Which technique is most suitable for modeling temperature and precipitation

This is the first time I'm using R to model climate.

I have three variables of 1-min data as per below:

x<-data.frame(matrix(c("2012-02-04", "2012-02-04", "2012-02-04", "2012-02-04", "00:00",
"00:01","00:02","00:03", "960.0244", "960.0258", "960.0272", "960.0286",
"12", "12.2", "12", "12.1", "0", "0.1","4", "2"), ncol=5))

names(x)<-c("date","time","pressure","temperature","precipitation")

date   time  pressure  temperature  precipitation
1 2012-02-04  00:00  960.0244           12              0
2 2012-02-04  00:01  960.0258         12.2            0.1
3 2012-02-04  00:02  960.0272           12              4
4 2012-02-04  00:03  960.0286         12.1              2


Of course, the original data is much much larger (approximately 8 variables) and much much longer (3 million rows, total 8 years of data).

I'm afraid conventional regression technique i.e. linear regression lm(precipitation~temperature+pressure) or even polynomial or multiple linear may not be sufficient for modeling this kinda research.

So I would like to know what kind of modeling technique can I use to model the relationship between precipitation to other variables?

• "I'm afraid conventional regression technique i.e. linear regression lm(precipitation~temperature+pressure) or even polynomial or multiple linear may not be sufficient for modeling this kinda research." What makes you think that? I guess it depends on what you mean by "conventional regression technique". I suggest taking a look at (quite conventional) ARIMA models. Jun 18, 2018 at 5:19
• @MauritsEvers because in the long term the temperature graph looks like a sine wave, and hence a straight linear line (or even a polynomial X^3) wouldn't be sufficient to describe the graph..
– MT32
Jun 18, 2018 at 5:26
• That's exactly why I mentioned ARIMA models; they can include seasonal (repetitive) effects; still very conventional modelling though... Jun 18, 2018 at 5:29
• @MauritsEvers, thanks for the tip. I'll look up the ARIMA models
– MT32
Jun 19, 2018 at 3:46
• PS. Perhaps share a bigger (more presentative) chunk of your data, including the code you've tried so far. This would give people a chance to come up with a more specific answer/solution to your question. Jun 22, 2018 at 10:30