OMPS Limb Profiler Retrieving Ozone from Limb Scatter Measurements

1. OMPS Limb ProfilerRetrieving Ozone from Limb Scatter Measurements Jack Larsen, Colin Seftor, Boris Petrenko, Vladimir Kondratovich Raytheon Information Technology and Scientific Services Dave Flittner University of Arizona Quinn Remund, Juan Rodriguez, Jim Leitch, Brian McComas Ball Aerospace and Technologies Corp Glen Jaross Science Systems and Applications, Inc Tom Swissler Swissler Info Tech

2. Presentation Outline Limb Profiler • Ozone limb scattering background • OMPS limb sensor overview • Spectral characteristics • Limb viewing geometry • Limb algorithm overview • Heritage basis (SOLSE/LORE) • OMPS enhancements to SOLSE/LORE algorithm • Channel selection • Algorithm flow • Optimal estimation • Selected sensitivity studies • Polarization • Sensor noise • Altitude registration • Conclusions

3. Ozone EDR profile requirements Limb Profiler Provide profiles of the volumetric concentration of ozone • Performance requirements: • Horizontal cell size : 250 km • Vertical cell size : 3 km • Horizontal coverage : global for SZAs < 80 degrees • Vertical coverage : tropopause height (or 8 km)- 60 km • Measurement range : 0.1-15 ppmv • Measurement accuracy : • tropopause - 15 km : greater of 20% and 0.1 ppmv • 15 - 60 km : greater of 10% and 0.1 ppmv • Measurement precision : • tropopause height- 15 km : 10% • 15 - 50 km : 3% • 50 - 60 km : 10% • Long term stability : 2% over 7-year single sensor lifetime • Maximum local average revisit time : 4 days • Exceptions to EDR performance (precision and accuracy) • Ozone volume mixing ratio < 0.3ppmv • Volcanic aerosol loading - CCD saturation - optical depth

4. Limb scattering technique has improved vertical resolution over Nadir profile products Limb Profiler General Description - Basis for SOLSE/LORE and OMPS Limb Algorithms • By measuring the amount of scatter and absorption of solar radiation through the atmosphere at different wavelengths (e.g. UV, visible, near-infrared), profile scattering instruments can infer the vertical profiles of a number of trace constituents, including ozone • Limb scatter combines advantages of both BUV and visible limb occultation methods • Limb viewing geometry provides good vertical resolution • Measurements can be made throughout the sunlit portion of the orbit; not restricted by sun within FOV Ozone Products • Profiling UV, VIS, NIR Limb

5. 290 nm 350 nm 600 nm 1000 nm Sensor is based on a Prism Spectrometer Limb Profiler M325 Model Atmosphere, SZA=40 • Prism spectrometer provides spectral coverage from 290 nm to 1000 nm • Scene dynamic range accommodated with 4 gain levels: • Aperture split provides two images/slit along the vertical direction of the focal plane • Two integration times for additional discrimination • Wavelength-dependent resolution of prism spectrometer is consistent with ozone spectral detail over this range • Three slits provide three cross-track samples with a single spectrometer and no moving parts • All three slit samples are included on a single focal plane • Radiances nearly simultaneous in altitude and wavelength • Limb radiances sampled multiple times within 38 second integration time • Calibration stability maintained on-orbit by periodic solar observations

6. 0-65km Limb 2.23 4.25 250km Center Slit Left Slit Right Slit OMPS Limb Sensor Views the Limb Along the Satellite Track Limb Profiler Photo from GSFC’s SOLSE/LORE Shuttle flight OMPS limb sampling • OMPS limb sensor has 3 slits separated by 4.25 degrees • 38 second reporting period: 250 km along track • 130 km (2.23 degree) vertical FOV at limb for 0-60 km coverage plus offsets (pointing, orbital variation, Earth oblateness)

7. Long Short Image 1 Image 3 4.42 4.55 4.55 Image 2 Image 4 High Gain Low Gain Radiance profiles constructed from 4 gain level images Limb Profiler Simultaneous imaging of all three slits • Focal plane images as viewed from behind CCD • Spectral and spatial smiles of ~8 pixels • Inter-image spacing of 50 pixels (vertical) and 20-35 pixels (spectral) 4 gain levels

8. J - source function w0 - single scatter albedo t - optical depth Heritage algorithm provides strong foundation for OMPS profile ozone retrieval Limb Profiler • Successful shuttle flight by GSFC Code 916 demonstrates that SOLSE / LORE retrieves ozone from space • Adapting the SOLSE / LORE algorithm developed by Ben Herman and Dave Flittner (U. of Arizona) • Herman code (Applied Optics, v. 34, 1995) • Multiple scattering solution in a spherical atmosphere • Molecular and aerosol scattering • Ozone absorption • Includes polarization • Combines spherical multiple scattering solution with integration of source function along line of sight

9. OMPS algorithm enhancements improve profile retrieval performance Limb Profiler • Inverts neutral number density at 350 nm • Eliminates need for external EDR temperature and pressure above 20 km • Use external EDR temperature and pressure to derive density from 10 to 20 km • If external EDR unavailable, use climatology for 10 to 20 km • Inverts aerosol at non-ozone visible wavelengths • Simple aerosol model interpolates to ozone wavelengths • Wavelength triplet formulation reduces effects of aerosol on ozone when aerosol inversion cannot be performed • Solves for visible surface reflectances • Solves for cloud fraction • Multiple scattering tables include clouds at four pressure levels

10. Ozone Aerosol Normalization Altitudes Neutral Number Density Surface Reflectance Cloud Fraction OMPS channels selected to optimize limb profile performance Limb Profiler • OMPS uses the UV and visible limb scatter spectrum to measure ozone • Middle and near-ultraviolet channels provide coverage from 28 to 60 km • Visible channels provide coverage from tropopause to 28 km • Additional channels between 350 and 1000 nm provide characterization of Rayleigh and aerosol scattering background

11. Limb profile algorithm flow Limb Profiler Recent Limb Profile Nadir Profile Scene Characterization Cloud ID Scheme Cloud Properties Surface Properties Cloud Fraction O3SDR Im(z) Inorm (z)=Im(z)/Im(zNorm) Initial T, P, Density, Aerosol, Ozone, R Surface Reflectances Cloud Fraction Reflectances Density Profile Aerosol Profiles O3N.D. Density Inversion Aerosol Inversion Iterated Database No Yes O3 Inversion (Number Density) Convergence Criterion Convert O3 N.D. to VMR SOLSE/LORE Algorithm OMPS Enhancements O3 EDR

12. Cloud Ground Scene Characterization Limb Profiler • Spatial variation in cloud and surface reflectivity • Radiances-weighted average (cloud fraction) of clear sky and cloud • Iterated solution for cloud fraction from 347, 353 nm channels Baseline approach Radiance multiple scattering component depends on lower boundary conditions

13. 500 nm 575 nm 290 nm 675 nm 347 nm Profile retrievals employ optimal estimation Limb Profiler Ozone • Kernels define sensitivity of radiances to atmospheric constituents • Kernel shapes sharply peaked due to limb geometry - provides high vertical resolution • Positive kernels: scattering • Negative kernels: absorption • Optimal estimation (Rodgers, 1976) Density Aerosol

14. Accuracy and Precision Error Terms Limb Profiler Sensitivity studies presented Complete error budget in ATBD-http://npoesslib.ipo.noaa.gov

15. Sensitivity studies find <0.1% ozone error due to polarization effects Sensor • Broad range of observing conditions studied • Error for a sensor with 10% polarization sensitivity reduced to 1.3% by depolarizer • Excess allocation for polarization stability reallocated to on-orbit wavelength calibration/stability and pixel-to-pixel calibration

16. Ozone sensor precision errors meet allocations for most model atmospheres Sensor • TOMS V7 Standard profiles • Background volcanic aerosol (May 9, 1991 30.1N)

17. Parallel approaches to altitude registration Pointing - Altitude Reg. RSAS C & Sigma New baseline approach : use S/C attitude only for first guess • Limb radiances compared to predictions based upon “known” ozone profiles • Information: 42 km < Z < 50 km • Registers limb profiles to a pressure scale • CrIS EDR provides pressure vs. Z; NP provides ozone vs. pressure Advantage: • Insensitive to surface and lower stratosphere • Uses multiple NP & LP channels Disadvantage: • Requires NP SDR radiances • Requires CrIS EDR • Limb radiances compared to predictions based upon “known” neutral density profiles • Information: 20 km < Z < 45 km • Registers limb profiles to a neutral density scale • CrIS EDR provides density vs. Z from temperature and pressure profiles Advantage: • Low variability in Rayleigh scatter Disadvantage: • Sensitive to surface and lower stratosphere • Requires 2 CrIS EDRs Dual approach reduces risk

18. Limb profile altitude registration algorithm flow Pointing - Altitude Reg. Z scale from S/C attitude Calibrated LP Radiances Write Ref. Z to SDR 2 minimization RSAS Calculate LP radiances CrIS D, T profiles Calculate LP radiances NP SDR radiances C- Write Ref. Z to SDR Peak fitting Z scale from S/C attitude Calibrated LP Radiances

19. Summary of C-sigma and RSAS accuracy errors Pointing - Altitude Reg. CrIS uncertainties dominate RSAS in the absence of aerosols Correctable errors excluded from total Lunar obs. can reduce accuracy errors (assuming good MTF knowledge)

20. Summary C-sigma and RSAS of precision errors Pointing - Altitude Reg. Geophysical uncertainties dominate Ozone volume match-up uncertainties have not been quantified TBD terms are not expected to be significant

21. OMPS Limb Profiler Summary Limb Profiler • Unique sensor design accommodates wide dynamic range of scene radiances and is spectrally optimized to match ozone absorption features • Sensor SNRs tailored to algorithm/EDR requirements • Requirements met except for a few model atmospheres-altitude regimes • Sensor-algorithm performance verified with on-going sensitivity studies • Polarization errors < 0.1% ozone • Ozone errors due to sensor noise meet requirements • C-Sigma selected as primary approach to altitude registration • Precision ~ 120 m exceeds error allocation of 55m • Accuracy ~ 500 m • Will continue to study RSAS • May combine both for operational use • OMPS algorithms to be tested on limb scatter observations • SAGE III, SOLSE/LORE 2, OSIRIS, SCIAMACHY, GOMOS • Engineering unit being built and tested fall-winter 2002-2003 • First NPOESS flight currently planned for 2011 • Early flight of opportunity on NPP (Launch 2006)