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Abstract Integrated quadrant analysis is a novel technique to identify and to characterize the trajectory and strength of turbulent coherent structures in the atmospheric surface layer. By integrating the three-dimensional velocity field characterized by traditional quadrant analysis with respect to time, the trajectory history of individual coherent structures can be preserved with Eulerian turbulence measurements. We develop a method to identify the ejection phase of coherent structures based on turbulence kinetic energy (TKE). Identifying coherent structures within a time series using TKE performs better than identifying them with the streamwise and vertical velocity components because some coherent structures are dominated by the cross-stream velocity component as they pass the sensor. By combining this identification method with the integrated quadrant analysis, one can animate or plot the trajectory of individual coherent structures from high-frequency velocity measurements. This procedure links a coherent ejection with the subsequent sweep and quiescent period in time to visualize and quantify the strength and the duration of a coherent structure. We develop and verify the method of integrated quadrant analysis with data from two field studies: the Eclipse Boundary Layer Experiment (EBLE) in Corvallis, Oregon in August 2017 (grass field) and the Vertical Cherry Array Experiment (VACE) in Linden, California in November 2019 (cherry orchard). The combined TKE identification method and integrated quadrant analysis are promising additions to conditional sampling techniques and coherent structure characterization because the identify coherent structures and couple the sweep and ejection components in space. In an orchard (VACE), integrated quadrant analysis verifies each coherent structure is dominated by a sweep. Conversely, above the roughness sublayer (EBLE), each coherent structure is dominated by an ejection. 

A semi-empirical approach based on surface-renewal theory for estimating the friction velocity is tested for measurements taken in the inertial sublayer. For unstable cases, the input requirements are the mean wind speed and the high-frequency trace (10 or 20 Hz) of the air or sonic temperature. The method has been extended to traces of water vapour (H2O) and carbon dioxide (CO2) concentrations. For stable cases, the stability parameter must also be considered. The method’s performance, taking the direct friction velocity measured by sonic anemometry as a reference, was tested over a growing cotton field that included bare soil with some crop residues at the beginning of the season. In general, the proposed friction-velocity estimates are reliable. For unstable cases, the method shows the potential to outperform the wind logarithmic-law computation. Discarding cases with low wind speeds (e.g., <0.3 m s−1 and mean wind shear<1 Hz), the proposed approach may be recommended as an alternative method to estimating the friction velocity. There is the potential, based on the input requirements, that the proposed formulation may offer significant advantages in the estimation of the friction velocity in some marine environments. 

Abstract Terrestrial evapotranspiration is the second‐largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross‐disciplinary group of ET scientists to overcome the challenges identified in this paper and ultimately advance our integrated understanding of ET.