Pseudo-Orbit Data Assimilation. Part II: Assimilation with Imperfect Models
Pseudo-Orbit Data Assimilation. Part II: Assimilation with Imperfect Models
复制标题
伪轨道数据同化。
DOI：
10.1175/jas-d-13-033.1
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发表时间：
2014
影响因子：
3.1
通讯作者：
Smith L
中科院分区：
文献类型：
--
作者：
Smith L
非线性模式的数据同化和状态估计是一项具有挑战性的数学任务。就像在业务天气预报中一样，实时执行这项任务甚至更具挑战性，因为模型并不完美：产生观测的数学系统(如果存在这样的东西)不是可用的模型类(即被认为是潜在模型的数学结构集)的成员。在某种程度上，传统方法根本无法解决结构性模型错误，大多数方法无法产生一致的处理方法。这导致对模型状态及其不确定性的估计都是有问题的。提出了一种有前景的替代方法，以产生更一致的模型状态估计，并同时估计(状态相关的)模型误差。这一替代方案包括带有停止标准的伪轨道数据同化。它比另一种变分方法[弱约束四维变分同化(4DVAR)的一种版本]更有效和更连贯。结果表明，伪轨道数据同化方法的性能也优于集合卡尔曼滤波方法。这两个比较都是在18维Lorenz96流和二维Ikeda图的背景下进行的。在定义数据同化的目标和实现高质量的状态估计方面，完美模式情景之外的许多挑战仍然存在。伪轨道数据同化方法为解决这一开放问题提供了一种新的工具。
Data assimilation and state estimation for nonlinear models is a challenging task mathematically. Performing this task in real time, as in operational weather forecasting, is even more challenging as the models are imperfect: the mathematical system that generated the observations (if such a thing exists) is not a member of the available model class (i.e., the set of mathematical structures admitted as potential models). To the extent that traditional approaches address structural model error at all, most fail to produce consistent treatments. This results in questionable estimates both of the model state and of its uncertainty. A promising alternative approach is proposed to produce more consistent estimates of the model state and to estimate the (state dependent) model error simultaneously. This alternative consists of pseudo-orbit data assimilation with a stopping criterion. It is argued to be more efficient and more coherent than one alternative variational approach [a version of weak-constraint four-dimensional variational data assimilation (4DVAR)]. Results that demonstrate the pseudo-orbit data assimilation approach can also outperform an ensemble Kalman filter approach are presented. Both comparisons are made in the context of the 18-dimensional Lorenz96 flow and the two-dimensional Ikeda map. Many challenges remain outside the perfect model scenario, both in defining the goals of data assimilation and in achieving high-quality state estimation. The pseudo-orbit data assimilation approach provides a new tool for approaching this open problem.
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DOI：
--
发表时间：
2001
期刊：
影响因子：
--
作者：
J. Hansen;Leonard A. Smith
通讯作者：
Leonard A. Smith
影响因子：
3.1
作者：
H. Du;Leonard A. Smith
通讯作者：
Leonard A. Smith
影响因子：
4
作者：
Judd, K;Smith, LA
通讯作者：
Smith, LA
DOI：
10.4172/2090-0902.1000167
发表时间：
2016-05
期刊：
Journal of Physical Mathematics
影响因子：
--
作者：
Tim Tarver
通讯作者：
Tim Tarver
模型误差的几何
DOI：
--
发表时间：
2008
期刊：
影响因子：
--
作者：
K. Judd;C. Reynolds;T. Rosmond;Leonard A. Smith
通讯作者：
Leonard A. Smith