When collecting the weather data, I suggest getting the longest period possible. Along with the weather data, you will need information on how the crop was managed during the period you want to simulate (information like planting and harvesting date, amount, type, and date of fertilizer used (if any), tillage operations, etc.).
Then, for the period you want to simulate, you will need observed data. You can have direct observations from the field you want to simulate (for instance crop yield or leaf area index), or you can have information like the average yield in the region where your study area is located. Then, you have to consider that observed data is needed for the calibration and validation of the model (this is an extensive topic, I can give you more information if needed or you can read about it, I am sure there are many resources available). So, to give you a final number, I consider one year not enough unless you have several observed data (for instance multiple daily observations in one year). If you are going to use only crop yield to calibrate/validate the model, I would say that three years (three observations) is the minimum to be able to do some statistical analysis to evaluate the model results.
I hope this is not confusing you. Let me know if you have more questions.