Pseudo-Orbit Data Assimilation. Part II: Assimilation with Imperfect Models

Ifs Documentation Part Ii: Data Assimilation (cy21r4)

Part II : Data Assimilation IFS DOCUMENTATION – Cy 36 r 1 Operational implementation 26 January 2010 PART II : DATA ASSIMILATION

Chapter 3 3D variational assimilation (with the first-guess at appropriate time) Chapter 4 Background term Chapter 5 Observation operators and observation cost function (J o) Chapter 6 Background, analysis and forecast errors Chapter 7 Gravity-wave control Chapter 8 Diagnostics Chapter 9 Observation processing Chapter 10 Observation screening Chapter 11 Land-surface analysis Chapter 12 Analysis...

Part II : Data Assimilation IFS DOCUMENTATION – Cy 33 r 1 Operational implementation 3 June 2008 PART II : DATA ASSIMILATION

Data Assimilation with Gaussian Mixture Models Using the Dynamically Orthogonal Field Equations. Part II: Applications

The properties and capabilities of the Gaussian Mixture Model–Dynamically Orthogonal filter (GMMDO) are assessed and exemplified by applications to two dynamical systems: 1) the double well diffusion and 2) sudden expansion flows; both of which admit far-from-Gaussian statistics. The former test case, or twin experiment, validates the use of the Expectation-Maximization (EM) algorithm and Bayes...

Data assimilation for plume models

We use a four-dimensional variational data assimilation (4D-VAR) algorithm to observe the growth of 2-D plumes from a point heat source. In order to test the predictability of the 4D-VAR technique for 2-D plumes, we perturb the initial conditions and compare the resulting predictions to the predictions given by a direct numerical simulation (DNS) without any 4D-VAR correction. We have studied p...