On a Quantitative Semicontinuity Property of Variational Systems with Applications to Perturbed Quasidifferentiable Optimization

2013 ◽  
pp. 115-136 ◽  
Author(s):  
A. Uderzo
Keyword(s):  
Semicontinuity Property ◽  
Variational Systems

scholarly journals Stability analysis of parametric variational systems

2011 ◽  
Vol 1 (2) ◽  
pp. 317-331 ◽  
Author(s):  
Shengji Li ◽  
◽  
Chunmei Liao ◽  
Minghua Li
Keyword(s):  
Stability Analysis ◽  
Parametric Variational Systems ◽  
Variational Systems

scholarly journals Full Stability of General Parametric Variational Systems

2018 ◽  
Vol 26 (4) ◽  
pp. 911-946 ◽  
Author(s):  
B. S. Mordukhovich ◽  
T. T. A. Nghia ◽  
D. T. Pham
Keyword(s):  
Parametric Variational Systems ◽  
Variational Systems

Coderivative Analysis of Variational Systems

2004 ◽  
Vol 28 (3/4) ◽  
pp. 347-362 ◽  
Author(s):  
Boris S. Mordukhovich
Keyword(s):  
Variational Systems

Strongly Regular Differential Variational Systems

2007 ◽  
Vol 52 (2) ◽  
pp. 242-255 ◽  
Author(s):  
Jong-Shi Pang ◽  
Jinglai Shen
Keyword(s):  
Strongly Regular ◽  
Variational Systems

scholarly journals A Comparison of Variational and Ensemble-Based Data Assimilation Systems for Reanalysis of Sparse Observations

2009 ◽  
Vol 137 (6) ◽  
pp. 1991-1999 ◽  
Author(s):  
Jeffrey S. Whitaker ◽  
Gilbert P. Compo ◽  
Jean-Noël Thépaut
Keyword(s):  
Data Assimilation ◽  
Variational Data Assimilation ◽  
System Experiment ◽  
Analysis Error ◽  
Comparable Quality ◽  
Data Assimilation System ◽  
Assimilation System ◽  
Variational Systems

Abstract An observing system experiment, simulating a surface-only observing network representative of the 1930s, is carried out with three- and four-dimensional variational data assimilation systems (3D-VAR and 4D-VAR) and an ensemble-based data assimilation system (EnsDA). It is found that 4D-VAR and EnsDA systems produce analyses of comparable quality and that both are much more accurate than the analyses produced by the 3D-VAR system. The EnsDA system also produces useful estimates of analysis error, which are not directly available from the variational systems.

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