The long-term measurements of sensible and latent heat and CO2 fluxes (H, lE, and Fc) in various terrestrial ecosystems contribute to improve understanding of the biogeochemical cycle on interaction between the biosphere and atmosphere. The flux is measured by the eddy covariance method using not only reliable micrometeorological knowledge but also developed instrumental techniques. However, the eddy covariance measurements should include error (δ) as a statistical uncertainty because of diverse measurement conditions based against theoretical assumptions. Here, we take account of the relative error (φ) to evaluate the flux measurements with statistical analysis of rainfed paddy field in tropical crop regions. The least median of squares (LMS) method is applied to estimate the spatiotemporal descriptive statistics of relative error [formula omitted] because the frequency distribution of φ has more significant kurtosis and skewness than Gaussian. Consequently, we found that [formula omitted], which is similar to other studies, despite the seasonal variation and the difference in land cover. The characteristic of φ presented in this study could be of significant use in the quality control analysis of eddy covariance flux measurements.
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