An Analysis of Interannual Variabilities in High Cloud Cover from AIRS Data: Imprints of the El Niño-Southern Oscillation and Comparison to Models

Monday, 15 December 2014: 11:50 AM
Yuk L Yung1, Katie Antilla1, Sze-Ning Mak2, Tiffany M Chang3, King-Fai Li4, Hui Su5, Sun Wong6 and Jonathan H. Jiang6, (1)California Institute of Technology, Pasadena, CA, United States, (2)The Chinese University of Hong Kong, Hong Kong, Hong Kong, (3)Brown University, Providence, RI, United States, (4)University Corporation for Atmospheric Research, Boulder, CO, United States, (5)Jet Propulsion Lab, Pasadena, CA, United States, (6)NASA Jet Propulsion Laboratory, Pasadena, CA, United States
Using data from the Atmospheric Infrared Sounder (AIRS), we examine how global high cloud cover varies over time in the decade from 2003 to 2012, with a focus on identifying dominant modes of variabilities and associated spatial patterns, and relate them to sea surface temperature (SST). By performing Empirical Orthogonal Function (EOF) analysis on satellite observations of high cloud cover, the El Niño-Southern Oscillation (ENSO) — including both EP-ENSO (canonical ENSO) and CP-ENSO (ENSO Modoki) — is found to be the leading source of variability in high cloud cover. High cloud distributions are further shown to be closely associated with SST variations. The observations are compared to simulations from 20 AMIP5 models. In general, the models are able to simulate the first EOF, the EP-ENSO, in the data. However, only about half of the AMIP5 models could realistically reproduce the second EOF, the CP-ENSO. Improved understanding of high cloud variabilities will advance climate model simulations and facilitate more accurate predictions of future climate, specifically the climate response to increasing greenhouse gases such as CO2.