Tarek S. El-Madany

One-year measurement of size-resolved particle fluxes in an urban area

Size-resolved particle flux measurements were carried out in an urban area from April 2012 to April 2013. Together with a standard eddy covariance system, two fast optical particle counters have been employed on a 65-meter-high tower in Münster, Germany. Particle number fluxes were directly calculated for particles with diameters from 0.06 to 10 µm within 16 individual size-bins. Whereas particle number concentrations show a distinct yearly pattern with maxima in winter and minima in summer, the flux time series is more multifaceted. Average daily maxima of 3.0e+07 particles m−2 s−1 occurred during winter while minima of 2.0e+06 particles m−2 s−1 were observed in fall. The size-resolved measurements revealed that during spring and summer a considerable number of accumulation mode particles deposits while a simultaneous net particle emission occurred, which is mostly driven by particles smaller than 0.12 µm. These bi-directional fluxes lead to a net mass deposition of up to 13.5 µg m−2 d−1. The tipping-point between the emission and deposition lay between 0.16 and 0.19 µm. In a comprehensive analysis of the flux and concentration time series, the degree of atmospheric stability, the seasons, and the type of source region have been identified as key influences for particle fluxes. Different responses between particle fluxes and concentrations have been found along these drivers.

Canopy‐atmosphere interactions under foggy condition—Size‐resolved fog droplet fluxes and their implications

Microphysical processes of fog and their spatial and temporal pattern are a challenge to study under natural conditions. This work focuses on the development of bidirectional fluxes of fog droplets above a forest canopy in northeastern Taiwan. Bidirectional fluxes occurred regularly, start from the smallest droplet class (<2.66 µm diameter), and subsequently extend to larger droplets up to 7.41 µm diameter. The development of the bidirectional fluxes with positive (upward) fluxes of smaller droplets and downward fluxes of larger fluxes is associated with a temperature gradient and with the activation of fog droplets according to the Kohler theory. Small fog droplets develop close to the canopy as result of evapotranspiration and subsequent condensation. The rapid growth of small fog droplets and the accelerated growth of activated droplets, a process which is more likely to occur at higher levels of the fog layer, lead to a sink of small droplets and a source of larger droplets within the fog. This is in accordance with the observation that positive droplet number fluxes of small fog droplets outnumber the negative fluxes from the larger fog droplets. For liquid water, the net flux is negative.

Using near-infrared-enabled digital repeat photography to track structural and physiological phenology in mediterranean tree–grass ecosystems

Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.

Spatio-temporal relationships between optical information and carbon fluxes in a mediterranean tree-grass ecosystem

Spatio-temporal mismatches between Remote Sensing (RS) and Eddy Covariance (EC) data as well as spatial heterogeneity jeopardize terrestrial Gross Primary Production (GPP) modeling. This article combines: (a) high spatial resolution hyperspectral imagery; (b) EC footprint climatology estimates; and (c) semi-empirical models of increasing complexity to analyze the impact of these factors on GPP estimation. Analyses are carried out in a Mediterranean Tree-Grass Ecosystem (TGE) that combines vegetation with very different physiologies and structure. Half-hourly GPP (GPPhh) were predicted with relative errors ~36%. Results suggest that, at EC footprint scale, the ecosystem signals are quite homogeneous, despite tree and grass mixture. Models fit using EC and RS data with high degree of spatial and temporal match did not significantly improved models performance; in fact, errors were explained by meteorological variables instead. In addition, the performance of the different models was quite similar. This suggests that none of the models accurately represented light use efficiency or the fraction of absorbed photosynthetically active radiation. This is partly due to model formulation; however, results also suggest that the mixture of the different vegetation types might contribute to hamper such modeling, and should be accounted for GPP models in TGE and other heterogeneous ecosystems.

Bigleaf—An R package for the calculation of physical and physiological ecosystem properties from eddy covariance data

We present the R package bigleaf (version 0.6.5), an open source toolset for the derivation of meteorological, aerodynamic, and physiological ecosystem properties from eddy covariance (EC) flux observations and concurrent meteorological measurements. A ‘big-leaf’ framework, in which vegetation is represented as a single, uniform layer, is employed to infer bulk ecosystem characteristics top-down from the measured fluxes. Central to the package is the calculation of a bulk surface/canopy conductance (Gs/Gc) and a bulk aerodynamic conductance (Ga), with the latter including formulations for the turbulent and canopy boundary layer components. The derivation of physical land surface characteristics such as surface roughness parameters, wind profile, aerodynamic and radiometric surface temperature, surface vapor pressure deficit (VPD), potential evapotranspiration (ET), imposed and equilibrium ET, as well as vegetation-atmosphere decoupling coefficients, is described. The package further provides calculation routines for physiological ecosytem properties (stomatal slope parameters, stomatal sensitivity to VPD, bulk intercellular CO2 concentration, canopy photosynthetic capacity), energy balance characteristics (closure, biochemical energy), ancillary meteorological variables (psychrometric constant, saturation vapor pressure, air density, etc.), customary unit interconversions and data filtering. The target variables can be calculated with a different degree of complexity, depending on the amount of available site-specific information. The utilities of the package are demonstrated for three single-level (above-canopy) eddy covariance sites representing a temperate grassland, a temperate needle-leaf forest, and a Mediterranean evergreen broadleaf forest. The routines are further tested for a two-level EC site (tree and grass layer) located in a Mediterranean oak savanna. The limitations and the ecophysiological interpretation of the derived ecosystem properties are discussed and practical guidelines are given. The package provides the basis for a consistent, physically sound, and reproducible characterization of biometeorological conditions and ecosystem physiology, and is applicable to EC sites across vegetation types and climatic conditions with minimal ancillary data requirements.

Partitioning eddy covariance water flux components using physiological and micrometeorological approaches

Eddy covariance (EC) provides ecosystem-scale estimates of photosynthesis (Ph) and evapotranspiration (ET; the sum of plant transpiration [T] and evaporation [Es]). Separating ET into its components is becoming necessary for linking plant-water use strategies to environmental variability. Based on optimality principles, a data-model based approach for partitioning ET was proposed and independently tested. Short-term responses of canopy-scale internal leaf-to-ambient CO2 (χ) were predicted based on a big-leaf representation of the canopy accounting for the influence of boundary-layer conductance. This representation allowed investigating stomatal behavior in accordance with the Ph estimates. With the objective of minimizing the carbon cost of transpiration, a novel optimization approach was implemented to develop solutions for an optimal stomatal conductance model as the basis to derive T. The Es was then calculated as a residual between the observed ET and modeled T. The proposed method was applied to long-term EC measurements collected above a Mediterranean tree-grass ecosystem. Estimated Es agreed with independent lysimeter measurements (r = 0.69). They also agreed with other partitioning methods derived from similarity theory and conditional sampling applied to turbulence measurements. These similarity schemes appeared to be sensitive to different χ parameterization. Measured Es was underestimated by 30% when χ was assumed constant (= 0.8). Diel and seasonal χ patterns were characterized in response to soil dryness. A surprising result was a large Es/ET throughout the seasons. The robustness of the results provides a new perspective on EC ET partitioning, which can be utilized across a wide range of climates and biomes.