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UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

OMPS Limb ProfilerRetrieving Ozone from Limb Scatter Measurements

Jack Larsen, Colin Seftor, Boris Petrenko, Vladimir KondratovichRaytheon Information Technology and Scientific Services

Dave FlittnerUniversity of Arizona

Quinn Remund, Juan Rodriguez, Jim Leitch, Brian McComasBall Aerospace and Technologies Corp

Glen JarossScience Systems and Applications, Inc

Tom SwisslerSwissler Info Tech

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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

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3

Ozone EDR profile requirementsLimb Profiler

Performance requirements:Horizontal cell size : 250 kmVertical cell size : 3 kmHorizontal coverage : global for SZAs < 80 degreesVertical coverage : tropopause height (or 8 km)- 60 kmMeasurement range : 0.1-15 ppmvMeasurement accuracy :

tropopause - 15 km : greater of 20% and 0.1 ppmv15 - 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 lifetimeMaximum local average revisit time : 4 days

Exceptions to EDR performance (precision and accuracy)Ozone volume mixing ratio < 0.3ppmvVolcanic 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

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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

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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

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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 SlitLeft Slit Right Slit

Limb

0-65km

2.23

4.25250km

Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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Radiance profiles constructed from 4 gain level images

250km Right Center Slit 250km Left

290nm 375nm 1000nm 290nm 375nm 1000nm 290nm 375nm 1000nm

Low Gain

High Gain

+65km

+65km

-65km

-65km

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)

Simultaneous imaging of all three slits

4 gain levels

Image 1

Image 4

Image 3

Image 2

Long Short

4.55 4.42 4.55

High Gain

Low Gain

Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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

deT

JI)(

0

0TotalLimb

J - source function 0 - single scatter albedo - optical depth

Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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

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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

SurfaceReflectance

NeutralNumberDensity

CloudFraction

Limb Profiler

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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

O3 Inversion(Number Density)

O3 EDR

Density Inversion

Aerosol Inversion

Recent Limb ProfileNadir Profile

Cloud FractionReflectances

Density ProfileAerosol Profiles

O3 N.D.

O3 SDRIm(z)

Inorm (z)=Im(z)/Im(zNorm)

ConvergenceCriterion

Iterated Database

Convert O3 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

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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

Terrain Cloud

UV Visible UV Visible

ReflectanceN7 TOMS DB

(Herman &Celarier)

IteratedSolution 0.8 0.8

Pressure/Altitude CrIS

VIIRS/OMPS 1000nm

channel

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

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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 nm500 nm347 nm

290 nm

575 nm

)]()[()( 01

01 nnmeT

xT

xn XXKYYSKKSKSXX

Limb Profiler

Ozone

DensityAerosol

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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Accuracy and Precision Error Terms

Sensor Algorithm Pointing/AltitudeAlbedo calibration-Independent

Rayleigh ScatteringCoefficients

Boresight alignment

Albedo calibration-Dependent

Ozone Absorption Coefs,including T dep

Sensor misalignment

Pixel-Pixel Aerosol correction Alignment knowledgeWavelength calibration MS table interpolation and

retrieval errorStructural/thermal distortion

On-orbit wavelength shifts Neutral number density Ephemeris knowledge, radialPolarization Non-homogeneous scene Attitude reference knowledgeA

cc

ura

cy

Straylight Cloud top/surface pressure

Random noise Ozone absorption coefs, Tdependence

Altitude registration

Neutral number density

Aerosol correctionOzone inhomogeneity-LOS

Ozone inhomogeneity-crosstrack

Cloud fraction/reflectivity

Surface reflectivity

Pre

cisi

on

Cloud top/surface pressure

Limb Profiler

Sensitivity studies presented

Complete error budget in ATBD-http://npoesslib.ipo.noaa.gov

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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

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Ozone sensor precision errors meet allocations for most model atmospheres

TOMS V7 Standard profiles Background volcanic aerosol (May 9, 1991 30.1N)

Sensor

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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

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Limb profile altitude registration algorithm flow

2 minimization

Calculate LP radiances

Calibrated LP

RadiancesWrite 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

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Summary of C-sigma and RSAS accuracy errors

Pointing - Altitude Reg.

C & RSAS

LP OOB Stray Light (no correction)

23 m 13 m

NP long-term drift 100 m N/A

NP retrieval errors ~ 500 m N/A

Aerosols (aged volcanic)

TBD 1000 m

CrIS T = 1K N/A 26 m

CrIS psurf = 2 mb 55 m 55 m

Total (RSS) ~ 500 m ~ 1000 m

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

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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

C & RSAS

LP SNR 0.1 m 3.3 m

NP SNR 2.5 m N/A

NP retrieval errors ~ 100 m * N/A

Aerosol variation TBD 165 m

Surface / ozone inhomogeneity

TBD < 1100 m

CrIS T (s = 1K) N/A 26 m

CrIS p vs. Z (ssurf = 2 mb)

55 m 55 m

Total (RSS) ~ 120 m 1100 m

UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003

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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 2002-2003 First NPOESS flight currently planned for 2011

– Early flight of opportunity on NPP (Launch 2006)

Limb Profiler