Biases of CO₂ storage in eddy flux measurements in a forest pertinent to vertical configurations of a profile system and CO₂ density averaging

Abstract

[1] CO 2 storage in a 30-min period in a tall forest canopy often makes significant contributions to net ecosystem exchange (NEE) in the early morning and at night. When CO 2 storage is properly measured and taken into account, underestimations of NEE on calm nights can be greatly reduced. Using CO 2 data from a 12-level profile at the Missouri Ozark flux site (an oak-hickory forest in central Missouri, USA), we demonstrate that the lower canopy layer (below the thermal inversion) is a disproportionately large contributor to the total CO 2 storage. This is because time derivative of CO 2 density (Dc/Dt) generally shows increasing magnitude of mean and standard deviation with decreasing heights at night and from sunrise to 1000 h in both growing and dormant seasons. Effects of resolution and configuration in a profiling system on the accuracy of CO 2 storage estimation are evaluated by comparing subset profiles to the 12-level benchmark profile. It is demonstrated that the effectiveness of a profiling system in estimating CO 2 storage is not only determined by its number of sampling levels but, more importantly, by its vertical configuration. To optimize a profile, one needs to balance the influence of two factors, Dc/Dt and layer thickness, among all vertical sections within a forest. As a key contributor to the total CO 2 storage, the lower canopy requires a higher resolution in a profile system than the layers above. However, if the upper canopy is oversparsely sampled relative to the lower canopy, the performance of a profile system might be degraded since, in such a situation, the influence of layer thickness dominates over that of Dc/Dt. We also find that because of different level of complexity in canopy structure, more sampling levels are necessary at our site in order to achieve the same level of accuracy as at a boreal aspen site. These results suggest that in order to achieve an adequate accuracy in CO 2 storage measurements, the number of sampling levels in a profile and its design should be subject to the site properties, e.g., canopy architecture and the resulted thermodynamic and flow structures. If CO 2 density from a single profile is averaged in time and then used in assessing CO 2 storage to reduce random errors, biases associated with this averaging procedure become inevitable. Generally, larger window sizes used in averaging CO 2 density generate poorer estimates of CO 2 storage. If absolute errors are concerned, it appears that the more significant the CO 2 storage is during a period, the larger effects the averaging procedure has.

Errors in Net Ecosystem Exchanges of CO₂, Water Vapor, and Heat Caused by Storage Fluxes Calculated by Single-level Scalar Measurements Over a Rice Paddy

“…따라서 정확한 F S 를 얻기 위해서는 높이에 따라 달라지는 스 칼라의 변화율을 고려하여야 할 것이다. 산림과 같이 식생의 키가 크고 지형이 복잡한 경우에는 높이에 따 라 스칼라 변화량의 차이가 뚜렷이 나타난다 (Yang et al, 2007;de Araujo et al, 2010). …”

Improving the CO2 storage measurements with a single profile system in a tall-dense-canopy temperate forest

“…Some researchers assume that estimates of F s based on tower-top and profile measurements are interchangeable (Carrara et al, 2003;Hollinger et al, 1994;Knohl et al, 2003), thus the tower-top method is widely used when profile measurements are not available. However, others report that the tower-top method substantially underestimates F s compared with the profile system (Gu et al, 2012;Iwata et al, 2005;Yang et al, 2007Yang et al, , 1999. Then how many measurement levels are required to accurately quantify the CO 2 mixing ratio profile may depend on canopy complexity and height (Munger et al, 2012).…”

“…The F c can be a close estimation of NEE under ideal conditions (horizontal homogeneity, enough footprint, flat terrain or after appropriate axis choice, strong turbulent mixing, and steady state conditions) (Aubinet et al, 2012;Baldocchi, 2003). However, the conditions in field are rarely ideal, which leads to frequent underestimation of NEE due to ignoring considerable contributions of the advection and F s especially in tall-canopy forest ecosystems (Papale et al, 2006;Yang et al, 2007).…”

“…The F s can be significant at short time periods such as half-hours, particularly around sunrise, sunset, or at night (e.g., Dolman et al, 2002;Finnigan, 2006;Yang et al, 2007). Therefore, the F s should be taken into account because of potential error propagation in the gap-filling processing for annual NEE estimation (Papale et al, 2006).…”

“…Therefore, the F s should be taken into account because of potential error propagation in the gap-filling processing for annual NEE estimation (Papale et al, 2006). As long as the F s is properly tackled, potential underestimations of NEE on calm nights can be greatly reduced after the critical friction velocity filtering (Papale et al, 2006;Yang et al, 2007) or by using the data in the early evening period (van Gorsel et al, 2007).…”