Comparing Two Approaches for Assessing Observation Impact
Comparing Two Approaches for Assessing Observation Impact
复制标题
比较两种评估观察影响的方法
DOI：
10.1175/mwr-d-12-00100.1
复制
发表时间：
2013
影响因子：
3.2
通讯作者：
R. Todling
中科院分区：
文献类型：
--
作者：
R. Todling
朗兰德和贝克引入了一种方法来评估观测对预报的影响。在这种方法中，定义了预报的状态空间方面，并导出了最终将该方面的变化与观测系统的变化联系起来的程序。值得注意的是，状态空间方法的一些特点是：预报方面的典型选择是相当主观的，导致对观测系统的不完全评估，它要求提供实际上与预报相关的验证状态，它涉及整个数据同化系统的伴随算子，因此受到该算子的有效性的限制。本文从估计理论的角度重新审视了观测影响这一话题。观测空间度量用于推断观测对预报的影响，而不受刚才提到的限制。利用连续预报得到的观测减去预报残差的差值可以产生以下优点：(1)它建议了一个相当自然的预报方面的选择，它直接与数据同化过程相联系；(2)它避免在预报方面引入不必要的相关性，因为是针对观测进行验证的；(3)它不涉及共轭的线性化和使用。观测空间方法还有一个额外的优势，那就是几乎没有成本，而且实施起来非常简单。在其最简单的形式中，它归结为用传统方法估计观测减去背景和观测减去分析残差的统计量。使用NASA戈达德地球观测系统给出了比较这两种方法的插图。
Langland and Baker introduced an approach to assess the impact of observations on the forecasts. In that approach, a state-space aspect of the forecast is defined and a procedure is derived ultimately relating changes in the aspect with changes in the observing system. Some features of the state-space approach are to be noted: the typical choice of forecast aspect is rather subjective and leads to incomplete assessment of the observing system, it requires availability of a verification state that is in practice correlated with the forecast, and it involves the adjoint operator of the entire data assimilation system and is thus constrained by the validity of this operator. This article revisits the topic of observation impacts from the perspective of estimation theory. An observation-space metric is used to allow inferring observation impact on the forecasts without the limitations just mentioned. Using differences of observation-minus-forecast residuals obtained from consecutive forecasts leads to the following advantages: (i) it suggests a rather natural choice of forecast aspect that directly links to the data assimilation procedure, (ii) it avoids introducing undesirable correlations in the forecast aspect since verification is done against the observations, and (iii) it does not involve linearization and use of adjoints. The observation-space approach has the additional advantage of being nearly cost free and very simple to implement. In its simplest form it reduces to evaluating the statistics of observationminus-background and observation-minus-analysis residuals with traditional methods. Illustrations comparing the approaches are given using the NASA Goddard Earth Observing System.