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The coupling between wind-waves and atmospheric surface layer turbulence sets surface drag. This coupling is however usually represented through a roughness length. Originally suggested on purely dimensional grounds, this roughness length does not directly correspond to a measurable physical quantity of the wind-and-wave system. Here, to go beyond this representation, we formalize ideas underlying the Beaufort scale by quantifying the velocity of breaking short waves that are the most coupled to near-surface wind. This velocity increases with wind speed, reflecting the fact that stronger winds can be visually identified by longer (and faster) breakers becoming predominant on the sea surface. A phenomenological turbulence model further shows that this velocity is associated with breaking waves that impede the most the formation of turbulent eddies. Scales of such eddies are then constrained inside a so-called roughness sub-layer. Unlike previous theoretical developments, the proposed breaker velocity is a directly measurable quantity, which could be used to characterize the coupling between wind and waves using remote sensing techniques. This work provides a physical framework for new formulations of air-sea momentum exchange in which the effects of surface currents and slicks on surface drag can also be incorporated. Finally, it provides a long-sought physical explanation for the Beaufort scale: a universal link between wave breaking, wind speed and surface drag., Comment: 21 pages, 9 figures

JGR-A: Turbulence Structures in the Strongly Stable Boundary Layer under the Influence of Wind Profile Distortion Data files can be open with Matlab

For JGR-A data files can be open with Matlab

Sweep and ejection events in turbulent boundary layer flows have been explored for half a century now to describe eddies impacting turbulent stresses. Yet, moving these studies from their current diagnostic phase to a prognostic form remains a formidable challenge. Here, a cumulant expansion is used to derive a link between the transport of shear stress and the balance of local sweep and ejection events. Cumulant expansion is further used to connect this transport to a metric of asymmetry in the streamwise velocity distribution. These relations are employed to develop two so-called structural models for predicting the turbulent stress transport, which is traditionally neglected in first-order closure of the shear stress budget. Several datasets collected in rough-wall conditions are used to show the importance of the transport term in the roughness sublayer and to demonstrate the predictive skill of the two structural models. The model parameters are invariant to the tested range of Reynolds number and surface roughness, indicating the structural similarity between the velocity asymmetry, sweep/ejection balance, and stress transport may be universal and independent of roughness. Finally, the implementation of the structural models for improved closure schemes of the shear stress budget in modeling applications and wall-modeling in large-eddy simulations are discussed.

The dataset contains the topography, flow field, and concentration data over forested topographies.

Anisotropy and multifractality in velocity and temperature time series sampled at multiple heights in the roughness sublayer (RSL) over a boreal mixed-coniferous forest are reported. In particular, a turbulent-stress invariant analysis along with a scalewise version of it are conducted to elucidate the nature of relaxation of large-scale anisotropy to quasi-isotropic states at small scales. As the return to isotropy is linked to nonlinear interactions and correlations between different fluctuating velocity components across scales, we study the velocity and temperature time series by using multifractal detrended fluctuation analysis and multiscale multifractal analysis to assess the effects of thermal stratification and surface roughness on turbulence in the RSL. The findings are compared so as to quantify the anisotropy and multifractality ubiquitous to RSL turbulent flow. As we go up in the RSL, (a) the length scale at which return to isotropy commences increases because of the weakening of the surface effects and (b) the largest scales become increasingly anisotropic. The anisotropy in multifractal exponents for the velocity fluctuations is diminished when we use the extended-self-similarity procedure to extract the multifractal-exponent ratios., Comment: 17 pages, 15 figures

The dispersal ability of plants is a major factor driving ecological responses to global change. In wind-dispersed plant species, non-random seed release in relation to wind speeds has been identified as a major determinant of dispersal distances. However, little information is available about the costs and benefits of non-random abscission and the consequences of timing for dispersal distances. We asked: 1) to what extent is non-random abscission able to promote long-distance dispersal and what is the effect of potentially increased pre-dispersal risk costs? 2) Which meteorological factors and respective timescales are important for maximizing dispersal? These questions were addressed by combining a mechanistic modelling approach and field data collection for herbaceous wind-dispersed species. Model optimization with a dynamic dispersal approach using measured hourly wind speed showed that plants can increase long-distance dispersal by developing a hard wind speed threshold below which no seeds are released. At the same time, increased risk costs limit the possibilities for dispersal distance gain and reduce the optimum level of the wind speed threshold, in our case (under representative Dutch meteorological conditions) to a threshold of 5–6 m s–1. The frequency and predictability (auto-correlation in time) of pre-dispersal seed-loss had a major impact on optimal non-random abscission functions and resulting dispersal distances. We observed a similar, but more gradual, bias towards higher wind speeds in six out of seven wind-dispersed species under natural conditions. This confirmed that non-random abscission exists in many species and that, under local Dutch meteorological conditions, abscission was biased towards winds exceeding 5–6 m s–1. We conclude that timing of seed release can vastly enhance dispersal distances in wind-dispersed species, but increased risk costs may greatly limit the benefits of selecting wind conditions for long-distance dispersal, leading to moderate seed abscission thresholds, depending on local meteorological conditions and disturbances.

© 2015. American Geophysical Union. All Rights Reserved. Surface flow redistribution on flat ground from crusted bare soil to vegetated patches following intense rainfall events elevates plant available water above that provided by rainfall. The significance of this surface water redistribution to sustaining vegetation in arid and semiarid regions is undisputed. What is disputed is the quantity and spatial distribution of the redistributed water. In ecohydrological models, such nonuniform flows are described using the Saint-Venant equation (SVE) subject to a Manning roughness coefficient closure. To explore these assumptions in the most idealized setting, flume experiments were conducted using rigid cylinders representing rigid vegetation with varying density. Flow was induced along the streamwise x direction by adjusting the free water surface height H(x) between the upstream and downstream boundaries mimicking the nonuniformity encountered in nature. In natural settings, such H(x) variations arise due to contrasts in infiltration capacity and ponded depths during storms. The measured H(x) values in the flume were interpreted using the SVE augmented with progressively elaborate approximations to the roughness representation. The simplest approximation employs a friction factor derived from a drag coefficient (Cd) for isolated cylinders in a locally (but not globally) uniform flow and upscaled using the rod density that was varied across experiments. Comparison between measured and modeled H(x) suggested that such a "naive" approach overpredicts H(x). Blockage was then incorporated into the SVE model calculations but resulted in underestimation of H(x). Biases in modeled H(x) suggest that Cd must be varying in x beyond what a local or bulk Reynolds number predicts. Inferred Cd(x) from the flume experiments exhibited a near-parabolic shape most peaked in the densest canopy cases. The outcome of such Cd(x) variations is then summarized in a bulk resistance formulation that may be beneficial to modeling runon-runoff processes on shallow slopes using SVE.

Micrometeorological measurements of aerosol sized dry particle deposition velocity (Vd) onto forested canopies have significantly advanced over the past two decades and now include both—airborne and stationary platforms. However, the interpretation of these Vd measurements still relies on stationary and planar homogeneous flow assumptions only appropriate to flat-terrain conditions. Simplified model calculations were used to examine how variations in hill height (H) introduce biases in Vd when assumptions appropriate to flat terrain are applied to periodic and gentle 2-D cosine topography covered with tall and dense forested canopies. It was shown that increasing H reduced the variability in Vd for all aerosol sized particle diameters (dp) inside the canopy when the hill slope (H/L) remained constant (=0.1), where L is the cosine hill half-length. At the landscape scale, as may be monitored from airborne platforms, assumptions appropriate to flat-terrain appear accurate with increasing H for a constant and gentle H/L (= 0.1). Inside the canopy, variability in Vd tends to be larger than above the canopy for all H values and dp classes.DOI: 10.1111/j.1600-0889.2011.00528.x

Progress on many practical problems in eco-hydrology and eco-hydraulics are now requiring fundamental understanding of how topography modulates the basic properties of turbulence. In particular, how hilly terrain alters the ejection-sweep cycle, which is the main coherent transporting motion, remains a problem that received surprisingly little theoretical and experimental attention. Here, we investigate how boundary conditions, including canopy and gentle topography, alter the properties of the ejection-sweep cycle and whether it is possible to quantify their combined impact using simplified models. Towards this goal, we conducted two new flume experiments that explore the higher order turbulence statistics above a train of gentle hills. The first set of experiments were conducted over a bare surface while the second set of experiments were conducted over a modelled vegetated surface composed of tall and densely arrayed rods. Using this data, the connections between the ejection-sweep cycle and the higher order turbulence statistics across various positions above the hill surface were investigated. We showed that ejections dominate momentum transfer for both surface covers at the top of the inner layer. However, within the canopy and near the canopy top, sweeps dominate momentum transfer irrespective of the longitudinal position. Ejections remain the dominant momentum transfer mode in the entire inner region over the bare surface. These findings were well reproduced using an incomplete cumulant expansion and the measured profiles of the second moments of the flow. This agreement partly stems from the fact that the imbalance in the flux-transport terms, needed in the incomplete cumulant expansion, were well modelled using "local" gradient-diffusion principles. This finding suggests that in the inner layer, the higher-order turbulence statistics appear to be much more impacted by their relaxation history towards equilibrium rather than the advection-distortion history from the mean flow. Hence, we showed that it is possible to explore how various boundary conditions, including canopy and topography, alter the properties of the ejection-sweep cycle by quantifying their impact on the gradients of the second moments only. Implications to numerical modelling of turbulent flows using Reynolds-Averaged Navier Stokes equations are briefly discussed.

The transposition of atmospheric turbulence statistics from the time domain, as conventionally sampled in field experiments, is explained by the so-called ergodic hypothesis. In micrometeorology, this hypothesis assumes that the time average of a measured flow variable represents an ensemble of independent realizations from similar meteorological states and boundary conditions. That is, the averaging duration must be sufficiently long to include a large number of independent realizations of the sampled flow variable so as to represent the ensemble. While the validity of the ergodic hypothesis for turbulence has been confirmed in laboratory experiments, and numerical simulations for idealized conditions, evidence for its validity in the atmospheric surface layer (ASL), especially for nonideal conditions, continues to defy experimental efforts. There is some urgency to make progress on this problem given the proliferation of tall tower scalar concentration networks aimed at constraining climate models yet are impacted by nonideal conditions at the land surface. Recent advancements in water vapor concentration lidar measurements that simultaneously sample spatial and temporal series in the ASL are used to investigate the validity of the ergodic hypothesis for the first time. It is shown that ergodicity is valid in a strict sense above uniform surfaces away from abrupt surface transitions. Surprisingly, ergodicity may be used to infer the ensemble concentration statistics of a composite grass-lake system using only water vapor concentration measurements collected above the sharp transition delineating the lake from the grass surface. Citation: Higgins, C. W., G. G. Katul, M. Froidevaux, V. Simeonov, and M. B. Parlange (2013), Are atmospheric surface layer flows ergodic?, Geophys. Res. Lett., 40, 3342–3346, doi:10.1002/grl.50642.

Katabatic flows over alpine mountainous terrain differ from their forested or bare slope counterparts due to the presence of well-ventilated, short vegetation. The impact of a grass canopy and larger-scale pressure perturbations on the one-dimensional mean momentum balance is explored via theory and field measurements. The model presented here reproduces the measured velocity jet shape and turbulent flux gradients. These two features imply that even when Monin-Obuhkov similarity theory breaks down, its use for a stability adjusted mixing length remains effective to first order. Results reveal that outer layer pressure effects can be significant under low-speed wind conditions at the top of the thin katabatic layer when larger variations in the wind direction are observed. An analytical expression to estimate the jet height, which can be utilized in large-scale weather prediction models, shows the importance of including canopy effects for the thin katabatic flow region above the vegetation.

Loblolly pine trees (Pinus taeda L.) occupy more than 20% of the forested area in the southern United States, represent more than 50% of the standing pine volume in this region, and remove from the atmosphere about 500 g C murn:x-wiley:13541013:media:gcb13221:gcb13221-math-0001 per year through net ecosystem exchange. Hence, their significance as a major regional carbon sink can hardly be disputed. What is disputed is whether the proliferation of young plantations replacing old forest in the southern United States will alter key aspects of the hydrologic cycle, including convective rainfall, which is the focus of the present work. Ecosystem fluxes of sensible (urn:x-wiley:13541013:media:gcb13221:gcb13221-math-0002) and latent heat (LE) and large-scale, slowly evolving free atmospheric temperature and water vapor content are known to be first-order controls on the formation of convective clouds in the atmospheric boundary layer. These controlling processes are here described by a zero-order analytical model aimed at assessing how plantations of different ages may regulate the persistence and transition of the atmospheric system between cloudy and cloudless conditions. Using the analytical model together with field observations, the roles of ecosystem urn:x-wiley:13541013:media:gcb13221:gcb13221-math-0003 and LE on convective cloud formation are explored relative to the entrainment of heat and moisture from the free atmosphere. Our results demonstrate that cloudy–cloudless regimes at the land surface are regulated by a nonlinear relation between the Bowen ratio urn:x-wiley:13541013:media:gcb13221:gcb13221-math-0004 and root-zone soil water content, suggesting that young/mature pines ecosystems have the ability to recirculate available water (through rainfall predisposition mechanisms). Such nonlinearity was not detected in a much older pine stand, suggesting a higher tolerance to drought but a limited control on boundary layer dynamics. These results enable the generation of hypotheses about the impacts on convective cloud formation driven by afforestation/deforestation and groundwater depletion projected to increase following increased human population in the southeastern United States.

Competition for water among multiple tree rooting systems is investigated using a soil–plant model that accounts for soil moisture dynamics and root water uptake (RWU), whole plant transpiration, and leaf-level photosynthesis. The model is based on a numerical solution to the 3D Richards equation modified to account for a 3D RWU, trunk xylem, and stomatal conductances. The stomatal conductance is determined by combining a conventional biochemical demand formulation for photosynthesis with an optimization hypothesis that selects stomatal aperture so as to maximize carbon gain for a given water loss. Model results compare well with measurements of soil moisture throughout the rooting zone, of total sap flow in the trunk xylem, as well as of leaf water potential collected in a Loblolly pine forest. The model is then used to diagnose plant responses to water stress in the presence of competing rooting systems. Unsurprisingly, the overlap between rooting zones is shown to enhance soil drying. However, the 3D spatial model yielded transpiration-bulk root-zone soil moisture relations that do not deviate appreciably from their proto-typical form commonly assumed in lumped eco-hydrological models. The increased overlap among rooting systems primarily alters the timing at which the point of incipient soil moisture stress is reached by the entire soil–plant system.

Urban heat islands (UHIs) exacerbate the risk of heat-related mortality associated with global climate change. The intensity of UHIs varies with population size and mean annual precipitation, but a unifying explanation for this variation is lacking, and there are no geographically targeted guidelines for heat mitigation. Here we analyse summertime differences between urban and rural surface temperatures (ΔTs) worldwide and find a nonlinear increase in ΔTs with precipitation that is controlled by water or energy limitations on evapotranspiration and that modulates the scaling of ΔTs with city size. We introduce a coarse-grained model that links population, background climate, and UHI intensity, and show that urban–rural differences in evapotranspiration and convection efficiency are the main determinants of warming. The direct implication of these nonlinearities is that mitigation strategies aimed at increasing green cover and albedo are more efficient in dry regions, whereas the challenge of cooling tropical cities will require innovative solutions.

With the green economy being promoted as a path to sustainable development and food security within the African continent, the influx of agricultural land is proliferating at a rapid pace often replacing natural savannah forests. Where agriculture is primarily rainfed, the possible adverse impacts of agricultural land influx on rainfall occurrences in water-limited areas such as West Africa warrant attention. Using field observations complemented by model calculations in southeastern Burkina Faso, the main causes of a 10-30% suppressed daytime rainfall recorded over agricultural fields when referenced to natural savannah forests are examined. Measurements and model runs reveal that the crossing of the mixed layer height and lifting condensation levels, a necessary condition for cloud formation and subsequent rainfall occurrence, was 30% more frequent above the natural savannah forest. This increase in crossing statistics was primarily explained by increases in measured sensible heat flux above the savannah forest rather than differences in lifting condensation heights.

Parametrization of momentum surface roughness length in mountainous regions continues to be an active research topic given its application to improved weather forecasting and sub-grid scale representation of mountainous regions in climate models. A field campaign was conducted in the Val Ferret watershed (Swiss Alps) to assess the role of topographic variability and snow cover on momentum roughness. To this end, turbulence measurements in a mountainous region with and without snow cover have been analyzed. A meteorological mast with four sonic anemometers together with temperature and humidity sensors was installed at an elevation of 2500 m and data were obtained from October 2011 until May 2012. Because of the long-term nature of these experiments, natural variability in mean wind direction allowed a wide range of terrain slopes and snow depths to be sampled. A theoretical framework that accounted only for topographically induced pressure perturbations in the mean momentum balance was used to diagnose the role of topography on the effective momentum roughness height as inferred from the log-law. Surface roughness depended systematically on wind direction but was not significantly influenced by the presence of snow depth variation. Moreover, the wind direction and so the surface roughness influenced the normalized turbulent kinetic energy, which in theory should not depend on these factors in the near-neutral atmospheric surface layer. The implications of those findings to modeling momentum roughness heights and turbulent kinetic energy (e.g. in conventional K-epsilon closure) in complex terrain are briefly discussed.

Terrestrial ecosystems, occupying more than 25% of the Earth's surface, can serve as`biological valves' in regulating the anthropogenic emissions of atmospheric aerosolparticles and greenhouse gases (GHGs) as responses to their surrounding environments.While the signicance of quantifying the exchange rates of GHGs and atmosphericaerosol particles between the terrestrial biosphere and the atmosphere ishardly questioned in many scientic elds, the progress in improving model predictability,data interpretation or the combination of the two remains impeded bythe lack of precise framework elucidating their dynamic transport processes over awide range of spatiotemporal scales. The diculty in developing prognostic modelingtools to quantify the source or sink strength of these atmospheric substancescan be further magnied by the fact that the climate system is also sensitive to thefeedback from terrestrial ecosystems forming the so-called `feedback cycle'. Hence,the emergent need is to reduce uncertainties when assessing this complex and dynamicfeedback cycle that is necessary to support the decisions of mitigation andadaptation policies associated with human activities (e.g., anthropogenic emissioncontrols and land use managements) under current and future climate regimes.With the goal to improve the predictions for the biosphere-atmosphere exchangeof biologically active gases and atmospheric aerosol particles, the main focus of thisdissertation is on revising and up-scaling the biotic and abiotic transport processesfrom leaf to canopy scales. The validity of previous modeling studies in determiningivthe exchange rate of gases and particles is evaluated with detailed descriptions of theirlimitations. Mechanistic-based modeling approaches along with empirical studiesacross dierent scales are employed to rene the mathematical descriptions of surfaceconductance responsible for gas and particle exchanges as commonly adopted by alloperational models. Specically, how variation in horizontal leaf area density withinthe vegetated medium, leaf size and leaf microroughness impact the aerodynamic attributesand thereby the ultrane particle collection eciency at the leaf/branch scaleis explored using wind tunnel experiments with interpretations by a porous mediamodel and a scaling analysis. A multi-layered and size-resolved second-order closuremodel combined with particle uxes and concentration measurements within andabove a forest is used to explore the particle transport processes within the canopysub-layer and the partitioning of particle deposition onto canopy medium and forestoor. For gases, a modeling framework accounting for the leaf-level boundary layereects on the stomatal pathway for gas exchange is proposed and combined with sapux measurements in a wind tunnel to assess how leaf-level transpiration varies withincreasing wind speed. How exogenous environmental conditions and endogenoussoil-root-stem-leaf hydraulic and eco-physiological properties impact the above- andbelow-ground water dynamics in the soil-plant system and shape plant responsesto droughts is assessed by a porous media model that accommodates the transientwater ow within the plant vascular system and is coupled with the aforementionedleaf-level gas exchange model and soil-root interaction model. It should be notedthat tackling all aspects of potential issues causing uncertainties in forecasting thefeedback cycle between terrestrial ecosystem and the climate is unrealistic in a singledissertation but further research questions and opportunities based on the foundationderived from this dissertation are also briey discussed.

Problems in the area of land/biosphere-atmosphere interaction, hydrology, climate modeling etc. can be systematically organized as a study of turbulent flow in presence of boundary conditions in an increasing order of complexity. The present work is an attempt to study a few subsets of this general problem of turbulence in natural environments- in the context of neutral and thermally stratified atmospheric surface layer, the presence of a heterogeneous vegetation canopy and the interaction between air flow and a static water body in presence of flexible protruding vegetation. The main issue addressed in the context of turbulence in the atmospheric surface layer is whether it is possible to describe the macro-states of turbulence such as mean velocity and turbulent velocity variance in terms of the micro-states of the turbulent flow, i.e., a distribution of turbulent kinetic energy across a multitude of scales. This has been achieved by a `spectral budget approach' which is extended for thermal stratification scenarios as well, in the process unifying the seemingly different and unrelated theories of turbulence such as Kolmogorov's hypothesis, Heisenberg's eddy viscosity, Monin Obukhov Similarity Theory (MOST) etc. under a common framework. In the case of a more complex scenario such as presence of a vegetation canopy with edges and gaps, the question that is addressed is in what detail the turbulence is needed to be resolved in order to capture the bulk flow features such as recirculation patterns. This issue is addressed by a simple numerical framework and it has been found out that an explicit prescription of turbulence is not necessary in presence of heterogeneities such as edges and gaps where the interplay between advection, pressure gradients and drag forces are sufficient to capture the first order dynamics. This result can be very important for eddy-covariance flux calibration strategies in non-ideal environments and the developed numerical model can be used in related dispersion studies and coupled land atmosphere interaction models. For other more complex biosphere atmosphere interactions such as greenhouse gas emissions from wetlands, the interplay between air and water, often in presence of flexible aquatic vegetation, controls turbulence in water, which in turn affect the gas transfer processes. This process of wind shear induced wave-turbulent-vegetation interaction is studied for the first time in the laboratory and the state of turbulence as well as the bulk flow is found to be highly sensitive to environmental controls such as water height, wind speed, vegetation density and flexibility. This dissertation describes and gradually develops these concepts in an increasing order of complexity of boundary conditions. The first three chapters address the neutral and thermally stratified boundary layers and the last two chapters address the canopy edge problem and the air-water-vegetation experiments respectively.

A large portion of the anthropogenic emissions of greenhouse gases (GHGs) are cycled through the terrestrial biosphere. Quantifying the exchange of these gases between the terrestrial biosphere and the atmosphere is critical to constraining their atmospheric budgets now and in the future. These fluxes are governed by biophysical processes like photosynthesis, transpiration, and microbial respiratory processes which are driven by factors like meteorology, disturbance regimes, and long term climate and land cover change. These complex processes occur over a broad range of temporal (seconds to decades) and spatial (millimeters to kilometers) scales, necessitating the application of simplifying models to forecast fluxes at the scales required by climate mitigation and adaptation policymakers. Over the long history of biophysical research, much progress has been made towards developing appropriate models for the biosphere-atmosphere exchange of GHGs. Many processes are well represented in model frameworks, particularly at the leaf scale. However, some processes remain poorly understood, and models do not perform robustly over coarse spatial scales and long time frames. Indeed, model uncertainty is a major contributor to difficulties in constraining the atmospheric budgets of greenhouse gases. The central objective of this dissertation is to reduce uncertainty in the quantification and forecasting of the biosphere-atmosphere exchange of greenhouse gases by addressing a diverse array of research questions through a combination of five unique field experiments and modeling exercises. In this first chapter, nocturnal evapotranspiration -- a physiological process which had been largely ignored until recent years -- is quantified and modeled in three unique ecosystems co-located in central North Carolina, U.S.A. In the second chapter, more long-term drivers of evapotranspiration are explored by developing and testing theoretical relationships between plant water use and hydraulic architecture that may be readily incorporated into terrestrial ecosystem models. The third chapter builds on this work by linking key parameters of carbon assimilation models to structural and climatic indices that are well-specified over much of the land surface in an effort to improve model parameterization schemes. The fourth chapter directly addresses questions about the interaction between physiological carbon cycling and disturbance regimes in current and future climates, which are generally poorly represented in terrestrial ecosystem models. And the last chapter explores effluxes of methane and nitrous oxide (which are historically understudied) in addition to CO2 exchange in a large temperate wetland ecosystem (which is an historically understudied biome). While these five case studies are somewhat distinct investigations, they all: a) are all grounded in the principles of biophysics, b) rely on similar measurement and mathematical modeling techniques, and c) are conducted under the governing objective of reducing measurement and model uncertainty in the biosphere-atmosphere exchange of greenhouse gases.