3.1.4 ATSK5

Algorithm for Aerosol Optical Property Retrieval
A. Algorithm Outline(1)

Algorithm Code: ATSK5(2)

Product Code: AROP, ARAE

(3)

PI names: G60 Teruyuki Nakajima(4)

Overview of algorithm（Status: standard level）
This algorithm has the following objectives:
1.

To retrieve aerosol optical thickness at 0.5 micron and any user defined wavelength over oceansurface.

2.

To retrieve aerosol Angstrom exponent which is an index of aerosol size distribution overocean surface.

B. Theoretical Description(1) Methodology and Logic flow
This satellite remote sensing algorithm retrieves aerosol optical thickness at 0.500nm and user defined
wavelength, and Angstrom exponent from two channel radiant data, that is, visible and near-IR, satellite
data. Satellite-received radiance is synthesized with four look-up tables (LUTs). For retreivals, ancillarydata are needed, which include wind velocity at 10 meter height, ozone and water vapor amount tocorrect radiance for surface reflectance, ozone and water vapor absorption.

Select 1 suitableradiance data from25 dataSegment DataR1, R2, 0, R=0.678 R=0.865(25 data per 1 pixel)Water Vaporand ozoneamount andsullll

q q fw(m )c n Rmol,mTW

t aFigure 1. Flow Chart of the Retrieval Algorithm
GLI Algorithm Description

3.1.4-1

(2)Physical and Mathematical aspects of the algorithm
By theoretical analysis and numerical simulation, the satellite received apparent reflectance iscomposed of the following six items:

R( m , m 0 , f ) = TO3 TW ( RS + Rmol ,m + Raer ,m + Rg )(1)

In which each item can be expressed in the following way:Single scattering componentpwP( Q) 1 - e -t (1 / m +1 / m0 )RS =mm 0 F0 1 / m + 1 / m 0(2)Multiple scattering component2(m)Rmol , m = Â Rmol, m cos mf

(3)

m =0

Raer ,m =41{ Â c nt an + c 5 1 - e -t a (1/ m +1/ m0 )mm0 n =1[]}(4)

Surface reflectance component

Rg = rs ( m , m 0 , f ,n )e -t (1 / m +1 / m0 )(5)Correction of ozone absorption-t

TO3 = e O3

(1 / m +1 / m0 )(6)

In this algorithm 4 LUTs are constructed to calculate the Phase fuction P, single scattering albedo w,(m)and coefficient of aerosol multiple scattering c n , and coefficient of Rayleigh multiple scattering Rmol ,m ,and Correction factor of water vapor absorption TW . For accurately calculating radiance in the visible andnear infrared channels of GLI, the gaseous absorption by ozone and water vapor has to be taken into
account, TO is calculated by use of Eq. (6) and TW is interpolated from LUTs.
3A suitable assumption of the aerosol optical model is another important point for realizing a goodaerosol retrieval algorithm, here, we introduce a bimodal log-normal volume spectrum for modeling theaerosol size distribution:2È (lnr - lnrm ,n )2 ˘
dV= Â C n exp Í ˙dlnr n =1
2s n2
ÎÍ
˚˙(7)

where subscript n indicates the mode number, rm1 = 0.17 mm, rm 2 = 3.44 mm, s1 =1.96, and s2 =2.37
are adopted for the parameters of the modeled volume spectrum, and the complex refractive index of m=GLI Algorithm Description

3.1.4-2

1.5-0.005i. is used in this retrieving scheme.
As shown in Figure 1, the theoretical reflectance can be reconstructed quickly and accurately by useof the LUTs, and these value are applied to compare with the satellite measured reflectance. The basis ofretrieval is the characteristic relationship between apparent reflectance of GLI channe-13 and channel-19
for various values of the aerosol optical thickness at 0.5 mm, ta and the peak ratio g of the size distribution
as shown in Fig. 2, which is caused by the difference in the extinction efficiency in each channel. The
figure suggests that the aerosol optical parameters, i.e., ta and g, are retrieved by comparing measured
reflectances and theoretical reflectances which are reconstructed from LUTs. It has be found that thepeak ratio g , which represents the contribution of large particles, can be used to calculate the Angstrom
exponent a, which is defined as,

a=-dlnt a ,ldlnl(8)Retrieving the set of (ta, a) is more essential since the satellite-received radiance is not sensitive to thedetailed structure of the size distribution, but depends nearly uniquely on (ta, a).

Channel-1 and -2 for various aerosol loading conditions.
Fig. 2 The relationship between apparent reflectances of NOAA/AVHRR
C. Practical Considerations(1)

Programming, Procedural, Running Considerations
Program Requirements:

The following table shows information about the expected software

generated from this algorithm.

GLI Algorithm Description

3.1.4-3

Program Memory

177KB

Program Size

2564 lines

Required Channels

Channel-13 (678nm) and Channel-19 (865nm)

Necessary/Ancillary DataColumn Water vapor amount and Ozone amount andwind

velocity of 10 meter height.
Expected Disk Volume78548 bytes

Special Programs or

22 subroutines

Subroutines
Use of existing data sets for developing algorithms(2)

Calibration and validation(3)

Quality Control and Diagnostic Information(4)

Exception Handling(5)

Constraints, Limitations, Assumptions(6)

Publications and Papers

D. References

Nakajima, T., and A. Higurashi, 1998: A use of two-channel radiances
for an aerosol characterization from space. Geophys. Res. Lett.,
25(20),3815-3818.
Nakajima, T., and A. Higurashi, 1997: AVHRR remote sensing of aerosol
optical properties in the Persian Gulf region, the Summer of 1991.
J. Geophys. Res., 102(D14), 16,935-16,946.
Higurashi, A., and T. Nakajima, 1998: Development of a Two Channel
Aerosol Retrieval Algorithm on Global Scale Using NOAA / AVHRR.
J. Atmos. Sci., 56, 924-941.
Higurashi, A., 1998: A study of aerosol properties on global scaleusing satellite remote sensning. University of Tokyo, Ph. D.
thesis.
Higurashi, A., and T. Nakajima, 1998: A Global characterization ofaerosols with a two channel remote sensing. Submitting to
J. Clim.

GLI Algorithm Description

3.1.4-4