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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 The measured variations in the turbulent static pressure structure function with scale in the roughness sublayer above a subarctic forest are empirically shown to exhibit exponents that are smaller than predicted for the inertial subrange (ISR). Three hypotheses are offered to explain these deviations. The first is based on conventional intermittency correction to the averaged turbulent kinetic energy dissipation rate, the second is based on shearing introducing deviations from locally isotropic state that must be sensed by both velocity and pressure structure functions, and the third is based on large and inertial scale pressure interactions that persist at values of within the resolvable ISR. The third hypothesis is shown to yield superior results, which allows a new formulation for to be derived that accommodates such finite interactions. 

Abstract Stemflow hydrodynamics is the study of water movement along the exterior surface area of plants. Its primary goal is to describe water velocity and water depth along the stem surface area. Its significance in enriching the rhizosphere with water and nutrients is not in dispute. Yet, the hydrodynamics of stemflow have been entirely overlooked. This review seeks to fill this knowledge gap by drawing from thin film theories to seek outcomes at the tree scale. The depth‐averaged conservation equations of water and solute mass are derived at a point. These equations are then supplemented with the conservation of momentum that is required to describe water velocities or relations between water velocities and water depth. Relevant forces pertinent to momentum conservation are covered and include body forces (gravitational effects), surface forces (wall friction), line forces (surface tension), and inertial effects. The inclusion of surface tension opens new vistas into the richness and complexity of stemflow hydrodynamics. Flow instabilities such as fingering, pinching of water columns into droplets, accumulation of water within fissures due to surface tension and their sudden release are prime examples that link observed spatial patterns of stemflow fronts and morphological characteristics of the bark. Aggregating these effects at the tree‐ and storm‐ scales are featured using published experiments. The review discusses outstanding challenges pertaining to stemflow hydrodynamics, the use of dynamic similarity and 3D printing to enable the interplay between field studies and controlled laboratory experiments. 

Abstract The turbulent static pressure spectrum as a function of longitudinal wavenumber in the roughness sublayer of forested canopies is of interest to a plethora of problems such as pressure transport in the turbulent kinetic energy budget, pressure pumping from snow or forest floor, and coupling between flow within and above canopies. Long term static pressure measurements above a sub‐arctic forested canopy for near‐neutral conditions during the winter and spring were collected and analyzed for three snow cover conditions: trees and ground covered with snow, trees are snow free but the ground is covered with snow, and snow free cover. In all three cases, it is shown that obeys the attached eddy hypothesis at low wavenumbers —with and Kolmogorov scaling in the inertial subrange at higher wavenumbers—with , where is the friction velocity at the canopy top, is the mean turbulent kinetic energy dissipation rate, is the distance from the snow top, and is the boundary layer depth. The implications of these two scaling laws to the normalized root‐mean squared pressure and its newly proposed logarithmic scaling with normalized wall‐normal distance are discussed for snow covered and snow free vegetation conditions. The work here also shows that the in the appears more extensive and robust than its longitudinal velocity counterpart. 

Abstract The relaxed eddy accumulation (REA) method is a widely‐known technique that measures turbulent fluxes of scalar quantities. The REA technique has been used to measure turbulent fluxes of various compounds, such as methane, ethene, propene, butene, isoprene, nitrous oxides, ozone, and others. The REA method requires the accumulation of scalar concentrations in two separate compartments that conditionally sample updrafts and downdraft events. It is demonstrated here that the assumptions behind the conventional or two‐compartment REA approach allow for one‐compartment sampling, therefore called a one compartment or 1‐C‐REA approach, thereby expanding its operational utility. The one‐compartment sampling method is tested across various land cover types and atmospheric stability conditions, and it is found that the one‐compartment REA can provide results comparable to those determined from conventional two‐compartment REA. This finding enables rapid expansion and practical utility of REA in studies of surface‐atmosphere exchanges, interactions, and feedbacks. 

Abstract Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's ). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation‐based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely‐used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties. 

Abstract Top‐down entrainment shapes the vertical gradients of sensible heat, latent heat, and CO₂fluxes, influencing the interpretation of eddy covariance (EC) measurements in the unstable atmospheric surface layer (ASL). Using large eddy simulations for convective boundary layer flows, we demonstrate that decreased temperature gradients across the entrainment zone increase entrainment fluxes by enhancing the entrainment velocity, amplifying the asymmetry between top‐down and bottom‐up flux contributions. These changes alter scalar flux profiles, causing flux divergence or convergence and leading to the breakdown of the constant flux layer assumption (CFLA) in the ASL. As a result, EC‐measured fluxes either underestimate or overestimate “true” surface fluxes during divergence or convergence phases, contributing to energy balance non‐closure. The varying degrees of the CFLA breakdown are a fundamental cause for the non‐closure issue. These findings highlight the underappreciated role of entrainment in interpreting EC fluxes, addressing non‐closure, and understanding site‐to‐site variability in flux measurements. 

Abstract In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity , where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts , where is the molecular Schmidt number, is the water kinematic viscosity, and is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous around , a mechanism that was not previously considered. As the coefficient of variation in increases, must be adjusted by a multiplier that was derived from a log‐normal model for the probability density function of . Reported variations in with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in . Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of . That varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade. 

Summary Plant response to water stress involves multiple timescales. In the short term, stomatal adjustments optimize some fitness function commonly related to carbon uptake, while in the long term, traits including xylem resilience are adjusted. These optimizations are usually considered independently, the former involving stomatal aperture and the latter carbon allocation. However, short‐ and long‐term adjustments are interdependent, as ‘optimal’ in the short term depends on traits set in the longer term.An economics framework is used to optimize long‐term traits that impact short‐term stomatal behavior. Two traits analyzed here are the resilience of xylem and the resilience of nonstomatal limitations (NSLs) to photosynthesis at low‐water potentials.Results show that optimality requires xylem resilience to increase with climatic aridity. Results also suggest that the point at which xylem reach 50% conductance and the point at which NSLs reach 50% capacity are constrained to approximately a 2 : 1 linear ratio; however, this awaits further experimental verification.The model demonstrates how trait coordination arises mathematically, and it can be extended to many other traits that cross timescales. With further verification, these results could be used in plant modelling when information on plant traits is limited. 

Abstract Turbulent flows over a large surface area (S) covered bynobstacles experience an overall drag due to the presence of the ground and the protruding obstacles into the flow. The drag partition between the roughness obstacles and the ground is analyzed using an analytical model proposed by Raupach (Boundary-Layer Meteorol 60:375-395, 1992) and is hereafter referred to as R92. The R92 is based on the premise that the wake behind an isolated roughness element can be described by a shelter areaAand a shelter volumeV. The individual sizes ofAandVwithout any interference from other obstacles can be determined from scaling analysis for the spread of wakes. To upscale from an individual roughness element ton/Selements where wakes may interact, R92 adopted a background stress re-normalizing instead of reducingAorVwith each element addition. This work demonstrates that R92’s approach results in a linear background stress reduction inAandVonly when the ratio ofn/Sis small, due to a low probability of wake interactions. This probabilistic nature suggests that up-scaling from individual to multiple roughness elements can be re-formulated using stochastic averaging methods proposed here. The two approaches are shown to recover R92 under plausible conditions. An alternative scaling for the shelter volume is also proposed here using thermodynamic arguments of work and dissipation though the final outcome remains similar to R92. Comparisons between R92 and available data spanning more than two decades after R92 on blocks and vegetation-like roughness elements confirm the practical utility of R92. The agreement between R92 and this updated databases of experiments and simulations confirm the potential use of R92 in large-scale models provided that the relevant parameters accommodate certain features of the roughness element type (cube versus vegetation-like) and, to a lesser extent, their configuration throughoutS. Last, a comparison between R92 and models based on first-order closure principles with constant mixing length suggests that R92 can outperform such models when evaluated across a wide range of roughness densities.