eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5

Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2  =  1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time

Scaling and balancing carbon dioxide fluxes in a heterogeneous tundra ecosystem of the Lena River Delta

The current assessments of the carbon turnover in the Arctic tundra are subject to large uncertainties. This problem can (inter alia) be ascribed to both the general shortage of flux data from the vast and sparsely inhabited Arctic region, as well as the typically high spatiotemporal variability of carbon fluxes in tundra ecosystems. Addressing these challenges, carbon dioxide fluxes on an active flood plain situated in the Siberian Lena River Delta were studied during two growing seasons with the eddy covariance method. The footprint exhibited a heterogeneous surface, which generated mixed flux signals that could be partitioned in such a way that both respiratory loss and photosynthetic gain were obtained for each of two vegetation classes. This downscaling of the observed fluxes revealed a differing seasonality in the net uptake of bushes (−0.89 µmol m−2 s−1) and sedges (−0.38 µmol mm−2 s−1) in 2014. That discrepancy, which was concealed in the net signal, resulted from a comparatively warm spring in conjunction with an early snowmelt and a varying canopy structure. Thus, the representativeness of footprints may adversely be affected in response to prolonged unusual weather conditions. In 2015, when air temperatures on average corresponded to climatological means, both vegetation-class-specific flux rates were of similar magnitude (−0.69 µmol m−2 s−1). A comprehensive set of measures (e.g. phenocam) corroborated the reliability of the partitioned fluxes and hence confirmed the utility of flux decomposition for enhanced flux data analysis. This scrutiny encompassed insights into both the phenological dynamic of individual vegetation classes and their respective functional flux to flux driver relationships with the aid of ecophysiologically interpretable parameters. For comparison with other sites, the decomposed fluxes were employed in a vegetation class area-weighted upscaling that was based on a classified high-resolution orthomosaic of the flood plain. In this way, robust budgets that take the heterogeneous surface characteristics into account were estimated. In relation to the average sink strength of various Arctic flux sites, the flood plain constitutes a distinctly stronger carbon dioxide sink. Roughly 42 % of this net uptake, however, was on average offset by methane emissions lowering the sink strength for greenhouse gases. With growing concern about rising greenhouse gas emissions in high-latitude regions, providing robust carbon budgets from tundra ecosystems is critical in view of accelerating permafrost thaw, which can impact the global climate for centuries

Upside-down fluxes Down Under: CO2 net sink in winter and net source in summer in a temperate evergreen broadleaf forest

Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800mm and a mean annual temperature of 18°C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225gCm−2yr−1 on average, with a standard deviation of 108gCm−2yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2= 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.The Australian Education Investment Fund, Australian Terrestrial Ecosystem Research Network, Australian Research Council and Hawkesbury Institute for the Environment at Western Sydney University supported this work. We thank Jason Beringer, Helen Cleugh, Ray Leuning and Eva van Gorsel for advice and support. Senani Karunaratne provided soil classification details

Preliminary results of the glacial winds regime on the Mandrone Glacier

4During the summer of 2008, from 13 June to 29 September, at an altitude of 2780 m asl, a micro–meteorological station was placed on the Mandrone Glacier (Adamello Group, Italian Central Alps) by a team of the University of Brescia. The aim of the MandronEX (Mandrone EXperiment) field campaign was the collection of useful data to analyse the glacial winds and estimate the mass balance of the glacier. In this study will the data recorded by the 3 axes Gill WindMaster sonic anemometer at a sampling rate of 20 Hz, during the first nine days of the experiment will be analysed, in order to detect the glacial winds. A general description of the atmospheric pressure, the air temperature and the wind directions was provided in order to understand the meteorological conditions on the glacier and to obtain preliminary information about the winds regime. The more accurate elaborations executed by means of the frequency analysis and the wind–roses have shown an alternate regime of anabatic winds, from the valley to the glacier, especially in the first days of the campaign, and katabatic ones from the glacier to the valley. The spectral analysis of the u and w wind speed components, instead, allowed to detect the presence of the -5/3 slope Kolmogorov law, in the inertial sub–range. Moreover, according to the analysis provided by Kaimal et al. (1972) the atmosphere seems to be stable during the investigated period.openopenFalocchi M.; S. Barontini; G. Grossi; R.RanziFalocchi, M.; Barontini, Stefano; Grossi, Giovanna; Ranzi, Robert

The role of surface roughness, albedo, and Bowen ratio on ecosystem energy balance in the Eastern United States

Land cover and land use influence surface climate through differences in biophysical surface properties, including partitioning of sensible and latent heat (e.g., Bowen ratio), surface roughness, and albedo. Clusters of closely spaced eddy covariance towers (e.g., \u3c10 \u3ekm) over a variety of land cover and land use types provide a unique opportunity to study the local effects of land cover and land use on surface temperature. We assess contributions albedo, energy redistribution due to differences in surface roughness and energy redistribution due to differences in the Bowen ratio using two eddy covariance tower clusters and the coupled (land-atmosphere) Variable-Resolution Community Earth System Model. Results suggest that surface roughness is the dominant biophysical factor contributing to differences in surface temperature between forested and deforested lands. Surface temperature of open land is cooler (−4.8 °C to −0.05 °C) than forest at night and warmer (+0.16 °C to +8.2 °C) during the day at northern and southern tower clusters throughout the year, consistent with modeled calculations. At annual timescales, the biophysical contributions of albedo and Bowen ratio have a negligible impact on surface temperature, however the higher albedo of snow-covered open land compared to forest leads to cooler winter surface temperatures over open lands (−0.4 °C to −0.8 °C). In both the models and observation, the difference in mid-day surface temperature calculated from the sum of the individual biophysical factors is greater than the difference in surface temperature calculated from radiative temperature and potential temperature. Differences in measured and modeled air temperature at the blending height, assumptions about independence of biophysical factors, and model biases in surface energy fluxes may contribute to daytime biases

Surface-Layer Similarity Functions for Dissipation Rate and Structure Parameters of Temperature and Humidity Based on Eleven Field Experiments

In the literature, no consensus can be found on the exact form of the universal funtions of Monin-Obukhov similarity theory (MOST) for the structure parameters of temperature, CT 2, and humidity, Cq 2, and the dissipation rate of turbulent kinetic energy, ε. By combining 11 datasets and applying data treatment with spectral data filtering and error-weighted curve-fitting we first derived robust MOST functions of CT 2,Cq 2 and ε that cover a large stability range for both unstable and stable conditions. Second, as all data weregathered with the same instrumentation and were processed in the same way—in contrast to earlier studies—we were able to investigate the similarity of MOST functions across different datasets by defining MOST functions for all datasets individually. For CT 2 and ε we found no substantial differences in MOST functions for datasets over different surface types or moisture regimes. MOST functions of Cq 2 differ from that of CT 2, but we could not relate these differences to turbulence parameters often associated with non-local effects.Furthermore, we showed that limited stability ranges and a limited number of data points are plausible reasons for variations of MOST functions in the literature. Last, we investigated the sensitivity of fluxes to the uncertainty of MOST functions.We provide an overview of the uncertainty range for MOST functions of CT 2,Cq 2 and ε, and suggest their use in determining the uncertainty in surface fluxes.<br/

Estimate of turbulent fluxes with eddy-covariance technique in a complex topography: A case study in the Italian Alps

A sensitivity analysis to different eddy—covariance data processing algorithms is presented for a dataset collected in an Alpine environment with complex topography. In Summer 2012 a micrometeorological station was installed at Cividate Camuno (274 m a.s.l., Oglio river basin, Central Italian Alps), in a flat and rectangular grass-covered lawn. The grass was 0.6 m tall during most of the field campaign. The station is equipped with traditional devices, four multiplexed TDR probes, and an eddy--covariance apparatus sampling at 20 Hz (Gill WindMaster Sonic Anemometer and Licor Li7500 Gas Analyzer), at about 3 m above the ground. The local winds regime is strongly affected by the morphology of the valley, and the topography is complex also due to the heterogeneity of the surrounding-areas land—cover. Using EddyPro software, the sensitivity of the turbulent fluxes estimate was assessed addressing three major issues of the data processing procedure, i.e. the choice of the computational averaging period, of the axis rotation method and of the data detrending criterion. Once identified three test periods of consecutive days without rainfall, the fluxes of momentum, sensible heat and latent heat were computed at the averaging period of 30, 60 and 120 min respectively. At each averaging period, both the triple rotation method, the double rotation method and the planar fit method were applied. Particularly the latter was applied both fitting a unique plane for all the wind directions and fitting multiple planes, one for each sector of the wind rose. Regarding the detrending criteria, data were processed with a block average and a linear detrend, the latter with time constant of 5, 30, 60 and 120 min respectively. Therefore, for each test period about 50 estimates of the fluxes were provided. As a result the obtained fluxes were compared. Even if with different flux quality, their pattern is quite stable with regard to the applied estimate procedures, but with sensitively different average values