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Abstract. Isoprene emissions are a key component in biosphere–atmosphere interactions, and the most significant global source is the Amazonrainforest. However, intra- and interannual variations in biological and environmental factors that regulate isoprene emission from Amazonia arenot well understood and, thereby, are poorly represented in models. Here, with datasets covering several years of measurements at the Amazon Tall TowerObservatory (ATTO) in central Amazonia, Brazil, we (1) quantified canopy profiles of isoprene mixing ratios across seasons of normal and anomalousyears and related them to the main drivers of isoprene emission – solar radiation, temperature, and leaf phenology; (2) evaluated the effect ofleaf age on the magnitude of the isoprene emission factor (Es) from different tree species and scaled up to canopy with intra- andinterannual leaf age distribution derived by a phenocam; and (3) adapted the leaf age algorithm from the Model of Emissions of Gasesand Aerosols from Nature (MEGAN) with observed changes in Esacross leaf ages. Our results showed that the variability in isoprene mixing ratios was higher between seasons (max during the dry-to-wettransition seasons) than between years, with values from the extreme 2015 El Niño year not significantly higher than in normal years. Inaddition, model runs considering in situ observations of canopy Es and the modification on the leaf age algorithm with leaf-levelobservations of Es presented considerable improvements in the simulated isoprene flux. This shows that MEGAN estimates of isopreneemission can be improved when biological processes are mechanistically incorporated into the model. 

Abstract Observational data from two field campaigns in the Amazon forest were used to study the vertical structure of turbulence above the forest. The analysis was performed using the reduced turbulent kinetic energy (TKE) budget and its associated two-dimensional phase space. Results revealed the existence of two regions within the roughness sublayer in which the TKE budget cannot be explained by the canonical flat-terrain TKE budgets in the canopy roughness sublayer or in the lower portion of the convective ABL. Data analysis also suggested that deviations from horizontal homogeneity have a large contribution to the TKE budget. Results from LES of a model canopy over idealized topography presented similar features, leading to the conclusion that flow distortions caused by topography are responsible for the observed features in the TKE budget. These results support the conclusion that the boundary layer above the Amazon forest is strongly impacted by the gentle topography underneath.