基于GOES数据和弱约束变分的地表水热通量估算

Estimating of Land Surface Turbulent Fluxes Based on Weak Constraint Variational Method and GOES Data

基于弱约束的四维变分方法和陆面过程模式发展了一个地表温度的陆面数据同化系统。本文反演了地球静止业务环境卫星(Geostationary operational environmental satellite,GOES)的地表温度,并将反演的地表温度同化入陆面过程模式,改进陆面过程模式中地表水热通量的估算精度。以弱约束的变分方法通过在代价函数中增加弱约束项代替陆面过程模式动力方程组中存在的模式误差,构建新的代价函数并对其优化,从而改善模式中显热与潜热的估算精度。将GOES地表温度与实测地表温度进行比较,其均方根误差(RMSE)作为试验中的观测误差。选择美国通量网AmeriFlux中2个主要农业站点的气象和通量数据作为试验数据,对同化系统进行驱动和验证。结果表明同化后的地表温度、潜/显热估算精度均有提高。其中,各站地表温度RMSE平均仅为1 K,显热通量平均RMSE下降22 W/m2,潜热通量平均RMSE下降26 W/m2。因此结合陆面过程模式的弱约束变分方法同化GOES反演温度产品估算近地表水热通量的方法是有效且可行的。

Wilting is one of life features of plants responding to drought stress. Early identification of plant wilting is of importance for effective use of water in crop production. For this purpose, a laser scanner based on the principle of triangulation project was used to obtain 3D images of plants and the DC component of 2DFT was extracted as a wilting index. Four species, including zucchini, gourd, pumpkin and okra, were tested. The experimental results demonstrated that this index could identify the early wilting for each species and has a good linear correlation with the wihing degrees （R2 〉 0. 82）. In addition, the statistical models of multiple linear regression, which relates the wilting index to OvpD and the solar effective radiation, was proposed; and it can be used as the qualitative index of plant water deficit stress degree.