Search for: All records

Methods that combine in-situ measurements, statistical methods, and model simulations with remotely sensed data provide a pathway for improving the robustness of surface flux products. For this research, we acquired eddy-covariance fluxes along a five-tower transect in a snowy montane forest over three consecutive winters to characterize near-field variability of the subcanopy environment. The novel experiment design enabled discriminating near-field evaposublimation sources. Boosted regression trees reveal that the predictive capacity of state variables change with season and storm cycle frequency. High rates of post-storm evaposublimation of canopy-intercepted snow at this site were constrained by short residence time of snow in the canopy due to throughfall and melt. The snow melt-out date for open vs. closed canopy conditions depended on total snowfall accumulation. Compared with low accumulation years, the snow melt-out date under the dense canopy during the high accumulation winter was later than for the open area, as shading became more important later in the season. The field experiments informed an environmental response function that was used to integrate ERA5-Land latent heat flux data at 20-km nominal resolution with USFS Tree Canopy Fraction data at 30-m resolution and showed near-field flux variability that was not resolved in model simulations. Previous evaposublimation results from experiments in alpine and subalpine environments do not directly translate to a montane forest due to differences in process rates. 

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.