Dust emission analysis of multi-year dust events by inverse model

Monday, 15 December 2014
Takashi Maki1, Taichu Y Tanaka2, Keiya Yumimoto1, Tsuyoshi Thomas Sekiyama1 and Masao Mikami1, (1)Meteorological Research Institute, Ibaraki, Japan, (2)Japan Meteorological Agency, Tokyo, Japan
We estimated the amount of emission of Aeolian dust aerosol from the Gobi desert area using the inverse technique, an Aeolian dust model (MASIGNAR), and surface observation data shared in the Triplet Environmental Ministers Meeting (TEMM) joint research project. We analyzed during the dust and sand storm (DSS) event in the May 2008, March 2009, October 2009 and December 2009 cases. We modified our inverse model system to set a constant dust emission flux at a grid-point where there is not enough dust emission flux from MASINGAR. We used the high-temporal-resolution (three hours) dust-emission estimating system using the Bayesian synthesis inversion, PM observation data and MASINGAR. Our research shows that we could modify MASINGAR’s Aeolian dust concentration to match the observation data with an increase or decrease in MASINGAR’s Aeolian dust flux. The estimated total dust emissions are from 1 to 9 Tg in the four cases. The estimated dust fluxes are increased in December 2009 case and decreased in other cases. This study suggests that there was a greater Aeolian dust flux than that estimated by MASINGAR in the middle part of the Gobi desert on winter case and smaller Aeolian dust flux on other seasons. This may come from the imperfectness of soil treatment of the model especially soil water and ice. We also find that new dust source area at northern eastern part of China in some cases. The results are sensitive to the observational network, the prior flux uncertainty and the observational error as previous study. In addition, the time resolution and data uncertainty of the observation data are also important for precise analysis. To obtain a precise estimation of the Aeolian dust-emission flux, it is critically important to share quality-controlled observation data among neighboring countries. We consider that inverse technique will become a powerful tool for estimating dust aerosol flux more precisely.