Variations of lower clouds and water vapor amount in deep ...mosir/pub/2019/2019-05-31/... · D....

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Variations of lower clouds and water vapor amount in deep Venus atmosphere based on night windows observations by the SPICAV- IR/Venus-Express D. Evdokimova 1,2 , A. Fedorova 1 , O. Korablev 1 , E. Marcq 2 , J.-L. Bertaux 1,2 (1) Space research institute (IKI) of the Russian academy of sciences, Russia (2) LATMOS-IPSL, France 03/06/2019 International Venus Conference 2019 1

Transcript of Variations of lower clouds and water vapor amount in deep ...mosir/pub/2019/2019-05-31/... · D....

Page 1: Variations of lower clouds and water vapor amount in deep ...mosir/pub/2019/2019-05-31/... · D. Evdokimova 11,2, A. Fedorova , O. Korablev 1, E. Marcq 2, J.-L. Bertaux 1,2 (1) Space

Variations of lower clouds and water vapor amount in deep Venus atmosphere based on

night windows observations by the SPICAV-IR/Venus-Express

D. Evdokimova 1,2, A. Fedorova 1, O. Korablev 1, E. Marcq 2, J.-L. Bertaux 1,2

(1) Space research institute (IKI) of the Russian academy of sciences, Russia

(2) LATMOS-IPSL, France

03/06/2019

International Venus Conference 2019

1

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SPICAV IR night nadir observations

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Spectral range 1.05 – 1.7 m

Covered transparency

windows

1.10 m

1.18 m

1.28 m

1.30 m

Spectral resolution 5.2 см-1

SPICAV – Spectroscopy for Investigation of Characteristics of the Atmosphere of Venus

Performing period – 2006-2014 years.

λ, μm R

ad

ian

ce, W

/m2/μ

m/s

tr

1.10

1.18

1.28

1.30 H2O

O2

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Night windows: SPICAV IR spectrum

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λ, μm

Rad

ian

ce,

W/m

2/μ

m/s

tr

1.10

1.18

1.28

1.30 H2O

O2

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Night windows at 1.74 and 2.3 µm: VIRTIS/VEX

McGouldrick & Tsang, 2017

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Optically thick

Reason for greenhouse

effect

H2O

H2O SO2

H2SO4

Aerosol of concentrated H2SO4 acid

Venus clouds

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Clouds model

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Haus et al., 2016

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SPICAV IR night nadir observations

Fluctuations of

mean value of

intensity

calculated in

maximum of

transparency

window (1.277-1.280

m)

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O2

MAX

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Radiative transfer model with multiple scattering

Model fixed parameters

Temperature and pressure – VIRA [Seiff, 1983]

CO2 lines – «High-T» database [Pollack, 1993]

Clouds aerosol – 75% H2SO4 solution

CO2 continuum factor [Fedorova et al., 2015]

1.28-μm – 0.75*10-9 cm-1 amagat-2 from (0.30-0.78)*10-9 cm-1 amagat-2

1.18-μm – 0.38*10-9 cm-1 amagat-2 from (0.29-0.66)*10-9 cm-1 amagat-2

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Method

SHDOMPP – method of spherical harmonical ordinates in plane

parallel atmospheres [Evans, 2007]

Look-up table with the nearest minimum adjustment

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Radiative transfer model with multiple scattering

Model fitting parameters

Common scaling factor applied to concentration

profiles of mode 2 and 3

H2O mixing ratio

H2O lines – the BT2 linelist [Barber et al., 2006]

Common surface emissivity

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Method

SHDOMPP – method of spherical harmonical ordinates in plane

parallel atmospheres [Evans, 2007]

Look-up table with the nearest minimum adjustment

SF – 5%, H2O – 2 ppmv, EMIS – 0.05

N2*SF

N3*SF

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Radiative transfer model with multiple scattering

Ob

s. n

um

ber

Ob

s. n

um

ber

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Preliminary results

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Scaling factor VMRH2O Coverage

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Conclusions

• SPICAV IR observations show in the 1.28 m transparency window that emission intensity is changing in range from 0.05 to 0.1 W/m2/m/sr

• Geographical distribution of window intensity does not exhibit any trends.

• Preliminary retrievals of water vapor VMR below clouds seems uniform and constant at 24.5±2 ppmv

• Preliminary retrievals of cloud opacity show some spatial variability yet to understand.

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