论文标题
在Granger因果关系中，了解气候对植被的影响
Understanding Climate Impacts on Vegetation with Gaussian Processes in Granger Causality
论文作者
论文摘要
全球变暖导致我们地球上的前所未有的变化，具有很大的社会，经济和环境影响，尤其是随着生物燃料和食物的需求不断增长。评估气候对植被的影响是紧迫的需求。我们通过一种新型的非线性Granger因果（GC）方法来解决归因问题，并使用了遥感卫星产品，环境变量和气候变量的大量数据存档，这些时空空间在30多年中暂时了。我们通过在希尔伯特空间中明确考虑变量的交叉关系，并在高斯过程中使用协方差来概括内核Granger因果关系。该方法概括了线性和内核GC方法，并基于Rademacher复杂性具有更严格的性能界限。与以前的GC方法相比，在植被绿色上的降水和土壤水分的空间上，全球Granger足迹更为鲜明。
Global warming is leading to unprecedented changes in our planet, with great societal, economical and environmental implications, especially with the growing demand of biofuels and food. Assessing the impact of climate on vegetation is of pressing need. We approached the attribution problem with a novel nonlinear Granger causal (GC) methodology and used a large data archive of remote sensing satellite products, environmental and climatic variables spatio-temporally gridded over more than 30 years. We generalize kernel Granger causality by considering the variables cross-relations explicitly in Hilbert spaces, and use the covariance in Gaussian processes. The method generalizes the linear and kernel GC methods, and comes with tighter bounds of performance based on Rademacher complexity. Spatially-explicit global Granger footprints of precipitation and soil moisture on vegetation greenness are identified more sharply than previous GC methods.
