Assigning values to missing target vector values in scikit-learn
The model likely won't have much predictive power if the input is a single day. No weather patterns longer than one day can be captured that way.

Instead you should aggregate the days together. You can come up with different features that describe your larger, aggregated unit of time (months, year). For example mean precipitation is a very simple one. Binning the data and using counts within those bins would also work.

More advanced options would roll the time all the way up to a full year and learn a feature set at that level.