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Mesoscale cloud organization patterns

Mesoscale cloud organization patterns refer to large-scale arrangement of low clouds into morphological structures, which can range from 20 to 2000 km for entire pattern systems. These patterns, which influence the climate by affecting cloud water distribution, precipitation, and radiation balance, can evolve through multiple pathways depending on initial and changing environmental conditions  or internal cloud system processes itself.

To detect and classify these cloud organizations, researchers use techniques such as human-trained algorithms and supervised machine learning. These methods utilize satellite images to analyze cloud cover across different climate regimes. The classifications reveal a range of organized cloud structures with different characteristics, including mesoscale cellular convections (MCC), subdivided MCC's and trade-wind cloud patterns (Sugar, Gravel, Flower, Fish).

Understanding these cloud organization patterns is useful for improving the knowledge of low cloud feedback mechanisms and their role in climate dynamics.