Climate paleogeography knowledge graph and deep time paleoclimate classifications

古气候学 古地理学 气候变化 可比性 气候模式 很深的时间 数据科学 气候学 地质学 计算机科学 古生物学 数学 海洋学 火山作用 构造学 组合数学
作者
Chenmin Yu,Laiming Zhang,Mingcai Hou,Jianghai Yang,Hanting Zhong,Chengshan Wang
出处
期刊:Geoscience frontiers [Elsevier]
卷期号:14 (5): 101450-101450 被引量:11
标识
DOI:10.1016/j.gsf.2022.101450
摘要

The climate paleogeography, especially the climate classifications, helps to interpret the global and regional climate changes and intuitively compare the climate conditions in different regions. However, the application of climate classification in deep time (i.e., climate paleogeography) is prohibited due to the usually qualitatively constrained paleoclimate and the inconsistent descriptions and semantic heterogeneity of the climate types. In this study, a climate paleogeography knowledge graph is established under the framework of the Deep-Time Digital Earth program (DDE). The hierarchical knowledge graph consists of five paleoclimate classifications based on various strategies. The classifications are described and their strengths and weaknesses are fully evaluated in four aspects: "simplicity, applicability, quantifiability, and comparability". We also reconstruct the global climate distributions in the Late Cretaceous according to these classifications. The results are compared and the relationships among these climate types in different classifications are evaluated. Our study unifies scientific concepts from different paleoclimate classifications, which provides an important theoretical basis for the application of paleoclimate classifications in deep time.

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