National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California Interannual Variability of AIRS CO 2 Xun Jiang 1 , Moustafa Chahine 2 , Edward Olsen 2 , Luke Chen 2 , and Yuk Yung 3 1 Department of Earth & Atmospheric Sciences, Univ. of Houston 2 Science Division, Jet Propulsion Laboratory, Caltech 3 Division of Geological & Planetary Sciences, Caltech AIRS Science Team Meeting, Apr 21-23, 2010 1
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Overview Atmospheric Infrared Sounder Pasadena, California Motivation Data Interannual Variability of AIRS CO 2 1. El Nino and Southern Oscillation (ENSO) 2. Northern Hemisphere Annular Mode 3. Quasi-Biennial Oscillation Conclusions 2
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Motivation Atmospheric Infrared Sounder Pasadena, California Improve understanding of CO 2 variability and its effect on the global climate change using satellite data Investigate how natural variability (e.g., ENSO, annular mode, and QBO) influence the global CO 2 Better improve CO 2 simulations from chemistry- transport models in the future 3
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Data Atmospheric Infrared Sounder Pasadena, California AIRS Mid-tropospheric CO 2 Sensitivity Peak: 500-300 hPa Stratosphere (depending upon latitude) Chahine et al . [2005; 2008] Tropopause Troposphere 4 Weighting Function
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Data Atmospheric Infrared Sounder Pasadena, California AIRS Mid-tropospheric CO 2 : Sep 2002 - present 5
National Aeronautics and Space Administration Influence of El Niño/La Niña on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California 6
National Aeronautics and Space Administration Influence of El Niño/La Niña on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California La Niña: Feb 2008 El Niño: Feb 2005 El Niño: Feb 2010 7
National Aeronautics and Space Administration Influence of El Niño/La Niña on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California El Niño [Feb 2005; Feb 2010] La Niña [Feb 2008] El Niño - La Niña 8
National Aeronautics and Space Administration Influence of El Niño/La Niña on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California La Niña: Feb 2008 Correlation: 0.55 El Niño: Feb 2005 El Niño: Feb 2010 Southern Oscillation Index (SOI) AIRS CO 2 Difference Between Central and Western Pacific Central Pacific: 180E-220E, 10S-14N; Western Pacific: 100E-140E, 10S-14N 9
National Aeronautics and Space Administration Influence of El Niño/La Niña on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California Principal Component Analysis (PCA) • Preprocess the data Remove mean; Detrend; Deseasonalize • PCA analysis 1 X T T ( N timesteps × M stations ) Covariance Matrix ( M × M ) C X X E E = � = � N 1 � EOFs ( e , Eigenvectors of C ): modes of spatial pattern PCs ( p , ): time-dependent amplitudes of the EOFs p X e = � Eigenvalue: the fraction of variance captured by each EOF The original data can be represented by T X p k e � = k k • To make EOF patterns have dimensional units. We multiply each EOF by the square root of their associated eigenvalue, and divide each PC by this value. 10
National Aeronautics and Space Administration Influence of El Niño/La Niña on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California Correlation: 0.58 Southern Oscillation Index (SOI) Second Mode of Tropical AIRS CO 2 - ENSO 11
National Aeronautics and Space Administration Influence of Annular Mode on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California Detrended AIRS CO 2 from Nov to Apr at 60N - 90N (Black) Detrended Arctic Oscillation Index from Nov to Apr (Red) Correlation Coefficient = 0.74 12
National Aeronautics and Space Administration Jet Propulsion Laboratory AIRS CO 2 in the NH California Institute of Technology Atmospheric Infrared Sounder Pasadena, California AIRS CO 2 averaged in 2005 and 2007 AIRS CO 2 averaged in 2006 and 2008 Positive AO index; Strong Vortex Negative AO index; Weak Vortex
National Aeronautics and Space Administration Jet Propulsion Laboratory AIRS CO 2 in the NH California Institute of Technology Atmospheric Infrared Sounder Pasadena, California AIRS CO 2 Difference t-value for AIRS CO 2 Difference Strong Vortex - Weak Vortex Results are within a 10% significance level when t > 2.9 14
National Aeronautics and Space Administration Influence of Quasi-Biennial Oscillation on AIRS CO 2 Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California biennial annual QBO 15
Influence of Quasi-Biennial Oscillation on AIRS CO 2
Conclusions During El Niño year, there is more CO 2 in the central Pacific and less CO 2 in the western Pacific. CO 2 at high latitudes correlates well with the strength of the polar vortex in the winter season. There is a Quasi-biennial Oscillation signal in AIRS mid-tropospheric CO 2 . References: Chahine et al ., GRL, doi:2005GL024165, 2005. Chahine et al ., GRL, doi:2008GL035022, 2008. Jiang et al ., GBC, doi:2008GL035022, 2008. Jiang et al ., Submitted to GRL, 2010.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Atmospheric Infrared Sounder Pasadena, California Thank you! 18 18
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