Python Analysis Berkley Earth Surface Temperature data set – Bubble Gum Data

Clyde Spencer wrote a post for the Watts Up With That? climate blog entitled The Gestalt of Heat Waves.

Clyde used data sets from the Berkley Earth Surface Temperature project. It has, of course, the self-aggrandising acronym, BEST.

Clyde’s article concentrated somewhat on heatwaves using covariance of moving average data blocks although that is a simplification. I would recommend reading the article.

My preference was to look at the data using Pandas in Jupyter Lab to get a feel for what the data could reveal. As usual, I have posted the Notebook and data to my Github page if you want to download it and comment.

The great thing about Jupyter is that the code for the analyses is clearly presented for anyone to follow and criticise or improve.

So here it is..

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view raw BEST.ipynb hosted with ❤ by GitHub

I sort of understand why people may be protective of the hard work they have put into creating data sets. But this data set seems so contrived as to be actually worthless. Why present it as the ‘BEST’ when it’s probably not even a good guess?

What is the confidence interval of a temperature data point for March the 5th 1883 in this data set? As that most eloquent and erudite POTUS said, “There’s an old saying in Tennessee — I know it’s in Texas, probably in Tennessee — that says, fool me once, shame on — shame on you. Fool me — you can’t get fooled again.”

Bubble Gum Data

5 Comments

  1. Hi Sabra
    My main criticism of BEST is that there is not enough historical data for the southern hemisphere. Stephen Mosher believes that a trace gas governs the temperature of the planet. Well, it’s a big universe. The earth wobbles about on it’s axis. It revolves around a start in a solar system affected by gravition from the other planets. The solar system is moving through space. Where I am sitting was covered in a mile of ice 15,000 years ago. Planes, trains and automobiles didn’t melt it.

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  2. Thank you for your kind words, Carolina.
    It was very simple 🙂 There is just not enough data from the Southern hemisphere to make accurate conclusions.

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