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National Oceanic and Atmospheric Administration Cooperative Remote Sensing Science and Technology Center

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Limb Scattering Radiative Transfer Model Development in Support of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler Mission

Robert Loughman, David Flittner, Ernest Nyaku,P.K. Bhartia and Lawrence Flynn


SATELLITE

TANGENT HEIGHT

LINE OF SIGHT

SOLAR IRRADIANCE

SURFACECLOUDS

MULTIPLE SCATTERING

SINGLE SCATTERING

Outline

• Review of OMPS and Limb Scattering (LS) • Reasons for studying stratospheric aerosol• Improving the OMPS LS Radiative Transfer Model• Conclusions and Future Work


OMPS Mission

OMPS = Ozone Mapping and Profiler SuiteLP = Limb Profiler

• 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


• 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:

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.



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.



• 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.

OMPS LP Radiative Transfer


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


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)


SS radiance improves greatly


GSLS RTM approximate MS

Fig. 9 of Loughman et al. (2004)

• This approximation minimizes the time required for multiple scattering MS - the slowest step in the RTM calculation

• But it leads to large radiance errors for cases when the radiation field varies rapidly along the line of sight

Multiple scattering is calculated at just one zenith: ↓


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 fieldso Horizontal variation

of atmospheric properties

o Near-twilight conditions


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


• 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

GSLS scalar radiance error


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


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


• At z = 20 km the aerosol size distribution (ASD) tends to contain larger particles, relative to z = 25 km

Stratospheric ASD measurements

Thanks to Deshler et al. for balloon measurements of aerosol properties at Laramie, Wyoming, 2012

• Recent RTM updates allow us to simulate this variation


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


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.


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


THE END


Backup Slides


Updated Model (Review)


So far, I’ve:

• Stripped down LP_RAD_SIMUL to make a single-wavelength, single-zenith model.

• Verified that the single-wavelength, single-zenith model replicates the Loughman et al. (2004) calculations for Rayleigh and Rayleigh + HG aerosol cases (in both scalar and vector modes).

• Begun to experiment with MS calculations at multiple zeniths.

MS can be calculated at several zeniths:↓ ↓ ↓ ↓ ↓


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


SS comparison to Siro • Wavelengths are 325, 345, and 600 nm

• Azimuth angles = 20 (solid), 90 (dashed), and 160 (dot-dashed) 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)


SS comparison to Siro (L04 vs current)


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


TS comparison to Siro (1 zenith vs 17 zeniths)


Aerosol Jacobians for event 151 (SSA = 24°)

Surface reflectivity = 0

λ = 325 nm




λ = 385 nm




λ = 521 nm




λ = 756 nm




λ = 1020 nm


ASD measurements


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• 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):

ASD measurements

Z(km) na,1 (cm-3) na,2 (cm-3) ra,1 (μm) ra,2 (μm) σ1 σ2

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


• At z = 20 km the distribution contains larger particles, relative to z = 25 km

ASD measurements

Thanks to Deshler et al., balloon measurements at Laramie, Wyoming, 2012


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


Difference in phase function, 449 nmTotal 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


Change in radiance, 676 nmDifference

shown for TH = 20, 25, 30, 35, 40 km

Effect covers a broad portion of the orbit, and exceeds ±20%


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

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