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The relationship between clouds and dynamics in Southern Hemisphere extratropical cyclones in the real world and a climate model
Author(s) -
Govekar Pallavi D.,
Jakob Christian,
Catto Jennifer
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2013jd020699
Subject(s) - extratropical cyclone , climatology , climate model , environmental science , cloud cover , meteorology , cyclone (programming language) , atmospheric sciences , cloud computing , northern hemisphere , cloud fraction , climate change , geology , geography , computer science , oceanography , field programmable gate array , computer hardware , operating system
The representation of clouds over the Southern Ocean in contemporary climate models remains a major challenge. A major dynamical influence on the structure of clouds is the passage of extratropical cyclones. They exert significant dynamical influences on the clouds in the dynamically active frontal regions as well as in the dynamically suppressed regions ahead and behind the cyclones. A cyclone compositing methodology is applied to a reanalysis and vertical profiles of cloudiness from CloudSat/CALIPSO to quantify the relationship between clouds and dynamics in extratropical cyclones over the Southern Ocean. It is found that the range of cloud fraction, vertical motion, and relative humidity changes considerably with height. There is a strong quasi‐linear relationship between the three variables which changes with altitude. After establishing the observed relationships, the methodology is applied to the Australian Community Climate and Earth System Simulator to evaluate the model's ability to simulate the identified cloud‐dynamics relationships. While the model is able to qualitatively reproduce the overall cloud structure, the circulation around the cyclone is generally too weak. As a result, the model fails to represent the observed cloud to dynamics relationship. This wrong relationship in the model leads to a misrepresentation of the cloud field manifested as either an error in the cloud fraction or as simulating the “right” clouds for the “wrong” reason. The result underscores the importance of relationship‐oriented model evaluation techniques over simple right or wrong assessments.