Challenges and opportunities of quantifying local CO2 advection at a mountain forest in the Alps

<p>Mountain forests, which play an important role in the mitigation of anthropogenic CO<sub>2</sub> emissions are supposed to be heavily affected by climatic changes and extremes. Efforts towards the understanding of the physiological processes regulating mountain forest carbon and water fluxes are crucial to correctly manage and protect these key ecosystems. However, among the challenges in micrometeorological flux measurements in complex terrain, the unaccounted presence of advective CO<sub>2</sub> fluxes has the potential to bias the daily and longer-term CO<sub>2</sub> exchange estimates towards unrealistic net uptake, a bias that urgently needs to be accounted for in order to reduce uncertainties related to role of mountain forests in the global carbon cycle. On the other hand, given the typical local bi-directional wind system in mountains, information on advective flows at these sites could be easier to detect compared to other terrains. We present the results of a CO<sub>2</sub> advection experiment conducted at a European larch site in Northern Italy (2100 m asl). The setup consisted of: the main eddy covariance flux tower (20 m), a sub-canopy eddy covariance flux system (2 m), a home-assembled system for measuring CO<sub>2</sub> concentrations at three heights on the four sides of a 40 x 40 m control volume, composed by a solenoid valve system, multiple sampling inlets and a gas analyzer, and three automatic chambers measuring bare soil respiration (two chambers) and the net ecosystem CO<sub>2</sub> exchange from the vegetated forest floor (one chamber). Results show that: i) advection is a not-negligible fraction of the total net ecosystem CO<sub>2</sub> exchange of this forest, ii) coupling measurements of above and below canopy eddy covariance in mountain forest sites could emerge essential for detecting/estimating the unaccounted CO<sub>2</sub> flux</p>

Effects of surface waves on hyporheic exchange over a permeable gravel bed

<p>Hyporheic exchange represents the interactions between surface and subsurface flows occurring at various geophysical scales. Its importance to the riverine ecological health and the fate of contaminants has long been recognized. Traditionally, the behaviors of hyporheic exchange are explained by the emergence of geomorphological features, such as dune-shaped bedforms, that usually introduce significant pressure differences along the channel bed and, therefore, facilitate exchanges by pumping the flow inward and outward the bed. In addition to this advective mechanism, near-bed turbulence has also been identified as another driver of flow exchange through the turbulent diffusive processes. This study, on the other hand, highlights the decisive control of surface waves on the hyporheic exchange at depth-limited flow conditions, especially for those unbroken standing waves commonly encountered in river riffle areas. It is hypothesized that the presence of surface waves will reshape the distribution of near-bed hydrodynamic pressures, thus altering the properties of advective flows along the channel bed. The validity of this hypothesis is carefully examined through the laboratory experiments using Refractive-Index-Matched (RIM) liquid and solid materials and Particle Tracking Velocimetry (PTV) techniques. This experimental setting helps to simultaneously resolve the surface and subsurface flow patterns to a sufficient detail; the hydrodynamic pressure field can then be derived from the obtained flow velocity fields. Further analysis in a Double-Averaged Navier-Stokes framework indicates that, among different contributing factors, pressure gradient is found to be the most dominant driver of interface exchange. The variations of this driving mechanism, interestingly, can be further decomposed into two parts, namely, the surface wave associated (global-scale) and the bed grain associated (local-scale) components, respectively.</p>

Fluid Flow and Mass Transport in Brain Tissue

Despite its small size, the brain consumes 25% of the body’s energy, generating its own weight in potentially toxic proteins and biological debris each year. The brain is also the only organ lacking lymph vessels to assist in removal of interstitial waste. Over the past 50 years, a picture has been developing of the brain’s unique waste removal system. Experimental observations show cerebrospinal fluid, which surrounds the brain, enters the brain along discrete pathways, crosses a barrier into the spaces between brain cells, and flushes the tissue, carrying wastes to routes exiting the brain. Dysfunction of this cerebral waste clearance system has been demonstrated in Alzheimer’s disease, traumatic brain injury, diabetes, and stroke. The activity of the system is observed to increase during sleep. In addition to waste clearance, this circuit of flow may also deliver nutrients and neurotransmitters. Here, we review the relevant literature with a focus on transport processes, especially the potential role of diffusion and advective flows.

A Three-Dimensional Trajectory Model with Advection Correction for Tropical Cyclones: Algorithm Description and Tests for Accuracy

When computing trajectories from model output, gridded winds are often temporally interpolated to a time step shorter than model output intervals to satisfy computational stability constraints. This study investigates whether trajectory accuracy may be improved for tropical cyclone (TC) applications by interpolating the model winds using advection correction (AC) instead of the traditional linear interpolation in time (LI) method. Originally developed for Doppler radar processing, AC algorithms interpolate data in a reference frame that moves with the pattern translation, or advective flow velocity. A previously developed trajectory AC implementation is modified here by extending it to three-dimensional (3D) flows, and the advective flows are defined in cylindrical rather than Cartesian coordinates. This AC algorithm is tested on two model-simulated TC cases, Hurricanes Joaquin (2015) and Wilma (2005). Several variations of the AC algorithm are compared to LI on a sample of 10 201 backward trajectories computed from the modeled 5-min output data, using reference trajectories computed from 1-min output to quantify position errors. Results show that AC of 3D wind vectors using advective flows defined as local gridpoint averages improves the accuracy of most trajectories, with more substantial improvements being found in the inner eyewall where the horizontal flows are dominated by rotating cyclonic wind perturbations. Furthermore, AC eliminates oscillations in vertical velocity along LI backward trajectories run through deep convective updrafts, leading to a ~2.5-km correction in parcel height after 20 min of integration.