Choosing an optimal <i>β</i> factor for relaxed eddy accumulation applications across vegetated and non-vegetated surfaces

Accurately measuring the turbulent transport of reactive and conservative greenhouse gases, heat, and organic compounds between the surface and the atmosphere is critical for understanding trace gas exchange and its response to changes in climate and anthropogenic activities. The relaxed eddy accumulation (REA) method enables measuring the land surface exchange when fast-response sensors are not available, broadening the suite of trace gases that can be investigated. The β factor scales the concentration differences to the flux, and its choice is central to successfully using REA. Deadbands are used to select only certain turbulent motions to compute the flux. This study evaluates a variety of different REA approaches with the goal of formulating recommendations applicable over a wide range of surfaces and meteorological conditions for an optimal choice of the β factor in combination with a suitable deadband. Observations were collected across three contrasting ecosystems offering stark differences in scalar transport and dynamics: a mid-latitude grassland ecosystem in Europe, a loose gravel surface of the Dry Valleys of Antarctica, and a spruce forest site in the European mid-range mountains. We tested a total of four different REA models for the β factor: the first two methods, referred to as model 1 and model 2, derive βp based on a proxy p for which high-frequency observations are available (sensible heat Ts). In the first case, a linear deadband is applied, while in the second case, we are using a hyperbolic deadband. The third method, model 3, employs the approach first published by Baker et al. (1992), which computes βw solely based upon the vertical wind statistics. The fourth method, model 4, uses a constant βp, const derived from long-term averaging of the proxy-based βp factor. Each β model was optimized with respect to deadband size before intercomparison. To our best knowledge, this is the first study intercomparing these different approaches over a range of different sites. With respect to overall REA performance, we found that the βw and constant βp, const performed more robustly than the dynamic proxy-dependent approaches. The latter models still performed well when scalar similarity between the proxy (here Ts) and the scalar of interest (here water vapor) showed strong statistical correlation, i.e., during periods when the distribution and temporal behavior of sources and sinks were similar. Concerning the sensitivity of the different β factors to atmospheric stability, we observed that βT slightly increased with increasing stability parameter z/L when no deadband is applied, but this trend vanished with increasing deadband size. βw was unrelated to dynamic stability and displayed a generally low variability across all sites, suggesting that βw can be considered a site-independent constant. To explain why the βw approach seems to be insensitive towards changes in atmospheric stability, we separated the contribution of w′ kurtosis to the flux uncertainty. For REA applications without deeper site-specific knowledge of the turbulent transport and degree of scalar similarity, we recommend using either the βp, const or βw models when the uncertainty of the REA flux quantification is not limited by the detection limit of the instrument. For conditions when REA sampling differences are close to the instrument's detection limit, the βp models using a hyperbolic deadband are the recommended choice.

Choosing an Optimal β Factor for Relaxed Eddy Accumulation Applications Across Vegetated and non-Vegetated Surfaces

Accurately measuring the turbulent transport of reactive and conservative greenhouse gases, heat, and organic compounds between the surface and the atmosphere is critical for understanding trace gas exchange and its response to changes in climate and anthropogenic activities. The Relaxed Eddy Accumulation (REA) method enables measuring the land surface exchange when fast-response sensors are not available, broadening the suite of trace gases that can be investigated. This study evaluates a variety of different REA approaches with the goal of formulating universally applicable recommendations for an optimal choice of the β factor in combination with a suitable deadband. The β factor scales the concentration differences to the flux, and its choice is central to successfully using REA. Deadbands are used to select only certain turbulent motions to compute the flux. Observations were collected across three contrasting ecosystems offering stark differences in scalar transport and dynamics: A mid-latitude grassland ecosystem in Europe, a loose gravel surface of the Dry Valleys of Antarctica, and a spruce forest site in the European mid-range mountains. We tested a total of three different REA models for the β factor: The first method derives β0 based on a proxy for which high-frequency observations are available (sensible heat). The second method employs the approach of Baker et al. (1992), which computes βw solely based upon the vertical wind statistics. The third method uses a constant β derived from long-term averaging of the proxy-based β0 factor. Each β model was optimized with respect to deadband type and size before intercomparison. Concerning deadband form and size, we found an optimum in RMSE for linear deadbands with sizes of 0.5 and 0.9σw. These deadband widths make this method approximately equal to the use of a constant β factor. With respect to overall REA performance, we found that the βw and constant β from long-term measurements performed more robustly than the proxy-dependent approach β0. The latter model still performed well when scalar similarity between the proxy (here sensible heat) and the scalar of interest (here latent heat) show strong statistical correlation, i.e. during periods when the distribution and temporal behavior of sources and sinks were similar. With respect to sensitivity of β to atmospheric stability, we observed that β0 slightly increased with increasing stability parameter z / L when no deadband is applied, but this trend vanished with increasing deadband size. βw was independent of z / L. To explain these surprising differences, we separated the contribution of w' kurtosis to the flux uncertainty, which can be expressed by the median ratio of the REA flux compared to that from classical eddy covariance FREAFEC. Results showed a strong sensitivity to site conditions: While the kurtosis of w' seems to have no effect on the flux estimate at the grassland site, decreasing trends with increasing kurtosis can be observed for the loose gravel and forests sites and could explain the variability of FREAFEC within 10 %. For REA applications without deeper site-specific knowledge of the turbulent transport and degree of scalar similarity, we recommend using either the constant β or βw models when REA scalar fluxes are not expected to be limited by the detection limit of the instrument. For conditions close to the instrument detection limit, the β0 models using a hyperbolic deadband are the optimum choice.

Prerequisites for application of hyperbolic relaxed eddy accumulation on managed grasslands and alternative net ecosystem exchange flux partitioning

Relaxed eddy accumulation is still applied in ecosystem sciences for measuring trace gas fluxes. On managed grasslands, the length of time between management events and the application of relaxed eddy accumulation has an essential influence on the determination of the proportionality factor b and thus on the resulting flux. In this study this effect is discussed for the first time. Also, scalar similarity between proxy scalars and scalars of interest is affected until the ecosystem has completely recovered. Against this background, CO2 fluxes were continuously measured and 13CO2 isofluxes were determined with a high measurement precision on two representative days in summer 2010. Moreover, a common method for the partitioning of the net ecosystem exchange into assimilation and respiration based on temperature and light response was compared with an isotopic approach directly based on the isotope discrimination of the biosphere. This approach worked well on the grassland site and could enhance flux partitioning results by better reproducing the environmental conditions.

Application of relaxed eddy accumulation (REA) on managed grassland

Relaxed eddy accumulation is applied for measuring fluxes of trace gases for which there is a lack of sensors fast enough in their resolution for eddy-covariance. On managed grasslands, the length of time between management events and the application of relaxed eddy accumulation has an essential influence on the determination of the proportionality factor b and thereby on the resulting flux. In this study this effect is discussed for the first time. Also, scalar similarity between proxy scalars and scalars of interest is affected until the ecosystem has completely recovered. Against this background, CO2 fluxes were continuously measured and 13CO2 isofluxes were determined with a high measurement precision on two representative days in summer 2010. This enabled the evaluation of the 13CO2 flux portion of the entire CO2 flux, in order to estimate potential influences on tracer experiments in ecosystem sciences and to compare a common method for the partitioning of the net ecosystem exchange into assimilation and respiration based on temperature and light response with an isotopic approach directly based on the isotope discrimination of the biosphere.

Soil, plant, and transport influences on methane in a subalpine forest under high ultraviolet irradiance

Recent studies have demonstrated direct methane emission from plant foliage under aerobic conditions, particularly under high ultraviolet (UV) irradiance. We examined the potential importance of this phenomenon in a high-elevation conifer forest using micrometeorological techniques. Vertical profiles of methane and carbon dioxide in forest air were monitored every 2 h for 6 weeks in summer 2007. Day to day variability in above-canopy CH4 was high, with observed values in the range 1790 to 1910 nmol mol−1. High CH4 was correlated with high carbon monoxide and related to wind direction, consistent with pollutant transport from an urban area by a well-studied mountain-plain wind system. Soils were moderately dry during the study. Vertical gradients of CH4 were small but detectable day and night, both near the ground and within the vegetation canopy. Gradients near the ground were consistent with the forest soil being a net CH4 sink. Using scalar similarity with CO2, the magnitude of the summer soil CH4 sink was estimated at ~1.7 mg CH4 m−2 h−1, which is similar to other temperate forest upland soils. The high-elevation forest was naturally exposed to high UV irradiance under clear sky conditions, with observed peak UVB irradiance >2 W m−2. Gradients and means of CO2 within the canopy under daytime conditions showed net uptake of CO2 due to photosynthetic drawdown as expected. No evidence was found for a significant foliar CH4 source in the vegetation canopy, even under high UV conditions. While the possibility of a weak foliar source cannot be excluded given the observed soil sink, overall this subalpine forest was a net sink for atmospheric methane during the growing season.