Towards a Flux-Partitioning Procedure Based on the Direct Use of High-Frequency Eddy-Covariance Data

2014 ◽  
Vol 153 (2) ◽  
pp. 327-337 ◽  
Author(s):  
Luigi Palatella ◽  
Gianfranco Rana ◽  
Domenico Vitale
Keyword(s):  
Eddy Covariance ◽  
High Frequency ◽  
Flux Partitioning ◽  
Partitioning Procedure ◽  
Direct Use

scholarly journals Source partitioning of H<sub>2</sub>O and CO<sub>2</sub> fluxes based on high-frequency eddy covariance data: a comparison between study sites

2019 ◽  
Vol 16 (6) ◽  
pp. 1111-1132 ◽  
Author(s):  
Anne Klosterhalfen ◽  
Alexander Graf ◽  
Nicolas Brüggemann ◽  
Clemens Drüe ◽  
Odilia Esser ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Eddy Covariance ◽  
High Frequency ◽  
Canopy Height ◽  
Canopy Density ◽  
Partitioning Methods ◽  
Site Characteristics ◽  
Measurement Height ◽  
Study Sites ◽  
Source Partitioning

Abstract. For an assessment of the roles of soil and vegetation in the climate system, a further understanding of the flux components of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions and physiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we applied source partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) to high-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands, and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O and CO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration. We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modifications of both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulence characteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height). We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioning methods. SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioning of CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencies on estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoing longwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the quality of the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditional sampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages compared to the original method versions developed by Thomas et al. (2008). The performance of each partitioning approach was dependent on meteorological conditions, plant development, canopy height, canopy density, and measurement height. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopy height. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristics that increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.

scholarly journals Operative Use of Eddy Covariance Measurements: Are High Frequency Data Indispensable?

2013 ◽  
Vol 19 ◽  
pp. 293-302 ◽  
Author(s):  
D. Masseroni ◽  
C. Corbari ◽  
A. Ceppi ◽  
C. Gandolfi ◽  
M. Mancini
Keyword(s):  
Eddy Covariance ◽  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data ◽  
Eddy Covariance Measurements

scholarly journals Measurements and quality control of ammonia eddy covariance fluxes: a new strategy for high-frequency attenuation correction

2019 ◽  
Vol 12 (11) ◽  
pp. 6059-6078 ◽  
Author(s):  
Alexander Moravek ◽  
Saumya Singh ◽  
Elizabeth Pattey ◽  
Luc Pelletier ◽  
Jennifer G. Murphy
Keyword(s):  
Detection Limit ◽  
Eddy Covariance ◽  
Attenuation Correction ◽  
High Frequency ◽  
Direct Method ◽  
Time Response ◽  
Trace Gas ◽  
Horizontal Wind ◽  
Nh3 Adsorption ◽  
Flux Loss

Abstract. Measurements of the surface–atmosphere exchange of ammonia (NH3) are necessary to study the emission and deposition processes of NH3 from managed and natural ecosystems. The eddy covariance technique, which is the most direct method for trace gas exchange measurements at the ecosystem level, requires trace gas detection at a fast sample frequency and high precision. In the past, the major limitation for measuring NH3 eddy covariance fluxes has been the slow time response of NH3 measurements due to NH3 adsorption on instrument surfaces. While high-frequency attenuation correction methods are used, large uncertainties in these corrections still exist, which are mainly due to the lack of understanding of the processes that govern the time response. We measured NH3 fluxes over a corn crop field using a quantum cascade laser spectrometer (QCL) that enables measurements of NH3 at a 10 Hz measurement frequency. The 5-month measurement period covered a large range of environmental conditions that included both periods of NH3 emission and deposition and allowed us to investigate the time response controlling parameters under field conditions. Without high-frequency loss correction, the median daytime NH3 flux was 8.59 ng m−2 s−1 during emission and −19.87 ng m−2 s−1 during deposition periods, with a median daytime random flux error of 1.61 ng m−2 s−1. The overall median flux detection limit was 2.15 ng m−2 s−1, leading to only 11.6 % of valid flux data below the detection limit. From the flux attenuation analysis, we determined a median flux loss of 17 % using the ogive method. No correlations of the flux loss with environmental or analyser parameters (such as humidity or inlet ageing) were found, which was attributed to the uncertainties in the ogive method. Therefore, we propose a new method that simulates the flux loss by using the analyser time response that is determined frequently over the course of the measurement campaign. A correction that uses as a function of the horizontal wind speed and the time response is formulated which accounts for surface ageing and contamination over the course of the experiment. Using this method, the median flux loss was calculated to be 46 %, which was substantially higher than with the ogive method.

scholarly journals Technical note: Water vapour concentration and flux measurements with PTR-MS

2006 ◽  
Vol 6 (3) ◽  
pp. 5329-5355 ◽  
Author(s):  
C. Ammann ◽  
A. Brunner ◽  
C. Spirig ◽  
A. Neftel
Keyword(s):  
Water Vapour ◽  
Eddy Covariance ◽  
High Frequency ◽  
Reference System ◽  
Transfer Functions ◽  
Terrestrial Ecosystems ◽  
Water Vapour Flux ◽  
Water Vapour Concentration ◽  
Vapour Concentration ◽  
Vapour Flux

Abstract. The most direct approach for measuring the exchange of biogenic volatile organic compounds between terrestrial ecosystems and the atmosphere is the eddy covariance technique. It has been applied several times in the last few years using fast response proton-transfer-reaction mass spectrometry (PTR-MS). We present an independent validation of this technique by applying it to measure the water vapour flux in comparison to a common reference system comprising an infra-red gas analyser (IRGA). Water vapour was detected in the PTR-MS at mass 37 (atomic mass units) corresponding to the cluster ion H3O+·H2O. During a five-week field campaign at a grassland site, we obtained a non-linear but stable calibration function between the mass 37 signal and the reference water vapour concentration. With a correction of the high-frequency damping loss based on empirical ogive analysis, the eddy covariance water vapour flux obtained with the PTR-MS showed a very good agreement with the flux of the reference system. The application of the empirical ogive method for high-frequency correction led to significantly better results than using a correction based on theoretical spectral transfer functions. This finding is attributed to adsorption effects on the tube walls that are presently not included in the theoretical correction approach.

Water Flux Partitioning for Eddy Covariance Data

2020 ◽  
Author(s):  
Jacob Nelson
Keyword(s):  
Eddy Covariance ◽  
Sap Flow ◽  
Meteorological Data ◽  
Water Flux ◽  
Carbon Fluxes ◽  
Seasonal Cycles ◽  
Flow Data ◽  
The Core ◽  
Core Energy ◽  
Flux Partitioning

&lt;p&gt;Here we present an overview of methods for partitioning evapotranspiration (ET) from eddy covariance data. We focus on methods that are designed to use the core energy and carbon fluxes, as well as meteorological data, and do not require supplemental measurements or campaigns. A comparison of three such methods for estimating transpiration (T) showed high correlations between them (R&lt;sup&gt;2&lt;/sup&gt; of &amp;#160;daily T between 0.80 and 0.87) and higher correlations to daily stand T estimates from sap flow data (R&lt;sup&gt;2&lt;/sup&gt; between 0.58 and 0.66) compared to the tower ET (R2 = 0.49). However, the three methods show significant differences in magnitude, with T/ET values ranging from 45% to 77%. Despite the differences in magnitude, the methods show plausible patterns with respect to LAI, seasonal cycles, WUE, and VPD; moreover, they represent an improvement compared to using ET as a proxy for T even when filtering for days after rain. Finally, we outline practical aspects of applying the methods, such as how to apply the methods and code availability.&lt;/p&gt;

scholarly journals InnFLUX – an open-source code for conventional and disjunct eddy covariance analysis of trace gas measurements: an urban test case

2020 ◽  
Vol 13 (3) ◽  
pp. 1447-1465 ◽  
Author(s):  
Marcus Striednig ◽  
Martin Graus ◽  
Tilmann D. Märk ◽  
Thomas G. Karl
Keyword(s):  
Open Source ◽  
Eddy Covariance ◽  
High Frequency ◽  
Urban Canopy ◽  
Lag Time ◽  
Trace Gas ◽  
High Temporal Resolution ◽  
Eddy Covariance Method ◽  
Wide Range ◽  
Gas Measurements

Abstract. We describe and test a new versatile software tool for processing eddy covariance and disjunct eddy covariance flux data. We present an evaluation based on urban non-methane volatile organic compound (NMVOC) measurements using a proton transfer reaction quadrupole interface time-of-flight mass spectrometer (PTR-QiTOF-MS) at the Innsbruck Atmospheric Observatory. The code is based on MATLAB® and can be easily configured to process high-frequency, low-frequency and disjunct data. It can be applied to a wide range of analytical setups for NMVOC and other trace gas measurements, and is tailored towards the application of noisy data, where lag time corrections become challenging. Several corrections and quality control routines are implemented to obtain the most reliable results. The software is open source, so it can be extended and adjusted to specific purposes. We demonstrate the capabilities of the code based on a large urban dataset collected in Innsbruck, Austria, where three-dimensional winds and ambient concentrations of NMVOCs and auxiliary trace gases were sampled with high temporal resolution above an urban canopy. Concomitant measurements of 12C and 13C isotopic NMVOC fluxes allow testing algorithms used for determination of flux limits of detection (LOD) and lag time analysis. We use the high-frequency NMVOC dataset to generate a set of disjunct data and compare these results with the true eddy covariance method. The presented analysis allows testing the theory of disjunct eddy covariance (DEC) in an urban environment. Our findings confirm that the disjunct eddy covariance method can be a reliable tool, even in complex urban environments when fast sensors are not available, but that the increase in random error impedes the ability to detect small fluxes due to higher flux LODs.

scholarly journals A performance evaluation of despiking algorithms for eddy covariance data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Domenico Vitale
Keyword(s):  
Eddy Covariance ◽  
Data Center ◽  
High Frequency ◽  
Complex Dynamics ◽  
Simulated Data ◽  
Quality Standard ◽  
High Quality Standard ◽  
High Level ◽  
Essential Prerequisite ◽  
Better Than

AbstractSpike detection for raw high-frequency eddy covariance time series is a challenging task because of the confounding effect caused by complex dynamics and the high level of noise affecting such data. To cope with these features, a new despiking procedure rooted on robust functionals is proposed. By processing simulated data, it is demonstrated that the proposed procedure performs better than the existing algorithms and can be therefore considered as a candidate for the implementation in data center environmental monitoring systems, where the availability of automatic procedures ensuring a high quality standard of released products constitutes an essential prerequisite.

scholarly journals On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning

2012 ◽  
Vol 9 (7) ◽  
pp. 9829-9873
Author(s):  
G. Lasslop ◽  
M. Migliavacca ◽  
G. Bohrer ◽  
M. Reichstein ◽  
M. Bahn ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Eddy Covariance ◽  
Carbon Dioxide Flux ◽  
Empirical Models ◽  
Temperature Data ◽  
Flux Partitioning ◽  
Soil Temperatures ◽  
Temperature Observations ◽  
Partitioning Algorithms ◽  
The Impact

Abstract. Networks that merge and harmonise eddy-covariance measurements from many different parts of the world have become an important observational resource for ecosystem science. Empirical algorithms have been developed which combine direct observations of the net ecosystem exchange of carbon dioxide with simple empirical models to disentangle photosynthetic (GPP) and respiratory fluxes (Reco). The increasing use of these estimates for the analysis of climate sensitivities, model evaluation, and calibration demands a thorough understanding of assumptions in the analysis process and the resulting uncertainties of the partitioned fluxes. The semi-empirical models used in flux partitioning algorithms require temperature observations as input, but as respiration takes place in many parts of an ecosystem, it is unclear which temperature input – air, surface, bole, or soil at a specific depth – should be used. This choice is a source of uncertainty and potential biases. In this study we analysed the correlation between different temperature observations and nighttime NEE (which equals nighttime respiration) across FLUXNET sites to understand the potential of the different temperature observations as input for the flux partitioning model. We found that the differences in the correlation between different temperature data streams and nighttime NEE are small and depend on the selection of sites. We investigated the effects of the choice of the temperature data by running two flux partitioning algorithms with air and soil temperature. We found the time lag (phase shift) between air and soil temperatures explains the differences in the GPP and Reco estimates when using either air or soil temperatures for flux partitioning. The impact of the source of temperature data on other derived ecosystem parameters was estimated, and the strongest impact was found for the temperature sensitivity. Overall, this study suggests that the choice between soil or air temperature must be made on site-by-site basis by analysing the correlation between temperature and nighttime NEE. We recommend using an ensemble of estimates based on different temperature observations to account for the uncertainty due to the choice of temperature and to assure the robustness of the temporal patterns of the derived variables.

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