qgplay.m

集合卡尔曼滤波(EnKF) 数据同化方法可以避免了EKF 中协方差演变方程预报过程中出现的计算不准确和关于协方差矩阵的大量数据的存储问题,最主要的是可以有效的控制估计误差方差的增长,改善预报的效果。

% function [] = qgplay(psi, q, t, delay, dn)
%
% Plays PSI and Q fields read by qgread() as a movie.
%
% @param psi - psi (stream function); input; use output from qgread()
% @param q - q (vorticity); input; use output from qgread()
% @param t - t (time); input; use output from qgread()
% @param dt - time delay between frames; input
% @param dn -- stop every dn dumps; input

% File:           qgplay.m
%
% Created:        15/08/2007
%
% Last modified:  08/02/2008
%
% Author:         Pavel Sakov
%
% Purpose:        Plays PSI and Q fields read by qgread() as a movie.
%
% Description:
%
% Revisions:

%% Copyright (C) 2008 Pavel Sakov
%% 
%% This file is part of EnKF-Matlab. EnKF-Matlab is a free software. See 
%% LICENSE for details.

function [] = qgplay(psi, q, t, delay, dn)
    figure
    [nr, ny, nx] = size(psi);
  
    psi_max = max(max(max(abs(psi))));
    psi_range = [-psi_max psi_max];

    q_max = max(max(max(abs(q))));
    q_range = [-q_max q_max];
  
    for dump = 1 : nr
        subplot(1, 2, 1);
        A = squeeze(psi(dump, :, :));
        imagesc(A, psi_range);
        str = sprintf('\\Psi, dump = %d, t = %.0f', dump, t(dump));
        title(str);
        axis image;
    
        subplot(1, 2, 2);
        B = squeeze(q(dump, :, :));
        imagesc(B, q_range);
        title('Q');
        axis image;
    
        pause(delay);

        if exist('dn', 'var') & mod(dump, dn) == 0
            pause
        end
    end
  
    return