1. 1 The intercomparison of tropical tropospheric compositions measured from satellite Jae Kim 1, Somyoung Kim 1, and M. J. Newchurch 2 1: Pusan National Univ, Korea 2: University of Alabama in Huntsville, USA

2. 2 Contents 1. Cloud-induced OMI total ozone error and its impact on tropospheric ozone 2. Empirical Orthogonal Function (EOF) method for evaluating satellite products

3. 3 Cloud-induced OMI total ozone error and its impact on tropospheric ozone

4. 4 OMI-MLS tropospheric ozone map March April September May August October

5. 5 OMI reflectivity OMI total ozone MODIS cloud fraction Ozone hole Marine stratocumulus regions Convective cloudy regions Ozone fountain

6. 6 OMI total O 3 (all) – total O 3 (clear) Jan (2005.01-2007.12)Feb (2005.01-2007.12) Mar (2005.01-2007.12)April (2005.01-2007.12)

7. 7 May (2005.01-2007.12)Jun (2005.01-2007.12) Jul (2005.01-2007.12)Aug (2005.01-2007.12) OMI total O 3 (all) – total O 3 (clear)

8. 8 Sep (2005.01-2007.12)Oct (2005.01-2007.12) Nov (2005.01-2007.12)Dec (2005.01-2007.12) OMI total O 3 (all) – total O 3 (clear)

9. 9 OMI-MLS tropospheric ozone before and after correction for cloud Dec Jan April

10. 10 OMI-MLS tropospheric ozone before and after correction for cloud Aug Sep Oct

11. 11 Tried to evaluate satellite product quantitatively by calculating correlation, STD, etc. with ground-based measurements and other satellite product. However, there is limitation in spatial and temporal coverage for ground-based data, and we don’t know how good the other satellite product is. Seek a different point of view in evaluating satellite products qualitatively by answering to the question: “Are satellite products self-consistent in chemical and dynamical point of view? Accomplish this objective by analyzing the spatial-temporal pattern of satellite products with the statistical tool, Empirical Orthogonal Function (EOF). The EOF method is the method of choice for analyzing the variability of a single filed. The method finds the spatial patterns of variability, their time variation, and gives a measure of the “importance” of each field. 2. Empirical orthogonal function (EOF) method for evaluating satellite products

12. 12

13. 13 EOF for test 1 case Spatial pattern; Blue: negative, red:positive value Time series; Principle Component

14. 14 Cloud fraction EOF mode 1 ATSR fire EOF MODIS AOD EOF OMI NO2 EOF MOPITT CO EOF

15. 15 OMI-MLS tropospheric O3 EOF SAM tropospheric O3 EOF TES tropospheric O3 EOF GOME tropospheric O3 EOF

16. 16 OMI-MLS tropospheric O3 EOF SAM tropospheric O3 EOF TES tropospheric O3 EOF GOME tropospheric O3 EOF

17. 17 SAM is not available in latitude higher than 20º GOME tropo O3 EOF TES tropos O3 EOF OMI-MLS tropo O3 EOF

18. 18 Cloud fraction EOF mode 1 OMI-MLS EOF mode 2

19. 19 OMI-MLS over western Pacific Ocean mode 1 mode 2 OMI-MLS over central Pacific Ocean mode 1 mode 2 GOME tropo O3 over western Pacific Ocean mode 1 mode 2 GOME tropo O3 over central Pacific Ocean mode 1 mode 2

20. 20 GOME tropo O3 over W. Pacific mode 3 GOME tropo O3 over C. Pacific mode 3 OMI-MLS tropo O3 over W. Pacific mode 3 OMI-MLS tropo O3 over C. Pacific mode 3

21. 21 Camp et al. (2003, JGR)

22. 22 Summary 1. OMI total ozone appears to have cloud related error. We found total ozone is overestimated over marine stratocumulus cloud and underestimated over convective cloud. This leads discontinuous tropospheric ozone distribution between ocean and continent. 2. Empirical Orthogonal Function (EOF) method can be effectively used to evaluate satellite products qualitatively.