showed good agreement with that seen in the literature, seen mainly around Antarctica, in a kind of spiral around it, in the cyclogenetic area of AS southeast of Uruguay over the South Atlantic Ocean, in the Southeast of mainland Australia and the Tasman Sea. The physical and dynamic characteristics, such as speed, lifetime, pressure gradient and penetration rate, showed good agreement with other works in the literature. There was a trend in the number of BC over the years with statistical evidence. There has been an increase of one BC every 4 years since 1999. Strong evidence has been identified that more than 35% of BC that form in the HS follow the theoretical cyclone model known as Shapiro-Keyser. In the evaluation of DN caused by the passage of a SF over southern Brazil, it was observed that the most affected regions are the coast of Santa Catarina and the central-eastern region of Rio Grande do Sul. In addition, it was found that the FS that generate ND are different from the other FS that affect the South of Brazil. The main differences noted were: a pattern of increase and accumulation of convective potential energy available west of southern Brazil before the DN, especially in spring; a considerable increase in specific humidity at low levels associated with runoff east of the Andes; and an anticyclonic circulation at high levels similar to the Bolivian high. The analysis of the behavior of the rain indicates that it is higher in the two days before the disaster. The average values of precipitation identified, together with the observed atmospheric behavior, allow identifying the potential occurrence of a disaster in the cities of southern Brazil in the passage of a frontal system.

A high-resolution air quality study over the Metropolitan Area of São Paulo (MASP), Brazil is presented using the EURopean Air Pollution Dispersion - Inverse Model (EURAD-IM) for a highly detailed simulation of the air pollution plume interactions. In these first case studies on particulate matter (PM2.5 and PM10) modeled data are evaluated with observational in-situ data from 24 surface stations from the Environmental Company of the State of São Paulo (CETESB) and a Lidar. The two presented case studies, focusing on July 10-13 and October 22-25, 2016, show how

different meteorological conditions affect the transport of pollution plumes over the MASP originating from (i) central South America, associated to biomass burning activities, (ii) from the interior of the state of São Paulo (SP), (iii) the metropolitan region of Rio de Janeiro (RMRJ) 429 km apart, including transportation in the opposite direction, (iv) the port and city of Santos, as well as Campinas and contrary direction. Three simulations were carried out, the first using the emissions inventory of EDGAR v4.3.2, the second replacing the category of land transport emissions with data from theVehicle Emissions Model (VEIN) with high spatial resolution and the third using the three dimensional variational data assimilation technique (3D-VAR) for PM2.5. The performance of the model varied from excellent to good agreement with the observations varying within the standard deviations and elucidated the role of long-range transport of particulate matter from central South America and local transport within the state of SP, affecting the air quality at MASP. For the period from July 10-13, the results of PM10 and PM2.5 in the simulations without assimilation for the domain with 1 km x 1 km resolution underestimated the observations, and the bias varied between 8 - 41%. For MASP center, EURAD-IM performed better using VEIN emissions. The second case study in October revealed that air pollution plumes from the MASP and MARJ interact with each other, through two possible routes: via the Paraíba Valley or via the ocean between the coast of Rio de Janeiro and São Paulo. For October 22-25, EURAD-IM performance was more accurate outside the city of SP where the simulation underestimated observations, and the bias varied between 2 - 41%. For the center of MASP, the model strongly overestimated the PM10 and PM2.5 observations. The 3D-VAR assimilation was also used to show how observations may be used to improve model simulations by using radii of influence.

In a scenario of climate change, the current levels of productivity, under broad environmental conditions, production per harvested area is intrinsically linked to issues of water availability in the soil. Understanding climate influence and water balance on agricultural productivity can assist in the performance of practices in the field and policies to reduce climate-related vulnerability. In this perspective, the objective of this thesis is to analyze the behavior of the productivity of the crops: cassava, corn and beans in view of the climatic variability and water balance, in the Northeast Region of Brazil. Two articles were developed: the first identifies space-time patterns of daily precipitation, verifying associations with crop yields, in the state of Rio Grande do Norte, 1980 to 2013; the second analyzes the Climatological Normal Water Balance and the sequential and its relationship with crop productivity in the Northeast region of Brazil, 1990 to 2019.Daily and climatic data provided by Xavier et al. (2015), from 1980 to 2013 and data from the Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) from the Global Modeling and Assimilation Office (GMAO) with the support of the modeling program of America's Space Agency (NASA), for the period from 1990 to 2019. Various statistical methods were used: correlation analysis, Mann Kendall trend test, Cluster analysis, Tukey test, Factor Analysis, among others. The first study observed from moderate to strong positive and significant correlations of precipitation indicators with the productivity of subsistence agriculture, its trends, regions of greater agricultural aptitude and better periods indicated for the beginning of planting, according to the climatology of each region of the state of Rio Grande do Norte. The second study evaluated, based on the Thornthwaite climate classification of the Moisture Index, six typologies: Arid (28 municipalities); Semiarid (746 municipalities); Dry Sub-humid (536 municipalities); Sub-humid (389 municipalities), Humid B1 (73 municipalities) and Humid B2 (20 municipalities). The results showed an increase in radiation, temperature and evapotranspiration, mainly in the humid regions of the NEB. There was also an increase in water deficiency in SON and, consequently, a reduction in storage in all regions during the DJF period. It was found that in the two most humid regions, evapotranspiration and temperature correlated positively with the yields of beans and corn, while in the less humid areas, storage and water surplus had greater positive associations with agricultural productivity. According to the monthly climatological water balance, the periods of greatest water capacity for the regions were different between January and April. It is concluded, therefore, that the understanding of the behavior of the water balance variables and their relationship with agricultural productivity help in management strategies associated with climatic variations / trends, especially for the purposes of agricultural and hydrological planning and for irrigation projects for farmers. and local managers in Northeast Brazil.

Sea ice, covering approximately 7% of the surface of the Earth’s oceans, is a fundamental climatic component for studying climate in the polar regions, mainly because it acts as a natural barrier at the ocean-atmosphere interface that restricts the exchange of heat, mass, and momentum between the sea and the air, and reflects much of the incident solar radiation. Satellite observations since the 1970s indicate an Arctic with increasingly thinner and younger sea ice, accompanied by a decline in its extent. While some areas of Antarctica (e.g. Ross Sea and Weddell Sea) have shown a slight increase in the extent of this climate component for the same period. In this context, this study had as main objective to evaluate the potential predictability of sea ice cover with the application of ANNs techniques (MLP, LSTM and CNN-LSTM) in 3 Antarctic seas, they are Weddell, Bellingshausen and Amundsen. The data used were the monthly reanalyses from Era-5, for the period 1979 to 2019. SARIMAX models served as reference values for gauging the accuracy of the predictions with ANNs. Analyzing the errors (RMSE and MAE) of Sea Ice Concentration (SIC) for all the studied seas it was observed that the CNN-LSTM was exceeded only in the months with values lower than ± 25%, and the maximum differences between the errors in these events did not reach values above 5% ,as what occurred in the months of July, September and October in the Weddell Sea. With these results it was possible to infer that the CNN-LSTM model was the one that most accurately predicted the periods with the greatest differences (> 0.15) of SIC. With the analyses of the spatial distributions of the SIC differences it can be affirmed that the delimitations of the fields with differences greater than 0.15 were also better predicted with the coupling of the CNN and LSTM architectures, as occurred with the negative anomaly of June in the Weddell Sea (MAE < 0.15) and the positive one, in September, in the Amundsen Sea (MAE < 0.10).

The water scarcity and abundance of the wind resource in northeastern Brazil is a relevant topic for the study focused on energy planning. Currently, electric energy is treated as sensitive input in production chain, and therefore, despite   considerable tradition in using this matrix, the electrical energy presents in the internal scenario considerable restrictions, due to the limitations about of availability of water resource. Its intrinsic relationship with the climate precedes a need for new matrices arise as a sigh of complementarity. In this way, the general objective of this research was to identify the influence of climate in the generation of electric energy in Northeast Brazil. The thesis is divided into two articles. In the first, it was intended to identify the relevant climatic variables that influence hydroelectric generation. The monthly data used were the flow (period from 1964 to 2017), useful volume of the Reservoir (Sobradinho), Tropical Atlantic dipole, sea surface temperature anomalies in the Equatorial Pacific, precipitation, generation, loading and imports of electricity between 2000 to 2017 annual periods. The methodology used is based on statistical inference, principal component analysis and dynamic linear regression model. The results showed a 30% reduction in the streamflow upstream of the surfy Reservoir passing from 2,027 m³.s^-1 to 1,428 m³.s^-1. Using the scores of the principal components in the dynamic linear regression model, there was a reduction in generation by the hydro source by up to 40%. The second objective article comparing the different characteristics of the alternative wind source submitted to the influence of the monthly data of the ocean indexes and also of the climatic elements, such as temperature, humidity, atmospheric pressure and precipitation. Thus, we intended to apply the stochastic weibull models and dynamic linear regression with monthly wind speed data observed from anemometric towers at 80 meters and 10 meters high in a complex terrain region for 2013 to 2020 period. In particular, in 2016 and 2020, there was a significant negative influence on power density with El Niño and negative dipole, respectively. Decreasing tendencies of time series of wind was confirmed at 80 and 10 meters and also from Tropical Atlantic Dipole. In addition to the seasonality used in the regression model, it was observed that the intensity of the wind has dependence on atmospheric pressure, air humidity and ambient temperature.

The study of ocean waves spread and dissipation is of extreme importance for the safety and efficiency to the offshore engineering works, as well as for the coastline management. However, there are difficulties associated with obtaining measured data at sea that make a good time-space sampling difficult to obtain. An alternative to filling these voids in the observations comes from the production of ocean waves data indirectly through the geophysical effect registered by means of the microseisms. The frequencies of the signals which are of interest of this proposition at frequencies lower than 1 Hz (períodos > 1 s). In this context, this research aims to evaluate the association of the oceanic gravity waves parameters and the microseismic signals recorded in the northeastern Brazilian coast. The oceanographic data come from the Recife buoy, which is the only one of the Programa Nacional de Boias (PNBOIA) located on the eastern part of the northeast Brazilian coast, from June 11 to November 16, 2015, in addition to WAVEWATCH III output, when required. The meteorological data come from reanalysis ERA5 and images of the infrared channel from GOES 13 and METEOSAT-10 satellites. The seismological data come from the NBRF station, installed in Rio Formoso – PE (closest station to the oceanic buoy). From the analysis of gravity wave characteristics, it was observed that H_s has a median of 1.99 m in winter and 1.53 in spring, predominantly from the southeast, with a median T_p of 8.3 s. From the investigation of the main oceanic events it was found that the largest H_s are related to advance of cold fronts that intensified the winds at the ASAS extremities and the southeastern trade wind, along with small trough near the east coast of the Northeast. The pre-processing and spectrograms of the seismograms revealed that for the work area the microsisms are in the range 0.04 - 0.12 Hz (8 - 25 s) for primary microseism and at 0.12 - 0.70 Hz (1 - 8 s) for secondary microseism. The amplitudes of secondary microseism, from 0.7 * (1e-7) nanometers, showed a linear behavior with the variation of H_s which allowed the estimation of a transfer equation given by . So the efficiency of the use of microseism for the oceanographic and, consequently, meteorological study was demonstrated.

Climate change has increasingly been present in several sectors of society, especially the water sector. As water resources gain more emphasis due to the increasing demand for water use, it becomes crucial to understand the effect of climate change on the components of the hydrological cycle at the basin scale for the development of hydroclimatic adaptation in water resources management. Thus, the objective of this work is to evaluate the pattern of the hydrological response in the Piancó catchment in a near future (2021-2040). This is a subbasin of the Piancó-Piranhas-Açu river basin, completely inserted in the Brazilian semi-arid, whose springs are in the state of Paraíba. The hydrological response will be evaluated from simulations with the distributed hydrological model Soil and Water Assessment Tool (SWAT). The hydrological simulations will be performed for three hydroclimatic conditions: 1^st – for the present climate (1982-2005), and 2^st and 3^st – for the climate in the near future (2021-2040) in two scenarios of Representative Concentration Pathway (RCP): 4.5 and 8.5. The data used to perform the hydrological simulations for the present climate will be of the Executive Agency of Management of Waters of the State of Paraíba (AESA) and of a database of surface stations, regularly arranged in the space with a resolution of ~ 25 km. The data of the climate projections used for hydrological simulations for the future climate will be of the Coupled Model Intercomparison Project Phase 5 (CMIP5), regionalized for a resolution of ~ 25 km for precipitation and temperature. The SWAT performance will be conducted using hydrographs, permanence curve, dispersion chart and statistical indices widely applied in hydrological studies. The initial stages of the research have already been developed, such as: the evaluation of observed hydroclimatology and the hydrological modeling, more specifically  the geoprocessing phase for the delimitation of catchment and the drainage network, as well as the SWAT implementation of the soil classes found in the basin and its types of land cover, according to the classes found in the model. The initial results indicate that the hydrological year of the basin begins in January, with April being the month that the peak of flow occurs (~ 50 m³.s^-1), whereas the months of Jul-Dec the streamflow is intermittent (~ null). With respect to the physical characteristics of the catchment, obtained in the geoprocessing phase, these indicate that the dominant soils and vegetation cover in the basin, respectively, are the neosols (57% of the area) and the caatinga (79% of the area), which was represented in the SWAT as a deciduous forest. With the development of the research, it´s expected to analyze the impacts in the basin scale on the hydrological processes and water availability in a condition of climatic change in the semiarid of Brazil

The high variability of rainfall in Northeast Brazil (NEB) can trigger periods of extreme drought, which imply a decrease in the volume of water stored in artificial reservoirs during the rainy season. Thus, in this research, the objective was to identify the relationship between climatic variability and the volume of water in the reservoirs of Northeast Brazil during the period from 1986 to 2018. For this purpose, rainfall data were used, the monthly volume percentage of the total capacity of the reservoirs, oceanic indices, zonal and meridional winds, emerging long wave radiation. Thus, for the aforementioned analyzes, statistical techniques of multivariate data analysis and correlations were used. The results showed that just like the rainfall, the water volumes of the artificial reservoirs inserted in the NEB are also sensitive to the modes of variability of the adjacent oceans. The variability of the main atmospheric systems acting on the NEB is also an important factor regarding the volume of water in the reservoirs. The average of the central position of the ITCZ near the north of the NEB during the months of February to May was approximately -1ºS. However, when this average was not reached, negative rain anomalies were observed, so the average volume of the reservoirs followed this pattern of reduction most of the time. Finally, it is noteworthy that the volume of water in the reservoirs is sensitive both to the indices of the Pacific and Atlantic oceans and to the variability of atmospheric systems that operate where the reservoirs are inserted.

Neutral thermospheric winds play a key role in ionospheric dynamics acting directly on the ionosphe- ric plasma drift, being the main mechanism of maintenance of the nocturnal ionosphere and also di- rectly infuencing the behavior of the equatorial ionization anomaly (AEI). There are measurements of thermospheric neutral wind using equipment such as Fabry-Pérot interferometer (FPI acronym for Fabry-Pérot interferometer), incoherent scattering radar (ISR acronym for Incoherent Scatter Radar) and rocket sounding data. However, these measures are located ofering low data coverage. \ith the use of satellite-based equipment, it was possible to obtain better data coverage regarding the behavior of the neutral winds, such as the Upper Atmosphere Research Satellite (UARS) and DE-2 (Dynamics Explo- rer 2) satellite. The thermospheric neutral wind models have become an important tool for the studies and understanding of the behavior of neutral thermospheric winds. However, the models of available neutral winds present faults when related to the behavior of the ionosphere, especially in the southern hemisphere, and consequently on Brazil. In this work, we propose a parametric termospheric neutral wind model based on a statistis of the thermospheric neutral wind records from the UARS satellite using the embedded \ind Imaging Interferometer (WINDII). The model considers the average behavior between the altitude of 225 km and 275 km in periods of solar and geomagnetic activities considered to be calm (F 10.7 cm ≤ 125 sf u, and kp ≤ 2, 33) to calculate values of the components of the neutral wind covering low and medium latitudes (±45◦  of geographical latitude) for the whole globe (±130◦  longitude) with seasonal coverage (day of the year) and local time. To evaluate the behavior and accuracy of the proposed model, we will confront the modeled values with original data from UARS record. Comparisons will also be made with the output of other termospheric neutral wind models, such as HWM (Horizontal \ind Model), and data from observations performed with Fabry-Pérot interferometer. In addition, it is also intended to evaluate the behavior of the neutral winds modeled in relation to parameters relevant to the dynamics of the ionosphere

The region of the upper troposphere and lower stratosphere, or correspondingly the region of the tropopause, has been identified as being of fundamental importance to the climate, to physics and to chemistry of the atmosphere. The altitude of the tropopause has a latitudinal variation, being 7-10 km in polar regions and 16-18 km in the tropics, in addition to being higher, tropical tropopause is cooler, while polar is lower and warmer , but little is known about the equatorial tropopause. In this context, the present work aims at a detailed investigation of the equatorial tropopause characteristics in the Natal-RN region, using meteorological balloon radiosonde data released by the Barreira do Inferno (CLBI), initially between 2010 and 2014. In this way comparisons were made between the experimental data and the theorists, generated from the semi-empirical model MSIS-90. In the first months of the study, a total of 1817 cases were verified, 932 daytime probes and 885 nocturnal probes, comparing the minimum temperatures of the tropopause, the thickness of the tropopause and the variations suffered by this region with the seasons. It is intended to analyze a larger time series to corroborate the initial results, since CLBI measures were made available since 1996. In addition, it is planned to integrate these data with PROCEOS software (Atmospheric Ocean Events Characterization Program). The results that will be obtained with this research, have great importance for aviation, studies in climatic sciences and for aeronomia, and in future publications, a change in the model can be suggested.

At present it is recognized that the melting of tropical glaciers is a problem
in South America, due to the rapid response of the glaciers to the changes
observed in recent decades. In Peru, there is the Vilcanota mountain range,
being the most important mountain range of the southern region of Peru, since in this area it is located
the largest tropical ice cap of the earth (Quelccaya). The water resource that is born in
The Vilcanota mountain range comes from the water of the Urubamba river valley, being
importance of developing an intensive agriculture, besides which, in the course of the
Urubamba is the hydroelectric plant of Machupicchu, an important energy supplier of
region. In this sense, the objective of this work is to measure the water contribution of the glaciers
in the Vilcanota mountain range located in Peru and identifying possible changes in the
of ice cover. For the present study, we consider images obtained by
remote sensing in the last 30 years, covering the period between 1984 and 2016, with the
In order to quantify the area of the glaciers, we will use the Naive Bayes algorithm.
As a next step, we will use the Soil and Water Assessment Tool (SWAT), with
which objective is to estimate the flow from the melting of the Vilcanota basin.
As initial results, a setback was identified in the set of glaciers belonging to the
Vilcanota mountain range, including the Quelccaya ice cap. In which between the years of 1985 and
2016 the ice cover presented a loss of 61.61 km2 .. On the other hand, noting the
Quelccaya cap, the results indicated that in the same period, there was a loss of
15.31 km2 of ice cover in the shell. In addition, it was verified that the region with lower
(<5000 meters) contributed to the greater loss of ice cover, while
area (> 5300 meters.) showed stability or slight increase in
during the analysis period. A study of these approaches in
glaciers, will allow a more precise follow-up on their alterations, becoming
valuable information for the community in the region and help in decision-making.

.

Urban areas modify the surface energy balance, leading to greater heat accumulation, resulting in an increase in air and surface temperature values when compared to surrounding rural areas. This condition is described by the phenomenon of the urban heat island, which has been further investigated by different fields in recent years. This phenomenon affects the health of the population, energy consumption among other areas. In Brazil, the intense urbanization, aggregating larger cities, has direct effects on the intensity of the phenomenon, which increases the risks of mortality from heat-related diseases, in addition to the increase in energy consumption among other impacts. Faced with this context, the concern arose to know in detail about the presence and effects of the ICU phenomenon in large Brazilian metropolises. to verify its influence on the characteristics of precipitation and microphysical properties of clouds. To allow this understanding, methodologies applied to active and passive remote sensing data were used, together with statistical studies, which allowed to understand the effects of the ICU in different metropolitan regions and its relationships with other environmental variables (surface albedo and NDVI), analyzing ICU trends over 17 years (2000-2016) and the similarities between metropolitan regions, from statistical tests such as: Mann Kendall, Theil-Sen, t-Student (t paired). Our results indicate that all the metropolitan regions studied have heat islands, both day and night. Of this total, 10 showed a positive trend in daytime ICU values being related to 2 different biophysical factors investigated, NDVI and superficial Albedo even if at different levels. Manaus was the metropolitan region with the largest registered daytime heat island, besides its homogeneous environment with forest cover, because of this it was selected to evaluate the cloud microphysical properties. The properties Ice Water Path (IWP), Rain Water Path (RWP), Convective Rain and Surface Rain for a period of 15 years (2000-2014) were studied during the dry season of the Manaus metropolitan region. The region was selected because it has the highest intensity of daytime heat island in Brazil. Observations indicated that in the period studied, the rates of urban convective rainfall were always higher, throughout the day. But there were variations in IWP and RWP concentrations, according to the time of day, due to variations in surface energy flows. Regarding the spatial-temporal distribution in the daytime cycle, it was evident that the precipitation and other microphysical properties of the clouds, are modulated by local circulation, especially by the action of river breeze. During the dawn, the highest values of all microphysical properties studied are on the river, while in the afternoon they occur on the banks. In this context we point out that in most of the Brazilian metropolises, during the dry season, the greatest intensities of the urban heat island phenomenon have been identified and that possibly one of the effects is on the reduction of precipitation (convective and surface) on the urban area during the day, which aggravates the impacts of heat on urban inhabitants and exposes the urban surface to a greater load of radiation.

The economic and social structure of a country is linked mainly to the energy sector. This
sector is vulnerable to climate change being responsible for most of the emission of
greenhouse gases. From this premise, investments are needed in new alternative energy
generation, such as wind power generation in offshore regions in view of its great potential for
power generation. However, estimating the wind potential of a region, especially offshore, is
difficult because of the low availability of observed wind speed data at these sites. Therefore,
the objectives of this study are to evaluate the performance of the RegCM4.2 regional climate
model in simulating the annual and seasonal wind speed climatology in the Tropical Atlantic
Ocean Basin and to identify the wind potential for energy generation. Firstly, a comparison
was performed between the data from the PIRATA program with satellite data from the
Blended Sea Winds (BSW) product, in order to verify the BSW quality. Then the model
simulations were compared with the BSW data, using root mean square error, BIAS and
Pearson (general) and Spearman (monthly) correlation coefficient. Finally, after the validation
of the data, the wind potential was calculated by calculating the power density. In relation to
the BSW wind speed data validation, it was possible to identify that the BSW was able to
represent wind speed data well, presenting a high correlation coefficient and a relatively low
error. Similarly, the model presented better simulation of the wind velocity in the regions near
the coast than in the more distant regions of the coast, when analyzed seasonally, it was
verified that the model has better performance during the winter and spring periods.
Regarding the PD results, during the summer and fall, the highest values of PD were
concentrated in the coastal regions located to the north of the equator, while during winter and
spring the highest values of PD were observed in the northern Brazilian coast. In conclusion,
the validation of the BSW data showed low errors, proving to be an efficient database.
RegCM4.2 showed simulations consistent with the wind speed distribution obtained by the
satellites, and for PD, NEB presented the greatest potential for wind power generation.

The city constitutes an environment of interests and ideals, where they can generate divergences, which in turn draw social conflicts. With regard to this theme, one issue that stands out too far is the use and occupation of land and how it has been unequally appropriated by private enterprise. In this context, the low-income population feels forced to live on “city margins”, in often inadequate places such as slopes, hills or river banks and even in unhealthy health conditions, with no basic sanitation, exhaustion. in the open and lack of collection of household waste, among many other factors. In this sense, it is proposed in this project, the mapping of three urban areas in Rio Grande do Norte. The purpose is to identify the recurrent flooding area of both urban areas. For this, however, the cities to be chosen were Pendências, Carnaubais and Alto do Rodrigues, which are intersected by the Piranhas Açu River, and are located downstream of the Armando Ribeiro Gonçalves dam, having recorded these municipalities, a history of such phenomena. Census tracts defined by the Brazilian Institute of Geography and Statistics (IBGE) were used as territorial units, and with flood spots, the next step was the overlapping of social data in order to find the most vulnerable sectors in the face of critical events. of the floods of the Piranhas Açu river in RN. The scope of this study aims to work in the conceptual light with regard to the geosystemic processes, which is supported by the use of modeling resources to portray reality. For this perspective we will take as base the methodology that is based on the configuration of a socioeconomic index to be obtained through a weighted average of the variables under study. With this we will identify the Flood Risk with the delimitation of areas with Hazard-related Vulnerability (Risk and Exposure), which in this case will be the flood of the river.

Identifying patterns of atmospheric circulation related to the development of drought episodes contributes to the process of mitigating impacts to society. In Northeastern Brazil (NEB), one of the regions most vulnerable to occurrence of extreme events in South America, episodes of droughts are frequently recorded. This was the scenario observed between the years of 2012-2016, in which a severe drought hit the region. It is estimated that in this period approximately 85% of the reservoirs had less than 25% of their maximum capacity, and about 80% of the cities and 33.4 million people were affected by this extreme event. In this context, considering that this episode of drought was probably the most intense and long lasting recorded in the history of NEB, this research proposal aims to analyze the climatic characteristics at regional scale and the teleconnection patterns associated with the extreme event of drought occurred in the NEB during the period from 2012 to 2016, as well as modeling rainfall variability over the same period using the RegCM4 (RegCM-TBAND) regional climate model. In the observational study, data will be used in the 1981-2016 period of precipitation and maximum and minimum temperature provided by Xavier et al., (2016), as well as monthly means of the zonal, southern wind, vertical velocity and specific humidity of the ERA-Interim reanalysis. In addition, Sea Surface Temperature (SST) and Outgoing Long Wave Radiation (OLR) data will be used. The period 1981-2010 will be considered climatological, and from it, the monthly and annual anomalies will be calculated to diagnose the anomalous behavior of the meteorological variables during the period of 2012-2016. Then the dynamic analysis will be performed. In order to do so, the space fields of SST and OLR, and the ascending and descending movements related to Hadley and Walker will be investigated in order to identify the large scale atmospheric mechanisms associated with the dry period. In the numerical study, the simulations will be produced by RegCM-TBAND on the domain from 30 ° S to 30 ° N with horizontal resolution of 30 km. Initially, the skill of the model will be evaluated for the entire domain, for which purpose, ERA5 reanalysis data will be used. Afterwards, a NEB-focused analysis will be carried out to evaluate if the model is capable of reproducing the negative rainfall anomalies in the region. In this step, data from Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Climatology Project (GPCP), Xavier and Climate Research Unit (CRU) will be used. Preliminary results indicated that this drought occurred between 2012-2016 was the most intense since 1981, and the Northern Northeast Brazil (NNEB) is the most affected region. In quantitative terms, the negative precipitation anomalies on the NEB were 1063.4 mm, while on the NNEB were 1395.4 mm. The most affected seasonal season was the austral autumn (MAM), in which an average water deficit of 462.2 mm was detected in relation to the climatology. The analyzes of the maximum and minimum temperature anomaly indicated that in MAM besides the negative precipitation anomalies, an increase in the frequency, with significance of 1%, in the periods of heat and a decrease of the cold nights was observed on the NNEB. The next steps of the research are to obtain the oceanic and atmospheric patterns that caused the drought in the region of study, as well as to initiate the analyzes of the numerical simulations. This study intends to contribute to the improvement of the seasonal forecast of NEB precipitation in years whose atmospheric characteristics are similar to those discussed in the paper. This improvement in seasonal forecasting may lead to several public policies to mitigate the social and economic impacts linked to the occurrence of drought events in NEB.

This research had as main proposal the establishment and simulation of the Galactic Cosmic Rays (GCR) role on the global energy balance in the Earth’s atmosphere, considering the performance of carbon dioxide (CO₂) individually and together with the GCR fluxes. In this way, a modified version of the Global Resolved Energy Balance (GREB) climate model was developed, making it possible to simulate new scenarios. The new model is being called GREB-GCR. The results suggest that the joint action of GCR and CO₂, Experiment 20 (EXP20), presented a better representation on the surface temperature when compared to the exclusive action of CO₂, Experiment 12 (EXP12). This fact is mainly evidenced on the oceans. It was identified from the root mean square error (RMSE) that the EXP20 presented a spatially reduction of the error on the tropical region while compared to the EXP12. However, it is noteworthy that in both experiments the GREB-GCR model presented more significant errors on high altitude and polar regions. The calculated surface fields indicate that the GREB-GCR model can better simulate the surface air temperature considering anthropogenic (CO₂) and natural (GCR) forcings. The model also points to a recent weakening of the global warming trend of recent decades, which is influenced by the GCR’s fluxes.

Saharan dust transport can reach distances of up to 5000 km and it is estimated that around 40 million tons of dust are transported annually from the Sahara to the Amazon basin, having important role as its main source of nutrients. In 2016, the first Brazilian LIDAR system with depolarization channels, DUSTER, designed for atmospheric transport studies and characterization of aerosols on the South Atlantic was installed. The DUSTER system has 4 detection channels, 1064 nm, 355 nm and depolarization channels 532 s nm and 532 p nm. The research was conducted to calibrate the DUSTER system, applying the method and characterize the atmospheric aerosols that are being transported over the atmospheric Natal city region. The data acquisition took place during the scientific campaigns that were designated MOLOTOV ZERO (February / 2016 to July / 2016), MOLOTOV I (December / 2016 to February / 2017) and MOLOTOV II (November / 2017 to February / 2018). The data obtained by the DUSTER allowed to calculate the ratio of linear depolarization of particles (), fundamental parameter in the characterization of atmospheric aerosols. The minimum and maximum values of  during the MOLOTOV ZERO, MOLOTOV I and MOLOTOV II campaigns were 0,02 ± 0,003 and 0,29 ± 0,023, 0,02 ± 0,002 and 0,28 ± 0,006, 0,02 ± 0,001 and 0.22 ± 0.001, respectively. The classification of aerosol intrusions on the Natal city atmospheric region indicated that they are predominantly marine aerosols and in some situations it is possible to identify mixtures of Saharan dust and biomass burning with marine aerosols to a greater or lesser degree. Data from the CIMEL photometer, installed next to DUSTER, corroborate the analyzes and indicate that there is a higher concentration of marine aerosols and of Saharan dust in two campaigns (MOLOTOV ZERO and MOLOTOV II). HYSPLIT transport model retro-analysis analyzes satisfactorily explain the presence of biomass burning aerosols in the atmosphere locally and their origin; however, there is no good correlation between retro-analysis and Saharan dust sources that explain their presence in latitudes further south such as Natal city and low altitudes, indicating that possibly events such as the ITCZ have an influence on this mechanism. The research data were also correlated with those of the CALIPSO satellite and the CATS system (coupled to International Space Station), indicating the presence of aerosols compatible, in some cases, with those detected with DUSTER system in soil.

Extreme weather events are becoming increasingly frequent in Brazil. The consequences have been catastrophic climate change, causing floods, drought, forest fires, landslides, river flows, cold or hot flashes, among others. These environmental changes have major implications for society, especially health, agriculture and water resources. Given this scenario, having knowledge of the behavior and frequency with which extreme values occur is of great importance to society. However, a major difficulty factor in performing these analyzes is the quality of the data series used, especially those on the daily scale. Therefore, the objectives of this study are to evaluate the quality of multiple imputation methods for filling in missing daily rainfall data, to investigate the ability of Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product to estimate occurrence and intensity of daily and extreme precipitation events, to estimate the return level of extreme daily precipitation events and to classify the microphysical parameters of the extreme precipitation generating clouds for Northeaster of Brazil (NEB). This region has high spatial and temporal variability of precipitation and is vulnerable to extremes of daily precipitation. For this purpose, it made use of daily rainfall data from rainfall during the period from 01/01/1986 to 12/31/2015 and from products 3B42, 2ACLIM and 2A12 from the TRMM satellite during the period from 01/01/2000 to 12/31/2015. Data analysis was performed by means of statistical measures and methods such as mean standard deviation, bias, mean square error, correlation, multiple imputation, t-student test, sensitivity analysis, cluster analysis, extreme value theory, analysis of variance, F test, Tukey test, among others. The main results indicated that multiple data imputation using the Bootstrap EM algorithm method could be a tool that corroborates the reconstruction of historical series of daily precipitation data. Overall, TRMM 3B42 product data performed well when estimating precipitation values for NEB. Its quality varies according to the location and time scale at which precipitation occurs. Estimates of the return level indicate that the expected daily extreme rainfall intensity depends on the seasonal period and where it occurs. The East of the NEB stands out as the region where the highest intensities of extreme precipitation are expected. Parameters such as amount of liquid water and integrated ice, height of the freezing top and type of rain were characterized, generating extreme precipitation clouds in relation to different NEB regions. 

Southern Brazil is the second region which most generates wind power in the country and its capacity could further increase if offshore resources would also be explored to this end. Offshore wind power generation is expanding in several regions of the globe but in Brazil, particularly in its southern portion, prospection studies are still scarce for this modality. In this context, the present study aims to assess wind variability and power density (PD) simulated by the Weather Research and Forecasting Model (WRF) in the Southern Brazil, focusing on the offshore region. For this, the simulations results were compared with data from the Blended Sea Winds (BSW) product from the National Environmental Satellite, Data and Information Service of the National Oceanic and Atmospheric Administration. The numerical experiment was carried out during a 5-year period, between 00UTC of 01/01/2006 until 00UTC of 31/12/2010. The domain has a total of 340 grid points in the zonal direction, 180 points in the meridional direction and 35 vertical layers with the top set at 50 hPa. This area comprehends the entirety of the Southern region of Brazil (Paraná, Santa Catarina and Rio Grande do Sul states), Uruguay and part of the Pacific and Atlantic Oceans. The WRF model was able to fairly accurately reproduce the position and intensity variability of the South Atlantic Subtropical High. Simulated wind speed values presented mean seasonal values equivalent to observed values in 98% of the seasonal periods and simulated PD in 90% of them. The possibility of hydro-wind complementarity in the region was also observed. In conclusion, it was found that it is possible to use the WRF model can be used as a tool to evaluate the potential for wind power generation in the Southern Brazil region. On the other hand, the model did not perform well in simulating wind in the regions near the Brazil and Falklands Currents. This shortcoming may be corrected by coupling the WRF with an oceanic model and using parameterizations which more adequately represent turbulence in the planetary boundary layer.

This work is devoted to the study of dynamic and thermodynamic characteristics of the High Level Cyclonic Vortexes (HLCV) in the Northeast of Brazil (NEB), using an objective VCAN identification algorithm (OVIA) using ERA-Interim data from the reanalysis of the the European Center for Medium-Range Weather Forecasts (ECMWF) and the NCEP (National Centers for Environmental Prediction) Climate Prediction Center (CPC) set, both from 1980 to 2016. The OVIA showed more efficiency after two added improvements and could be redirected to other studies. The AIOV results were confirmed by the climatology, identifying 1493 VCAN, 51% occurring in the summer and 5% in the astral winter. In the analysis of the spatial climatology, the regions of greater occurrence of the HLCV on the continent are: The central region of Pernambuco; The coast in the border of Pernambuco and Paraíba; northern coast of Bahia; Central region of Bahia; South region of Bahia. It is observed that in the South Atlantic Ocean adjacent to the coast of NEB there is a great density of HLCV. In the summer, HLCV occur more frequently in the coastal and south-central regions of Bahia, central Pernambuco and the coast of the border of Pernambuco and Paraíba, while in autumn, the central and coastal region of Bahia are the most affected. Evidence that this system acts as an inhibitor of precipitation in NEB is shown when precipitation and preferential positioning of the HLCV is related. This result indicates that in addition to the systems that modify the dynamics of precipitation, the HLCV is responsible for the water deficit. The atmospheric profile of the divergence shows that there is a phase change in the mean atmosphere, the monthly analysis of vorticity and divergence show that March is the most intense HLCV. Two conceptual surveys are presented, they show that the lifted condensation level (LCL) at 860 hPa at the center of the HLCV and 940 hPa at the border. The profile on the border region was more unstable than the profile at the center of the HLCV. The behavior analyzed by the thermodynamic indices indicates that situations occur that even without favorable local thermodynamics, the atmosphere responds to a more intense dynamic system that forces conditions to favor convection.

There are many factors that turn the quantification of the aerosol’s influence on climate change processes challenging. These factors are associated to the uncertainties in the distribution and properties of aerosols and clouds, as well as their global interactions. With the purpose of reducing those uncertainties, the National Aeronautics and Space Administration (NASA) in collaboration with the Centre National d'Études Spatiales (CNES), launched the Cloud-Aerosol LIDAR and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, that has on board a Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP), consisting of a light detector and tracker Light Detection and Ranging (LIDAR). This system performs a vertical sounding of thin clouds and aerosols properties around the globe as the satellite passes. The optical properties of the atmosphere along the pathway where the CALIOP laser propagates, are recovered by a number of algorithms, and to ensure the quality of the results, it is necessary to validate the data by different instruments and/or methods. Even though satellite measurements have a wide coverage area, they need to be more accurate, since the incorporated data acquisition and processing algorithms still lack precision. For this reason ground-based measurements are necessary for calibration purposes.  In this study a methodology was used to validate the Lidar Ratio from CALIOP, by obtaining the aerosol optical depth data from 2007-2016 of a sun photometer part of the AERONET network and installed in Petrolina-PE in the Brazilian Northeast. The CALIOP data were obtained using 54 coincident measurements under cloud-free conditions which corresponds to 31%of all existing measurements in the proximity of Petrolina/PE from 2007-2016. An AERONET/CALIPSO model (A/C-Model) developed by Lopes et al. (2003) was used, which defined the new Lidar Ratio, for comparison with the values of the CALIOP HERA algorithm. The performance of the A/C-Model for the characterization of the different aerosol types in the study area registered high frequency occurrences of clean marine aerosol (25 to 30 sr) and smoke (70 sr),  whereas CALIOP registered high frequencies of a mixture of dust with pollution aerosol (55 sr to 60 sr), and biomass burning or polluted continental aerosol (70 sr). The results of the A/C model were compared to CALIOP, which showed that the global model indicated a superestimation of the Lidar Ratio. We assume that the global model may not be adequate for the region. A super estimation may be associated to the CALIOP calibration, especially due to the influence of the South Atlantic Anomaly of the Earth’s magnetic field that may affect the accuracy of the system’s measurements.

Observational data acquisition related to atmospheric aerosols is relevant for the progress in research on their influence on climate change related processes. Due to their optical properties, they can interfere with the radiative balance and with cloud microphysics changing their dimensions and lifetimes. The active remote sensing system Light Detection and Ranging (LIDAR), called Duster, located in Natal, capital of Rio Grande do Norte, Brazil, sends laser pulses to the atmosphere and detects aerosols optical characteristics through their interaction with light. This research had two main foci: the first one is the LIDAR Duster quality assurance during the operational acquisition campaigns. The assurance was made by the following instrumental tests: Dark Measurment, Zero Bin, Bin-Shift, Telecover and Rayleigh Fit according to the Latin America LIDAR Network (LALINET) and the European Aerosol Research LIDAR Network (EARLINET) standards. By means of these tests it was possible to detect noises, recorder delays and check de alignment in near and far range. A set of algorithms called Duster Quality Assurance (DQA), with modules which read the instrumental quality test data, pre-process data, generate graphics and write the results in ASCII format were developed. The results point that the errors relative to the alignment testes, Telecover and Rayleigh Fit, are less than 0.1 in most of the channels.  The second focus was to compare tropospheric aerosol backscatter profiles by the Klett-Fernald-Sasano inversion method in two different tools: the Single Calculus Chain and the LALINET Inversion Algorithm. Two days of data acquisition with 1064 nm wave length were selected to acquire the profiles. The computation happened by means of the relative error among the profiles. The relative error profiles varied among 0 and 10% on the two days. This research also shows for the first time the filter Duster Cloud Free wich removes cloudy files automatically, assisting in the LIDAR data treatment for later obtaining of products.

The semi - arid region of the Northeast of Brazil (NEBSA) has complex climatic characteristics which allows a great variation in the spatial distribution of precipitation, related to different rainfall regimes. Therefore, studies on atmospheric systems related to precipitation are relevant since they are associated with disasters that cause great social and economic impacts. Within this context the doctoral thesis is divided into articles format, thus: (i) The first article had the task to verify if there are trends in events of weak precipitation (WRE) and events of intense precipitation (HRE) for the periods less rainy and rainy during the years 1961 to 2011. Firstly, to define extreme precipitation events, the percentile tool (P) with values below P5 representing precipitation events weak (WRE) and above P95 intense (HRE), with a threshold of 5% in each percentile analyzed. The Mann-Kendall test allowed us to identify increasing and / or decreasing trends among extreme rainfall events. The results showed significant trends for the two extremes in both periods. The intensity of precipitation in the WRE and HRE had a statistical significance of 5% in the months of June, July, August, October, November and December. (ii) The second article aimed to define the beginning and end of the rainy season for each homogeneous rainfall sub-region of NEBSA during the period from 1979 to 2013. For this purpose, cluster analysis was used to define homogeneous regions of precipitation. And then, it was used pentad to identify the beginning and the end rainy in each subregion. As a result, five homogeneous sub-regions of precipitation were identified, with different periods of rainy onset, with the exception of the S2 and S3 sub-regions that coincide on November 27 to December 1, possibly due to the activities of ZCIT and VCAN. The months from November to April are the rainiest throughout NEBSA. With higher accumulated per pentad occur in the month of March and the smaller ones in the month of September.  (iii) Subsequently, the third article addresses the main theme of this, to identify existing differences in the dynamic characteristics of the atmosphere over NEBSA, with performance of each meteorological system in situations WRE and HRE for the period 1961-2011. For that, the Conceptual Model (MC) was adopted as the main tool for capturing extreme events associated to different meteorological systems, taking into account the duration in days and months of greater performance of each system. In order to support the investigation of the methodology applied in this thesis, the objective methods of Coutinho 2010 were used to select VCAN and ForTraCC for SCM. The anomaly compositions were analyzed for the day of the event and up to four days prior to the event, using meteorological variables provided by NCEP / NCAR, according to the need of each system. In summary, the results of this study broaden our global understanding of the role of seven atmospheric systems operating in different regions of NEBSA, whether or not they influence the total precipitation. In the anomaly compounds of each system associated to WRE and HRE days, it was possible to identify the location of its performance as well as to identify the systems that influenced or acted together. In relation to the extremes, it was observed that the events have similarities with each other, in relation to the behavior of the atmosphere, and what differs is the intensity of the event. In relation to SCM, it was seen that they are always associated with one or more systems.  (iv) Finally, the fourth article studied the mesoscale convective systems operating on NEBSA in the period from 2010 to 2011, a differentiated contribution of this thesis, whose objective was to identify the main physical and morphological characteristics of the atmosphere, when the SCM associated with the WRE and HRE events. For this, a software was created that tracked the results provided by ForTraCC, allowing to separate only the SCM that were acting on the station located inside the NEBSA. The results showed that the SCM have similar physical and morphological characteristics when they were classified as WRE and HRE and both events occur more frequently in the period of OND and JFM.  When analyzing the periods of each event, it was possible to verify that the HRE occurred more frequently in all quarters analyzed, possibly due to the greater intensity of the system, to be favored by the characteristics of the NEBSA region.

In the amazonian region and the Brazilian northeast, extreme climatic events such as torrential rains and severe droughts are potentiated against a situation of poverty resulting in an increase or intensification of the incidence of endemic diseases, water supply problems, agricultural losses often leading to greater vulnerability. Thus, the main objective of this study is to construct and analyze an epidemiological vulnerability index associated with extreme climatic indexes for the Brazilian Amazon and Northeast region and it was analyzed the mesoregions of the study area according to the risk characteristics to the climatic trend. For this, different datasets were used: meteorological data from Xavier et al. (2015) from a project of the University of Texas and Federal University of Espírito Santo corresponding to the period from 1980 to 2013; health data provided by the Ministry of Health on websites of the System of Information on Mortality (SIM), SUS Hospital Information System (SIH / SUS) of DATASUS and demographic data with the Brazilian Institute of Geography and Statistics (IBGE) and Program of the United Nations (UNDP). The meteorological data were applied to the software RClimdex, which 21 indices were selected, 10 being related to precipitation and 7 to the temperature according to the meteorological and climatic conditions of each region of this study. For the creation of the epidemiological indicator of vulnerability to climatic extreme, the cumulative normal distribution was used to assign scores varying from 0 to 1 for the calculation of vulnerability components: risk, susceptibility and adaptive capacity. For the analysis, understanding and identification of the susceptible areas to morbimortalities, we used cluster analysis. The results showed that the indexes TXx, TNx, TX10p, TX90p, SDII, R20mm, CDD, R95p and PRECPTOT presented the highest trends of climatic changes for Amazonia and Brazilian Northeast, with emphasis on the Sergipe backwoods mesoregion. Although, it has observed high epidemiological vulnerability associated with climatic extreme for the whole region of study. The mesoregion of Marajó and Southeast of Amazonia had the highest vulnerability (0.98), explained by high adaptive incapacity, moderate susceptibility and high climatic risk. On the other hand, mesoregions as metropolitan region of Belém (0.72), East of Sergipe (0.68) and Rio Grande do Norte (0.75) presented lower vulnerabilities, associated with a low adaptive disability and low susceptibility, despite presenting a moderate climatic risk. The results of the cluster analysis revealed that groups that are very susceptible to morbimortalities presented high rates of respiratory diseases and infectious and parasitic diseases. This study made it possible to identify the mesoregions of Amazonia and Brazilian Northeast more vulnerable to the epidemiological aspect in the occurrence of extreme events.

Dengue is one of the major human diseases transmitted by mosquitoes and has caused several social and economic impacts in Brazil, particularly on human health. The Northeast Brazil (NEB) has experienced successive epidemic outbreaks of the disease. The aim of this study was to estimate dengue incidence rates for municipalities of NEB using the Empirical Bayesian Method (EB) and to identify dengue hotspots considering the precipitation homogeneous regions of NEB. It was also intended to estimate the Relative Risk (RR) of dengue epidemic rates according to the classification of the House Index (HI). And, finally, it was also aimed to identify profiles and types of climate and social-sanitary vulnerability to Aedes aegypti larval infestation and to dengue incidence in the municipalities of the NEB. Data from the Ministry of Health, IBGE, PNUD and ANA were used. The data analysis period was from 2001 to 2015. The methods used were: EB, Grade of Membership (GoM), Moran’s Index, RR and the tests: t of paired samples, Pearson and Kruskal-Wallis tests. The results showed that 66.56% (in 2002), 49.73% (in 2010) and 62.19% (in 2014) of NEB municipalities registered pre-epidemic (100<IR<300) or epidemic (IR>300) dengue rates. The North and South of the Semi-arid (NS and SS) are among the areas that presented the highest rates of dengue incidence (IR> 300).. In 2014, most municipalities (473) that performed LIRAa/HI were in Alert (1.00<HI<3.99) or in Risk conditions (HI>4.00). An association between HI classification and the IR (p-value <0.001) was found, indicating a RR of dengue 1.20 times greater (95%CI: 0.97-1.48; p-value:0.0803) in municipalities with HI in Alert and 1.81 times greater (95%CI: 1.43-2.29, p-value<0.001) in those with HI at risk compared to those with satisfactory HI. Constatou-se, a partir da utilização do GoM, que 66.3% of the NEB municipalities presented "high" or "intermediate" climate and social-sanitary vulnerability to larval infestation by Aedes aegypti and dengue incidence. Areas classified as "high" vulnerability had the worst social-sanitary conditions and highest annual precipitation rates. These are located mainly in the state of Maranhão (except for its southwestern portion) and scattered areas in the Piauí. It was also noted that the "low" vulnerability areas are located mainly in the coastal region (except in the state of Maranhão and Piauí). The results pointed out significant implications for the identification of areas with dengue epidemic risk trends in one of the regions of Brazil most vulnerable to climate changes.

The gravity waves can be defined as wavelike disturbances, almost periodic, which is horizontally and vertically propagate in the atmosphere, with characteristic periods of a few minutes to order three hours and spatial scale from a few kilometers to thousands of kilometers. The vertical propagation of gravity waves is a subject of particular interest, since they carry energy and momentum to the region of the lower termosphere to upper mesosfera. Hines published in the 1960s a series of studies suggesting that gravity waves of demonstrations provoke ionospheric disturbances (Travelling Ionospheric Disturbances, TID's). Thereafter several authors showed that the gravity waves and their ionospheric manifestations as TID's represent an important source of interaction between the neutral atmosphere and ionized and changes morphology and electrodynamics this ionosphere. The mechanisms of generation of gravity waves in regions close to the magnetic equator are often unknown making it difficult to understand the phenomenology of these structures, which suggests that this is an important topic in the media climatology studies and upper atmosphere. So we have to investigate what would be the main source of gravity waves near the magnetic equator, as well as understand how is the stratosphere-thermosphere coupling. In our studies of the gravity waves will use temperature profile data covering the geomagnetic quiet and disturbed periods, which shall include the solar cycles 23 and 24, and study periods between maximum and solar minimum.

Keywords: Gravity waves; radiosondes; Coupling, troposphere-thermosphere

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Among the various factors influencing the positioning through artificial satellites or GNSS (Global Navigation Satellite System), we highlight the error caused by the Tropospheric Zenith Delay, which is basically composed by a hydrostatic component (ZHD - Zenithal Hidrostatic Delay), influenced predominantly by nitrogen and oxygen, and the second one, a wet (ZWD - Zenithal Wet Delay), which is influenced by the presence of water vapor in the Troposphere. Both components can be estimated from observations of GNSS signals collected from ground-based receiving stations. The wet component has a strong relationship with the IWV (Integrated Water Vapor) which in turn is directly influenced by the amount of precipitated water vapor in the troposphere. This work aims to develop a graphical interface program with main focus on the generation of IWV databases obtained through radiofrequency signals from any GNSS receiving station, and to relate them to oceanic and meteorological variables. The software PROCEOS (Program for the Characterization of Atmospheric Oceanic Events), has as a differential when compared to other softwares: (a) it is structurally  friendly with ease of use in relation to software of the genre; (b) It has a multitasking structure, also allowing the user to perform reanalysis data manipulations of weather and climate centers, such as the European Center for Medium-Range Weather Forecasts (ECMWF) and the OAFLUX (Objectively Analyzed Air-Sea for Global Oceans ), as well as spatial and temporal distributions of the variables - maps and time series – in addition to filtering and perform statistical treatments of the results obtained, such as imputations and correlations of variables. Furthermore, the software allows to extrapolation the variables wind and evaporation on the ocean surface, in levels of atmospheric pressure. The software has been tested to predict rainfall using data from GNSS-RNNA and Meteorological Natal-A304 ground-based stations, both located at the UFRN Central Campus in Natal city, Brazil.  PROCEOS has produced excellent results when related to other software of the genre.  It also presents itself as an alternative and promising tool for nowcasting predictions, since its results are used as input data for weather forecasting models.

The study of atmospheric pollution is becoming increasingly common, as this causes impacts both at climate and environmental levels as well as in human health. Air pollution is the result of contamination by gases and solid and liquid particles suspended in the atmosphere. The effect can be immediate or medium / long term, since the pollution present in the atmosphere can be difficult to disperse. Particulate matter is the pollutant that presents the greatest danger, as it attaches itself to other pollutants and can become even more harmful. The objective of this study is to analyze and compare the concentration of PM10 in three regions of Rio de Janeiro, Cidade de Deus, Seropédica and Duque de Caxias, verifying if the type of activity developed (urban, rural or industrial) influences the pollution. In addition, verifying if the air quality standards adopted by Brazil are respected in the three regions of study, as well as verifying the trajectory of the pollutant of each region, through the "" Hysplit. For the current study, data from the PM10, from 1998 to 2013, from the three regions of the state of Rio de Janeiro with totally different characteristics were provided by the State Environmental Institute (INEA-RJ), with the Seropédica region being a rural area , Cidade de Deus an urban region and the region of Duque de Caxias, characterized as industrial. The analysis will involve data imputation techniques as well as time series analysis. As the initial results, the difference between the means of the regions stands out, being the rural area, Seropédica, with a lower concentration of PM10, having a mean of 33.2 μg / m3, while the regions of Cidade de Deus have an average of 90 μg / m3. Besides of identifying that air quality standards are not respected for most of the days under study in urban and industrial regions, unlike the rural region, which indicates preliminarily that the type of activity developed in the region influences the concentration of PM10 . It is hoped that this study can serve as a basis for the elaboration of public 4 policies, provide knowledge and awareness of the population on the importance of reducing the emission of pollutants.

In recent years the Industrial sector of red pottery has developed representatively
with the implantation of micro and small Ceramics companies throughout Brazil.
There were, however, no precautions regarding the use of natural resources used as
a source of raw material for the Industry. Thus, in this study, we investigated the
indications of possible micrometeorological alterations associated to the Structural
Ceramics Industry in the meteorological elements in five ceramic poles located in
the states of Rio Grande do Norte and Paraíba, during the period of 1980 to 2013.
The In order to verify if the meteorological variables: precipitation,
evapotranspiration, radiation, wind speed, humidity, and maximum and minimum
temperature presented tendencies, the Mann Kendal test was used; And to calculate
the indexes of climatic extremes was used the Data Set for Indexes of Climatic
Extremes - RClimDex. Five ceramic poles were identified, where there were
negative trends for precipitation, minimum temperature, relative humidity and wind.
And, positive trends for the variables maximum temperature, evapotranspiration and
solar radiation. There was a trend in all poles, except for the minimum temperature
for the P2 pole, which has a higher number of ceramics. A trend was also identified
for the indexes of climatic extremes of Rx1day, R99p, Txn, Tnx, Tn10p, Tx10p, Txx
and Tnn. With positive trends of temperature extremes for all poles studied, with the
exception of pole P1, which showed a decreasing trend, thus indicating a decrease
in the maximum values of the minimum temperature; And the P2 pole that did not
show a trend. These contrary behaviors may be associated with anthropic actions in
the region, specifically the intense ceramist activity. However, it can not be said
categorically that this behavior is associated only with anthropic actions, since it
may be under the influence of global climatic factors.

The change in soil cover causes changes in the energy balance and surface water balance. Inadequate soil use can lead to an advanced degradation condition, which is called a desertification process. In Brazil, there are several Desertification Nuclei, among which the Seridó Desertification Nucleus (RN-PB). Thus, the present work was based on the premise that the desertification process in the Seridó Potiguar (RN) region has possibly caused variability in surface temperature, albedo and energy and mass fluxes (evapotranspiration / evaporative fraction). To verify the changes resulting from this process, a descriptive / comparative analysis was performed between degraded area data and preserved Caatinga area (Seridó-ESEC Ecological Station). For this, a hybrid algorithm was used, which consists of parametrization of several algorithms such as SEBAL, SSEB, S-SEBI, and TM-Landsat 5 images, from orbit-points: 215/64, acquired free of charge Together with INPE - National Space Research Institute - under the condition of a clear sky, in the period 1995-2008. With this, it was observed that, due to the results for the studied period, there was stagnation of the heat flux in the soil (increase of 0.5%), an increase of the albedo, around 17% and 19%, with consequent decrease of the Radiation balance between 5% and 7%, and an increase in the evaporative fraction of 40% and 34% for the degraded area and ESEC, respectively, and the latter should be better analyzed, as it may have been influenced or even overestimated the effects Two extreme events (Drought in 1998 and rains higher than expected in 2008).

The production of sea salt in Rio Grande do Norte has contributed significantly to the social and economic development of the State, creating jobs, increasing incomes and adding to the public revenue through taxes. Climatic conditions that favor this activity are observed in regions of low latitude characterized by high temperatures and constant winds, as well as low precipitation. Thus, as the production of sea salt depends on climate conditions, the aim of this thesis is to analyze, statistically, how the influences of the climate variability and changes affect the production of this mineral. To this end, the thesis comprises four articles. In the first article, the main objective was to analyze the correlation between these climatic variables and the production of sea salt, as well as estimate the intensity with which the volume of this mineral varies as a result of climate change in the city of Macau, RN. The results show positive correlations between the volume of sea salt production and the temperature, hours of sunlight, evaporation and wind speed, and negative correlations with precipitation and relative humidity. In relation to climate changes, findings showed an increase in the volume of sea salt in four scenarios of climate change, which were presented by the IPCC, in the city of Macau, RN. Results showed that the best scenario for the salt industry proved to be solar evaporation at a rate of RCP8.5. In the second article, the main objective was to analyze the influence of the ENSO on sea salt production in RN. The results showed positive and statistically significant associations with the El Niño phenomenon. In relation to La Niña, the results do not show statistically significant associations with this phenomenon, regarding the production of sea salt in RN. In the third article, the main objective was to estimate the impact of climate change on the volume of sea salt produced in Rio Grande do Norte. The results showed positive impacts on the volume of sea salt produced in the four scenarios of climate change. In the scenario with less carbonic gas emissions, the positive impact, in relation to the average in the period studied, will be from 9.1227%  in the RCP2.6 scenario to 16.5350% in the RCP8.5 scenario, making it possible to affirm that the climate changes projected by the IPCC will have a positive impact on the production of sea salt. In the fourth article, the main objective was to estimate the economic impact of climate change on sea salt production. The results showed that climate changes will generate a positive impact on the income from sales in the sea salt industry in RN, in all of the climate change scenarios. The average annual increase in income from sales in this industry is estimated at varying from 9.1227% in scenario RCP2.6 to 16.5350% in scenario RCP8,5, making it possible to affirm that the sea salt industry in RN will benefit, economically, from climate changes.

In this work, it was made a statistical modeling of precipitation. This is a methodological work that uses stochastic simulations to estimate the probability distributions related to this atmospheric variable. In order to estimate the parameters of these distributions, Markov chain Monte Carlo methods were used to generate large size synthetic samples from observed data. The used methods were the Metropolis-Hastings algorithm and the Gibbs sampler. The simulations were performed under the hypothesis that the days of of the same period of the year (month or rainy season) can be considered to be identically distributed concernig the probability of precipitation. This research allowed the production of four papers. The first paper used the Metropolis-Hastings algorithm to model the probability of occurrence of precipitation on any day of the month. The simulations of this paper were perfomed with observed data of some Brazilian cities. The other papers used the Gibbs sampler and the proposed methods were applied to data from cities in the Northeast Brazil. In the second paper, Beta and Binomial distributions were used to model the number of days of the month with occurrence of precipitation. In the third paper, the Poisson distribution was used to model the number of days with precipitation extreme values in the rainy season. An alternative method for estimating these extreme values and their distribution is presented in the fourth paper, using the Gamma distribution. According to the results obtained by these researches, the Gibbs sampler was considered to be adequate to estimate distributions in the modeling of precipitation on cities for which there are few historical data.

Os Desastres Naturais (DN) são estabelecidos pela ocorrência de fenômenos naturais em áreas ou regiões habitadas, e caracterizados pelo fato de seu impacto causar danos à população afetada. Caso não apresente danos à sociedade ou aconteça em áreas não ocupadas, o fenômeno é considerado apenas um evento natural.  As ocorrências de Desastres Naturais originam grandes problemas e prejuízos para as sociedades afetadas, além de ocasionar grandes perdas humanas. O objetivo do trabalho é realizar uma análise das ocorrências dos DN nas dezenove microrregiões do estado do Rio Grande do Norte, no período de1991 a2012, traçando um paralelo com os registros ao longo do tempo dos limiares de precipitação. Utilizou-se de técnicas estatísticas, como análise espacial para a construção de mapas temáticos de forma a identificar áreas com maior risco, e o teste de qui-quadrado para verificar associações entre as variáveis. O Índice de Precipitação Padronizado (SPI) foi considerado, objetivando evidenciar as condições meteorológicas das áreas analisadas no momento da publicação dos Decretos de Estado de Emergência ou Calamidade Pública.  Os resultados demonstraram um aumento expressivo de 98,7% nos registros das ocorrências para o Estado, uma vez que nos 11 (onze) primeiros anos foram registrados 535 ocorrências e nos 11 anos subsequentes foram registrados 1.063, com um total de 2.447.683 pessoas afetadas por DN. Para o Estado, os fenômenos que apresentaram maior frequência foram: as estiagem/seca (81,1%), as enxurradas e as inundações (18,9%), provenientes das relações de fatores com características entre o natural e social. Os dados apresentaram relações estatisticamente significativas entre as ocorrências para os dois períodos em análise, bem como sua relação com a precipitação média acumulada anual. A compreensão deste comportamento ao longo do tempo levará as autoridades competentes, a identificar as condições que se encontra a sociedade, possibilitando no direcionamento de ações e políticas públicas eficazes na gestão para a mitigação do risco a desastres naturais.

The GNSS signal analysis (Global Navigation Satellite System) issued by satellites has been widely used in the field of geodynamics and geodesy, as a sensor for speed measurements and displacement of tectonic plates and the representation of the shape and the Earth's surface. However, the satellite signal is delayed as it crosses the earth's atmosphere, specifically in two of its layers: (a) the ionospheric layer, where the signal is delayed by  ionized atoms present in this region, and (b) the tropospheric layer, due to the presence of water vapor, and is strongly related to the amount of water vapor precipitable present in that region. This work presents data analysis of GNSS signals obtained from surface gauge stations, aiming applications related to the amount of water vapor in the troposphere. Data from GNSS signals were obtained from IBGE (Instituto Brasileiro de Geografia e Estatística) through RBMC web (Rede Brasileira de Monitoramento Continuo dos Sistemas GNSS). Data processing was performed using the GIPSY software, from JPL-NASA (Jet Propulsion Laboratory), which processes the observed data from satellites and provides ZTD values (Zenithal Tropospheric Delay). Knowing the temperature and pressure on the antenna, one can estimate IWV (Integrated Water Vapor), which can be related to the local pluviometry. Applications were made on the cities of Natal and Mossoró, in the Rio Grande do Norte State, and correlations were made between the variables from the time series obtained for the ZTD parameters, IWV and Pluviometry, using statistical analysis from the R-software. The use of GNSS signals has been used as a tool for NWP, numerical weather prediction, using the IWV parameter as input for applications in Nowcasting models.

Environmental and Climate changes are interdisciplinary themes of high complexity, which in recent years has been widely disseminated to society in various media. These environmental climate changes has been validated by the reports of the Intergovernmental Panel on Climate Change, as well as other environmental bodies and the results indicate a worrying future for the climate, environment and humanity. Much of the negatives effects of these changes are caused by human excessive activities in nature. These excesses are made to meet the demands of consumerism contemporary , a social model that is generated by a misinterpretation of natural resources and powered by the rational
scientific current paradigm of development. This paper proposes that reforms in the education system can mitigate the long term, the acceleration of climate changes and the environmental degradation. The basis of this reform are high investments in better quality of education, with a greater focus on the dimension environmental aiming to educate the human being, about importance of the environment to humanity. In this sense, education can increase understanding of the causes and effects, of acceleration of climate changes environmental, through many pedagogical processes and transform human activities harmful in sustainable activities.

This study presents an analysis of the performance of the method forecasting ensemble by Multiple Linear Regression Principal Component (RPC) to combine simulations with different configurations, performed with a regional climate model (downscaling dynamic technique) in order to simulate rainfall on tropical portion of South America. The analysis focused on two sub-regions of Brazil: Northeast Brazil (NEB) and Amazon (AMZ). The regional model used in the simulations was the RegCM4, forced by ERA-Interim data produced by the European Center for Medium-Range Weather Forecast (ECMWF). They analyzed 18 autumns austral (1991 until 2008). For the composition of a prediction ensemble, were used for training period 2/3 and 1/3 for validation, as holdout technique. The results were compared to daily precipitation data from the Global Precipitation Climatology Center (GPCC) and the average of the simulations (MA method), which is the method generally used for forecastingensemble. The RegCM4 model showed potential to predict rainfall over the tropical region of AS. Moreover, different parameterization of the model can be modified to make it more effective. However, the good performance of the model combined with the method of predictionensemble (RPC) increased accuracy compared to the MA method, with: less biased bias (average close to zero), while the MA method was biased (underestimated precipitation); greater capture the variability of GPCC data and moderate correlation with the GPCC data, while MA obtained weak correlation and greater mean square error. In addition, the reproduced PCR method with improved performance, the frequency of particular precipitation rates (0-5; 5-10; 10-15 and 15-20 mm/day) along the entire the period for both regions. Therefore, from the developed and implemented methodology yielded improvements in forecasting intensity of daily rainfall over the tropical region of South America.

Esta pesquisa se propôs a investigar aspectos climatológicos (caracterização) mensais, sazonais, anuais e interdecadais da Evapotranspiração potencial para o estado do Acre a fim de compreender melhor sua variabilidade temporal e espacial e identificar possíveis tendências na região, tendo como unidades de estudos os municípios de Rio Branco, capital do Estado, Tarauacá e Cruzeiro do Sul, considerando um período de 35 anos: 1980 a 2014, a partir de dados mensais de estações meteorológicas de superfície do Instituto de Nacional de Meteorologia. Como metodologia adotou-se realizar, primeiramente, a consistência dos dados meteorológicos desta forma foi feito o preenchimento de falhas através da imputação de dados na série temporal por meio da imputação multivariada, na seqüência foram realizados testes estatísticos de homogeneidade, de tendência (Mann-kendall) e do estimador de Sen's (magnitude), assim como os testes de t-student e Mann-Whitney para identificar a partir de que ano a tendência passou a ser significativa. E por fim, a técnica de Análise de Variância - ANOVA foi adotada a fim de verificar se há diferença significativa nas médias anuais da evapotranspiração entre as localidades. O método indireto de Penmann-Montheith foi utilizado para o cálculo da Evapotranspiração potencial. Os resultados deste trabalho, permitiram concluir que a média anual da ETp é de 3,78, 2,90 e 2,80 mm dia ano^-1, para Rio Branco, Tarauacá e Cruzeiro do Sul, respectivamente. Apresentando sinal sazonal bastante marcante com um mínimo em junho e um máximo em outubro. Pela ANOVA foi verificada que as médias entre as localidades diferem estatisticamente para um nível de significância de 1%. A década de 2000 foi a que apresentou os anos com maiores valores de evapotranspiração, associados à fase fria da ODP, e a década de 80 os de menores, associada à fase quente da ODP, para as três localidades. Mediante análise do teste de Mann-kendall, verificou-se tendência de elevação de 0,10 mm/década, aproximadamente, na evapotranspiração potencial na escala anual e sazonal, com exceção do verão na localidade de Cruzeiro do Sul. Esta tendência tronou-se estatisticamente significativa a partir dos anos: 2000, 1996 e 1988/90 para as localidades de Rio Branco, Tarauacá e Cruzeiro do Sul, respectivamente. Para análise de tendência dos parâmetros meteorológicos que condicionam a ETp foi observado tendência positivo/negativa em nível de 5% de significância, com exceção do Déficit de Pressão de Vapor que não apresentou incremento/declínio nas escalas anual ou sazonal.

Neste trabalho foi desenvolvido um magnetômetro, em que toda a etapa de conversão de sinais e aquisição de dados foi realizada por software, constituída unicamente de um sensor de fluxo saturado, comercial. O magnetômetro possui alta sensibilidade para medir campos magnéticos de baixa intensidade, estático ou de pequenas variações. Esse tipo de sensor funciona a partir da saturação de um material ferromagnético utilizado como núcleo. Foram elaborados dois programas. O primeiro em linguagem Labview, esse faz a comunicação entre o sensor e o usuário através de um computador, o aplicativo produzido é responsável pela obtenção e armazenamento dos dados referentes ao sinal de saída do sensor. O segundo programa feito em linguagem Java é incumbido pela conversão dos dados para assim estudá-los, além de armazená-los em vários formatos e construir gráficos. Os resultados obtidos são de grande importância para estudos do comportamento do campo geomagnético, pois as variações de fluxo magnético podem induzir correntes elétricas na superfície e assim afetar a distribuição de energia elétrica e também os sistemas de telecomunicações. Mostrou-se que é possível, com este magnetômetro, estudar as variações de campos em tempestades magnéticas e em períodos considerados calmos.

O estudo sobre o clima vem crescendo constantemente no decorrer dos últimos anos e a precipitação é uma das variáveis em destaque para essa finalidade. Neste estudo levando em consideração as dimensões territoriais e as distinções físico-climáticas existentes entre os estados do Nordeste Brasileiro (NEB), objetiva-se estudar as oscilações da precipitação no NEB, no período de 1961 a 2010, tendo como referência as médias mensais das capitais da região. Para tanto, inicialmente foi feita a descrição dos principais sistemas meteorológicos geradores de chuva na região e em seguida a análise dos dados com o auxílio da estatística descritiva, assim como a divisão dos nove estados em três grupos homogêneos com o auxilio de cluster, por meio de K-Means e a Análise dos Componentes Principais, para assim poder observar as séries temporais. Partindo dessas questões, fez-se uso da Transformada Wavelet (TW), a qual se apresenta como ferramenta eficaz na obtenção da variabilidade periódica num dado recorte temporal dos elementos meteorológicos, visando detectar alterações no padrão da precipitação. Os resultados são apresentados a partir das TW, a fim de visualizar as oscilações. Tais resultados possuem importância nos estudos climáticos, pois são obtidos por meio de um método que se utiliza de representações de tempo e frequência de forma simultânea e precisa, permitindo a análise de qualquer serie temporal. 

Nos últimos anos o município de Bom Jesus (PI) passou a figurar como uma região de grande potencial para produção de soja (Glycine max (L.) Merrill) em larga escala. Esta cultura agrícola ganha espaço nos cerrados bonjesuenses apresentando, no decorrer dos anos, crescimento exponencial de áreas cultivadas. Entretanto, a produtividade não acompanha esse mesmo ritmo de crescimento, passando por períodos de oscilações, ainda que exista disponível um grande suporte de tecnologias, materiais genéticos de maior potencial produtivo, uso de técnicas de manejo e correção do solo e da crescente qualificação dos produtores rurais. Portanto, no presente estudo, considerou-se que as condições climáticas exercem uma ação limitante às máximas produtividades de soja neste município. Diante desse contexto, a pesquisa visa analisar possíveis tendências em variáveis meteorológicas que possam influenciar na produtividade da soja no município de Bom Jesus. Para tanto utilizaram-se diferentes conjuntos de dados meteorológicos: i) dados diários de dois períodos (1984-2014) e (1974-2014), ambos obtidos a partir do banco de dados do Instituto Nacional de Meteorologia (INMET); ii) Normais Climatológicas do Brasil de 1961-1990 do INMET; iii) dados de produção agrícola municipal da cultura da soja dos anos/safras de 1997/1998 a 2012/2013 obtidos no banco de dados de Produção Agrícola Municipal (PAM) do Instituto Brasileiro de Geografia e Estatística (IBGE). Nas análises foram realizados cálculos para o cômputo das Normais Climatológicas (1984-2014) e aplicações estatísticas. Dentre os métodos estatísticos foram realizados: i) o teste de Wilcoxon – pareado para avaliar as diferenças entre as climatologias dos períodos de 1961-90 e 1984-14; ii) o teste de tendência (Mann-Kendall), no intuito de analisar a tendência de variação dos dados agrometeorológicos (precipitação, temperatura máxima, temperatura mínima e amplitude diurna da temperatura – DTR); iii) análise multivariada (análise de Cluster) pelo método de Ward e o teste de correlação de Spearman (rs), para identificar a relação entre os dados agrometeorológicos e dados de variabilidade anual da produtividade da soja. Para a aplicação dos testes o estudo adotou nível de significância estatística de 5%. Os resultados apresentados indicam que a sazonalidade da climatologia de 1984-2014 apresentou mudanças com relação à climatologia passada em todas as variáveis analisadas, exceto na insolação e na precipitação. Quanto à variabilidade dos elementos agrometeorológicos, observaram-se tendência negativa significativa para a precipitação no mês de outubro e positiva significativa no mês de dezembro, as quais constatam alterações nos padrões do clima local, demonstrado pelo atraso da retomada do período chuvoso, que poderá ser considerado na condução de medidas de planejamento para a definição da época de semeadura do cultivo da soja. Foi possível identificar também tendências positivas com significâncias estatísticas, na temperatura máxima, para todos os meses que fazem parte do ciclo da soja (novembro - abril), que por sua vez tenderá a provocar efeitos adversos sobre a fisiologia da cultura, e consequentemente impactos no rendimento final. Notou-se uma correlação positiva significativa entre a produtividade de soja e a precipitação no mês de março, apontando que períodos de estiagens neste mês são prejudiciais para o desenvolvimento da cultura da soja. Quanto à correlação entre as variáveis (temperatura máxima, mínima e DTR) e a variabilidade anual da produtividade da soja, o resultado do teste não mostrou correlação com significância estatística para o período analisado, visto que considerando a faixa recomendada para o desenvolvimento do cultivo, estas variáveis climáticas não são fatores limitantes na produtividade final da soja no município de Bom Jesus (PI). Assim, espera-se que este estudo possa contribuir para a proposição de medidas estratégias de planejamento, que levam em conta o papel da variabilidade climática sobre a produtividade final da cultura da soja.

A variabilidade intrassazonal é uma importante componente do sistema climático da Terra, apresenta interação com diversos fenômenos meteorológicos, sendo um elo entre os sistemas de tempo e clima, tornando-se uma ferramenta essencial para previsão e projeção do clima. O objetivo principal deste trabalho é avaliar o comportamento intrassazonal da precipitação sobre o Brasil Tropical e possíveis alterações ocasionadas nos cenários de simulação climática: “Historical” que representa o clima atual (1979 -2005) e “RCP8.5” representando as projeções de mudanças climáticas com o aumento da forçante radioativa da atmosférica em 8,5 W/m² para o período de 2070 até 2100. Entre os resultados obtidos estão: na primeira etapa à elaboração de um índice multivariado intrassazonal para o Brasil Tropical, por meio da aplicação da análise de máxima covariância, associada à projeção dos modos dominantes em eixos ortogonais. Desta forma é possível caracterizar os padrões resultantes em oitos fases, cujas composições representam a evolução da intrassazonalidade sobre a região de estudo. Na segunda Etapa foi realizada uma avaliação da sensibilidade dos modelos do “Coupled Model Intercomparison Project Phase 5”(CMIP5) à variabilidade semanal de precipitação durante os meses de verão e outono austal, dos dezesseis modelos avaliados, observou-se que apenas seis foram capazes de representar de forma significativa o padrão de precipitação, e dentre estes o modelo MRI-CGCM3 foi o que obteve o melhor resultado. A terceira e ultima etapa consistiu na aplicação da metodologia empregada na etapa 1 no modelo que melhor representou o padrão de precipitação, encontrado na Etapa 2, ou seja no MRI-CGCM3, num contexto geral notou-se que este modelo é capaz de representar bem o padrão de variabilidade espacial e ciclo evolutivo, entretanto do ponto de vista regional, ainda há necessidade de melhorias na representatividade dos sistemas.

O clima e a poluição do ar, dentre outros, são fatores responsáveis pelo aumento da vulnerabilidade da saúde das populações residentes nos grandes centros urbanos. Alterações climáticas combinadas a altas concentrações de poluentes atmosféricos estão associadas a doenças respiratórias e cardiovasculares. Neste sentido, o objetivo principal da pesquisa é modelar de diferentes formas a relação clima e saúde, especificamente para a população de crianças e idosos residentes em São Paulo. Para tanto, foram utilizados dados de variáveis meteorológicas, poluentes atmosféricos, internações e óbitos por doenças respiratórias e cardiovasculares no período de 10 anos (2000 a 2010). Por intermédio da modelagem via equações de estimação generalizadas, captou-se o risco relativo. Com a regressão dinâmica, foi possível prever o número de óbitos por meio das variáveis atmosféricas e o modelo beta-binomial-poisson foi capaz de estimar o número de óbitos e simular cenários. Os resultados mostraram que o risco das internações por asma aumenta aproximadamente duas vezes para crianças expostas às concentrações do material particulado do que crianças que não são expostas. O risco de morte por infarto agudo do miocárdio de idosos aumenta em 3%, 6%, 4% e 9% devido ao CO, SO2, O3 e PM10, respectivamente. Com relação à modelagem via regressão dinâmica, os resultados mostraram que os óbitos por doenças respiratórias podem ser previstos de forma consistente. Já o modelo beta-binomial-poisson conseguiu retratar o número médio de óbitos por insuficiência cardíaca, na região de Santo Amaro o número observado foi de 2.462 e o simulado de 2.508, na região da Sé o observado foi de 4.308 e o simulado de 4.426, o que possibilitou a geração de cenários que possam servir como parâmetro para a análise destinada à tomada de decisão. A partir dos resultados obtidos, é possível contribuir com metodologias que possam auxiliar a compreensão da relação clima e saúde fornecendo subsídios aos gestores no planejamento de políticas de saúde pública e ambiental.

Objetivo desta tese foi estudar experimentalmente o comportamento termodinâmico da Camada
Limite Convectiva (CLC) durante a estação seca e chuvosa em uma região de clima semiárido do
nordeste brasileiro (NEB), com o uso de radiossondas nos dias 16, 17 e 18 de novembro de 2013
(estação seca) e de 03 a 08 de abril de 2014 (estação chuvosa) no município de Apodi-RN e no
2
período chuvoso de 09 a 17 de abril de 2011 nos municípios de Mossoró-RN e Quixeramobim-
CE. Foram lançados 15 balões (período seco) e 32 (chuvoso) em Apodi, 35 em Mossoró e 36 em
Quixeramobim (chuvoso). Através das radiossondagens foram coletados dados do perfil de
pressão atmosférica, temperatura do ar, umidade relativa do ar, velocidade e direção do vento.
Para os dados de superfície em Apodi, utilizou-se uma estação meteorológica de superfície
modelo Vantage Pro 2 da Davis Company (EUA). Como procedimento de análise aplicou-se o
método dos perfis na determinação da altura da CLC e se analisou três informações de cada
perfil: a média da camada, o valor na base e no topo. Aplicou-se o teste t-Student para avaliar a
diferença estatística entre os dados por período e localidade. Em Apodi, a altura da CLC foi
aproximadamente 850 m (estação seca) e 362 m (estação chuvosa), no início da manhã (05:00
HL - Hora Local) e no final da tarde as 17:00 HL atingiu a altura máxima de 2500 m (seca) e
1765 m (chuvosa), já a temperatura potencial mínima às 05:00 HL foi de 298 K (seco) e 297 K
(chuvosa) atingindo a máxima de 306 K (seca) e 304 K (chuvosa) às 17:00 HL. Em Mossoró e
Quixeramobim, a altura da CLC no período chuvoso, em média, atingiu 839,6 m e 965 m
enquanto que a temperatura potencial atingiu 301 K com um razão de mistura de 15,5 (g/kg) e
temperatura potencial de 302 K com uma razão de mistura 16,6 g/kg respectivamente em ambos
os sítios. Para os dados de superfície coletados em Apodi foram calculados as médias, máximos e
mínimos a cada 10 minutos durante 24 horas, também foi aplicado o teste t-Student, e se
constatou que algumas variáveis meteorológicas apresentaram diferenças estatísticas
significantes ao nível de 5%.

No contexto de mudanças climáticas sobre a América do Sul (AS) tem-se observado que a combinação de altas temperaturas mais chuvas e altas temperaturas menos chuvas, provocam diferentes impactos como: eventos extremos de precipitação, condições favoráveis para queimadas e secas. Com isto, estas regiões enfrentam ameaça crescente de escassez de água, local ou generalizada. Assim, a disponibilidade de água no Brasil depende em grande parte, do clima e de suas variações em diversas escalas de tempo. Neste sentido, o objetivo principal desta pesquisa é estudar o balanço de umidade por meio de Regional Climate Models (RCM) do Project Regional Climate Change Assessments for La Plata Basin (CLARIS- LPB), assim como, combinar estes RCM por meio de duas técnicas estatísticas, na tentativa de melhorar a previsão sobre três áreas da AS: Amazônia (AMZ), Nordeste do Brasil (NEB) e Bacia do Prata (LPB) nos climas do passado (1961-1990) e do futuro (2071-2100). O transporte de umidade sobre AS foi investigado por meio do fluxo de umidade integrado verticalmente. Os principais resultados mostraram que os fluxos médios de vapor d’água nas regiões tropicais (AMZ e NEB) são maiores através das bordas leste e norte, assim indicando que as contribuições dos ventos alísios do Atlântico Norte e do Sul são igualmente importantes para a entrada de umidade durante os meses de JJA e DJF. Esta configuração foi observada em todos os modelos e climas. Na comparação dos climas verificou-se que a convergência do fluxo de umidade no clima passado foi menor em relação ao futuro em diferentes regiões e épocas. De forma semelhante, constatou-se que a precipitação foi reduzida no clima futuro nas regiões tropicais (AMZ e NEB), possivelmente devido os intensos fluxos de umidade que adentraram nas regiões. Por intermédio das técnicas de Regressão Múltipla por Componente Principal (C_RCP) e da combinação convexa (C_EQM), analisamos e comparamos as combinações dos modelos (ensemble). Os resultados indicaram que a combinação por RCP foi melhor em representar a precipitação observada em ambos os climas. Sendo que, além dos valores mostrarem ser próximos aos observados, a técnica obteve coeficiente de correlação de moderada à forte magnitude, em praticamente todos os meses nos diferentes climas e regiões. Além do mais, na avaliação das técnicas de combinação, a tendência percentual (PBIAS) mostrou que em geral, a C_RCP obteve valores de baixa magnitude (PBIAS = 0%) indicando ter um desempenho “muito bom” no clima passado e (PBIAS = -4% a 3%) para o clima futuro, sobre as regiões de estudo. Enquanto a C_EQM mostrou no clima passado, que a AMZ obteve um desempenho “bom” e nas regiões do NEB e LPB obtiveram desempenho de “bom a satisfatório”. Logo, os resultados mostraram que as técnicas tem um potencial promissor para aplicações operacionais em centro de previsão de tempo e clima.

Este estudo tem como objetivo investigar os impactos da oscilação de Madden–Julian (OMJ) na precipitação da região Nordeste do Brasil (NEB). Para tanto foram utilizados dados diários de precipitação baseados em 492 pluviômetros distribuídos na região e cobrindo um período de 30 anos (1981 − 2010). As análises através de composições de anomalias de precipitação, radiação de onda longa e fluxo de umidade, foram obtidas com base no índice da OMJ desenvolvido por Jones–Carvalho.

Para distinguir o sinal da OMJ de outros padrões de variabilidade climática, todos os dados diários foram filtrados na escala de 20 − 90 dias; portanto somente dias classificados como eventos da OMJ foram considerados nas composições.

Uma análise preliminar baseada apenas nos dados de precipitação foi feita para uma pequena área localizada no interior semiárido do NEB, conhecida como Seridó. Essa microrregião é uma das áreas mais secas do NEB e foi reconhecida pela Convenção das Nações Unidas para o Combate à Desertificação e Mitigação dos Efeitos das Secas como particularmente vulnerável à desertificação. Composições de anomalias de precipitação foram feitas para cada uma das oito fases da OMJ durante Fevereiro–Maio (principal período chuvoso da microrregião). Os resultados mostraram a existência de variações significativas nos padrões de precipitação (de precipitação excessiva à deficiente) associados à propagação da OMJ. A combinação dos sinais de precipitação obtidos durantes as fases úmidas e secas da OMJ mostrou que a diferença corresponde cerca de 50 − 150% de modulação das chuvas na microrregião.

Em seguida, uma investigação abrangente sobre o papel da OMJ sobre toda a região Nordeste foi feita considerando-se as quatro estações do ano. Os resultados mostraram que os impactos da OMJ na precipitação intrassazonal do NEB apresentam forte sazonalidade. A maior coerência espacial dos sinais de precipitação ocorreram durante o verão austral, quando cerca de 80% das estações pluviométricas apresentaram anomalias positivas de precipitação durante as fases 1 − 2 da OMJ e anomalias negativas de precipitação nas fases 5 − 6 da oscilação.

Embora impactos da OMJ na precipitação intrassazonal tenham sido encontrados na maioria das localidades e em todas as estações do ano, eles apresentaram variações na magnitude dos sinais e dependem da fase da oscilação.

As anomalias de precipitação do NEB observadas são explicadas através da interação existente entre as ondas de Kelvin-Rossby acopladas convectivamente e as características climáticas predominantes sobre a região em cada estação do ano. O aumento de precipitação observado sobre a maior parte do NEB durante o verão e primavera austrais encontra-se associado com o fluxo de umidade de oeste (regime de oeste), o qual favorece a atividade convectiva em amplas áreas da América do Sul tropical. Por outro lado, as anomalias de precipitação durante o inverno e outono austrais apresentaram uma variabilidade espacial mais complexa. Durante estas estações, as anomalias de precipitação observadas nas estações localizadas na costa leste do NEB dependem da intensidade do anticiclone do Atlântico Sul, o qual é modulado em grande parte por ondas de Rossby. As características topográficas do NEB parecem desempenhar um papel importante na variabilidade observada na precipitação, principalmente nestas áreas costeiras. A intensificação do anticiclone aumenta a convergência dos ventos alísios na costa contribuindo para a ocorrência de precipitação observada à barlavento do planalto da Borborema. Por outro lado, o aumento da subsidência parece ser responsável pelos déficits de precipitação observados à sotavento. Tais condições mostraram-se típicas durante o predomínio do regime de leste sobre a região tropical da América do Sul e o NEB, durante o qual ocorre uma diminuição no fluxo de umidade proveniente da Amazônia. 

A estabilização da oferta de energia no Brasil tem sido um desafio para o planejamento do Sistema Interligado Nacional, diante das variações hidrológicas e climáticas. Termoelétricas são utilizadas como fonte emergencial no período de escassez hídrica. Porém a utilização de combustíveis fósseis tem elevado o custo de produção, da energia elétrica. Por outro lado, a energia eólica em alto mar (offshore) vem ganhando importância no cenário internacional, e tornando-se competitiva a ponto de tornar-se uma possibilidade futura de geração no Brasil. Nesse sentido, o objetivo principal desta tese foi investigar a magnitude e distribuição dos recursos eólicos offshore, verificando também possibilidades de complementaridade com a fonte hídrica. Para isto, foi utilizado uma série de dados de precipitação do Climatic Research Unit (CRU) e conjunto de dados satelitários de velocidade de vento do projeto Blended Sea Winds da National Climatic Data Center (NCDC/NOAA). De acordo com critérios estatísticos foi encontrado três tipos de complementaridade presentes no território brasileiro: hídrica  hídrica, eólica  eólica e hídrica  eólica. Notou-se que houve complemento bastante significativo (r=-0,65) entre as fontes, hídrica e eólica, principalmente das bacias hidrográficas do sudeste e centro oeste com os ventos do Nordeste. Com intuito de refinar a extrapolação dos ventos sobre o oceano, foi utilizado método baseado na teoria de Monin-Obukhov para modelar a estabilidade da camada limite atmosférica. Foi utilizado o conjunto de dados de fluxos de calor, temperatura e umidade do Projeto Objectively Analized Air-Sea Flux (OAFLUX), além de dados de pressão ao nível do mar do projeto NCEP/NCAR e o modelo de relevo global ETOPO1 da National Geophysical Data Center (NGDC/NOAA). Verificou-se um bom recurso em águas rasas, entre 0-20 metros, estimados em 559 GW. A contribuição do recurso eólico em um reservatório, foi investigada com um modelo híbrido eólico-hidráulico simplificado que permitiu o cálculo do nível dos reservatórios a partir de dados de vazão afluente, defluente e produção de turbina. Notou-se que o sistema híbrido evita os períodos de estiagem, poupando continuamente água dos reservatórios através da produção eólica. Assim, a partir dos resultados obtidos, é possível afirmar que os bons ventos das costa brasileira podem, além de diversificar a matriz elétrica, estabilizar as flutuações hídricas evitando racionamentos e apagões, reduzindo o uso das térmicas que eleva o custo de produção e emite gases poluentes. Políticas públicas voltadas ao incentivo da energia eólica offshore serão necessárias para seu pleno desenvolvimento.

Os distúrbios ionosféricos propagantes - TID’s - são irregularidades no plasma ionosférico propagando-se com velocidades da ordem de dezenas a poucas centenas de metros por segundo. O presente trabalho foi desenvolvido visando detectar e caracterizar os TID’s do tipo LSTID’s (Large scale Travelling Ionospheric Disturbances) em baixas latitudes durante intensas tempestades geomagnéticas e sua propagação sobre setor brasileiro. Para este fim utilizamos registros ionosféricos obtidos a partir de digissondas do tipo CADI (Canadian Advanced Digital Ionosonde) localizada em Nata e do tipo DSP localizadas em Cachoeira Paulista, Fortaleza e São Luiz, no qual utilizamos uma série de dados de 12 anos colhidos pelo INPE (Instituto Nacional de Pesquisas Espaciais). Neste estudo foram relacionados tanto dias calmos quanto, os quais antecediam as tempestades e dias geomagneticamente perturbados durante os anos de 2000 e 2012, os quais englobam um período de máxima e mínima atividade solar. Este trabalho apresenta as variações ocorridas nas densidades eletrônicas da região F da ionosfera sobre o setor brasileiro, principalmente próximo ao equador (Natal, Fortaleza e São Luís), causadas por distúrbios ionosféricos propagantes na região equatorial durante intensas tempestades geomagnéticas, pois como sabemos da literatura na área esse fenômeno contribui positivamente para o surgimento de LSTID’s na região auroral, mas que podem se deslocar para a região equatorial onde poucos casos têm sido documentados e estudados de forma sistematizada. A partir da observação de assinaturas de TID´s em registros de ionogramas foi realizado um estudo da morfologia desses eventos e comparados com as principais características de onda desse fenômeno durante grandes tempestades magnéticas, isto é DST < (-200 nT) e KP > 6. Com isso obtivemos as características principais dos TID´s sobre nossa região, isto é, período, comprimento de onda vertical, velocidade de fase e velocidade de propagação, assim como o delay desses distúrbios em relação ao início das tempestades magnéticas para o setor brasileiro.  

Este trabalho propõe um estudo a partir de um conjunto de dados meteorológicos coletados na cidade de Natal/RN, buscando identificar evidências de alterações no seu clima urbano no período de 1970 a 2010. As variáveis utilizadas são: temperatura média, temperatura mínima e umidade relativa. Os dados foram obtidos a partir das estações meteorológicas localizada no Campus Central da Universidade Federal do Rio Grande do Norte (UFRN) e que faz parte da rede de observações do Instituto Nacional de Meteorologia (INMET) e do Centro de Lançamento de Foguetes Barreira do Inferno (CLBI), localizadas dentro de uma área urbana e de uma área não urbanizada, respectivamente. Procuram-se evidências da formação de uma Ilha de Calor Urbana na cidade de Natal, possivelmente relacionadas ao crescente processo de urbanização existente nos últimos anos. Foi avaliada a tendência linear nas séries temporais através do template MAKESENS, usado para determinar o teste de Mann-Kendall e do método de estimativa de inclinações de Sen. Os resultados apontam para tendências de crescimento em algumas séries de dados referentes à temperatura média e temperatura mínima e para tendências de decrescimento da umidade relativa média, essas tendências são mais evidentes na área urbana relativamente a área não urbanizada, o que evidenciam algumas características típicas das Ilhas de Calor Urbanas.

O objetivo desta pesquisa foi estimar avaliar a evapotranspiração na microrregião do Seridó a partir de dados pontuais de alguns municípios pertencentes para verificar os potenciais evapotranspirométricos da região. Os resultados apresentados pelos  principais métodos de estimativa deram conta de que o método de Hagreaves-Samani foi o que apresentou melhor ajuste em relação ao método de Penman-Monteith (FAO 56), mostrando ser viável de utilização,
apresentando “muito bom” desempenho conforme os dados medidos e estimados para as localidades estudadas. Os métodos de Penman, Thornthwaite e Romanenko não responderam muito bem em pelo menos 4 das localidades estudadas, ficando com o “péssimo” desempenho para o estudo devido a análise estatística ter mostrado resultados menos significativos e não significativos em relação ao método padrão de Penman-Monteith. A simulação de cenários segundo o IPCC foram plotados conforme os aumentos na temperatura média do ar, e utilizando dos métodos de evapotranspiração mostraram que os valores resultantes apontam alta na metade oeste da região do Seridó. E que devido a essas previsões de aumento gradativo na temperatura e conseqüentemente na evapotranspiração, os municípios pertencentes a essa região poderão ser
castigados com o alto valor no déficit hídrico. Em complemento a esses resultados foram levantadas questões com relação ao contínuo desenvolvimento da região, pois com o aumento nos altos valores de Eto poderá acarretar sérios problemas às comunidades que necessitam da água
disponível em açudes e reservatórios destinados ao abastecimento para consumo, agricultura familiar e a agropecuária.

Nesta tese foram utilizados três diferentes modelos de regressão, os Modelos Lineares Generalizados via regressão logística e de Poisson e os Modelos Vetoriais Lineares Generalizados via distribuição generalizada de valores extremos (MVLG-GEV) com o objetivo de detectar os extremos de precipitação no Nordeste do Brasil. Inicialmente aplicaram-se os modelos de regressão logística e de Poisson para identificar as interações entre os extremos de precipitação e as demais variáveis a partir das razões de chances e de riscos relativos. Constatou-se que a variável indicadora da ocorrência de extremos de precipitação é a radiação de onda longa, verificada nas regiões leste, norte e semiárido do NEB, e a umidade relativa foi verificada no sul do NEB, em ambos os modelos. Os resultados apresentados pelos modelos de regressão logística e de Poisson mostram evidências de que estes extremos de precipitação são impulsionados pela Oscilação Madden-Julian, que ao interagir com os outros sistemas meteorológicos locais, regionais e grande escala podem ocasionar a ocorrência destes extremos. O terceiro modelo, MVLG-GEV, avaliou os extremos a partir dos máximos anuais de precipitação de forma múltipla (a partir de um conjunto de variáveis) e constatou-se que as variáveis que subsidiaram a ocorrência dos extremos de precipitação foram: as componentes zonal e meridional do vento, evaporação e TSM (Atlântico e Pacífico). Este artigo mostra evidências de que a variabilidade da TSM vistas no Atlântico como no Pacífico (El Niño-Oscilação Sul) interfera na variabilidade interanual da precipitação, modificando o padrão de circulação atmosférica na região, resultando na intensificação ou inibição da ocorrência dos extremos de precipitação. Os coeficientes de regressão logística, de Poisson e de MVLG-GEV demonstraram significância estatística, inferiores a 5%. Em relação aos níveis de retorno para os próximos 30 anos pelos MVLG-GEV, o menor nível foi de 91,62mm no sul da Bahia, enquanto o maior foi de 185,72mm no norte do Ceará.

O objetivo do trabalho foi estudar a possibilidade de calibração do fotômetro solar multibanda (FSM-4), desenvolvido para esse trabalho, que opera nas bandas de 500 nm, 670 nm 870 nm e 940 nm.  Investigou-se a estabilidade da profundidade óptica da atmosfera em um sítio na cidade de Caicó/RN, situada região semiárida do nordeste do Brasil. O sítio é uma região afastada de grandes centros e de atividades geradoras de poluição atmosférica. Foram coletados dados de irradiância solar direta em duas campanhas distintas durante o período seco, sendo uma em Dezembro de 2012 e outra em Setembro de 2013, para fins de calibração do protótipo. Para a calibração foram utilizados os métodos de Langley (ML) e método modificado de Langley (MLM), fazendo-se uso das medidas coletadas. Para as bandas de 500 nm, 670 nm e 870 nm, utilizadas para a medida da profundidade óptica por aerossóis (AOD), foi utilizado o ML e para a banda de 940 nm, na qual é medida a coluna de água precipitável (PWC) ou vapor de água na atmosfera, utilizou-se o MLM. Dentre os vários componentes constituintes da atmosfera, o vapor de água e os aerossóis são os que apresentam a maior variabilidade temporal, devido a fenômenos naturais e antropogênicos, e exercem um papel importante no balanço de energia do planeta. O que justifica os esforços para o desenvolvimento de um equipamento de baixo custo. Assim, por meio do ML e MLM aplicado aos dados coletados, foram observadas variabilidades na AOD e PWC para as quatro bandas, nos dois períodos estudados. Essa variabilidade da AOD e PWC no momento da coleta, que se dá por meio do espalhamento ou absorção da radiação solar na atmosfera, prejudicam o ajuste da reta aos dados e dificultando a obtenção da constante de calibração. Entretanto a região ainda não pode ser totalmente descartada como sítio de calibração, pois as campanhas foram de duração reduzida e as metodologias devem ser testadas em outros períodos do ano. Como alternativa para a calibração do fotômetro solar, foi feito um estudo de curta duração, junto ao fotômetro da rede mundial AERONET (AERsol RObotic NETwork), instalado em Petrolina/PE, da agência espacial americana (NASA). Foram coletados dados durante três dias com os instrumentos AERONET e FSM-4 operados simultaneamente no mesmo local. Por meio das técnicas de ML e MLM foram obtidos valores para teste das constantes de calibração. Foi observada uma convergência dos valores, apesar da pouca quantidade de dados coletados. A metodologia mostrou-se uma alternativa viável para a calibração do FSM-4.

A região Nordeste do Brasil (NEB) é susceptível a extremos climáticos devido à alta variabilidade temporal e espacial da precipitação. Vários estudos têm investigado tal variabilidade com o propósito de compreender os episódios danosos, como secas e enchentes. O fenômeno da seca no NEB configura-se por tratar-se de tema complexo por afetar milhões de pessoas e ser objeto de estudos em diversas áreas do conhecimento. Uma forma de tentar argumentar sobre esse fenômeno é utilizando o conceito de vulnerabilidade. Para mensurar um indicador de vulnerabilidade é necessário grande quantidade de dados de diferentes áreas do conhecimento, dentre as quais incluem-se a meteorologia, socioambiental, econômico, saúde pública, entre outros. O principal objetivo desse trabalho foi criar um indicador de vulnerabilidade à extremos climáticos (seca e inundação) para o NEB. Os dados que foram utilizados pertencem a ANA (Agência Nacional das Águas), IBGE (Instituto Brasileiro de Geografia e Estatística) e Ministério da Integração Nacional. Os resultados mostram que o sul da NEB apresentou os maiores indicadores de vulnerabilidade, sendo que parte do semiárido grau moderado, relacionando-se ao grau de exposição ou susceptibilidade a seca e sensibilidade agrícola nas áreas mais produtivas da região. Em relação ao fator incapacidade adaptativa AI, este não apresentou resultados significativos para a composição do indicador de vulnerabilidade.