Atmospheric convection is sensitive to the nature of the surface and its temperature. Both dry (without cloud) and moist (with cloud) convections depend on the surface temperature. Surface temperature is of critical importance in several practical applications like human comfort and crop cultivation. In the climate change scenario too, variations in the surface temperature take the center stage. Therefore, prediction of surface temperature is important. The evolution of the temperature is governed by the energy equation and the surface temperature by the surface energy balance. Important components of the surface energy balance are radiation (incoming solar radiation, reflected solar radiation, incoming and outgoing longwave radiation), sensible and latent heat fluxes and heat flux into the ground (called ground heat flux). A large number of individual and collective observations have been carried out in the past to understand the atmospheric boundary layer and the surface energy budgets. However a major share of the observations is from mid-latitudes. There have been few experiments carried out in India, for example, MONTBLEX, LASPEX, etc. One common drawback among these experiments is that the data time series is discontinuous and continuous measurements covering an entire season are lacking. Moreover these measurements were not comprehensive and hence did not allowed to calculate complete surface energy balance – in some cases radiation data is not available while in some humidity data. Therefore, continuous time series of sufficient duration and covering all variables needed to look at the seasonal energy balance based on measurements alone is missing in the Indian context. New programmes with the main objective of predicting convection are being planned in India. For example, PROWNAM (Prediction of Regional Weather with Observational Meso-Network and Atmospheric Modeling) is aimed at predicting the short term weather at SHAR and STORM (Severe Thunderstorms – Observations and Regional Modeling) aims to predict the occurrence of severe thunderstorms in the northeastern India. In both these programmes, measurement of all components of surface energy balance is one of the main objectives. However, the minimum configuration and data accuracy requirements for the flux towers, sensitivity of computed fluxes on data accuracy have not been carefully evaluated. This thesis is aimed at filling this gap. As a part of my work, a 10 m high micrometeorological tower was installed in an open area within the Indian Institute of Science (IISc) Air Field. Temperature, relative humidity and wind speed and direction instruments were mounted at two levels, 2 m and 8 m. All components of radiation were measured. Data, sampled every 5 s and averaged for 2 minutes were continuously stored, starting May 2006 onwards. Soil temperature was measured at 4 depths, 5 cm, 10 cm, 15 cm and 20 cm. In addition, a sonic anemometer capable of measuring 3 components of velocity and air temperature was installed at 2 m height, and data was collected for more than a month to enable the calculation of momentum and buoyancy fluxes using the Eddy correlation method (ECM). The present work evaluated the sensitivity of the fluxes for small calibration errors and quantified the minimum data accuracies and configuration needed for flux measurement with the Profile method (PM). After applying corrections, the comparison of fluxes from PM and ECM are in good agreement. The complete long-term surface energy balances is calculated in terms of source and sink. One aspect that emerges from the observation is that the seasonal variation in the sink term is relatively small (150-170 Wm-2) whereas the source term shows much larger variation from 180-250 Wm-2. A method has been implemented by which the ground surface temperature can be estimated by using the subsurface temperature timeseries by the method of Fourier decomposition and using the Fourier heat conduction equation. In addition we can compute the thermal diffusivity of the soil by using the amplitude and phase information of the sub-surface soil time series. The estimated temperatures from this method and one that estimated from radiation method are in good agreement with the maximum difference being less than 0º C.

I examined the hypothesis that high variability in Sea Surface Temperature (SST) and ocean color are associated with higher coral cover and slower rates of decline of coral cover within the Florida Keys National Marine Sanctuary (FKNMS). Synoptic SST time series maps, covering the period 1994-2005, were constructed for the FKNMS with data collected using the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite sensors. The SST data were compared with coral cover time series assessments at 36 sites conducted by the Coral Reef and Evaluation Monitoring Program (CREMP; 1996-2005), sponsored by the Environmental Protection Agency and the State of Florida. Out of the 36 stations, Smith Shoals routinely experienced very different and extreme environmental conditions relative to the rest of the stations, including extreme salinity, suspended sediments, and "black water" events that led to the death of coral reef organisms such as in 2002. Among the other 35 stations, sites that experienced moderately higher SST variability (mean variance > 6) relative to other sites showed a trend toward higher percentage coral cover (r=0.62, p=6.33x10-5, N=35) and relatively slower rates of decline (r=0.41, p=0.02, N=35) over the 12-year study period. The results suggest that coral reefs sites that are continuously exposed to high but not extreme variability in temperature may develop resilience against episodes of extreme cold or elevated SST. Variability of suspended sediments and water clarity were estimated using satellite-derived, normalized water-leaving radiance products. Ocean color data were obtained from the Sea-viewing Wide-Field-of View Sensor (Sea WiFS) from 1998 to 2005. Normalized water-leaving radiance at 443 (Lwn443) was used as a proxy to examine variability in water clarity, and normalized water-leaving radiance at 670 (Lwn670) was used as a proxy to study variability in suspended sediments. A weak relationship was identified between variability of Lwn443 and Lwn670 and coral cover as estimated by CREMP assessments in 2005 (r=0.43, p = 0.01, N=35 and r = 0.47, p = 0.005, N=35, respectively). There was a weak relationship between coral cover change and Lwn670 from 1988 to 2005 (r = 0.46, p = 0.05, N=35), but there no relationship was observed between variability of Lwn443 and change in coral cover (r =0.27, p =0.11, N=35). Further research is required to understand the origin, concentration and composition of dissolved or suspended materials that change the turbidity of waters around reefs of the FKNMS, and whether these changes can be adequately interpreted by examining concurrent satellite imagery. Ultimately, such remote sensing and field research is required to understand how water quality affects the health of coral reefs, and how coral ecosystems adapt to environmental variability.

The aim of this thesis is the modeling of surface directional thermal radiation and angular correction on the LST by using empirical and physical methods as well as the analysis of field validation. The work has conducted to some conclusions. The directional emissivity of natural surfaces was obtained from MODIS emissivity product and then used in the split-window algorithm for angular correction on LST. The parameterization models of directional emissivity and thermal radiation were developed. As for the non-isothermal pixels, the daytime-TISI method was proposed to retrieve directional emissivity and effective temperature from multi-angular middle and thermal infrared data. This was validated using an airborne dataset. The kernel-driven BRDF model was checked in the thermal infrared domain and its extension was used to make angular normalization on the LST. A new model, namely FovMod that concerns on the footprint of ground sensor, was developed to simulate directional brightness temperature of row crop canopy. Based on simulation result of the FovMod, an optimal footprintfor field validation of LST was obtained. This thesis has systematically investigated the topic of directional thermal radiation and angular correction on surface temperature and its findings will improve the retrieval accuracy of temperature and emissivity from remotely sensed data and will also provide suggestion for the future design of airborne or spaceborne multi-angular thermal infrared sensors and also for the ground measurement of surface parameters.

Ocean uptake of anthropogenic CO2 causes ocean acidification, a secular, global-scale decline in the pH of seawater. In order to better understand the implications of contemporary acidification for marine organisms and ecosystems, there is a need to better characterise natural variability in carbonate chemistry. In this thesis, climatological seasonal variability of sea surface pH and aragonite saturation state (OmegaA) in the open ocean is indirectly derived from other parameters of the marine CO2 system, namely total alkalinity (TA) and seawater pCO2/fCO2 (pCO2sw/fCO2sw). New monthly sea surface TA, fCO2sw and temperature climatologies are developed for this purpose, utilising newly-released observational synthesis products (PACIFICA for TA and SOCAT v2 for fCO2sw). Two versions of the new SST climatology are developed, referred to as upper and lower SST (USST and LSST), to test sensitivity to the depth range of the input observations. Annual ranges are generally found to be larger for the USST climatology, derived using observations from the upper 2 m, compared to LSST (which is based on deeper observations). Further, a seasonal cycle is found in the monthly average of the differences between these climatologies north of 30 degN, perhaps partly due to seasonal variation in near-surface stratification. The USST seasonal ranges are also found to be generally larger than in two previous SST climatologies, however, difference in the depth distribution of the input measurements is unlikely the main cause. The new monthly sea surface TA climatology extends coverage into the Nordic seas, excluded from previous climatologies. TA seasonality is found to be small outside of regions with large seasonal ranges in salinity. Large seasonal ranges in salinity and TA are found beneath the Intertropical Convergence Zone, in the Antarctic seasonal sea ice zone and in the western Greenland Sea. Non-salinity driven TA seasonality is found to be large in the Gulf of Alaska, eastern equatorial Pacific and western Greenland Sea. Compared to the Lee et al. (2006) TA climatology, substantially lower annual means and seasonal ranges are found for the subarctic Pacific, a region with greatly improved coverage courtesy of PACIFICA. The pH/OmegaA climatologies derived in the final chapter suggest pH seasonality is predominantly temperature driven in the subtropics and mainly driven by variation in salinity normalised dissolved inorganic carbon (sDIC) in the subpolar north Atlantic, western subarctic Pacific and Southern Ocean. Salinity variation is found to only exert a strong influence on pH seasonality in the western Greenland Sea. Climatological seasonal pH ranges are found to be mostly small in the tropics (<0.05), moderate in the subtropics (0.05-0.10) but very large (>0.1) in parts of the Ross, Weddell, Irminger and Iceland Seas and western subarctic Pacific gyre. OmegaA seasonality is found to be predominantly sDIC-driven everywhere except in the western Greenland Sea, with temperature variation generally being of modest influence. Seasonal cycles of pH and OmegaA are found to be in anti-phase where pH is mainly thermally driven and in-phase where pH is mainly sDIC-forced (both pH and OmegaA vary inversely with DIC). Comparison is made between the primary new pH/OmegaA climatology and various open ocean carbonate chemistry time-series. The climatology captures the general form of the climatological seasonal cycles of pH and OmegaA from the time-series, although with some differences in phasing and seasonal range. Analysing the time-series for long-term trends, I find that inter-decadal anthropogenic CO2 uptake driven pH and OmegaA declines can be modulated by trends in temperature, salinity or sTA. Investigation is also conducted into how the amplitude of pH and OmegaA seasonal cycles might change by 2100 for a subpolar and subtropical time-series. Under a high CO2 emissions scenario, the seasonal range of pH is found to be strongly enhanced for the subpolar time-series and moderately reduced for the subtropical time-series, with both being due to changes in seawater buffer capacity. / Graduate / 0425 / 0415 / robdj87@hotmail.com

Devido às características geopolíticas do Brasil, a obtenção de estimativas agrícolas confiáveis é de fundamental importância para o país proporcionando a manutenção do equilíbrio entre oferta e demanda na cadeia produtiva de alimentos. Os Estados do Mato Grosso e Rio Grande do Sul são dois grandes produtores de soja no Brasil, ocupando a primeira e a terceira posição respectivamente, e apresentam características climáticas e ecoregionais bem diferenciadas. Tipicamente, dados de imagens dos satélites Terra do programa EOS-MODIS (Earth Observing System- Moderate Resolution Imaging Spectroradiometer), e dos satélites NOAA (National Oceanic and Atmospheric Administration) têm sido utilizadas em aplicações do monitoramento do ciclo de desenvolvimento das culturas e estimativa da produção agrícola. Em busca da estruturação de modelos de caráter prognóstico, inteiramente baseados em dados de sensoriamento remoto, este estudo visa explorar a combinação entre o EVI (Enhanced Vegetation Index - ou Índice de vegetação realçado), produto MOD13Q1-V005 e a LST (Land Surface Temperature – ou Temperatura da Superfície Terrestre), produto MYD11A2-V005 na estimativa da produtividade da soja. Nesse sentido, o objetivo nesta Tese foi aprofundar o conhecimento sobre os efeitos conjugados do estresse hídrico e da ocorrência de temperaturas elevadas no dossel da vegetação como contribuição ao avanço dos modelos espectrais de estimativa da produção. A abordagem inicial foi desenvolver um modelo espectral acoplado CM (Coupled Model) a partir do MCDA (MODIS Crop Detection Algorithm – ou Algoritmo de Detecção de Área Agrícola por MODIS) e do MPDM (MODIS Productivity Detection Model – ou Modelo de Detecção de Produtividade da Soja por MODIS), que utilizam apenas dados EVI como variáveis de entrada. Os resultados do modelo acoplado de estimativa da produção foram comparados com dados provenientes do IBGE (Instituto Brasileiro de Geografia e Estatística) e de precipitação ocorrida proveniente do INMET (Instituto Nacional de Meteorologia), entre 2001 e 2011 para os Estados do Mato Grosso e Rio Grande do Sul. Os dois Estados apresentaram tendências semelhantes com aderência aos dados oficiais em nível estadual e municipal. Para o Mato Grosso o modelo acoplado CM, obteve estimativas de R2=0,96 e RMSD=47.878 toneladas em nível municipal. Testes de validação adicionais foram realizados na safra 2006, utilizando dados de campo, em que se obteve R2=0,88 e RMSD=104 toneladas. Para o Rio Grande do Sul foi obtido R2=0,91 e RMSD=10.841 toneladas em nível municipal. Na análise da relação entre LST sobre o dossel da vegetação agrícola e produtividade, Mato Grosso e Rio Grande do Sul apresentaram respostas divergentes. O Mato Grosso apresentou uma relação matemática direta entre LST-dossel e produtividade, com R2=0,60 e RMSD=6,2%. No Rio Grande do Sul foi observado uma relação matemática inversa, com R2=0,73 e RMSD=17,8%. Os resultados mostram que a quantidade da precipitação acumulada, no período da safra de verão, desempenha papel fundamental na manutenção do equilíbrio da demanda evaporativa quando ocorrem temperaturas elevadas sobre o dossel da vegetação. / Reliable agricultural estimates are important for most countries, and crucial for Brazil, due to its geopolitical characteristics derived from a vast territory. Good estimates ensure a balance between offer and needs inside the food chain production. The States of Mato Grosso and Rio Grande do Sul are large soybean producers, ranking first and third respectively in Brazil, and present quite different climatic and ecological characteristics. As an alternative to conventional estimation methods, soybean crops have been monitored and grain production estimated using Remote Sensing data with sources as EOS-MODIS (Earth Observing System-Moderate Resolution Imaging Spectroradiometer) from Terra satellite and also from the NOAA (National Oceanic and Atmospheric Administration) satellites. This work aimed to the development of forecasting models completely based in Remote Sensing data, by integrating information on EVI (Enhanced Vegetation Index), product MOD13Q1-V005, and LST (Land Surface Temperature), produto MYD11A2-V005, to estimates of soybean yield. More precisely, the objective of this work was to advance the knowledge on the superposed effects of water stress and high temperatures on the vegetation canopy, as a contribution to the development of spectral models for production estimates. The starting approach was to develop a coupled spectral model (CM - Coupled Model), from the MCDA (MODIS Crop Detection Algorithm) and from the MPDM (MODIS Productivity Detection Model), which use only EVI data as input variables. The production estimates, as results of this Coupled Model, were compared with similar data from IBGE (Instituto Brasileiro de Geografia e Estatística) and matched with records on precipitation from INMET (Instituto Nacional de Meteorologia) between 2001 and 2011 for Mato Grosso and Rio Grande do Sul States. For both States the application of the coupled model produced results close to the official data at state and county levels. For Mato Grosso, correlations of CM with official data were R2=0.96 and RMSD=47,878 metric tons at county level. Additional validation tests were performed for the 2006 crop, using field data, producing R2=0.88 and RMSD=104 metric tons. For Rio Grande do Sul results were R2=0.91 and RMSD=10,841 metric tons at municipality level. In the analysis on the relationship between canopy LST and yield, Mato Grosso and Rio Grande do Sul presented opposite results. Mato Grosso showed a direct mathematical correlation between canopy LST and yield, with R2=0.60 and RMSD=6.2%. For Rio Grande do Sul an inverse mathematical expression was derived, with R2=0.73 and RMSD=17.8%. These results show that the accumulated precipitation during the summer crops is crucial to maintain a balance of the evaporative demand when the vegetation canopy is exposed to high temperatures.

La température de surface de l'océan (SST) est depuis l'avènement des satellites, l'une des variables océaniques la mieux observée. Les modèles réalistes de circulation générale océanique ne la prennent pourtant pas en compte explicitement dans leur fonction de forçage. Dans cette dernière, seules interviennent les variables atmosphériques à proximité de la surface (température, humidité, vitesse du vent, radiations descendantes et précipitations) connues pour être entachées d'incertitudes importantes dès lors qu'on considère l'objectif d'étudier la variabilité à long terme de l'océan et son rôle climatique. La SST est alors classiquement utilisée en assimilation de données pour contraindre l'état du modèle vers une solution en accord avec les observations mais sans corriger la fonction de forçage. Cette approche présente cependant les inconvénients de l'incohérence existant potentiellement entre la solution « forcée » et « assimilée ». On se propose dans cette thèse de développer dans un contexte réaliste une méthode d'assimilation de données de SST observée pour corriger les paramètres de forçage atmosphérique sans correction de l'état océanique. Le jeu de forçage faisant l'objet de ces corrections est composé des variables atmosphériques issues de la réanalyse ERAinterim entre 1989 et 2007. On utilise pour l'estimation de paramètres une méthode séquentielle basée sur le filtre de Kalman, où le vecteur d'état est augmenté des variables de forçage dont la distribution de probabilité a priori est évaluée via des expériences d'ensemble. On évalue ainsi des corrections de forçage mensuelles applicables dans un modèle libre pour la période 1989-2007 en assimilant la SST issue de la base de données de Hurrel (Hurrel, 2008), ainsi qu'une climatologie de salinité de surface (Levitus, 1994). Cette étude démontre la faisabilité d'une telle démarche dans un contexte réaliste, ainsi que l'amélioration de la représentation des flux océan-atmosphère par l'exploitation d'observations de la surface de l'océan. / Sea surface temperature (SST) is more accurately observed from space than near-surface atmospheric variables and air-sea fluxes. But ocean general circulation models for operational forecasting or simulations of the recent ocean variability use, as surface boundary conditions, bulk formulae which do not directly involve the observed SST. In brief, models do not use explicitly in their forcing one of the best observed ocean surface variable, except when assimilated to correct the model state. This classical approach presents however some inconsistency between the “assimilated” solution of the model and the “forced” one. The objective of this research is to develop in a realistic context a new assimilation scheme based on statistical methods that will use SST satellite observations to constrain (within observation-based air-sea flux uncertainties) the surface forcing function (surface atmospheric input variables) of ocean circulation simulations. The idea is to estimate a set of corrections for the atmospheric input data from ERAinterim reanalysis that cover the period from 1989 to 2007. We use a sequential method based on the SEEK filter, with an ensemble experiment to evaluate parameters uncertainties. The control vector is extended to correct forcing parameters (air temperature, air humidity, downward longwave and shortwave radiations, precipitation, wind velocity). Over experiments of one month duration, we assimilate observed monthly SST products (Hurrel, 2008) and SSS seasonal climatology (Levitus, 1994) data, to obtain monthly parameters corrections that we can use in a free run model This study shows that we can thus produce in a realistic case, on a global scale, and over a large time period, an optimal flux correction set that improves the forcing function of an ocean model using sea surface observations.

Submitted by Leonardo Cavalcante (leo.ocavalcante@gmail.com) on 2018-04-17T16:12:32Z No. of bitstreams: 1 Arquivototal.pdf: 5868651 bytes, checksum: e5d4ddb02a065600f83257ded96722d7 (MD5) / Made available in DSpace on 2018-04-17T16:12:32Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 5868651 bytes, checksum: e5d4ddb02a065600f83257ded96722d7 (MD5) Previous issue date: 2015-03-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The practices of soil usage and occupation generate severe deterioration processes and in semiarid areas may result in desertification. In Paraiba, one of the areas representing this process is the one named “Cariris Velhos”. Through a multitemporal analysis, aided by statistical techniques and geotechnologies, it was possible to carry out some analysis and to diagnose the desertification state. Descriptive analysis, non-parametric test and multivariate statistics techniques were used. The precipitation was used and revealed three important patterns that explain about 70% of data variability, exposing how the rainfall occurred in the years of the images, making visible the rainy occurred, drought and transitioning periods. It was possible to confirm the edaphoclimatic frailty existent and the strong correlation with the climate anomalies (El Niño and La Niña) caused by meteorological systems. The second aspect to be analyzed was the vegetation coverage, defined in different strata and surface temperature. Three timed clippings were selected to compose these aspects: images from the 80’s (1989, 1985), from the 90’s (1990 and 1995) and of the 2000 years (2004,2005 and 2007). The images processing was done with part of algorithm SEBAL which were determined SAVI, IAF and Surface Temperature. SAVI and IAF were obtained, however, owing few studies with IAF for semiarid was decided to used. The results have shown that the vegetation strata diminished gradually, from a moderate stage to a severe one, with coefficient of variation (56%, 78,75% e 84%) unrepresentative, proving the diversity of landscapes. A significant amount of municipalities, on the last clipping, already presented, in its majority, more than 50% of values of the pixels presented in the classes of exposed soil, that is, with accentuated deterioration, proving strong evidence of desertification. With the deforestation, the surface temperature increased significantly configuring a higher number of pixels presented in classes superior to 30ºC. This factor, allied to the rainfall, hampers the development and spreading of species, since seed dispersal is by anemochory, diminishing the biodiversity of the caatinga. Concerning the agricultural, economic and social aspects, three profiles were revealed for each clipping, showing the most important indicators on each one. With this, it was observed that between 1980 and 1995, the population was more dependent of the land, in a way that when there was a worsening in the physical plan, a diminishing in the rainfall, the production also diminished, directly affecting social and economically the population. Between 2000 and 2010, the governmental incentives contribute to an improvement of these aspects so that they did not contribute, not directly, for the process of desertification, configuring a smaller impact (weight) on the analysis. In this case, the deterioration is originated from the agricultural aspect, being an example the incentive to the goatrearing and wood extraction to the plaster polo of Pernambuco in some municipalities of the “Cariris Velhos” region. / As práticas de uso e ocupação do solo geram processos de degradação intensa e em regiões semiáridas podem culminar na desertificação. Na Paraíba, uma das áreas representativas desse processo é a delimitação denominada de Cariris Velhos. Através de uma análise multitemporal, com o auxílio de algumas técnicas estatísticas e das geotecnologias, foi possível realizar algumas análises e diagnosticar o quadro da desertificação. Foram utilizadas análises descritivas, teste não paramétrico e a técnica da estatística multivariada: análise fatorial em componentes principais. Utilizou-se a precipitação pluviométrica que revelou três padrões importantes que explicaram cerca de 70% da variabilidade dos dados cada, expondo a forma como a chuva ocorreu para os anos das imagens, tornando visíveis períodos chuvosos, secos e de transição. Pôde-se comprovar a fragilidade edafoclimática existente e a forte relação com as anomalias climáticas (El Niño e La Niña) provocadas por sistemas meteorológicos. O segundo aspecto a ser analisado foi a cobertura vegetal, definida em diferentes estratos, e a temperatura da superfície. Foram selecionados três recortes temporais para compor esses aspectos: imagens da década de 80 (1989, 1985), da década de 90 (1990 e1995) e dos anos 2000 (2004, 2005 e 2007). O processamento das imagens foi feito com parte do algoritmo SEBAL onde foram determinados o SAVI, o IAF e a Temperatura da Superfície. Foram gerados o SAVI e IAF, entretanto, devido a poucos trabalhos realizados com o IAF para o semiárido considerou-se utilizá-lo. Os resultados mostraram que os estratos de vegetação diminuíram gradativamente, passando para um estágio moderado para muito grave, com coeficientes de variação (56%, 78,75% e 84%) pouco representativos, comprovando a diversidade de paisagens. Boa parte dos municípios, no último recorte, já apresentava, em sua maioria, mais de 50% dos valores dos pixels presentes nas classes de solo exposto, isto é, com degradação acentuada, comprovando forte evidencia de desertificação. Com o desmatamento, a temperatura da superfície aumentou significativamente passando a configurar um maior número de pixels presentes em classes superiores aos 30ºC. Este fator, aliado ao quadro de chuvas, dificulta o desenvolvimento e a propagação de espécies, uma vez que a dispersão das sementes se dá por anemocoria, o que diminui a biodiversidade da caatinga. Em relação aos aspectos agropecuários, econômicos e socais, foram revelados três perfis, para cada recorte, mostrando os indicadores mais importantes em cada um. Com isso, observou-se que entre 1980 e 1995, a população dependia mais da terra, de forma que uma piora no quadro físico, na diminuição no quadro de chuvas, diminuía a produção, refletindo diretamente no econômico e no social e deste modo na população. Entre 2000 e 2010, os incentivos governamentais contribuíram para a melhora desses aspectos de forma que eles passaram a não contribuir, diretamente, para o processo de desertificação, configurando um menor impacto (peso) na análise. Neste caso, a degradação é mais proveniente do aspecto agropecuário, tendo como exemplo o incentivo a caprinocultura e a extração da madeira para o polo gesseiro de Pernambuco, em alguns municípios dos Cariris Velhos.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Between 3-12 December 2012, the Oceanographic Vessel Alpha Crucis held oceanographic stations in the Southwestern Atlantic Ocean in support to both SAMOC (South Atlantic Meridional Overturning Circulation) and ACEx (Atlantic Ocean Carbon Experiment) projects. During the research cruise, the vessel performed 19 measurements with the release of weather balloons with radiosondes. From the data collected by the radiosondes, it was possible to verify the variability of the marine atmospheric boundary layer (MABL) over different synoptic conditions occurring in the area and period of study. From meteorological and oceanographic data collected throughout the trajectory of the ship by an automatic weather station and the onboard termosalinograph, it was possible to estimate the latent and sensible heat fluxes between the ocean and the atmosphere from bulk parameterization. In order to better understand the importance of the local forcing mechanisms imposed by the sea surface temperature (SST) and the large-scale forcing by the current synoptic conditions in the study period, 19 measurements were divided into four transects along the complete ship's trajectory, where the data were grouped with respect to the active synoptic weather conditions in the study area. Our results demonstrate that in the absence of large-scale transient systems acting in the study area, the MABL was modulated by the SST field. This was observed in the first transect, were we found a thick and turbulent MABL with its top at around 600 m and more intense heat fluxes (up to 209 W/m² of latent heat and 47 W/m² of sensible heat) mainly over the warm waters associated with the Brazil Current (BC). Over cooler waters of the transect, outside the domain of the BC, the MABL was shallower, around 200 m, with less intense heat fluxes (up to 1.4 W/m² of latent heat and -16.8 W/m² of sensible heat). In the second transect with the formation of an extratropical cyclone in the La Plata river mouth region, we noted the impact of the synoptic atmospheric conditions influencing the evolution of the MABL during the prefrontal condition when a MABL stratification was verified. During the pos frontal situation, the MABL was a well developed one, with a 1200 m height. In the pos frontal environment, latent heat fluxes (average 290 W/m² with a peak of 468 W/m²) and sensible heat fluxes (average of 18 W/m² with a peak of 45 W/m²) indicate a heat flux directed from the ocean to the atmosphere much more intense in his latent component. On the other hand, in the prefrontal region, lower values of the latent heat fluxes (average of 18 W/m² with a minimum of 15.8 W/m²) and sensible heat fluxes (-63.4 W/m²) were found. During the third transect with the incursion of the warm air mass, the MABL became shallower over the cooler waters of the Brazilian Coastal Current. Along of the entire third transect the SST was lower than the air temperature and this transect presented a stable boundary layer. Throughout the fourth and final transect, there was a secondary cyclogenesis off the coast of the Rio Grande do Sul state in southern Brazil, just north of the cyclone that has been formed in the vicinity of the La Plata river mouth. This cyclone has developed rapidly and has moved toward the Southwestern Atlantic Ocean, leaving the study area in the cold sector of the cyclone. With the incursion of the cold air mass, the MABL become thicker and more turbulent with its top around 600 m. The values of latent heat fluxes ranged between 461.2 W/m² over the warm waters associated with the BC and 30.2 W/m² on the cooler waters outside the domain of the BC. This work offers an analysis of movel meteorological and oceanographic observations taken simultaneously in the Southwestern Atlantic Ocean. These observations are fundamental to widen our understanding on the physical processes occurring at the ocean-atmosphere interface and have primary importance for the weather and climate forecast of the south-southwestern region of Brazil. / Entre os dias 3 a 12 de dezembro de 2012, o Navio Oceanográfico Alpha-Crucis realizou estações oceanográficas no Oceano Atlântico Sudoeste em apoio aos projetos SAMOC (South Atlantic Meridional Overturning Circulation) e ACEx (Atlantic Ocean Carbon Experiment). Durante o cruzeiro de pesquisa, o navio realizou 19 medições, com o lançamento de balões meteorológicos com radiossondas. A partir dos dados coletados pelas radiossondas, foi possível verificar a variabilidade da camada limite atmosférica marinha (CLAM) durante distintas condições sinóticas atuantes na área e período de estudo. A partir de dados meteorológicos e oceanográficos coletados ao longo de toda a derrota do navio através da estação meteorológica automática e do termosalinógrafo de bordo, foi possível estimar os fluxos de calor latente e sensível entre o oceano e a atmosfera a partir de parametrizações bulk. Para entender a importância dos mecanismos de forçamento local impostos pela temperatura da superfície do mar (TSM) e de grande escala imposto pelas condições sinóticas vigentes no período de estudo, as 19 medições foram divididas em 4 transectos realizados ao longo da trajetória, onde os dados foram agrupados com respeito às condições atmosféricas sinóticas atuantes. Os resultados do trabalho demonstram que, na ausência de sistemas transientes de grande escala atuantes na região de estudo, a CLAM foi modulada pelo campo de TSM. Isso foi observado no primeiro transecto, onde a CLAM apresentou-se espessa e turbulenta com seu topo em torno de 600 m e com fluxos de calor mais intensos (chegando até 209 W/m² de calor latente e 47 W/m² de calor sensível) principalmente sobre as águas quentes associadas à Corrente do Brasil (CB). Sobre águas mais frias, a CLAM foi mais rasa, em torno de 200 m e com fluxos de calor menos intensos (chegando até 1,4 W/m² de calor latente e -16,8 W/m² de calor sensível). No segundo transecto, com a formação de um ciclone extratropical, nota-se o impacto das condições sinóticas influenciando a evolução da CLAM durante a condição pré-frontal, onde se verificou uma estratificação da CLAM. Na condição pós-frontal, a CLAM apresentou-se bem desenvolvida, com uma altura de 1200 m e os fluxos de calor latente (média de 290 W/m² e com pico de 468 W/m²) e calor sensível (média de 18 W/m² e com pico de 45 W/m²) indicam um fluxo de calor do oceano para a atmosfera muito mais intenso em sua componente latente. Por outro lado, na região pré-frontal, valores mais baixos de fluxos de calor latente (média de 18 W/m² e com um mínimo de -15,8 W/m²) e calor sensível (-63,4 W/m²) foram encontrados. Durante o terceiro transecto com a incursão da massa de ar quente, a CLAM ficou mais rasa sobre as águas mais frias da Corrente Costeira do Brasil. Ao longo de todo o terceiro transecto a TSM esteve menor que a temperatura do ar e esse apresentou uma camada limite estável. Ao longo do último transecto, verificou-se uma ciclogênese secundária na costa do Rio Grande do Sul, imediatamente ao norte do ciclone que havia se formado nas proximidades da desembocadura do Rio da Prata. Esse se desenvolveu rapidamente e se deslocou para o Oceano Atlântico Sudoeste, deixando a região de estudo sob o setor frio do ciclone. Com a incursão da massa de ar frio, a CLAM ficou mais espessa e turbulenta com seu topo em torno de 600 m. Os valores dos fluxos de calor latente variaram entre 461,2 W/m² sobre as águas quentes associadas à da CB e 30,2 W/m² sobre as águas mais frias fora do domínio dessa. Esse trabalho oferece uma análise de observações meteorológicas e oceanográficas inéditas tomadas simultaneamente no Oceano Atlântico Sudoeste. Essas observações são fundamentais para ampliar o entendimento dos processos físicos que ocorrem na interface oceano-atmosfera e tem importância primária para a previsão do tempo e clima na região sul-sudeste do Brasil.

Submitted by Viviane Lima da Cunha (viviane@biblioteca.ufpb.br) on 2017-04-20T11:23:36Z No. of bitstreams: 1 arquivototal.pdf: 8351291 bytes, checksum: 9c34c27730ae5014b89097e887df8ee5 (MD5) / Made available in DSpace on 2017-04-20T11:23:36Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 8351291 bytes, checksum: 9c34c27730ae5014b89097e887df8ee5 (MD5) Previous issue date: 2016-03-31 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The recent process of city urbanization has intensified the changes in the land use and occupation, causing various environmental impacts from the transformation of the natural environment without planning. Among the environmental impacts there is the reduction of vegetation cover areas, occurrence of floods, air pollution and rising temperatures. Urban areas of cities tend to have higher temperatures than the areas to their surroundings and the very urban area, this phenomenon is called heat islands. Various techniques have been used to analyze the influence of the use and occupation of land in the heat island phenomenon, among them stands out the use of geotechnology for the Remote Sensing and Geographic Information Systems (GIS). In this perspective, this study aims to analyze the influence of land use and occupation in the emergence of heat islands in the city Paço do Lumiar – MA. The Delimitation of the study area analyzed in this study area analyzed in this research is justified by the fact present: (1) quick growth of urban population, (2) expansion of the urban network and (3) severe change of use and occupation of land. To develop this research, were adopted using techniques of remote sensing, digital processing of satellite imagery in a GIS environment. These techniques were used to classify the use and occupation of land and estimation of biophysical parameters: vegetation index (NDVI, IVAS and LAI), albedo, surface temperature (°C) and net radiation (W/m²). The results of the land use and occupancy classification showed that in 1988 the urban area occupied a total of 10.84 square kilometers and in 2014 rose to 22.47 km². The albedo values ranged from 0.06 to 1.02. The lowest values of albedo were found in areas with presence of water and vegetation cover higher density and higher values in more densely urbanized areas without vegetation. The analysis of NDVI of the spatio-temporal variation, IVAS and LAI occurred to the surface showed clear reduction of the class of higher values of vegetation, showing the replacement of vegetation by areas with greater urbanization, the lowest values of vegetation indices are observed mainly in the southwest portion of the city, area where are located the most densely occupied neighborhoods, like the Maiobão the neighborhood. It was verified that the surface temperatures showed certain pattern of spatial variation, above all, time. In dates analyzed surface temperature ranged from 23 to 37 °C, the lowest values were observed in class and vegetation water of higher density, showing that areas with greater availability of water and the presence of vegetation. The estimated net radiation revealed that the highest values of net radiation are found on areas with presence of dense vegetation and water bodies and the lowest values in the urban classes and shrub/herbaceous, with values ranging from 450 to 736 W/m² . The results of multi-temporal analysis of the use and occupation of the land made it possible to evaluate the influence of vegetation cover and fragmentation on the urban environment of the study area and contributed to data acquisition for monitoring environmental quality. / O processo de urbanização recente das cidades tem intensificado as modificações do uso e ocupação da terra, ocasionando diversos impactos ambientais oriundos da transformação do meio natural sem planejamento. Dentre os impactos ambientais, destaca-se a redução das áreas com cobertura vegetal, ocorrência de enchentes, poluição do ar e aumento das temperaturas. As zonas urbanas das cidades tendem a apresentar temperaturas mais elevadas do que as áreas ao seu entorno e na própria área urbana, este fenômeno é denominado de ilhas de calor. Várias técnicas têm sido utilizadas para analisar a influência do uso e ocupação da terra no fenômeno de ilhas de calor, entre elas destaca-se o uso das geotecnologias referentes ao Sensoriamento Remoto e aos Sistemas de Informações Geográficas (SIG). Nessa perspectiva, este estudo tem como objetivo analisar a influência do uso e ocupação da terra no surgimento de ilhas de calor na cidade de Paço do Lumiar - MA. A delimitação da área de estudo analisada nesta pesquisa se justifica pelo fato de apresentar: (1) crescimento acelerado da população urbana, (2) expansão da malha urbana e (3) intensa alteração do uso e ocupação da terra. Para desenvolver desta pesquisa, foram adotados o uso de técnicas de sensoriamento remoto, processamento digital de imagens de satélite em ambiente SIG. Essas técnicas foram utilizadas para a classificação do uso e ocupação da terra e estimativa dos parâmetros biofísicos: índices de vegetação (IVDN, IVAS e IAF), albedo, temperatura da superfície (°C) e saldo de radiação (W/m²). Os resultados da classificação de uso e ocupação da terra mostraram que em 1988 a área urbana ocupava um total de 10,84 km² e em 2014 passou para 22,47 km². Os valores do albedo variaram entre 0,061,02. Os menores valores do albedo foram encontrados em áreas com presença de água e com cobertura vegetal de maior densidade e os maiores valores em áreas mais densamente urbanizada e sem cobertura vegetal. A análise da variação espaço-temporais do IVDN, IVAS e IAF ocorridas à superfície, demonstrou clara diminuição da classe dos valores mais elevados de vegetação, evidenciando a substituição da cobertura vegetal por áreas com maior urbanização. Os menores valores dos índices de vegetação são observados principalmente na porção sudoeste do município, área onde estão localizados os bairros mais densamente ocupados, a exemplo o bairro do Maiobão. Pôde-se verificar que as temperaturas de superfície apresentaram certo padrão de variação espacial, sobretudo, temporal. Nas datas analisadas a temperatura de superfície variou de 23 a 37°C, cujos menores valores são observados na classe de água e vegetação de maior densidade, evidenciando que áreas com maior disponibilidade de água e presença de vegetação podem contribuir para a amenização dos efeitos de anomalias térmicas como as ilhas de calor. A estimativa do saldo de radiação revelou que os maiores valores do saldo de radiação são encontrados sobre áreas com presença de vegetação densa e corpos hídricos e os menores valores nas classes urbano e vegetação arbustiva/herbácea, com valores variaram de 450 a 736 W/m². Os resultados da análise multitemporal do uso e ocupação da terra possibilitaram avaliar a influência da cobertura vegetal e sua fragmentação sobre o ambiente urbano da área de estudo e contribuíram para aquisição de dados para monitoramento da qualidade ambiental.

Evapotranspiration (ET) is a significant hydrological process. It can be studied and estimated using remote sensing based methods at multiple spatial and temporal scales. Most commonly and widely used remote sensing based methods to estimate actual evapotranspiration (AET) are a) methods based on energy balance equations, b) vegetation coefficient based method and c) contextual methods. These three methods require reflectance and land surface temperature (LST) data measured at optical and thermal portion of the electromagnetic spectrum. However, these data are available only for clear sky conditions and fail to be retrieved under overcast conditions creating gaps in the data, which result in discontinuous of AET product. Moreover, energy balance equation based methods and evaporative fraction (EF) based contextual methods are difficult to apply over overcast conditions. In this context, vegetation coefficient based (Tasumi et al., 2005; Allen et al., 2005) and microwave remote sensing based methods can be applied under cloudy sky conditions (Sun et al., 2012), since microwave radiations can penetrate through clouds, but these data are available at coarse resolution. In the vegetation coefficient method temporal upscaling can be avoided. Therefore in this research vegetation coefficient based method is employed over Cauvery basin to estimate daily AET for clear and cloudy sky conditions. Required critical variables for this method such as reference evapotranspiration (ETo) and vegetation coefficients are obtained using LST and optical vegetation indices for all sky conditions. In this study, all sky conditions refer to both clear and cloudy sky conditions. Most important variable for estimation of ETo using radiation and temperature based models is air temperature (Ta). In this study, for better accuracy of Ta, two satellite based approaches namely, Temperature Vegetation Index (TVX) and Advance Statistical Approaches (ASA) were evaluated. In the TVX approach, in addition to traditional Normalized Difference Vegetation Index (NDVI), other vegetation indices such as Enhanced Vegetation Index (EVI) and Global Vegetation Moisture Index (GVMI) were also examined. In case of ASA, bootstrap technique was used to generate calibration and validation samples and Levenberg Marquardt algorithm was used to find the solution of the models. The better of the Ta results obtained out of these two approaches were employed in the ETo models and are referred as Ta based ETo models. Instead of Ta, processed LST data obtained directly from the satellite (Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS)) was applied in the ETo models and these are referred as LST based ETo models. These Ta and LST based Hargreaves-Samani (H-S), Makkink (Makk) and Penman Monteith Temperature (PMT) models were evaluated by comparing with the FAO56 PM model. Additionally, simple LST based equation (SLBE) proposed by Rivas et al. (2004) was also examined. Required solar radiation (Rs) data for ETo estimation was obtained from Kalpana1/VHRR satellite data. Results implied that, Ta based PMT model performed better than the Ta based H-S, Makk and SLBE with less RMSE, MAPE and MBE values for all land cover classes and for various climatic regions for clear sky conditions. LST based H-S, PMT, Makk and Ta based Makkink advection models predominantly overestimated ETo for the study region. In the case of TVX approach, to estimate maximum Ta (Tmax), GVMI performed better than NDVI and EVI. Nevertheless, TVX approach poorly estimated Tmax in comparison with statistical approach. ASA performed better for both Tmax and minimum Ta. This study demonstrates the applicability of satellite based Ta and ETo models by considering very few variables for clear sky conditions. Spatially distributed vegetation coefficients (Kv) data with high temporal resolution is another important variable in vegetation coefficient method for daily AET estimation and also it is in demand for crop condition assessment, irrigation scheduling, etc. But available Kv models application hinders because of two main reasons i.e 1) Spectral reflectance based Kv accounts only for transpiration factor but not evaporation, which fails to account for total AET. 2) Required optical spectral reflectances are available only during clear sky conditions, which creates gaps in the Kv data. Hence there is a necessity of a model which accounts for both transpiration and evaporation factors and also gap filling method, which produces accurate continuous quantification of Kv values. Therefore, different combinations of EVI, GVMI and temperature vegetation dryness index (TVDI) have been employed in linear and non linear regression techniques to obtain best model. This best Kv model had been compared with Guershman et al. (2009) Kv model. To fill the gaps in the data, initially, temporal fitting of Kv values have been examined using Savitsky-Goley (SG) filter for three years of data (2012 to 2014), but this fails when sufficient high quality Kv values were unavailable. In this regard, three gap filling techniques namely regression, Artificial Neural Networks (ANNs) and interpolation techniques have been analyzed. Microwave polarization difference index (MPDI) has been employed in ANN technique to estimate Kv values under cloudy sky conditions. The results revealed that the combination of GVMI and TVDI using linear regression technique performed better than other combinations and also yielded better results than Guershman et al. (2009) Kv model. Furthermore, the results indicated that SG filter can be used for temporal fitting and for filling the gaps, regression technique can be used as it performed better than other techniques for Berambadi station. Land Surface Temperature (LST) with high spatiotemporal resolution is required in the estimation of ETo to obtain AET. MODIS is one of the most commonly used sensors owing to its high spatial and temporal availability over the globe, but is incapable of providing LST data under cloudy conditions, resulting in gaps in the data. In contrast, microwave measurements have a capability to penetrate under clouds. The current study proposes a methodology by exploring this property to predict high spatiotemporal resolution LST under cloudy conditions during daytime and night time without employing in-situ LST measurements. To achieve this, ANN based models were employed for different land cover classes, utilizing MPDI at finer resolution with ancillary data. MPDI was derived using resampled (from 0.250 to 1 km) brightness temperatures (Tb) at 36.5 GHz channel of dual polarization from Advance Microwave Scanning Radiometer (AMSR)-Earth Observing System and AMSR2 sensors. The proposed methodology was quantitatively evaluated through three performance measures namely correlation coefficient (r), Nash Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). Results revealed that during daytime, AMSR-E(AMSR2) derived LST under clear sky conditions corresponds well with MODIS LST resulting in values of r ranging from 0.76(0.78) to 0.90(0.96), RMSE from 1.76(1.86) K to 4.34(4.00) K and NSE from 0.58(0.61) to 0.81(0.90) for different land cover classes. For night time, r values ranged from 0.76(0.56) to 0.87(0.90), RMSE from 1.71(1.70) K to 2.43(2.12) K and NSE from 0.43 (0.28) to 0.80(0.81) for different land cover classes. RMSE values found between predicted LST and MODIS LST during daytime under clear sky conditions were within acceptable limits. Under cloudy conditions, results of microwave derived LST were evaluated with Ta which indicated that the approach performed well with RMSE values lesser than the results obtained under clear sky conditions for land cover classes for both day and nighttimes. These predicted LSTs can be applied for the estimation of soil moisture in hydrological studies, in climate studies, ecology, urban climate and environmental studies, etc. AET was estimated for all sky conditions using vegetation coefficient method. Essential parameter ETo under cloudy conditions was estimated using LST and Ta based PMT and H-S models and required solar radiation (Rs) in these two models estimated using equation proposed by Samani (2000). In this equation it was found that the differences between LSTmax or Tmax and LSTmin or Tmin could able to capture the variations due to cloudy sky conditions and hence can be used for estimating ETo under cloudy sky conditions. Results revealed that the estimated Rs correlated well with observed Rs for Berambadi station under cloudy conditions for the year 2013. PMT based ETo values were corresponded with observed ETo under cloudy sky condition. The difference between LST and Ta was less during cloudy conditions, therefore LST or Ta can be used as the only input in temperature based PMT model to estimate ETo. AET estimated correlated well with the observed AET values for clear and cloudy sky conditions. In addition, AET estimated using vegetation coefficient method was compared with two source energy balance (TSEB) method developed by Nishida et al. (2003) under clear sky conditions. It was found that the improved vegetation coefficient method performed better than the TSEB method for Berambadi station. Other microwave vegetation indices such as Microwave Vegetation Indices (MVIs) and Emissivity Difference Vegetation Index (EDVI) are available in literature. Therefore in this study, MVIs are used to predict LST under cloudy conditions using proposed methodology to check whether the MVIs could yield better LST values. Results showed that MPDI performed better than MVIs to predict LST under cloudy sky conditions. Furthermore, MPDI obtained using dual polarizations of 37 GHz channel Tb has advantage of having fine spatial resolution compared to MVIs, as it requires Tb of 19 GHz in addition to Tb of 37 GHz channel which is of coarse resolution and therefore uncertainties resulting from re-sampling technique can be minimized. x