Use or disclosure of this information may be subject to United States export control laws. For official use only. UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, OMPS Limb Profiler Retrieving 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

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 2 Presentation Outline 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 Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 3 Ozone EDR profile requirements Limb Profiler 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 : ppmv Measurement accuracy : tropopause - 15 km : greater of 20% and 0.1 ppmv km : greater of 10% and 0.1 ppmv Measurement precision : tropopause height- 15 km : 10% km : 3% 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 Provide profiles of the volumetric concentration of ozone

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 4 Limb scattering technique has improved vertical resolution over Nadir profile products 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 Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 5 Sensor is based on a Prism Spectrometer 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 290 nm 350 nm 600 nm 1000 nm M325 Model Atmosphere, SZA=40 Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 6 OMPS Limb Sensor Views the Limb Along the Satellite Track Photo from GSFC’s SOLSE/LORE Shuttle flight 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) OMPS limb sampling Center Slit Left SlitRight Slit Limb 0- 65km 2.23  4.25  250km Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 7 Radiance profiles constructed from 4 gain level images Focal plane images as viewed from behind CCD Spectral and spatial smiles of ~8 pixels Inter-image spacing of 50 pixels (vertical) and pixels (spectral) Simultaneous imaging of all three slits 4 gain levels Image 1 Image 4 Image 3 Image 2 LongShort High Gain Low Gain Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 8 Heritage algorithm provides strong foundation for OMPS profile ozone retrieval 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 J - source function  0 - single scatter albedo  - optical depth Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 9 OMPS algorithm enhancements improve profile retrieval performance 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 Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 10 Normalization Altitudes OMPS channels selected to optimize limb profile performance 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 Ozone Aerosol Surface Reflectance Neutral Number Density Cloud Fraction Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 11 Limb profile algorithm flow Scene Characterization Cloud ID Scheme Cloud Properties Surface Properties Cloud Fraction Initial T, P, Density, Aerosol, Ozone, R Surface Reflectances O 3 Inversion (Number Density) O 3 EDR Density Inversion Aerosol Inversion Recent Limb Profile Nadir Profile Cloud Fraction Reflectances Density Profile Aerosol Profiles O 3 N.D. O 3 SDR I m (z) I norm (z)=I m (z)/I m (z Norm ) Convergence Criterion Iterated Database Convert O 3 N.D. to VMR No Yes SOLSE/LORE Algorithm OMPS Enhancements Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 12 Scene Characterization 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 Cloud Ground Baseline approach Radiance multiple scattering component depends on lower boundary conditions Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 13 Profile retrievals employ optimal estimation 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) 675 nm 500 nm 347 nm 290 nm 575 nm Limb Profiler Ozone Density Aerosol

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 14 Accuracy and Precision Error Terms Limb Profiler Sensitivity studies presented Complete error budget in ATBD-

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 15 Sensitivity studies find <0.1% ozone error due to polarization effects 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 Sensor

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 16 Ozone sensor precision errors meet allocations for most model atmospheres TOMS V7 Standard profiles Background volcanic aerosol (May 9, N) Sensor

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 17 Parallel approaches to altitude registration RSAS C & Sigma 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 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 New baseline approach : use S/C attitude only for first guess Dual approach reduces risk Pointing - Altitude Reg.

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 18 Limb profile altitude registration algorithm flow  2 minimization Calculate LP radiances Calibrated LP Radiances Write Ref. Z to SDR Z scale from S/C attitude Peak fitting Calculate LP radiances Calibrated LP Radiances Write Ref. Z to SDR Z scale from S/C attitude NP SDR radiances CrIS D, T profiles RSAS C-  Pointing - Altitude Reg.

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 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)

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 20 Summary C-sigma and RSAS of precision errors Pointing - Altitude Reg. Geophysical uncertainties dominate TBD terms are not expected to be significant Ozone volume match-up uncertainties have not been quantified

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003 Use or disclosure of this information may be subject to United States export control laws. For official use only. 21 OMPS Limb Profiler Summary 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 First NPOESS flight currently planned for 2011 –Early flight of opportunity on NPP (Launch 2006) Limb Profiler