2011-12-27 10:53:54Summary of Hansen 2011
michael sweet


I wrote a summary of Hansen 2011 for general readers.  It is available here.  It is intended to summarize the paper for the general public.  I am not strong enough at statistics to review Hansen's claims, and I have not seen any comments on the web, does anyone have comments?  The analysis seems simple to me. 

I would like to emphasize that this analysis shows that the three sigma areas on the map are due to AGW if that can be justified.  Can this be claimed?

2011-12-27 16:20:43Contacting Hansen?


Michael, how about sending your summary to James Hansen before publishing it? That would ensure that it's correct from the lead author's perspective.

2011-12-27 20:31:59
Mark Richardson

Hi michael,

I think this is good work on the cntent, but the style needs improving.


1) the writing style is sometimes a bit like a report. You could cut down a lot of words to make it flow better and change the description slightly. e.g. words like 'quantify' are more common and easy to read than 'quantitate'. At the moment it doesn't read like a blog post!

2) Wiki (and elsewhere) have some good pictures of what standard deviation means in a Gaussian distribution. Might be worth getting one of these.

3) When you have a caption below a picture, it's recommended to make it look different. I make the Figure # bold and the caption italic, some just italicise the whole thing.

4) The graphs could do with being a bit bigger! You can try stretching them out, or if that doesn't work you can make them bigger by zooming into the .pdf (CTRL+mouse wheel on a PC) and taking a screengrab.

2011-12-27 22:12:42
michael sweet


Baerbel: I was planning on sending it to Hansen for comments after the other authors at Skeptical Science think it is good enough to post.  I have asked him questions before and he is very helpful.

Mark: thank you for your comments.

1) Unfortunately, I write good reports and poor descriptive articles.  If someone else wanted to edit the post to make it more readable I am open to help, but I doubt I can make it more readable on my own.  Is the post good enough as it is?  Two points that are important to me: Is it clear to someone who does not know statistics?  Is it so hard to read that people will skip it? 

2)   I think the article is a good length and has enough graphs as it is.  Would adding another graph make it more readable for those people who do not know what a Gaussian distribution is? Hansen has a graph showing the data approximates a Gaussian distribution from 1950 to 1980.  I expect there to be discussion in the comments about the suitability of this type of analysis.

3) Changes made.

4) The graphs are hard to read in the original, full page format.  They do not fit well in the Skeptical Science format.  I thought that people who really want to review the graphs will go to the original.  Will most people who have not read the original look carefully at the graphs?  I could expand say the graph of 1975 and 2010 only and then they would be more readable.  Would I then have to answer for cherry picking?  It is hard for me to manipulate the graphs, that is one reason it took so long to post the article here.

2011-12-28 02:56:07Michael Seeet
John Hartz
John Hartz

I'll take a crack at rewritting your article. (During my professional career in the transportation sector, i spent a considerable amount of time editing draft technical documents to make them understandable to the general public.) It may take me a couple of days though because of other draws on my time.

2011-12-28 03:21:21
Mark Richardson

My suggested style changes for the first 3 paragraphs (I have to rush off now :P ):


James Hansen, M. Sato and R. Ruedy have posted a new paper to their website. It has not been peer reviewed yet, but will eventually be published with some changes.  Hansen et al analyze the NASA temperature data quantify the number of very hot and very cold summers and winters. 

Temperature anomalies

Hansen et al use the period 1951-1980 to calculate an average temperature for each location. Then the difference between a measured temperature and the average is calculated and called an anomaly. For example, if the average temperature in a place is 10 C, and one day records 15 C, then the anomaly is +5 C.

Where there are data, this allows maps of hotter-than-normal and colder-than-normal temperatures to be created, like in the figure below.


2011-12-30 02:58:04edits made
michael sweet



I made the changes you suggested.  I added one line about using anomalies to compare temperatures.  I was surprised how much minor changes made the readability much easier.  I went through the rest of the post and made a few minor changes. 

Thank you for your help.