Model Builder/ Inverse Distance Weighting

[SindanaIlango]

Hello, 

I would like some help creating a dataset with interpolated values for a set of defined regions. 

Have: I am starting with a shapefile of zipcodes, and a point file of estimates of daily values of pollutants at various coordinates (monitoring stations). Each row is a different day/monitoring station. There are many more zipcodes than coordinates with data. 

Want: I want to create a dataset with an interpolated estimates of pollutants for each zipcode, for each day, using information from the nearby monitoring stations. 

I am currently trying to approach this task with model builder with IDW and zonal statistics and using row iterator to iterate through the different days. It's not quite working, and would like some help. 

This is what I have (but, these aren't working) 

1) Is this an appropriate approach to create my goal dataset/ 

2) If so, how can I get this to work? If not, could you point me to a reference to get what I want/

Thank you!

[curtvprice]

Just a piece of advice.

It's really best to pull out the data for a single day, convert it to points 'by hand', and get your process working for ONE day's data. I'm thinking you may want to interpolate and then use zonal statistics as table (for zip code polygons) or extract values to points (for zip code centroids, which may be much more efficient and good enough if your zipcodes aren't too big).

Then add your iterator/convert to points later.