If you just want to model the variance and you are able to reformulate your two-level model as a single level multivariate model you can use the constraint feature, see example 5.23 in the user's guide.
Another approach is to use mixtures with a level 2 class variable and allow the variance to take different values across class.
The third approach (probably the best) is illustrated in this montecarlo example - however I did this for an observed variable rather than a factor for simplicity. You can see I used a constant of 0.1 to avoid singularity issues. This method gives you an actual variable on the between level that is not the variance but the square root of the variance. Run this example in Mplus to see the details.