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Investigating the assimilation of CALIPSO global aerosol vertical observations using a four-dimensional ensemble Kalman filter

机译:使用四维集合Kalman滤波器调查Calipso全球气溶胶垂直观测的同化

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Aerosol vertical information is critical to quantify the influences of aerosol on the climate and environment; however, large uncertainties still persist in model simulations. In this study, the vertical aerosol extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are assimilated to optimize the hourly aerosol fields of the Non-hydrostatic ICosahedral Atmospheric Model (NICAM) online coupled with the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) using a four-dimensional local ensemble transform Kalman filter (4-D LETKF). A parallel assimilation experiment using bias-corrected aerosol optical thicknesses (AOTs) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is conducted to investigate the effects of assimilating the observations (and whether to include vertical information) on the model performances. Additionally, an experiment simultaneously assimilating both CALIOP and MODIS observations is conducted. The assimilation experiments are successfully performed for 1?month, making it possible to evaluate the results in a statistical sense. The hourly analyses are validated via both the CALIOP-observed aerosol vertical extinction coefficients and the AOT observations from MODIS and the AErosol RObotic NETwork (AERONET). Our results reveal that both the CALIOP and MODIS assimilations can improve the model simulations. The CALIOP assimilation is superior to the MODIS assimilation in modifying the incorrect aerosol vertical distributions and reproducing the real magnitudes and variations, and the joint CALIOP and MODIS assimilation can further improve the simulated aerosol vertical distribution. However, the MODIS assimilation can better reproduce the AOT distributions than the CALIOP assimilation, and the inclusion of the CALIOP observations has an insignificant impact on the AOT analysis. This is probably due to the nadir-viewing CALIOP having much sparser coverage than MODIS. The assimilation efficiencies of CALIOP decrease with increasing distances of the overpass time, indicating that more aerosol vertical observation platforms are required to fill the sensor-specific observation gaps and hence improve the aerosol vertical data assimilation.
机译:气溶胶垂直信息对于量化气溶胶对气候和环境的影响至关重要;然而,大量的不确定性仍然存在于模型模拟中。在这项研究中,来自云 - 气溶胶激光乐的垂直气溶胶消光系数(Caliop)船上云 - 气溶胶激光乐队和红外探测卫星观察(Calipso)被同化化,以优化非静液压二核型大气的每小时气溶胶田在线(NICAM)在线耦合使用四维局部集合变换卡尔曼滤波器(4-D Letkf)的气溶胶物种(Sprintars)的光谱辐射传输模型。进行了使用来自中等分辨率成像光谱仪(MODIS)的偏置校正气溶胶光学厚度(AOTs)的并行同化实验,以研究同化在模型表演上的观察(以及是否包括垂直信息)的影响。另外,进行了同时同时吸收卡索和MODIS观察的实验。同化实验成功进行1?月,使得可以评估统计学意义的结果。每小时分析通过调用型气溶胶垂直消光系数和来自MODIS和气溶胶机器人网络(AEROONET)的AOT观测来验证。我们的结果表明,卡利普和MODIS同化都可以改善模型模拟。 Caliop同化优于修改型气溶胶垂直分布和再现真正的大小和变化的Modis同化,并且联合卡利普和Modis同化可以进一步改善模拟气溶胶垂直分布。然而,Modis同化可以更好地再现AOT分布,而不是卡利普同化,并包含对AOT分析的微不足道的影响。这可能是由于Nadir-Viewing Caliop具有比MODIS多得多的稀疏覆盖率。 Caliop的同化效率随着立交桥时间的越来越长,表明需要更多的气溶胶垂直观察平台来填充传感器特定的观察间隙,从而改善气溶胶垂直数据同化。

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