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Inversion and assimilation methods with applications in geophysical remote sensing

机译:反演和同化方法及其在地球物理遥感中的应用

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摘要

Stratospheric ozone can be measured accurately using a limb scatter remote sensing technique at the UV-visible spectral region of solar light. The advantages of this technique includes a good vertical resolution and a good daytime coverage of the measurements. In addition to ozone, UV-visible limb scatter measurements contain information about NO2, NO3, OClO, BrO and aerosols. There are currently several satellite instruments continuously scanning the atmosphere and measuring the UVvisible region of the spectrum, e.g., the Optical Spectrograph and Infrared Imager System (OSIRIS) launched on the Odin satellite in February 2001, and the Scanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) launched on Envisat in March 2002. Envisat also carries the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, which also measures limb-scattered sunlight under bright limb occultation conditions. These conditions occur during daytime occultation measurements.The global coverage of the satellite measurements is far better than any other ozone measurement technique, but still the measurements are sparse in the spatial domain. Measurements are also repeated relatively rarely over a certain area, and the composition of the Earth’s atmosphere changes dynamically. Assimilation methods are therefore needed in order to combine the information of the measurements with the atmospheric model. In recent years, the focus of assimilation algorithm research has turned towards filtering methods. The traditional Extended Kalman filter (EKF) method takes into account not only the uncertainty of the measurements, but also the uncertainty of the evolution model of the system. However, the computational cost of full blown EKF increases rapidly as the number of the model parameters increases. Therefore the EKF method cannot be applied directly to the stratospheric ozone assimilation problem.The work in this thesis is devoted to the development of inversion methods for satellite instruments and the development of assimilation methods used with atmospheric models.
机译:平流层臭氧可以使用肢体散射遥感技术在太阳光的紫外线可见光谱区域内准确测量。该技术的优点包括良好的垂直分辨率和良好的白天覆盖范围。除臭氧外,紫外线可见的肢体散射测量还包含有关NO2,NO3,OClO,BrO和气溶胶的信息。当前有几种卫星仪器不断扫描大气并测量光谱的紫外可见区域,例如2001年2月在Odin卫星上发射的光学光谱仪和红外成像仪系统(OSIRIS),以及用于大气CartograpHY的扫描成像吸收光谱仪( SCIAMACHY)于2002年3月在Envisat发射。Envisat还带有全球星际掩星监测臭氧(GOMOS)仪器,该仪器还可以在明亮的四肢掩星条件下测量四肢散射的阳光。这些条件发生在白天的掩星测量中。卫星测量的全球覆盖范围远胜过其他任何臭氧测量技术,但在空间范围内测量仍然很少。在特定区域也很少重复进行测量,并且地球大气的组成会动态变化。因此需要同化方法,以便将测量信息与大气模型结合起来。近年来,同化算法研究的重点已转向过滤方法。传统的扩展卡尔曼滤波器(EKF)方法不仅考虑了测量的不确定性,而且还考虑了系统演化模型的不确定性。但是,随着模型参数数量的增加,全吹式EKF的计算成本会迅速增加。因此,EKF方法不能直接应用于平流层臭氧的同化问题。本文的工作致力于卫星仪器反演方法的发展和大气模型的同化方法的发展。

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    Auvinen Harri;

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  • 年度 2009
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