1. Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin, Mike Newchurch, PK Bhartia San Franciso, CA December 17, 2004 2004 AGU Fall Meeting Direct Tropospheric Ozone Retrieval from GOME

2. 2 Outline n Introduction n Algorithm description 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 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 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

6. 6 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

7. 7 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

8. 8 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

9. 9 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

10. 10 Monthly Mean Tropospheric Ozone (09/96-10/97)

11. 11 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

12. 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 tropospheric column ozone compare well with ozonesonde measurements. 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.

13. Future Work n Retrieve tropospheric ozone for the 8-year GOME data record and apply the algorithm to SCIMACHY data n With the aid of GEOS-CHEM, investigate global/regional distribution of tropospheric ozone and understand the GOME/GEOS-CHEM similarities and differences. n Tropospheric ozone radiative forcing n Tropospheric/stratospheric ozone variability Acknowledgements n This study is supported by the NASA ACMAP and by Smithsonian Institution. n We thank WOUDC and its data providers, SHADOZ, CMDL, NDSC, TOMS, and M. Fujiwara for providing correlative measurements. n We are grateful to M. Fu and P.I. Palmer for providing the GEOS-CHEM model results. n We thank R. van Oss for providing look-up table and software for correcting radiance errors due to neglect polarization.