Aerosol retrieval based oncombination use of POLDER andGLI data

Itaru Sano
Kinki University

Contents• Background• Algorithm description for aerosol retrieval• Retrieved results derived from POLDER• (Preliminary) results of combination use ofPOLDER and GLI• Air quality estimation based on AOT

BackgroundAerosols : One of the most variable components of theatmosphere# for radiative transfer models ( Atmos. Corr. )# for GCM models# for air quality indexetc.

SGLI ≈ POLDER + GLI• Stokes parameter
I, Q, U : (0 – 60 –120 position angles)
at 0.67 and 0.86 µm channels (POLDER)• Near UV and violet data
at 0.38 and 0.40 (0.41) µm channels ( GLI )• Large tilting angle± 45 degrees about nadir in the along-track
direction (POLDER)• Fine resolution
1 km ( GLI )cf. 6×7 km (POLDER)

Aerosol information from SGLIMinimum
success

Aerosol optical thickness (AOT; τ)
increased accuracy over land and over water
Size information ( Spectral AOT )Angstrom exponent (α),(fine and coarse mode optical thickness)
Aerosol type
Single Scattering Albedo (ω),
Refractive Index (m),Fullsuccess

ShapeAlgorithm for aerosol retrieval
1. Four-channel algorithm over ocean
2. Two-channel algorithm over ocean and land
3. Two-channel algorithm over land

Retrieval algorithm for aerosols (over ocean)

1. Four-channel algorithm(by Higurashi and Nakajima):– Retrieval of τ, α, and absorptivity in blue
over ocean:– 0.412, 0. 443, 0.670, and 0.865 µm(Blue, VIS, NIR)
– Species; soil dust, carbonaceous, sulfate, and sea salt

Retrieval algorithm for aerosols (ocean/land)

2. Two-channel method (by R. Hoeller et al. );– Retrieval of τ and ω (land and ocean)– 0.380 and 0.412 µm (UV-absorbing and Blue);
Species； soot and dust (absorbing) andsulfate (non-absorbing)

Retrieval algorithm for aerosols (over land)

3. Two-channel Polarization method- Retrieval of τ, and α, on a global scale- 0.678 and 0.865 µm(Polarization and Directionality)
4. Two-channel Polarization method withUV-V channel method

Aerosol models• Spherical shape• Size distribution (Bi-modal log-normal)– Modal radius of fine and coarse are chosen fromaerosol climatology based on AERONET (Dubovik,2002).

– Fine mode (rg_f, cg_f) = ( 0.135, 0.430 µm )• Urban, Industrial and Biomass burning aerosols– (GSFC, Paris, Mexico, and Maldives)– Coarse mode (rg_c, cg_c) = (2.365, 0.630 µm )• Dust and Oceanic aerosols– (Bahrain, Solar-Villeage, Cape Verde, and Lanai Island)• Complex Refractive Index (n, k)– 1.40-0.000i, 1.45-0.0005i, 1.50-0.001i, 1.55-0.010i

Polarization (0.87 µm)

Polarization (0.67 µm)

Look up table for aerosol retrieval over land

Polarization (0.67 µm)

Polarization (0.44 µm)

Annual change of AOT (1997, 2003)

Annual change of AOT (difference 2003−1997)
April
0.0

0.1

May
0.2

>0.3JuneAerosols over East Asia : November, 1996

Accuracy of AOT retrieval

Aerosol optical thickness (τ)
RMS error ~ 0.11 (POLDER-1)~ 0.17 (POLDER-2)

Aerosol retrieval based on POLDER and GLIGCOM / SGLI

R.T. calc.
SpectralAOTA system flow of aerosol retrieval based on combination use of POLDER and GLI data.

Detection of biomass burning plume by GLI
Composite (POLDER)GLI Radiance ratio ( 0.40 µm / 0.38 µm)

NDVI images
after and before atmospheric correction

Air quality study by PM2.5 and AOT
Kobe

Higashi-Osaka
Kobe
Osaka

Kyoto
Osaka

Kyoto

Nara

Mt.IkomaNara（Osaka site）
AERONET, SKYNET⇒ PMc,

PM2.5,OBC
Japan

Filter sample of SPM613D

PM1 (2006/12-PM2.5 & coarse Measurements

Regression analysis between PM and sun photometry

NaraKobe0.092 τ a (0.87) - 0.021 for dust events,
PM 2.5 =  0.294 τ a (0.87) - 0.014 for other days.

Japan

PM2.5 maps in 1997, 2003
April

MayJune

100
1997

50

2003

0[µg/m3]

An enlarged map of PM2.5 over Japan
April, 2003
100

50

0
[µg/m3]

Summary• Aerosol properties, e.g., spectral AOT and aerosol
type (absorbing aerosols ) are derived fromcombination use of POLDER and GLI data.
These data are useful to correct the atmosphericeffect.
• Air quality (PM2.5) is evaluated from the derived
relationship between AOT and SPM.