optical properties

1
Optical properties Satellite observation ? T,H 2 O… From dust microphysical properties to dust hyperspectral infrared remote sensing Clémence Pierangelo (1) , Michael Mishchenko (2) , Alain Chédin (1) (1) Laboratoire de Météorologie Dynamique - Institut Pierre Simon Laplace, Ecole Polytechnique (2) Goddard Institute for Space Sciences – NASA [email protected] Dust optical properties at infrared wavelengths Dust optical properties at infrared wavelengths Radiative transfer computations with aerosols at infrared wavelengths Radiative transfer computations with aerosols at infrared wavelengths Remote sensing of dust with hyperspectral infrared sounders : Application Remote sensing of dust with hyperspectral infrared sounders : Application to AIRS to AIRS IPCC 2001: dust radiative forcing poorly known. Since then, most studies focus on the visible wavelength, whereas the closure of the Earth radiative balance also needs knowledge of the dust effect on terrestrial and atmospheric infrared radiation (3.5 to 15 µm), and computations of IR forcing from visible or near-IR measurements are not reliable enough. For realistic values of r e (1 to 3µm), moderate impact on , g and Q ext normalized (max 30%). y studying dust in the infrared? Advantages: night and day detection • sensitivity to dust vertical distribution : altitude retrieval • sensitivity to dust mineralogical composition : might be retrieved • over deserts Limitations: Spatial resolution (20km) • Aerosol refractive indices poorly known + high spectral dependency • High sensitivity to temperature and gas profiles •No direct validation Optical depth Layer altitude BT 177 (8.14µm)– BT 165 (9.33µm)(K.) Simulations for 100 tropical atmospheric situations (Same aerosol properties) The aerosol impact itself depends on the atmospheric situation First component to the signal: the temperature and the water vapor profiles. The error in the retrieval caused by the use of spherical particles is below 10% for the AOD, and still lower for the altitude Very strong effect of the refractive index on the AOD!!! But, with the data sets “dust”, “mineral” or “SHADE”, the retrieved AOD could not be greater than 0.5… way to exclude these models Purpose: modelling of the maximum effect of shape: spheroids with aspect ratio=2 (effect stronger than a mixture of spheroids with several aspect ratios) 9.5 m 9.5 m 9.5 m 3.75 m C ext 3.75 m g 3.75 m Optical properties are greater for oblate or prolate spheroids than spheres. The maximum impact is about 10%. Weak impact of the aspect ratio on the phase function because the size parameter is relatively small. Note that the impact of the phase function on the radiance at satellite level is not as crucial as in the visible (no reflected solar radiation). INFRARED VISIBLE/NEAR-IR REFRACTIVE INDEX +++ High variability of the refractive indices with the wavelength and with the dust model + Dependency of the refractive indices to the wavelength pretty well known SIZE DISTRIBUTION ++ Moderate impact +++ High impact SHAPE + Small impact (no impact on phase function for longwave) ++ Moderate impact on phase function with effect on the solar reflected radiance Simulations of AIRS (Advanced Infrared Sounder-AQUA) brightness temperatures for 324 channels with a code coupling the line-by-line « 4A » and DISORT The impact of size is greater in the visible than in the IR. The ratio of IR to visible extinction increases with dust size. Huge variability of refractive indices with wavelength + with data set… Aerosol optical depth (AOD) and altitude impact: a few K. Aerosol size and shape impact: a few tenth of K. Aerosol microphysical properties -Size distribution -Refractive index at each wavelength -Shape Aerosol optical properties -Extinction cross- section C ext / efficiency Q ext -Single-scattering albedo -Phase function or asymetry parameter g -Mie code -T Matrix code Imaginary part Real part … and big variability of optical properties with data set too! (“SHADE” model probably not realistic) Q ext g g Norm. Q ext Norm. Q ext Wavelength (µm) Q ext Wavelength (µm) Refractive index is a more problematic issue than size or shape 1. effective radius 3. Refractive indices 2. shape 1. Dust altitude and 10 µm AOD (LUT retrieval) 2. Optical depth and altitude 3. Size and shape size BT (3µm-1µm) shape BT (spheroids-spheres) 1. Atmospheric situation 3. Dust effective radius Method: Look-Up-Tables (LUT) built for 8 AIRS channels, several dust altitudes and 10 µm AOD, one aerosol model (OPAC) and almost 600 atmospheric situations (Pierangelo et al., ACP, in press) Method: Channel 165 (1072cm -1 ) sensitive to size, not to shape 2. Validation of the LUT approach Validation of the LUT retrieved atmospheric situation is performed comparing its surface temperature (SST) and water vapor content (WVC) to MODIS / SSMI observations. RetrievalAtmosph ere, dust AOT, dust altitude BT 165 (re) calculated BT 165 observed Validation with simulations Results: April-May 2003 The effective radius of Saharan dust decreases from 2.8 µm to 1.2 µm with transport. The error in the retrieval caused by the use of one fixed size distribution is below 10% for the AOD, and still lower for the altitude Robustness of the retrieval to dust microphysical properties aspect ratio aspect ratio OPAC Volz SHADE dust mineral OPAC Volz SHADE dust mineral Input AOD Output AOD Effective radius (µm) Effective radius (µm) Size Ref. indices Shape AIRS 10 µm AOD AIRS dust altitude MODIS 0.55 µm AOD April 2003 September 2003 August 2003 July 2003 June 2003 May 2003 Microphysical properties Reid et al., 2003 3.75 m 9.5 m Phase function 285 30 3 SST (K) MODIS night SST AIRS night SST July 2003 0 60 WVC (mm) AIRS night WVC SSMI WVC night+day July 2003

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From dust microphysical properties to dust hyperspectral infrared remote sensing. Optical depth. Layer altitude. BT 165 (re) calculated. BT 165 observed. aspect ratio. Volz. Volz. dust. dust. OPAC. OPAC. mineral. mineral. SHADE. SHADE. - PowerPoint PPT Presentation

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Page 1: Optical properties

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Optical properties Satellite observation

?T,H2O…

From dust microphysical properties to dust hyperspectral infrared remote

sensingClémence Pierangelo(1), Michael Mishchenko(2), Alain Chédin(1) (1) Laboratoire de Météorologie Dynamique - Institut Pierre Simon Laplace, Ecole Polytechnique

(2) Goddard Institute for Space Sciences – [email protected]

Dust optical properties at infrared wavelengthsDust optical properties at infrared wavelengths

Radiative transfer computations with aerosols at infrared wavelengthsRadiative transfer computations with aerosols at infrared wavelengths

Remote sensing of dust with hyperspectral infrared sounders : Application to AIRSRemote sensing of dust with hyperspectral infrared sounders : Application to AIRS

IPCC 2001: dust radiative forcing poorly known. Since then, most studies focus on the visible wavelength, whereas the closure of the Earth radiative balance also needs knowledge of the dust effect on terrestrial and atmospheric infrared radiation (3.5 to 15 µm), and computations of IR forcing from visible or near-IR measurements are not reliable enough.

For realistic values of re (1 to 3µm), moderate impact on , g and Qext normalized (max 30%).

Why studying dust in the infrared? Advantages:• night and day detection• sensitivity to dust vertical distribution : altitude retrieval• sensitivity to dust mineralogical composition : might be retrieved• over deserts

Limitations: • Spatial resolution (20km)• Aerosol refractive indices poorly known + high spectral dependency• High sensitivity to temperature and gas profiles•No direct validation

Optical depth Layer altitude

BT 177 (8.14µm)– BT 165 (9.33µm)(K.)Simulations for 100 tropical atmospheric situations (Same aerosol properties)

The aerosol impact itself depends on the atmospheric situation

First component to the signal: the temperature and the water vapor profiles.

The error in the retrieval caused by the use of spherical particles is below 10% for the AOD, and still lower for the altitude

Very strong effect of the refractive index on the AOD!!! But, with the data sets “dust”, “mineral” or “SHADE”, the retrieved AOD could not be greater than 0.5… way to exclude these models

Purpose: modelling of the maximum effect of shape: spheroids with aspect ratio=2 (effect stronger than a mixture of spheroids with several aspect ratios)

9.5 m 9.5 m9.5 m

3.75 mCext

3.75 mg

3.75 m

Optical properties are greater for oblate or prolate spheroids than spheres. The maximum impact is about 10%.

Weak impact of the aspect ratio on the phase function because the size parameter is relatively small.Note that the impact of the phase function on the radiance at satellite level is not as crucial as in the visible (no reflected solar radiation).

INFRARED VISIBLE/NEAR-IR

REFRACTIVE INDEX

+++ High variability of the refractive indices with the wavelength and with the dust model

+ Dependency of the refractive indices to the wavelength pretty well known

SIZE DISTRIBUTION

++ Moderate impact +++ High impact

SHAPE+ Small impact (no impact on phase function for longwave)

++ Moderate impact on phase function with effect on the solar reflected radiance

Simulations of AIRS (Advanced Infrared Sounder-AQUA) brightness temperatures for 324 channels with a code coupling the line-by-line « 4A » and DISORT

The impact of size is greater in the visible than in the IR.The ratio of IR to visible extinction increases with dust size.

Huge variability of refractive indices with wavelength + with data set…

Aerosol optical depth (AOD) and altitude impact: a few K. Aerosol size and shape impact: a few tenth

of K.

Aerosol microphysical properties-Size distribution-Refractive index at each wavelength-Shape

Aerosol optical properties-Extinction cross-section Cext

/ efficiency Qext

-Single-scattering albedo -Phase function or asymetry parameter g

-Mie code-T Matrix code

Imaginary part Real part… and big variability of optical properties with data set too!(“SHADE” model probably not realistic)

Qext g

gNorm. Qext

Norm. Qext

Wavelength (µm)

Qext

Wavelength (µm)

Refractive index is a more problematic issue than size or shape

1. effective radius

3. Refractive indices

2. shape

1. Dust altitude and 10 µm AOD (LUT retrieval)

2. Optical depth and altitude 3. Size and shape

size

BT (

m-1

µm

)

shapeB

T (

sph

ero

ids-

sph

ere

s)

1. Atmospheric situation

3. Dust effective radius

Method: Look-Up-Tables (LUT) built for 8 AIRS channels, several dust altitudes and 10 µm AOD, one aerosol model (OPAC) and almost 600 atmospheric situations (Pierangelo et al., ACP, in press)

Method: Channel 165 (1072cm-1) sensitive to size, not to shape

2. Validation of the LUT approachValidation of the LUT

retrieved atmospheric situation is performed comparing its surface temperature (SST) and water vapor content (WVC) to MODIS / SSMI observations.

RetrievalAtmosphere, dust AOT, dust altitude

BT 165 (re)

calculated BT 165

observed

Validation with simulations

Results: April-May 2003

The effective radius of Saharan dust decreases from 2.8 µm to 1.2 µm with transport.

The error in the retrieval caused by the use of one fixed size distribution is below 10% for the AOD, and still lower for the altitude

Robustness of the retrieval to dust microphysical properties

aspect ratio aspect ratio

OPA

C

Volz

SH

AD

E

dust

min

era

l

OPA

C

Volz

SH

AD

E

dust

min

era

l

Input AOD Output AOD

Effective radius (µm)

Effective radius (µm)

Siz

eR

ef.

in

dic

es

Sh

ap

e

AIRS 10 µm AOD

AIRS dust altitude

MODIS 0.55 µm AOD

Apr

il 2

003

Sep

tem

ber

2003

Aug

ust 2

003

July

200

3Ju

ne 2

003

May

200

3

Microphysical propertiesReid et al., 2003

3.75 m

9.5 m

Phase function

285 303 SST (K)

MO

DIS

nig

ht S

ST

AIR

S n

ight

SS

T

July 2003

0 60WVC (mm)

AIR

S n

ight

WV

C

SS

MI

WV

C

nig

ht+

day

July 2003