Data Standardization Question

[Miordamas]

Hi everyone.
I’m doing a project on the urban heat island effect. To that end, I’ve got daily temperature data at different climate sites for the 100 largest metro areas from 1966-2015. I’m using census data to get the populations of each metro area during each decade.

The thing is, there’s a very noticable effect from global warming: after standardizing temperature data for each climate site based on averages over the whole timescale, I’m getting an R-squared of nearly 30% just from comparing decade to standardized temps. Some of that is due to increasing urban heat island from growing population, but it exists pretty strongly even for the most rural climate sites I’ve got data from (35-50km from metro center), where the urban heat island is lessened.

Sure, some metro areas are big enough where that far might be within a dense area, but some of the ones showing this certainly aren’t — for instance, I doubt the station in Claremore, OK outside of Tulsa is in a pretty darn rural area.

Is there a good way to separate the global warming effect from the population effect, or is that unrealistic?

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Hi everyone.
I’m doing a project on the urban heat island effect. To that end, I’ve got daily temperature data at different climate sites for the 100 largest metro areas from 1966-2015. I’m using census data to get the populations of each metro area during each decade.

The thing is, there’s a very noticable effect from global warming: after standardizing temperature data for each climate site based on averages over the whole timescale, I’m getting an R-squared of nearly 30% just from comparing decade to standardized temps. Some of that is due to increasing urban heat island from growing population, but it exists pretty strongly even for the most rural climate sites I’ve got data from (35-50km from metro center), where the urban heat island is lessened.

Sure, some metro areas are big enough where that far might be within a dense area, but some of the ones showing this certainly aren’t — for instance, I doubt the station in Claremore, OK outside of Tulsa is in a pretty darn rural area.

Is there a good way to separate the global warming effect from the population effect, or is that unrealistic?

How are you currently standardizing the temperatures? I was thinking you could compare the graphs of the city temperature to the graphs of the temperature of surrounding regions. You might find something useful by researching about the confounding effect.