1. Retrieval of thermal infrared cooling rates from EOS instruments Daniel Feldman Thursday IR meeting January 13, 2005

2. Outline Introduction Methodology Clear vs. Scattering Instrumentation questions Representative scenarios

3. Introduction State vector components are frequently retrieved to derive standard products We intend to explore in detail infrared cooling rate retrievals in clear and scattering atmospheres using EOS instruments: –AIRS –TES –MODIS/MISR

4. Motivation Closure of infrared radiation balance for input to regional-scale models Evaluate the direct forcing of mineral dust in the infrared via direct measurement. Ultimately improve parameterizations of treatment of radiation in regional-scale models.

5. Previous work: Cooling rate retrieval: –Liou and Xue (1988) –Liou (2002) AIRS dust: –X. Huang (JGR 2004) –Thomas (AGU) –Pierangelo (ACP 2004)

6. Liou and Xue (1988 & 2002) –Analytic expression derives spectral and band radiance as a Fredholm integral of cooling rate profile and kernel transmittance function. Assumptions: Utilize either Goody random model or correlated-k Transmittance function assumes constant form over spectral and band regions Planck function for band equals Planck function for spectral channel. –Limitations: Clear-sky calculations only, transmission function takes simple form

7. EOS L1B Products EOS L2 Standard Products Using Operational Retrieval Algorithm Perform Error Analysis on Standard and Research Products Derived Analyses Of IR Heat Budgets Retrieve Cooling Rate Profiles from Radiance Data Directly Perform Error Analysis on Cooling Rate Profiles Compare Retrieved Data To Derived IR Heat Budget Analyses Project Flow Chart

8. Methodology Heating/cooling rate profile retrieval methods show distinct differences compared to standard retrievals –Standard retrieval performs an inversion of the forward model mapping state vector to radiances. –Given full radiance field, heating rate calculation is trivial –Challenge of heating/cooling rate retrieval involves determining spectral and channel information to perform forward model heating/cooling rate calculation.

9. Clear-sky Roadmap Utilize LBRTM with RADSUM For faster calculations, use Modtran 5 Develop framework for cooling rate retrieval –Test cooling rate retrieval algorithm for H 2 O (800-960) using AIRS scan pattern Perform retrieval test by first deriving a state vector and then deriving the cooling rate.

10. Clear-Sky Verification

11. Presence of Mineral Dust Included Volz description of dust indices of refraction and tri-model log-normal distribution of aerosols per Seinfeld and Pandis (AOD ~ 1)

12. Cooling rate profile difference with dust

13. Cooling rate retrieval with scattering in source function Doubling-adding module on top of LBLRTM called CHARTS User-supplied spectral functions for Modtran 5 Derivation by Liou and Xue no longer valid because source function is not Planck function. –What are valid assumptions that can be made about source function?

14. Current foci of IR mineral dust research Composition –Sokolik et al. Phase function/sphericity Spatial/height distribution –Pierangelo et al. –Mahowald Particle Size Distribution –MODIS/MISR products AERONET validation –Thomas

15. Cooling Rate Retrieval Road Map Use Modtran 5 to develop a cooling rate retrieval program similar to that described by Liou. –Need validation with AIRS spectra –Use of DISORT option –Problems with sertran parameters Test out program sensitivity to dust layer using range of dust fields provided by Mahowald.

16. Numerical methods for cooling rate retrieval Create cooling rate jacobians with respect to standard state vector Look at variation in band radiance with respect to view angle Explore band radiance variations with respect to state components Effect of uncertainty in measurements and state components (chain rule) I = radiance x = state vector T = heating/cooling (h/c) rate z = height coordinate k = state vector component index j = channel index n = matrix index for h/c rate designation

17. Questions for future: AIRS vs. TES –TES has coverage over bright surfaces –AIRS radiances are better validated Surface emissivity –MODIS 5km land emissivity map? Role of AERONET for validation