DRAGON ADVANCED TRAINING COURSE IN …earth.esa.int/dragon/D3_L3_Kyrola.pdf · Day 3 Lecture 3...

Day 3 Lecture 3 Retrieval techniques - Erkki Kyrölä 1

DRAGON ADVANCED TRAINING COURSE IN ATMOSPHERE REMOTE SENSING

Occultation and limb scatteringErkki Kyrölä

Finnish Meteorological Institute

1. Instruments2. Occultation: GOMOS inversion

3. Limb scattering: OSIRIS inversion4. Summary

5. References



Occultation: SAGE, MSX UVISI, GOMOS, SCIAMACHY

Limb: OSIRIS, SOLSE/LORE, SCIAMACHY, GOMOS

INSTRUMENTS



Iref

occI

T(λ)= Iref(λ)Iocc(λ)

OCCULTATION

calibration free principle



GOMOS: Measured Sirius reference spectrum



GOMOS: Measured Sirius transmitted spectrum



GOMOS: Calculated Sirius transmissions



T(λ,z) = exp(− σ j (λ,T(z(s))ρ j∫∑ (z(s))ds) Beer-Lambert law

Occultation inversion is simple because...

But ...

Occultation inversion

sσ = cross section

z(s)

ρ = number density

= temperatureT



Weak scintillations: intensity maxima and minima

Density fluctuation

Strong scintillations: multiple stars

Stellar occultations: dilution & scintillations



T(λ,z,t2)

T(λ,z,t1)

different times

Stellar occultations: chromatic time delay

Different colors different refraction angles



T(z,λ) = Tref Text

We can, however, write

Transmission from refractive effects can be estimated from ray tracing calculations (dilution, chromatic effects). In addition, we need photometer measurements to estimate the random part (scintillations).



GOMOS: Horizontal transmissions 5-100 km

O3 inmesosphere

O3 instratosphere

NO2 instratosphere



T(λ,z) = exp(− σ j (λ)N∑ j(z))

N j (z) = ρ j∫ (z(s))ds

Occultation inversion using Beer-Lambert: Two step

Spectral inversion

Vertical inversion

This separation is not true if cross sections depend on temperature. In these cases we can use iteration over spectral and vertical inversion or one-step inversion.



C = covariance matrixT = transmission vector (all wavelengths)N = column density vector (different constituents)

We aim to minimize

Solution by Levenberg-Marquardt algorithm

Spectral inversion

S(N) = (Tobs − Tmod (N))T C−1((Tobs − Tmod (N))



Aspects of spectral inversion in UV-VIS

• Linearization• Non-linear approach

• Spectrally global• Spectral windows

• Absolute cross sections• DOAS



10-23

10-22

10-21

10-20

10-19

10-18

10-17

Cro

ss se

ctio

n (c

m 2

)

6000500040003000Wavelength (Å)

O3

NO2

O3

NO3

OClO

BrO

Cross sections



Transmission components at 27 km

ozone

NO2

NO3

Rayleigh

aerosol



An example of LM iteration

red=model to be fittedblue =data

black=residual



Chi2 vs iteration number



GOMOS vertical inversion

K =

d11

2d21 d22

2d31 2d32 d33

⎡

⎣

⎢ ⎢ ⎢ ⎢ ⎢ ⎢

⎤

⎦

⎥ ⎥ ⎥ ⎥ ⎥ ⎥

Discretize N(z) = ρ∫ (z(s))ds

N = Kρ

where the kernel matrix is

Onion peel solution

d11d22 d21



Tikhonov regularization



• Data extraction• Datation•Geolocation (ECMWF+MSIS90)• Wavelength assignment• Spectrometer samples correction• Photometer data processing• Central band background estimation• Star spectra computation• Transmission computation• Products generation

GOMOS Level 1b



GOMOS level 1Raw data

Geolocation& ray tracing

Instrumentalcorrections

Photometerdata

Transmissiondata

Limbdata

ECMWFprediction/analysisMSIS90

Calibrationdatabase



GOMOS level 2

Crosssections

Spectralinversion

Local densitiesO3, NO2, NO3aerosols, AirT, H2O, O2

Verticalinversion

Line densities

Level 1transmissions

Dilution& scintillation

corrections

Level 1photometer

data



LIMB SCATTERING



OSIRIS radiances



Scattered limb radiances

Total radiance= single scattering + multiple scattering

I = Isun Tsun∫ (s)(ρa (s)σ a (λ)Pa + ρR (s)σ R (λ)PR )Tdet (s)ds + Ims

s



Single and multiple scattering



Difficulties in limb radiative transfer

• MS time consuming• Albedo• Clouds• Aerosols• Polarization• Raman scattering



Modified onion peeling method

M = Itotal

I ss

S(ρ) = RModel − RMeas[ ]T ⋅ C −1 ⋅ RModel − RMeas[ ]

Measured transferspectra:

Modelled transfer

spectra:

Robs(z,λ) = Iobs(z,λ)Iref (zref ,λ)

Rmod (z,λ) = Imodss (ρ, z,λ )

Imodref (ρref , zref ,λ)

⋅ M

tabulated

Minimize

with onion peel type inversion or with one-step inversion



An example of LM iteration at 32 km (LimbLab SS)



An example of LM iteration at 24 km (LimbLab SS)



Summary

DOAS with spectral windowsFlittner for limb scattering; 3 wavelengths

Occultation and limb scattering retrievals can be approachedwith similar methods. They are based on:

-non-linear approach-using relative quantities, not directly measured quantities-original cross sections-all wavelengths

Other methods

Difficulties : Aerosol modelling, scintillations, multiple scattering



ReferencesThis presentation has followed:

Kyrölä, E., E. Sihvola, M. Tikka, Y. Kotivuori T. Tuomi, and H. Haario, Inverse Theory for Occultation Measurements 1. Spectral Inversion, J. Geophys. Res., 98, 7367-7381, 1993.

Oikarinen, L., E. Sihvola, and E. Kyrölä, Multiple scattering radiance in limb-viewing geometry, J. Geophys. Res., 104, 31261-31274, 2000.

Auvinen, H., L. Oikarinen and E. Kyrölä, Inversion algorithms for limb measurements, J. Geophys. Res., 107, D13, 2001JD000407, ACH 7-1: 7-7, 2002

Reference search (free): http://adsabs.harvard.edu/abstract_service.htmltitle words: osiris gomos sciamachy msx solse loreabstract words: retrieval limb occultation

More references from

Numerical examples: GomLab and LimbLab

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