APAN Conference, Fukuoka Jan 21 -23, 2003 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)
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. 05 N, 140. 12 E) 1996 -Nagasaki (32. 78 N, 129. 86 E) Mar. 2001 -Beijing, China (39. 9 N, 116. 3 E) Mar. 2001 -Sri Samrong, Thailand (17. 15 N, 99. 95 E) Oct. 2001 -Suwon, Korea (37. 14 N, 127. 04 E) 2002 -Amami-Ohshima (28. 44 N, 129. 70 E) 2002 -Miyakojima (24. 7 N, 125. 3 E) 2002 -Fukue (32. 63 N, 128. 83 E) Oct. 2002 -Hefei, China (31. 90 N, 117. 16 E) Oct. 2002 -Research Vessel “Mirai” 1999 --
Map. New
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 Tsukuba Nagasaki NIES Lidar Network for Asian Dust Observation
NIES Compact Mie Lidar
Beijing 2002 Lidar data
spherical aerosol dust Laser Scattering intensity Laser ice cloud water cloud P// Depolarization ratio d = P⊥/P// dust P⊥ P// spherical aerosols Depolarizati on ratio Target classification method
April 2001 Target classification 2 rain ice cloud water cl. dust aerosols unknown no obs. Target classification using the signal intensity and the depolarization ratio.
Histogram 2001
Histogram 2002
Tsukuba 2000 -2002
Comparison with Models The Chemical Forecast System (CFORS), (I. Uno) (A RAMS based regional model including chemistry)
Chemical Forecast System (CFORS)
Lidar signal intensity (depolarization) S 1 extinction coefficient assumption on external mixing distribution and characteristics of other aerosols dust extinction coefficient mass/extinction conversion factor dust density optical characteristics of dust Chemical Transport Model Which parameter shall we compare?
Ratio of dust is estimated by the following equations when we consider external mixture of dust and other spherical aerosols. R={(1 -d 2’)d-d 2’}/{(d 1’-d 2’)(1+d)} …………. . (1) d 1’＝d 1/(1+d 1） ……………(2) d 2’＝d 2/(1+d 2） ……………(3) where d 1 is depolarization ratio of dust, and d 2 is depolarization ratio of other aerosols. Empirically, d 1~0. 35, d 2~0. 05.
Beijing March 2001 dust air pollution aerosols dust Day (UTC) Distributions of dust and spherical (air-pollution) aerosols estimated from the signal intensity and depolarization ratio
Comparison with CFORS
Chemical Forecast System (CFORS)
Dust Number(Lidar)
Dust Number
Asian dust source regions
XZ 2001 Apr
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.
RIAM-NIES CFORS Dust event on November 12, 2002
Lidar. CFORS 1 Beijing Suwon
Lidar. CFORS 2 Fukue Tsukuba
Lidar. CFORS 3 Hefei Miyako-jima
Perspective Understanding dust phenomena Dust forecast Constructing dust monitoring network Ground based observation network Chemical transport model Satellite data (surface, dust)
ふろく
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