Eddy Covariance Flux Measurements Research Articles

Applicability of a closed-path quantum cascade laser spectrometer for eddy covariance (EC) flux measurements of nitric oxide (NO) over a cropland during a low emission period

Croplands are important sources of atmospheric nitric oxide (NO). However, high-frequency measurements of NO fluxes over croplands using the eddy covariance (EC) technique are still scarce, mainly due to instrumental limitation. In this study, a closed-path NO analyzer based on a quantum cascade laser (QCL) absorption spectrometer was employed for EC flux measurements over a subtropical vegetable field during a two-month summer period with the lowest NO emission intensity of the year. The purpose was to investigate the detection limit of the EC system based on this NO analyzer and evaluate its applicability for measuring the turbulent fluxes of NO under field conditions. The performance of the analyzer was stable, showing an average precision (0.1 s) of 0.338 nmol mol−1 and a corresponding flux detection limit of 5.6 μg N m−2h−1 at the 95% confidence interval. The measured turbulent NO fluxes ranged from −7.1 to 61.4 μg N m−2h−1 (median: 3.5 μg N m−2h−1), with a relative random error of 386% before field ploughing and 76% thereafter. The systematic errors due to the high-frequency loss and the use of lag times of carbon dioxide for NO flux calculation were estimated at 12% and 3%, respectively. During the measurement period, 37% of the observed half-hourly fluxes were larger than the detection limit; the magnitude of these fluxes is comparable with that measured by the static chambers. Nevertheless, this EC system could be still qualified for measuring turbulent NO fluxes over common croplands if the flux averaged at daily or longer timescales are of interest, because either flux detection limit or random error would decrease by an order of n, wherein n is the number of half-hourly fluxes being taken for averages. This study shows that the closed-path dual-QCL analyzer could be an effective option for EC measurements of turbulent NO fluxes with the advantages of (i) stable performance, (ii) high precision and fast response, and (iii) feasible instrumental maintenance for long-term field measurements. However, the observed turbulent fluxes still underestimated the soil NO emissions likely due to chemical reaction loss of NO below the sensor height. Further studies are necessary to address this systematic error.

Comparison of Bi-Hemispherical and Hemispherical-Conical Configurations for In Situ Measurements of Solar-Induced Chlorophyll Fluorescence

During recent decades, solar-induced chlorophyll fluorescence (SIF) has shown to be a good proxy for gross primary production (GPP), promoting the development of ground-based SIF observation systems and supporting a greater understanding of the relationship between SIF and GPP. However, it is unclear whether such SIF-oriented observation systems built from different materials and of different configurations are able to acquire consistent SIF signals from the same target. In this study, we used four different observation systems to measure the same targets together in order to investigate whether SIF from different systems is comparable. Integration time (IT), reflectance, and SIF retrieved from different systems with hemispherical-conical (hemi-con) and bi-hemispherical (bi-hemi) configurations were also evaluated. A newly built prism system (SIFprism, using prism to collect both solar and target radiation) has the shortest IT and highest signal to noise ratio (SNR). Reflectance collected from the different systems showed small differences, and the diurnal patterns of both red and far-red SIF derived from different systems showed a marginal difference when measuring the homogeneous vegetation canopy (grassland). However, when the target is heterogeneous, e.g., the Epipremnum aureum canopy, the values and diurnal pattern of far-red SIF derived from systems with a bi-hemi configuration were obviously different with those derived from the system with hemi-con configuration. These results demonstrate that different SIF systems are able to acquire consistent SIF for landscapes with a homogeneous canopy. However, SIF retrieved from bi-hemi and hemi-con configurations may be distinctive when the target is a heterogeneous (or discontinuous) canopy due to the different fields of view and viewing geometries. Our findings suggest that the bi-hemi configuration has an advantage to measure heterogeneous canopies due to the large field of view for upwelling sensors being representative for the footprint of the eddy covariance flux measurements.

Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits

The most recent efforts to provide remote sensing (RS) estimates of plant function rely on the combination of Radiative Transfer Models (RTM) and Soil-Vegetation-Atmosphere Transfer (SVAT) models, such as the Soil-Canopy Observation Photosynthesis and Energy fluxes (SCOPE) model. In this work we used ground spectroradiometric and chamber-based CO2 flux measurements in a nutrient manipulated Mediterranean grassland in order to: 1) develop a multiple-constraint inversion approach of SCOPE able to retrieve vegetation biochemical, structural as well as key functional traits, such as chlorophyll concentration (Cab), leaf area index (LAI), maximum carboxylation rate (Vcmax) and the Ball-Berry sensitivity parameter (m); and 2) compare the potential of the of gross primary production (GPP) and sun-induced fluorescence (SIF), together with up-welling Thermal Infrared (TIR) radiance and optical reflectance factors (RF), to estimate such parameters. The performance of the proposed inversion method as well as of the different sets of constraints was assessed with contemporary measurements of water and heat fluxes and leaf nitrogen content, using pattern-oriented model evaluation.The multiple-constraint inversion approach proposed together with the combination of optical RF and diel GPP and TIR data provided reliable estimates of parameters, and improved predicted water and heat fluxes. The addition of SIF to this scheme slightly improved the estimation of m. Parameter estimates were coherent with the variability imposed by the fertilization and the seasonality of the grassland. Results revealed that fertilization had an impact on Vcmax, while no significant differences were found for m. The combination of RF, SIF and diel TIR data weakly constrained functional traits. Approaches not including GPP failed to estimate LAI; however GPP overestimated Cab in the dry period. These problems might be related to the presence of high fractions of senescent leaves in the grassland. The proposed inversion approach together with pattern-oriented model evaluation open new perspectives for the retrieval of plant functional traits relevant for land surface models, and can be utilized at various research sites where hyperspectral remote sensing imagery and eddy covariance flux measurements are simultaneously taken.

Surface renewal measurements of H, λE and CO2 fluxes over two different agricultural systems

The importance of understanding turbulent scalar exchange over agricultural landscapes motivated this study of the surface renewal (SR) method for deployment in place of or alongside eddy covariance (EC) instrumentation. High-frequency (20 Hz) scalar data were used with turbulence and similarity parameters for SR measurements of turbulent sensible heat (H), latent heat (λE), and CO2 (Fc) flux. The eddy covariance method was used to provide a reference data set to compare the performance of SR to EC flux measurements when the SR input requirements were determined with either: (1) fast-response (SR1) or (2) slow-response (SR2) wind velocities. We test SR1 and SR2 over two agricultural crops, cotton and rice, that are suitable for adaptive (“climate-smart”) management solutions which rely on decisions informed by extensive micrometeorological measurements. One advantage that the SR method provides is its simplicity of deployment and maintenance, requiring less energy and resources than typical EC networks. Regardless of the crop and scalar eddy flux, both SR flux methods agreed well with the EC flux measurements; coefficients of determination (R2) and slopes (s) of linear regression analysis ranges were [0.88, 0.98] and [1.01, 1.22], respectively. It was concluded that when EC measurements are unavailable, SR may be used as an alternative for additional climate-smart agriculture research efforts and this method may allow for higher spatial monitoring resolution because of the possibility to avoid the use of sonic anemometry.

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology.

A global network of long-term carbon and water flux measurements has existed since the late 1990s. With its representative sampling of the terrestrial biosphere's climate and ecological spaces, this network is providing background information and direct measurements on how ecosystem metabolism responds to environmental and biological forcings and how they may be changing in a warmer world with more carbon dioxide. In this review, I explore how carbon and water fluxes of the world's ecosystem are responding to a suite of covarying environmental factors, like sunlight, temperature, soil moisture, and carbon dioxide. I also report on how coupled carbon and water fluxes are modulated by biological and ecological factors such as phenology and a suite of structural and functional properties. And, I investigate whether long-term trends in carbon and water fluxes are emerging in various ecological and climate spaces and the degree to which they may be driven by physical and biological forcings. As a growing number of time series extend up to 20years in duration, we are at the verge of capturing ecosystem scale trends in the breathing of a changing biosphere. Consequently, flux measurements need to continue to report on future conditions and responses and assess the efficacy of natural climate solutions.

Influence of Forest-Edge Flows on Scalar Transport with Different Vertical Distributions of Foliage and Scalar Sources

Forest edges have significant impacts on flow dynamics and mass exchange across the forest–atmosphere interface. A better understanding of edge flows and scalar transport has implications for locating and interpreting eddy-covariance flux measurements over finite-size forests with edges. Here the large-eddy simulation module within the Weather Research and Forecasting model is deployed to study the influence of forest edges on flow dynamics and scalar transport for a range of vertical distributions of foliage and scalar sources/sinks. For plant canopies with a relatively dense trunk space, a strong in-canopy flow convergence develops near the leading edge, which dominates the flow dynamics and leads to distinct scalar concentration and flux patterns not only across edges but also across the forest–atmosphere interface for sources near the ground and lower part of the canopy. For plant canopies with a deep, sparse trunk space, a strong and long sub-canopy jet develops, leading to simpler features in flow dynamics and scalar transfer. A real case with scalar sources/sink distributions as simulated by a newly developed multiple-layer canopy module produces even more complex scalar concentration and flux patterns. The budget equations for scalars are also analyzed to quantify the contributions of different terms to scalar fluxes. Our results demonstrate that both the scalar source distributions and canopy structures should be considered when eddy-covariance flux measurements are made over finite-size forests with edges.

Evaluation of the rescaled complementary principle in the estimation of evaporation on the Tibetan Plateau

Accurate quantification of the terrestrial water balance can improve our knowledge of regional water cycle changes, and deepen our understanding of evaporation in hydrological cycle and under climate change. However, sparse observation networks on the Tibetan Plateau (TP) prevent the reliable estimates of actual evaporation. Based on the China regional surface Meteorological Feature Dataset (CMFD) and the Global Land Surface Satellite (GLASS) product, we adopted the latest rescaled nonlinear complementary relationship (CR) to calculate the monthly actual evaporation (E) from 1982 to 2015. We analyzed the spatio-temporal variability of the annual E on the entire TP, and explored the main meteorological factors controlling the annual E and the regulation of multiyear average annual E in different vegetation zones from southeast to northwest. Our results indicated that the net radiation (Rn) and E exhibited a favorable agreement with monthly changes of the observed values; and E estimated by the CR explained 79–96% variation of the eddy covariance flux measurements. The multiyear average E was 373.12 mm yr−1 and displayed similar spatial patterns of decreasing from southeast to northwest with two remote sensing products (GLDAS_VIC, GLEAM_v3.3) and one hydrological model (Budyko). Additionally, based on the Mann-Kendall trend test, there were 21.56% of the TP with significant upward trend of annual E which mainly distributed in the area with dense glaciers. The Nyenchen Tanglha Mountains and Pamirs Plateau area had the most obvious upward trend, with up to over 6 mm yr−1. In a relative sense, the key meteorological elements which affected annual E on the TP were relative humidity (RH) (r = 0.63) and Rn (r = 0.56).

Insect outbreaks have transient effects on carbon fluxes and vegetative growth but longer-term impacts on reproductive growth in a mangrove forest

Mangroves are experiencing frequent severe insect outbreaks, and the bud moth larvae (BML; Lasiognatha cellifera) is one of the most common leaf-feeding insects. However, the effects of insect outbreaks on ecosystem carbon fluxes of mangrove ecosystems are not well understood, and more importantly, the relative effects of these disturbances on vegetative and reproductive growth of mangroves remain unclear. We used measurements of plant litterfall, leaf damage percentage, and insect frass production, satellite-derived normalized difference vegetation index (NDVI), and eddy covariance flux measurements to quantify the impacts of a BML outbreak in 2010 on carbon fluxes and both vegetative and reproductive growth of a mangrove forest. The BML outbreak occurred in 2010 damaged nearly 90% of the foliage, increased the annual leaf litterfall, and decreased the flower and propagule production. Net ecosystem productivity decreased following the insect disturbance and recovered within several months. There were no significant differences in annual carbon fluxes among the four years from 2009 to 2013. In contrast, the flower production significantly decreased and there was nearly no propagule production after the insect outbreak. Reproductive growth did not recover even two years after the insect outbreak. Our results showed that the BML outbreak had asymmetric effects on vegetative and reproductive growth of mangrove forests. Our findings can help us better understand the impacts of insect disturbances on mangrove ecosystems and also have implications for informing mangrove conservation and restoration efforts.

Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Abstract. Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

Estimating Herd-Scale Methane Emissions from Cattle in a Feedlot Using Eddy Covariance Measurements and the Carbon Dioxide Tracer Method.

Measurements of methane (CH) emissions from ruminants could provide invaluable data to reduce uncertainties in the global CH budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The main objective of this study was to evaluate a new CO tracer (COT) approach that combined CH and CO atmospheric concentrations with eddy covariance (EC) CO flux measurements to estimate CH emissions from cattle in a feedlot. A closed-path EC system was used to measure CH and CO fluxes from a feedlot in Kansas. The EC flux measurements were scaled from landscape to animal scale using footprint analyses. Emissions of CH from the cattle were also estimated using the COT approach and measured CO and CH concentration, and scaled EC CO fluxes. The CH and CO concentration ratios showed a distinct diel trend with greater values during the daytime. Average monthly CH emission estimates using the COT approach ranged from 72 to 127 g animal d, which was consistent with the values reported in other studies that had similar animal characteristics. The COT method CH emission estimates showed good agreement with scaled CH EC fluxes (slope = 0.9 and = 0.8) for cold and dry months. However, the agreement between the two techniques was significantly reduced (slope = 1.5 and = 0.6) during wet and warm months. On average, the COT method CH emission estimates were 3% greater than the EC CH emissions. Overall, our results suggest that the COT method can be used to estimate enteric feedlot CH emissions.

Locating and quantifying multiple landfills methane emissions using aircraft data

A mass balance approach to quantify methane (CH4) emission of four co-located landfills by means of airborne measurements and dispersion modelling was proposed and assessed. By flying grids at different heights above the landfills, atmospheric CH4 densities and wind components were measured along the edges and inside the study atmospheric volume, in order to calculate mass flows in the along- and across-wind directions. A steady-state Gaussian dispersion model was applied to build the concentration fields associated to unit emission from each landfill, while the contribution of each one to the total emission was assessed using a General Linear Model approach, minimizing the difference between measured and modeled mass flows. Results showed that wind spatial and temporal variability is the main factor controlling the accuracy of the method, as a good agreement between measured and modeled mass flows was mainly found for flights made in steady wind conditions. CH4 emissions of the entire area ranged from 213.5 ± 33.5 to 317.9 ± 90.4 g s−1 with a mean value of 252.5 ± 54.2 g s−1. Contributions from individual sources varied from 17.5 to 40.1 g m−2 day−1 indicating a substantial heterogeneity of the different landfills, which differed in age and waste composition. The proposed method was validated against tower eddy covariance flux measurements made at one of the landfills, revealing an overall agreement within 20%.

SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis.

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

Carbon use efficiency of mycorrhizal fungal mycelium increases during the growing season but decreases with forest age across a Pinus sylvestris chronosequence

Abstract In boreal forest soils, mycelium of mycorrhizal fungi is pivotal for regulating soil carbon (C) cycling and storage. The carbon use efficiency (CUE), a key parameter in C cycling models, can inform on the partitioning of C between microbial biomass, and potential soil storage, and respiration. Here, we test the dependency of mycorrhizal mycelial CUE on stand age and seasonality in managed boreal forest stands. Based on mycelial production and respiration estimates, derived from sequentially incubated ingrowth mesh bags, we estimated CUE on an ecosystem scale during a seasonal cycle and across a chronosequence of eight, 12‐ to 158‐year‐old, managed Pinus sylvestris forest stands characterized by decreasing pH and nitrogen (N) availability with increasing age. Mycelial respiration was related to total soil respiration, and by using eddy covariance flux measurements, primary production (GPP) was estimated in the 12‐ and 100‐year‐old forests, and related to mycelial respiration and CUE. As hypothesized, mycelial CUE decreased significantly with increasing forest age by c. 65%, supposedly related to a shift in mycorrhizal community composition and a metabolic adjustment reducing their own biomass N demand with declining soil N availability. Furthermore, mycelial CUE increased by a factor of five over the growing season; from 0.03 in May to 0.15 in November, and we propose that the seasonal change in CUE is regulated by a decrease in photosynthate production and temperature. The respiratory contribution of mycorrhizal mycelium ranged from 14% to 26% of total soil respiration, and was on average 17% across all sites and occasions. Synthesis. Carbon is retained more efficiently in mycorrhizal mycelium late in the growing season, when fungi have access to a more balanced C and nutrient supplies. Earlier in the growing season, at maximum host plant photosynthesis, when below‐ground C availability is high in relation to N, the fungi respire excess C resulting in lower mycelial carbon use efficiency (CUE). Additionally, C is retained less efficiently in mycorrhizal fungal biomass in older forest stands characterized by more nutrient depleted soils than younger forest stands.

Effects of changes in precipitation on energy and water balance in a Eurasian meadow steppe

IntroductionWater such as precipitation is the most critical environment driver of ecosystem processes and functions in semi-arid regions. Frequency and intensity of drought and transient waterlogging are expected to increase in the meadow steppe in northeastern China. Using a 4-year dataset of eddy covariance flux measurements, ground measurements of biomass, phenology, and meteorological conditions, we investigated the changes in energy fluxes at multiple temporal scales and under different precipitation regimes.ResultsThe meadow steppe was latent heat (LE) dominated when soil water content was > 0.3 m3 m−3, but switched to sensible heat (H) dominated status when soil water content fell below 0.3 m3 m−3. LE dominated the energy exchange of the meadow grasslands on a yearly basis. Intensive precipitation had a profound impact on water-energy balance that could reduce the damages of drought by elevating deep soil moisture. The influence of LE on waterlogging depended on timing, with increased LE at the beginning of growing season and decreased LE after waterlogging. Spring and summer droughts resulted in different energy partitioning between latent and sensible heat energies, with spring drought dramatically decreased the LE fraction due to the change in water. In contrast, summer drought had little impact on LE due to the sufficient water input from large precipitation events at the beginning of the growing season.ConclusionsThere existed great seasonal and interannual variabilities in energy balance and partitioning in the meadow steppe over the 4-year study period, which were strongly influenced by changes in precipitation. The water loss through latent heat was more sensitive to spring drought than to summer drought, while summer drought had negligible impact on LE. Waterlogging contributed to LE by enhancing its values during and after the waterlogged periods at the beginning of the growing season in a dry year, but lowering its value after the waterlogged periods in growing season.

Aggregation of area-averaged evapotranspiration over the Ejina Oasis based on a flux matrix and footprint analysis

The determination of area-averaged evapotranspiration (ET) over a heterogeneous land surface at the satellite pixel scale/model grid scale (103–104 m) is crucial to the evaluation of the remote sensing ET products and development of the parameterization schemes of general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix of multi-site eddy-covariance (EC) and large aperture scintillometers (LASs) provided an unprecedented opportunity to establish an aggregation scheme for determining area-averaged surface fluxes. Based on the HiWATER flux matrix datasets and high-resolution land-cover map, a new flux aggregation method was developed by using footprint analysis and multiple-linear regression. The area-averaged sensible heat fluxes aggregated from the multi-site EC flux measurements using the developed method were compared with the LAS measured fluxes. The results showed that the new method produced reasonable estimates of sensible heat flux with a mean absolute percentage error (MAPE) value of around 20–30%. The new aggregation method also significantly outperformed other methods being applied commonly, such as the rather simple area-weighted method. The daily ET of various land-cover types and the area-averaged ET over the key area of the Populus euphratica forest reserve in the Ejina Oasis were separately estimated using the established disaggregation and aggregation schemes of the new method. The area-averaged ET over this key area ranged between 1 and 5 mm d−1 for the 68 days growing period in 2014. Results of this study can be used for the evaluation of relevant remote sensing models and land surface process models.

Accounting for spectroscopic effects in laser-based open-path eddy covariance flux measurements.

A significant portion of the production and consumption of trace gases (e.g. CO2 , CH4 , N2 O, NH3 , etc.) by world ecosystems occurs in areas without sufficient infrastructure or easily available grid power to run traditional closed-path flux stations. Open-path analyzer design allows such measurements with power consumption 10-150 times below present closed-path technologies, helping to considerably expand the global coverage and improve the estimates of gas emissions and budgets, informing the remote sensing and modeling communities and policy decisions, all the way to IPCC reports. Broad-band nondispersive infrared devices have been used for open-path CO2 and H2 O measurements since the late 1970s, but since recently, a growing number of new narrow-band laser-based instruments are being rapidly developed. The new design comes with its own challenges, specifically: (a) mirror contamination, and (b) uncontrolled air temperature, pressure and humidity, affecting both the gas density and the laser spectroscopy of the measurements. While the contamination can be addressed via automated cleaning, and density effects can be addressed via the Webb-Pearman-Leuning approach, the spectroscopic effects of the in situ temperature, pressure and humidity fluctuations on laser-measured densities remain a standing methodological question. Here we propose a concept accounting for such effects in the same manner as Webb et al. proposed to account for respective density effects. Derivations are provided for a general case of flux of any gas, examined using a specific example of CH4 fluxes from a commercially available analyzer, and then tested using "zero-flux" experiment. The proposed approach helps reduce errors in open-path, enclosed, and temperature- or pressure-uncontrolled closed-path laser-based flux measurements due to the spectroscopic effects from few percents to multiple folds, leading to methodological advancement and geographical expansion of the use of such systems providing reliable and consistent results for process-level studies, remote sensing and Earth modeling applications, and GHG policy decision-making.

Analysing the characteristic features of a pre-monsoon thunderstorm event over Pune, India, using ground-based observations and WRF model

In the present work, the characteristic features and factors contributed to the formation of a typical pre-monsoon thunderstorm that occurred over Pune has been studied using various ground-based observations, such as microwave radiometer profiler, wind lidar and surface eddy covariance flux measurements along with weather research and forecast (WRF) model. Initially, the thermodynamic state of atmosphere, variation in fluxes, as well as convective updrafts and downdrafts associated with the thunderstorm event, has been studied using ground-based observations. Thermodynamic indices derived from ground-based microwave radiometer observations showed significant variation before, during and after the development of thunderstorm such as smaller humidity index and higher values of total total index and K-index during the storm. Convective available potential energy (CAPE) and equivalent potential temperature have also shown an increase prior to the event. It is noted that sensible heat flux is higher than latent heat flux before the initiation of storm, however, the latent heat flux increased significantly during the storm. Wind lidar-derived vertical velocities showed strong variation i.e., exceeding \(3 \,\hbox {m} \,\hbox {s}^{-1}\) during the event. Signatures of veering effect indicated the transport of moisture to higher levels was noticed from the altitude variability of wind vector. Ground observations suggested strong crosswind wind shear, convergence of moisture that originated at elevated levels in the boundary layer and enhancement of moist static energy in the elevated layer above the surface was pre-storm characteristics that conducive for the storm enhancement. Secondly, the capabilities of a WRF model in simulating the storm development, structure and evolution have been verified. The WRF model was able to recreate major features of the environment in which the storm was developed. The model output was compared with ground observations, which showed that the model has well captured the sensible heat and friction velocity as that of observation compared to mixing ratio and latent heat. It is observed that the water vapour variation in the model is having a lag, about an hour, with that of observations. The detailed analysis of model output did not show triggering of a thunderstorm as noted in the observation at the same location, which may be probably due to model bias in the moisture transport or moisture convergence was weaker in the model.

Modelling random uncertainty of eddy covariance flux measurements

The eddy-covariance (EC) technique is considered the most direct and reliable method to calculate flux exchanges of the main greenhouse gases over natural ecosystems and agricultural fields. The resulting measurements are extremely important to characterize ecosystem exchanges of carbon, water, energy and other trace gases, and are widely used to validate or constrain parameter of land surface models via data assimilation techniques. For this purpose, the availability of both complete half-hourly flux time series and its associated uncertainty is mandatory. However, uncertainty estimation for EC data is challenging because the standard procedures based on repeated sampling are not suitable for this kind of measurements, and the presence of missing data makes it difficult to build any sensible time series model with time-varying second-order moments that can provide estimates of total random uncertainty. To overcome such limitations, this paper describes a new method in the context of the strategy based on the model residual approach proposed by Richardson et al. (Agric For Meteorol 148(1): 38–50, 2008). The proposed approach consists in (1) estimating the conditional mean process as representative of the true signal underlying observed data and (2) estimating the conditional variance process as representative of the total random uncertainty affecting EC data. The conditional mean process is estimated through the multiple imputation algorithm recently proposed by Vitale et al. (J Environ Inform https://doi.org/10.3808/jei.201800391 , 2018). The conditional variance process is estimated through the stochastic volatility model introduced by Beltratti and Morana (Econ Notes 30(2): 205–234, 2001). This strategy is applied to ten sites that are part of FLUXNET2015 dataset, selected in such a way to cover various ecosystem types under different climatic regimes around the world. The estimated uncertainty is compared with estimates by other well-established methods, and it is demonstrated that the scaling relationship between uncertainty and flux magnitude is preserved. Additionally, the proposed strategy allows obtaining a complete half-hourly time series of uncertainty estimates, which are expected to be useful for many users of EC flux data.

Evaluating multi-year, multi-site data on the energy balance closure of eddy-covariance flux measurements at cropland sites in southwestern Germany

Abstract. The energy balance of eddy-covariance (EC) measurements is typically not closed, resulting in one of the main challenges in evaluating and interpreting EC flux data. Energy balance closure (EBC) is crucial for validating and improving regional and global climate models. To investigate the nature of the gap in EBC for agroecosystems, we analyzed EC measurements from two climatically contrasting regions (Kraichgau – KR – and Swabian Jura – SJ) in southwestern Germany. Data were taken at six fully equipped EC sites from 2010 to 2017. The gap in EBC was quantified by ordinary linear regression, relating the energy balance ratio (EBR), calculated as the quotient of turbulent fluxes and available energy, to the residual energy term. In order to examine potential reasons for differences in EBC, we compared the EBC under varying environmental conditions and investigated a wide range of possible controls. Overall, the variation in EBC was found to be higher during winter than summer. Moreover, we determined that the site had a statistically significant effect on EBC but no significant effect on either crop or region (KR vs SJ). The time-variable footprints of all EC stations were estimated based on data measured in 2015, complimented by micro-topographic analyses along the prevailing wind direction. The smallest mean annual energy balance gap was 17 % in KR and 13 % in SJ. Highest EBRs were mostly found for winds from the prevailing wind direction. The spread of EBRs distinctly narrowed under unstable atmospheric conditions, strong buoyancy, and high friction velocities. Smaller footprint areas led to better EBC due to increasing homogeneity. Flow distortions caused by the back head of the anemometer negatively affected EBC during corresponding wind conditions.

Deviation of Wind Stress From Wind Direction Under Low Wind Conditions

AbstractThe deviation of the wind stress vector from the wind direction at the air‐sea interface under low wind conditions was investigated based on direct eddy covariance flux measurements taken at a coastal tower in the northern South China Sea. The wind stress deviates significantly from the mean wind direction under low wind conditions, with the deviation angle sometimes exceeding 90°, indicating upward momentum transfer from the ocean to the atmosphere. Negative downwind drag coefficient values begin to occur at a wind speed of approximately 4 m/s. Our results show that ocean swells and nonstationary airflow play critical roles in wind stress. Prominent peaks at the dominant swell frequency in the vertical velocity spectra are observed at a height of 17 m over the mean sea surface, implying that swell‐induced perturbations can reach a height of at least 17 m, and the wave boundary layer can extend more than 10 m above the sea surface. The results of our analysis indicate that at the observation height, the influence of nonstationarity in the wind field is more significant than that of swell‐induced motions on the deviation of wind stress. After the removal of nonstationary motions, the deviation angles of the wind stress from the wind direction are generally reduced and vary substantially at low wind speeds.