Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2016-12-20T10:57:25Z No. of bitstreams: 2 Tese - Sylvia Elaine Marques de Farias - 2016.pdf: 7335718 bytes, checksum: 48824dd4042523e464e099f9a62371b3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-12-27T12:49:46Z (GMT) No. of bitstreams: 2 Tese - Sylvia Elaine Marques de Farias - 2016.pdf: 7335718 bytes, checksum: 48824dd4042523e464e099f9a62371b3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-12-27T12:49:46Z (GMT). No. of bitstreams: 2 Tese - Sylvia Elaine Marques de Farias - 2016.pdf: 7335718 bytes, checksum: 48824dd4042523e464e099f9a62371b3 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-04-18 / The Brazilian savanna is the second largest biome, covering an approximate area of 21% of the national territory. Among other factors, the rainfall favored the activities of agribusiness and hydro-dependent activities of the climate pattern of rainfall. However, the biome is complex climatologically and rainfall network is sparse or poorly distributed. In this sense, this study sought to evaluate the precipitation estimates of the Savanna. The main results of this thesis are: a) by the need to assess the rainfall pattern on the Savanna it was found that the rains are caused due to phenomena of weather and climate that operate seasonally, featuring the region by dry winters, from May to August, and rainy summers, from September to April. A deficit above -5,0 mm.mes-1 is observed between May and June, while the excess water, the rainy season can reach 240,0 mm.mes-1; b) given the complexity rainfall observed in the biome, statistical tests showed that version 7 algorithm was more accurate to estimate precipitation. As for the regions of the state inserted in the biome, Goiás presented the highest value as the Pearson correlation, 0,99. Estimates between area and pixel showed that the satellite estimates are consistent with the observations. Considering the ability of estimates of the annual and seasonal pattern, the precipitation anomalies reproduce the variability of dry and wet periods. The estimate for the year 2009, under the influence of the beginning of a moderate El Nino, played a rainy year throughout the Savanna. Conversely, 2007, characterized by end of an El Nino low intensity, reproduced a dry year; c) Analysis of Main Components (ACP) were characterized by the three most significant factors explaining 97,5% of the total variance of monthly precipitation data both for Brazil and for the Savanna. The CP1 varies linearly indicating that it explains both the Savanna as to Brazil the annual variation in rainfall. The CP2 brand significantly seasonality between Brazil and the Savanna. The CP3 varies significantly between characteristic months due to seasonality. The results suggest that the satellite rainfall estimates, version (3B43), are accurate on a complex and extensive biome as the Savanna. / O cerrado é o segundo maior bioma brasileiro, ocupando uma área aproximada de 21% do território nacional. Dentre outros fatores, a pluviosidade favoreceu ao agro e ao hidro negócio, atividades dependentes do padrão climático da precipitação. No entanto, o bioma é complexo climatologicamente e a rede pluviométrica é escassa ou mal distribuída. Neste sentido, esta pesquisa procurou avaliar as estimativas de precipitação sobre o bioma Cerrado. Os principais resultados desta tese são: a) mediante a necessidade de se avaliar o padrão pluviométrico sobre o bioma Cerrado, constatou-se que as chuvas são originadas devido a fenômenos de tempo e clima que atuam sazonalmente, caracterizando a região por invernos secos, entre maio a agosto, e verões chuvosos, entre setembro a abril. Um déficit superior a -5,0 mm.mes-1 é observado entre maio e junho, enquanto o excedente hídrico, no período chuvoso, pode chegar até 240,0 mm.mes-1; b) diante da complexidade pluviométrica observada no bioma, os testes estatísticos mostraram que a versão 7 do algoritmo se mostrou mais acurada para estimar a precipitação. E, quanto às regiões dos Estados inseridas no bioma, Goiás apresentou o maior valor quanto à correlação de Pearson, 0,99. As estimativas entre área e pixel mostraram que as estimativas por satélite estão de acordo com as observações. Considerando-se a habilidade de estimativas quanto ao padrão anual e sazonal, as anomalias de precipitação reproduziram a variabilidade dos períodos secos e chuvosos. A estimativa para o ano de 2009, sob a influência do início de um El Niño moderado, reproduziu um ano chuvoso em todo o Cerrado. Por outro lado, o ano de 2007, caracterizado pelo final de um El Niño de fraca intensidade, reproduziu um ano seco; c) as Análises de Componentes Principais (ACP) foram caracterizadas por três fatores mais significativos que explicam 97,5% da variância total dos dados mensais de precipitação tanto para o território brasileiro quanto para o bioma Cerrado. A CP1 varia linearmente indicando que ela explica tanto para o Cerrado quanto para o Brasil a variação anual da precipitação. A CP2 marca significativamente a sazonalidade entre o Brasil e o Cerrado. A CP3 varia significativamente entre meses característicos devido à sazonalidade. Os resultados sugerem que as estimativas de precipitação por satélite, versão (3B43), são acuradas sobre um bioma complexo e extenso como o Cerrado.

East Asian Paleogene climates have long been regarded as controlled by the planetary wind system, which might result in a climate pattern with three latitudinally distributed zones. Two humid zones located separately in the north and south were lithologically designated by coals and oil shales, while an arid zone in the middle was represented by red beds and evaporites. Because the middle arid zone was located along ~. 30° N paleolatitude, its presence had been further linked with a then subtropical high. However, this long-standing model has recently been challenged by growing evidence from petrology, sedimentology, paleontology, paleobiogeography, paleoclimatology, and climate modeling. Here we review the primary data from these disciplines and reinterpret their climate significances to revisit the East Asian climate pattern during the Paleogene. Petrologically, while the occurrence of coals and/or oil shales is accepted as an indicator for overall humid climates, that of red beds and/or evaporites is highly equivocal to exclusively indicate perennial arid climates unless their origins are carefully investigated. In reality, generic red beds merely represent an oxidizing environment, not essentially associated with a single specific climate type. Meanwhile evaporites, although typically precipitated in arid environments, may be deposited in either perennial dry or seasonal/monsoonal climates. There is no solid evidence so far to convincingly support that the landscape of the so-called middle arid zone was dominated by desert and/or steppe under a then subtropical high during most of the Paleogene. The plant function type study additionally suggests that the "middle arid zone" appears to be lack of xerophytic vegetation, even though some xerophytic or sclerophyllous plant taxa did sporadically occur. Interestingly, paleozoological data show that the Paleogene mammalian faunas were somewhat equably distributed over East Asia, strongly suggesting the evident absence of a critical biogeographical or climatic barrier stretched across the "middle arid zone" as the planetary wind model implied. In contrast to the planetary wind model, monsoonal or monsoon-like Paleogene climates have been broadly reported from the northern, middle, and southern East Asia, as well as adjacent regions of Russia and Kazakhstan. If only the indicators for humid climates are considered, simply due to the uncertainty of those for perennial arid climates, East Asia must have had a relatively dry region in the continental interior during the late Eocene to Oligocene transition, likely caused by the continentality and/or the rain shadow effect along with the global cooling. The monsoonal interpretation is highly in agreement with the evidence from floras, faunas, basin analyses, and modeling experiments, and well explicates the Paleogene climate distribution and seasonal dynamics of East Asia. However, further studies will be largely needed to verify whether, uniformly according to the modern criteria, the Paleogene climates of the East Asia interior can be accurately attributed to the arid category.