Dominant Scale Research Articles

Investigation of Scaling and Materials’ Performance in Simulated Geothermal Brine

Geothermal energy generation faces challenges in efficiency, partly due to restrictions on reinjection temperatures caused by scaling issues. Therefore, developing strategies to prevent scaling is critical. This study aims to simulate the scaling tendencies and corrosion effects of geothermal fluids on various construction materials used in scaling reactor/retention tank systems. A range of materials, including carbon steel, austenitic stainless steel, duplex stainless steel, two proprietary two-part epoxy coatings, and thermally sprayed aluminium (TSA), were tested in a simulated geothermal brine. Experiments were conducted in a laboratory vessel designed to replicate the wall shear stress conditions expected in a scaling reactor. The tests revealed varying scaling tendencies among the materials, with minimal corrosion observed. The dominant scale formed was calcium carbonate, consistent with geochemical modelling. The findings suggest that despite the high operating temperatures, the risk of corrosion remains low due to the brine’s low chloride content, while the wettability of materials after immersion may serve as a useful indicator for selecting those that promote scaling.

The Unique Behavior of Vertical Velocity in Developing Deep Convection

AbstractWhen daytime tropical convection develops away from mesoscale disturbances, it typically transitions gradually from dry to shallow to deep convection on hourly timescales. The transition is commonly associated with the formation of larger horizontal boundary‐layer structures and an increasing level of cloud organization aloft. This study demonstrates that a spectral analysis of the resolved high‐resolution sub‐cloud flow features allows for a robust identification of dominant length scales and the quantification of their growth rates during the transition. Furthermore, it is shown that temperature, moisture, and horizontal winds develop multiple length scales with the largest ones growing up to several kilometers in magnitude. However, the vertical velocity behaves in a distinct manner developing significantly smaller values, comparable over land and ocean. This indicates stronger inherent limits of vertical velocity to self‐organize by size.

Quantification and assessment of the atmospheric boundary layer height measured during the AWAKEN experiment by a scanning LiDAR

The atmospheric boundary layer (ABL) height plays a key role in many atmospheric processes as one of the dominant flow length scales. However, a systematic quantification of the ABL height over the entire range of scales (i.e., with periods ranging from one minute to one year) is still lacking in literature. In this work, the ABL height is quantified based on high-resolution measurements collected by a scanning pulsed Doppler LiDAR during the recent American WAKE experimeNt (AWAKEN) campaign. The high availability of ABL height estimates (≈2200 collected over one year and each of them based on 10-min averaged statistics) allows to robustly assess five different ABL height models, i.e., one for convective thermal conditions and four for stable conditions. Thermal condition is quantified by a stability parameter spanning three orders of magnitude and probed by near-ground 3D sonic anemometry. The free-atmosphere stability, quantified by the Brunt–Väisälä frequency, is both calculated from simultaneous radiosonde measurements and obtained from the best fit of two of the chosen ABL height models. Good agreement is found between the data and three of the chosen models, quantified by mean absolute errors on the ABL height between 281 and 585 m. Furthermore, the seasonal variability of the convective ABL height model parameters (−15% to +23% with respect to the year baseline) agrees with the variability of buoyancy-generated turbulence caused by the variation in solar radiation throughout the year.

Extending speech emotion recognition systems to non-prototypical emotions using mixed-emotion model

In the conventional approach to speech emotion recognition (SER), the classifier is usually trained on acted emotional speech data to predict individual basic emotions. In this work, we extend the SER systems with the realistic assumption of the coexistence of multiple basic emotions in an utterance. We utilize the MSP-Podcast database for developing the SER system, which contains spontaneous speech utterances. From the primary and secondary emotion annotations of this database, we organize six prototypical and seven non-prototypical emotions. We then propose the mixed-emotion model and express the non-prototypical emotions as a linear combination of prototypical emotions. The combination weights of the mixed-emotion model are computed using a normalized dominance scale based algorithm inspired by the integration of basic emotion theory and dimensional emotion theory in human psychology. We first train a prototypical SER model using the ECAPA-TDNN architecture. The softmax predictions from this model serve as emotion profile inputs to the mixed-emotion model, which then predicts the non-prototypical emotions. Assuming the coexistence of multiple emotions, we only apply the utterances with uniform emotion profiles to the mixed-emotion model. The developed system continues with the conventional SER model if the emotion profile tends to delta function owing to the probable occurrence of a single prototypical emotion. We develop the proposed mixed-emotion model based SER framework using MFCC and wav2vec 2.0 extracted features. Further, we show that due to human perception variations, there exist prominent annotation variations in the non-prototypical emotion ground truths. To address that, we extend the supervised evaluation protocols in four different formulations that capture the subjective variability at different levels. The proposed system shows a best-case performance improvement of 7.10% and 8.39% over the conventional prototypical SER model for the MFCC and wav2vec 2.0 features, respectively.

Visualizing plasmons and ultrafast kinetic instabilities in laser-driven solids using X-ray scattering

Ultra-intense lasers that ionize atoms and accelerate electrons in solids to near the speed of light can lead to kinetic instabilities that alter the laser absorption and subsequent electron transport, isochoric heating, and ion acceleration. These instabilities can be difficult to characterize, but X-ray scattering at keV photon energies allows for their visualization with femtosecond temporal resolution on the few nanometer mesoscale. Here, we perform such experiment on laser-driven flat silicon membranes that shows the development of structure with a dominant scale of 60 nm in the plane of the laser axis and laser polarization, and 95 nm in the vertical direction with a growth rate faster than 0.1 fs−1. Combining the XFEL experiments with simulations provides a complete picture of the structural evolution of ultra-fast laser-induced plasma density development, indicating the excitation of plasmons and a filamentation instability. Particle-in-cell simulations confirm that these signals are due to an oblique two-stream filamentation instability. These findings provide new insight into ultra-fast instability and heating processes in solids under extreme conditions at the nanometer level with possible implications for laser particle acceleration, inertial confinement fusion, and laboratory astrophysics.

Measurement of Anisotropies in Supernova Remnant Observations and Their Interpretation Using Numerical Models

Supernova remnants (SNRs) exhibit varying degrees of anisotropy, which have been extensively modeled using numerical methods. We implement a technique to measure anisotropies in SNRs by calculating power spectra from their high-resolution images. To test this technique, we develop 3D hydrodynamical models of SNRs and generate synthetic X-ray images from them. Power spectra extracted from both the 3D models and the synthetic images exhibit the same dominant angular scale, which separates large-scale features from small-scale features due to hydrodynamic instabilities. The angular power spectrum at small length scales during relatively early times is too steep to be consistent with Kolmogorov turbulence, but it transitions to Kolmogorov turbulence at late times. As an example of how this technique can be applied to observations, we extract a power spectrum from a Chandra observation of Tycho’s SNR and compare with our models. Our predicted power spectrum picks out the angular scale of Tycho’s fleecelike structures and also agrees with the small-scale power seen in Tycho. We use this to extract an estimate for the density of the circumstellar gas (n ∼ 0.28 cm−3), consistent with previous measurements of this density by other means. The power spectrum also provides an estimate of the density profile of the outermost ejecta. Moreover, we observe additional power at large scales, which may provide important clues about the explosion mechanism itself.

Enhancing the description of multi-time-scale geophysical phenomena: Incorporating finite time Scale separation and feedback, illustrated with the case of a 1D variable of interest.

Stochastic approaches play a vital role in weather, climate, and, more in general, geophysics systems, addressing processes and scales beyond the resolution of deterministic models. Similar to equilibrium/non-equilibrium thermodynamics, intricate fast and local dynamics may not always be the primary focus. Practical applications often prioritize observables capturing phenomena at dominant temporal and spatial scales. Developing models for these "large-scale" observables, resulting from averaging fast and local contributions, can be simplified into Low Order Models (LOMs) with reduced degrees of freedom described by ordinary differential equations. Unresolved degrees of freedom are introduced as stochastic components, exhibiting either Markovian or non-Markovian characteristics. The challenge lies in deriving dependable stochastic differential equations representing the statistics of real large-scale, slow features in the climate/ocean system. While paralleling material physics, it is crucial to recognize that direct transfer of tools and outcomes is hindered by the non-Hamiltonian nature of climate/geophysical LOMs and the impracticality of a Markovian treatment of noise due to wide-ranging time scales. A critical examination of the conventional statistical mechanics approach, customized for such LOMs, becomes essential. To this end, we propose utilizing an approach based on the operator cumulant method, which has been recently revisited and generalized, along with the linear response method in a non-Hamiltonian setting. Formal results are then derived, and applications to some typical classes of examples are presented to clarify this approach.

Social rank affects the endocrine response to frequent regroupings in grazing dairy heifers

The objectives of this study were to determine the social behavior response to repeated social regrouping (SR), and if social rank and the changes of social rank affect the growth rate and some metabolites and hormones linked to energy status, in “resident” replacement dairy heifers subjected to SR for 205 d. Fourteen dairy heifers (153.3 ± 16.1 kg; 9 to 11 mo old), maintained under grazing conditions, were regrouped every 21 d with 5 new animals (total = 10 SR). Two days after each SR, heifers were weighed and their withers height was measured, and blood samples for nonesterified fatty acids, glucose, and IGF-1 were taken. Concentrations of nonesterified fatty acids, glucose, and IGF-1 were taken. Social behavior was registered by continuous sampling and social status was calculated by the ETlog software, considering the total number of agonistic interactions on 2 d before and 7 d after each SR. A dominance scale was constructed in each SR, and heifers were categorized as high-ranked (HRA), medium-ranked (MRA), and low-ranked (LRA). In addition, the social rank in the first and the last 5 SR were compared, resulting in 3 categories: heifers that remained in the same social rank (Mai), and heifers that lowered (Low) and raised (Rai) their social ranks. Variables were analyzed by repeated measures using a generalized lineal mixed model, considering the social rank in each SR or the change in social rank, the number of SR and their interaction as main effects, and the farm of origin and animal as random effects. Heifers performed more agonistic (2.6 vs. 1.8 ± 0.6, day of SR and 7 d later, respectively) and total (3.8 ± 1.2 vs. 2.5 ± 0.7, day of SR and 7 d later, respectively) interactions on the day of each SR than 7 d after, whereas the number of interactions decreased after the first 2 SR. Medium-ranked heifers presented greater IGF-1 concentrations than HRA heifers at SR1, SR4, and SR9, and than LRA heifers at SR3 and SR4, whereas IGF-1 concentrations were greater in HRA heifers than MRA heifers at SR3 and SR7. In addition, LRA heifers had greater IGF-1 concentrations than MRA ones at SR3 and compared with HRA heifers at SR9. Heifers that lowered their social had greater IGF-1 concentrations than Mai heifers along the SR (132.5 ± 17.1 vs. 97.8 ± 11.2 ng/mL, Low and Mai heifers, respectively) and at SR1, SR3, and SR9. In conclusion, although regrouping animals according to their characteristics can facilitate farm handling, it should be considered that endocrine profile may be affected according to heifers' position in the social hierarchy.

Time-dependent dispersion coefficients for the evolution of displacement fronts in heterogeneous porous media

We present an approach for quantifying displacement fronts in heterogeneous porous media based on the concept of time-dependent apparent dispersion coefficients. The concept of constant asymptotic macrodispersion generally overestimates the area swept by a displacement front and leads to unrealistic upstream dispersion. We show that the large-scale front spreading can be captured by a one-dimensional advection–dispersion equation that is parameterized by a suitably chosen temporally evolving dispersion coefficient. For purely advective front spreading, we derive an analytical expression based on a predictive continuous time random walk approach, which applies to highly heterogeneous porous media. This analysis elucidates the variability of solute travel times as the key longitudinal spreading mechanism. It shows that the evolution of dispersion can be captured as the sum of exponentials that decay on two dominant time scales. In a particle-based picture, these scales mark the short time at which transported particles start exploring the flow variability and the large time at which the slowest particles start decorrelating their transport velocity. Based on these insights, we propose a heuristic formula that accounts for the impact of local-scale dispersion as an additional decorrelation mechanism. The heuristic expression for the longitudinal dispersion coefficient captures solute spreading for a broad range of Péclet numbers and heterogeneity variances. The proposed approach is tested against direct numerical simulations. It provides a robust and fast method for quantifying the evolution of displacement fronts in heterogeneous porous media with possible applications, for example, in groundwater contamination modelling, underground gas storage, and geothermal energy production.

Self-assessment of emotional arousal in adolescents and young adults

Introduction. The deep level of integration of cognitive and emotional processes must be taken into account in the modern education system and in the training of teaching staff. Adolescence is characterized by intense changes in the emotional sphere. At the same time, the data on emotional processes changes in adolescents are quite contradictory. In addition, most studies of emotions in this age period were carried out in Western culture and the problem of cross-cultural comparisons of emotional development patterns rarely attract the attention of researchers. To correctly measure a person’s emotional sphere, methods that have passed the validation procedure in the country where the work is planned are needed. One way to study emotional reactions is the IAPS database of emotionally evocative photographs. The aim of the study was to compare emotional performance at different stages of adolescence and early adulthood in as part of testing emotionally charged IAPS stimuli on a Russian adolescent sample. Materials and methods. The study involved 436 adolescents and young adults. Four groups were compared: 10-12 years old (49 boys and 51 girls), 13-14 years old (48 boys, 48 girls), 15-17 years old (45 boys, 75 girls) and 18-25 years old (24 men and 96 women). Participants in the study were required to evaluate the emotions that arose in response to the presentation of IAPS pictures on the screen on the scales of valence (feeling of pleasure - displeasure), arousal (strength of excitation) and dominance (feeling of control over the situation). Results. The valence, arousal and dominance scores were obtained for Russian samples 10-12 years old, 13-14 years old, 15-17 years old, 18-25 years old, with a high level of reliability. In addition, cross-cultural differences from American norms were demonstrated, emphasizing the necessity to use scores developed on representatives of the culture where the study is planned to be carry out. The study also showed that in adolescence there is a change in the affective space formed by the scale of valence and arousal, which indicates a crucial change in the emotional sphere during this period. The comparison showed significant differences on emotional scales for both positive and negative emotions between different age groups, indicating the dynamics of emotional development. The complex pattern of differences in valence, arousal and dominance scales between different age groups suggests non-linear changes. Conclusion. The standards for the valence, arousal and dominance scales of the IAPS database for Russian adolescents and young adults, which can be used to measure the emotional variables are presented in a study.

On top of the world: mapping the Nordic crime fiction boom based on translation data

ABSTRACT Nordic Noir – crime fiction originating in the Nordic region – is one of the most significant international publishing success stories of the twenty-first century. Despite its importance, no one has mapped and analysed the circulation of Nordic Noir as world literature. The present study addresses this knowledge gap by quantitatively mapping the global translation flows of Nordic Noir during the period of its greatest international success, from 2000 to 2020. Drawing on the “Nordic Noir in Translation Database” containing 8,886 translations from all five main Nordic languages – Danish, Finnish, Icelandic, Norwegian and Swedish – this study is the first to chart the so-called “boom” in a comparative macro perspective, bringing to light the nuances of its international dissemination and impact. Key findings relate to the chronological structure of the boom, the scale of Swedish dominance and the role of a small group of top authors in driving overall translation rates.

Telic-Paratelic Dominance and Heart Rate Variability in Athletes Engaged in Power and Endurance Training.

Purpose: The current study aimed to evaluate the telic-paratelic tendency and heart rate variability in athlete participants from different sports activities.Methods: We assigned 117 healthy participants (M age = 20, SD = 3 years) into three groups according to their training activity: power-trained (PT; n=43), endurance-trained (ET; n=36), and healthy untrained individuals (n=38). We assessed their telic-paratelic tendencies with the validated Telic Dominance Scale and their autonomic nervous system activity with heart rate variability (HRV) analyses.Results: Our findings revealed no significant differences in the telic-paratelic tendencies between ET and PT groups. However, significant differences were observed between athletes and untrained individuals (p = 0.001). Indeed, compared to untrained participants, ET and PT athletes had a greater telic tendency (both p = 0.001), were more focused on planning orientation (ET: p = 0.003; PT: p=0.001), and less often avoided arousal or activation (For ET 31% and for PT 26% of participants). The paratelic tendency was more important in untrained individuals, with most of these participants lacking in seriousmindedness and planning. In addition, we found higher HRV in paratelic ET athletes (SDNN p = 0.050, LF p = 0.022, and LF/HF p = 0.031) compared to their telic peers.Conclusion: our results suggest that sport activity did not influence the telic-paratelic tendency. Nevertheless, this tendency differentiates trained from untrained participants. HRV was higher among paratelic ET athletes, potentially reflecting less stress and more training adaptability in these athletes.

Mixed-Material Feedstocks for Cold Spray Additive Manufacturing of Metal–Polymer Composites

High-performance polymers such as poly(ether ether ketone) (PEEK) are appealing as composite components for a wide variety of industrial and medical applications due to their excellent thermomechanical properties. However, conventional PEEK metallization methods can often lead to poor quality control, low deposition rate, and high cost. Cold spray is a promising potential alternative to produce polymer–metal composites rapidly and inexpensively due to its relatively mild operating conditions and high throughput. In this study, we investigated the deposition characteristics of metal–polymer composite feedstock, composed of PEEK powder and copper flake in varying ratios, onto a PEEK substrate. Copper-PEEK powder blends were prepared by both hand-mixing and cryogenic milling (cryomilling), which predominantly creates composite particles with micron-scale copper domains coating PEEK particle surfaces. This process non-monotonically affects the relative dominance and length scales of the multiple contributing deposition mechanisms present in mixed-material cold spray. In low-pressure cold spray, deposits showed significant changes in deposition efficiency and composition as a result of milling, with improvements in these characteristics most dramatic at lower Cu fractions. Deposits of a cryomilled blend of nominally 30 vol.% copper in PEEK exhibited minimal porosity under scanning electron microscopy, complete retention of powder composition, and the highest deposition efficiency among all samples tested. Notably, neither neat PEEK nor neat Cu meaningfully deposited at the same mild conditions as this 30 vol.% Cu blend, indicating a synergistic departure from linear mixing rules driven by the relative balance of local deposition interactions (e.g., hard–soft, soft–soft, etc.). Intentional powder and process design toward optimizing this balance may facilitate cold spray metallization applications.

Asymptotic scaling relations for rotating spherical convection with strong zonal flows

We analyse the results of direct numerical simulations of rotating convection in spherical shell geometries with stress-free boundary conditions, which develop strong zonal flows. Both the Ekman number and the Rayleigh number are varied. We find that the asymptotic theory for rapidly rotating convection can be used to predict the Ekman number dependence of each term in the governing equations, along with the convective flow speeds and the dominant length scales. Using a balance between the Reynolds stress and the viscous stress, together with the asymptotic scaling for the convective velocity, we derive an asymptotic prediction for the scaling behaviour of the zonal flow with respect to the Ekman number, which is supported by the numerical simulations. We do not find evidence of distinct asymptotic scalings for the buoyancy and viscous forces and, in agreement with previous results from asymptotic plane layer models, we find that the ratio of the viscous force to the buoyancy force increases with Rayleigh number. Thus, viscosity remains non-negligible and we do not observe a trend towards a diffusion-free scaling behaviour within the rapidly rotating regime.

Detecting periodic time scales of changes in temporal networks

Abstract Temporal networks are commonly used to represent dynamical complex systems like social networks, simultaneous firing of neurons, human mobility or public transportation. Their dynamics may evolve on multiple time scales characterizing for instance periodic activity patterns or structural changes. The detection of these time scales can be challenging from the direct observation of simple dynamical network properties like the activity of nodes or the density of links. Here, we propose two new methods, which rely on already established static representations of temporal networks, namely supra-adjacency and temporal event graphs. We define dissimilarity metrics extracted from these representations and compute their power spectra from their Fourier transforms to effectively identify dominant periodic time scales characterizing the changes of the temporal network. We demonstrate our methods using synthetic and real-world data sets describing various kinds of temporal networks. We find that while in all cases the two methods outperform the reference measures, the supra-adjacency-based method identifies more easily periodic changes in network density, while the temporal event graph-based method is better suited to detect periodic changes in the group structure of the network. Our methodology may provide insights into different phenomena occurring at multiple time scales in systems represented by temporal networks.

Multi‐Time Scale Variations in Atlantic Niño and a Relative Atlantic Niño Index

AbstractAtlantic Niño is a leading mode of climate variability in the tropical Atlantic Ocean with important regional impacts. Tropical Atlantic sea surface temperatures (SSTs) connected with Atlantic Niño exhibit notable multi‐time scale variations, including a quasi‐linear warming trend and sub‐annual to interdecadal variability associated with different physical processes. Contrasting the tropical Pacific SST associated with the El Niño‐Southern Oscillation (ENSO), which has a weak trend and quasi‐periodic oscillatory variability with a period of 2–7 years, the ATL3 index, the primary index for monitoring the Atlantic Niño, has no dominant time scale, that is likely responsible for its low prediction skills. Following the same spirit as the relative Niño3.4 index, we demonstrate that a relative ATL3 index, which is defined as the difference between the raw ATL3 index and the global SST anomaly, provides distinct advantages for monitoring the sub‐annual‐to‐interdecadal variations for Atlantic Niño in real time.

Coexistence of two dune scales in a lowland river

Abstract. A secondary scale of bedforms, superimposed on larger, primary dunes, has been observed in fluvial systems worldwide. This notwithstanding, very little is known about the morphological behavior and characteristics of this secondary scale. This study aims to better characterize and understand how two dune scales coexist in fluvial systems and how both scales adapt over time and space, considering their interdependence. The study is based on analysis of a large biweekly multibeam echo sounding dataset from the river Waal, a lowland sand-bedded river. Results reveal that the secondary dune scale is ubiquitous across space and time and not limited to specific flow or transport conditions. Whereas primary dunes lengthen during low flows, secondary dune height, lee slope angle, and length correlate with discharge. Secondary dune size and migration strongly depend on the primary dune lee slope angle and height. Secondary dunes can migrate over the lee slope of low-angled primary dunes, and their height is inversely correlated to the upstream primary dune height and lee slope angle. In the Waal river, a lateral variation in bed grain size, attributed to shipping, largely affects dune morphology. Primary dunes are lower and less often present in the southern lane, where grain sizes are smaller. Here, secondary bedforms are more developed. At peak discharge, secondary bedforms even become the dominant scale, whereas primary dunes entirely disappear but are re-established during lower flows.

Significant gender-specific difference in brain lateralization of schizophrenia patients assessed by new combined foot dominance scale

ObjectiveReduced hemispheric asymmetry has been identified as a potential risk factor for schizophrenia, characterized by diminished brain lateralization and a lack of dominance in the left hemisphere. Moreover, there is growing evidence of disrupted connectivity between various cortical regions. This study aimed to investigate gender differences in left-footedness as a potential biological marker for neuronal dysontogenesis in individuals with schizophrenia and control subjects.Materials and methodsA New Combined Foot Dominance Scale (14 foot tests), comprising a Modified Chapman & Chapman Subscale (10 foot tests) and a Complex Tasks Subscale (four foot tests) was administered as performance tasks in 180 subjects [98 schizophrenia patients with mean age 34.45 years (SD = 15.67, range 23–79) for men and 42.20 years (SD = 11.38, range 21–63) for women and 82 controls with a mean age 34.70 years (SD = 16,82, range 18–79) for men and 44.50 years (SD = 10.73, range 23–67)]. As our data are not continuous and lacks normal distribution, the non-parametric Mann–Whitney test was used for comparing categorical data.ResultsThe mean left-footedness, as assessed by the New Combined Foot Dominance Scale, is significantly higher in individuals with schizophrenia compared to control subjects. Our findings from inter-gender comparisons reveal that female schizophrenia patients exhibit a significantly greater average left-footedness than female control subjects, while in males no such a statistical significant difference is detected.ConclusionLeft foot dominance is higher in patients with schizophrenia than in control subjects and women contribute significantly more to this difference.

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET‐CH4 Sites Using Wavelet Analyses

AbstractProcess‐based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site‐level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model‐observation disagreements are mainly at multi‐day time scales (<15 days); (b) most of the models can capture the CH4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability, especially at short time scales, in future wetland CH4 model developments.

Coherent structures detection within a dense Alpine forest

The influence of coherent vortices on the turbulence structure above and below a dense plant canopy is investigated using turbulence measurements collected at five levels on top and inside a coniferous forest on an Alpine Plateau. Five different stability regimes, from free convection to very stable stratification, were identified and considered in the analysis. Coherent structures are detected by fitting the vertical velocity auto-correlation functions with a theoretical oscillating function. This allowed to evaluate the coherent vortices characteristic timescales and to discriminate between turbulent data subsets characterized by fine-scale turbulence and subsets in which turbulence is dominated by coherent structures generated at the canopy top. An original methodology to fit cross-correlation function and to single out the most energetic frequency in presence of periodic behaviour is presented and applied to the turbulent momentum flux. The analysis shows how not far from neutral conditions the dominant time scale of the momentum flux is mainly determined by the longitudinal wind velocity component, rather than vertical one, while in free convection and very stable conditions coherent vortices do not seem to influence the momentum transport, dominated by large-scale structures. This is confirmed by the fine-scale turbulence and coherent structures efficiency in turbulence transport throughout the stability regimes.