Observations and Model Analysis of Recent Asian Dust Events

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Observations and Model Analysis of Recent Asian
Dust Events
APAN Conference, Fukuoka Jan 21-23, 2003

• 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)

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Heavy dust event in Beijing on March 20, 2002.
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Dust Project in the Global Environment Research
Program of the Ministry of the Environment

• Observation of distribution and movement of Asian
  dust using lidars
• (2) Chemical analysis of Asian dust
• (3) Modeling study

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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--
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MapNew
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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

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NIES Compact Mie Lidar
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NIES Lidar Network for Asian Dust Observation
Beijing
Nagasaki
Tsukuba
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NIES Compact Mie Lidar
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Lidar data
Beijing 2002
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Target classification method
spherical aerosol
dust
Scattering intensity
Laser
ice cloud
Laser
water cloud
dust
P?
P//
P//
Depolarization ratio
spherical aerosols
Depolarization ratio d P?/P//
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Target classification 2
April 2001
Target classification using the signal intensity
and the depolarization ratio.
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Histogram 2001
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Histogram 2002
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Tsukuba 2000-2002
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The Chemical Forecast System (CFORS), (I. Uno)(A
RAMS based regional model including chemistry)
Comparison with Models
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Chemical Forecast System (CFORS)
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Which parameter shall we compare?
Lidar
signal intensity (depolarization)
S1
extinction coefficient
distribution and characteristics of other aerosols
assumption on external mixing
dust extinction coefficient
mass/extinction conversion factor
optical characteristics of dust
dust density
Chemical Transport Model
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Ratio of dust is estimated by the following
equations when we consider external mixture of
dust and other spherical aerosols.
R(1-d2)d-d2/(d1-d2)(1d)
..(1) d1d1/(1d1)
(2) d2d2/(1d2)
(3)where d1 is depolarization ratio of
dust, and d2 is depolarization ratio of other
aerosols. Empirically, d10.35, d20.05.
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Distributions of dust and spherical
(air-pollution) aerosols estimated from the
signal intensity and depolarization ratio
Beijing March 2001
Day (UTC)
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Comparison with CFORS
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Chemical Forecast System (CFORS)
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Dust Number(Lidar)
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Dust Number
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Asian dust source regions
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XZ2001Apr
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CFORS 2001, 2002
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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.
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RIAM-NIES CFORS
Dust event on November 12, 2002
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Lidar-CFORS1
Suwon
Beijing
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Lidar-CFORS2
Fukue
Tsukuba
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Lidar-CFORS3
Hefei
Miyako-jima
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Perspective
Understanding dust phenomena
Dust forecast
Constructing dust monitoring network
Ground based observation network
Chemical transport model
Satellite data (surface, dust)
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???
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Thank You