Chapter Variational Data Assimilation : Theory and Applications 1
نویسنده
چکیده
Variational data assimilation is performed using either a T40 18 layer version of the National Meteorological Center spectral model or a limited-area shallow-water equations model, with operationally analyzed fields as well as simulated datasets. Issues of incomplete observations, control of gravitational oscillations, and inclusion of “on-off” physical processes are addressed in the framework of Variational data assimilation.
منابع مشابه
IFS Documentation Cycle CY25r1 IFS DOCUMENTATION PART II: DATA ASSIMILATION (CY25R1)
Table of contents Chapter 1 ‘Incremental formulation of 3D/4D variational assimilation—an overview’ Chapter 2 ‘3D variational assimilation’ Chapter 3 ‘4D variational assimilation’ Chapter 4 ‘Background term’ Chapter 5 ‘Conventional observational constraints’ Chapter 6 ‘Satellite observational constraints’ Chapter 7 ‘Background, analysis and forecast errors’ Chapter 8 ‘Gravity-wave control’ Chap...
متن کاملIFS Documentation Cycle CY23r4 IFS DOCUMENTATION PART II: DATA ASSIMILATION (CY23R4)
Table of contents Chapter 1 ‘Incremental formulation of 3D/4D variational assimilation—an overview’ Chapter 2 ‘3D variational assimilation’ Chapter 3 ‘4D variational assimilation’ Chapter 4 ‘Background term’ Chapter 5 ‘Conventional observational constraints’ Chapter 6 ‘Satellite observational constraints’ Chapter 7 ‘Background, analysis and forecast errors’ Chapter 8 ‘Gravity-wave control’ Chap...
متن کاملEnsemble Kalman Filter: Current Status and Potential
In this chapter we give an introduction to different types of Ensemble Kalman filter, describe the Local Ensemble Transform Kalman Filter (LETKF) as a representative prototype of these methods, and several examples of how advanced properties and applications that have been developed and explored for 4D-Var (four-dimensional variational assimilation) can be adapted to the LETKF without requiring...
متن کاملSensitivity Analysis in Nonlinear Variational Data Assimilation: Theoretical Aspects and Applications
This chapter presents the mathematical framework to evaluate the sensitivity of a model forecast aspect to the input parameters of a nonlinear four-dimensional variational data assimilation system (4D-Var DAS): observations, prior state (background) estimate, and the error covariance specification. A fundamental relationship is established between the forecast sensitivity with respect to the in...
متن کاملVariational Data Assimilation Optimal Parameter Estimation and Sensitivity Analysis for Environmental Problems
Optimal control theory of partial di erential equations has emerged as a new way to attack problem of D atmospheric oceanic data assimilation problems These variational techniques attempt to achieve a best t between data observations and forecast model subject to some a priori criteria This review paper presents new trends for utilizing model adjoint equations for variational data assimilation ...
متن کامل