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Abstract The influence of thermal stratification on the turbulent kinetic energy balance has been widely studied; however, its influence on the turbulent stress remains less explored in the presence of tall vegetated canopies and less ideal micrometeorological conditions. Here, the impact of thermal stratification on turbulent momentum flux is considered in the roughness sublayer (RSL) and the atmospheric surface layer (ASL) using the Amazon Tall Tower Observatory (ATTO) in Brazil. A scalewise co‐spectral budget (CSB) model is developed using standard closure schemes for the pressure–velocity decorrelation. The CSB revealed that the co‐spectrum between longitudinal () and vertical () velocity fluctuations is impacted by the energy spectrum of the vertical velocity and the much less studied longitudinal heat‐flux co‐spectrum , where are temperature fluctuations and is the longitudinal wavenumber. Under stable, very stable, and dynamic–convective conditions, the scaling exponent in for the inertial subrange (ISR) scales is dominated by instead of . A near scaling in robust to large variations in thermal stratification is found, whereas the Kolmogorov ISR scaling for is not found. The scale‐dependent decorrelation time between and is dominated by in the ISR, but is nearly constant for eddies larger than the vertical velocity integral scale, regardless of stability. Implications of these findings for generalized stability correction functions that are based on the turbulent stress budget instead of the turbulent kinetic energy budget are discussed. 

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.