Turbulent Flux Measurements Research Articles

Surface energy balance closure over melting snow and ice from in situ measurements on the Greenland ice sheet

Abstract Accurately quantifying all the components of the surface energy balance (SEB) is a prerequisite for the reliable estimation of surface melt and the surface mass balance over ice and snow. This study quantifies the SEB closure by comparing the energy available for surface melt, determined from continuous measurements of radiative fluxes and turbulent heat fluxes, to the surface ablation measured on the Greenland ice sheet between 2003 and 2023. We find that the measured daily energy available for surface melt exceeds the observed surface melt by on average 18 ± 30 W m−2 for snow and 12 ± 54 W m−2 for ice conditions (mean ± SD), which corresponds to 46 and 10% of the average energy available for surface melt, respectively. When the surface is not melting, the daily SEB is on average closed within 5 W m−2. Based on the inter-comparison of different ablation sensors and radiometers installed on different stations, and on the evaluation of modelled turbulent heat fluxes, we conclude that measurement uncertainties prevent a better daily to sub-daily SEB closure. These results highlight the need and challenges in obtaining accurate long-term in situ SEB observations for the proper evaluation of climate models and for the validation of remote sensing products.

An evaluation of different measurement strategies to measure wind turbine near wake flow with small multicopter UAS

Wind turbine wake flow, especially in the near wake, that is up to one rotor diameter D downstream, is subject to interaction between tip vortices and ambient turbulence. These interactions are important to understand wake decay, but most difficult to measure with common instrumentation. Small uncrewed aerial systems (UAS) can help to measure at such locations where no masts can be installed. We contrast two measurement strategies, the hover flight with multiple UAS and cross-section flights with single UAS. We show that both strategies have advantages; the cross-section flights provide a full picture of the width and wind speed deficit across the rotor diameter whereas multi-UAS hover flights can provide more reliable turbulence intensity and turbulent flux measurements at specific locations. With both strategies, tip vortices can be detected and qualified to characterize the state of wake decay at different positions. A fit to the vortex models Lamb-Oseen and Burnham-Hallock allows to estimate circulation and core radius of the vortices. For best characterization of the wake, we recommend to combine the hover and cross-section flight strategies in future.

Modeling Heat and Water Exchanges between the Atmosphere and an 85-km2 Dimictic Subarctic Reservoir Using the 1D Canadian Small Lake Model

Abstract Accurately modeling the interactions between inland water bodies and the atmosphere in meteorological and climate models is crucial, given the marked differences with surrounding landmasses. Modeling surface heat fluxes remains a challenge because direct observations available for validation are rare, especially at high latitudes. This study presents a detailed evaluation of the Canadian Small Lake Model (CSLM), a one-dimensional mixed-layer dynamic lake model, in reproducing the surface energy budget and the thermal stratification of a subarctic reservoir in eastern Canada. The analysis is supported by multiyear direct observations of turbulent heat fluxes collected on and around the 85-km2 Romaine-2 hydropower reservoir (50.7°N, 63.2°W) by two flux towers: one operating year-round on the shore and one on a raft during ice-free conditions. The CSLM, which simulates the thermal regime of the water body including ice formation and snow physics, is run in offline mode and forced by local weather observations from 25 June 2018 to 8 June 2021. Comparisons between observations and simulations confirm that CSLM can reasonably reproduce the turbulent heat fluxes and the temperature behavior of the reservoir, despite the one-dimensional nature of the model that cannot account for energy inputs and outputs associated with reservoir operations. The best performance is achieved during the first few months after the ice break-up (mean error = −0.3 and −2.7 W m−2 for latent and sensible heat fluxes, respectively). The model overreacts to strong wind events, leading to subsequent poor estimates of water temperature and eventually to an early freeze-up. The model overestimated the measured annual evaporation corrected for the lack of energy balance closure by 5% and 16% in 2019 and 2020. Significance Statement Freshwater bodies impact the regional climate through energy and water exchanges with the atmosphere. It is challenging to model surface energy fluxes over a northern lake due to the succession of stratification and mixing periods over a year. This study focuses on the interactions between the atmosphere of an irregular shaped northern hydropower reservoir. Direct measurements of turbulent fluxes using an eddy covariance system allowed the model assessment. Turbulent fluxes were successfully predicted during the open water period. Comparison between observed and modeled time series showed a good agreement; however, the model overreacted to high wind episodes. Biases mostly occur during freeze-up and breakup, stressing the importance of a good representation of the ice cover processes.

A New Post‐Hoc Method to Reduce the Energy Imbalance in Eddy Covariance Measurements

AbstractLatent and sensible heat flux observations are essential for understanding land–atmosphere interactions. Measurements from the eddy covariance technique are widely used but suffer from systematic energy imbalance problems, partly due to missing large eddies from sub‐mesoscale transport. Because available energy drives the development of large eddies, we propose an available energy based correction method for turbulent flux measurements. We apply our method to 172 flux tower sites and show that we can reduce the energy imbalance from −14.99 to −0.65 W m−2 on average, together with improved consistency between turbulent fluxes and available energy and associated increases in r2 at individual sites and across networks. Our results suggest that our method is conceptually and empirically preferable over the method implemented in the ONEFlux processing. This can contribute to the efforts in understanding and addressing the energy imbalance issue, which is crucial for the evaluation and calibration of land surface models.

Development of a footprint description tool utilizing SMEAR Estonia eddy-covariance data and footprint modelling in combination with remote sensed forest species and land cover data

Abstract Understanding how forest ecosystems respond to environmental factors, particularly in the context of global climate change, is essential for devising effective mitigation strategies. This study focuses on quantifying the interaction between forest ecosystems and atmospheric gases. To achieve our objectives, we are using the eddy covariance (EC) flux method to measure air turbulence and gas concentrations above the forest canopy at the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) in southern Estonia. We apply a flux footprint (FFP) model to describe the spatial extent and position of the surface area contributing to the turbulent flux measurements. The FFP analysis provides valuable insights into the long-term changes in SMEAR Estonia, the FFP and its relationship with forest management and land use changes. Our findings reveal that the FFP area varies from year to year due to changes in wind speed and direction, affecting the contribution of different land cover elements to the overall FFP. The average changes in the FFP area at a height of 30 meters were approximately 4.9%, while those at a height of 70 meters were only 1.6%. Moreover, human activities, such as thinning and clear-cutting, influence the growing stock and increment of forest stands.

Quality evaluation for measurements of wind field and turbulent fluxes from a UAV-based eddy covariance system

Abstract. Instrumentation packages for eddy covariance (EC) measurements have been developed for unoccupied aerial vehicles (UAVs) to measure the turbulent fluxes of latent heat (LE), sensible heat (H), and CO2 (Fc) in the atmospheric boundary layer. This study aims to evaluate the performance of this UAV-based EC system. First, the measurement precision (1σ) of georeferenced wind was estimated to be 0.07 m s−1. Then, the effect of the calibration parameter and aerodynamic characteristics of the UAV on wind measurement was examined by conducting a set of calibration flights. The results showed that the calibration improved the quality of the measured wind field, and the influence of upwash and the leverage effect can be ignored in wind measurement by the UAV. Third, for the measurements of turbulent fluxes, the error caused by instrumental noise was estimated to be 0.03 µmolm-2s-1 for Fc, 0.02 W m−2 for H, and 0.08 W m−2 for LE. Fourth, data from the standard operational flights were used to assess the influence of resonance on the measurements and to test the sensitivity of the measurement under the variation (±30 %) in the calibration parameters around their optimum value. The results showed that the effect of resonance mainly affected the measurement of CO2 (∼5 %). The pitch offset angle (εθ) significantly affected the measurement of vertical wind (∼30 %) and turbulent fluxes (∼15 %). The heading offset angle (εψ) mainly affected the measurement of horizontal wind (∼15 %), and other calibration parameters had no significant effect on the measurements. The results lend confidence to the use of the UAV-based EC system and suggest future improvements for the optimization of the next-generation system.

Wind-tunnel measurements of sensible turbulent heat fluxes over melting ice

Accelerated glacier melt and the loss of perennial snowfields have been associated with increased warming in polar regions, at rates up to four times faster than the rest of the world, thereby reinforcing the critical need for improved models (and predictions) of glacier melt. An essential requirement for such models is an improved understanding of the sensible heat fluxes over glaciers. Since their complexity makes them difficult to model, and direct measurements of sensible turbulent heat fluxes over real glaciers are both rare and impractical, the present work involves simultaneous hot-wire anemometry and cold-wire thermometry measurements of two components of velocity and temperature above a melting glacier model in a series of wind-tunnel experiments. Both single- and multi-variable statistics were used to compare the turbulent velocity field measured over melting ice with that of a similar flow in the absence of ice. The results demonstrate that the ice's presence reduces the magnitude of the Reynolds stresses and vertical velocity variance, but also increases the streamwise velocity variance. The transient evolution of temperature statistics throughout the melt process was also investigated and found to be similar when suitably non-dimensionalized. The velocity and temperature fields were furthermore evaluated at an equivalent non-dimensional time during the melt process, in which statistics of the temperature field, and joint statistics of the vertical velocity and temperature, were studied. The present work lays the foundation for future laboratory-scale replications of the flow above melting glaciers, and provides additional insight into turbulent heat transfer over melting ice.

Surface energy balance fluxes in a suburban area of Beijing: energy partitioning variability

Abstract. Measurements of radiative and turbulent heat fluxes for 16 months in suburban Miyun with a mix of buildings and agriculture allows the changing role of these fluxes to be assessed. Daytime turbulent latent heat fluxes (QE) are largest in summer and smaller in winter, consistent with the net all-wave radiation (Q*), whereas the daytime sensible heat flux (QH) is greatest in spring but smallest in summer rather than in winter, as commonly observed in suburban areas. The results have larger seasonal variability in energy partitioning compared to previous suburban studies. Daytime energy partitioning is between 0.15–0.57 for QH/Q* (mean summer = 0.16; winter = 0.46), 0.06–0.56 for QE/Q* (mean summer = 0.52; winter = 0.10), and 0.26–7.40 for QH/QE (mean summer = 0.32; winter = 4.60). Compared to the literature for suburban areas, these are amongst the lowest and highest values. Results indicate that precipitation, irrigation, vegetation growth activity, and land use and land cover all play critical roles in the energy partitioning. These results will help to enhance our understanding of surface–atmosphere energy exchanges over cities and are critical to improving and evaluating urban canopy models needed to support integrated urban services that include urban planning to mitigate the adverse effects of urban climate change.

Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables

Abstract. This study evaluates water and energy fluxes and variables in combination with parameter optimization of version 5 of the state-of-the-art Community Land Model (CLM5) land surface model, using 6 years of hourly observations of latent heat flux, sensible heat flux, groundwater recharge, soil moisture and soil temperature from an agricultural observatory in Denmark. The results show that multi-objective calibration in combination with truncated singular value decomposition and Tikhonov regularization is a powerful method to improve the current practice of using lookup tables to define parameter values in land surface models. Using measurements of turbulent fluxes as the target variable, parameter optimization is capable of matching simulations and observations of latent heat, especially during the summer period, whereas simulated sensible heat is clearly biased. Of the 30 parameters considered, the soil texture, monthly leaf area index (LAI) in summer, stomatal conductance and root distribution have the highest influence on the local-scale simulation results. The results from this study contribute to improvements of the model characterization of water and energy fluxes. This work highlights the importance of performing parameter calibration using observations of hydrologic and energy fluxes and variables to obtain the optimal parameter values for a land surface model.

Airborne observations of the surface cloud radiative effect during different seasons over sea ice and open ocean in the Fram Strait

Abstract. This study analyses the cloud radiative effect (CRE) obtained from near-surface observations of three airborne campaigns in the Arctic north-west of Svalbard: Airborne measurements of radiative and turbulent FLUXes of energy and momentum in the Arctic boundary layer (AFLUX, March/April 2019), Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD, May/June 2017), and Multidisciplinary drifting Observatory for the Study of Arctic Climate – Airborne observations in the Central Arctic (MOSAiC-ACA, August/September 2020). The surface CRE quantifies the potential of clouds to modify the radiative energy budget at the surface and is calculated by combining broadband radiation measurements during low-level flight sections in mostly cloudy conditions with radiative transfer simulations of cloud-free conditions. The significance of surface albedo changes due to the presence of clouds is demonstrated, and this effect is considered in the cloud-free simulations. The observations are discussed with respect to differences of the CRE between sea ice and open-ocean surfaces and between the seasonally different campaigns. The results indicate that the CRE depends on cloud, illumination, surface, and thermodynamic properties. The solar and thermal-infrared (TIR) components of the CRE, CREsol and CRETIR, are analysed separately, as well as combined for the study of the total CRE (CREtot). The inter-campaign differences of CREsol are dominated by the seasonal cycle of the solar zenith angle, with the strongest cooling effect in summer. The lower surface albedo causes a stronger solar cooling effect over open ocean than over sea ice, which amounts to −259 W m−2 (−108 W m−2) and −65 W m−2 (−17 W m−2), respectively, during summer (spring). Independent of campaign and surface type, CRETIR is only weakly variable and shows values around 75 W m−2. In total, clouds show a negative CREtot over open ocean during all campaigns. In contrast, over sea ice, the positive CREtot suggests a warming effect of clouds at the surface, which neutralizes during mid-summer. Given the seasonal cycle of the sea ice distribution, these results imply that clouds in the Fram Strait region cool the surface during the sea ice minimum in late summer, while they warm the surface during the sea ice maximum in spring.

Eddy Covariance Measurements of Turbulent Heat Fluxes over a Grass-covered Surface in a Tropical Location

In this study, an Eddy Covariance (EC) system was deployed to measure the turbulent heat fluxes (sensible and latent heat fluxes) at a farmland located at Obafemi Awolowo University, Ile-Ife, Nigeria. The period of measurement was between 2016 and 2019. The surface of the measurement area was covered by grass (Axonopus fissifolius) and changes from leafy-green during the wet season to dry twigs during the dry season. The sensible heat flux, Hs obtained ranged between -0.8 and 181.9 Wm-2 while the latent heat flux, Hl varied between 0.9 and 218.0 Wm-2. The maximum daytime value of Hs peaked in January while the maximum daytime value of Hl peaked in October. The sensible heat flux was 59 % higher than the latent heat flux during the Harmattan months (January, February and December), while the latent heat flux was 63 % higher than the sensible heat flux during the wet months (April - November). The study concluded that 91 % of the energy available at the surface during the period of study, was used for evapotranspiration while only 9 % was used for sensible heating as shown by the distribution of the Bowen ratio.

Urbanization associated changes in biogeochemical cycles.

Urbanization associated changes in biogeochemical cycles.

AirSeaFluxCode: Open-source software for calculating turbulent air-sea fluxes from meteorological parameters

The turbulent exchanges, or fluxes, of heat, moisture and momentum between the atmosphere and the ocean play a crucial role in the Earth’s climate system. Direct measurements of turbulent fluxes are very challenging and sparse, and do not span the full range of environmental conditions that exist over the ocean. This means that empirical “bulk formulae” parameterizations that relate direct flux observations to concurrent measurements of the mean meteorological and sea surface variables contain considerable uncertainty. In this paper, we present a Python 3.6 (or higher) open-source software package “AirSeaFluxCode” for the computation of the heat (latent and sensible) and momentum fluxes. Ten different parameterizations are included, each based on published descriptions or code and each derived from a different set of observations, or different assumptions about the turbulent exchange processes. They represent a range of current expert opinion on how the fluxes depend on mean properties and can be used to explore uncertainty in calculated fluxes. AirSeaFluxCode also allows the adjustment of the mean meteorological input parameters (air temperature, humidity and wind speed) from the height at which they are obtained to a user-defined output height. This height adjustment enables the comparison of measurements, or model-derived values, made at different heights above sea-level. The parameterizations calculate the fluxes using input parameters that are relatively easily to measure, or are available as model output: wind speed, air temperature, sea surface temperature, atmospheric pressure and humidity. Where original code is available we have compared its output with that of AirSeaFluxCode. Any changes made to increase consistency across algorithms by standardizing computational methods or calculation of meteorological variables, for example, are discussed and the impacts quantified: these are shown to be insignificant except for a few cases where conditions were extreme, and AirSeaFluxCode is shown to be robust. We also investigate the impact on the fluxes caused by different assumptions about the exchange processes, or the choices inherent in the implementation of the parameterizations. For example, sea surface temperature usually refers to data typically obtained at depths of between 1 and 10 m. However, since some parameterizations require a “skin” sea surface temperature, code that adjusts temperature at depth to skin temperature is included: this has a very significant impact on the fluxes. Selecting a parameterization that is appropriate for the available sea surface temperature will avoid the need to adjust the sea temperature data and the uncertainties associated with that adjustment, and will also avoid the biases due to use of the “wrong” measure of temperature. Significant differences also resulted from assumptions about the size of reduction in sea surface humidity to account for salinity effects: the uncertainty in the reduction factor needs to be quantified in future analyses. Fluxes in extreme conditions are particularly uncertain since the transfer coefficients in the different parameterizations vary most at very high and very low wind speeds. Low wind speeds are also challenging for numerical implementation since choices have to be made regarding: convergence criteria for the iterative calculation, inclusion of a parameterization for convective gustiness, or application of ad hoc limits to various parameters. All of these choices can significantly affect the flux estimates for light winds.

Seasonal Changes in Atmospheric Optical Turbulence in a Near Maritime Environment Using Turbulence Flux Measurements

Light propagation through the atmosphere is affected by fluctuations in the refractive index along the path of propagation, called optical turbulence. In the atmospheric surface layer, these fluctuations are due mostly to turbulent mixing of variations in temperature. To this end, a characterization of the atmospheric surface layer above the water in Maryland, USA, is presented. Meteorological data were collected from a sensor array comprising two sonic anemometers and an infrared gas analyzer (IRGASON) over the 12-month period from January to December, 2021. The instruments were positioned vertically at heights of approximately 4 m, 6 m, and 8 m above the water. The temperature structure parameter CT2 was calculated and scaled using Monin–Obukhov assumptions. We find that the distribution of atmospheric stability presents as an approximately normal distribution during the winter and early spring, but is skewed negatively during the summer and late fall. We hypothesize that this could be due to a more stable stratification of the underlying water during summer months. Under unstable (−z/L) conditions, turbulent quantities including the temperature structure parameter scale in a manner consistent with the literature, but with generally better agreement during the summer months. Additionally, the CT2 estimations appear more consistent during the summer months across all values of (z/L). Under stable (+z/L) conditions, there are wide variations in CT2, which is also consistent with the literature.

MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC

Two airborne field campaigns focusing on observations of Arctic mixed-phase clouds and boundary layer processes and their role with respect to Arctic amplification have been carried out in spring 2019 and late summer 2020 over the Fram Strait northwest of Svalbard. The latter campaign was closely connected to the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Comprehensive datasets of the cloudy Arctic atmosphere have been collected by operating remote sensing instruments, in-situ probes, instruments for the measurement of turbulent fluxes of energy and momentum, and dropsondes on board the AWI research aircraft Polar 5. In total, 24 flights with 111 flight hours have been performed over open ocean, the marginal sea ice zone, and sea ice. The datasets follow documented methods and quality assurance and are suited for studies on Arctic mixed-phase clouds and their transformation processes, for studies with a focus on Arctic boundary layer processes, and for satellite validation applications. All datasets are freely available via the world data center PANGAEA.

Turbulent Flux Measurements of the Near‐Surface and Residual‐Layer Small Particle Events

AbstractAccording to recent field studies, almost half of the New Particle Formation (NPF) events occur aloft, in a residual layer, near the top of the boundary layer. Therefore, measurements of the meteorological parameters, precursor gas concentrations, and aerosol loadings conducted at the ground level are often not representative of the conditions where the NPFs take place. This paper presents new measurements obtained during the Turbulent Flux Measurements of the Residual Layer Nucleation Particles, conducted at the Southern Great Plains research site. Vertical turbulent fluxes of 3–10 nm‐sized particles were measured using a sonic anemometer and two condensation particle counters with nominal cutoff diameters of 3 nm and 10 nm mounted at the top of the 10‐m telescoping tower. Aerosol number size distribution (5–300 nm) was determined through the ground‐based Scanning Mobility Particle Sizers. The size selected (15–50 nm) particle hygroscopicity was derived with the Humidified Tandem Differential Mobility Analyzer. The ground level observations were supplemented by vertically‐resolved measurements of horizontal and vertical wind speeds and aerosol backscatter. The data analysis suggests that (a) turbulent flux measurements of 3–10 nm particles can distinguish between near‐surface and residual‐layer small particle events; (b) sub‐50 nm particles had a hygroscopicity value of 0.2, suggesting that organic compounds dominate atmospheric nanoparticle chemical composition at the site; and (c) current methodologies are inadequate for estimating the dry deposition velocity of sub‐10 nm particles because it is not feasible to measure particle concentration very near the surface, in the diffusion sublayer.

On the Variability of Floc Characteristics in a Shallow Estuary

AbstractWe conducted field work in South San Francisco Bay to examine cohesive sediment flocculation dynamics in a shallow, wave‐ and current‐driven estuarine environment. Drawing on data collected using a suite of acoustic and optical instrumentation over three distinct seasons, we found that the factors driving floc size variability differed substantially when comparing locally sourced sediment (i.e., through wave‐driven resuspension) to suspended sediment advected from upstream. Statistical analysis of our extensive field data revealed additional seasonal variability in these trends, with wave stress promoting floc breakup during the summer and winter months, and biological processes encouraging floc growth during the spring productive period. Combining these data with fractal dimension estimates, we found that seasonally varying floc composition can lead to differences in floc settling velocity by a factor of approximately two to five for a given floc size. Finally, by analyzing co‐located turbulence and sediment flux measurements from the bottom boundary layer, we present evidence that the relationship between floc size and the inverse turbulent Schmidt number varies with floc structure. These results can be used to inform sediment transport modeling parameterizations in estuarine environments.

Options to correct local turbulent flux measurements for large-scale fluxes using an approach based on large-eddy simulation

Abstract. The eddy-covariance method provides the most direct estimates for fluxes between ecosystems and the atmosphere. However, dispersive fluxes can occur in the presence of secondary circulations, which can inherently not be captured by such single-tower measurements. In this study, we present options to correct local flux measurements for such large-scale transport based on a non-local parametric model that has been developed from a set of idealized large-eddy simulations. This method is tested for three real-world sites (DK-Sor, DE-Fen, and DE-Gwg), representing typical conditions in the mid-latitudes with different measurement heights, different terrain complexities, and different landscape-scale heterogeneities. Two ways to determine the boundary-layer height, which is a necessary input variable for modelling the dispersive fluxes, are applied, which are either based on operational radio soundings and local in situ measurements for the flat sites or from backscatter-intensity profiles obtained from co-located ceilometers for the two sites in complex terrain. The adjusted total fluxes are evaluated by assessing the improvement in energy balance closure and by comparing the resulting latent heat fluxes with evapotranspiration rates from nearby lysimeters. The results show that not only the accuracy of the flux estimates is improved but also the precision, which is indicated by RMSE values that are reduced by approximately 50 %. Nevertheless, it needs to be clear that this method is intended to correct for a bias in eddy-covariance measurements due to the presence of large-scale dispersive fluxes. Other reasons potentially causing a systematic underestimated or overestimation, such as low-pass filtering effects and missing storage terms, still need to be considered and minimized as much as possible. Moreover, additional transport induced by surface heterogeneities is not considered.

Evaluation of Profiles of Standard Deviation of Vertical Wind in the Urban Area of Rome: Performances of Monin–Obukhov Similarity Theory Using Different Scaling Variables

The parametrizations of meteorological variables provided by the Monin–Obukhov similarity theory (MOST) is of major importance for pollutant dispersion assessment. However, the complex flow pattern that characterizes the urban areas limits the applicability of the MOST. In this work, the performance of different existing parametrizations of the standard deviation of vertical wind velocity were tested in the city of Rome. Results were compared with experimental data acquired by a sonic detection and ranging (SODAR) and a sonic anemometer. Different scaling variables estimated from the anemometer data by considering two coordinate systems—one aligned with the geodetic reference frame and the other following the flow streamlines—were used to evaluate the effects of flow distortion due to the presence of buildings. Results suggest that the MOST parametrizations perform better if the scaling variables obtained using the coordinate system following the flow streamlines are used. This estimation of the scaling variables would make it possible to overcome the difficulties in conducting measurements of turbulent fluxes, either at different altitudes or even in the constant flux layer.

Sampling error in aircraft flux measurements based on a high-resolution large eddy simulation of the marine boundary layer

Abstract. A high-resolution (1.25 m) large eddy simulation (LES) of the nocturnal cloud-topped marine boundary layer is used to evaluate random error as a function of continuous track length L for virtual aircraft measurements of turbulent fluxes of sensible heat, latent heat, and horizontal momentum. Results are compared with the widely used formula of Lenschow and Stankov (1986). In support of these comparisons, the relevant integral length scales and correlations are evaluated and documented. It is shown that for heights up to approximately 100 m (z/zi=0.12), the length scales are accurately predicted by empirical expressions of the form If=Azb. The Lenschow and Stankov expression is found to be remarkably accurate at predicting the random error for shorter (7–10 km) flight tracks, but the empirically determined errors decay more rapidly with L than the L-1/2 relationship predicted from theory. Consistent with earlier findings, required track lengths to obtain useful precision increase sharply with altitude. In addition, an examination is undertaken of the role of uncertainties in empirically determined integral length scales and correlations in flux uncertainties as well as of the flux errors associated with crosswind and along-wind flight tracks. It is found that for 7.2 km flight tracks, flux errors are improved by factor of approximately 1.5 to 2 for most variables by making measurements in the crosswind direction.