3 resultados para LAND-SURFACE


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Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.

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Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.

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A avaliação de terras é o processo que permite estimar o uso potencial da terra com base em seus atributos. Grande variedade de modelos analíticos pode ser usada neste processo. No Brasil, os dois sistemas de avaliação das terras mais utilizados são o Sistema de Classificação da Capacidade de Uso da Terra e o Sistema FAO/Brasileiro de Aptidão Agrícola das Terras. Embora difiram em vários aspectos, ambos exigem o cruzamento de inúmeras variáveis ambientais. O ALES (Automated Land Evaluation System) é um programa de computador que permite construir sistemas especialistas para avaliação de terras. As entidades avaliadas pelo ALES são as unidades de mapeamento, as quais podem ser de caráter generalizado ou detalhado. A área objeto desta avaliação é composta pelas microrregiões de Chapecó e Xanxerê, no Oeste catarinense, e engloba 54 municípios. Os dados sobre os solos e sobre as características da paisagem foram obtidos no levantamento de reconhecimento dos solos do Estado, na escala de 1:250.000. O presente estudo desenvolveu o sistema especialista ATOSC (Avaliação das Terras do Oeste de Santa Catarina) e, na sua construção, incluiu-se a definição dos requerimentos dos tipos de utilização da terra, bem como foi feita a subsequente comparação destes com os atributos de cada unidade de mapeamento. Os tipos de utilização da terra considerados foram: feijão, milho, soja e trigo, em cultivos solteiros, sob condições de sequeiro e de manejo característicos destas culturas no Estado. As informações sobre os recursos naturais compreendem os atributos climáticos, de solos e das condições da paisagem que interferem na produção destas culturas. Para cada tipo de utilização da terra foram especificados, no ATOSC, o código, o nome e seus respectivos requerimentos de uso da terra. Os requerimentos de cada cultura foram definidos por uma combinação específica das características das terras selecionadas, que determina o nível de severidade de cada um deles em relação à cultura. Estabeleceram-se quatro níveis de severidade que indicam aumento do grau de limitação ou diminuição do potencial para determinado tipo de uso da terra, a saber: limitação nula ou ligeira (favorável); limitação moderada (moderadamente favorável), limitação forte (pouco favorável); e limitação muito forte (desfavorável). Na árvore de decisão, componente básico do sistema especialista, são implementadas as regras que permitirão o enquadramento das terras em classes de adequação definidas, baseado na qualidade dos requerimentos de acordo com o tipo de uso. O ATOSC facilitou o processo de comparação entre as características das terras das microrregiões de Chapecó e Xanxerê e os requerimentos de uso considerados, por permitir efetuar automaticamente a avaliação das terras, reduzindo, assim, o tempo gasto neste processo. As terras das microrregiões de Chapecó e Xanxerê foram enquadradas, em sua maior parte, nas classes de adequação pouco favorável (3) e desfavorável (4) para os cultivos considerados. Os principais fatores limitantes identificados nestas microrregiões foram a fertilidade natural e o risco de erosão, para o feijão e o milho, e condições de mecanização e risco de erosão, para a soja e o trigo.