Observations and Model Analysis of Recent Asian Dust Events

Nobuo Sugimoto (National Institute for Environmental Studies)

Itsushi Uno (Research Institute for Applied Mechanics, Kyushu University) Atsushi Shimizu, Ichiro Matsui (National Institute for Environmental Studies)

Kimio Arao (Nagasaki University) Hao Quan, Yan Cheng (CJFCEP, China)

Jun Zhou (AIOFM, China)C-H Lee (Kyung Hee University, Korea)

APAN Conference, Fukuoka Jan 21-23, 2003

Heavy dust event in Beijing on March

20, 2002.

Dust Project in the Global Environment Research Program of the Ministry of the Environment

(1) Observation of distribution and movement of Asian dust using lidars

(2) Chemical analysis of Asian dust

(3) Modeling study

NIES lidar observation network

Tsukuba (36.05N, 140.12E) 1996--Nagasaki (32.78N, 129.86E) Mar. 2001--Beijing, China (39.9N, 116.3E) Mar. 2001--Sri Samrong, Thailand (17.15N, 99.95E) Oct. 2001-- Suwon, Korea (37.14N, 127.04E) 2002--Amami-Ohshima (28.44N, 129.70E) 2002--Miyakojima (24.7N, 125.3E) 2002--Fukue (32.63N, 128.83E) Oct. 2002--Hefei, China (31.90N, 117.16E) Oct. 2002--

Research Vessel “Mirai” 1999--

MapNew

Purpose of the lidar network observations

- Climatology of aerosols and clouds

- To understand aerosol phenomena including effects of Asian dust and anthropogenic aerosols on the environment and climate

- To validate chemical transport models

- Monitoring of Asian dust and anthropogenic aerosols in the regional and global scales

NIES Compact Mie Lidar

Beijing

NagasakiTsukuba

NIES Lidar Network for Asian Dust Observation

NIES Compact Mie Lidar

Lidar dataBeijing 2002

Target classification method

Scattering

intensity

Depolarization ratio

water cloud

ice cloud

spherical aerosols

dust

LaserLaser

P//

P⊥

P//

Depolarization ratio = P⊥/P//

dustspherical aerosol

Target classification 2

dust

rain

ice cloud

water cl.

aerosols

unknown

no obs.

April 2001

Target classification using the signal intensity and the depolarization ratio.

Histogram 2001

Histogram 2002

Tsukuba 2000-2002

The Chemical Forecast System (CFORS), (I. Uno)(A RAMS based regional model including chemistry)

Comparison with Models

Chemical Forecast System (CFORS)

Lidar

Chemical Transport Model

signal intensity (depolarization)

Which parameter shall we compare?

dust extinction coefficient

extinction coefficient

dust density

S1

assumption on external mixing

mass/extinctionconversion factor

distribution and characteristics of other aerosols

optical characteristics of dust

Ratio of dust is estimated by the following equations when we consider external mixture of dust and other spherical aerosols.

　 R={(1-2’)-2’}/{(1’-2’)(1+)} …………………… ..(1) 1’ ＝ 1/(1+1 ） ……………………… (2) 2’ ＝ 2/(1+2 ） ……………………… (3)

where 1 is depolarization ratio of dust, and 2 is depolarization ratio of other aerosols. Empirically, 1~0.35, 2~0.05.

dust

air pollution aerosols

dust

Distributions of dust and spherical (air-pollution) aerosols estimated from the signal intensity and depolarization ratio

Beijing March 2001

Day (UTC)

Comparison with CFORS

Chemical Forecast System (CFORS)

Dust Number(Lidar)

Dust Number

Asian dust source regions

XZ2001Apr

CFORS 2001, 2002

Summary

We conducted continuous observations in Beijing, Nagasaki, and Tsukuba with automated polarization lidars since March 2001.

A statistical analysis showed that the frequency of dust events in 2002 and 2001 was not very different in Beijing, but the frequency was much higher in 2002 in Tsukuba.

We studied the dust source regions and transport paths using the regional chemical transport model CFORS.

The results showed that most major dust events originated in Inner Mongolia and/or Mongolia. The dust was transported rapidly with the strong westerly of the storm, and the main part was transported northeast near the coast of China.

In 2002, the location of dust streams were shifted slightly to the east, and this caused heavy dust events in Korea and northern Japan. This is probably related with the climate change.

Dust event on November 12, 2002

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RIAM-NIES CFORS

Lidar-CFORS1

SuwonBeijing

Lidar-CFORS2

Fukue Tsukuba

Lidar-CFORS3

Miyako-jimaHefei

Perspective

Understanding dust phenomena

Constructing dust monitoring network

Dust forecast

Ground based observation network

Satellite data (surface, dust)

Chemical transport model

ふろく

Thank You