Stepping vorticity covariance observation data processing method

Abstract

The invention discloses a stepping vorticity covariance observation data processing method. On the basis of obtained original observation data, and by adopting a segmented moving average processing mode, the whole average time period is divided into a plurality of sub-time periods which are overlapped on the time scale by an equal-length stepping time, and the number of calculation time periods isremarkably increased, and meanwhile, the original observation data is contained as much as possible, so that more calculation flux values are obtained; besides, when the gas exchange capacity in eachsub-time period is accumulated, the exchange capacity in the middle stepping time of each sub-time period is used as the exchange flux of the sub-time period for superposition, so that the superposition effect caused by accumulation of the whole time period is effectively avoided. According to the scheme, the abandoning rate of original observation data is remarkably reduced, and the data volumeof the obtained gas exchange flux is increased; and moreover, the vorticity covariance data processed by the method can improve the spatial-temporal resolution of vorticity covariance flux, and provides a more detailed and accurate basis for community-scale biogeochemical process research and carbon balance evaluation.

Description

technical field [0001] The invention belongs to the field of environmental science and carbon cycle research, and specifically relates to a step-by-step eddy covariance observation data processing method. Background technique [0002] The eddy covariance method is an international common method for in situ observation of the exchange of greenhouse gases between ecosystems and the atmosphere. Data post-processing methods can screen and eliminate the exchange flux under these unideal conditions, but the final flux data set will still have missing data. [0003] The traditional eddy covariance method needs to calculate the average exchange flux within a period of time by using the segmented average, divide the entire observation period into time periods with the same length and end-to-end links, and calculate the average exchange flux of this time period in each time period. Greenhouse gas exchange flux, and simple accumulation to obtain the total gaseous carbon budget. Using ...

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Problems solved by technology

[0005] Aiming at the shortcomings of the traditional eddy covariance method, such as the relatively high discarding rate of original data and the relatively small amount of gas exchange flux data obtained, the invention proposes a step-by-step eddy covariance observation data processing method

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