Overview Atmospheric Infrared Sounder Pasadena, California - - PowerPoint PPT Presentation

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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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

Xun Jiang1, Moustafa Chahine2, Edward Olsen2, Luke Chen2, and Yuk Yung3

Interannual Variability of AIRS CO2

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Overview

• Motivation
• Data
• Interannual Variability of AIRS CO2
• 1. El Nino and Southern Oscillation (ENSO)
• 2. Northern Hemisphere Annular Mode
• 3. Quasi-Biennial Oscillation
• Conclusions

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Motivation

• Improve understanding of CO2 variability and its effect
• n the global climate change using satellite data
• Investigate how natural variability (e.g., ENSO, annular

mode, and QBO) influence the global CO2

• Better improve CO2 simulations from chemistry-

transport models in the future

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Data

Weighting Function

Stratosphere Troposphere

Tropopause

• AIRS Mid-tropospheric CO2

Sensitivity Peak: 500-300 hPa

(depending upon latitude)

Chahine et al. [2005; 2008]

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Data

AIRS Mid-tropospheric CO2: Sep 2002 - present

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Influence of El Niño/La Niña on AIRS CO2

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Influence of El Niño/La Niña on AIRS CO2

El Niño: Feb 2005 La Niña: Feb 2008 El Niño: Feb 2010

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Influence of El Niño/La Niña on AIRS CO2

La Niña

[Feb 2008]

El Niño - La Niña El Niño

[Feb 2005; Feb 2010]

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Influence of El Niño/La Niña on AIRS CO2

El Niño: Feb 2005 La Niña: Feb 2008 El Niño: Feb 2010

  Southern Oscillation Index (SOI)   AIRS CO2 Difference Between Central and Western Pacific

Central Pacific: 180E-220E, 10S-14N; Western Pacific: 100E-140E, 10S-14N

Correlation: 0.55

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Principal Component Analysis (PCA)

• Preprocess the data

Remove mean; Detrend; Deseasonalize

• PCA analysis

(N timesteps × M stations ) Covariance Matrix ( M × M )

X

The original data can be represented by

e X p

• =

EOFs ( e, Eigenvectors of C ): modes of spatial pattern PCs (p, ): time-dependent amplitudes of the EOFs Eigenvalue: the fraction of variance captured by each EOF

• 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.

• =

k T k ke

p X

T T

E E X X N C

• =
• =

1 1

Influence of El Niño/La Niña on AIRS CO2

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Influence of El Niño/La Niña on AIRS CO2   Southern Oscillation Index (SOI) Second Mode of Tropical AIRS CO2 - ENSO

Correlation: 0.58

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Detrended AIRS CO2 from Nov to Apr at 60N - 90N (Black) Detrended Arctic Oscillation Index from Nov to Apr (Red) Correlation Coefficient = 0.74

Influence of Annular Mode on AIRS CO2

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

AIRS CO2 in the NH

AIRS CO2 averaged in 2006 and 2008 Negative AO index; Weak Vortex AIRS CO2 averaged in 2005 and 2007 Positive AO index; Strong Vortex

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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AIRS CO2 in the NH

AIRS CO2 Difference Strong Vortex - Weak Vortex t-value for AIRS CO2 Difference

Results are within a 10% significance level when t > 2.9

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California

Atmospheric Infrared Sounder

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Influence of Quasi-Biennial Oscillation on AIRS CO2 QBO

biennial annual

Influence of Quasi-Biennial Oscillation on AIRS CO2

Conclusions

• During El Niño year, there is more CO2 in the central Pacific

and less CO2 in the western Pacific.

• CO2 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 CO2.

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 Pasadena, California

Atmospheric Infrared Sounder

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Thank you!