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Cloud MacRoscopic Organization: Order Emerging from Randomness : Volume 11, Issue 1 (17/01/2011)

By Yuan, T.

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Book Id: WPLBN0003975107
Format Type: PDF Article :
File Size: Pages 15
Reproduction Date: 2015

Title: Cloud MacRoscopic Organization: Order Emerging from Randomness : Volume 11, Issue 1 (17/01/2011)  
Author: Yuan, T.
Volume: Vol. 11, Issue 1
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Yuan, T. (2011). Cloud MacRoscopic Organization: Order Emerging from Randomness : Volume 11, Issue 1 (17/01/2011). Retrieved from

Description: Joint Center for Environmental Technology, UMBC, Baltimore, MD, USA. Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds and it follows a power-law distribution with exponent Γ close to 2. Γ is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also show clear-cloudy sky symmetry in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random simple interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. This approach is fully complementary to deterministic models and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Cloud macroscopic organization: order emerging from randomness

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