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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Data assimilation: From photon counts to Earth System forecasts
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Data assimilation: From photon counts to Earth System forecasts

机译:数据同化:从光子数到地球系统预测

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Data assimilation - the set of techniques whereby information from observing systems and models is combined optimally - is rapidly becoming prominent in endeavours to exploit Earth Observation for Earth sciences, including climate prediction. This paper explains the broad principles of data assimilation, outlining different approaches (optimal interpolation, three-dimensional and four-dimensional variational methods, the Kalman Filter), together with the approximations that are often necessary to make them practicable. After pointing out a variety of benefits of data assimilation, the paper then outlines some practical applications of the exploitation of Earth Observation by data assimilation in the areas of operational oceanography, chemical weather forecasting and carbon cycle modelling. Finally, some challenges for the future are noted. (C) 2007 Elsevier Inc. All rights reserved.
机译:数据同化(将观测系统和模型中的信息进行最佳组合的一组技术)在利用地球观测进行地球科学(包括气候预测)的努力中正迅速变得突出。本文解释了数据同化的广泛原理,概述了不同的方法(最佳插值,三维和四维变分方法,卡尔曼滤波器),以及通常使它们可行的近似方法。在指出了数据同化的各种好处之后,本文概述了通过数据同化开发地球观测的一些实际应用,这些数据在可操作的海洋学,化学天气预报和碳循环建模领域中得到应用。最后,指出了未来的一些挑战。 (C)2007 Elsevier Inc.保留所有权利。

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