Energy and mass transfer parameters in a brazilian semi-arid ecosystem under different thermohydrological conditions

• Autor(a) principal: Teixeira,Antônio Heriberto de Castro
• Data de Publicação: 2015
• Outros Autores: Andrade,Ricardo Guimarães, Leivas,Janice Freitas
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Meteorologia (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862015000400381
• topic: energy balance; roughness parameters; modelling; "Caatinga".

ABSTRACT In the Brazilian semi-arid region, the natural vegetation ("Caatinga") has been replaced by irrigated agriculture, emphasising the importance for quantification of the energy and mass exchanges. Eddy covariance and micro-climatic measurements in this natural ecosystem, were analysed for two years under different thermohydrological conditions. Sensible heat flux (H) accounted for 49 and 64% of the net radiation (Rn), respectively, during the wetter and the drier conditions of 2004 and 2005. The corresponding fractions of Rn partitioned as latent heat flux (LE) were 40% and 25%. Evapotranspiration (ET) in 2004, with 693 mm, represented 96% of precipitation (P), while in 2005 (399 mm), it was 18% higher than P, which evidenced the use of the remaining soil moisture from the previous wetter year. All the soil-water-vegetation-atmosphere transfer parameters were influenced by the rainfall amounts. However, the surface resistance (rs) was the most strongly affected by the soil moisture status, dropping with increases of the ratio of ET to reference evapotranspiration (ET0). On the other hand, the highest rs values were related to increases in both vapour pressure deficit (De) and aerodynamic temperature (T0). The current research aimed to quantify the energy and mass exchange between the "Caatinga" and the lower atmosphere, testing in which circumstances the biophysical controlling parameters can be reasonably predicted from agrometeorological data, throughout parameterizations, to incorporate in large-scale models.