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