The paper presents the results of a study of seasonal and interannual variability of CO2 concentration above the moist tropical forest in southern Vietnam. Experimental data were collected during year-long observation of CO2 directly in the forest from 2012 to 2017. All data were obtained through the use of an air intake tube, placed on a metal tower at a height of 46 m and connected to a Li-Cor 820 gas analyzer (Li-Cor Inc., USA) located in a building at the foot of the tower. The values of the concentration were recorded with a resolution of 1 second; for further analysis, all data was averaged to 0.5 h values. Statistical processing based on the Fourier analysis allowed to evaluate the main characteristics of the annual distribution of CO2 concentration, such as the amplitude and phase, as well as to analyze their variability over the years. The results of the study showed a presence of a well-determined annual course of CO2 concentration above the canopy of the moist tropical forest.
The article is devoted to the problem of recovering gaps in the data series of experimental long-term
continuous high-frequency observations of carbon dioxide concentration and air temperature. The study was
carried out on the example of the results of observations of an automatic ecological and climatic station
located in a tropical monsoon forest on the territory of south Vietnam (Dong Nai Nature Reserve). Omissions
in the series of observations, as a rule, are random and are caused by technical malfunctions of the instrument
base. Correctly recovered series of observations allow us to estimate the temporal variability of the observed
parameters on different time scales. Within the framework of this study, options for recovering the continuity
of time series based on the methods of mathematical statistics - autoregression (ARIMA) and the method of
linear prediction were considered. A comparative analysis of the accuracy of restoring omissions by various
methods is given.
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