MMCCT: A Multi-Medium Framework for Distributed Climate Intelligence and Bounded Local Climate Regulation
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Authors
Kookmin University
South China Agricultural University
Abstract
Climate monitoring still depends primarily on satellite remote sensing and fixed ground-station networks. These systems provide indispensable regional coverage and long time series, but they often lack the spatial and cross-medium resolution needed to identify micro-scale climate anomalies in dense urban districts, industrial interfaces, wetland edges, and other heterogeneous environments. Many such anomalies arise from coupled interactions among atmosphere, water, land surface, and human infrastructure rather than from isolated atmospheric change. This article proposes Multi-Medium Coordinated Climate Control Theory (MMCCT) as a conceptual framework for distributed environmental sensing and bounded cross-medium climate regulation. MMCCT defines climate as a four-medium system composed of the atmosphere, hydrosphere, land surface, and anthropogenic system. It then organizes climate intelligence through three layers: an environmental media system that identifies critical interface zones, a distributed sensing network combining UAV monitoring nodes, nano environmental sensors, and ground IoT stations, and an intelligence and coordination system for data fusion, anomaly detection, and adaptive intervention support. The framework advances a monitoring-to-governance sequence of sensing, diagnosis, coordinated response, and recursive feedback learning. Rather than claiming deterministic control over climate, MMCCT focuses on actionable local and regional variables such as shading, ventilation, irrigation, water retention, surface treatment, and emissions management. As a Methods & Frameworks contribution, the article formulates three research questions, specifies the theoretical mechanism of MMCCT, and outlines a validation strategy based on simulation modelling, UAV field experiments, and multi-source data integration. The framework offers a theoretical foundation for next-generation climate intelligence infrastructures in urban and regional environmental governance.
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No new datasets were generated or analyzed in this study. This article develops a conceptual and methodological framework based on the existing scholarly literature.
This work is licensed under a Creative Commons Attribution 4.0 International License.