Abstract:

Based on the observed data in 2008 at Litang site over the alpine meadow surface on the east edge of Tibetan Plateau, the temporal variations of surface fluxes measured by an eddy-covariance system were analyzed, and the flux-variance relationships of normalized standard deviations of temperature, water vapor and CO₂ concentration as a function of stability parameter were determined. Sensible heat, latent heat and CO₂ fluxes were computed by using a flux-variance method, and they were compared with results from eddy-covariance measurements. The results indicate that there is a regular daily variation for surface fluxes, and seasonal variations are also significant. Latent heat flux is greater than sensible heat flux in a rainy season (May to September), whereas sensible heat flux is dominant in a dry season, and CO₂ flux is overwhelming during June to September. Under unstable conditions, the normalized variances of the scalars and stability parameter satisfy the similarity, and their universal functions also can be fitted according to the law of “-1/3 fractional power”. Similarity constants of heat, water vapor and CO₂ are 1.2, 1.4, and 0.9, respectively. Flux estimations are found to be in good agreement with observation. Among three parameters, estimation of sensible heat flux is better than that of other two fluxes. In general, this method overestimates the sensible heat flux and latent heat flux, while it underestimates CO₂ flux. Prediction accuracy of latent heat and CO₂ fluxes can be improved if predictions are obtained using the flux-variance method in combination with the measured sensible heat flux.

Key words: Underlying surface, Flux-variance method, Eddy-covariance method, Surface fluxes