Here are the [results]( of training a model
using 12 month window of past pressures to predict 6 month into the future.
It is a little better than using just one month but not massively so.
Looking at the results I noticed that all models predict very conservatively, this was particularly noticeable in the scatterplots which had slope of around 0.5.
This is primarily due to the strong normalization required for training on more features than inputs.

I have gone through and consistently multiplied all the model outputs by a factor of 2.
This primarily affects the appearance of the side by side plots.
Correlation values are not affected by scaling.

This is a modification after looking at the results, but given that it is just uniform scaling I think it is justifiable.