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Atmospheric Boundary Layer Flows: Their Structure And Measurement
... where P is pressure in hPa and T is temperature in Kelvin. Commonly used methods to obtain C 2 T from time series of temperature include power spectrum and structure function approaches [1,2]. In this analysis, we compare calculations based on these two techniques as well as two other less-commonly utilized methods, specifically, a nearest neighbor technique [3] and a Bayesian statistical method [4]. ...
... Computing the integral of this spectrum provides an estimation of the total variance. The assumption of locally isotropic turbulence within the inertial subrange establishes a connection between the structure function parameter C 2 T of a fluctuation component of the temperature T and the one-dimensional Fourier power spectrum S TT , commonly referred to as the Kolmogorov inertial subrange spectrum [2]: ...
... To obtain the power spectra of temperature, a 5-min time series of temperature measurements from ultrasonic anemometers was subjected to FFT. Prior to computing the power spectrum, a linear detrending process was applied to remove long-term variations, such as those induced by the diurnal cycle, which are not relevant for small-scale turbulence [2]. Additionally, high-frequency filtering was employed to reduce potential noise caused by aliasing, which can be detected by an approximate increase of one in the power spectrum. ...
Wind speed and sonic temperature measured with ultrasonic anemometers are often utilized to estimate the refractive index structure parameter $C_n^2$ C n 2 , a vital parameter for optical propagation. In this work, we compare four methods to estimate $C_n^2$ C n 2 from $C_T^2$ C T 2 , using the same temporal sonic temperature data streams for two separated sonic anemometers on a homogenous path. Values of $C_n^2$ C n 2 obtained with these four methods using field trial data are compared to those from a commercial scintillometer and from the differential image motion method using a grid of light sources positioned at the end of a common path. In addition to the comparison between the methods, we also consider appropriate error bars for $C_n^2$ C n 2 based on sonic temperature considering only the errors from having a finite number of turbulent samples. The Bayesian and power spectral methods were found to give adequate estimates for strong turbulence levels but consistently overestimated the $C_n^2$ C n 2 for weak turbulence. The nearest neighbors and structure function methods performed well under all turbulence strengths tested.
... Numerical steep topography can also lead to high flow slope angles and high turbulence regions (even flow recirculation areas) [4,5,6], which may cause an increase in wind turbine loading and power variability if the wind turbine location is not carefully decided. The topology of the flow in these regions is affected not only by the topography but also by the stability conditions of the atmosphere [4]. ...
... Numerical steep topography can also lead to high flow slope angles and high turbulence regions (even flow recirculation areas) [4,5,6], which may cause an increase in wind turbine loading and power variability if the wind turbine location is not carefully decided. The topology of the flow in these regions is affected not only by the topography but also by the stability conditions of the atmosphere [4]. As a result of the dynamic behavior of the ABL during the diurnal cycle, wind turbine performance and wake propagation are affected by the change in atmospheric stability, as the terrain-induced flow and wind turbine wake interact dynamically. ...
... The prime and overbar denote the fluctuation and time-average, respectively. In complex terrain, non-dimensional Froude number, F L , can also be used to determine the atmospheric stability in areas where hills or mountainous regions occupy a significant portion of the ABL [4]. It is defined as ...
Comparing numerical simulations of wind turbine wakes in neutral atmospheric boundary layer (ABL) flow over complex terrains with full-scale experiments is not always straightforward. Pure neutral ABL conditions are rarely found in the atmosphere as the characteristics of the ABL change during the diurnal cycle. This study presents some insights into how a single wind turbine (WT) and its wake behave under near-neutral ABL conditions in complex terrain. The Perdigão Valley in Portugal was chosen as the test case as it is an excellent case study of three-dimensional flow in complex terrain to validate numerical simulations of WT wake with experimental data due to the availability of extensively deployed remote sensing equipment (e.g., German Aerospace Center (DLR) and Technical University of Denmark (DTU) multi-Doppler lidars). The Weather Research and Forecasting (WRF) [1] model is utilized in large-eddy simulation (LES) mode in order to simulate the period of interest with a multi-scale modeling approach. Five nested domains, with the finest domain having a spatial resolution of 5 m, are used to dynamically downscale mesoscale flow features to microscale. A generalized actuator line (GAL) WT parameterization is used to model the wind turbine-flow interaction. WRF-LES-GAL (hereinafter referred to as WLG) results compare quite well with the experimental data obtained from lidars and meteorological mast, with minor biases between the simulated and observed data. Due to insufficient buoyancy generation from the WRF-LES model, the simulated track wake was found to have lower vertical deflection compared to the lidar data; hence, no recirculation zone is observed in the valley. Overall, the WLG model is able to reproduce the wake characteristics observed on the first ridge top into the valley, as well as the power and thrust generation, and can be used for further analysis of other stability conditions.
... In most applications, the scales not captured by the sensor include part of the inertial range and the dissipative scales of the atmospheric flow. Furthermore, the supporting structure of the sensor can also cause flow distortion (Kaimal and Finnigan 1994). Therefore, many turbulence phenomena related to the smallest scales of the flow-including the direct estimation of the turbulent kinetic energy (TKE) dissipation rate itself-cannot be investigated using typical field experiment data. ...
... From this calibration, 33 subblocks of 2 min data were obtained, which were averaged to provide the results presented next. Because a 2 min sample size can be small compared to the integral time scale, tapering the time series is recommended to compensate for the sample size effect on the spectra (Kaimal and Finnigan 1994). However, when comparing the 2 min sonic spectra to the original 3 h spectra, the spectral loss was negligible for the analyses Shapkalijevski et al. (2016)), h ≈ 10 m is the canopy height and L • = 22.7 m is the Obukhov length. ...
... Re L 3.6 × 10 5 performed here, and tapering the time-series using a Hamming window (as suggested by Kaimal and Finnigan (1994)) had virtually no effect (not shown). Therefore, tapering was also not included in the final analyses. ...
The behavior of small-scale atmospheric turbulence is investigated using the three-dimensional Canopy Horizontal Array Turbulence Study hot-film data. The analysis relies on an in situ calibration versus simultaneous sonic anemometer measurements. The calibration is based on King’s law and geometric relationships between the individual hot-film sensors, and is able to account for the errors associated with sensors’ misalignment and the high turbulence intensity. The details of the calibration are provided, and its performance is validated by comparing results of spectra and structure functions with standard wind-tunnel data and model spectra. A single 3 h block of data was selected, containing 33 subblocks of 2 min data without error gaps, whose statistics were averaged to provide smooth results. These data were measured above canopy under stable conditions, and correspond to a Taylor Reynolds number Reλ≈1550\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Re_\lambda \approx 1550$$\end{document}. The agreement with wind tunnel results for a similar Reλ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Re_\lambda $$\end{document} and with model predictions provides a validation for the in situ calibration method applied. Furthermore, the results indicate a presence of the bottleneck effect in the lateral and vertical spectra, in addition to a lack of inertial range in the second-order structure function due to the low Reynolds number. An additional analysis of the effect of Reynolds number on the inertial range is provided using atmospheric data from the literature.
... W literaturze spotykane jest także pojęcie pokrewne: atmosferyczna warstwa graniczna (ang. atmospheric boundary layer, ABL) [444,445]. Parametry tej warstwy mają duże znaczenie dla określenia zmienności stężenia gazów śladowych w atmosferze. Pojawiająca się w nocy warstwa przypowierzchniowa (ang. ...
... W nocy jest dodatnia, natomiast w godzinach południowych ujemna. Zakłada się, że dla wartości poniżej 0,25 występują warunki sprzyjające rozwojowi warstwy konwekcyjnej [445,465]. W zakresie 0-0,25 głównym czynnikiem powodującym konwekcję turbulentną będzie jedynie prędkość wiatru i szorstkość aerodynamiczna powierzchni [463,466]. Przy ujemnych wartościach Ri b siła wyporu związana z warunkami termicznymi na danym terenie staje się czynnikiem dominującym w zjawisku konwekcji wirowej. ...
... where A(t * ) represents the autocorrelation function at time lag t * . The integral of the autocorrelation curve first provides the integral time scale T w , which can be transferred into a length scale by L T = ⋅ U w w using Taylor's hypothesis of "frozen turbulence" transported by the mean wind 21 . The detrended 20 min time series of U and w are shifted by time lags t * between 0 s and 20 min, and for each lag, the autocorrelation coefficient A of the original with the shifted time series is calculated. ...
... The detrended 20 min time series of U and w are shifted by time lags t * between 0 s and 20 min, and for each lag, the autocorrelation coefficient A of the original with the shifted time series is calculated. As an approximation for the integral under the A w (t * ) curve, the curve is assumed to be an exponential function, and the intercept A t e 19,21 . If the time scale is larger than the time series segment, the result is excluded. ...
Wind loading is a primary contributor to structural design costs of concentrating solar-thermal power collectors, such as heliostats and parabolic troughs. These structures must resist the mechanical forces generated by turbulent wind, while the reflector surfaces must maintain optimal optical performance. Studying wind-driven loads at a full-scale, operational concentrating solar-thermal power plant provides insights into the wind impact on the solar collector field beyond the capabilities of wind tunnel tests or state-of-the-art simulations. We conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant over a two-year period. The measurement setup included meteorological masts and structural load sensors on four trough rows. Additionally, a lidar scanned the horizontal plane above the trough field. In this study, we describe the high-resolution dataset characterizing the complex flow field and resulting structural loads. This first-of-its-kind dataset will enhance the understanding of wind loading on collector structures and will help in designing the next-generation solar collectors and photovoltaic trackers.
... The main objective of the present work is to investigate the response of a fixed offshore wind turbine structure subjected to random loading due to wind as well as wave and to study how the response can be controlled by using multiple tuned mass dampers distributed along the tower. To meet the objective of the present work, a lumped mass model of an offshore wind turbine is considered and subjected to random wind and wave loading that are simulated using Kaimal spectrum [29] and Pierson and Maskowitz (1964) spectrum, respectively [27]. The force spectra are converted to time domain using conventional techniques. ...
... To calculate this, a Power Spectral Density Function (PSDF) matrix denoted as S vv is derived from the along-wind forces applied to the structure and the turbulence between two specific points for a structure with N degrees of freedom (DOF). Holmes [27] (2018) introduced a formula to estimate the total drag force in the along-wind direction at the j th height, which is expressed as follows: [29], Simiu (1974) [46], and Simiu and Scanlan (1996) [47]. This PSDF is formulated as follows: ...
... However, the origin of daytime TKE is related to the radiative energy of the sun heating the earth's surface, while nighttime TKE comes mainly from low-level jets (LLJ) near the ground. Thus, the daytime ABL is called the Convective Mixed Layer (CML), with the Mixed Layer (ML) as a portion of it, where the TKE is substantial, and the Nocturnal Boundary Layer (NBL), mainly a stable stratified layer, above which there is a relatively quiet residual layer (RL) that occupies the remaining space of what was just a few hours before the ML [2,[5][6][7]. ...
... In other words, during the day, solar heats the land surface, activating positive heat fluxes and creating atmospheric instability with a negative vertical temperature gradient, the ML expands within the ABL; meanwhile, above the ML remains a thermal inversion layer (IL) characterized by a positive vertical temperature gradient, which inhibits the mixing of air parcels. In contrast, at night, as the radiative fluxes cool the land surface, it forms a surface inversion layer (SIL) with a severe stable temperature gradient at the base of the atmosphere, above which develops the NBL, where the LLJs produce turbulence [1,[4][5][6] ( Fig. 1). ...
The atmospheric processes that affect the Nocturnal Boundary Layer (NBL) raise unresolved questions, more critical in the case of urban, tropical, and mountainous areas. This research examines the structure of the NBL in the Aburrá Valley - Colombia, a tropical and urbanized region characterized by complex topography. Here six methods were used to estimate the thickness of the NBL, considering the minimum backscattering gradient method (based on ceilometer data) as a reference. Although all the methods contribute to the understanding of the NBL, it was found that the Critical Richardson Number equal to 0,5 fits the best to the reference method, at least for the year 2017, indicating that the tops of the NBL were below the peaks of the surrounding mountains. These results provide technical arguments to consider in managing urban air quality in Valle de Aburrá and other urban, tropical, and mountain areas.
... This selected range aligns with the inertial sublayers (ISLs) where MOST is applicable. It is noteworthy that the common practice of estimating aerodynamic roughness parameters through curve fitting would be prone to error [59,60]. As such, only 0 is derived in this paper through fitting to minimize the potential inaccuracy [59]. ...
... It is noteworthy that the common practice of estimating aerodynamic roughness parameters through curve fitting would be prone to error [59,60]. As such, only 0 is derived in this paper through fitting to minimize the potential inaccuracy [59]. Despite the inherent uncertainties, the wind-speed profiles calculated by LES and theory Eq. (9) agree well with each other in which the average relative error in the surface layer ( ≤ ≤ 0.2 ) is less than 2% across all the stabilities (not shown here for brevity). ...
... The planetary boundary layer (PBL) is the atmosphere's lowest part, where Earth's surface directly influences meteorological variables, impacting the climate system (Garratt, 1994;Kaimal and Finnigan, 1994). The PBL height (PBLH) is a meteorological factor that strongly influences surface-atmosphere exchanges of heat, moisture, and energy (Stull, 1988;Caughey, 1984;Holtslag and Nieuwstadt, 1986;Mahrt, 1999;Helbig et al., 2021;Guo et al., 2024;Beamesderfer et al., 2022). ...
The planetary boundary layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, which can estimate PBLH by integrating the morning temperature profiles and surface meteorological observations. The DNN model is developed by leveraging a rich dataset of PBLH derived from long-standing radiosonde records augmented with high-resolution micro-pulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden-layer structures, which collectively yield a robust 27-year PBLH dataset over the southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote sensing method-ologies, including Doppler lidar, ceilometer, Raman lidar, and micro-pulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (Green Ocean Amazon; tropical rainforest) and CACTI (Cloud, Aerosol, and Complex Terrain Interactions; middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary layer processes with implications for improving the representation of PBL in weather forecasting and climate modeling.
... The objective of this study is to explore and quantify the variability of TKE and 100 the TKE budget terms with elevation and topography in a shallow high mountain val- Using the Ogive function for 1 hour periods between 1 pm and 6 pm when the mesoscale 147 wind was the most prominent, the co-spectra of u ′ w ′ and v ′ w ′ converged to a 30-min av- The raw data from the sonic anemometer was first despiked using the routine of 154 Vickers and Mahrt (1997). After the data was detrended and block averaged to the av-155 eraging period, the turbulence data were rotated into a streamline coordinate system af-156 ter applying a double rotation scheme (Kaimal & Finnigan, 1994). Finally, the turbu-157 lence characteristics were quality checked using EddyPro to satisfy the stationary test (Lilly, 1966(Lilly, , 1967. ...
This paper is in peer review process
... Secondly, the spectral energy contained in wind turbulence is not equally distributed but shows dominating low-frequency parts. This effect is accounted for by appropriate turbulence models as proposed by von Karman [129] or Kaimal [58] as depicted in Fig 1.2. Flexible multibody model As part of the research project DynAWind 2 , a detailed multibody model of the wind turbine prototype W2E-100/2.0 ...
The present dissertation introduces a thorough and consistent framework for model-based estimation of elastic deformations in wind turbine support structures which solely relies on inertial sensor provided by so-called Inertial Measurement Units (IMU). An IMU is essentially a combination of accelerometers and gyroscopes that convinces through its vibrational robustness and comparably low cost. The analyses presented are in fact driven by but not restricted to wind turbine systems, since fundamental aspects similarly apply to general elastic mechanical structures. In contrast to traditional strain-based fatigue estimation schemes, the IMU-based sensor concept requires thorough and carefulf signal processing to extract information on the structural deformation fields. As a central idea of the developed framework, the wind turbine support structure is divided into individual mechanical substructures for the tower and the rotor blades. Recovery of deformation fields is then performed for each subsystem independently by means of a classical state observer scheme which requires a suitable mathematical model of the substructure under consideration. A model representation is regarded suitable in this context if it is able to represent the structural dynamics of the relevant wind turbine components and provide consistent stress and strain recovery. Therefore, the promising Nodal-based Floating Frame of Reference (NFFR) formulation is pursued and analyzed in detail within this thesis, as it allows to derive the corresponding Equations Of Motion (EOM) for each substructure based on standard data provided by every commercial finite element software environment.
The preformance of the proposed state estimation framework is demonstrated by application to different simulation models with gradually increasing complecity as well as by practical test scenarios using a small-scale wind turbine.
... In this regime, the turbulent heat fluxes increase with increasing temperature gradient because more heat is available to be transported. The inertial range in the turbulence spectra is well defined and exhibits a Kolmogorov slope of − 5/3 (Kaimal and Finnigan, 1994). The other is the strongly stable regime, where turbulent sensible heat fluxes instead decrease with increasing temperature gradient because the effect of strong stability leads to a turbulence decay. ...
In this study, the Noah land surface model used in conjunction with the Mellor–Yamada–Janjić surface layer scheme (hereafter, Noah-MYJ) and the Noah multiphysics scheme (Noah-MP) from the Weather Research and Forecasting (WRF) 4.5.1 mesoscale model are evaluated with regard to their performance in reproducing positive temperature gradients over forested areas in the Arctic winter. First, simplified versions of the WRF schemes, recoded in Python, are compared with conceptual models of the surface layer in order to gain insight into the dependence of the temperature gradient on the wind speed at the top of the surface layer. It is shown that the WRF schemes place strong limits on the turbulent collapse, leading to lower surface temperature gradient at low wind speeds than in the conceptual models. We implemented modifications to the WRF schemes to correct this effect. The original and modified versions of Noah-MYJ and Noah-MP are then evaluated compared to long-term measurements at the Ameriflux Poker Flat Research Range, a forest site in interior Alaska. Noah-MP is found to perform better than Noah-MYJ because the former is a two-layer model which explicitly takes into account the effect of the forest canopy. Indeed, a non-negligible temperature gradient is maintained below the canopy at high wind speeds, leading to overall larger gradients than in the absence of vegetation. Furthermore, the modified versions are found to perform better than the original versions of each scheme because they better reproduce strong temperature gradients at low wind speeds.
... Analysis from FLUXNET sites shows that average turbulent energy fluxes underestimate available energy by 20% at most sites (Wilson et al., 2002). Instrumental errors (Richardson et al., 2012;Mauder and Zeeman, 2018), data processing errors (Kaimal and Finnigan, 1994;Leuning et al., 2012), additional sources of energy (Mauder et al., 2013;Garcia-Santos et al., 2019), and sub-mesoscale transport processes (Mauder et al., , 2020 are supposedly the underlying reasons for the surface energy imbalance. In the past 25 years, although a great deal of research has attempted to address the energy imbalance in the ASL, the results have not been satisfactory. ...
Surface energy balance has always been a goal of those studying the Earth’s climate system. However, many studies have demonstrated that turbulent heat fluxes are usually underestimated by eddy covariance (EC) measurements, such that the energy balance is not closed. This study proposes a new perspective on calculating sensible heat flux based on the environmental temperature using EC. Using this approach, additional sensible heat fluxes were detected as outcomes of the vertical transportation of thermal structures in the atmospheric surface layer (ASL). For data obtained over a 40-day period over a grassland in Southern China, additional sensible heat flux observations exceeding 50 W m⁻² were measured for 8 of the 40 days; smaller but still significant contributions were captured for another 11 days. In the proposed model, the difference between the mean and environmental temperature ( ∆ T ) and the local mean vertical velocity ( w ¯ ) serve as determinants for the additional flux, where the former can be deemed as the activity level of the thermal structures. A modeled underestimation of α[ w ¯ ] H t of the total vertical sensible heat flux was revealed using our method, where α equals 3.55 for this study, H t is the traditional EC results, and [ w ¯ ] is the non-dimensional w ¯ . Moreover, the additional flux usually showed large values in the daytime that were not detectable using the traditional EC method; this may help explain the energy imbalance problem in the ASL.
... The stability parameter (ζ ) in Eq. (10) can be expressed in terms of the Obukhov length (L) (Kaimal and Finnigan 1994) as follows: ...
Wildland fire–atmosphere interaction generates complex turbulence patterns, organized across multiple scales, which inform fire-spread behaviour, firebrand transport, and smoke dispersion. Here, we utilize wavelet-based techniques to explore the characteristic temporal scales associated with coherent patterns in the measured temperature and the turbulent fluxes during a prescribed wind-driven (heading) surface fire beneath a forest canopy. We use temperature and velocity measurements from tower-mounted sonic anemometers at multiple heights. Patterns in the wavelet-based energy density of the measured temperature plotted on a time–frequency plane indicate the presence of fire-modulated ramp–cliff structures in the low-to-mid-frequency band (0.01–0.33 Hz), with mean ramp durations approximately 20% shorter and ramp slopes that are an order of magnitude higher compared to no-fire conditions. We then investigate heat- and momentum-flux events near the canopy top through a cross-wavelet coherence analysis. Briefly before the fire-front arrives at the tower base, momentum-flux events are relatively suppressed and turbulent fluxes are chiefly thermally-driven near the canopy top, owing to the tilting of the flame in the direction of the wind. Fire-induced heat-flux events comprising warm updrafts and cool downdrafts are coherent down to periods of a second, whereas ambient heat-flux events operate mainly at higher periods (above 17 s). Later, when the strongest temperature fluctuations are recorded near the surface, fire-induced heat-flux events occur intermittently at shorter scales and cool sweeps start being seen for periods ranging from 8 to 35 s near the canopy top, suggesting a diminishing influence of the flame and increasing background atmospheric variability thereat. The improved understanding of the characteristic time scales associated with fire-induced turbulence features, as the fire-front evolves, will help develop more reliable fire behaviour and scalar transport models.
... Prediction of upstream water surface elevation, or backwater rise, is necessary to evaluate the hydraulic impact of natural and engineered logjams (Hankin et al., 2020;Ruiz Villanueva et al., 2014;Wohl et al., 2010). Follett et al. (2020) was the first to show that the loss of momentum within a logjam can be explained by a spatial average canopy drag model (Kaimal & Finnigan, 1994), and that the backwater rise can be predicted from a combination of momentum and energy constraints. This enabled a physically-based approach for including jams in hydraulic models (Follett & Hankin, 2022). ...
Plain Language Summary
Logjams can increase upstream water surface elevation, creating an upstream pool with slower, deeper water. We demonstrated that the increase in water depth upstream of a logjam is related to the number, size, and packing density of the logs and the jam length. In this Reply to a Comment by Poppema and Wüthrich (2024, https://doi.org/10.1029/2023gl106348), we clarify that our prediction of upstream water depth does not depend on river steepness and sediment size. We go on to show that a progressive increase in upstream depth is possible under some low flow conditions, if logjams are spaced closely enough so that each logjam is impacted by its downstream neighbor. This arrangement could be used to design nature‐based solutions for water retention during drought. In response to Poppema and Wüthrich (2024, https://doi.org/10.1029/2023gl106348), we clarify the observed agreement between our model and a similar model by Schalko et al. (2018, https://doi.org/10.1061/(asce)hy.1943‐7900.0001501) and suggest that the effect of log orientation can be included in our model by varying the drag coefficient in addition to the frontal area perpendicular to the flow.
... where ϕ = 28°is the zenith angle. To align with the methodology outlined by Kaimal and Finnigan [15], the coordinate axes were rotated. This adjustment ensured that the u y aligned with the 10 min mean wind direction, and the mean velocity of u x became 0, thereby yielding the along-wind and cross-wind velocities, referred to as u and v, respectively. ...
This study examines how motion influences turbulent velocity fluctuations utilizing measurements obtained from a wind lidar profiler. Onshore tests were performed using a WindCube v2.1 lidar, which was mobile and mounted on a hexapod to simulate buoy motion. Additionally, a fixed WindCube v2.1 lidar was used as a reference during these tests. To assess the motion-induced effects on velocity fluctuations measured by floating lidar systems, the root-mean-square error (RMSE) of velocity fluctuations obtained from the fixed and mobile lidars was calculated. A comprehensive wind dataset spanning 22.5 h was analyzed, with a focus on regular motions involving single-axis rotations and combinations of rotations around multiple axes. The investigation of single-axis rotations revealed that the primary influencing factor on the results was the alignment between the tilt direction of the mobile lidar and the wind direction. The highest RMSE values occurred when the tilt of the mobile lidar leans in the wind direction, resulting in pitch motion, whereas the lowest RMSE values were observed when the tilt of the mobile lidar leans perpendicular to the wind direction, resulting in roll motion. Moreover, the addition of motion around extra axes of rotation was found to increase RMSE.
... software (LI-COR Biosciences, Lincoln, NE, USA) was used to process the raw 10 Hz flux data. Data processing flow was as follows: data quality control was carried out according to the method recommended by Vickers et al. [19], and a double rotation [20] (forest and cropland sites) and planar fit coordinate rotation [21] (non-timber forest site) were used to eliminate the influence of instrument tilt or terrain irregularity on airflow. The effects of air density fluctuations due to heat and water vapor transfer were corrected using Webb-Pearman-Leuning (WPL) correction [22]. ...
Small watersheds are fundamental units for natural processes and social management in Southwestern China. Accurately assessing carbon sinks in small watersheds is crucial for formulating carbon sink management policies. However, there has been a lack of assessment of the dynamics of carbon fluxes in the major ecosystems of small watersheds. Here, we selected the Reshuihe River watershed, which is a typical small watershed in Southwestern China, to measure carbon fluxes using eddy covariance systems for two years (October 2021 to September 2023) from three major ecosystems, namely forest, cropland, and non-timber forest. We compared variations and controlling factors of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Re) among different ecosystems, and estimated annual watershed carbon flux based on the land cover areas of the three ecosystems. This study found that three ecosystems were net annual carbon sinks during the study period. Forest was the strongest (−592.8 and −488.1 gC m−2 a−1), followed by non-timber forest (−371.0 gC m−2 a−1), and cropland was the smallest (−92.5 and −71.6 gC m−2 a−1), after taking fallow period into account. Weeds were a significant source of carbon flux in non-timber forest ecosystems. It was also found that variations in daily NEE were controlled by photosynthetically active radiation and soil volumetric water content, with weak effects related to temperature also being observed. However, when the temperature exceeded 21 °C, GPP and Re were significantly reduced in cropland. Finally, it was discovered that the total carbon sink of the three ecosystems in the watershed for one year was −52.15 Gg C. Overall, we found that small watersheds dominated by forest ecosystems in Southwestern China have a strong carbon sink capacity.
... The method of this filtering process includes linear detrending, block averaging, autoregressive filtering, and other detrending schemes (such as quadratic detrending), and the benefits and defects of these methods have been discussed in detail (Culf, 2000;Moncrieff et al., 2005;Rannik & Vesala, 1999). However, these methods are not well-defined in either mathematics or physics (Kaimal & Finnigan, 1994). On the one hand, the arbitrary usage of detrending may enhance the effect of low-frequency loss (Aubinet et al., 2012), which merely makes the systematic error shift to inexplicable fluctuations, rather than disappear. ...
Turbulent fluxes play a critical role in atmospheric science and are usually calculated from the eddy covariance system. However, the presence of motions of larger scale and the bias from observational instruments often affects the procurement of turbulent fluxes. Based on the Hilbert–Huang transform, the properties of transport can be defined and used to distinguish non‐turbulent motions from the observational data, and a new way of decomposing the variables is thereby put forward to reconstruct the turbulent flux series. To quantify the influence of non‐turbulent motions on the calculation of turbulent flux, the non‐turbulent motions extracted from the five‐level turbulence data of the Tianjin 255‐m meteorological tower from July 1 to August 31, 2017 are examined. The results reveal that the presence of non‐turbulent motion can lead to a universal overestimation of turbulent flux, and the degree of overestimation increases with the complexity and the intensity of non‐turbulent motion. According to the consequences above, an empirical relationship, together with the corresponding coefficients, is given to provide a guidance on the correction of turbulent fluxes in practical use, such as the simulation of atmospheric turbulence and the parameterization in meteorological and climate models.
... The friction velocity is often used as a scaling velocity in the Atmospheric Surface Layer (ASL) [69]. In wind energy, the standard deviation of the along-wind component, symbolised by , is more widely adopted. ...
This paper examines metocean data from NORA3, a state-of-the-art wind and wave hindcast dataset for Northern Europe. Two offshore Norwegian areas, Utsira Nord (UN) and Sørlige Nordsjø II (SN2), are investigated. Both areas offer significant potential for the offshore wind sector. UN is situated in deep-sea water, suitable for floating offshore wind turbines. In contrast, SN2 lies in intermediate waters and ranks among the North Sea's most promising regions allocated for offshore wind. Data from NORA3, originally on a 3-km resolution grid, are resampled into unstructured grids spanning from 1982 to 2022. This refined dataset offers a climatology time scale with superior spatial and temporal resolution compared to most other hindcast and reanalysis databases. The study examines mean wind speed and direction across seven levels, ranging from 10 m to 750 m above the surface. Analyses of extreme wind and wave conditions have been conducted. Results reveal that UN experiences higher extreme wave heights than SN2 while the extreme wind speeds may be substantially larger at SN2 than UN. Moreover, this study establishes joint distribution models that encompass several parameters, including mean wind speed, significant wave height, wave spectral peak period, and direction difference between wind and waves. Thus, this metocean data is valuable for designing and analyzing floating wind farms over their lifecycles.
... For #7, we apply necessary corrections to the inertial subrange observed by UATs, which is caused by the well-known acoustic path-averaging bias. 33 For future field observations, this problem may be mitigated by using recently developed systems integrating UAT and hot film (or wire) sensors. 34 After applying ARIIS to the CASPER data, additional processing steps were taken to address spurious samples. ...
The −5/3 power law over the inertial subrange of the turbulence kinetic energy spectrum is one of the most well-known concepts in fluid physics. Obukhov and Corrsin extended the original hypothesis to a passive tracer, leading to the concept of an inertial-convective subrange. These postulates have been empirically validated in the atmospheric turbulence over land but have not been comprehensively studied in the marine air flow. During a recent oceanic campaign, the platform FLIP was deployed with an array of sensors to measure the perturbation wind velocity, temperature, and water vapor. Using these data, a previous study found that Kolmogorov's hypothesized −5/3 was not universally valid over the ocean. Here, we continue that work to analyze the spectrum of temperature and water vapor to empirically evaluate the theoretical extension by Obukhov-Corrsin. For temperature, the observed spectra were too noisy for thorough analysis; our conjecture for the source of noise and its implications for near-surface observations of atmospheric turbulence are discussed. For water vapor, we found strong agreement with the previous analysis of the kinetic energy spectrum. These findings corroborate (1) the theoretical notion of the scalar energy dissipation subrange driven by the inertial motions in the marine boundary layer and (2) evidence for non-Kolmogorov turbulence in the high Reynolds flow immediately above ocean waves. Our analysis shows a strong relationship with distance from the wavy surface; using linear extrapolation, we find that divergence from −5/3 persists in the lowest 25 m of the atmosphere.
... Earth's surface directly influences meteorological variables, impacting the climate 45 system (Garratt, 1994; Kaimal and Finnigan, 1994). The PBL height (PBLH) is a 46 meteorological factor that strongly influences surface-atmosphere exchanges of heat, 47 moisture, and energy (Stull, 1988;Caughey, 1984;Holtslag and Nieuwstadt, 1986; 48 Mahrt, 1999 weather forecasts and climate models (Menut et al., 1999;Park et al., 2001;54 Emanuel, 1994; Guo et al., 2017;Lilly, 1968;Matsui et al., 2004). ...
The planetary boundary layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, designed to estimate PBLH by integrating morning temperature profiles with surface meteorological observations. The DNN model is developed by leveraging a rich dataset of PBLH derived from long-standing radiosonde records and augmented with high-resolution micro-pulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of ten members, each featuring distinct hidden layer structures, which collectively yield a robust 27-year PBLH dataset over the Southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and Micro-pulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (Tropical Rainforest) and CACTI (Middle Latitude Mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary layer dynamics with implications for enhancing the representation of PBL in weather forecasting and climate modeling.
... The daytime planetary boundary layer (PBL) turbulence is characterized with a broad spectrum, ranging from the energy containing convective circulations that span the entire depth of the boundary layer, to the dissipative eddies with sizes on the order of 1 mm (Kaimal and Finnigan 1994). As a result, turbulence is almost never fully resolved in numerical simulations of the PBL. ...
When the horizontal grid spacing of a numerical weather prediction model approaches kilometer scale, the so-called gray zone range, turbulent fluxes in the convective boundary layer (CBL) are partially resolved and partially subgrid scale (SGS). Knowledge of the partition between resolved and SGS turbulent fluxes is key to building scale-adaptive planetary boundary layer (PBL) schemes that are capable of regulating the SGS fluxes with varying grid spacing. However, flux partition depends not only on horizontal grid spacing, but also on local height, bulk stability of the boundary layer, and the particular turbulent flux. Such multivariate functions are difficult to construct analytically, so their implementations in scale-adaptive PBL schemes always involve certain levels of approximation that can lead to inaccuracies. This study introduces a physically based perspective for the flux partition functions that greatly simplifies their implementation with high accuracy. By introducing an appropriate scaling length λ that accounts for both height and bulk stability dependencies, the dimensionality of the partition functions is reduced to a single dimensionless group. Based on the analysis of a comprehensive large-eddy simulation dataset of the CBL, it is further shown that λ ’s height and bulk stability dependencies can be separately represented by a similarity length scale and a stability coefficient. The resulting univariate partition functions are incorporated into a traditional first-order PBL scheme as a proof of concept. Our results show that the augmented scheme well-reproduces the SGS fluxes at gray zone resolutions.
Significance Statement
Flux partition functions are a key component in most scale-adaptive planetary boundary layer (PBL) schemes developed for kilometer- and subkilometer-resolution numerical weather prediction models. They regulate the parameterized turbulent fluxes as a function of horizontal grid spacing, while they also depend on height and atmospheric stability. Such multivariate dependencies forbid simple analytical expressions, and as a result, partition functions implemented in scale-adaptive PBL schemes are generally simplified at the cost of accuracy in previous works. This study investigates the possibility of constructing partition functions that are both accurate and easy to parameterize. Utilizing a physically based length scale, univariate partition functions are built, evaluated, and put into a conventional PBL scheme to improve the gray zone turbulence parameterization.
... For tilt correction, we applied a planar-fit coordinate rotation (Wilczak et al., 2001) with four wind sectors for the above-canopy measurements to account for the complex terrain and tall, heterogeneous vegetation. A conventional double rotation (Kaimal and Finnigan, 1994) was used for the below-canopy measurements with lower wind speed conditions and more homogeneous terrain (see Rebmann et al., 2012). Turbulent half-hourly H 2 O fluxes were calculated by Reynolds averaging from the covariance of vertical wind velocity with H 2 O molar density, and were corrected for air density fluctuations (Webb et al., 1980). ...
Evapotranspiration (ET) from the land surface to the atmosphere is a major component of Earth’s water cycle, and comprises both transpiration (T) of xylem water from plants and evaporation (E) of water from soils and vegetation surfaces. These two component fluxes respond differently to changes in temperature, water availability and atmospheric CO2 concentrations. Concurrent eddy covariance (EC) measurements above and below forest canopies provide a promising approach to partition ET into E and T. However, below-canopy EC measurements are rare, and questions remain regarding their spatial variability, canopy coupling, and temporal dynamics. To address these challenges, we measured and partitioned ET over more than three years, using concurrent above- and below-canopy EC towers in a montane forest at Sagehen Creek in California’s Sierra Nevada mountains. This is the establishing study for the AmeriFlux site US-SHC. The main environmental control for ET was available energy; other important controls were canopy & soil temperature, soil moisture, vapor pressure deficit, and wind speed. Below-canopy measurements at two locations within the above-canopy footprint were similar to one another, suggesting low spatial heterogeneity in understory ET near the creek at our Sagehen site. We observed a total forest ET of 606 ± 50 mm yr-1 with 275 ± 17 mm yr-1 measured in the understory (all mean ± SD) during the water years 2018–2020. Interannual variability in ET and T was small despite large variability in precipitation totals; thus the P–ET water balance was mainly driven by variations in water supply. Partitioning the components of total forest ET at Sagehen with concurrent EC measurements showed that on average, 67–74% of ET originated from T (47% from trees and 20–27% from understory vegetation), while 26–33% were from E (mostly from the understory). Our results demonstrate the potential of concurrent above- and below-canopy EC measurements for ET partitioning.
... In the absence of direct measurements of the rate at which asymmetric dunes revert to a symmetric morphology (Parteli et al., 2014a), this provides at least a strong constraint on the value of q shif t . Interestingly, this range of q shif t is also consistent with the 395 range of the intensity of isotropic turbulence in atmospheric boundary layers (Kaimal and Finnigan, 1994). ...
We perform simulations of barchan swarms using the Two-Flank Agent-Based model investigating the effects of changing the angular separation between primary and secondary modes of wind, the density at which new dunes are injected, and the parameter qshift which controls the rate at which sediment is reorganised to restore symmetry in an asymmetric dune. Unlike previous agent-based models, we are able to produce longitudinally homogeneous size distributions and, for sparse swarms, steady longitudinal number density. We are able to constrain qshift by comparing the range of values for which longitudinally stability is observed with the range of values for which the width of asymmetry distributions is consistent with real-world swarms. Furthermore, we demonstrate dune size, asymmetry, dune density, spatial alignment, and collision dynamics are all strongly influenced by the angular separation of bimodal winds.
... We used EddyPro-7.0.9 software (EddyPro, Li-Cor Inc., Lincoln, NE, USA) to process the high-frequency data into 30-min fluxes. The quality checks and corrections include despiking (Vickers & Mahrt, 1997), double-coordinate rotation (Kaimal & Finnigan, 1994), Webb-Pearman-Leuning correction (Detto & Katul, 2007;Webb et al., 1980), and time lag correction following (Morin et al., 2014). After obtaining the half-hourly fluxes, the data were further processed, filtered, gap-filled, and partitioned in R (see Sections 2.3.2 and 2.3.3) ...
Compost amendment to rangelands is a proposed nature‐based climate solution to increase plant productivity and soil carbon sequestration. However, it has not been evaluated using quasicontinuous ecosystem‐scale measurements. Here, we present the first study to utilize eddy covariance and footprint partitioning to monitor carbon exchange in a grassland with and without compost amendment, monitoring for 1 year before and 1 year after treatment. Compost amendment to an annual California grassland was found to enhance net ecosystem removal of carbon. Our study confirmed that compost‐amended grasslands, similar to nonamended grasslands, are net carbon sources to the atmosphere; however, the amendment appears to be slowing down the rate at which these ecosystems lose carbon by 0.71 Mg C ha⁻¹ per growing season. Digital repeated imagery of the canopy revealed that compost‐amended grasslands experienced an earlier green‐up, resulting in an overall longer growing season by >60 days. Notably, we did not detect significantly higher amounts of soil carbon in compost‐amended soils. High variability in soil carbon demands greater sampling replication in future studies. A longer growing season and higher productivity are hypothesized to be a result of greater availability of macronutrients and micronutrients in the top layer of soil (specifically nitrogen, phosphorus, and zinc).
... LI-COR Biosciences) to obtain half-hourly averaged uxes. The double rotation method was used to align the sonic anemometer with the local wind streamlines (Kaimal and Finnigan 1994). Block averaging determined turbulent uctuations over each half-hour period (Gash and Culf 1996). ...
Background
Fungal morphology such as the hydrophobicity of ectomycorrhizae may correspond to functional attributes including enzymatic capabilities, carbon (C) demand from host plants, temporal patterns of fruiting, C sequestration, and nitrogen (N) sequestration. Here, we assessed how ectomycorrhizal hydrophobicity influenced the timing of C dynamics and fungal processing of C and N, as integrated by fruiting patterns, δ¹³C, δ¹⁵N, and loge C/N of ectomycorrhizal sporocarps.
Methods
We linked δ¹³C, δ¹⁵N, loge C/N, and temporal fruiting patterns of ectomycorrhizal sporocarps and soils across seven N fertilization treatments in two Swedish Pinus sylvestris L. forests to ectomycorrhizal hydrophobicity and daily gross primary production.
Results
Gross primary production of seven and 6–9 days prior to collection correlated positively with sporocarp δ¹³C and loge C/N, respectively, reflecting transit times of peak delivery of plant-derived carbohydrates to sporocarp formation. Hydrophobic taxa fruited 10 days later than hydrophilic taxa, suggesting greater C demands for hydrophobic taxa. Taxa with hydrophobic ectomycorrhizae had lower δ¹³C, higher δ¹⁵N, and higher loge C/N (less protein) than taxa with hydrophilic ectomycorrhizae.
Conclusions
Long C accumulation times and high sequestration (hydrophobic taxa) versus low sequestration (hydrophilic taxa) of ¹³C-enriched carbohydrates and ¹⁵N-depleted chitin in mycelia could account for the late fruiting, ¹³C depletion, and ¹⁵N enrichment of hydrophobic sporocarps. We concluded that sporocarp production and hydrophobicity integrated functional information about the extent of belowground hyphal development and the C accumulation times of C transfers from host Pinus.
... 34 Double rotation (vertical and cross wind) was performed to nullify the mean cross-stream and vertical wind component. 35 Corrections for the both the low and high frequency losses were made using analytical methods outlined in Fratini, Ibrom 36 and Moncrieff, Clement, 37 respectively. Due to the majority of ux measurements being relatively low in magnitude, the time lag between the sonic anemometer and the QCL was calculated outside of the Eddypro soware, using the covariance maximization method as described by Murphy, Richards. ...
Carbon monoxide (CO) is classed as a secondary greenhouse gas (GHG) as it can extend the lifetime of GHGs such as methane and ozone by reacting with hydroxyl (OH) radicals and thus controlling the oxidizing capacity of the atmosphere. CO fluxes were measured from a fertilized and grazed temperate grassland in south-east Ireland using a high frequency quantum cascade laser (QCL) and the eddy covariance method. Measurements were carried out in 2019 (12 months) and 2020 (10 months). In both datasets, a diurnal pattern was observed where CO fluxes peaked between 8 am and 6 pm, and between 8 pm and 2 am during the colder months of the year. Quality controlled CO flux data was gap-filled using a general additive model (GAM) that incorporated photosynthetic photon flux density (PPFD), air temperature, water-filled pore space (WFPS) and month of the year. Modelled CO emissions showed less divergence with measured CO fluxes in 2020 compared to 2019, suggesting that the environmental variables in the GAM were the predominant driver of CO emissions in 2020 but not in 2019. Cumulative CO emissions in 2019 and 2020 were 39.7 ± 147.1 mgCO–C per m² per month and 31.5 ± 75.2 mgCO–C per m² per month, respectively. While soils are typically considered a sink of CO, our results show that managed pastures can act as a source of CO and thus warrant further investigation into the implications CO may have on GHG dynamics from agricultural landscapes.
... The measurements of meteorological parameters temperature, relative humidity, wind speed, and wind direction are obtained from different levels at 2 m, 8 m, 16 m, 32 m, and 50 m. The sensible heat flux is derived using the eddy correlation method (Arya, 2001;Kaimal & Finnigan, 1994) from the ultra-sonic anemometer observations gathered at a frequency of 10 Hz. Landsat satellite images (https://www.usgs. ...
Horizontal convective rolls (HCR) are sub-mesoscale motions that influence the transport of heat, momentum, and pollutants within the boundary layer. In this work, a high-resolution (0.666 km) Weather Research and Forecasting (WRF) model is employed to simulate the structure of the HCRs over Kalpakkam along the southeast coast of India. The sensitivity of HCR simulation to model land surface physics is studied with two land surface models (LSM), (i) Noah and (ii) Noah multi-parameterization (NMP), for three selected days (15 April 2013, 07 May 2015, 28 March 2018) during summer synoptic conditions. On all three selected days, the boundary layer rolls formed over a period of about 2–3 h in the morning under moderate winds (4–5.0 m/s), moderate vertical wind shear (2.4–3.5 m/s) in the lower atmosphere, and slightly unstable conditions [gradient Richardson number (RiG) −4.5 to −5.0] in both simulations and observations, indicating that thermal instability is the chief mechanism in their development. Simulated mean surface meteorological parameters by NMP were found to be in better agreement with observations than Noah. Results suggest that the LSMs mainly affected the simulated turbulent roll structure in terms of updraft cores and their horizontal and vertical extent by variation in simulated surface energy fluxes, boundary layer structure, wind shear, and stability. The structure of simulated HCRs is better represented by NMP due to the improvements in the flux distribution and surface properties. Simulations using the FLEXPART dispersion model for a hypothetical case of tracer release indicated an uneven spatial concentration pattern due to upward and downward motions in the region of HCRs. The stronger winds and stronger flow convergence in Noah and higher heat flux and more unstable conditions in NMP led to differences in the simulated tracer concentrations in the two cases.
... During dust storms, the turbulence intensity can increase due to the presence of strong winds and turbulent mixing. While turbulence intensity can vary depending on the specific conditions, studies have reported turbulence intensities ranging roughly from 10 % to 40 % during dust storms close to the Earth's surface (Kaimal & Finnigan, 1994). ...
Martian dust storms in the planetary boundary layer share many qualitative similarities to terrestrial sandstorms. Both of these turbulence-driven, particle-laden boundary layer flows are known to generate electric fields due to the transport of differentially charged particles; this charge separation can be strong enough to lead to dielectric breakdown in the form of sparks or lightning. Using wall-modelled large-eddy simulations supplemented with conservation of equations for the charged particle transport, representative simulations of neutrally stable Martian and terrestrial particle-laden boundary layer flows are compared. The simulations, albeit canonical in nature, provide evidence to support previous observations of the less frequent occurrence of lightning on Mars but a higher occurrence of localised electric discharge events due to the much lower breakdown potential. The rarefied Martian atmosphere impedes charged particle transport, resulting in a weaker electric field than the equivalent terrestrial sandstorm. The lower drag force in the rarefied Martian atmosphere means that the electrostatic force plays a more significant role in the particle transport, which results in a self-regulation of the electric field. The strongest Martian dust storms show evidence of significant breakdown events and these discharge events only occur very close to the ground despite the very large boundary layer on Mars.
... Radiosondes were used to provide the initial conditions for the numerical experiments (see Table 1 for exact values). Estimations of boundary layer height were obtained from the radiosondes profiles using the parcel method (Kaimal and Finnigan, 1994). Mixed-layer values for potential temperature and specific humidity were obtained averaging the 140 profiles below the boundary layer height minus a constant entrainment zone of 50 m and excluding the surface layer assumed to be the lower 10 % of the boundary layer. ...
Quantifying water vapor and carbon dioxide exchange dynamics between land and atmosphere through observations and modelling is necessary to reproduce and project near surface climate in coupled land-atmosphere models. The exchange of water and carbon dioxide (CO2) occurs at the leaf surfaces (leaf level) and in a net manner through the exchanges at all the leaf surfaces composing the vegetation canopy and at the soil surface (canopy level). These exchanges depend on the meteorological forcings imposed by the overlying atmosphere (atmospheric boundary layer level). In this manuscript, we investigate the effect of four canopy environmental variables (photosynthetic active radiation (PAR), water vapor pressure deficit (VPD), air temperature (T) and atmospheric CO2 concentration (Ca)) on the local individual leaf exchange and canopy exchange of water and CO2 at hourly time scales and the effect of atmospheric boundary layer (ABL) processes on the local exchange. To that end, we simultaneously investigated the exchanges of water and CO2 at leaf level and canopy level for an alfalfa field in Northern Spain during a day in the summer of 2021. We used comprehensive observations ranging from stomatal conductance to ABL measurements collected during the Land Surface Interactions with the Atmosphere in the Iberian Semi-Arid Environment (LIAISE) experiment. To support the observational analysis, we used an integrative mixed-layer atmospheric model (CLASS) that have representations at all considered levels. To relate how temporal changes of the four environmental variables modify the fluxes of water and CO2, we studied tendency equations of the leaf gas exchange. These mathematical expressions quantify the temporal evolution of the leaf gas exchange as a function of the temporal evolution of PAR, VPD, T and Ca. To investigate the effects of ABL processes on the local exchange, we developed three modelling experiments that impose surface radiative perturbations by a cloud passage (which perturbed PAR, T and VPD), entrainment of dry air from the free troposphere (which perturbed VPD) and advection of cold air (which perturbed T and VPD). Model results and observations matched the leaf gas exchange (with r2 between 0.23 and 0.67) and canopy gas exchange (with r2 between 0.90 and 0.95). The tendency equations of the modelled leaf gas exchange during the studied day revealed that the temporal dynamics of PAR were the main contributor to the temporal dynamics of the leaf gas exchange with atmospheric CO2 temporal dynamics being the least important contributor. From the three modelling experiments with ABL perturbations, the surface radiative changes induced by a cloud perturbed the CO2 exchange the most, whereas all of them perturbed the water exchange to a similar extent. Second order effects on the dynamics of the leaf gas exchange were also identified using the tendency equations. For instance, the decrease of net CO2 assimilation rate during the cloud due to a decrease in surface radiation was further enhanced due to the decrease in air temperature also associated with the cloud. With this research we showcase that the proposed tendency equations can disentangle the effect of environmental variables on the leaf exchange of water and CO2 with the atmosphere as represented in land-surface parameterization schemes and become a useful tool to analyze these schemes in weather and climate models.
... T HE planetary boundary layer (PBL) is the lower atmosphere closest to the surface [1], [2]. It plays a dominant role in the transport of turbulence, which leads to significant changes in meteorological elements [3], [4], [5]. An accurate estimation of PBLH with high accuracy is often challenging, primarily due to the significant variability [6]. ...
The planetary boundary layer height (PBLH) has a significant impact on the energy and material exchange in the atmosphere. The traditional gradient method (GM) determines the PBLH based on the gradient change of the aerosol profile. It is susceptible to the effect of complex atmospheric conditions, which leads to uncertainties in the estimation of PBLH. Here, a random forest (RF) algorithm that considers the vertical distribution of aerosols is proposed to find the PBLH under complex atmospheric conditions. The height of the three minimum local peaks of the range correction signal profile and 7 other variables, such as aerosol layer number (ALN), relative humidity, solar radiation, and other meteorological parameters, from January 2017 to December 2021 is used as RF model input. The radiosonde estimated PBLH (PBLHRS) is used as reference value. The sensitivity analysis indicates that the relative error of RF-estimated PBLH (PBLHRF) is smaller than that of GM-estimated PBLH (PBLHGM), and it decreases with an increase in aerosol optical depth. Moreover, RF achieves good performance under different atmospheric conditions. It can effectively overcome the effects of complex atmospheric conditions in PBLH estimation. Based on the correlation analysis, it is found that the estimation accuracy of the RF algorithm is greatly improved compared with the GM. The correlation coefficient between the PBLHRF and the PBLHRS reaches 0.8, which is much larger than that of the PBLHGM (0.47). Finally, long-term PBLHRF analysis show that there are obvious diurnal and seasonal variations of PBLH. It increases and then decreases from early morning to late evening. It is highest in summer and lowest in winter. Overall, RF can effectively overcome the shortcomings of traditional GM and has high accuracy and robustness for various atmospheric conditions. The findings obtained here have great potential for lidar application in obtaining reliable PBLH estimations.
... Turbulent characteristics and fluxes were measured by a CSAT3 sonic anemometer (Campbell Scientific, USA) located at the north-west-facing slope station, Tripod (TRI), in FMRB. High frequency wind speed measurements were detrended and block averaged over 30 min intervals for flux estimates after applying a double rotation scheme (Kaimal & Finnigan, 1994) to align the coordinates with the mean wind. ...
Improving the calculation of land‐atmosphere fluxes of heat and water vapor in mountain terrain requires better resolution of thermally driven diurnal winds (i.e., valley, slope winds) due to differential heating by terrain and radiative fluxes. In this study, the Weather Research and Forecasting model is used to simulate flow in large‐eddy simulation (LES) mode over the complex terrain of the Fortress Mountain and Marmot Creek research basins, Kananaskis Valley, Canadian Rockies, Alberta in mid‐summer. The model was used to examine the temporal and spatial evolution of local winds and near‐surface boundary layer processes with variability in topography and elevation. Numerically resolving complex terrain wind flow effects require smaller grid cell size. However, the use of terrain‐following coordinates in most numerical weather prediction models results in large numerical errors when flow over steep terrain is simulated. These errors propagate through the domain and can result in numerical instability. To avoid this issue when simulating flow over steep terrain a local smoothing approach was used, where smoothing is applied only where slope exceeds some predetermined threshold. LES results from local smoothing were compared with a mesoscale model and LES with global smoothing. Simulations are evaluated using sounding data and meteorological stations. The differences in flow patterns and reversals in two mountain basins suggest that valley geometry and volume is relevant to the break up of inversion layers, removal of cold‐air pools, and strength of thermally driven winds.
... In most cases, the wind speed increases with height above the ground due to the velocity gradient created due to the atmospheric boundary layer. 22 For general purposes, especially for the placement of wind turbines, an optimal height is typically between 30 to 100 m above ground level. 23 At this height, the wind speed is usually significantly higher than at the ground level, providing more kinetic energy. ...
... Since the magnitude of any turbulent eddies will depend upon the wind strength, we assume that q shift ∝ q sat with a proportionality constant of 0.2 used unless otherwise stated. This value was chosen as it enables all the interactions described below and is also consistent with typical isotropic turbulence intensity in atmospheric boundary layers (Kaimal & Finnigan, 1994). In the absence of detailed lab or field measurements of asymmetry reduction and collisional phase-spaces, we are unable to constrain this parameter at this time (see Supporting Information S1 for a more detailed discussion). ...
Plain Language Summary
Barchans are naturally occurring sand dunes found in regions where the wind direction is near‐constant, and the overall supply of sand is low. Because of these conditions, barchans migrate very quickly resulting in collisions between the dunes. Interactions between dunes also occur as sand streams off upwind dunes and is absorbed into downwind barchans. In this work, we present an agent‐based model which treats the dunes themselves as the elementary objects, rather than the sand and airflow. Such models are capable of simulating large populations of dunes. We model barchans as comprising two flanks which can grow semi‐independently. With this structure, we can replicate complex phenomena, including dune asymmetry due to varying winds, restoration of symmetry under a constant wind, and the spontaneous breakup of dunes due to strong winds in directions close to 90° from the usual. These phenomena were inaccessible to previous agent‐based models of barchans. We are also able to reproduce all of the different types of collision which have been observed in lab experiments and more computationally intensive models. The new model, therefore, represents an improvement on previous agent‐based models while remaining computationally cheap enough to simulate large populations.
... where a is the Kolmogorov constant. The value of a is set to 0.55 (between 0.5 and 0.6) refer to the previous study (Kaimal & Finnigan, 1994). In future studies, based on the valuable data obtained through these two voyages, we will evaluate different values of the Kolmogorov constant under various turbulence conditions. ...
A method to identify the turbulent mixing sources within the marine atmospheric boundary layer (MABL) based on the shipborne coherent Doppler lidar measurements is introduced in this paper. Combining with the coherent Doppler lidar signal‐to‐noise ratio, vertical velocity skewness, turbulence kinetic energy dissipation rate, and wind shear intensity, the categories of turbulent mixing sources and the specific turbulent mixing sources could be determined. The method is applied into two voyages of MABL observation during May 2021 in the South China Sea and during April 2022 in the Bohai Sea and Yellow Sea. The turbulent mixing processes are captured and the classification of the turbulence driven sources within the MABL are realized. The temporal‐spatial evolution characteristics of the turbulence mixing process in the MABL are investigated under different weather conditions containing clear‐sky day, cloudy‐sky day, and sea‐fog day. The convective mixing process is recognized in the daytime of the clear‐sky day and the intermittent cloud‐driven turbulence exists below the cloud layer. Additionally, the turbulent mixing is weak which could not act as the main driven source during the sea‐fog day. Furthermore, the dominant turbulence scale analyses of different turbulence sources are conducted based on the cospectra of the vertical velocity and the horizontal speed measurements. The turbulence parameters of different turbulence sources are statistical analyzed and compared in different sea areas. The classification method has the broad application prospects on the study of the air‐sea interaction.
... The critical aspect of the SRM for simulating wind loads is defining the underlying (target) stochastic process. Analytical formulations of the power spectral density (PSD) and CPSD Wind 2023, 3 functions have been largely used to define the target load process and are generally limited to a few wind directions (e.g., along-wind, across-wind) and geometries [9,[19][20][21][22][23]. Some recent studies have used measured data as input (sample-based), to calibrate the stochastic process [8,10,16,24,25], which is seen as a straightforward and physically meaningful alternative. ...
The simulation of stochastic wind loads is necessary for many applications in wind engineering. The proper-orthogonal-decomposition-(POD)-based spectral representation method is a popular approach used for this purpose, due to its computational efficiency. For general wind directions and building configurations, the data-informed POD-based stochastic model is an alternative that uses wind-tunnel-smoothed auto- and cross-spectral density as input, to calibrate the eigenvalues and eigenvectors of the target load process. Even though this method is straightforward and presents advantages, compared to using empirical target auto- and cross-spectral density, the limitations and errors associated with this model have not been investigated. To this end, an extensive experimental study on a rectangular building model considering multiple wind directions and configurations was conducted, to allow the quantification of uncertainty related to the use of short-duration wind tunnel records for calibration and validation of the data-informed POD-based stochastic model. The results demonstrate that the data-informed model can efficiently simulate stochastic wind loads with negligible model errors, while the errors associated with calibration to short-duration wind tunnel data can be important.
... Raw EC data were collected at 20 Hz and averaged every 30min. Corrections for coordinate rotation (double rotation; Kaimal and Finnigan, 1994), time lag and sensor separation (Leuning and Judd, 1996) and density effects (Burba et al., 2012) were applied, following common Fluxnet protocols (Webb et al., 1980;Leuning and Judd, 1996;Foken and Leclerc, 2004;Aubinet et al., 2012). Resulting half-hour fluxes were then quality checked and further processed using a custom R-Software script. ...
... To calculate turbulent flows in a horizontally statistically uniform surface layer, the Monin-Obukhov similarity theory (MOST) (Monin and Obukhov, 1954) became widely used, the generalization to the case of a flow over an inhomogeneous surface of which is still not practically developed. The use of MOST is limited to the lower layer of the atmosphere above a homogeneous surface, in which the stability parame-ter is (Monin and Yaglom, 1965;Kaimal and Finnigan 1994;Wyngaard 2010). Under these conditions, the statistical characteristics of meteorological fields can depend only on the measurement height. ...
... The Reynolds averaging operation follows the conventional approach of 30-min bulk averaging, which is supported explicitly by flux ogive functions for sensible heat and water vapor (quantitative results to appear in Fig. 4a). Moreover, potential flux loss at high frequencies has to be corrected due to path averaging and limited sampling frequency, especially relevant to a low measurement height, i.e., on the order of 10 0 m (see [43]). Scalar flux data are corrected using the transfer-function approach in combination with the cospectral models of [42] (cf. ...
Based on eddy-covariance measurements over a glacier, we investigate the scalar flux dissimilarity between sensible heat and water vapor transport in a stably stratified flow. The scalar flux correlation coefficient \({{R}_{F}}\) is used as a measure of variable levels of the flux similarity, which are often elevated due to a rising degree of the kinetic anisotropy of turbulence. Moreover, sensible heat is transported more efficiently than water vapor; and transport efficiencies of these two scalars are separated in terms of their variability with the velocity aspect ratio. Compared with air temperature fluctuations, turbulence characteristics of the water vapor concentration are subject to a more pronounced modification because of distinct magnitudes of \({R}_{F}\). An innovative method is employed for connecting quadrant analysis and cospectral analysis, so that the hyperbolic quadrant-hole size can be coupled to the natural frequency underlying the fast Fourier transform. Then, we introduce a hypothetical octant hole whose size is invoked as a metric for the amplitude scale of fluctuating scalar fluxes. The contributions to \({R}_{F}\) are quantified for a variety of eddy structures that are associated with different ranges of the amplitude scale. Regarding larger-amplitude fluxes due to heated drier air parcels in descending motions, reductions in \(\left|{R}_{F}\right|\) correspond to increasing flux fractions for water vapor, whereas the flux fractions for sensible heat are largely unchanged. Overall, a more substantial portion of the changes in \(\left|{R}_{F}\right|\) can be ascribed to smaller-amplitude fluxes due to cooled moister air parcels and heated drier air parcels being involved, respectively, in ascending and descending motions. Reductions in \(\left|{R}_{F}\right|\) relate to the flux fractions of a decreasing magnitude for sensible heat but of an increasing magnitude for water vapor.
... Such measurements are inherently limited by the optical transparency of the air. To date, the most common solutions to this limitation require introducing an engineered, physical object into the flow whose interaction with the wind can be detected visually as a qualitative indicator (a windsock or wind vane 23 , for example) or alternatively, by converting the physical interaction of the object and the wind into a calibrated, quantitative signal (using a cup anemometer or light detection and ranging system [24][25][26] , for example). Measurements using these approaches are all fundamentally constrained by the requirement that the measurement device must be in close proximity to the measurement domain of interest. ...
Accurate measurements of atmospheric flows at metre-scale resolution are essential for many sustainability applications, including optimal design of wind and solar farms, navigation and control of air flows in the built environment, monitoring of environmental phenomena such as wildfires and air pollution dispersal, and data assimilation into weather and climate models. Measurement of the relevant multiscale wind flows is inherently challenged by the optical transparency of the wind. This Perspective article explores new ways in which physics can be leveraged to ‘see’ environmental flows non-intrusively, that is, without the need to place measurement instruments directly in the flows of interest. Specifically, although wind itself is transparent, its effect can be seen in the motion of objects embedded in the environment and subjected to wind — swaying trees and flapping flags are commonly encountered examples. We survey emerging efforts to accomplish visual anemometry, the task of quantitatively inferring local wind conditions on the basis of the physics of observed flow–structure interactions. Approaches based on first-principles physics as well as data-driven, machine learning methods will be described, and remaining obstacles to fully generalizable visual anemometry are discussed.
... Initially, any outliers were removed. Subsequently, trend correction [34], the double rotation method [35], frequency response correction [36], sonic temperature correction [37], and Webb-Pearman-Leuning correction [38] were applied. Additionally, a turbulence stationarity test and an overall turbulence characteristic test were conducted to assess the quality of the data. ...
Grassland ecosystems are an important component of global terrestrial ecosystems and play a crucial role in the global carbon cycle. Therefore, it is important to study the carbon dioxide (CO2) process in the Middle Tien Shan grassland ecosystem, which can be regarded as a typical representative of the mountain grasslands in Xinjiang. Eddy covariance (EC) and the global carbon fluxes dataset (GCFD) were utilized to continuously monitor the Middle Tien Shan grassland ecosystem in Xinjiang throughout the 2018 growing season. The findings revealed notable daily and monthly fluctuations in net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco). On a daily basis, there was net absorption of CO2 during the day and net emission during the night. The grassland acted as a carbon sink from 6:00 to 18:00 and as a carbon source for the remaining hours of the day. On a monthly scale, June and July served as carbon sinks, whereas the other months acted as carbon sources. The accumulated NEE, GPP, and Reco during the growing season were −329.49 g C m−2, 779.04 g C m−2, and 449.55 g C m−2, respectively. On the half-hourly and daily scales, soil temperature (Ts) was the main contributor to CO2 fluxes and had the greatest influence on the variations in CO2 fluxes. Additionally, air temperature (Ta) showed a strong correlation with CO2 fluxes. The grassland ecosystems exhibited the strongest CO2 uptake, reaching its peak at soil temperatures of 25 °C. Moreover, as the air temperatures rose above 15 °C, there was a gradual decrease in NEE, while CO2 uptake increased. The applicability of GCFD data is good in the grassland ecosystem of the Middle Tien Shan Mountains, with correlations of 0.59, 0.81, and 0.73 for NEE, GPP, and Reco, respectively, compared to field observations. In terms of remote sensing spatial distribution, the Middle Tien Shan grassland ecosystem exhibits a carbon sink phenomenon.
... These results indicate that the simulated wind speeds exhibit similar fractal and commonly used HSM method are similar to that of the measured wind record, and each probability 393 distribution fits well with the Gaussian distribution. According to Fig. 14, it can be observed that the 394 original wind speed spectrum shows a tendency to deviate from the classical von Karman spectrum 395 beyond a frequency of 2 Hz, which might be attributed to the existence of Gaussian white noise in the 396 measured wind data as reported by Kaimal and Finnigan (1994). Fig. 15 shows the evolutionary power 397 spectral density (EPSD) of nonstationary wind speeds to reveal the turbulent energy distribution both 398 in time and frequency domain (Priestley, 1965). ...
This paper proposes a fractal-based technique for simulating multivariate nonstationary wind speed fields by the stochastic Weierstrass Mandelbrot function. Upon conducting a systematic fractal analysis, it was found that the structure function method is more suitable and reliable than the box counting method, variation method, and R/S analysis method for estimating the fractal dimension of the stochastic wind speed series. Wind field measurement at the meteorological gradient tower with a height of 356 m in Shenzhen was conducted during Typhoon Mangkhut (2018). Significant non-stationary properties and fractal dimensions of typhoon wind speed data at various heights were analyzed and used to demonstrate the effectiveness of the proposed multivariate typhoon wind speed simulation method. The multivariate wind speed components simulated by the proposed fractal-based method are in good agreement with the measured records in terms of the fractal dimension, standard deviation, probability density function, wind spectrum and cross-correlation coefficient.
... The eddy covariance micrometeorological technique was applied in this work to quantify the atmosphere-surface particle exchange in a size-dependent mode. The flux is computed as the mean cross-product of the fluctuations in a scalar concentration (s ) and the vertical component of wind velocity (w ) as F s = w s , where the overbar indicates the average values (Kaimal and Finnigan, 1994;Stull, 1988). Turbulent fluxes were calculated on a 30 min basis, using a homemade code developed in MATLAB ® 2018b. ...
Estimating aerosol depositions on snow and ice surfaces and assessing the aerosol lifecycle in the Arctic region is challenged by the scarce measurement data available for particle surface fluxes. This work aims at assessing the deposition velocity of atmospheric particles at an Arctic site (Ny-Ålesund, Svalbard islands) over snow, during the melting season, and over dry tundra. The measurements were performed using the eddy covariance method from March to August 2021. The measurement system was based on a condensation particle counter (CPC) for ultrafine particle (UFP; < 0.25 µm) fluxes and an optical particle counter (OPC) for evaluating particle size fluxes in the accumulation mode (ACC; 0.25 < d p < 0.7 µm) and quasi-coarse mode (CRS; 0.8 < d p < 3 µm). Turbulent fluxes in the ultrafine particle size range were prevalently downward, especially in summertime. In contrast, particle fluxes in the accumulation and quasi-coarse mode were more frequently positive, especially during the colder months, pointing to surface sources of particles from, for example, sea spray, snow sublimation, or local pollution. The overall median deposition velocity (V + d) values were 0.90, 0.62, and 4.42 mm s −1 for UFP, ACC, and CRS, respectively. Deposition velocities were smaller, on average, over the snowpack, with median values of 0.73, 0.42, and 3.50 mm s −1. The observed velocities differ by less than 50 % with respect to the previous literature in analogous environments (i.e. ice/snow) for particles in the size range 0.01-1 µm. At the same time, an agreement with the results of predictive models was found for only a few parameterizations, in particular with Slinn (1982), while large biases were found with other models, especially in the range 0.3-10 µm, of particle diameters. Our observations show a better fit with the models predicting a minimum deposition velocity for small-accumulation-mode particle sizes (0.1-0.3 µm) rather than for larger ones (about 1 µm), which could result from an efficient interception of particles over snow surfaces which are rougher and stickier than the idealized ones. Finally, a polynomial fit was investigated (for the ACC-CRS size range) to describe the deposition velocity observations which properly represents their size dependence and magnitude. Even if this numerical fit is driven purely by the data and not by the underlying chemical-physical processes, it could be very useful for future model parameterizations.
This study evaluated the performance of remote sensing (RS) algorithms for the estimation of actual maize evapotranspiration (ETa) using different spaceborne, airborne, and proximal multispectral data in a semi-arid climate region to identify the optimal platform that provides the best ETa estimates to improve irrigation water management and help make irrigated agriculture sustainable. The RS platforms used in the study included Landsat-8 (30 m pixel spatial resolution), Sentinel-2 (10 m), Planet CubeSat (3 m), multispectral radiometer or MSR (1 m), and a small uncrewed aerial system or sUAS (0.03 m). Two-source surface energy balance (TSEB) models, implementing the series and parallel surface resistance approaches, were used in this study to estimate hourly maize ETa. The data used in this study were obtained from two maize research sites in Greeley and Fort Collins, CO, USA, in 2020 and 2021. Each research site had different irrigation systems. The Greeley site had a subsurface drip system, while the Fort Collins site had surface irrigation (furrow). Maize ETa predictions were compared to observed maize ETa data from an eddy covariance system installed at each research site. Results indicated that the MSR5 proximal platform (1 m) provided optimal RS data for the TSEB algorithms. The MSR5 “point-based” nadir-looking surface reflectance data and surface radiometric temperature combination resulted in the smallest error when predicting hourly (mm/h) maize ETa. The mean bias and root mean square errors (MBE and RMSE, respectively), when predicting maize hourly ETa using the MSR5 sensor data, were equal to −0.02 (−3%) ± 0.07 (11%) mm/h MBE ± RMSE and −0.02 (−3%) ± 0.09 (14%) mm/h for the TSEB parallel and series approaches, respectively. The poorest performance, when predicting hourly TSEB maize ETa, was from Landsat-8 (30 m) multispectral data combined with its original thermal data, since the errors were −0.03 (−5%) ± 0.16 (29%) mm/h and −0.07 (−13%) ± 0.15 (29%) mm/h for the TSEB parallel and series approaches, respectively. These results indicate the need to develop methods to improve the quality of the RS data from sub-optimal platforms/sensors/scales/calibration to further advance sustainable irrigation water management.
To better understand the effects of clearing size and forest characteristics on wind flow, two-dimensional Reynolds-Averaged Navier-Stokes (RANS) simulations were performed. A modified k−ε model accounting for vegetation drag was used following its validation against wind tunnel experiments. The neutrally stable stratified Horizontally Homogeneous Atmospheric Surface Layer (HHASL) was driven both by a pressure gradient and a shear stress, which decreased with height, and original top boundary conditions for the turbulent quantities were introduced. Agreement with field measurements was significantly better than when the shear stress was assumed constant across the domain. Clearing sizes ranging from 1h to 100h were investigated within a boreal forest, and with six other forest morphologies. Assuming that a wind turbine was installed in the clearing, spatial variations of available wind Energy (E), Average Wind Shear (AWS) and cumulative Turbulent Kinetic Energy (cTKE) in layers where the wind flow intersects with the swept area were estimated for three hub heights. Unexpectedly, the results show that a forest clearing does not generate a gain in E or a significant reduction of cTKE or AWS compared to an undisturbed forested. Enlarging the clearing does not necessarily improve these variables and, contrary to current practice, it appears optimal to minimize clearings.
Accurate air temperature measurements are essential in eddy covariance systems, not only for determining sensible heat flux but also for applying the density effect corrections (DEC) to water vapor and CO2 fluxes. However, the influence of wind-induced vibrations of mounting structures on temperature fluctuations remains a subject of investigation. This study examines 30-min average temperature variances and fluxes using eddy covariance systems, combining Campbell Scientific Anemometer Thermometry (CSAT3B) with closely co-located fine-wire thermocouples alongside LI-COR CO2/H2O gas analyzers at multiple heights above a sagebrush ecosystem. The variances of sonic temperature after humidity corrections (Ts) and sensible heat fluxes derived from are underestimated (e.g., by approximately 5 % for temperature variances and 4 % for sensible heat fluxes at 40.2 m, respectively) as compared with those measured by a fine-wire thermocouple (Tc). Spectral analysis illustrates that these underestimated variances and fluxes are caused by the lower energy levels in the Ts spectra than the Tc spectra in the low frequency range (natural frequency < 0.02 Hz). This underestimated Ts spectra in the low frequency range become more pronounced with increasing as wind speeds, especially when wind speed exceeds 10 m s-1. Moreover, the underestimated temperature variances and fluxes cause overestimated water vapor and CO2 fluxes through DEC. Our analysis suggests that these underestimations when using Ts are likely due to wind-induced vibrations affecting the tower and mounting arms, altering the time of flight of ultrasonic signals along three sonic measurement paths. This study underscores the importance of further investigations to develop corrections for these errors.
This paper investigates the impact of large-scale turbulence on the aerodynamic characteristics of a pitching wind turbine blade at Reynolds number 135 000, whose cross-section is a NACA0012 airfoil with constant chord length. Large-eddy simulations at reduced frequencies, $k_{red} = 0.05$ and 0.1, were validated against reference data from the literature. An efficient method capable of generating synthetic large-scale turbulence at the inlet was applied by using two streamwise integral length scales $L_{x} = 1c$ and 1.5$c$, which represent energetic turbulence eddies at the height where the wind turbine operates. For $k_{red}= 0.1$, the change in the maximum lift coefficient at the dynamic stall angle near the maximum angle of attack is on average 20 % lower and during the downstroke it is on average 22 % lower, compared with the smooth inflow. A higher reduced frequency ($k_{red} = 0.2$) apparently does not further change the lift, drag and moment coefficients, and the inflow turbulence disordered leading-edge vortices. The turbulent shear stress and the phase-averaged dispersive shear stress in the wake are of the same magnitude, but with negative and positive signs, respectively, suggesting that the large-scale phase-averaged fluctuations transfer momentum in the opposite direction compared with the turbulent fluctuations, reducing the drag on the suction-side flow, and subsequently increasing the averaged lift coefficient. This demonstrates the critical importance of the large-scale non-turbulent unsteadiness in the wake of a pitching wing.
Dedicated to the 150th anniversary of the appearance of Gibbs' Fundamental Thermodynamic Relation. Abstract: Under typical marine conditions of about 80% relative humidity, evaporation of water from the ocean is an irreversible process accompanied by entropy production. In this article, equations are derived for the latent heat of irreversible evaporation and the related nonequilibrium entropy balance at the sea surface. To achieve this, linear irreversible thermodynamics is considered in a conceptual ocean evaporation model. The equilibrium thermodynamic standard TEOS-10, the International Thermodynamic Equation of Seawater-2010, is applied to irreversible evaporation under the assumption of local thermodynamic equilibrium. The relevance of local equilibrium conditions for irreversible thermodynamics is briefly explained. New equations are derived for the mass flux of evaporation and for the associated nonequilibrium enthalpies and entropies. The estimated entropy production rate of ocean evaporation amounts to 0.004 W m −2 K −1 as compared with the average terrestrial global entropy production of about 1 W m −2 K −1 .
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