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Over the last 30 years, dozens of networks of eddy covariance flux stations have been introduced in different countries and continents around the world. Many of them, such as the ICOS network in Europe or the AmeriFlux network in the US, have a specific focus on greenhouse gas measurement focus, mainly CO2, but in all cases, the latent heat flux is concurrently measured as a required variable, thus actual evapotranspiration can be derived.This important hydrologic parameter is needed both in rainfed and irrigated areas to monitor drought conditions, and soil water balance as well as to determine irrigation water amounts to be applied to crops and the timing of optimal fertilizer applications. Quasi-real-time measurements of actual evapotranspiration can be used by water managers, crop consultants, and producers in both rainfed and irrigated agriculture, reducing water and energy use and associated expenses, ultimately helping increase the efficiency of global food production while reducing its costs. So, the importance of providing freely available, scientific-grade data is imperative.The cutting-edge technologies to assess water use on leaf-level to ecosystem-level scales has been actively developed in academia for past 40 years. One example of such technologies is a next-generation fully-automated evapotranspiration station network, to effectively and efficiently handle the “big data” on water use coming from a grid of measurement stations providing high spatial and temporal coverage of water usage on multiple scales, ranging from a single watershed to a region, state, or a continent.This presentation aims to provide multiple examples, and validations against existing standards, of the latest technology, hardware, and scientific method behind the eddy covariance approach to direct, field-scale, unattended, and automated measurements of evapotranspiration.

Growing food demand and declining water availability are among key global concerns in the modern society. These two opposing trends manifest uniquely at different scales, from the farm field to the global food distribution, and require innovative composite solutions in terms of policy, education, science and technology.To solve the complex interactions of financial, social, and scientific issues, solutions to water use for crops require resource management based upon socioeconomic and scientific understanding. These important goals are achieved through a number of crucial regulatory, social and technical means. The latter include water inventories, water loss and water use measurements, as well as development of the techniques for water use reduction, optimization and prediction, and require direct measurements of water transport in real time, with high temporal resolution.Cutting-edge technologies to assess water use at leaf to ecosystem scales have been actively developed in the academia for the past 40 years. One example of such technologies is a next-generation fully-automated evapotranspiration station network, to effectively and efficiently handle the “big data” on water use coming from a grid of measurement stations providing high spatial and temporal coverage of water usage on multiple scales, ranging from a single watershed to a region, state, or a continent.In this presentation, we will focus on the main features and specifications of the very latest technology and the explanation of the latest scientific assessment methods available for direct, field-scale, unattended, and automated measurements of evapotranspiration.

An analysis based on the law of linear momentum conservation demonstrates unequivocally that the mass fraction is the scalar whose gradient determines gas diffusion, both molecular and turbulent. It illustrates sizeable errors in previous micrometeorological definitions of the turbulent gas flux based on fluctuations in other scalars such as the mixing ratio or density. In deference to conservation law, we put forth a new definition for the turbulent gas flux. Net gas transport is then defined as the sum of this turbulent flux with systematic transport by the mean flow. This latter, non-diffusive flux is due to the net upward boundary-layer momentum, a Stefan flow forced by evaporation, which is the dominant surface gas exchange. A comparison with the traditional methodology shows exact agreement between the two methods regarding the net flux, but with the novelty of partitioning gas transport according to distinct physical mechanisms. The non-diffusive flux is seen to be non-negligible in general, and to dominate turbulent transport under certain conditions, with broad implications for boundary-layer meteorology., Spanish Ministry of Economy project ELEMENTAL CGL2017-83538-C3-1-R, Andalusian government P18-RT-3629, European Commission

The Tibetan alpine steppe ecosystem covers an area of roughly 800 000 km 2 and contains up to 3.3 % soil organic carbon in the uppermost 30 cm, summing up to 1.93 Pg C for the Tibet Autonomous Region only (472 037 km 2 ). With temperatures rising 2 to 3 times faster than the global average, these carbon stocks are at risk of loss due to enhanced soil respiration. The remote location and the harsh environmental conditions on the Tibetan Plateau (TP) make it challenging to derive accurate data on the ecosystem–atmosphere exchange of carbon dioxide (CO 2 ) and water vapor ( H2O ). Here, we provide the first multiyear data set of CO 2 and H2O fluxes from the central Tibetan alpine steppe ecosystem, measured in situ using the eddy covariance technique. The calculated fluxes were rigorously quality checked and carefully corrected for a drift in concentration measurements. The gas analyzer self-heating effect during cold conditions was evaluated using the standard correction procedure and newly revised formulations ( Burba et al. , 2008 ; Frank and Massman , 2020 ) . A wind field analysis was conducted to identify influences of adjacent buildings on the turbulence regime and to exclude the disturbed fluxes from subsequent computations. The presented CO 2 fluxes were additionally gap filled using a standardized approach. The very low net carbon uptake across the 15-year data set highlights the special vulnerability of the Tibetan alpine steppe ecosystem to become a source of CO 2 due to global warming. The data are freely available at https://doi.org/10.5281/zenodo.3733202 ( Nieberding et al. , 2020 a ) and https://doi.org/10.11888/Meteoro.tpdc.270333 ( Nieberding et al. , 2020 b ) and may help us to better understand the role of the Tibetan alpine steppe in the global carbon–climate feedback.

The Tibetan alpine steppe ecosystem covers an area of roughly 800,000 km2, containing up to 3.3 % soil organic carbon in the uppermost 30 cm, summing up to 1.93 PgvC for the Tibet Autonomous Region only (472,037 km2). With temperatures rising two to three times faster than the global average, these carbon stocks are at risk of loss due to enhanced soil respiration. The remote location and the harsh environmental conditions on the Tibetan Plateau (TP) make it challenging to derive accurate data on ecosystem-atmosphere exchange of carbon dioxide (CO2) and water vapor (H2O). Here, we provide the first multi-year data set of CO2 and H2O fluxes from the central Tibetan alpine steppe ecosystem, measured in situ using the eddy covariance technique. The calculated fluxes were rigorously quality checked and carefully corrected for a drift in concentration measurements and gas analyzer self heating during cold conditions. A wind field analysis was conducted to identify influences of adjacent buildings on the turbulence regime and to exclude the disturbed fluxes from subsequent computations. The presented CO2 fluxes were additionally gap filled using a standardized approach. The very low net carbon uptake across the 15-year data set highlights the special vulnerability of the Tibetan alpine steppe ecosystem to become a source of CO2 due to global warming. The data is freely available (https://www.doi.org/10.5281/zenodo.3733203, Nieberding et al., 2020b) and may help to better understand the role of the Tibetan alpine steppe in the global carbon-climate feedback.

Arithmetic averaging procedures are traditionally used in many applications in the field of micrometeorology, but these neglect Osborne Reynolds's specification of turbulence, and thus, strictly speaking, violate the momentum conservation law. Recently, it has been shown that applying linear momentum conservation to surface exchanges defines an average motion in the surface-normal direction (i.e., a Stefan flow), and thereby describes a non-diffusive transport that is distinct from turbulent transport. Here we examine data from a nearly ideal micrometeorological field site (extensive, flat, and mono specific-reed wetland) to show that traditional flux-tower calculations, including but not limited to the Webb corrections, generally provide an inadequate approximation of turbulent fluxes and yet still adequately characterize the net fluxes in most traditional cases. The importance of such conflation of diffusive and non-diffusive transport is greatest for situations with relatively large non-diffusive fluxes, as occurs during particular times of day in general and particularly when considering fluxes in the stream-wise direction. An examination of fluxes calculated using the traditional arithmetic averaging procedure, versus the proposed, more theoretically appropriate calculations that fully obey conservation law, illustrates important implications for the characterization of gas-exchange processes and more generally the discipline of micrometeorology. These implications may become particularly critical in near future as gas flux measurements enter an era of automated operation on massive network scales, including automated gas flux calculations. At the same time, such measurements strive to adequately represent gas exchange of newer species with extremely low fluxes (vs traditionally measured larger fluxes of H2O and CO2). Multiple assumptions, and neglected terms and processes historically deployed for evaluating larger fluxes, may no longer work well when much smaller fluxes are considered, especially when measured by a non-expert using a fully automated flux station. These no-longer-negligible aspects include fundamentals of adequately handling the diffusive and non-diffusive transport mechanisms addressed in this presentation.

Data from thousands of past and present eddy covariance flux stations are available across the globe, while multiple hundreds actively operating as individual process-level studies, small flux networks dedicated to specific research goals, and larger national and continental networks with broad ecological and environmental foci.Many flux stations have weather and soil data to help clean, analyze and interpret the fluxes but most do not have optical proximal sensors, do not allow straightforward coupling with remote sensing (drone, aircraft, satellite, etc.) data, and cannot easily be used for validation of remotely sensed products, ecosystem modeling, or upscaling from field to regional levels. The flux source areas themselves (e.g., flux footprints) are typically not defined in the flux datasets, and the time stamps of the fluxes come in a large number of outdated non-trackable formats. Finally, the past ways of the flux data quality control, analysis and interpretation require a participation of micrometeorological expert (or an entire network) with their own custom codes or exceptional skills in using existing software such as MatLab or VB Tools in Excel. These are the key issues effectively preventing a larger environmental research community and remote sensing community from fully utilizing eddy covariance flux data.In 2016-2020, a set of new tools to collect, process, analyze, time- and space- allocate and share time-synchronized flux data from multiple flux stations were developed and deployed globally. These new tools can be effective in solving most or all of the key issues listed above. The fully automated FluxSuite system combines hardware, software and web services, and does not require an expert to run it. It can be incorporated into a new flux station or added to a present station, using a weatherized remotely-accessible microcomputer, SmartFlux3 which utilizes EddyPro software to calculate fully-processed fluxes in near-real-time, alongside biomet data and flux footprints. All data are merged into a single quality-controlled file timed using PTP time protocol. Remote sensing researchers and modelers without actual physical stations can form “virtual networks” of actual stations by collaborating with tower PIs from different physical networks and flux databases.The very latest development in this overall approach is the flux data analysis software, Tovi, designed to seamlessly ingest the data from the flux stations and to allow a non-micrometeorologist to quality control, analyze and interpret the flux data. It allows rapid execution of the QC/QA and data analysis steps which have been time-consuming and complicated in the past, and other data analysis steps virtually not doable in the past, all using interactive and intuitive GUI, including advanced footprint calculations and flux apportioning necessary for remote sensing community; NEE flux partitioning; automated generation specific lists of references for each workflow; etc.This presentation will show how combinations of these new tools are used by major networks, and describe how this approach can be utilized for matching remote sensing and tower data for ground truthing, improve scientific interactions, and promote a better utilization of the eddy covariance flux data by a wider environmental research community.

When using open path infrared gas analyzers (IRGA), lens contamination, calibration inaccuracies and ageing internal chemicals may lead to a slow drift in gas concentration measurements. During flux calculations, these errors are usually not accounted for under the assumption, that a slow drift in mean gas concentrations (i.e. over several weeks to months) does not affect the estimation of turbulent fluctuations and, hence, of covariances. This is however not the case. In fact, Serrano-Ortiz et al. (2008) estimated that an underestimation of the CO2 concentration will propagate into an overestimation of the carbon uptake via the WPL correction. In addition, for instruments – such as the widely used LI-7500 – where a nonlinear calibration curve relates raw absorptance measurements to gas concentration, Fratini et al. (2014) have shown that errors in mean concentrations leak into errors in fluxes on account of amplified or dampened estimated fluctuations. Both these effects can be eliminated, possibly completely, when the drift in gas concentration is corrected before raw data processing. Therefore, the offset between measured and reference (i.e. "real") gas concentrations has to be quantified and converted into the corresponding zero absorption biases. We performed the drift correction on a 15 years dataset from the Tibetan Plateau, where an extreme drift in concentration measurements occurred. Due to the remote location, user calibrations were performed irregularly, and no independent gas concentration measurements are available. Hence, we used the CO2 concentration measurements from the Mauna Loa atmospheric observatory (NOAA ESRL Global Monitoring Division, 2018, updated annually) as reference gas concentration to derive an offset for every half hour measurement. The offset in H­­2O mixing ratios could be determined from auxiliary low frequency measurements of relative humidity, temperature and air pressure. We then converted mixing ratios to raw absorptances using the instrument-specific calibration curve to apply an absorptance offset to every 10 Hz measurement, thus eliminating the long-term drift in both mean values and fluctuations of gas concentrations. The corrected raw data time series were then used for calculation of fluxes and subsequent corrections, including de-spiking, axis rotation, detrending and correction for spectral attenuations and air density fluctuations. In comparison to the uncorrected fluxes, the corrected fluxes yielded a considerably lower carbon uptake during daytime and summer, which is in compliance with instrument theory of operation and the results from numerical simulations and field data analysis as conducted by Fratini et al. (2014). Fratini, G., McDermitt, D.K. & Papale, D. (2014) Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction. Biogeosciences, 11, 1037–1051.NOAA ESRL Global Monitoring Division (2018, updated annually) Atmospheric Carbon Dioxide Dry Air Mole Fractions from quasi-continuous measurements at Mauna Loa, Hawaii, Barrow, Alaska, American Samoa and South Pole. Compiled by K.W. Thoning, D.R. Kitzis, and A. Crotwell., 2019th edn. NOAA ESRL GMD CCGG Group, Boulder, Colorado, USA.Serrano-Ortiz, P., Kowalski, A.S., Domingo, F., Ruiz, B. & Alados-Arboledas, L. (2008) Consequences of Uncertainties in CO2 Density for Estimating Net Ecosystem CO2 Exchange by Open-path Eddy Covariance. Boundary-Layer Meteorology, 126, 209–218.

In order to assure the quality of operational satellite products, there is a strong demand for timely available in-situ flux data. Typically, the Earth Observation Community has to rely on publicly available data processed and distributed by flux networks such as the European Fluxes Database Cluster, AmeriFlux Network, and other major networks globally.While the centralized processing systems employed by the major networks provide exceptional advantages for long-term data quality, reproducibility and comparability, to date these result in 1-5 year delays between the time of the actual in-situ flux measurement and the publicly online availability of processed and quality controlled data, especially for derived parameters such as Gross Primary Production (GPP) often used by Earth Observation experts. Such delays hamper the use of in-situ fluxes for timely (and ultimately near-real-time) operational satellite product monitoring, envisioned and often required by the Earth Observation Community.Within the European Copernicus Global Land Service (CGLOPS), a validation protocol is in place for each publicly available satellite product. One of the elements is the yearly Scientific Quality Evaluation (SQE), where data of the most recent calendar year are quality checked within the three months after the end of the year. This implies that in-situ data should be available within this timespan in order to be included in the operational quality monitoring. Recently, a set of new tools to collect, process, analyze, partition, time- and space- allocate and share time-synchronized flux data from multiple flux stations were developed and deployed globally. These new tools can be effective in solving the time delay issues listed above without sacrificing quality, reproducibility and comparability of the in-situ flux data.The fully automated remotely-accessible microcomputer, SmartFlux, utilizes EddyPro software to calculate fully-processed fluxes in near-real-time, alongside supporting data and flux footprints. All data are merged into a single quality-controlled file timed using GPS-driven PTP time protocol to assure a microseconds-scale time synch between the instruments within each station and between different stations.The flux data analysis software, Tovi, can seamlessly ingest the data from the SmartFlux stations to allow a non-micrometeorologist analyze and interpret the flux data. Specifically, it allows rapid execution of the QC/QA and data analysis steps using interactive GUI, including advanced QC and gap fill schemes, footprint calculations and flux apportioning, NEE (Net Ecosystem Exchange) flux partitioning, automated generation of specific lists of references for each workflow, etc. All processing routines and analysis steps are reproducibile and intercomparable to other SmartFlux stations across the globe.Based upon the timely needs for the in-situ flux data and the newly available technical tools, a pilot initiative was set-up to test the viability of using 2019 data generated by multiple SmartFlux stations and Tovi analysis software to quality control, gap fill, and partition NEE into GPP product to support the quality assurance analysis of the global Copernicus Dry Matter Productivity (DMP) product. This presentation will show the actual established workflow, and demonstrate the detailed post-processing of in-situ flux data for timely operational satellite product monitoring.

Modern eddy covariance (EC) systems collect high-frequency data (10–20 Hz) via digital outputs of instruments. This is an important evolution with respect to the traditional and widely used mixed analog/digital systems, as fully digital systems help overcome the traditional limitations of transmission reliability, data quality, and completeness of the datasets.However, fully digital acquisition introduces a new problem for guaranteeing data synchronicity when the clocks of the involved devices themselves cannot be synchronized, which is often the case with instruments providing data via serial or Ethernet connectivity in a streaming mode. In this paper, we suggest that, when assembling EC systems in-house, aspects related to timing issues need to be carefully considered to avoid significant flux biases.By means of a simulation study, we found that, in most cases, random timing errors can safely be neglected, as they do not impact fluxes significantly. At the same time, systematic timing errors potentially arising in asynchronous systems can effectively act as filters leading to significant flux underestimations, as large as 10 %, by means of attenuation of high-frequency flux contributions. We characterized the transfer function of such filters as a function of the error magnitude and found cutoff frequencies as low as 1 Hz, implying that synchronization errors can dominate high-frequency attenuations in open- and enclosed-path EC systems. In most cases, such timing errors neither be detected nor characterized a posteriori. Therefore, it is important to test the ability of traditional and prospective EC data logging systems to assure the required synchronicity and propose a procedure to implement such a test relying on readily available equipment.

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

The eddy covariance is a powerful technique to estimate the surface-atmosphere exchange of different scalars at the ecosystem scale. The EC method is central to the ecosystem component of the Integrated Carbon Observation System, a monitoring network for greenhouse gases across the European Continent. The data processing sequence applied to the collected raw data is complex, and multiple robust options for the different steps are often available. For Integrated Carbon Observation System and similar networks, the standardisation of methods is essential to avoid methodological biases and improve comparability of the results. We introduce here the steps of the processing chain applied to the eddy covariance data of Integrated Carbon Observation System stations for the estimation of final CO2, water and energy fluxes, including the calculation of their uncertainties. The selected methods are discussed against valid alternative options in terms of suitability and respective drawbacks and advantages. The main challenge is to warrant standardised processing for all stations in spite of the large differences in e.g. ecosystem traits and site conditions. The main achievement of the Integrated Carbon Observation System eddy covariance data processing is making CO2 and energy flux results as comparable and reliable as possible, given the current micrometeorological understanding and the generally accepted state-of-the-art processing methods.

Most plot-scale methane emission models – of which many have been developed in the recent past – are validated using data collected with the closed-chamber technique. This method, however, suffers from a low spatial representativeness and a poor temporal resolution. Also, during a chamber-flux measurement the air within a chamber is separated from the ambient atmosphere, which negates the influence of wind on emissions. Additionally, some methane models are validated by upscaling fluxes based on the area-weighted averages of modelled fluxes, and by comparing those to the eddy covariance (EC) flux. This technique is rather inaccurate, as the area of upscaling might be different from the EC tower footprint, therefore introducing significant mismatch. In this study, we present an approach to validate plot-scale methane models with EC observations using the footprint-weighted average method. Our results show that the fluxes obtained by the footprint-weighted average method are of the same magnitude as the EC flux. More importantly, the temporal dynamics of the EC flux on a daily timescale are also captured (r2 = 0.7). In contrast, using the area-weighted average method yielded a low (r2 = 0.14) correlation with the EC measurements. This shows that the footprint-weighted average method is preferable when validating methane emission models with EC fluxes for areas with a heterogeneous and irregular vegetation pattern.

Modern Eddy Covariance (EC) systems collect high-frequency data (10–20 Hz) via instruments’ digital outputs. While this helps overcome the limits of traditional mixed analog/digital systems, it also introduces the new problem of guaranteeing data synchronicity when the clocks of the involved devices cannot themselves be synchronized, which is often the case with instruments providing data via serial or Ethernet connectivity. By means of a simulation study, we found that in most cases random timing errors can safely be neglected, as they do not impact fluxes to a large extent. On the contrary, realistic systematic timing errors potentially arising in asynchronous systems can lead to flux underestimations as large as 10 %, by means of attenuation of high-frequency flux contributions. We characterize the transfer function of such filters as a function of the error amount and find cut-off frequencies as low as 1 Hz, which means that synchronization errors can dominate high-frequency attenuations in open- and enclosed-path EC systems. In most cases, such timing errors cannot be detected nor quantified a posteriori. Therefore, we suggest testing the ability of prospect EC data logging systems to assure required synchronicity and propose a procedure to implement such a test, which relies on readily available equipment.

International Agrophysics, 32 (4), ISSN:0236-8722, ISSN:2300-8725

Simulations of the dust cycle and its interactions with the changing Earth system are hindered by the empirical nature of dust emission parameterizations in weather and climate models. Here we take a step towards improving dust cycle simulations by using a combination of theory and numerical simulations to derive a physically based dust emission parameterization. Our parameterization is straightforward to implement into large-scale models, as it depends only on the wind friction velocity and the soil's threshold friction velocity. Moreover, it accounts for two processes missing from most existing parameterizations: a soil's increased ability to produce dust under saltation bombardment as it becomes more erodible, and the increased scaling of the dust flux with wind speed as a soil becomes less erodible. Our treatment of both these processes is supported by a compilation of quality-controlled vertical dust flux measurements. Furthermore, our scheme reproduces this measurement compilation with substantially less error than the existing dust flux parameterizations we were able to compare against. A critical insight from both our theory and the measurement compilation is that dust fluxes are substantially more sensitive to the soil's threshold friction velocity than most current schemes account for.

Errors in gas concentration measurements by infrared gas analysers can occur during eddy-covariance campaigns, associated with actual or apparent instrumental drifts or to biases due to thermal expansion, dirt contamination, aging of components or errors in field operations. If occurring on long time scales (hours to days), these errors are normally ignored during flux computation, under the assumption that errors in mean gas concentrations do not affect the estimation of turbulent fluctuations and, hence, of covariances. By analysing instrument theory of operation, and using numerical simulations and field data, we show that this is not the case for instruments with curvilinear calibrations; we further show that if not appropriately accounted for, concentration biases can lead to roughly proportional systematic flux errors, where the fractional errors in fluxes are about 30–40% the fractional errors in concentrations. We quantify these errors and characterize their dependency on main determinants. We then propose a correction procedure that largely – potentially completely – eliminates these errors. The correction, to be applied during flux computation, is based on knowledge of instrument calibration curves and on field or laboratory calibration data. Finally, we demonstrate the occurrence of such errors and validate the correction procedure by means of a field experiment, and accordingly provide recommendations for in situ operations. The correction described in this paper will soon be available in the EddyPro software (www.licor.com/eddypro).

The use of micrometeorological (MM) techniques for methane (CH4) and nitrous oxide (N2O) flux measurements in terrestrial ecosystems is increasing and a general outline which summarizes key results is needed. This work provides an overview of the current status of global flux measurements of CH4 and N2O by MM techniques in terrestrial ecosystems. Published studies were grouped into four main terrestrial land cover categories and the reported flux ranges, the consistency of different MM approaches over the same ecosystem types, the variability of the MM technique performances as regards the flux detection limit and environmental conditions, were analysed. Furthermore, the issue of the comparability between MM and soil chambers measurements was evaluated. The existing dataset, although temporally and spatially limited, shows that CH4 and N2O fluxes are extremely variable in both time and space with mean fluxes spanning within interquartile ranges of 1.33 divided by 5.45, 11.02 divided by 68.48, 5.38 divided by 29.28, 13.87.10(3) divided by 47.60.10(3) nmol CH4 m(-2) s(-1) in forest, wetlands, croplands and artificial lands respectively, and of 0.09 divided by 0.42, 0.24 divided by 1.47, 9.13 divided by 20.89 nmol N2O m(-2) s(-1) in forest, croplands and artificial lands (no published works were found for wetlands). When environmental conditions were comparable, a general agreement of flux ranges was found within each ecosystem type, in particular when estimates were based on accurate footprint analysis. Exceptions were mainly related to site-specific aspects or to particular measurement periods. Not all the measurement set-ups were suitable for all ecosystems, environmental conditions, turbulence characteristics and flux intensity, however the latest technological improvements make the detection of fluxes feasible virtually in all ecosystems. MM studies of CH4 and N2O fluxes were unevenly distributed around the globe and, in particular, were lacking in sensitive areas like Africa, South America and Central Asia. (C) 2013 Elsevier Ltd. All rights reserved. The use of micrometeorological (MM) techniques for methane (CH4) and nitrous oxide (N2O) flux measurements in terrestrial ecosystems is increasing and a general outline which summarizes key results is needed. This work provides an overview of the current status of global flux measurements of CH4 and N2O by MM techniques in terrestrial ecosystems. Published studies were grouped into four main terrestrial land cover categories and the reported flux ranges, the consistency of different MM approaches over the same ecosystem types, the variability of the MM technique performances as regards the flux detection limit and environmental conditions, were analysed. Furthermore, the issue of the comparability between MM and soil chambers measurements was evaluated. The existing dataset, although temporally and spatially limited, shows that CH4 and N2O fluxes are extremely variable in both time and space with mean fluxes spanning within interquartile ranges of 1.33÷5.45, 11.02÷68.48, 5.38÷29.28, 13.87·103÷47.60·103nmolCH4m-2s-1 in forest, wetlands, croplands and artificial lands respectively, and of 0.09÷0.42, 0.24÷1.47, 9.13÷20.89nmolN2Om-2s-1 in forest, croplands and artificial lands (no published works were found for wetlands). When environmental conditions were comparable, a general agreement of flux ranges was found within each ecosystem type, in particular when estimates were based on accurate footprint analysis. Exceptions were mainly related to site-specific aspects or to particular measurement periods. Not all the measurement set-ups were suitable for all ecosystems, environmental conditions, turbulence characteristics and flux intensity, however the latest technological improvements make the detection of fluxes feasible virtually in all ecosystems. MM studies of CH4 and N2O fluxes were unevenly distributed around the globe and, in particular, were lacking in sensitive areas like Africa, South America and Central Asia. © 2013 Elsevier Ltd.

A sonic anemometer comparison was performed at a mountain cloud forest site in Taiwan to evaluate the effect of fog on sonic anemometers performance, with particular emphasis to their employment in eddy-covariance applications. Four sonic anemometers (Campbell CSAT3, Gill R3-50, METEK USA-1, and R.M. Young 81000VRE) were tested for 15 consecutive days with an overall fog duration of 86 h. Four aspects were analyzed: (1) spike statistics during foggy and non-foggy conditions, (2) spectral and co-spectral analyses before, during, and after 16 fog events, (3) correlations between turbulence characteristics of wind and temperature, and (4) flux error estimations. All sonic anemometers produce more spikes when the visibility is below 1000 m, compared to conditions with visibilities above 1000 m. However, the overall number of spikes caused by fog is generally low and therefore of no concern for any of the tested sonic anemometers. Spectral analyses showed that for most anemometers fog mostly affects spectra of the sonic temperature. Here, the high frequency range is either damped or amplified. These effects worsen with increasing duration and density of fog. In case of the 81000VRE and the USA-1, all three wind component spectra, sonic temperature spectra as well as the co-spectra of w’T’ and w’u’ show white noise in the high frequency range during dense fog. The CSAT3 shows noise only in the high frequency range of the sonic temperature and the co-spectra of w’T’. Smallest sensitivity to fog was observed for the R3-50. Nevertheless, differences in resulting fluxes are usually smaller than the flux error of the measurements. Due to the results of the spectral analysis and small flux errors the R3-50 seems to be suited best for eddy covariance measurements and process studies under dense foggy conditions.

Eddy covariance (EC) flux measurements of CO 2 , CH 4 and particles in densely urbanized area in Florence are reported, and partitioned into emission categories. CO 2 fluxes are a net source to the atmosphere, with small inter-annual variability and high seasonality. CH 4 fluxes represent about 8% of CO 2 -equivalent emissions, and do not exhibit significant seasonality. Heating and road traffic account for 68% and 32% of observed CO 2 emissions, respectively, and for 14% of CH 4 emissions, while gas network leakages are responsible for the residual. Particle fluxes exhibit a pronounced weekend decrease, highlighting that the main contribution to emissions comes from road traffic.

It has been formerly recognised that increasing relative humidity in the sampling line of closed-path eddy-covariance systems leads to increasing attenuation of water vapour turbulent fluctuations, resulting in strong latent heat flux losses. This occurrence has been analyzed for very long (50 m) and long (7 m) sampling lines. To date, only a few analytical or in situ analyses have been proposed to quantify and correct such effects, among which the comprehensive method by Ibrom et al. (2007) was proved effective for the very long sampling line of a forest eddy-covariance setup. Here we analyze data from eddy-covariance systems featuring short (4 m) and very short (1 m) sampling lines running at the same clover field and show that relative humidity effects persist also for these setups, and should not be neglected. Starting from the work of Ibrom and co-workers, we propose a mixed method, a composite of two existing approaches, for correcting eddy-covariance fluxes. By means of a comparison with parallel open-path measurements, we show that the mixed method leads to an improved estimation of latent heat fluxes, with respect to the method described by Ibrom et al. (2007) . The quantification and correction method proposed here is deemed applicable to closed-path systems featuring a broad range of sampling lines, and indeed applicable also to passive gases as a special case. The methods described in this paper are incorporated, as processing options, in the free and open-source eddy-covariance software packages ECO2S and EddyPro.

Eddy covariance flux research has relied on open- or closed-path gas analyzers for producing estimates of net ecosystem exchange of carbon dioxide (CO2) and water vapor (H2O). The two instruments have had different challenges that have led to development of an enclosed design that is intended to maximize strengths and minimize weaknesses of both traditional designs. Similar to the closed-path analyzer, the enclosed design leads to minimal data loss during precipitation events and icing, and it does not have surface heating issues. Similar to the open-path design, the enclosed design has good frequency response due to small flux attenuation loss in the short intake tube, does not need frequent calibration, has minimal maintenance requirements, and can be used in a very low power configuration. Another important feature of such a design is the ability to output instantaneous mixing ratio, or dry mole fraction, so that instantaneous thermal and pressure-related expansion and contraction, and water dilution of the sampled air have been accounted for. Thus, no density corrections should be required to compute fluxes during postprocessing. Calculations of CO2 and H2O fluxes via instantaneous mixing ratio from the new enclosed CO2/H2O gas analyzer were tested in nine field experiments during 2009–2010 in a wide range of ecosystems and setups. Fluxes computed via a mixing ratio output from the instrument without applying density corrections were compared to those computed the traditional way using density corrections. The results suggest that with proper temperature, water vapor, and pressure measurements in the cell, gas fluxes can be computed confidently from raw covariance of mixing ratio and vertical wind speed, multiplied by a frequency response correction. This has important implications for future flux measurements, because avoiding hourly density corrections could have the advantages of increasing flux measurement quality and temporal resolution, reducing the magnitude of minimum detectable flux, unifying data processing steps, and assuring better intercomparison between different sites and networks.

Ammonia (NH3) emissions have been quantified during slurry spreading in two experimental trials in two intensively managed agricultural fields in northern Italy, during spring 2009 and 2011. NH3 fluxes have been measured by Eddy covariance (EC) method from the slurry application to the soil incorporation until the end of the emission phenomenon. The EC system was equipped with a fast sensor for NH3 concentration measurements based on Tunable Infrared Laser Differential Absorption Spectrometry (QC-TILDAS). NH3 volatilisation has been monitored in continuous for both experimental trials, confirming the rapidity of the NH3 losses when slurry is spread to the field. Within 24 h from the application the volatilisation suddenly decreases, stopping after soil incorporation occurred 24 and 30 h from the spreading for the two experimental trials. The maximum NH3 emission levels were 138.3 and 243.5 μg m−2 s−1 and the total losses of NH4-N were 19.4% and 28.5%, determined 7 days after the spreading for the first and the second trial, respectively. EC measurements have been compared to the emissions estimated by a backward Lagrangian stochastic model, resulting consistent for dynamic and quantitative emitted. To explain the differences between the losses in the two experiments, the relationship between emission and meteorological conditions has been investigated. In particular, rain during the 2009 trial caused a significant reduction in emissions, whereas high air temperatures enhanced the emission phenomenon in the 2011 trial. The results shown that for improving nitrogen efficiency, slurry incorporation has to be performed in times closer from spreading than 24 h, under weather conditions which limit NH3 emissions (such as cloudy with low solar radiation and temperature).

Most plot-scale methane emission models – of which many have been developed in the recent past – are validated using data collected with the closed-chamber technique. This method, however, suffers from a low spatial representativeness and a poor temporal resolution. Also, during a chamber-flux measurement the air within a chamber is separated from the ambient atmosphere, which negates the influence of wind on emissions. Additionally, some methane models are validated by upscaling fluxes based on the area-weighted averages of closed-chamber measurements, and by comparing those to the eddy covariance (EC) flux. This technique is rather inaccurate, as the area of upscaling might be different from the EC tower footprint, therefore introducing significant mismatch. In this study, we present an approach to validate plot-scale methane models with EC observations using the footprint-weighted average method. Our results show that the fluxes obtained by the footprint-weighted average method are of the same magnitude as the EC flux. More importantly, the temporal dynamics of the EC flux on a daily time scale are also captured (r2 = 0.7). In contrast, using the area-weighted average method yielded a low (r2 = 0.14) correlation with the EC measurements and an underestimation of methane emissions by 27.4%. This shows that the footprint-weighted average method is preferable when validating methane emission models with EC fluxes for areas with a heterogeneous and irregular vegetation pattern.

Simulations of the global dust cycle and its interactions with a changing Earth system are hindered by the empirical nature of dust emission parameterizations in climate models. Here we take a step towards improving global dust cycle simulations by presenting a physically-based dust emission model. The resulting dust flux parameterization depends only on the wind friction speed and the soil's threshold friction speed, and can therefore be readily implemented into climate models. We show that our parameterization's functional form is supported by a compilation of quality-controlled vertical dust flux measurements, and that it better reproduces these measurements than existing parameterizations. Both our theory and measurements indicate that many climate models underestimate the dust flux's sensitivity to soil erodibility. This finding can explain why dust cycle simulations in many models are improved by using an empirical preferential sources function that shifts dust emissions towards the most erodible regions. In fact, implementing our parameterization in a climate model produces even better agreement against aerosol optical depth measurements than simulations that use such a source function. These results indicate that the need to use a source function is at least partially eliminated by the additional physics accounted for by our parameterization. Since soil erodibility is affected by climate changes, our results further suggest that many models have underestimated the climate sensitivity of the global dust cycle.

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.

This document is the D.3.5_BRIDGE observation protocols. Work package 3 has the role of systematically monitor the main fluxes using remote in situ measurements and sensing techniques and to address socioeconomic issues for each case study (Helsinki, Athens, London, Firenze and Gliwice). The final products of WP3 are datasets and maps of energy and water fluxes, pollution concentrations, land cover and vegetation per each case study. The aim of this document is to provide a comprehensive report on the methodologies applied and lessons learned in the course of the measurements campaigns carried on in the measurement campaigns of the BRIDGE Project.

For the first time, vertical fluxes of mineral dust measured by Eddy Covariance in two desert sites of Northern Asia have been used to test the performances of a wind erosion model in the field. Soil parameters required by the model were obtained through field and laboratory determinations. Model predictions and direct measurements have been compared. The main finding was that the direction of the horizontal wind relative to the orientation of nebkhas played a crucial role in determining the emission of particles in one of the investigated sites. Being unable to simulate such interaction, the model generally overestimated the actual emission. It provided, instead, reliable predictions (r2 = 0·87) when the wind direction was suitable in detaching loose erodible elements placed on nebkhas thanks to their normal orientation. Copyright © 2009 John Wiley & Sons, Ltd.

Mineral dust emission accounts for a substantial portion of particles present in the troposphere. It is emitted mostly from desert areas, mainly through intense storm episodes. The aim of this work was to quantify size-segregated fluxes of mineral dust particles emitted during storm events occurring in desert areas of northern China (Alashan desert, Inner Mongolia), known to act as one of the strongest sources of mineral dust particles in the Asian continent. Long-range transport of mineral dust emitted in this area is responsible for the high particle concentrations reached in densely populated areas, including the city of Beijing. Based on a theoretical analysis, an eddy covariance system was built to get size-segregated fluxes of mineral dust particles with optical diameters ranging between 0.26 and 7.00 µm. The system was optimised to measure fluxes under intense storm event conditions. It was tested in two sites located in the Chinese portion of the Gobi desert. During the field campaign, an intense wind erosion event, classified as a "weak dust storm", was recorded in one of them. Data obtained during this event indicate that particle number fluxes were dominated by the finer fraction, whereas in terms of mass, coarser particle accounted for the largest portion. It was found that during the storm event, ratios of size-segregated particle mass fluxes remained substantially constant and a simple parameterization of particle emission from total mass fluxes was possible. A strong correlation was also found between particle mass fluxes and the friction velocity. This relationship is extremely useful to investigate mechanisms of particle formation by wind erosion.

Integration of long-term eddy covariance (EC) flux datasets over regional and global scales requires high degree of comparability of flux data measured at different stations, which entails not only similar-performing instrumentation and their appropriate deployment, but also standardized and reproducible data processing and quality control (QC) procedures. This work focuses on the latter topic and, in particular, on the development of a robust data cleaning procedure. The proposed strategy includes a set of tests aimed at detecting the presence of specific sources of systematic error in the data, as well as an outlier detection procedure aimed at identifying aberrant flux values. Results from tests and outlier detection are integrated in such a way as to leave a large degree of flexibility in the choice of tests and of test threshold values without losing in efficacy and, at the same time, to avoid the use of subjective criteria in the decision rule that specifies whether to retain or reject flux data of dubious quality. Tests development was rooted on advanced time series analysis techniques that consider the stochastic properties of both raw, high-frequency EC data and of flux time series, such as complex dynamics, high persistence and possible presence of stochastic trends. The performance of each proposed test is evaluated by means of Monte Carlo simulations on synthetic datasets, whereas their impact on observed times series was evaluated on a selection of EC datasets distributed by the ICOS research infrastructure. Simulation results evidenced that the proposed tests have a better performance compared to alternative existing QC routines, showing lower false positive and false negative error rates. The application of the proposed tests on real datasets led to an effective cleaning of EC flux data retaining the maximum number of good quality data. Although there is still room for improvement, in particular with the development of new QC tests, we think that the proposed data cleaning procedure can serve as a basis towards a unified QC strategy for EC datasets which i) includes only completely data-driven routines and is therefore suitable for automatic and centralized data processing pipelines, ii) guarantees results reproducibility and iii) is flexible and scalable to accommodate new and additional tests that makes the approach also suitable for other greenhouse gases.

Emission of carbon from ecosystems in the form of volatile organic compounds (VOC) represents a minor component flux in the global carbon cycle that has a large impact on ground-level ozone, particle and aerosol formation and thus on air chemistry and quality. This study reports exchanges of CO2 and VOC between a poplar-based short rotation coppice (SRC) plantation and the atmosphere, measured simultaneously at two spatial scale, one at stand level and another at leaf level. The first technique combined Proton Transfer Reaction “Time-of-Flight” mass spectrometry (PTR–TOF–MS) with the eddy covariance method, to measure fluxes of a multitude of VOC. Abundant fluxes of isoprene, methanol and, to a lesser extent, fluxes of other oxygenated VOC such as formaldehyde, isoprene oxidation products (methyl vinyl ketone and methacrolein), methyl ethyl ketone, acetaldehyde, acetone and acetic acid, were measured. Under optimal environmental conditions, isoprene flux was mostly controlled by temperature and light. Differently, methanol flux underwent a combined enzymatic and stomatal control, together involving environmental drivers such as vapour pressure deficit (VPD), temperature and light intensity. Moreover fair weather condition favoured ozone deposition to the poplar plantation.The second technique involved trapping the VOCs emitted from leaves followed by gas chromatography-mass spectrometry (GC–MS) analysis. These leaf-level measurements showed that emission of isoprene in adult leaves and of monoterpenes in juvenile leaves are widespread across poplar genotypes. Detection of isoprene oxidation products (iox) emission with leaf-level measurements confirmed that a fraction of isoprene may be already oxidized within leaves, possibly when isoprene copes with foliar reactive oxygen species (ROS) formed during warm and sunny days.