AD-Net status

GALION WS, 20-23 Sep 2010, Geneva

Nobuo SUGIMOTO National Institute for Environmental Studies

nsugimot@nies.go.jp

Atsushi Shimizu, Ichiro Matsui, Tomoaki Nishizawa, Boyan Tatarov, Yukari Hara, Tamio Takamura, Soon-chang Yoon, Zifa Wang, Itsushi Uno, …

AD-Net stations

*NIES Lidar Network

****

****

****

**SKYNET

NIES lidar network (1)AD Net stations

Ryori

Gwangju

Taipei

Mineral dust

Forest fire

Industrial

Biomass burning

NIES lidar network (2)

Two-wavelength (1064nm, 532nm) Mie-scattering lidar with polarization channels at 532nm. (Raman receivers (607nm) are being added at several observation sites.)

Realtime data processing system

Extinction coefficient estimates of dust (left) and spherical aerosols (right) for primary locations (April 2009).

Dust event

(NIES Lidar Network)

Data distribution

(NIES Lidar Network)

Research programs and international cooperation

-Research on Asian dust in the Research Program of Ministry of the Environment of Japan

-Research on regional air pollution in the Research Program of Ministry of the Environment of Japan

-Research on the effects of aerosols on plants and human health with Ministry of Education Science and Technology of Japan

International cooperation-Working group on Dust and Sand Storm under Japan-China-Korea Tripartite Environment Ministers Meeting (TEMM) (Data sharing and model inter-comparison)

-WMO Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) (Realtime data sharing and model intercomparison in Asian node)

-Plan to cooperate with the Seven Southeast Asian Studies (7SEAS)

-GALION

(NIES Lidar Network)

NIES lidar network (3)

4D-Var data assimilation system for Asian dust

4DVAR data assimilation of Asian dust using the NIES lidar network data (Yumimoto et al. 2007, 2008)

Comparison of the assimilated dust transport model with CALIPSO data (Hara et al. 2009)Please see the publication list athttp://www-lidar.nies.go.jp/~cml/English/PublicationsE.html

March 25- April 3, 2007

May 21-30, 2007

without assimilation

with assimilation

dust emission factor

2.2 Monthly (non-dust) AOT variation at NIES lidar sites2006 2007 2008 Summertime peak

Autumn peak

Summertime trough (clean)

Guangzhou

Beijing

Okinawa/Hedo

・ Space and ground-based lidar AOT values show relatively good agreement.・ CMAQ shows similar seasonal variation.

(7/15)

(Hara et al.)

2.3 Seasonal variation of vertical profiles

・ The seasonal variation in the aerosol scale height at Beijing is largest (about 1 km) among these sites which is correlated to the large seasonal variation of the mixing layer depth .

・ We can classify typical seasonal variations of spherical AOT at the three lidar sites into two types: the ‘summertime peak’ type and the ‘summertime trough’ type.

Beijing

Guangzhou Okinawa/HedoSummertime trough type

Summertime peak type

(8/15)AOT(ZH)=AOT(6km)(1-e-1) 0.63 AOT(6km)ZH=aerosol scale height

Time

Time Time

富山の例

Near-surface (120m-1km) dust and spherical-aerosol extinction coefficient used in

the epidemiological study.

Desert-dust is associated with increased risk of asthma

hospitalization in children

Figure 2 Meteorologically adjusted Odds Ratios (ORs) for the relations between asthma hospitalizations and heavy dust exposure (daily average level above 0.1mg/m3) with various cumulative lags

Figure * Adjusted OR for the relations between asthma hospitalizations and heavy sphere particle exposure (daily average level above 0.1mg/m3) for various cumulative lag periods

Figure ** Adjusted OR for the relations between asthma hospitalizations and heavy SPM (suspended particulate matter) exposure (daily average level above 0.1mg/m3) for various cumulative lag periods

K. Kanatani, et. al. American Journal of Respiratory and Critical Care Medicine, 2010.

cutoff

Figure 3 Association between meteorologically adjusted OR and cut-off values for dust particle level.

Mass(SPM)/extinction ~ 1000 (g/m3)/(km-1)

Mass/extinction conversion factor (MEF)PM10/(Lidar extinction) and assimilated CFORS model was compared for mineral dust.

MEF for PM10 shows temporal (and spatial variation)Variation in MEF for PM2.5 is much smaller. PM2.5 is less dependent on particle size distribution. We can better quantify “dust PM2.5” from the dust extinction coefficient.

CFORS has 12 size bins for dust

(Sugimoto et al., 2010)

Mongolian forest fire in June 2007

(Sugimoto et al., SOLA 2010)

S1(532nm)= 65±5sr, PDR= 0.14±0.03, BAE(532,1064)=1.1±0.2

Moscow forest fire smoke

NRL NAAPS

Russian forest fire smoke in Aug 2010

Ongoing projects

1) Climatology and case studies using lidar network data (and CALIPSO)

2) Real time data assimilation for dust forecasting.

3) Assimilation of regional chemical transport models including spherical aerosols

4) Assimilation of global aerosol climate models including the lidar network data

-Meteorological Research Institute (T. Sekiyama) -Kyushu University (T. Takemura, K. Yumimoto) -University of Tokyo (T. Nakajima, N. Schutgens) 4) Development of a multi-wavelength high-spectral-resolution lidar

(2+3+2) and a data analysis method

2+3+2 HSRL system

532nm HSRL + 1064nm receiver

Iodine filter

APD(1064nm)

PMT(532nm)

355nm HSRL receiver

EtalonPMT(355nm)

Laser wavelength tuning system

LaserPinhole

PC ADC

Photodiode

AOM

AOM

I2cell(L=10cm)

NDFilter

Wavelength shift [pm]

Tran

smitt

ance

Pinhole

AOM

I2 cell

Photodiode

Measured Iodine absorption spectrumλo+δλ

λo−δλ

Ratio of P(λo+δλ) to P(λo−δλ)Center wavelength of Iodine absorption line used in this study （ line number:1111 ）

Preliminary measurement17LT Aug. 20 ~ 9LT Aug. 21 at Tsukuba (140.12E, 36.05N),

JapanMeasured signals

P532,paericle+molecule

P532,molecule

P1064, particle+molecule

δ532

Derived particle opt. prop.

Backscatter [/km/sr]

Extinction [/km]

Extinction / Backscatter [sr]

Particle depolarization ratio

Cloud

Etalon wavelength tuning system

Etalon

1m(Focused light dia. ＝

4mm)

PM

T355,M

ie,ch1

PMT355,Mie,ch2Pinhole mirror(Pinhole dia. = 3mm)

Lens

Finness = 10FSR = 5GHz

Simulated interference fringes

P=+1.6hPa

P=-1.6hPaP=-3.2hPa

P=+3.2hPa

Measured signalsSimulated signals

Maximum transmittance for Mie scatter

NIES lidar network (1)

NIES Lidar Network

7SEAS Network (J. Campbell et al.)

ChinaIndia