def METHOD_NAME(states, tstep):
    '''
    Plot extracted model states XY slices
    :param states: extracted model states.
    :type states: dict of `numpy.array` objects.
    :param str tstep: timestep value of data.
    '''
    levels = list(states.keys())
    for i, level in enumerate(levels):
        # Get coordinates and data to plot
        x_val = states[level][:, 0]
        y_val = states[level][:, 1]
        height = states[level][:, 2][0]
        data = states[level][:, 3]
        # Create contour plot from flattened arrays
        fig = plt.figure(i + 1)
        plt.subplot()
        ax_plt = plt.gca()
        tcf = ax_plt.tricontourf(x_val, y_val, data)
        fig.colorbar(tcf)
        ax_plt.set_aspect('equal')
        ax_plt.set_xlabel('x')
        ax_plt.set_ylabel('y')
        ax_plt.set_title("Output field values at level %i (z = %.2f m) and "
                         "timestep %s" % (level, height, tstep))
        # Save plots on each levels as a PNG file
        fig_name = '_'.join(["Level", str(level), "timestep", tstep])
        plt.savefig(fig_name+".png")