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In this study, we compare the wind measurements of a virtual tower triple Doppler lidar setup to those of a sonic anemometer located at a height of 90 m above ground on an instrumented tower and with those of two single Doppler lidars to evaluate the effect of the horizontal homogeneity assumption used for single Doppler lidar applications on the measurement accuracy. The triple lidar setup was operated in a 90 m stare and a step–stare mode at six heights between 90 and 500 m above ground, while the single lidars were operated in a continuous scan velocity–azimuth display (VAD) mode where one of them had a zenith angle of 54.7° and the other one of 28.0°. The instruments were set up at the boundary-layer field site of the German Meteorological Service (DWD) in July and August of 2020 during the FESST@MOL (Field Experiment on sub-mesoscale spatiotemporal variability at the Meteorological Observatory Lindenberg) 2020 campaign. Overall, we found good agreement of the lidar methods for the whole study period for different averaging times and scan modes compared to the sonic anemometer. For the step–stare mode wind speed measurements, the comparability between the triple lidar and the sonic anemometer was 0.47 m s−1 at an averaging time of 30 min with a bias value of −0.34 m s−1. For wind speed measured by one single lidar setup for the same period with an averaging time of 30 min, we found a comparability of 0.32 m s−1 at an averaging time of 30 min and a bias value of −0.07 m s−1 as well as values of 0.47 and −0.34 m s−1 for the other one, respectively. We also compared the wind velocity measurements of the single and triple lidars at different heights and found decreasing agreement between them with increasing measurement height up to 495 m above ground for the single lidar systems. We found that the single Doppler lidar with the increased zenith angle produced poorer agreement with the triple Doppler lidar setup than the one with the lower zenith angle, especially at higher altitudes. At a height of 495 m above ground and with an averaging time of 30 min the comparability and bias for the larger zenith angle were 0.71 and −0.50 m s−1, respectively, compared to values of 0.57 and −0.28 m s−1 for the smaller zenith angle. Our results confirm that a single Doppler lidar provides reliable wind speed and direction data over heterogeneous but basically flat terrain in different scan configurations. For the virtual tower scanning strategies, we developed a new filtering approach based on a median absolute deviation (MAD) filter combined with a relatively relaxed filtering criterion for the signal-to-noise ratio output by the instrument.

Long-term tall-tower eddy-covariance (EC) measurements have been recently established in three European pilot cities as part of the ICOS-Cities project. We conducted a comparison of EC software to ensure a reliable generation of interoperable flux estimates, which is the prerequisite for avoiding methodological biases and improving the comparability of the results. We analyzed datasets covering 5 months collected from EC tall-tower installations located in urbanized areas of Munich, Zurich, and Paris. Fluxes of sensible heat, latent heat, and CO2 were calculated using three software packages (i.e., TK3, EddyPro, and eddy4R) to assess the uncertainty of flux estimations attributed to differences in implemented postprocessing schemes. A very good agreement on the mean values and standard deviations was found across all three sites, which can probably be attributed to a uniform instrumentation, data acquisition, and preprocessing. The overall comparison of final flux time series products showed a good but not yet perfect agreement among the three software packages. TK3 and EddyPro both calculated fluxes with low-frequency spectral correction, resulting in better agreement than between TK3 and the eddy4R workflow with disabled low-frequency spectral treatment. These observed flux discrepancies indicate the crucial role of treating low-frequency spectral loss in flux estimation for tall-tower EC systems.

It is known from arid and semi-arid ecosystems that atmospheric water vapor can directly be adsorbed by the soil matrix. Soil water vapor adsorption was typically neglected and only recently received attention because of improvements in measurement techniques. One technique rarely explored for the measurement of soil water vapor adsorption is eddy covariance (EC). Soil water vapor adsorption may be detectable as downwardly directed (i.e., negative) EC latent heat (λE) flux measurements under dry conditions, but a systematic assessment of the use of negative λE fluxes from EC flux stations to characterize adsorption is missing. We propose a classification method to characterize soil water vapor adsorption, excluding conditions of dew and fog when λE derived from EC is not trustworthy due to stable atmospheric conditions. We compare downwardly directed λE fluxes from EC with measurements from weighing lysimeters for 4 years in a Mediterranean savanna ecosystem and 3 years in a temperate agricultural site. Our aim is to assess if overnight water inputs from soil water vapor adsorption differ between ecosystems and how well they are detectable by EC. At the Mediterranean site, the lysimeters measured soil water vapor adsorption each summer, whereas at the temperate site, soil water vapor adsorption was much rarer and was measured predominantly under an extreme drought event in 2018. During 30 % of nights in the 4-year measurement period at the Mediterranean site, the EC technique detected downwardly directed λE fluxes of which 88.8 % were confirmed to be soil water vapor adsorption by at least one lysimeter. At the temperate site, downwardly directed λE fluxes were only recorded during 15 % of the nights, with only 36.8 % of half hours matching simultaneous lysimeter measurement of soil water vapor adsorption. This relationship slightly improved to 61 % under bare-soil conditions and extreme droughts. This underlines that soil water vapor adsorption is likely a much more relevant process in arid ecosystems compared to temperate ones and that the EC method was able to capture this difference. The comparisons of the amounts of soil water vapor adsorption between the two methods revealed a substantial underestimation of the EC compared to the lysimeters. This underestimation was, however, comparable with the underestimation in evaporation by the eddy covariance and improved in conditions of higher turbulence. Based on a random-forest-based feature selection, we found the mismatch between the methods being dominantly related to the site's inherent variability in soil conditions, namely soil water status, and soil (surface) temperature. We further demonstrate that although the water flux is very small with mean values of 0.04 or 0.06 mm per night for EC or lysimeter, respectively, it can be a substantial fraction of the diel soil water balance under dry conditions. Although the two instruments substantially differ with regard to the measured ratio of adsorption to evaporation over 24 h with 64 % and 25 % for the lysimeter and EC methods, they are in either case substantial. Given the usefulness of EC for detecting soil water vapor adsorption as demonstrated here, there is potential for investigating adsorption in more climate regions thanks to the greater abundance of EC measurements compared to lysimeter observations.

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.

The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation–environmental response function (NS–ERF) approach to observing system simulation experiments that aids surface–atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS–ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72 h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2 h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS–ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS–ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases.

In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism.

The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases, and energy. Nonlinear feedback and scale-dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local-area weather prediction. This study examines the ability of the hydrologically enhanced version of the Weather Research and Forecasting model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assesses the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identically calibrated parameter settings for the land surface model (Noah-Multiparametrization; Noah-MP). The simulations are evaluated based on extensive observations at the Terrestrial Environmental Observatories (TERENO) Pre-Alpine Observatory for the Ammer (600 km2) and Rott (55 km2) river catchments in southern Germany, covering a 5-month period (June–October 2016). The sensitivity of seven land surface parameters is tested using the Latin-Hypercube–One-factor-At-a-Time (LH-OAT) method, and six sensitive parameters are subsequently optimized for six different subcatchments, using the model-independent Parameter Estimation and Uncertainty Analysis software (PEST). The calibration of the offline WRF-Hydro gives Nash–Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of the classic WRF and fully coupled WRF-Hydro models, both using the calibrated parameters from the offline model, shows only tiny alterations for radiation and precipitation but considerable changes for moisture and heat fluxes. By comparison with TERENO Pre-Alpine Observatory measurements, the fully coupled model slightly outperforms the classic WRF model with respect to evapotranspiration, sensible and ground heat flux, the near-surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation, whereas soil moisture and precipitation change randomly.

In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.

Accurate measurements of turbulence statistics in the atmosphere are important for eddy-covariance measurements, wind energy research, and the validation of atmospheric numerical models. Sonic anemometers are widely used for these applications. However, these instruments are prone to probe-induced flow distortion effects, and the magnitude of the resulting errors has been debated due to the lack of an absolute reference instrument under field conditions. Here, we present the results of an intercomparison experiment between a CSAT3B sonic anemometer and a high-resolution bistatic Doppler lidar, which is inherently free of any flow distortion. This novel remote sensing instrument has otherwise very similar spatial and temporal sampling characteristics to the sonic anemometer and hence served as a reference for this comparison. The presented measurements were carried out over flat homogeneous terrain at a measurement height of 30 m. We provide a comparative statistical analysis of the resulting mean wind velocities, the standard deviations of the vertical wind speed and the friction velocity and investigate the reasons for the observed deviations based on the turbulence spectra and co-spectra. Our results show an agreement of the mean wind velocity measurements and the standard deviations of the vertical wind speed with a comparability of 0.082 and 0.020 m s−1, respectively. Biases for these two quantities were 0.003 and 0.012 m s−1, respectively. Slightly larger differences were observed for friction velocity. Analysis of the corresponding co-spectra showed that the CSAT3B underestimates this quantity systematically by about 3 % on average as a result of co-spectral losses in the frequency range between 0.1 and 5 s−1. We also found that an angle-of-attack-dependent transducer-shadowing correction does not improve the agreement between the CSAT3B and the Physikalisch-Technische Bundesanstalt (PTB) lidar effectively.

Rising temperatures and changes in snow cover, as can be expected under a warmer global climate, may have large impacts on mountain grassland productivity limited by cold and long winters. Here, we combined two existing models, the multi-layer atmosphere-SOiL-VEGetation model (SOLVEG) and the BASic GRAssland model (BASGRA), which accounts for snow, freeze–thaw events, grass growth, and soil carbon balance. The model was applied to simulate the responses of managed grasslands to anomalously warm winter conditions. The grass growth module considered key ecological processes under a cold environment, such as leaf formation, elongation and death, tillering, carbon allocation, and cold acclimation, in terms of photosynthetic activity. Input parameters were derived for two pre-Alpine grassland sites in Germany, for which the model was run using 3 years of data that included a winter with an exceptionally small amount of snow. The model reproduced the temporal variability of observed daily mean heat fluxes, soil temperatures, and snow depth throughout the study period. High physiological activity levels during the extremely warm winter led to a simulated CO2 uptake of 100 gC m−2, which was mainly allocated into the belowground biomass and only to a minor extent used for additional plant growth during early spring. If these temporary dynamics are representative of long-term changes, this process, which is so far largely unaccounted for in scenario analysis using global terrestrial biosphere models, may lead to carbon accumulation in the soil and/or carbon loss from the soil as a response to global warming.

Evaporation (E) and transpiration (T) respond differently to ongoing changes in climate, atmospheric composition, and land use. It is difficult to partition ecosystem-scale evapotranspiration (ET) measurements into E and T, which makes it difficult to validate satellite data and land surface models. Here, we review current progress in partitioning E and T and provide a prospectus for how to improve theory and observations going forward. Recent advancements in analytical techniques create new opportunities for partitioning E and T at the ecosystem scale, but their assumptions have yet to be fully tested. For example, many approaches to partition E and T rely on the notion that plant canopy conductance and ecosystem water use efficiency exhibit optimal responses to atmospheric vapor pressure deficit (D). We use observations from 240 eddy covariance flux towers to demonstrate that optimal ecosystem response to D is a reasonable assumption, in agreement with recent studies, but more analysis is necessary to determine the conditions for which this assumption holds. Another critical assumption for many partitioning approaches is that ET can be approximated as T during ideal transpiring conditions, which has been challenged by observational studies. We demonstrate that T can exceed 95 % of ET from certain ecosystems, but other ecosystems do not appear to reach this value, which suggests that this assumption is ecosystem-dependent with implications for partitioning. It is important to further improve approaches for partitioning E and T, yet few multi-method comparisons have been undertaken to date. Advances in our understanding of carbon–water coupling at the stomatal, leaf, and canopy level open new perspectives on how to quantify T via its strong coupling with photosynthesis. Photosynthesis can be constrained at the ecosystem and global scales with emerging data sources including solar-induced fluorescence, carbonyl sulfide flux measurements, thermography, and more. Such comparisons would improve our mechanistic understanding of ecosystem water fluxes and provide the observations necessary to validate remote sensing algorithms and land surface models to understand the changing global water cycle.

Large-eddy simulation (LES) has become a well-established tool in the atmospheric boundary layer research community to study turbulence. It allows three-dimensional realizations of the turbulent fields, which large-scale models and most experimental studies cannot yield. To resolve the largest eddies in the mixed layer, a moderate grid resolution in the range of 10 to 100 m is often sufficient, and these simulations can be run on a computing cluster with a few hundred processors or even on a workstation for simple configurations. The desired resolution is usually limited by the computational resources. However, to compare with tower measurements of turbulence and exchange fluxes in the surface layer, a much higher resolution is required. In spite of the growth in computational power, a high-resolution LES of the surface layer is often not feasible: to fully resolve the energy-containing eddies near the surface, a grid spacing of O(1 m) is required. One way to tackle this problem is to employ a vertical grid nesting technique, in which the surface is simulated at the necessary fine grid resolution, and it is coupled with a standard, coarse, LES that resolves the turbulence in the whole boundary layer. We modified the LES model PALM (Parallelized Large-eddy simulation Model) and implemented a two-way nesting technique, with coupling in both directions between the coarse and the fine grid. The coupling algorithm has to ensure correct boundary conditions for the fine grid. Our nesting algorithm is realized by modifying the standard third-order Runge–Kutta time stepping to allow communication of data between the two grids. The two grids are concurrently advanced in time while ensuring that the sum of resolved and sub-grid-scale kinetic energy is conserved. We design a validation test and show that the temporally averaged profiles from the fine grid agree well compared to the reference simulation with high resolution in the entire domain. The overall performance and scalability of the nesting algorithm is found to be satisfactory. Our nesting results in more than 80 % savings in computational power for 5 times higher resolution in each direction in the surface layer.

For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

The role of secondary circulations has recently been studied in the context of well-defined surface heterogeneity in a semiarid ecosystem where it was found that energy balance closure over a desert–forest system and the structure of the boundary layer was impacted by advection and flux divergence. As a part of the CliFF (Climate feedbacks and benefits of semi-arid forests, a collaboration between KIT, Germany, and the Weizmann Institute, Israel) campaign, we studied the boundary layer dynamics and turbulent transport of energy corresponding to this effect in Yatir Forest situated in the Negev Desert in Israel. The forest surrounded by small shrubs presents a distinct feature of surface heterogeneity, allowing us to study the differences between their interactions with the atmosphere above by conducting measurements with two eddy covariance (EC) stations and two Doppler lidars. As expected, the turbulence intensity and vertical fluxes of momentum and sensible heat are found to be higher above the forest compared to the shrubland. Turbulent statistics indicative of nonlocal motions are also found to differ over the forest and shrubland and also display a strong diurnal cycle. The production of turbulent kinetic energy (TKE) over the forest is strongly mechanical, while buoyancy effects generate most of the TKE over the shrubland. Overall TKE production is much higher above the forest compared to the shrubland. The forest is also found to be more efficient in dissipating TKE. The TKE budget appears to be balanced on average both for the forest and shrubland, although the imbalance of the TKE budget, which includes the role of TKE transport, is found to be quite different in terms of diurnal cycles for the forest and shrubland. The difference in turbulent quantities and the relationships between the components of TKE budget are used to infer the characteristics of the turbulent transport of energy between the desert and the forest.

The imbalance of the surface energy budget in eddy-covariance measurements is still an unsolved problem. A possible cause is the presence of land surface heterogeneity, which affects the boundary-layer turbulence. To investigate the impact of surface variables on the partitioning of the energy budget of flux measurements in the surface layer under convective conditions, we set up a systematic parameter study by means of large-eddy simulation. For the study we use a virtual control volume approach, which allows the determination of advection by the mean flow, flux-divergence and storage terms of the energy budget at the virtual measurement site, in addition to the standard turbulent flux. We focus on the heterogeneity of the surface fluxes and keep the topography flat. The surface fluxes vary locally in intensity and these patches have different length scales. Intensity and length scales can vary for the two horizontal dimensions but follow an idealized chessboard pattern. Our main focus lies on surface heterogeneity of the kilometer scale, and one order of magnitude smaller. For these two length scales, we investigate the average response of the fluxes at a number of virtual towers, when varying the heterogeneity length within the length scale and when varying the contrast between the different patches. For each simulation, virtual measurement towers were positioned at functionally different positions (e.g., downdraft region, updraft region, at border between domains, etc.). As the storage term is always small, the non-closure is given by the sum of the advection by the mean flow and the flux-divergence. Remarkably, the missing flux can be described by either the advection by the mean flow or the flux-divergence separately, because the latter two have a high correlation with each other. For kilometer scale heterogeneity, we notice a clear dependence of the updrafts and downdrafts on the surface heterogeneity and likewise we also see a dependence of the energy partitioning on the tower location. For the hectometer scale, we do not notice such a clear dependence. Finally, we seek correlators for the energy balance ratio in the simulations. The correlation with the friction velocity is less pronounced than previously found, but this is likely due to our concentration on effectively strongly to freely convective conditions.

Three-dimensional sonic anemometers are the core component of eddy covariance systems, which are widely used for micrometeorological and ecological research. In order to characterize the measurement uncertainty of these instruments we present and analyse the results from a field intercomparison experiment of six commonly used sonic anemometer models from four major manufacturers. These models include Campbell CSAT3, Gill HS-50 and R3, METEK uSonic-3 Omni, R. M. Young 81000 and 81000RE. The experiment was conducted over a meadow at the TERENO/ICOS site DE-Fen in southern Germany over a period of 16 days in June of 2016 as part of the ScaleX campaign. The measurement height was 3 m for all sensors, which were separated by 9 m from each other, each on its own tripod, in order to limit contamination of the turbulence measurements by adjacent structures as much as possible. Moreover, the high-frequency data from all instruments were treated with the same post-processing algorithm. In this study, we compare the results for various turbulence statistics, which include mean horizontal wind speed, standard deviations of vertical wind velocity and sonic temperature, friction velocity, and the buoyancy flux. Quantitative measures of uncertainty, such as bias and comparability, are derived from these results. We find that biases are generally very small for all sensors and all computed variables, except for the sonic temperature measurements of the two Gill sonic anemometers (HS and R3), confirming a known transducer-temperature dependence of the sonic temperature measurement. The best overall agreement between the different instruments was found for the mean wind speed and the buoyancy flux.

Semi-arid forests are found to sustain a massive sensible heat flux in spite of having a low surface to air temperature difference by lowering the aerodynamic resistance to heat transfer (rH) – a property called the canopy convector effect (CCE). In this work large-eddy simulations are used to demonstrate that the CCE appears more generally in canopy turbulence. It is indeed a generic feature of canopy turbulence: rH of a canopy is found to reduce with increasing unstable stratification, which effectively increases the aerodynamic roughness for the same physical roughness of the canopy. This relation offers a sufficient condition to construct a general description of the CCE. In addition, we review existing parameterizations for rH from the evapotranspiration literature and test to what extent they are able to capture the CCE, thereby exploring the possibility of an improved parameterization.

In the spring of 2013, extensive measurements with multiple Doppler lidar systems were performed. The instruments were arranged in a triangle with edge lengths of about 3 km in a moderately flat, agriculturally used terrain in northwestern Germany. For 6 mostly cloud-free convective days, vertical velocity variance profiles were calculated. Weighted-averaged surface fluxes proved to be more appropriate than data from individual sites for scaling the variance profiles; but even then, the scatter of profiles was mostly larger than the statistical error. The scatter could not be explained by mean wind speed or stability, whereas time periods with significantly increased variance contained broader thermals. Periods with an elevated maximum of the variance profiles could also be related to broad thermals. Moreover, statistically significant spatial differences of variance were found. They were not influenced by the existing surface heterogeneity. Instead, thermals were preserved between two sites when the travel time was shorter than the large-eddy turnover time. At the same time, no thermals passed for more than 2 h at a third site that was located perpendicular to the mean wind direction in relation to the first two sites. Organized structures of turbulence with subsidence prevailing in the surroundings of thermals can thus partly explain significant spatial variance differences existing for several hours. Therefore, the representativeness of individual variance profiles derived from measurements at a single site cannot be assumed.

Watersheds with rich hydrometeorological equipment are still very limited in West Africa but are essential for an improved analysis of environmental changes and their impacts in this region. This study gives an overview of a novel hydrometeorological observatory that was established for two mesoscale watersheds in the Sudan Savanna of Southern Burkina Faso and Northern Ghana as part of the West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) program. The study area is characterized by severe land cover changes due to a strongly increasing demand of agricultural land. The observatory is designed for long-term measurements of >30 hydrometeorological variables in subhourly resolution and further variables such as CO. This information is complemented by long-term daily measurements from national meteorological and hydrological networks, among several other datasets recently established for this region. A unique component of the observatory is a micrometeorological field experiment using eddy covariance stations implemented at three contrasting sites (near-natural, cropland, and degraded grassland) to assess the impact of land cover changes on water, energy, and CO fluxes. The datasets of the observatory are needed by many modeling and field studies conducted in this region and are made available via the WASCAL database. Moreover, the observatory forms an excellent platform for future investigations and can be used as observational foundation for environmental observatories for an improved assessment of environmental changes and their socioeconomic impacts for the savanna regions of West Africa.

Global change has triggered several transformations, such as alterations in climate, land productivity, water resources, and atmospheric chemistry, with far reaching impacts on ecosystem functions and services. Finding solutions to climate and land cover change-driven impacts on our terrestrial environment is one of the most important scientific challenges of the 21st century, with far-reaching interlinkages to the socio-economy. The setup of the German Terrestrial Environmental Observatories (TERENO) Pre-Alpine Observatory was motivated by the fact that mountain areas, such as the pre-alpine region in southern Germany, have been exposed to more intense warming compared with the global average trend and to higher frequencies of extreme hydrological events, such as droughts and intense rainfall. Scientific research questions in the TERENO Pre-Alpine Observatory focus on improved process understanding and closing of combined energy, water, C, and N cycles at site to regional scales. The main long-term objectives of the TERENO Pre-Alpine Observatory include the characterization and quantification of climate change and land cover–management effects on terrestrial hydrology and biogeochemical processes at site and regional scales by joint measuring and modeling approaches. Here we present a detailed climatic and biogeophysical characterization of the TERENO Pre-Alpine Observatory and a summary of novel scientific findings from observations and projects. Finally, we reflect on future directions of climate impact research in this particularly vulnerable region of Germany.

A comparison of two popular eddy-covariance software packages is presented, namely, EddyPro and TK3. Two approximately 1-month long test data sets were processed, representing typical instrumental setups (i.e., CSAT3/LI-7500 above grassland and Solent R3/LI-6262 above a forest). The resulting fluxes and quality flags were compared. Achieving a satisfying agreement and understanding residual discrepancies required several iterations and interventions of different nature, spanning from simple software reconfiguration to actual code manipulations. In this paper, we document our comparison exercise and show that the two software packages can provide utterly satisfying agreement when properly configured. Our main aim, however, is to stress the complexity of performing a rigorous comparison of eddy-covariance software. We show that discriminating actual discrepancies in the results from inconsistencies in the software configuration requires deep knowledge of both software packages and of the eddy-covariance method. In some instances, it may be even beyond the possibility of the investigator who does not have access to and full knowledge of the source code. Being the developers of EddyPro and TK3, we could discuss the comparison at all levels of details and this proved necessary to achieve a full understanding. As a result, we suggest that researchers are more likely to get comparable results when using EddyPro (v5.1.1) and TK3 (v3.11) – at least with the setting presented in this paper – than they are when using any other pair of EC software which did not undergo a similar cross-validation. As a further consequence, we also suggest that, to the aim of assuring consistency and comparability of centralized flux databases, and for a confident use of eddy fluxes in synthesis studies on the regional, continental and global scale, researchers only rely on software that have been extensively validated in documented intercomparisons.

The goal of this study is to characterize the sensible (H) and latent (LE) heat exchange for different land covers in the heterogeneous steppe landscape of the Xilin River catchment, Inner Mongolia, China. Eddy-covariance flux measurements at 50–100 m above ground were conducted in July 2009 using a weight-shift microlight aircraft. Wavelet decomposition of the turbulence data enables a spatial discretization of 90 m of the flux measurements. For a total of 8446 flux observations during 12 flights, MODIS land surface temperature (LST) and enhanced vegetation index (EVI) in each flux footprint are determined. Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River catchment (&approx;3670 km2) are accurate to ≤18% (1 σ). The predictions are then summarized for each land cover type, providing individual estimates of source strength (36 W m−2 < H < 364 W m−2, 46 W m−2 < LE < 425 W m−2) and spatial variability (11 W m−2 < σH < 169 W m−2, 14 W m−2 < σLE < 152 W m−2) to a precision of ≤5%. Lastly, ERF predictions of land cover specific Bowen ratios are compared between subsequent flights at different locations in the Xilin River catchment. Agreement of the land cover specific Bowen ratios to within 12 &pm; 9% emphasizes the robustness of the presented approach. This study indicates the potential of ERFs for (i) extending airborne flux measurements to the catchment scale, (ii) assessing the spatial representativeness of long-term tower flux measurements, and (iii) designing, constraining and evaluating flux algorithms for remote sensing and numerical modelling applications.

The objective of this study is to assess the feasibility and quality of eddy-covariance flux measurements from a weight-shift microlight aircraft (WSMA). Firstly, we investigate the precision of the wind measurement (σu,v ≤ 0.09 m s−1, σw = 0.04 m s−1), the lynchpin of flux calculations from aircraft. From here, the smallest resolvable changes in friction velocity (0.02 m s−1), and sensible- (5 W m−2) and latent (3 W m−2) heat flux are estimated. Secondly, a seven-day flight campaign was performed near Lindenberg (Germany). Here we compare measurements of wind, temperature, humidity and respective fluxes between a tall tower and the WSMA. The maximum likelihood functional relationship (MLFR) between tower and WSMA measurements considers the random error in the data, and shows very good agreement of the scalar averages. The MLFRs for standard deviations (SDs, 2–34%) and fluxes (17–21%) indicate higher estimates of the airborne measurements compared to the tower. Considering the 99.5% confidence intervals, the observed differences are not significant, with exception of the temperature SD. The comparison with a large-aperture scintillometer reveals lower sensible heat flux estimates at both tower (−40 to −25%) and WSMA (−25–0%). We relate the observed differences to (i) inconsistencies in the temperature and wind measurement at the tower and (ii) the measurement platforms' differing abilities to capture contributions from non-propagating eddies. These findings encourage the use of WSMA as a low cost and highly versatile flux measurement platform.

As part of the quality assurance and quality control activities within the CarboEurope-IP network, a comparison of eddy-covariance software was conducted. For four five-day datasets, CO2 flux estimates were calculated by seven commonly used software packages to assess the uncertainty of CO2 flux estimates due to differences in post-processing. The datasets originated from different sites representing different commonly applied instrumentation and different canopy structures to cover a wide range of realistic conditions. Data preparation, coordinate rotation and the implementation of the correction for high frequency spectral losses were identified as crucial processing steps leading to significant discrepancies in the CO2 flux results. The overall comparison indicated a good although not yet perfect agreement among the different software within 5–10% difference for 30-min CO2 flux values. Conceptually different ideas about the selection and application of processing steps were a main reason for the differences in the CO2 flux estimates observed. A balance should be aspired between scientific freedom on the one hand, in order to advance methodical issues, and standardisation of procedures on the other hand, in order to obtain comparable fluxes for multi-site synthesis studies.

We applied a site evaluation approach combining Lagrangian Stochastic footprint modeling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types.

After briefly discussing several reasons for the energy balance closure problem in the surface layer, the paper focuses on the influence of the low frequency part of the turbulence spectrum on the residual. Changes in the turbulent fluxes in this part of the turbulence spectrum were found to have a significant influence on the changes of the residual. Using the ogive method, it was found that the eddy-covariance method underestimates turbulent fluxes in the case of ogives converging for measuring times longer than the typical averaging interval of 30 min. Additionally, the eddy-covariance method underestimates turbulent fluxes for maximal ogive functions within the averaging interval, both mainly due to advection and non-steady state conditions. This has a considerable influence on the use of the eddy-covariance method.

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.