This program is a very simple implementation of a basic Cressman scheme, to illustrate how the scheme performs in areas of sparse and dense observations. [A. Lawless, The University of Reading]
This set of routines allows the user to see how different settings of the statistical parameters affect the final analysis, using small one-dimensional optimal interpolation problems. Three different routines are provided, which are explained in the documentation. It is also necessary to include the routines plclose.pro and plopen.pro in your directory, to enable printing of plots. [R. Swinbank, Met Office]
Four sequential data assimilation schemes are implemented on two simple problems, an oscillating system and the Lorenz system. For each problem the user can choose which data assimilation scheme to use and can add random noise to the observations. All inputs are through menu interfaces. The programs use the routine menu_asl.m, which is an altered version of the standard menu routine and must be downloaded with the main programs. [M. Martin & A. Lawless, The University of Reading]
This program illustrates the principle of linear and nonlinear normal mode initialization on the swinging spring problem. The user can compare how the two initializations perform as the parameters of the problem are changed. [Peter Lynch, Met Eireann]
For more information on this problem, including a Java animation, see Peter Lynch's Swinging Spring page.
An illustration of 4D-Var applied to the Lorenz system, using a modified Euler system and its adjoint. The program runs an identical twin experiment. The user can compare the analysis and convergence for different model parameters and observations. [M. Wlasak & A. Lawless, The University of Reading]
A more complex 4D-Var system, based on the double pendulum, which performs several cycles of the data assimilation algorithm. One plotting routine is made available, but many other data can be plotted, as discussed in the documentation. [R. Bannister, The University of Reading]