can reconcile() be used for distributional forecasts

I would like to know if reconcile() can be used with distributional forecasts.

As a reproducible example I took the m5 data and generated naive forecasts for total, ca, wi, and tx. The total is the sum of the three states. I generated 8000 samples over a 10 day forecast horizon. The data set can be grabbed with the following.

wget https://storage.googleapis.com/data_xvzf/m5_hierarchical_forecast.csv

This is the head

      ds         rep y_sim_total y_sim_ca y_sim_tx y_sim_wi 
1     2016-05-23 0   42171.      15851    13205.   13970.   
2     2016-05-23 1   30535.      13646.   13284.   13211.   
3     2016-05-23 2   44897.      16215.   13132.   12586.   
4     2016-05-23 3   39906.      16860.   11361.   13291.   
5     2016-05-23 4   47499.      18238.   13715.   13108.   
6     2016-05-23 5   46119.      18963.   9978.    11286.   
7     2016-05-23 6   46307.      18532.   13197.   12959.   
8     2016-05-23 7   35262.      18930.   11556.   9308.    
9     2016-05-23 8   43877.      18618.   11755.   14966.   

Can I use the reconcile() function to reconcile these forecasts to the total?