• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.5-17
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• 2018

The standardized eddy covariance flux data processing in KoFlux has been updated, and its database has been amended accordingly. KoFlux data users have not been informed properly regarding these changes and the likely impacts on their analyses. In this paper, we have documented how the current structure of data processing in KoFlux has been established through the changes and improvements to ensure transparency, reliability and usability of the KoFlux database. Due to increasing diversity and complexity of flux site instrumentation and organization, we have re-implemented the previously ignored or simplified procedures in data processing (e.g., frequency response correction, stationarity test), and added new methods for $CH_4$ flux gap-filling and $CO_2$ flux correction and partitioning. To evaluate the effects of the changes, we processed the data measured at a flat and homogeneous paddy field (i.e., HPK) and a deciduous forest in complex and heterogeneous topography (i.e., GDK), and quantified the differences. Based on the results from our overall assessment, it is confirmed that (1) the frequency response correction (HPK: 11~18% of biases for annually integrated values, GDK: 6~10%) and the stationarity test (HPK: 4~19% of biases for annually integrated values, GDK: 9~23%) are important for quality control and (2) the minimization of the missing data and the choice of the appropriate driver (rather than the choice of the gap-filling method) are important to reduce the uncertainty in gap-filled fluxes. These results suggest the future directions for the data processing technology development to ensure the continuity of the long-term KoFlux database.