Jul 23, 2017
Interesting idea but again, do we have so much input data for making a good sample size? How do we get that data and how long will it take? This may help to find the best method that is available but that may not be the best method possible.
I feel the budget is too low as well. An engineer salary is $100k which could be for year or two, but the project timeline is more than that.
Mona Al Zubaidi
Jul 24, 2017
It's a very important question to ask: where and how to get the data?
There are several resources that provide data, there's a data that available in R which covers 24 observations from the cloud seeding experiments in Florida: https://vincentarelbundock.github.io/Rdatasets/doc/HSAUR/clouds.html
There's another huge synthesised rainfall dataset that was collected between 1960-2005 in Australia, however it's not publicly available(we have to request for that):
Cloud seeding in the UAE started in 1990, I couldn't find any dataset online about the results of these experiments, but I believe there is some data collected and documented during these years for research purposes, and we have to ask them to give us the data (i'm still not sure about this).
Using local data could help us build more accurate results that are customised for the UAE weather, however using global data to build the model, and comparing it with the local model can help us more in understanding how different factors affect each others in the cloud seeding process.
The budget is just an estimation, this project could take a year or two, maybe less maybe more. Also, this depends weather the engineer is working full time on the project or not.