Limb Scattering Radiative Transfer Model
Development in Support of the Ozone Mapping
and Profiler Suite (OMPS) Limb Profiler Mission
Space Shuttle
limb view
Robert Loughman, David Flittner, Ernest Nyaku,
P.K. Bhartia and Lawrence Flynn
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Outline
• Review of OMPS and Limb Scattering (LS)
• Reasons for studying stratospheric aerosol
• Improving the OMPS LS Radiative Transfer Model
• Conclusions and Future Work
SOLAR IRRADIANCE
MULTIPLE SCATTERING
SATELLITE
LINE OF SIGHT
SINGLE SCATTERING
TANGENT HEIGHT
CLOUDS
SURFACE
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
OMPS Mission
• OMPS launched on the
Suomi NPP satellite in October
2011
•The mission of OMPS is to
continue the long-term ozone
record for trend assessment
• But the properties of other
species (such as aerosol) must
also be known to achieve the
desired ozone retrieval
performance
OMPS = Ozone Mapping
and Profiler Suite
LP = Limb Profiler
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Why worry about Stratospheric Aerosol?
• Poor estimates of stratospheric aerosol → poor ozone profile
retrievals.
• Stratospheric aerosol has a significant cooling effect on
climate: Some radiation that would have reached the lower
atmosphere is instead reflected back to space.
• Important questions persist about the processes that govern
stratospheric aerosol:
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Why worry about Stratospheric Aerosol?
1. Solomon et al. (2011) challenges the simplistic model that the
stratosphere has a well-defined “background aerosol level”
that is perturbed by irregular volcanic eruptions (such as
Pinatubo).
•
Brief summary: Recent measurements show that
stratospheric aerosol is changing in unexpected ways
(~50% increase from its minimum level, despite a notable
lack of explosive volcanic eruptions).
•
Bottom line: Failure to capture these stratospheric aerosol
changes may lead climate models to make poor
predictions of future temperature variations.
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Why worry about Stratospheric Aerosol?
2. Bourassa et al. (2012), Fromm et al. (2013), Vernier et al. (2013)
and finally Bourassa et al. (2013) have engaged in a spirited
debate concerning recent measurements of stratospheric aerosol.
Brief summary: All agree that the 2011 Nabro eruption caused
aerosol to appear in the stratosphere, but they sharply disagree
about how it got there – injection, or transport, or both?
Bottom line: Debates about the mechanisms that control the
abundance of aerosol in the stratosphere continue. Recent
analyses have shown that tropospheric aerosol can be injected
into the stratosphere (e.g., during forest fires, Fromm et al., 2010).
If tropospheric injection is a significant source of stratospheric
aerosol, that has significant implications for future climate.
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
OMPS LP Radiative Transfer
• The OMPS ozone and aerosol profile retrieval algorithms
fundamentally depend upon comparing measured radiances
to calculated radiances.
• The level of agreement between these two sets of radiances
is a key part of our assessment of the OMPS instrument.
• The calculated radiances in the OMPS come from a version
of the GSLS radiative transfer model (RTM) that has been
highly optimized for speed.
• In the past year, I was asked by the OMPS Science Team to
revisit the RTM, with the aim of repairing some known defects
that cause systematic errors in the calculated radiances.
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Single-scattering comparison to Siro benchmark
• Wavelengths are 325, 345, and 600 nm
• Azimuth angles = 20° (solid), 90° (dashed), and 160°(dot-dashed)
• Solar zenith angles (SZA) = 15° & 60° (left), 80° & 90° (right)
• Thin line = smaller SZA, thick line = larger SZA in each picture
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Refinement of atmospheric representation
• A known deficiency (see Loughman et al., 2004) of the
GSLS model concerns its calculation of the optical path
length τ through an atmospheric layer, given the
extinction coefficient β and path length s:
• GSLS model (for all but the tangent layer) makes an
error that → 1% as θ → 90°: τ = s * (layer avg β)
• Updated model:
τ = ∫ β ds
(allowing β to vary as a linear function of height)
(NOTE that the Siro benchmark model uses the
updated model’s approach)
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SS radiance improves greatly
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
GSLS RTM approximate MS
Multiple scattering is calculated at just one zenith:
↓
• This approximation
minimizes the time
required for
multiple scattering
MS - the slowest
step in the RTM
calculation
Fig. 9 of Loughman et al. (2004)
• But it leads to large
radiance errors for
cases when the
radiation field
varies rapidly along
the line of sight
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Updated RTM
MS can be calculated at several zeniths:
↓
↓
↓
↓
↓
• This model is
several times
slower than GSLS,
but it allows us to
better simulate:
o Broken cloud fields
o Horizontal variation
of atmospheric
properties
o Near-twilight
conditions
Fig. 9 of Loughman et al. (2004)
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Multi-zenith MS improvement
•
•
•
•
Same wavelengths and azimuth angles as previously
Concentrate on total radiance for large SZA (> 80°) cases
Left panel: GSLS calculations, 1 MS zenith
Right panel: Current calculations, 17 MS zeniths
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
GSLS scalar radiance error
• The GSLS model used for OMPS LP retrievals also neglects
polarization, and instead calculates approximate (scalar)
radiances.
• This approximation decreases the RTM computational
burden, and has little influence on the retrieval algorithms, but
it produces significant radiance errors (up to 12% worst case)
•The updated model has restored the capability to make
correct (vector) radiance calculations
• The scalar radiance error is shown on the following slides
for a simulated OMPS LP orbit
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
OMPS Variation of single-scattering angle
Small event
number: Early
orbit, Southern
Hem., large scat.
angle, backscatter view
Large event
number: Late
orbit, Northern
Hem., small scat.
angle, forwardscat. view
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Scalar radiance error at 40 km
Error is shown for λ =
325, 345, 385, 400,
449, 521 nm (solid
lines) and 602, 676,
756, 869, 1020 nm
(dashed line)
Same scalar radiance
error pattern
prevails for all
wavelengths
Amplitude approaches
10 % at 345 nm
(-3.5% to +5.5%),
for R = 0.3
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Stratospheric ASD measurements
• At z = 20 km the aerosol size distribution (ASD)
tends to contain larger particles, relative to z = 25
km
• Recent RTM
updates allow
us to simulate
this variation
Thanks to Deshler et al.
for balloon
measurements of
aerosol properties at
Laramie, Wyoming,
2012
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
ASD effect on radiance, 676 nm
The radiance
difference is
shown for TH
= 20, 25, 30,
35, 40 km
The ASD effect
exceeds
±20% for a
broad portion
of the orbit
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Conclusions and Future Work
• OMPS LP instrument and retrieval algorithms are
performing well
• But the more accurate RTM described herein will
help us understand the measurements better, and
enable retrievals for previously unpromising
situations (large SZA, broken cloud fields, variable
aerosol properties, etc.)
• Systematically analyze the impact of these RTM
improvements in the ozone and aerosol retrievals
• Develop innovative retrievals that extract more
useful information from OMPS LP radiance data.
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Acknowledgements
• NASA NPP Science Team and NOAA / CREST for
supporting LS research
• Didier Rault, for his work leading the development of
the OMPS LP retrieval algorithm
• The OSIRIS, SCIAMACHY, SAGE II, SAGE III, and
U. of Wyoming measurement teams, for maintaining
and sharing their high-quality data sets
• Ghassan Taha, Zhong Chen, Nick Gorkavyi, Philippe
Xu, and Leslie Moy for helpful discussions
• Daryl Ludy, Ricardo Uribe and Curtis Driver for their
help with testing the algorithms as students
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
THE END
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Backup Slides
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Updated Model (Review)
MS can be calculated at several zeniths:
↓
↓
↓
↓
↓
So far, I’ve:
• Stripped down
LP_RAD_SIMUL to make
a single-wavelength, singlezenith model.
• Verified that the singlewavelength, single-zenith
model replicates the
Loughman et al. (2004)
calculations for Rayleigh
and Rayleigh + HG aerosol
cases (in both scalar and
vector modes).
Fig. 9 of Loughman et al. (2004)
• Begun to experiment with
MS calculations at multiple
zeniths.
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Refinement of atmospheric representation
• A known deficiency of the GSLS and
LP_RAD_SIMUL models concerns its
calculation of the optical path length τ through
an atmospheric layer (path length = s):
• Current model: τ = s * (layer avg ext coef)
• Updated model: τ = ∫ (ext coef) ds
(allowing ext coef to vary as a linear function of
height)
• NOTE: Siro (benchmark) model uses the updated
approach
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
SS comparison to Siro
•
Wavelengths are 325, 345, and 600 nm
•
Azimuth angles = 20 (solid), 90 (dashed), and 160 (dotdashed) deg
•
Solar zenith angles are 15, 60, 80 and 90 deg
•
Thin line = smaller SZA, thicker line = larger SZA in each
picture
•
Top panel: L04 calculations (constant ext coef within each
layer)
•
Bottom panels: Current calculations (ext coef is a linear
f(height) within each layer)
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
SS comparison to Siro (L04 vs current)
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Now add multiple zeniths
•
Same wavelengths (325, 345, and 600 nm)
•
Same azimuth angles (20, 90 and 160 deg)
•
Same solar zenith angles, except that 90 deg is
excluded (model fails for MS calculation below
horizon), so only (15, 60 and 80 deg) remain
•
Top panel: Current calculations, 1 MS zenith
•
Bottom panel: Current calculations, 17 MS zeniths
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TS comparison to Siro (1 zenith vs 17 zeniths)
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Aerosol Jacobians for event 151 (SSA = 24°)
Surface
reflectivity
=0
λ = 325 nm
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Aerosol Jacobians for event 151 (SSA = 24°)
Surface
reflectivity
=0
λ = 385 nm
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Aerosol Jacobians for event 151 (SSA = 24°)
Surface
reflectivity
=0
λ = 521 nm
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Aerosol Jacobians for event 151 (SSA = 24°)
Surface
reflectivity
=0
λ = 756 nm
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Aerosol Jacobians for event 151 (SSA = 24°)
Surface
reflectivity
=0
λ = 1020 nm
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ASD measurements
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
ASD measurements
• To see how these ASDs affect the extinction
coefficient and phase function, I made
calculations using the average characteristics
for z = 20 km and z = 25 km (averaging over
the 6 Laramie measurements from 2012):
ra,2 (μm) σ1
σ2
Z(km) na,1 (cm-3)
na,2 (cm-3)
ra,1
(μm)
20
6.572
0.5364
0.07655 0.2645
1.31
1.485
25
5.718
0.2347
0.05105 0.2025
1.438
1.15
[ln(ra / r0,1 )]2
na ,1
dna

exp 
0.5
dra
ra (2 ) ln  1
2[ln 1 ]2
{
na , 2
}  r (2 )
a
0.5
ln  2
{
exp 
[ln(ra / r0, 2 )]2
2[ln 2 ]
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2
}
ASD measurements
• At z = 20 km the distribution contains larger
particles, relative to z = 25 km
Thanks to Deshler et al.,
balloon measurements
at Laramie, Wyoming,
2012
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
OMPS Variation of single-scattering angle
Small event number:
Early orbit,
Southern Hem.,
large scat. angle,
back-scatter view
Large event number:
Late orbit,
Northern Hem.,
small scat. angle,
forward-scat. view
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Difference in phase function, 449 nm
Total phase function
shown for TH = 20,
25, 30, 35, 40 km
Solid = ASD20, dashed
= ASD25
Black line = Rayleigh
As Rayleigh scattering
weakens, the aerosol
difference has a
larger effect on the
overall phase
function, over a
broader range of
events
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Change in radiance, 676 nm
Difference
shown for TH
= 20, 25, 30,
35, 40 km
Effect covers a
broad portion
of the orbit,
and exceeds
±20%
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center
Scalar radiance error at 40 km
Error is shown for λ =
325, 345, 385, 400,
449, 521 nm (solid
lines) and 602, 676,
756, 869, 1020 nm
(dashed line)
Same scalar radiance
error pattern
prevails for all
wavelengths
Amplitude approaches
10 % at 345 nm
(-3.5% to +5.5%),
for R = 0.3
National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center