Abstract
Airborne eddy covariance (EC) is one of the most effective ways to directly measure turbulent flux at a regional scale. This study aims to find the optimum spatial window length for turbulent heat fluxes calculation from airborne eddy covariance measurements under near neutral to unstable atmospheric stability conditions, to reduce the negative influences from mesoscale turbulence, and to estimate local meaningful turbulent heat fluxes accurately. The airborne flux measurements collected in 2008 in the Netherlands were used in this study. Firstly, the raw data was preprocessed, including de-spike, segmentation, and stationarity test. The atmospheric stability conditions were classified as near neutral, moderately unstable, or very unstable; the stable condition was excluded. Secondly, Ogive analysis for turbulent heat fluxes from all available segmentations of the airborne measurements was used to determine the possible window length range. After that, the optimum window length for turbulent heat flux calculations was defined based on the analysis of all possible window lengths and their uncertainties. The results show that the choice of the optimum window length strongly depends on the atmospheric stability conditions. Under near neutral conditions, local turbulence is mixed insufficiently and vulnerable to heterogeneous turbulence. A relatively short window length is needed to exclude the influence of mesoscale turbulence, and we found the optimum window length ranges from 2000 m to 2500 m. Under moderately unstable conditions, the typical scale of local turbulence is relative large, and the influence of mesoscale turbulence is relatively small. We found the optimum window length ranges from 3900 m to 5000 m. Under very unstable conditions, large convective eddies dominate the transmission of energy so that the window length needs to cover the large eddies with large energy transmission. We found the optimum window length ranges from 4500 m to 5000 m. This study gives a comprehensive methodology to determine the optimizing window length in order to compromise a balance between the accuracy and the surface representativeness of turbulent heat fluxes from airborne EC measurements.
Highlights
Information on the heat and moisture flux exchanges between the land surface and the atmosphere is crucial for a better understanding of the role of terrestrial ecosystems in the global climate system
The main purpose of this study was to find the optimum window length for heat flux calculation under near neutral to unstable atmospheric stability conditions, which is meaningful for depicting the flux contribution from local land surfaces
The results of the Ogive classification indicate that the reference window length of 2 km cannot capture a reliable estimate of the turbulent heat fluxes in any of the atmospheric stability conditions
Summary
Information on the heat and moisture flux exchanges between the land surface and the atmosphere is crucial for a better understanding of the role of terrestrial ecosystems in the global climate system. The tower-based eddy covariance (EC) method provides turbulent flux measurements with good temporal samples (e.g., every 30 min) but usually with a small spatial representative (i.e., footprint, typically less than 1 km2) [3,4]. If the spectral gap is unclear or absent, other methods such as “ensemble block averaging” or statistical error analysis can be used to find the integral interval [18,19,20] These methods cannot decompose the turbulent flow, and the decomposition of turbulence is very important for studying the distribution of turbulent energy among the different wavelengths. Numerous researchers have carried out studies to determine the optimum averaging periods over different sites, and the results revealed that the traditional 30 min averaging time should be adjusted or site-specific to capture all fluxes taking place on a field scale and to avoid the influence of low-frequency turbulence [10,12,18,23,24]
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