scholarly journals Determining the Isotopic Composition of Surface Water Vapor Flux From High-Frequency Observations Using Flux-Gradient and Keeling Plot Methods

2020 ◽  
Author(s):  
Yongbo Hu ◽  
Wei Xiao ◽  
Zhongwang Wei ◽  
Lisa Welp ◽  
Xuefa Wen ◽  
...  
2020 ◽  
Vol 20 (19) ◽  
pp. 11435-11449
Author(s):  
Shaakir Shabir Dar ◽  
Prosenjit Ghosh ◽  
Ankit Swaraj ◽  
Anil Kumar

Abstract. The stable oxygen and hydrogen isotopic composition of water vapor over a water body is governed by the isotopic composition of surface water and ambient vapor, exchange and mixing processes at the water–air interface, and the local meteorological conditions. These parameters form inputs to the Craig–Gordon models, used for predicting the isotopic composition of vapor produced from the surface water due to the evaporation process. In this study we present water vapor, surface water isotope ratios and meteorological parameters across latitudinal transects in the Southern Ocean (27.38–69.34 and 21.98–66.8∘ S) during two austral summers. The performance of Traditional Craig–Gordon (TCG) (Craig and Gordon, 1965) and the Unified Craig–Gordon (UCG) (Gonfiantini et al., 2018) models is evaluated to predict the isotopic composition of evaporated water vapor flux in the diverse oceanic settings. The models are run for the molecular diffusivity ratios suggested by Merlivat (1978), Cappa et al. (2003) and Pfahl and Wernli (2009), referred to as MJ, CD and PW, respectively, and different turbulent indices (x), i.e., fractional contribution of molecular vs. turbulent diffusion. It is found that the UCGx=0.8MJ, UCGx=0.6CD, TCGx=0.6MJ and TCGx=0.7CD models predicted the isotopic composition that best matches with the observations. The relative contribution from locally generated and advected moisture is calculated at the water vapor sampling points, along the latitudinal transects, assigning the representative end-member isotopic compositions, and by solving the two-component mixing model. The results suggest a varying contribution of the advected westerly component, with an increasing trend up to 65∘ S. Beyond 65∘ S, the proportion of Antarctic moisture was found to be prominent and increasing linearly towards the coast.


2021 ◽  
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>


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.


2011 ◽  
Vol 284 (5) ◽  
pp. 1295-1298 ◽  
Author(s):  
Luca Fiorani ◽  
Francesco Colao ◽  
Antonio Palucci ◽  
Davod Poreh ◽  
Alessandro Aiuppa ◽  
...  

2021 ◽  
Author(s):  
Hongmei Ren ◽  
Ang Li ◽  
Pinhua Xie ◽  
Zhaokun Hu ◽  
Jin Xu ◽  
...  

<p>      Water vapor transport affects regional precipitation and climate change. The measurement of precipitable water and water vapor flux is of great significance to the study of precipitation and water vapor transport. In the study, a new method of computing the precipitable water and estimating the water vapor transport flux using multi-axis differential optical absorption spectroscopy (MAX-DOAS) were presented. The calculated precipitable water and water vapor flux were compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the correlation coefficient of the precipitable water, the zonal and meridional water vapor flux and ECMWF are r≥0.92, r=0.77 and r≥0.89, respectively. The seasonal and diurnal climatologies of precipitable water and water vapor flux in the coastal (Qingdao) and inland (Xi’an) cities of China using this method were analyzed from June 1, 2019 to May 31, 2020. The results indicated that the seasonal and diurnal variation characteristics of the precipitable water in the two cities were similar. The zonal fluxes of the two cities were mainly transported from west to east, Qingdao's meridional flux was mainly transported to the south, and Xi'an was mainly transported to the north. The results also indicated that the water vapor flux transmitting belts appear near 2km and 1.4km above the surface in Qingdao and appeared around 2.8km, 1.6km and 1.0km in Xi'an. </p>


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