Applying an ensemble Kalman filter to the assimilation of AERONET observations in a global aerosol transport model
Applying an ensemble Kalman filter to the assimilation of AERONET observations in a global aerosol transport model
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DOI：
10.5194/acp-10-2561-2010
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发表时间：
2009-11
影响因子：
6.3
通讯作者：
N. Schutgens;T. Miyoshi;T. Takemura;T. Nakajima
中科院分区：
文献类型：
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作者：
N. Schutgens;T. Miyoshi;T. Takemura;T. Nakajima
抽象的。我们提出了一个全球性的气溶胶同化系统的基础上的Enhancement卡尔曼滤波器，我们相信，导致气溶胶领域的显着改善。集合允许现实的，空间和时间可变的模型协方差（不同于其他同化方案）。由于分析的变量是混合比（气溶胶传输模式的预测变量），因此不需要以前分析气溶胶光学厚度（AOT）的同化方案所需的额外假设。我们描述了这个同化系统的实施，特别是合奏的建设。这个集合应该代表我们对当前模型不确定性的估计。因此，我们构建的合奏周围随机修改的排放情况。用AERONET的AOT和埃指数（AE）观测对系统进行了测试。在规定观测误差时要特别小心。同化场（AOT和AE）通过独立的AERONET，SKYNET和MODIS Aqua观测进行验证。我们表明，在一般情况下，同化AOT观测导致全球AOT的建模改进，而同化AE只提高建模时，AOT是高的。
Abstract. We present a global aerosol assimilation system based on an Ensemble Kalman filter, which we believe leads to a significant improvement in aerosol fields. The ensemble allows realistic, spatially and temporally variable model covariances (unlike other assimilation schemes). As the analyzed variables are mixing ratios (prognostic variables of the aerosol transport model), there is no need for the extra assumptions required by previous assimilation schemes analyzing aerosol optical thickness (AOT). We describe the implementation of this assimilation system and in particular the construction of the ensemble. This ensemble should represent our estimate of current model uncertainties. Consequently, we construct the ensemble around randomly modified emission scenarios. The system is tested with AERONET observations of AOT and Angstrom exponent (AE). Particular care is taken in prescribing the observational errors. The assimilated fields (AOT and AE) are validated through independent AERONET, SKYNET and MODIS Aqua observations. We show that, in general, assimilation of AOT observations leads to improved modelling of global AOT, while assimilation of AE only improves modelling when the AOT is high.