As well known, the methods of remote sensing and Bowen Ratio for retrieving surface flux are based on energy balance closure; however, in most cases, surface energy observed in experiment is lack of closure. There are two main causes for this: one is from the errors of the observation devices and the differences of their observational scale; the other lies in the effect of horizontal advection on the surface flux measurement. Therefore, it is very important to estimate the effects of horizontal advection quantitatively. Based on the local advection theory and the surface experiment, a model has been proposed for correcting the effect of horizontal advection on surface flux measurement, in which the relationship between the fetch of the measurement and pixel size for remote sensed data was considered. By means of numerical simulations, the sensitivities of the main parameters in the model and the scaling problems of horizontal advection were analyzed. At last, by using the observational data acquired in agricultural field with relatively homogeneous surface, the model was validated.
We discuss the determination of membership of 42 open clusters. Our analysis shows that Vasilevskis' mathematical model can be reasonably applied to this case. Our improved version of Sanders' method and our definition of cluster member based on the principles of discriminatory analysis effectively exclude stars of low probabilities. It is important in the study of open cluster to use only those with high probabilities. The effectiveness of the statistical method is closely related to the velocity distributions of the member and field stars. For fields where the error rate is high, it is better to combine other data than proper motion in determining membership. 相似文献
A nutrient dynamic model coupled with a 3D physical model has been developed to study the annual cycle of phytoplankton production in the Yellow Sea. The biological model involves interactions between inorganic nitrogen (nitrate and ammonium), phosphate and phytoplankton biomass. The model successfully reproduces the main features of phytoplankton-nutrient variation and dynamics of production. 1. The well-mixed coastal water is characterized by high primary production, as well as high new production. 2. In summer, the convergence of tidal front is an important hydrodynamic process, which contributes to high biomass at frontal areas. 3. The evolution of phytoplankton blooms and thermocline in the central region demonstrate that mixing is a dominant factor to the production in the Yellow Sea. In this simulation, nitrate- and ammonium-based productions are estimated regionally and temporally. The northern Yellow Sea is one of the highly ranked regions in the Yellow Sea for the capability of fixing carbon and nitrogen. The annual averaged f-ratio of 0.37 indicates that regenerated production prevails over the Yellow Sea. The result also shows that phosphate is the major nutrient, limiting phytoplankton growth throughout the year and it can be an indicator to predict the bloom magnitude. Finally, the relative roles of external nutrient sources have been evaluated, and benthic fluxes might play a significant role in compensating 54.6% of new nitrogen for new production consumption. 相似文献
