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AEROSOL CLASSIFICATION RETRIEVAL ALGORITHMS FOR EARTHCARE/ATLID, CALIPSO/CALIOP, AND
GROUND-BASED LIDARS
Sugimoto, N., T. Nishizawa, I. Matsui, National Institute for Environmental Studies (NIES), Tsukuba, Japan
H. OkamotoKyushu Univ., Fukuoka, Japan
IGARSS 2011, 29/Jul/2011
FR2T03
NIES Lidar Network
20 observation sites in East-Asia using 2+1 Mie lidar 532nm attenuated Backscatter (532)
532nm total depolarization (532) 1064nm attenuated backscatter (1064)
Measured data
APD(1064nm)
PMTs(532nm)
2+1 Mie lidar
China
Japan
Thai
Mongol
Korea
NIES Lidar network
Lidar at “Hedo” site
The lidars measure aerosols (& clouds) 24-hour-automatically and we provide 2+1 data in semi-real-time (http://www-lidar.nies.go.jp/)
NIES Lidar Network
ObservationCompact 2 (532, 1064nm) + 1 (532nm) Mie lidar
with automatically measurement capability 20 sites ground based network observation in East Asia (2001~) Ship-borne measurements (1999~, vessel “MIRAI” (JAMSTEC))
[Sugimoto et al., 2001; 2005]Data analysis Classify aerosol components and Retrieve their extinctions at each layer
(assuming external mixture of each aerosol component) 1(532)+1 data Dust (nonSpherical) + non-Dust (Spherical)
[Sugimoto et al., 2003; Shimizu et al., 2004]
2 data Air-pollution aerosol*(Small) + Sea-salt or Dust(Large)[Nishizawa et al., 2007; 2008]
2+1 data Air-pollution aerosol* (Spherical / Small) + Sea-salt (Spherical / Large) +Dust (nonSpherical / Large) [Nishizawa et al., 2010]
Polarization
Spectral
Polarization + Spectral
*Air-pollution aerosol is defined as mixture of Sulfate, Nitrate, Organic carbon, and Black carbon
2+1 algorithm
Spheroidal for dust (Spherical for the other components)
AP SS DS
rm 0.13 3.0 2.0
S 55 20 48
0 0 0.3
AssumptionsLog-normal size distributionMode radius, standard deviation, refractive indexes
3 components in each layerAP : Air-pollutionSS : Sea-saltDS : Dust
532, ||
1064
532,
SSAP
DS
rm: Mode radiusS : Lidar ratio (Extinction-to-Backscatter ratio)δ : Particle depolarization ratio
Application to shipborne lidar data I
Pacific Ocean near Japan Observed data(2+1 Mie lidar)
Tohoku Univ. HP, http://caos-a.geophys.tohoku.ac.jp
14 days
6 km
0 km532
1064
6 km
0 km
532
6 km
0 km
MIRAI/JAMSTEC
Retrieved aerosol component dataAir-pollution aerosols
Dust
Sea-salt
AOT (532) Angstrom
Agreement within 5%
Total
Application to shipborne lidar data II
Tropical Pacific Ocean
Mirai CruisesMR01K05: 9.21 ~ 12.17, 2001MR04K07: 11.18 ~ 12.9, 2004MR04K08: 12.16 ~ 2.17, 2005MR06K05: 10.16 ~ 11.25, 2006
7-month data in total
TotalAir-Pollution
SS DS12-hour average
Horizontal distribution (Optical thickness)
The total optical thicknesses were larger from the Japan to the New Guinea and in the western region off Sumatra Island than in the other regions.
AP was the major contributor to the total optical thickness of aerosols.
Comparison with a global aerosol transport model “SPRINTARS” [Nishizawa et al. JGR 2008]
*SPRINTARS is a global, three-dimensional aerosol transport model [Takemura et al. 2005].
The simulation data by the SPRINTARS was provided by Takemura of Kyusyu Univ.
Mean values(Obs.)=0.0006 km-1sr -1
(Sim.)=0.0003 km-1sr -1
Mean values(Obs.)=0.0027 km-1sr -1
(Sim.)=0.0017 km-1sr -1
532 1064
532
SPRINTARS
Lidar
Mean values(Obs.)=0.044 km-1
(Sim.)=0.009 km-1
Mean values(Obs.)=0.005 km-1
(Sim.)=0.014 km-1
AP SS
AP
SPRINTARS
Lidar
Application to satellite-borne 2+1 lidar[CALIOP/NASA 2006~]
Saharan Dust transport to the Atlantic Ocean
2006.8/1, 2:36UTC
Aerosol Mask Scheme●Remove cloud area CloudSat + CALIOP [Hagihara et al. 2009]●Remove molecule scat. area CALIOP (β1064) * β1064 was re-calibrated by using water-cloud signals
β1064
β532
δ532
Airpollution
Sea-salt
Dust
Alti
tude
[km
]A
ltitu
de [
km]
Latitude [deg]
Cited from NASA/CALIOP website
532
Observed dataApril 8 2005, 0~10 UTC
532
S532= 532 / 532
1064
Observation Site NIES, TsukubaHSRL Extinction (532nm ) Backscatter (532nm )Mie lidar Backscatter (1064nm ) Depolarization (532nm)
HSRLMie lidar
Mie-lidar and High-Spectral-Resolution-Lidar (HSRL) measurements (1α+2β+1δ)
Aerosol classification algorithmsusing 1α+2β+1δ data
Classify aerosol components and Retrieve their extinctions at each layer(assuming external mixture of each aerosol component)
1α+2 data SF-NT-OC (Weak / Small) + BC (Strong / Small) +Dust (Weak / Large) [Nishizawa et al., 2008]
1α+1+1 data SF-NT-OC (Weak / Spherical) + BC (Strong / Spherical) +Dust (Weak / Non-spherical)
*Air-pollution aerosol is defined as mixture of Sulfate (SF), Nitrate (NT), Organic carbon (OC), and Black carbon (BC)
Light absorption+ Spectral
Light absorption+ Polarization
1 + 1 + 1 algorithm
Dust + BC + SF-NT-OC
SF-NT-OC
BC DS
rm 0.13 0.05 2.0
S 55 101 48
0 0 0.3α532
532, ||
532,
SF-NT-OC
BC
DS
Spheroidal for dust (Spherical for the other components)
AssumptionsLog-normal size distributionMode radius, standard deviation, refractive indexes
rm: Mode radiusS : Lidar ratio (Extinction-to-Backscatter ratio)δ : Particle depolarization ratio
Estimates
SF-NT-OC
Dust
BC
Application to ground-based Mie/HSRL data(NIES, Tsukuba, Japan)
Sulfate
Dust
BC+OC
Observation site
Sulfate originated from Coastal area of ChinaDust originated from Gobi desertBC+OC originated from Coastal area of China and Indochina peninsula
SPRINTARS
Provided by Dr. Takemura (Kyusyu Univ.)
ATLID / EarthCARE (2015 ~)
355 nm High Spectral Resolution lidar (HSRL)
3 channels: 1α+1+1 Extinction coefficient () Backscattering coefficient () Depolarization ratio ()
Summary
We developed several aerosol classification and retrieval algorithms.=> The algorithms can be used to understand aerosol component distributions
in regional and global scales by applying to the network lidar data and the satellite-borne lidar data.
We are going on developing (or improving) aerosol classification and retrieval algorithms using more channels. NIES 2+1 Mie lidar + Raman (or HSRL) 1α+2+1 data SF-NT-OC (Weak / Small / Spherical) +
BC (Strong / Small / Spherical) +Dust (Weak / Large / Non-spherical) +Sea-salt (Weak / Large / Spherical)
NIES 2α+3+2 HSRL (Under development : Nishizawa et al. FR2T07) 2α+3+2 data SF-NT-OC (Weak / Small / Spherical) +
BC (Strong / Small / Spherical) +Dust (Weak / Large / Non-spherical) +Sea-salt (Weak / Large / Spherical) +Size information for SF-NT-OC, Dust, Sea-salt
Light absorption+ Spectral
+ Polarization
Light absorption+ Spectral
+ Polarization