Improved eddy covariance flux based transpiration estimates at high relative humidity and comparison to sap flux

Author(s):  
Weijie Zhang ◽  
Jacob A. Nelson ◽  
Rafael Poyatos ◽  
Diego Miralles ◽  
Mirco Migliavacca ◽  
...  

<p>Eddy covariance (EC) directly measures evapotranspiration (ET), which consists of transpiration and evaporation (E) from the soil and other surfaces. For process understanding it is pivotal to separate ET into its components. Yet, its computation is highly sensitive to the methodology used to estimate T. Among the multiple methods proposed in recent years, T has been estimated from EC via the Transpiration Estimation Algorithm (TEA, Nelson et al., 2020), and from the sap flux measurement network SAPFLUXNET (Poyatos et al., 2020). These methods are applicable to a large number of measurement sites worldwide, and can help constrain the global estimates of the ratio of T to ET, T/ET. While EC measures water and carbon fluxes across ecosystems globally, water vapor flux measurements can be underestimated at high relative humidity (Ibrom et al., 2007; Mammarella et al., 2009) causing errors in the measured ET and propagating into the predicted T.</p><p>Here we report a method to detect and correct the high relative humidity error caused by attenuation of high frequency in water vapor measurements of a closed-path EC system. Our results of the comparison between present water use efficiency (WUE) with previous TEA-based WUE show that the corrected WUE is lower at high relative humidity than that derived from previous TEA at the sub-daily scale. Besides, we compare the corrected T estimates from EC to concurrent SAPFLUXNET sites to show an improved relationship between sap flux and EC based T, T/ET, and WUE. Finally, we explore the main abiotic factors, such as vapor pressure deficit, air temperature, and precipitation, influencing WUE estimated from different T estimation methodologies. These results provide an improved data-driven approach to the ongoing research on ET partitioning and the factors influencing the WUE across ecosystems globally.</p><p> </p><p>Ibrom, A. et al. (2007) ‘Strong low-pass filtering effects on water vapour flux measurements with closed-path eddy correlation systems’, Agricultural and Forest Meteorology. doi.org/10.1016/j.agrformet.2007.07.007.</p><p>Mammarella, I. et al. (2009) ‘Relative humidity effect on the high-frequency attenuation of water vapor flux measured by a closed-path eddy covariance system’, Journal of Atmospheric and Oceanic Technology. doi.org/10.1175/2009JTECHA1179.1.</p><p>Nelson, J. A. et al. (2020) ‘Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites’, Global Change Biology. doi: 10.1111/gcb.15314.</p><p>Poyatos, R. et al. (2020) ‘Global transpiration data from sap flow measurements: the SAPFLUXNET database’, Earth System Science Data. doi:10.5194/essd-2020-227.</p>

2015 ◽  
Vol 8 (10) ◽  
pp. 4123-4131 ◽  
Author(s):  
J. B. Wu ◽  
X. Y. Zhou ◽  
A. Z. Wang ◽  
F. H. Yuan

Abstract. Eddy covariance using infrared gas analyzes has been a useful tool for gas exchange measurements between soil, vegetation and the atmosphere. So far, comparisons between the open- and closed-path eddy covariance (CP) system have been extensively made on CO2 flux estimations, while lacking in the comparison of water vapor flux estimations. In this study, the specific performance of water vapor flux measurements of an open-path eddy covariance (OP) system was compared against a CP system over a tall temperate forest in northeastern China. The results show that the fluxes from the OP system (LEop) were generally greater than the LEcp though the two systems shared one sonic anemometer. The tube delay of closed-path analyzer depended on relative humidity, and the fixed median time lag contributed to a significant underestimation of LEcp between the forest and atmosphere, while slight systematic overestimation was also found for covariance maximization method with single broad time lag search window. After the optimized time lag compensation was made, the average difference between the 30 min LEop and LEcp was generally within 6.0 %. Integrated over the annual cycle, the CP system yielded a 5.1 % underestimation of forest evapotranspiration as compared to the OP system measurements (493 vs. 469 mm yr−1). This study indicates the importance to estimate the sampling tube delay accurately for water vapor flux calculations with closed-path analyzers, and it also suggests that some of the imbalance of the surface energy budget in flux sites is possibly caused by the systematic underestimation of water vapor fluxes measured with closed-path eddy covariance systems.


2015 ◽  
Vol 8 (5) ◽  
pp. 4711-4736
Author(s):  
J. B. Wu ◽  
X. Y. Zhou ◽  
A. Z. Wang ◽  
F. H. Yuan

Abstract. Eddy covariance using infrared gas analyses has been a useful tool for gas exchange measurements between soil, vegetation and atmosphere. So far, comparisons between the open- and closed-path eddy covariance (CP) system have been extensively made on CO2 flux estimations, while lacking in the comparison of water vapor flux estimations. In this study, the specific performance of water vapor flux measurements of an open-path eddy covariance (OP) system was compared against a CP system over a tall temperate forest in Northeast China. The results show that the fluxes from the OP system (LEop) were generally greater than the (LEcp though the two systems shared one sonic anemometer. The tube delay of closed-path analyser depended on relative humidity, and the fixed median time lag contributed to a significant underestimation of (LEcp between the forest and atmosphere, while slight systematic overestimation was also found for covariance maximization method with single broad time lag search window. After the optimized time lag compensation was made, the average difference between the 30 min (LEop and (LEcp was generally within 6%. Integrated over the annual cycle, the CP system yielded a 5.1% underestimation of forest evapotranspiration as compared to the OP system measurements (493 vs. 469 mm yr−1). This study indicates the importance to estimate the sampling tube delay accurately for water vapor flux calculations with closed-path analysers, and it also suggests that when discuss the energy balance closure problem in flux sites with closed-path eddy covariance systems, it has to be aware that some of the imbalance is possibly caused by the systematic underestimation of water vapor fluxes.


2009 ◽  
Vol 26 (9) ◽  
pp. 1856-1866 ◽  
Author(s):  
Ivan Mammarella ◽  
Samuli Launiainen ◽  
Tiia Gronholm ◽  
Petri Keronen ◽  
Jukka Pumpanen ◽  
...  

Abstract In this study the high-frequency loss of carbon dioxide (CO2) and water vapor (H2O) fluxes, measured by a closed-path eddy covariance system, were studied, and the related correction factors through the cospectral transfer function method were calculated. As already reported by other studies, it was found that the age of the sampling tube is a relevant factor to consider when estimating the spectral correction of water vapor fluxes. Moreover, a time-dependent relationship between the characteristic time constant (or response time) for water vapor and the ambient relative humidity was disclosed. Such dependence is negligible when the sampling tube is new, but it becomes important already when the tube is only 1 yr old and increases with the age of the tube. With a new sampling tube, the correction of water vapor flux measurements over a Scots pine forest in Hyytiälä, Finland, amounted on average to 7%. After 4 yr the correction increased strongly, ranging from 10%–15% during the summer to 30%–40% in wintertime, when the relative humidity is typically high. For this site the effective correction improved the long-term energy and water balance. Results suggest that the relative humidity effect on high-frequency loss of water vapor flux should be taken into account and that the effective transfer function should be estimated experimentally at least once per year. On the other hand, this high correction can be avoided by a correct choice and periodic maintenance of the eddy covariance system tube, for example, by cleaning or changing it at least once per year.


2012 ◽  
Vol 5 (1) ◽  
pp. 351-384 ◽  
Author(s):  
R. V. Hiller ◽  
C. Zellweger ◽  
A. Knohl ◽  
W. Eugster

Abstract. Recently, instruments became available on the market that provide the possibility to perform eddy covariance flux measurements of CH4 and many other trace gases, including the traditional CO2 and H2O. Most of these instruments employ laser spectroscopy, where a cross-sensitivity to H2O is frequently observed leading to an increased dilution effect. Additionally, sorption processes at the intake tube walls modify and delay the observed H2O signal in closed-path systems more strongly than the signal of the sampled trace gas. Thereby, a phase shift between the trace gas and H2O fluctuations is introduced that dampens the H2O flux observed in the sampling cell. For instruments that do not provide direct H2O measurement in the sampling cell, transfer functions from externally measured H2O fluxes are needed to estimate the effect of H2O on trace gas flux measurements. The effects of cross-sensitivity and the damping are shown for an eddy covariance setup with the Fast Greenhouse Gas Analyzer (FGGA, Los Gatos Research Inc.) that measures CO2, CH4, and H2O fluxes. This instrument is technically identical with the Fast Methane Analyzer (FMA, Los Gatos Research Inc.) that does not measure H2O concentrations. Hence, we used measurements from a FGGA to derive a modified correction for the FMA accounting for dilution as well as phase shift effects in our instrumental setup. With our specific setup for eddy covariance flux measurements, the cross-sensitivity counteracts the damping effects, which compensate each other. Hence, the new correction only deviates very slightly from the traditional Webb, Pearman, and Leuning density correction, which is calculated from separate measurements of the atmospheric water vapor flux.


Author(s):  
Andreas Giez ◽  
Gerhard Ehret ◽  
Ronald L. Schwiesow ◽  
Kenneth J. Davis ◽  
Donald H. Lenschow

1991 ◽  
pp. 245-260 ◽  
Author(s):  
R. L. Desjardins ◽  
J. I. MacPherson

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