Temporally or spatially?Causation inference in Earth System Sciences  

地球系统科学中的因果推断:时间角度还是空间角度?

作　　者：Bingbo Gao Manchun Li Jinfeng Wang Ziyue Chen 高秉博;李满春;王劲峰;陈子悦(College of Land Science and Technology,China Agricultural University,Beijing 100083,China;School of Geography and Ocean Science,Nanjing University,Nanjing 210023,China;State Key Laboratory of Resources and Environmental Information Systems,Institute of Geographic Science&Nature Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Global and Earth System Sciences,Beijing Normal University,Beijing 100875,China)

机构地区：[1]College of Land Science and Technology,China Agricultural University,Beijing 100083,China [2]School of Geography and Ocean Science,Nanjing University,Nanjing 210023,China [3]State Key Laboratory of Resources and Environmental Information Systems,Institute of Geographic Science&Nature Resources Research,Chinese Academy of Sciences,Beijing 100101,China [4]College of Global and Earth System Sciences,Beijing Normal University,Beijing 100875,China

出　　处：《Science Bulletin》2022年第3期232-235,共4页科学通报（英文版）

基　　金：the National Key Research and Development Program of China(2021YFE0102300);the Natural Science Foundation of Beijing(8282031);the Fundamental Research Funds for the Central Universities。

摘　　要：The discovery of cause–effect relationships helps to understand the natural or physical mechanism[1].Causation inference is a key issue in many disciplines and has a long study history,especially in statistics,social,and biomedical sciences[2].In Earth System Sciences,the cause–effect relationship also plays a fundamental role and has drawn increasing interests.However,for spatially large-scale research,it is not feasible to design and conduct con-trolled experiments to reveal the cause–effect relationships.There-fore,causation inference from time series data has been frequently employed,under the assumption that the cause precedes the effect[3].While the temporal inference works effectively to identify most causation between variables,limitations remain.If the time series is not long enough to catch significant changes of causes and effects,some important cause–effect relationships may be neglected.This limitation is highlighted in Earth System Sciences,as the evolution of global changes may take an extreme long period to present discernible variations.For instance.The discovery of cause–effect relationships helps to understand the natural or physical mechanism[1].Causation inference is a key issue in many disciplines and has a long study history,especially in statistics,social,and biomedical sciences[2].In Earth System Sciences,the cause–effect relationship also plays a fundamental role and has drawn increasing interests.However,for spatially large-scale research,it is not feasible to design and conduct controlled experiments to reveal the cause–effect relationships.Therefore,causation inference from time series data has been frequently employed,under the assumption that the cause precedes the effect[3].While the temporal inference works effectively to identify most causation between variables,limitations remain.If the time series is not long enough to catch significant changes of causes and effects,some important cause–effect relationships may be neglected.This limitation is highlighted in Earth System Sciences,as the evolution of global changes may take an extreme long period to present discernible variations.

关 键 词：空间角度 因果推断 EFFECT 

分 类 号：P3[天文地球—地球物理学]