TY - JOUR
T1 - Forecasting of Asian dust storm that occurred on May 10–13, 2011, using an ensemble-based data assimilation system
AU - Yumimoto, Keiya
AU - Murakami, Hiroshi
AU - Tanaka, Taichu Y.
AU - Sekiyama, Tsuyoshi T.
AU - Ogi, Akinori
AU - Maki, Takashi
N1 - Funding Information:
The aerosol data assimilation system developed in this study is based on LETKF source codes (available at https://code.google.com/p/miyoshi ) for which we thank Dr. Takemasa Miyoshi and developers. This study was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI grants ( 24740326 , 25220101 , and 26701004 ), JSPS Core-to-Core Program (B. Asia–Africa Science Platforms), and Global Environment Research Fund (S-12) of the Ministry of Environment, Japan . This research paper is a contribution to the Joint Research on Dust and Sandstorm under TEMM-WG1.
Publisher Copyright:
© 2015 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences
PY - 2016/10/1
Y1 - 2016/10/1
N2 - An ensemble-based assimilation system that used the MASINGAR mk-2 (Model of Aerosol Species IN the Global AtmospheRe Mark 2) dust forecasting model and satellite-derived aerosol optical thickness (AOT) data, processed in the JAXA (Japan Aerospace Exploration Agency) Satellite Monitoring for Environmental Studies (JASMES) system with MODIS (Moderate Resolution Imaging Spectroradiometer) observations, was used to quantify the impact of assimilation on forecasts of a severe Asian dust storm during May 10–13, 2011. The modeled bidirectional reflectance function and observed vegetation index employed in JASMES enable AOT retrievals in areas of high surface reflectance, making JASMES effective for dust forecasting and early warning by enabling assimilations in dust storm source regions. Forecasts both with and without assimilation were validated using PM10 observations from China, Korea, and Japan in the TEMM WG1 dataset. Only the forecast with assimilation successfully captured the contrast between the core and tail of the dust storm by increasing the AOT around the core by 70–150% and decreasing it around the tail by 20–30% in the 18-h forecast. The forecast with assimilation improved the agreement with observed PM10 concentrations, but the effect was limited at downwind sites in Korea and Japan because of the lack of observational constraints for a mis-forecasted dust storm due to cloud.
AB - An ensemble-based assimilation system that used the MASINGAR mk-2 (Model of Aerosol Species IN the Global AtmospheRe Mark 2) dust forecasting model and satellite-derived aerosol optical thickness (AOT) data, processed in the JAXA (Japan Aerospace Exploration Agency) Satellite Monitoring for Environmental Studies (JASMES) system with MODIS (Moderate Resolution Imaging Spectroradiometer) observations, was used to quantify the impact of assimilation on forecasts of a severe Asian dust storm during May 10–13, 2011. The modeled bidirectional reflectance function and observed vegetation index employed in JASMES enable AOT retrievals in areas of high surface reflectance, making JASMES effective for dust forecasting and early warning by enabling assimilations in dust storm source regions. Forecasts both with and without assimilation were validated using PM10 observations from China, Korea, and Japan in the TEMM WG1 dataset. Only the forecast with assimilation successfully captured the contrast between the core and tail of the dust storm by increasing the AOT around the core by 70–150% and decreasing it around the tail by 20–30% in the 18-h forecast. The forecast with assimilation improved the agreement with observed PM10 concentrations, but the effect was limited at downwind sites in Korea and Japan because of the lack of observational constraints for a mis-forecasted dust storm due to cloud.
UR - http://www.scopus.com/inward/record.url?scp=84991020850&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991020850&partnerID=8YFLogxK
U2 - 10.1016/j.partic.2015.09.001
DO - 10.1016/j.partic.2015.09.001
M3 - Article
AN - SCOPUS:84991020850
SN - 1674-2001
VL - 28
SP - 121
EP - 130
JO - Particuology
JF - Particuology
ER -