An analysis of high cloud variability: imprints from the El Niño–Southern Oscillation

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• 作者：King-Fai Li ; Hui Su ; Sze-Ning Mak ; Tiffany M. Chang ; Jonathan H. Jiang&#8230
• 关键词：Sea surface temperature ; Cloud fraction ; Interannual variability ; Principal component analysis
• 刊名：Climate Dynamics
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：48
• 期：1-2
• 页码：447-457
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Geophysics/Geodesy; Climatology; Oceanography;
• 出版者：Springer Berlin Heidelberg
• ISSN：1432-0894
• 卷排序：48

文摘

Using data from the International Satellite Cloud Climatology Project (ISCCP), we examine how near-global (60°N–60°S) high cloud fraction varies over time in the past three decades. Our focus is on identifying dominant modes of variability and associated spatial patterns, and how they are related to sea surface temperature. By performing the principal component analysis, we find that the first two principal modes of high cloud distribution show strong imprints of the two types of El Niño–Southern Oscillation (ENSO)—the canonical ENSO and the ENSO Modoki. Comparisons between ISCCP data and 14 models from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) show that models simulate the spatial pattern and the temporal variations of high cloud fraction associated with the canonical ENSO very well but the magnitudes of the canonical ENSO vary among the models. Furthermore, the multi-model mean of the second principal mode in the AMIP5 simulations appears to capture the temporal behavior of the second mode but individual AMIP5 models show large discrepancies in capturing observed temporal variations. A new metric, defined by the relative variances of the first two principal components, suggests that most of the AMIP5 models overestimate the second principal mode of high clouds.