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Diagnoses of Climate using Model Simulations and Satellite IR Spectral Data

Diagnoses of Climate using Model Simulations and Satellite IR Spectral Data. V. Ramaswamy and Y. Huang NOAA/ GFDL and AOS Program, Princeton University. Mean spectrum. Note: Radiances (represented through brightness temperatures) are in the unit of Kelvin.

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Diagnoses of Climate using Model Simulations and Satellite IR Spectral Data

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  1. Diagnoses of Climateusing Model Simulations and Satellite IR Spectral Data V. Ramaswamy and Y. Huang NOAA/ GFDL and AOS Program, Princeton University

  2. Mean spectrum

  3. Note: Radiances (represented through brightness temperatures) are in the unit of Kelvin. GCM vs. AIRS –Global annual mean spectra Clear-sky Total-sky [Huang et al. 2007 GRL]

  4. Water vapor band radiance error budget Overestimation Underestimation Window H2O vib-rot Model – satellite difference spectrum Total-sky MODEL-AIRS radiance difference [Huang et al. 2007 GRL]

  5. Day-night difference

  6. Large, positive diurnal difference Small, negative Diurnal difference spectrum Total-sky In equatorial ocean, model simulated total-sky radiances have a strong diurnal contrast at the two AIRS observation times (1:30p.m. – 1:30a.m.), which does NOT exist in the observation. Clear-sky

  7. Spectrum variability

  8. Natural variabilities of OLR spectrum Standard deviations of a) annual mean radiances and b) monthly mean radiances, computed from the time series of all-sky global means. c) different components that contribute to the overall radiance variation:

  9. Using Coupled Climate Model Simulations

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