Uncertainty analysis of eddy covariance CO<sub>2</sub> flux measurements for different EC tower distances using an extended two-tower approach
Abstract. The use of eddy covariance CO2 flux measurements in data assimilation and other applications requires an estimate of the random uncertainty. In previous studies, the two-tower approach has yielded robust uncertainty estimates, but care must be taken to meet the often competing requirements of statistical independence (non-overlapping footprints) and ecosystem homogeneity when choosing an appropriate tower distance. The role of the tower distance was investigated with help of a roving station separated between 8 m and 34 km from a permanent EC grassland station. Random uncertainty was estimated for five separation distances with an extended two-tower approach which removed systematic differences of CO2 fluxes measured at two EC towers. This analysis was made for a dataset where (i) only similar weather conditions at the two sites were included and (ii) an unfiltered one. The extended approach, applied to weather-filtered data for separation distances of 95 m and 173 m gave uncertainty estimates in best correspondence with the independent reference method The introduced correction for systematic flux differences considerably reduced the overestimation of the two-tower based uncertainty of net CO2 flux measurements, e.g. caused by different environmental conditions at both EC towers. It is concluded that the extension of the two-tower approach can help to receive more reliable uncertainty estimates because systematic differences of measured CO2 fluxes which are not part of random error are filtered out.