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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
Use or disclosure of this informationmay 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 informationmay be subject to United States export
control laws. For official use only.
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
Use or disclosure of this informationmay 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 informationmay 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 informationmay 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 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
Use or disclosure of this informationmay be subject to United States export
control laws. For official use only.
7
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
Use or disclosure of this informationmay 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
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
Use or disclosure of this informationmay 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 informationmay 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
SurfaceReflectance
NeutralNumberDensity
CloudFraction
Limb Profiler
UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003
Use or disclosure of this informationmay 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
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
Use or disclosure of this informationmay 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
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
Use or disclosure of this informationmay 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 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
Use or disclosure of this informationmay be subject to United States export
control laws. For official use only.
14
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
Use or disclosure of this informationmay 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 informationmay 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, 1991 30.1N)
Sensor
UV/VIS Limb Scatter Workshop- University of Bremen April 14-16, 2003
Use or disclosure of this informationmay 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 informationmay 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
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
Use or disclosure of this informationmay be subject to United States export
control laws. For official use only.
19
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
Use or disclosure of this informationmay 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
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
Use or disclosure of this informationmay 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 2002-2003 First NPOESS flight currently planned for 2011
– Early flight of opportunity on NPP (Launch 2006)
Limb Profiler