Options to correct local turbulent flux measurements for large-scale fluxes using an approach based on large-eddy simulation

The eddy-covariance method provides the most direct estimates for fluxes between ecosystems and the atmosphere. However, dispersive fluxes can occur in the presence of secondary circulations, which can inherently not be captured by such single-tower measurements. In this study, we present options to correct local flux measurements for such large-scale transport based on a non-local parametric model that has been developed from a set of idealized large-eddy simulations. This method is tested for three real-world sites (DK-Sor, DE-Fen, and DE-Gwg), representing typical conditions in the mid-latitudes with different measurement heights, different terrain complexities, and different landscape-scale heterogeneities. Two ways to determine the boundary-layer height, which is a necessary input variable for modelling the dispersive fluxes, are applied, which are either based on operational radio soundings and local in situ measurements for the flat sites or from backscatter-intensity profiles obtained from co-located ceilometers for the two sites in complex terrain. The adjusted total fluxes are evaluated by assessing the improvement in energy balance closure and by comparing the resulting latent heat fluxes with evapotranspiration rates from nearby lysimeters. The results show that not only the accuracy of the flux estimates is improved but also the precision, which is indicated by RMSE values that are reduced by approximately 50 %. Nevertheless, it needs to be clear that this method is intended to correct for a bias in eddy-covariance measurements due to the presence of large-scale dispersive fluxes. Other reasons potentially causing a systematic underestimated or overestimation, such as low-pass filtering effects and missing storage terms, still need to be considered and minimized as much as possible. Moreover, additional transport induced by surface heterogeneities is not considered.

Advances in the True Eddy Accumulation Method: New theory, implementation, and field results

The true eddy accumulation method (TEA) provides direct measurements of ecosystem-level fluxes for a wide range of atmospheric constituents. TEA utilizes conditional sampling to overcome the requirement for a fast sensor response usually demanded by the state-of-the-art eddy covariance method (EC). However, the assumptions and conditions required for the TEA method are often not met. Here we explore the limitations caused by the assumption of zero mean vertical wind velocity during the averaging interval and by the fixed accumulation interval. We extend the theory of TEA method to non-zero vertical wind velocity by employing information about the scalar transport. We further derive a new method with adaptive time varying accumulation intervals. The new method, termed short-time eddy accumulation (STEA), was successfully implemented and deployed to measure CO2 fluxes over an agricultural field in Braunschweig, Germany. The measured fluxes matched very well against a conventional EC system (slope of 1.05, R2 of 0.87). We provide a detailed description of the setup and operation of the STEA system in the flow-through mode, devise an empirical correction for the effect of buffer volumes, and describe the important considerations for the successful operation of the STEA method. The new theory developments reduce the bias and uncertainty in the measured fluxes and create new ways to design eddy accumulation systems with finer control over sampling and accumulation. The results encourage the application of TEA and STEA for measuring fluxes of more challenging atmospheric constituents such as reactive species as well as other constituents where no fast gas analyzers are available.

Intrinsic non-stationarity of carbon dioxide turbulent fluxes in the urban boundary layer

Stationarity is a critical assumption in the eddy-covariance method that is widely used to calculate turbulent fluxes. Many methods have been proposed to diagnose non-stationarity attributed to external non-turbulent flows. In this paper, we focus on intrinsic non-stationarity (IN) attributed to turbulence randomness. The detrended fluctuation analysis is used to quantify IN of CO2 turbulent fluxes in the downtown of Beijing. Results show that the IN is widespread in CO2 turbulent fluxes and is a small-scale phenomenon related to the inertial sub-range turbulence. The small-scale IN of CO2 turbulent fluxes can be simulated by the Ornstein-Uhlenbeck (OU) process as a first approximation. Basing on the simulation results, we find that the average time should be greater than 27 s to avoid the effects of IN. Besides, the non-stationarity diagnosis methods that do not take into account IN would possibly make a wrong diagnosis with some parameters.

Evaluation of Evapotranspiration in Brazilian Cerrado Biome Simulated with the SWAT Model

Evapotranspiration represents a significant part on the water balance and, thus, the correct evaluation of this hydrological parcel is relevant when modeling a watershed. The objective of this work is to evaluate the Soil and Water Assessment Tool (SWAT) model’s capability in adequately simulating evapotranspiration in a watershed with predominance of the Brazilian Cerrado biome. Hydrological modeling of the Gama watershed located in the Federal District, which has 57.5% of its total area covered by pristine Cerrado, was conducted. Hydrometeorological and turbulent flow variables have been monitored in weather station and Eddy Covariance (EC) tower, respectively. SWAT simulations were performed for potential evapotranspiration methods: Hargreaves (H), Priestley–Taylor (PT) and Penman–Monteith (PM). Modified versions of SWAT for estimating actual (ET) by Strauch and Volk (2013) (SV) and Arroio Junior (2016) (AR) were also tested. The calibration and verification of the SWAT model, in terms of daily flow, were carried out using a Particle Swarm Optimization algorithm, and fair results were obtained with all the methods evaluated. The actual evapotranspiration (ET) simulated with SWAT (ETsim) using the PM, PT, H, SV and AR methods for a Cerrado hydrological response unit (HRU) were evaluated and compared with the ET obtained using the turbulent flow (Eddy Covariance) method (ETobs). Comparing ETobs and ETsim results, the PM method showed the best fitness and the H and PT methods showed better fit for the dry and the rainy periods, respectively. Although representing an advance on ET modeling, the SV and AR modifications did not improve the response in terms of simulation of the studied area.

Options to correct local turbulent flux measurements for large-scale fluxes using a LES-based approach

The eddy-covariance method provides the most direct estimates for fluxes between ecosystems and the atmosphere. However, dispersive fluxes can occur in the presence of secondary circulations, which can inherently not be captured by such single-tower measurements. In this study, we present options to correct local flux measurements for such large-scale transport based on a non-local parametric model that has been developed from a set of idealized LES runs for three real-world sites. The test sites DK-Sor, DE-Fen, and DE-Gwg, represent typical conditions in the mid-latitudes with different measurement height, different terrain complexity and different landscape-scale heterogeneity. Different ways to determine the boundary-layer height, which is a necessary input variable for modelling the dispersive fluxes, are applied, either from operational radio-soundings and local in-situ measurements for the flat site or from backscatter-intensity profile obtained from collocated ceilometers for the two sites in complex terrain. The adjusted total fluxes are evaluated by assessing the improvement in energy balance closure and by comparing the resulting latent heat fluxes with evapotranspiration rates from nearby lysimeters. The results show that not only the accuracy of the flux estimates is improved but also the precision, which is indicated by RMSE values that are reduced by approximately 50 %. Nevertheless, it needs to be clear that this method is intended to correct for a bias in eddy-covariance measurements due to the presence of large-scale dispersive fluxes. Other reasons potentially causing a systematic under- or overestimation, such as low-pass filtering effects and missing storage terms, still need to be considered and minimized as much as possible. Moreover, additional transport induced by surface heterogeneities is not considered.