Data treatment and corrections for estimating H₂O and CO₂ isotope fluxes from high-frequency observations

Abstract

Abstract. Current understanding of land-atmosphere exchange fluxes is limited by the fact that available observational techniques mainly quantify net fluxes, which are the sum of generally larger, bi-directional fluxes that partially cancel out. As a consequence, validation of gas exchange fluxes applied in models is challenging due to the lack of ecosystem-scale exchange flux measurements partitioned into soil, plant, and atmospheric components. One promising experimental method to partition measured turbulent fluxes uses the exchange-process-dependent isotopic fractionation of molecules like CO2 and H2O. When applying this method at a field scale, an isotope flux (δ-flux) needs to be measured. Here, we present and discuss observations made during the LIAISE 2021 field campaign using an Eddy Covariance (EC) system coupled to two laser spectrometers for high frequency measurement of the isotopic composition of H2O and CO2. This campaign took place in the summer of 2021 in the irrigated Ebro River basin near Mollerussa, Spain, embedded in a semi-arid region. We present a systematic procedure to scrutinise and analyse the measured values of central δ-flux variable. Our experimental data indicated a larger relative signal loss in the δ-fluxes of H2O compared to the net ecosystem flux of H2O, while this was not true for CO2. Furthermore, we find that mole fractions and isotope ratios measured with the same instrument can be offset in time by more than a minute for the H2O isotopologues. We discuss how such artifacts can be detected and how they impact flux partitioning. We argue that these effects are likely due to condensation of water on a cellulose filter in our inlet system. Furthermore, we show that these artifacts can be resolved using physically sound corrections for inlet delays and high frequency loss. After such corrections and verification’s are made, isotopic ecosystem scale flux partitioning can be used reliably to validate conceptual land-atmosphere exchange models.