ADEOS-II

Stratospheric aerosol and cloud characterization

from ILAS observations(extended)

Sergey Oshchepkov

Yasuhiro Sasano

Tatsuya Yokota

Hideaki Nakajima

Satellite Remote Sensing Research Team, National Institute for Environmental Studies, Tsukuba,

JAPAN

FUJITSU FIP Corporation, Tokyo,

JAPAN

Limb Workshop, Bremen, 14-16 April 2003

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What is the main importance of the aerosol retrievals for the ILAS?

• First of all, For the accurate gas retrievalsThe point is that Infrared transmission spectra are affected by aerosol components which is especially

true in the presence of PSC

• On the other hand, The aerosol information is of great interest in itselfin studying various heterogeneous reactions related to ozone depletion, etc.

Limb Workshop, Bremen, 14-16 April 2003

3

Sketch of the talk• Very short ILAS / ILAS-II overview (toward to

simultaneous gas and aerosol retrievals)

• Classification of aerosol retrievals for • the ILAS / ILAS-II data processing

• Short description of each method

• Representative results

Limb Workshop, Bremen, 14-16 April 2003

4

Limb Workshop, Bremen, 14-16 April 2003

- ILAS … was on board ADEOS (satellite) for the period from November 1996 to June 1997 - ILAS-II is currently on board ADEOS-II and has been launched in December 14th, 2002)

Short ILAS/ILAS-II overview (time period and main targets)

Both apparatus operate in the Solar occultation mode

The main target is to derive vertical profiles of O3, HNO3, CH4, H2O, N2O,

NO2, CFC-11, CFC-12, ClONO2, aerosol (related to ozone depletion)

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Expected ILAS-II 2D map in a day

Short ILAS/ILAS-II overview

(Observation Region)

N: 57-730 , S: 64-900

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Limb Workshop, Bremen, 14-16 April 2003

Spectral coverage:

Ch.1: 6.21 - 11.76 µm (44) Ch.2: 753- 784 nm

Altitude resolution: 1 kmAltitude observation: 10-60 km

ILAS ILAS-II has two additional channels

Short ILAS/ILAS-II overview (spectral coverage)

Spectral coverage:

Ch.1: 6.21 - 11.76 µm (44)Ch.2: 3.0- 5.7 µm (22)

Ch.3: 12.78- 12.85 µm

Ch.2: 753- 784 nm

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The main advantage of

ILAS-II versus ILAS due to additional IR spectral channels

from 3.0 to 5.7 µm is

1

2

OCSCFC 12CFC 11

CO CLONO2

N2O

CH4

HNO3

H2O

O3

N2O

5

CO2

0.05

0.10

0.15

0.20

0.25

0.005

0.010

0.015

0.020

3 4 5 6 7 8 9 10 11 120.000

0.001

0.002

0.003

0.004

Wavelength , (m)

CO2 CO Additional retrievals!

N2O H2O CH4Retrieval improvements!

Gas Optical Depth for layer of 20km 8

Classification of aerosol correction or retrievals using ILAS/ ILAS-II observations

(both in the operational data processing and for the future algorithms)

• Linear interpolation technique• Non linear interpolation using smoothness constraints

• Simultaneous gas and aerosol retrievals using aerosol physical modeling

- Simple gas Window Channel analysis for aerosol retrievals

- All channels analysis for simultaneous gas and aerosol retrievals

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Linear interpolation technique(the simplest way to take aerosol contribution into account)

3 4 5 6 7 8 9 10 11 120.0

0.1

0.2

STS

NAT

CH4

NO2

H2O

NO2

Op

tica

l Dep

th

Wavelength (m)

3 4 5 6 7 8 9 10 11 120.0

0.1

0.2

0.3

0.4

0.5

0.6

Op

tica

l Dep

th

Wavelength (m)

To realize the technique1. The aerosol optical depth is estimated

at the gas window channels;

2. Climatological gas data set is used to

subtract the remainder gas contribution;

3. Then, linear interpolation is utilized to estimate

the optical depth over all channels.

The main problem isThe broken line is not representative enough

to describe real aerosol spectra

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Non linear “interpolation” method

22,

min{( ( , ) ) ( ( , ) ) ( ) ( )}T TT 2 2 2 2C σ

T C σ T* W T C σ T* S σ Δ W S σ Δterm

of transmission data

term of smoothness

constrains on desiredaerosol spectra

In this method, gas concentrations and aerosol extinction coefficient spectra are subjects of simultaneous retrievals

The good point: there is no need to make aerosol physical modeling

The bad point: it is quite difficult to choose appropriate level of smoothness constraints

for low spectral resolution

The Chi square minimization procedure is extended here by additional

7 8 9 10 11 12 13 14-10

-5

0

5

10 O

3 0.09

NO2 0.05

HNO3 0.08

N2O 0 05

CH4 0.13

H2O 0.10

CFC-11 0.04CFC-12 0.05CO

2 0.09

COF2 0.04

N2O

5 0.02

Total 0.15

For

Gas

Spe

cies

Wavelength , (m)

-10

-5

0

5

10

Sulfuric 0.93Ice 9.52NAT 0.91HNO3 1.20 NAM 0.28NAD 0.25

For

Aer

osol

Com

pone

nts

11

Method of simultaneous gas and aerosol retrievals using aerosol physical modeling

(set up for the inverse problem)

( ), ()aerosoli

ih C h ˆiInfrared Channels

The main question is how to select representative aerosol

component the inverse modeling?

In both techniques the AEC is presented through linear combination of the basic

aerosol components:

Then, subject of the retrievals is aerosol volume density profileat a given specific spectrum for each component

1. representative & 2. retrievable

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Method of simultaneous gas and aerosol retrievals using aerosol physical modeling

(component selection)

190K

220K

6

5

4

3

2

1

0

Par

ticl

e R

adiu

s (

m)

Supercooled Ternary Solution (0.075-1µm)

Nitric Acid Trihydrate (0.5-2µm)Nitric Acid Dihydrate (0.5-2µm)

Water Ice (1-5 µm)

All of these component are retrieved simultaneously

in rather a wide range of particle sizes

There are some physical assumptions like temperature dependence of

size and component composition for both internal and external mixture

(Rm)

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12 Basic aerosol spectral functions used in the inverse modeling

0.5

1.0

1.5

2.00.5m1.0m2.0m

Nitric Acid Trihydrate

0.5

1.0

1.5 0.075m (75% H2SO

4)

0.5m (24% HNO3)

1.0m (40% HNO3)

Ext

inct

ion

Co

effi

cien

t (

m-1)

Supercooled Ternary Solution

3 4 5 6 7 8 9 10 11 12

0.5

1.01.0m2.0m5.0m

Wavelength (m)

Water Ice

3 4 5 6 7 8 9 10 11 12

0.5

1.0

1.5

2.00.5m1.0m2.0m

Wavelength (m)

Nitric Acid Dihydrate

The simplest explanation to recognize between selected components is

their different spectral features

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Aerosol retrievals using aerosol physical modeling(Window Channel Analysis)

2

2 2 Tmin

[ ]( ) ({ }

W)

km

n

k mn n

mn

n

kn

km

kna

C

B B

a a

Using these base function, the numerical procedure constitutes weighted least

square minimization procedure with smoothness and positive constraints

on the desired aerosol volume vertical profiles

The good point: is very rapid data processing with small amount of aerosol look up table

The bad point: is the window channel data might be affected by gas contribution and limited … that is the reason

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Method of simultaneous gas and aerosol retrievals from

the total transmission measurements is priority!!!

Among other features, the numerical solution involves:

- Levenberg-Marquardt iteration procedure

- Positive constraints for both gas and aerosol profiles (through penalty functions)

- Onion peeling technique

- HITRAN database for gas cross sections

In this method, a set up for the inverse problem involves simultaneous retrievals

of 14 GASES

and 4 types of AEROSOL

O3 HNO3 CH4 H2O, N2O NO2 CFC-11 CFC-12 ClONO2 N2O5 CO2 CO OCS N2O5

Supercooled Ternary Solution (weights of Nitric & Sulfuric acid are available)

Nitric Acid Trihydrate, Nitric Acid Dihydrate, Water Ice

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Aerosol retrievals from Window Channel Data(An example of background aerosol)

The retrieval volume density profiles (black linesblack lines) are supported here by error bars and independent equilibrium thermodynamic predictions (red symbolsred symbols) using Carslaw modeling.

… this is the first time such agreement has been obtained.

0.01 0.1

15

20

25

0.01 0.1

65.340S154.90W

Alt

utu

de

(km

)

0.01 0.1

Temperature (K)

Aerosol Volume Density (m3/cm3)

200205210215 200205210215

65.540S161.20W

65.290S175.20W

200205210215

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Aerosol retrievals from Window Channel Data

(Two typical examples of PSC state)

One of the reason for the multicomponent composition is that the occultation measurement has rather a long

path length and PSC are subject to to high horizontal chemical inhomogeneity.

15

20

25

30

0.01 0.1 1

Alt

itu

de

(km

)

theoretical STS theoretical NAT theoretical NAD

Aerosol Volume Density

180 190 200 210 220Temperature (K)

0.78 7 8 9 10 110.0

0.2

0.4

0.6

0.8

1.0Altitude 20 km

MeasurementsRetrievals

Total Aerosol STS NAT NAD Ice

Wavelength (m)

(k

m-1)

20

25

30

0.01 0.1 1

theoretical STS theoretical NAT theoretical NAD

Alt

itu

de

(km

)Aerosol Volume Density

180 190 200 210 220Temperature, (

0K)

0.78 7 8 9 10 11 120.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8 Measurements

Retrievals Total Aerosol STS NAT NAD Ice

(k

m-1)

Altitude 23 km

Wavelength (m)

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First one represents mostly NAD In the second, no preferable component

As to the comparison with thermodynamic predictions, the agreement could be acceptable since we have to be

careful to apply thermodynamic equilibriums to PSC.

Gas retrievals from all IR Channels (PSC state)

For the simultaneous gas and aerosol … Jacobean (onion peeling …)

15

20

25

30

35

40

1 2 3 4 5 6

O3

Alt

itu

de

(km

)

O3 (ppmV)

15

20

25

30

35

40

-0.001 0.000 0.001 0.002 0.003 0.004 0.005 0.006

NO2

NO2 (ppmV)

15

20

25

30

35

40

0.000 0.005 0.010 0.015

HNO3

HNO3 (ppmV)

15

20

25

30

35

40

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

N2O

N2O (ppmV)

Alt

itu

de

(km

)

15

20

25

30

35

40

0.0 0.5 1.0 1.5 2.0 2.5 3.0

CH4

CH4 (ppmV)

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10

H2O

H2O (ppmV)

15

20

25

30

35

40

0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008

CLONO2

CLONO2 (ppmV)

15

20

25

30

35

40

100 200 300 400 500 600 700 800

CO2

CO2 (ppmV)

Alt

itu

de

(km

)

15

20

25

30

35

40

0.0000 0.0005 0.0010 0.0015

OCS

OCS (ppmV)

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- Denotations

- All gases are

affected by PSC

- H2O

CONCLUSSIONS

Limb Workshop, Bremen, 14-16 April 2003

• Three methods have been developed for aerosol

retrievals using the ILAS / ILAS-II data

• The methods are shown to be very important

both for accurate gas retrievals and aerosol

characterization

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