1. A model study on satellite observed tropical tropospheric ozone columns Model results and satellite observations: How can we optimally confront them? W. Peters, M.C. Krol, F.J. Dentener, A.M. Thompson and J. Lelieveld

2. Message:  A quantitative approach is necessary.  This requires a careful evaluation of modeling strategies.

3. Satellite observations: 1979-1992 Modified-Residual TTOC (2x1, monthly mean) Model 1979-1993 off-line meteo (ECMWF) (5x4, monthly mean) Atlantic ~40 DU Atlantic ~60 DU Pacific ~15 DU

4.  Zonal wave one (zwo): Pacific fit, Atlantic mismatch  Quantitative measure of error:  1 = correlation{zwo tm3,zwo obs }  2 = RMS {zwo tm3,zwo obs } /  obs latit. avg. (Sept ‘92) Observations+  Model

5. Quantify discrepancies:  2 l. time Atl. Pac.

6. Sensitivities and Priorities Biomass burning injection height Biomass burning injection height Biomass burning fire calendar Biomass burning fire calendar Lightning NOx emission yearly total Lightning NOx emission yearly total Lightning NOx emissions distribution Lightning NOx emissions distribution Biomass burning emission factors (NOx) Biomass burning emission factors (NOx) Lightning NOx emission profiles Lightning NOx emission profiles … …

7. Sensitivities and Priorities  Base run: 1992 meteo 1992 emissions 1992 MR-TTOC Pacific = 90E to 90W Atlantic = 90W to 90E

8. Threshold for better than 10% random  2 = 0.01 2x NOx from biomass burning 2x J(HNO3) in free troposphere New fire calendar from fire counts 5 DU reduction of observations 

9. Recommendations:  Quantify results (despite uncertainties)  Tailor strategies:  Interact with satellite retrieval community  Anticipate ongoing retrieval developments Peters et. al. (2002), Chemistry-transport modeling of the satellite observed distribution of tropical tropospheric ozone, Atm. Chem. Phys. Vol 2, p 103-120. http://www.copernicus.org/EGS/acp

10. Results  Quantification of transport influence  Priority list for model improvements  Detailed list of model sensitivities  Suggested improvements in MR-retrieval  Insights in feasibility of inversions  Experience in model-satellite combination

11. Sensitivities and Directions  Lightning param. Land/Ocean ratio 

12. Sensitivities and Directions  Biomass burning Double HNO3 photolysis  Threshold for better than 10% random  2 = 0.01

13. Sensitivities and Directions  Biomass burning New fire calendar Threshold for better than 10% random  2 = 0.01

14. Sensitivities and Directions  Lightning param. Double NOx  mid-latitudes Threshold for better than 10% random  2 = 0.01

15. Sensitivities and Directions  Satellite data 5 DU reduction Threshold for better than 10% random  2 = 0.01

16. Sensitivities / Directions Threshold for better than 10% random  2 = 0.01

17. Importance of transport Actual year Average El Niño Threshold for better than 10% random= 0.001