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首页> 外文期刊>Nonlinear processes in geophysics >Impact of an observational time window on coupled data assimilation: simulation with a simple climate model
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Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

机译：观测时间窗口对耦合数据同化的影响：使用简单气候模型的模拟

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Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and qtwin/q CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.
机译：气候信号是耦合地球系统中多种时标介质（如大气和海洋）相互作用的结果。耦合数据同化（CDA）通过将来自多种媒体的观测值整合到耦合模型中，追求平衡，一致的气候分析和预测初始化。在实践中，通常使用观测时间窗口（OTW）收集同化周期的测量数据，以增加按顺序被其原始误差标度同化的观测样本。给定不同介质的特征变化的时间尺度不同，耦合介质的最佳OTW是多少，以便CDA可以最准确地恢复气候信号？通过一个简单的耦合模型来模拟气候系统中典型的尺度相互作用以及 twin CDA实验，我们在这里解决了这个问题。结果表明，在每种耦合介质中，最佳OTW可以提供最大的观测信息，从而最适合数据混合过程中介质的特征变异性。保持正确的尺度相互作用，生成的CDA大大改善了对气候信号的分析。这些简单的模型结果为将实际观测值吸收到耦合的一般环流模型中提供了指导，以通过准确恢复重要的特征变化（例如大气中的亚昼间和海洋的日间变化）来改善气候分析和预测初始化。

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