Berkeley Earth vs. NOAA/NCDC

In honor of Earth Day I’m continuing my analysis of temperature data for the United States. We’ve already looked at the state-level data produced by Berkeley Earth, and used it to develop a map of the rise in annual mean temperature (AMT) for the lower 48 US states over the past century. NOAA/NCDC also provides time series of monthly mean temperatures for the individual US States (the data are available near the bottom of this page in the file climdiv-tmpcst-v1.0.0-20170404). We can use it to produce a similar map of the AMT rise for each state and compare it with a map developed using the Berkeley data.

To estimate statewide rise in AMT over a given time interval, I use loess to generate a smooth curve through the annual temperatures, then take the difference between the smoothed temperatures at the endpoints of the interval.

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Climate Change by US Climate Division

The previous post presented a choropleth map of the rise in annual mean temperature for each of the lower 48 US States over the period 1901-2012 based on data produced by Berkeley Earth. The map shows that over the period in question, the northern states experienced the largest rise in mean temperature. However, since statewide averages tend to smooth out changes that occur over smaller areas, my next objective was to develop a similar map for all 3,108 counties in the lower 48 States. Though such data likely exists (and could be generated using the Berkeley Earth software), I was unable to find it online. I did however find another interesting dataset with temperatures on a smaller scale: the NOAA/NCDC Climate Division data.

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Climate Change by US State

In this post I’m going to take a look at some data from Berkeley Earth that I obtained from this page on It’s important to understand the content of these files: Berkeley Earth has produced time series of monthly average temperatures over long periods of time for various land surface locations around the globe. They use a technique called kriging that allows them to combine data from multiple nearby sites to produce more accurate estimates of the actual temperature over time at a given location. The important point is that these adjusted temperatures do not necessarily correspond to measured temperatures at any particular location. The statistical procedure they use is intended to correct for the numerous factors that affect the accuracy of site temperature measurements: urban heat island effects, and changes in weather station location, instrumentation, time of day at which temperatures are measured, etc. A more complete discussion of this topic can be found here.
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