xiong liu harvard-smithsonian center for astrophysics [email protected] kelly chance, christopher...

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Xiong Liu Harvard-Smithsonian Center for Astrophysics [email protected]. 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

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Page 1: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

Xiong Liu

Harvard-Smithsonian Center for [email protected]

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

Page 2: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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Outline

Introduction

Algorithm description

Intercomparison with Ozonesonde, TOMS, and Dobson

Global distribution of tropospheric ozone and comparison with GEOS-CHEM model results

Summary and future work

Page 3: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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Introduction

GOME: first nadir-viewing satellite instrument that allows direct tropospheric ozone retrieval from the space.

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.

However, tropospheric ozone retrieval remains very challenging from GOME:

Require accurate and consistent calibrations.

Need to fit the Huggins bands to high precision.

Tropospheric ozone is only ~10% of total column ozone.

Page 4: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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Algorithm Description Inversion technique: Optimal Estimation

Measurements: 289-307 nm, 326-338 nm; Spatial resolution: 960×80 km2

Perform detailed wavelength and radiometric calibrations:Derive variable slit widths and shifts between radiances/irradiancesFit shifts between trace gas absorption cross-sections and radiancesCo-add adjacent pixels from 289-307 nm to reduce noise Improve polarization correction using GOMECAL (www.knmi.nl/gome_fd/) Perform undersampling correction with a high-resolution solar referenceFit degradation for 289-307 nm on line in the retrieval

Use LIDORT to simulate radiances and weighting functions

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]

20 1 0 2 0' exp( ( / ) ( / ) )R R a a a

Page 5: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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Algorithm Description Improve forward model simulation (continue):

Brion’s ozone absorption cross-sections [Brion et al., 1993]Daily ECMWF temperature profiles (www.ecmwf.int)Daily NCEP/NCAR surface pressure (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

A priori: latitude and monthly dependent TOMS V8 climatology (a priori and its variance) [McPeters et al., 2003, AGU]

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

State Vector: 47 parameters 11 O3 + 4 albedo (1 for ch1a & 3 for ch2b) + 4 Ring (1 for ch1a & 3 for ch2b) + 8 O3 shift + 8 rad./irrad. shift + 3 degradation correction (ch1a only) + 2 undersampling + 2 NO2 + 2 BrO + 2 SO2 + 1 internal scattering

Fitting residual: 0.40% for band 1a, 0.17% for band 2b, 0.3% for both

Speed : ~17 hours on a 2GHz processor for one day, could be operational

Page 6: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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Validation and Intercomparison

GOME data are collocated at 25 ozonesonde stations during 96-99. Validate retrievals against TOMS V8, Dobson/Brewer total ozone, and ozonesonde. Ozonesonde data mostly from WOUDC, and some from CMDL, SHADOZ, and NDSC. Collocation criteria:

Within ~8 hours, 1.5° latitude and ~500 km in longitude Average all TOMS points within GOME footprint

Number of comparisons: 4429, 952, and 1937 with TOMS, Dobson, and ozonesonde, respectively. http://www.woudc.org; http://croc.gsfc.nasa.giv/shadoz

http://ndsc.ncep.noaa.gov; http://toms.gsfc.nasa.gov/http://www.cmdl.noaa.gov/infodata/ftpdata.html

Page 7: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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GOME-Dobson: within retrieval uncertainties and ozone variability.Biases: <5 DU, and <8 DU at two high-latitude stations1 : 3-6 DU in the tropics, 6-19 DU at higher latitudes.

Total Column Ozone Comparison

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

Page 8: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

8A Priori Retrieval Ozonesonde

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

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

Page 9: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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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

Page 10: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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

Page 11: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

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GOME vs. GEOS-CHEM Tropospheric Ozone

SON,96 R=0.671.8±6.8DU

DJF,96-97 R=0.83 0.0±5.3DU

MAM,97 R=0.822.2 ±4.5DU

JJA,97R=0.642.5 ±5.7DU

Page 12: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

Summary

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.

Retrieved total ozone compares very well with TOMS and Dobson/Brewer total ozone.

The tropospheric column ozone compare well with ozonesonde measurements.

Global distribution of tropospheric ozone is presented. It clearly shows the signals due to biomass burning, air pollution, stratospheric-troposphere exchange, transport and convection.

The overall structures of retrieved tropospheric ozone are similar to those of GEOS-CHEM, but significant differences exist.

Page 13: Xiong Liu Harvard-Smithsonian Center for Astrophysics xliu@cfa.harvard.edu Kelly Chance, Christopher Sioris, Robert Spurr, Thomas Kurosu, Randall Martin,

Future Work Retrieve tropospheric ozone for the 8-year GOME data record and apply

the algorithm to SCIMACHY data

With the aid of GEOS-CHEM, investigate global/regional distribution of tropospheric ozone and understand the GOME/GEOS-CHEM similarities and differences.

Tropospheric ozone radiative forcing

Tropospheric/stratospheric ozone variability

Acknowledgements

This study is supported by the NASA ACMAP and by Smithsonian Institution.

We thank WOUDC and its data providers, SHADOZ, CMDL, NDSC, TOMS, and M. Fujiwara for providing correlative measurements.

We are grateful to M. Fu and P.I. Palmer for providing the GEOS-CHEM model results.

We thank R. van Oss for providing look-up table and software for correcting radiance errors due to neglect polarization.