Second-Order Information in Data Assimilation*
نویسندگان
چکیده
منابع مشابه
Second-Order Information in Data Assimilation*
In variational data assimilation (VDA) for meteorological and/or oceanic models, the assimilated fields are deduced by combining the model and the gradient of a cost functional measuring discrepancy between model solution and observation, via a first-order optimality system. However, existence and uniqueness of the VDA problem along with convergence of the algorithms for its implementation depe...
متن کاملEfficiency of a POD-based reduced second-order adjoint model in 4D-Var data assimilation
Order reduction strategies aim to alleviate the computational burden of the four-dimensional variational data assimilation by performing the optimization in a low-order control space. The proper orthogonal decomposition (POD) approach to model reduction is used to identify a reduced-order control space for a two-dimensional global shallow water model. A reduced second-order adjoint (SOA) model ...
متن کاملSecond-order motion conveys depth-order information.
Psychophysical and neurophysiological studies have revealed that the visual system is sensitive to both "first-order" motion, in which moving features are defined by luminance cues, and "second-order" motion, in which motion is defined by nonluminance cues, such as contrast or flicker. Here we show psychophysically that common types of second-order stimuli provide potent cues to depth order. Al...
متن کاملReduced-order Observation Sensitivity in 4d-var Data Assimilation
Observation sensitivity techniques have been initially developed in the context of 3D-Var data assimilation for applications to targeted observations (Baker and Daley 2000, Doerenbecher and Bergot 2001). Adjoint-based methods are currently implemented in NWP to monitor the observation impact on analysis and short-range forecasts (Fourrié et al. 2002, Langland and Baker 2004, Zhu and Gelaro 2008...
متن کاملAccelerating SVRG via second-order information
We consider the problem of minimizing an objective function that is a sum of convex functions. For large sums, batch methods suffer from a prohibitive periteration complexity, and are outperformed by incremental methods such as the recent variance-reduced stochastic gradient methods (e.g. SVRG). In this paper, we propose to improve the performance of SVRG by incorporating approximate curvature ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Monthly Weather Review
سال: 2002
ISSN: 0027-0644,1520-0493
DOI: 10.1175/1520-0493(2002)130<0629:soiida>2.0.co;2