I'm hoping to get clarification about the integration of a rain sensor and its effect on the RM algorithms when coupled with the NOAA weather forecasts..

We get frequent PopUp Storms in Georgia which can be very local and as such easily throw off the NOAA forecasting : for example, one side of our Zip Code can be deluged while the other is Sunny and dry ; i noticed last year that RM often forecast rain (so cancelled water) which we never got - while other times we forecast a dry day but got alot of rain.

Scenario 1 ; RM forecasts a dry day - so calls for watering - but the rain sensor can see it has rained -  so is that amount of rain measured and watering amount compensated?, or is watering cancelled ?, or something else ?

Scenario 2 ; RM forecasts a wet day and cancels watering - but the rain sensor never sees any rain at all that day ; at some point in time does the RM figure out it never rained as NOAA forecast and then calls for watering to make up for the lack of rain that didn't arrive ?

There are a couple of other similar "reverse logic" type of scenarios but hopefully you will get my drift here...

Thoughts would be welcome on above scenarios and also which rain sensor would work best in my local weather conditions ?

Thanks in advance.