Temporal and Spatial Matching in Human‐Earth System Model Coupling

Abstract

In the use of integrated assessment models to determine how the economy is affected by climate change, the bidirectional coupling of Earth system model with the integrated assessment model is needed. In the context of coupled problems in human‐Earth systems, two issues persist: spatial and temporal scale matching. For spatial scale matching, this paper proposes the area weight conversion method, a gridding method for calculations to accord with the grid of the Earth's system mode, where administrative data cells are transformed into grid data by “pregridding” and “postgridding.” For temporal scale matching, the temporal scale of the economic statistics was shortened to 1 year to render it consistent with the Earth system model. Using the area weight conversion method, grid processing was performed in terms of population and Gross Domestic Product for all provinces of China and every country of the world, respectively. The results showed that the characteristics of gridding population and Gross Domestic Product data were consistent with their actual distributions, that is, the credibility of gridding was high. The temporal matching treatment refined to the year and the spatial matching treatment following gridding met the overall requirements of coupling. Moreover, they provide a foundation for the coupling of the human‐Earth system model.

A brief review of the coupled human-Earth system modeling: Current state and challenges

“…This inevitably leads to some mismatched issues in data transfer, particularly the mismatching of the temporal and spatial scales between different components in the coupling system. For example, the typical IAMs are built based on countries or more aggregated regions with a 5- or 10-year time step (Chou et al, 2018), whereas the ESMs are constructed on a grid scale with a variety of time steps ranging from minutes to years or even centuries (Flato, 2011). On the premise of no big changes in structures of the involved submodels, it is not easy to reconcile the mismatched scales via specialized spatial and temporal downscaling of one submodel outputs to provide inputs for another submodel.…”

A system dynamics-based synergistic model of urban production-living-ecological systems: An analytical framework and case study

“…Generally, existing studies on the coordination of production-living-ecological functions have been performed from a systematic perspective. However, these have been primarily focused on the internal mechanisms of human-land relationship coordination [ 33 , 34 ], and strategies to promote the coordination, balance and sustainable development of geographical environment and human well-being [ 35 , 36 ]. Meanwhile, research particularly focused on the coordination between human and "production-living-ecological" functions have remained lacking, in which only few studies have attempted to combine only two of the "production-living-ecological" functions, and urban ecology, production, living functions.…”

Spatiotemporal Differentiation and Coupling Coordination Relationship of the Production–Living–Ecological Function at County Scale: A Case Study of Jiangsu Province

“…This interaction is not unidirectional but constitutes an interdependent system [4]. In addition, the complexity of this interaction Land 2023, 12, 2027 2 of 21 is reflected not only in resource utilization and transformation of the environment [5] but also in its shaping of human social structures and development patterns [6].…”