Adjoint inverse modeling of dust emission and transport over East Asia
Adjoint inverse modeling of dust emission and transport over East Asia
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DOI：
10.1029/2006gl028551
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发表时间：
2007-04
影响因子：
5.2
通讯作者：
K. Yumimoto;I. Uno;N. Sugimoto;A. Shimizu;Shinsuke Satake
中科院分区：
文献类型：
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作者：
K. Yumimoto;I. Uno;N. Sugimoto;A. Shimizu;Shinsuke Satake
发展了一个区域沙尘模式的四维变分(4DVAR)资料同化系统。本报告介绍了利用NIES激光雷达观测资料，针对2005年4月30日的极端沙尘现象，首次对东亚上空的亚洲沙尘排放进行伴随反演的结果。优化的尘埃排放减轻了对尘埃浓度的低估，并使升高的尘埃层的结构(起始时间和消光系数强度)与激光雷达观测结果更好地吻合。我们通过数据同化得到计算的沙尘排放量增加了31%(3.2Tg)，特别是在蒙古地区。同化结果与TOMS AI分布相吻合，表明4DVAR方法在统一观测和数值模拟方面具有很强的能力。该方法提供了更好的估计能力。
A four‐dimensional variational (4DVAR) data assimilation system was developed for a regional dust model. This report presents results of the first adjoint inversion of Asian dust emissions over East Asia using NIES LIDAR observations, targeting the extreme dust phenomenon on 30 April 2005. Optimized dust emissions mitigated underestimation of dust concentrations and brought the structure of the elevated dust layer (both onset timing and extinction coefficient intensity) into better agreement with LIDAR observations. We obtained a 31% (3.2 Tg) increase of calculated dust emissions through data assimilation, especially over the Mongolian region. The assimilated results agree with the TOMS AI distribution and indicate that the 4DVAR method is very powerful for unification of observation and numerical modeling. The method provides better estimation capability.