1. Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu December 20, 2004 Direct Tropospheric Ozone Retrieval from GOME

2. 2 Outline n Introduction n Algorithm description n Retrieval characterization n Intercomparison with Ozonesonde, TOMS, and Dobson n Global distribution of tropospheric ozone and comparison with GEOS-CHEM model results n Summary and future work

3. 3 Introduction n Current tropospheric ozone retrievals are mainly based on the residual approaches: limited to certain latitude ranges and to monthly level n GOME: first nadir-viewing satellite instrument that allows direct tropospheric ozone retrieval from the space. n Several groups [Munro et al., 1998; Hoogen et al., 1999; Hasekamp et al., 2001; van der A et al, 2002; Muller et al., 2003; Liu et al., 2004] have developed ozone profile retrieval algorithms from GOME: each of them demonstrates that limited tropospheric ozone information can be derived. n However, tropospheric ozone retrieval remains very challenging from GOME: u Require accurate and consistent calibrations. u Need to fit the Huggins bands to high precision. u Tropospheric ozone is only ~10% of total column ozone.

4. 4 Algorithm Description n Inversion technique: Optimal Estimation n Measurements: 289-307 nm, 326-338 nm; Spatial resolution: 960×80 km 2 n Perform detailed wavelength and radiometric calibrations:  Derive variable slit widths and shifts between radiances/irradiances  Fit shifts between trace gas absorption cross-sections and radiances  Co-add adjacent pixels from 289-307 nm to reduce noise  Improve polarization correction using GOMECAL (www.knmi.nl/gome_fd/)www.knmi.nl/gome_fd/  Perform undersampling correction with a high-resolution solar reference  Fit degradation for 289-307 nm on line in the retrieval n Use LIDORT to simulate radiances and weighting functions n Improve forward model simulation:  On-line correction of Ring filling in of the solar and telluric absorption feature with first-order single scattering RRS model [Sioris and Evans, 2002]  Look-up table correction of polarization errors [van Oss, personal comm.]  Monthly-mean SAGE stratospheric aerosols [Bauman et al., 2003]  GEOS-CHEM tropospheric aerosols [Martin et al., 2002]

5. 5 Variable Slit Widths and Shifts

6. 6 Algorithm Description n Improve forward model simulation (continue):  Brion’s ozone absorption cross-sections [Brion et al., 1993]  Daily ECMWF temperature profiles (www.ecmwf.int)www.ecmwf.int  Daily NCEP/NCAR surface pressure (www.cdc.noaa.gov)www.cdc.noaa.gov  Cloud-top height from GOMECAT [Kurosu et al., 1999]  Cloud fraction derived at 370.2 nm with albedo database [Kolemeijer et al.,2003]  Wavelength dependent albedo (2-order polynomial) from 326-338 nm n A priori: latitude and monthly dependent TOMS V8 climatology (a priori and its variance) [McPeters et al., 2003, AGU] n Retrieval Grid: 11 layers, almost the same as the Umkehr grid  Bottom 2-3 layers are modified by tropopause/surface pressure  Tropospheric column ozone is directly retrieved n State Vector: 47 parameters  11 O 3 + 4 albedo (1 for ch1a & 3 for ch2b) + 4 Ring (1 for ch1a & 3 for ch2b) + 8 O 3 shift + 8 rad./irrad. shift + 3 degradation correction (ch1a only) + 2 undersampling + 2 NO 2 + 2 BrO + 2 SO 2 + 1 internal scattering n Fitting residual: 0.40% for band 1a, 0.17% for band 2b, 0.3% for both n Speed : ~17 hours on a 2GHz processor for one day, could be operational

7. 7 Retrieval Characterization n Averaging Kernel: characterize the retrieval n DFS: diagonal elements of averaging kernels n A priori influence:

8. 8 Examples of Averaging Kernels

9. 9

10. 10 A Priori Influence (06/7-9/1997) TOMS V8 A Priori GEOS-CHEM A Priori Retrieval with TOMS V8 A Priori Retrieval with GEOS-CHEM A Priori

11. 11 Retrieval Errors

12. 12 Validation and Intercomparison n GOME data are collocated at 25 ozonesonde stations during 96-99. n Validate retrievals against TOMS V8, Dobson/Brewer total ozone, and ozonesonde. n Ozonesonde data mostly from WOUDC, and some from CMDL, SHADOZ, and NDSC. n Collocation criteria:  Within ~8 hours, 1.5° latitude and ~500 km in longitude  Average all TOMS points within GOME footprint n Number of comparisons: 4429, 952, and 1937 with TOMS, Dobson, and ozonesonde, respectively. http://www.woudc.orghttp://www.woudc.org; http://croc.gsfc.nasa.giv/shadozhttp://croc.gsfc.nasa.giv/shadoz http://ndsc.ncep.noaa.govhttp://ndsc.ncep.noaa.gov; http://toms.gsfc.nasa.gov/http://toms.gsfc.nasa.gov/ http://www.cmdl.noaa.gov/infodata/ftpdata.html

13. 13 n GOME-Dobson: within retrieval uncertainties and ozone variability.  Biases: <5 DU, and <8 DU at two high-latitude stations  1  : 3-6 DU in the tropics, 6-19 DU at higher latitudes. Total Column Ozone Comparison n GOME-TOMS: within retrieval uncertainties and saptiotemporal variability.  Biases: <3 DU except 3-8 DU at a few high-latitude stations  1  : 2-4 DU in the tropics, 4-11 DU at higher latitudes. A Priori Retrieval Dobson TOMS

14. 14 n GOME-Ozonesonde:  Systematic differences exists at Carbon Iodine, CMDL, SHADOZ stations  Bias: <3 DU (2%), except at Ny Ålesund and Neumayer (-3.3% and 4.5%)  1  : 4-9 DU (4-6%) in the tropics and 10-22 DU (5-10%) at higher latitudes. Stratospheric Column Ozone Comparison A Priori Retrieval Ozonesonde Column ozone between tropopause to~30-35 km 1%-KI buffered 2%-KI unbuffered

15. 15 A Priori Retrieval Ozonesonde n GOME-SONDE within retrieval uncertainties.  Biases: <4 DU (15%) except –5.5, 4.4, 5.6 DU (16-33%) at NyÅlesund, Naha, Tahiti  1  : 3-7 DU (13-28%) A Priori Retrieval Ozonesonde n GOME-SONDE within retrieval uncertainties.  Biases: <4 DU (15%) except –5.5, 4.4, 5.6 DU (16-33%) at NyÅlesund, Naha, Tahiti  1  : 3-7 DU (13-28%) Tropospheric Column Ozone Comparison

16. 16 n The degradation is well handled n GOME retrievals agree well with ozonesonde  Biases: <2 DU (10%)  1  : <10 DU (25%) Profile: Hohenpeißenberg (48N,11E), 1996-1999 A Priori Retrieval Ozonesonde

17. 17 n Positive bias in the middle, negative bias at two ends, probably due to some systematic bias in radiance spectra and the wavelength dependent correction is not perfect.  Biases: < 4 DU (40%)  1  : <4 DU (30%) n Bias in tropospheric/stratospheric column ozone is reduced due to canceling errors. Profile: America Samoa (14S,171W), 1996-1997 A Priori Retrieval Ozonesonde

18. 18 Examples of Daily Global Tropospheric Ozone High ozone over biomass burning South Atlantic Paradox Low tropospheric ozone in tropical Pacific Bands of high ozone at mid-latitudes High ozone at high-latitudes during late winter and early spring

19. 19 Monthly Mean Tropospheric Ozone (09/96-11/97)

20. 20 GOME vs. GEOS-CHEM Tropospheric Ozone SON,96 R=0.67 1.8±6.8DU DJF,96-97 R=0.83 0.0±5.3DU MAM,97 R=0.82 2.2 ±4.5DU JJA,97 R=0.64 2.5 ±5.7DU

21. 21 Summary n Ozone profiles and tropospheric column ozone are derived from GOME using the optimal estimation approach after detailed treatments of wavelength and radiometric calibrations and improvement of forward model inputs. n Retrieved total ozone compares very well with TOMS and Dobson/Brewer total ozone. n The profiles, stratospheric ozone, and tropospheric ozone compare well with ozonesonde observations except some stratospheric bias at Carbon Iodine stations, CMDL, and SHADOZ stations. n Global distribution of tropospheric ozone is presented. It clearly shows the signals due to biomass burning, air pollution, stratospheric- troposphere exchange, transport and convection. n The overall structures of retrieved tropospheric ozone are similar to those of GEOS-CHEM, but significant differences exist.

22. 22 Future Work n Complete tropospheric ozone retrieval for the 8-year GOME data record and apply the algorithm to SCIMACHY and OMI data n With the aid of GEOS-CHEM, other observations, or model fields, understand the GOME/GEOS-CHEM similarities and differences, and investigate global/regional distribution of tropospheric ozone. n Tropospheric ozone radiative forcing n Tropospheric/stratospheric ozone variability

23. 23 GOME vs. GEOS-CHEM Tropospheric Ozone

24. 24 GOME vs. GEOS-CHEM Tropospheric Ozone

25. 25 GOME vs. GEOS-CHEM Tropospheric Ozone

26. 26 GOME vs. GEOS-CHEM Tropospheric Ozone

27. 27 GOME vs. GEOS-CHEM Tropospheric Ozone