Inside The Sausage Factory

Reblogged from Watts up with That:

Guest Post by Willis Eschenbach

There’s an old saying that “Laws are like sausages. It’s better not to see either one being made” … and I fear the same is true for far too much of what passes for climate “science” these days.

However, ignoring such wise advice, I’ve taken another look under the hood at the data from the abysmal Nature Communications paper entitled “Discrepancies in scientific authority and media visibility of climate change scientists and contrarians.” My previous analysis of the paper is here on WUWT.

In that article, it says that the “Source Data files” for the article are located here. That seemed hopeful, so I looked at that page. There, they say:

We document the media visibility and climate change research achievements of two groups of individuals representing some of  the most prominent figures in their respective domains: 386  climate change contrarians (CCC)  juxtaposed with 386 expert climate change scientists (CCS). These data were collected from the Media Cloud project (MC), an open data project hosted by the MIT Center for Civic Media and the Berkman Klein Center for Internet & Society at Harvard University. 

Enclosed are raw MC data and parsed media article data files obtained from two types of MC database queries: 

(i) ~105,000 media articles derived from the MC search query ”climate AND change AND global AND warming”; 

(ii) 772 individual data files, for each member of the CCC and CCS groups, each derived from a single MC search query ”MemberFullName AND climate”. 

Well hooray, that sounded great, that the raw data was “enclosed”. I was even happier to see that they’d provided the computer code they’d used, viz:

Source code: provided in a Mathematica (v11.1) notebook (MediaSource_Annotated_ALL_2256.nb using MediaSource_Annotated_ALL_2256.txt) reproduces the subpanels for Fig. 5 in the following research article

Outstanding, I thought, I have everything I need to replicate the study—the full code and data as used to do the calculations! That hardly ever happens … but then I noticed the caveat at the top of the page:

Data Files: This dataset is private for peer review and will be released on January 1, 2020.

Grrr … these jokers write a “scientific” paper and then they don’t release the code or the data for six months after publication? That’s not science, that a buncha guys engaged in what we used to call “hitchhiking to Chicago” accompanied by the appropriate obscene one-handed gesture with the thumb extended…

Undeterred, I went to take a look at the “Mediacloud” that they referred to. It’s an interesting dataset of hundreds of thousands of articles, and I’ll likely make use of it in the future. But it turns out that there was a huge problem … you can’t just enter e.g. “Willis Eschenbach” AND climate as their web page fatuously claims. You also need to specify just which sources you are searching, as well as the date range you’re interested in … and their information page says nothing about either one.

Now, in my list of media mentions in the Supplementary Information from their paper, there are only 40 results … but when I searched the entire Mediacloud dataset from 2001-01-01 to the present for my name plus “climate” as they say that they did, I got over 500 results … say what?

I’ve written to the corresponding author listed on that web page for clarification on this matter, but I’m not optimistic about the speed of his response … he may have other things on his mind at the moment.

Frustrated at Mediacloud, I returned to the paper’s data. In total there are over 60,000 media mentions between all of the 386 of us who are identified as “contrarians”. I decided to see which websites got the most mentions. Here are the top twenty, along with the number of times they were referenced:

  •           6279
  •              4877
  •          3908
  •            2543
  •            1442
  •    1115
  •              871
  •                 827
  •               709
  •                 650
  •               641
  •                609
  •               515
  •                   426
  •            411
  •                      398
  •                384
  •                  379
  •            355
  •                 334

There are some real howlers in just these top twenty. First, as near as I can tell the most referenced site, the local California newspaper “Laguna Beach Independent” with 6,279 mentions, doesn’t contain any of the 386 listed names. Totally bogus, useless, and distorts the results in every direction.

Next, DeSmogBlog has 827 mentions … all of which will probably be strongly negative. After all, that’s their schtick, negative reviews of “contrarians”. I’ll return to this question of negative and positive mentions in a moment.

Then there’s “” with 411 mentions, which is a dead link. Nobody home, the website is not “pining for the fjords” as they say.

And “” seems to be an aggregator which often references a study or news article more than once. Here’s an example of such double-counting, from one person’s list of media mentions:,en,Firedoglake,809,247540225,CNBC Caught Soliciting Op-Ed Calling Climate Change A ‘Hoax’,2014-6-30,en,,58791,247551206,CNBC Caught Soliciting Op-Ed Calling Climate Change A ‘Hoax’,2014-6-30″

Note that both of these links reference the same underlying document, “CNBC Caught Soliciting Op-Ed Calling Climate Change A ‘Hoax’”, but the document is located on two different websites. I didn’t have the heart or the time to find out how often that occurred … but the example above was from the very first person I looked at who had in their list of mentions.

(I suppose I shouldn’t be surprised by the abysmal lack of quality control on their list of websites, because after all these authors are obviously devout Thermageddians … but still, those egregious errors were a real shock to me. My high school science teacher would have had a fit if we’d done that.)

Next, as I mentioned above, looking at that list I was struck by the fact that there is a huge difference between being mentioned on say DeSmogBlog, which will almost assuredly be a negative review, and being mentioned on ClimateDepot, which is much more likely to be positive in nature. But how could I quantify that?

To answer the question, I went back to Mediacloud. They have about a thousand websites which they have categorized as either Left, Center Left, Center, Center Right, or Right. So I decided to see how many times each category of websites was mentioned in the 60,000 media mentions for contrarians … here are those numbers.

  • Left:             6628
  • Center Left:    4051
  • Center:           2241
  • Center Right: 2056
  • Right:           4582
  • Total Left:     10679
  • Total Right:     6638

As you can see, there are about 50% more mentions on left-leaning websites than on right-leaning … so it appears quite possible that, rather than “contrarians” getting more good publicity than mainstream climate scientists as the paper claims, per their calculations “contrarians” are getting more bad publicity than mainstream climentarians.

Finally, before I left the subject and the website behind, I used Mediacloud to see how a couple of other people fared. Recall that all 396 of us “contrarians” garnered about 60,000 media mentions between us.

I first took a look at the media mentions of St. Greta of Thunberg, the Patron Saint of the Easily Led. Since she burst on the scene a few months ago, she has gotten no less than 36,517 mentions in the media, about 60% of the total of all the “contrarians” listed in their study.

I then looked at the man who has made more money out of climate hysteria than any living human being, the multimillionaire Climate Goracle, Mr. Al Gore himself. A search of Mediacloud for ‘”Al Gore” AND climate’ returned a total of 92,718 hits.

So while the clueless authors of this paper are so concerned about how much air time we “contrarians” get, between them just Al Gore and Greta Thunberg alone got twice the number of media mentions as all of us climate contrarians combined ….

Gotta say, every time I look at this heap of steaming bovine waste products it gets worse … but hopefully, this will be the last time I have to look at how this particular sausage was made.



July 2019 Was Not the Warmest on Record

Reblogged from Dr Roy

August 2nd, 2019 by Roy W. Spencer, Ph. D.

July 2019 was probably the 4th warmest of the last 41 years. Global “reanalysis” datasets need to start being used for monitoring of global surface temperatures.

[NOTE: It turns out that the WMO, which announced July 2019 as a near-record, relies upon the ERA5 reanalysis which apparently departs substantially from the CFSv2 reanalysis, making my proposed reliance on only reanalysis data for surface temperature monitoring also subject to considerable uncertainty].

We are now seeing news reports (e.g. CNN, BBC, Reuters) that July 2019 was the hottest month on record for global average surface air temperatures.

One would think that the very best data would be used to make this assessment. After all, it comes from official government sources (such as NOAA, and the World Meteorological Organization [WMO]).

But current official pronouncements of global temperature records come from a fairly limited and error-prone array of thermometers which were never intended to measure global temperature trends. The global surface thermometer network has three major problems when it comes to getting global-average temperatures:

(1) The urban heat island (UHI) effect has caused a gradual warming of most land thermometer sites due to encroachment of buildings, parking lots, air conditioning units, vehicles, etc. These effects are localized, not indicative of most of the global land surface (which remains most rural), and not caused by increasing carbon dioxide in the atmosphere. Because UHI warming “looks like” global warming, it is difficult to remove from the data. In fact, NOAA’s efforts to make UHI-contaminated data look like rural data seems to have had the opposite effect. The best strategy would be to simply use only the best (most rural) sited thermometers. This is currently not done.

(2) Ocean temperatures are notoriously uncertain due to changing temperature measurement technologies (canvas buckets thrown overboard to get a sea surface temperature sample long ago, ship engine water intake temperatures more recently, buoys, satellite measurements only since about 1983, etc.)

(3) Both land and ocean temperatures are notoriously incomplete geographically. How does one estimate temperatures in a 1 million square mile area where no measurements exist?

There’s a better way.

A more complete picture: Global Reanalysis datasets

(If you want to ignore my explanation of why reanalysis estimates of monthly global temperatures should be trusted over official government pronouncements, skip to the next section.)

Various weather forecast centers around the world have experts who take a wide variety of data from many sources and figure out which ones have information about the weather and which ones don’t.

But, how can they know the difference? Because good data produce good weather forecasts; bad data don’t.

The data sources include surface thermometers, buoys, and ships (as do the “official” global temperature calculations), but they also add in weather balloons, commercial aircraft data, and a wide variety of satellite data sources.

Why would one use non-surface data to get better surface temperature measurements? Since surface weather affects weather conditions higher in the atmosphere (and vice versa), one can get a better estimate of global average surface temperature if you have satellite measurements of upper air temperatures on a global basis and in regions where no surface data exist. Knowing whether there is a warm or cold airmass there from satellite data is better than knowing nothing at all.

Furthermore, weather systems move. And this is the beauty of reanalysis datasets: Because all of the various data sources have been thoroughly researched to see what mixture of them provide the best weather forecasts
(including adjustments for possible instrumental biases and drifts over time), we know that the physical consistency of the various data inputs was also optimized.

Part of this process is making forecasts to get “data” where no data exists. Because weather systems continuously move around the world, the equations of motion, thermodynamics, and moisture can be used to estimate temperatures where no data exists by doing a “physics extrapolation” using data observed on one day in one area, then watching how those atmospheric characteristics are carried into an area with no data on the next day. This is how we knew there were going to be some exceeding hot days in France recently: a hot Saharan air layer was forecast to move from the Sahara desert into western Europe.

This kind of physics-based extrapolation (which is what weather forecasting is) is much more realistic than (for example) using land surface temperatures in July around the Arctic Ocean to simply guess temperatures out over the cold ocean water and ice where summer temperatures seldom rise much above freezing. This is actually one of the questionable techniques used (by NASA GISS) to get temperature estimates where no data exists.

If you think the reanalysis technique sounds suspect, once again I point out it is used for your daily weather forecast. We like to make fun of how poor some weather forecasts can be, but the objective evidence is that forecasts out 2-3 days are pretty accurate, and continue to improve over time.

The Reanalysis picture for July 2019

The only reanalysis data I am aware of that is available in near real time to the public is from, and comes from NOAA’s Climate Forecast System Version 2 (CFSv2).

The plot of surface temperature departures from the 1981-2010 mean for July 2019 shows a global average warmth of just over 0.3 C (0.5 deg. F) above normal:


Note from that figure how distorted the news reporting was concerning the temporary hot spells in France, which the media reports said contributed to global-average warmth. Yes, it was unusually warm in France in July. But look at the cold in Eastern Europe and western Russia. Where was the reporting on that? How about the fact that the U.S. was, on average, below normal?

The CFSv2 reanalysis dataset goes back to only 1979, and from it we find that July 2019 was actually cooler than three other Julys: 2016, 2002, and 2017, and so was 4th warmest in 41 years. And being only 0.5 deg. F above average is not terribly alarming.

Our UAH lower tropospheric temperature measurements had July 2019 as the third warmest, behind 1998 and 2016, at +0.38 C above normal.

Why don’t the people who track global temperatures use the reanalysis datasets?

The main limitation with the reanalysis datasets is that most only go back to 1979, and I believe at least one goes back to the 1950s. Since people who monitor global temperature trends want data as far back as possible (at least 1900 or before) they can legitimately say they want to construct their own datasets from the longest record of data: from surface thermometers.

But most warming has (arguably) occurred in the last 50 years, and if one is trying to tie global temperature to greenhouse gas emissions, the period since 1979 (the last 40+ years) seems sufficient since that is the period with the greatest greenhouse gas emissions and so when the most warming should be observed.

So, I suggest that the global reanalysis datasets be used to give a more accurate estimate of changes in global temperature for the purposes of monitoring warming trends over the last 40 years, and going forward in time. They are clearly the most physically-based datasets, having been optimized to produce the best weather forecasts, and are less prone to ad hoc fiddling with adjustments to get what the dataset provider thinks should be the answer, rather than letting the physics of the atmosphere decide.

10 fallacies about Arctic sea ice & polar bear survival: teachers & parents take note


Summer sea ice loss is finally ramping up: first year is disappearing, as it has done every year since ice came to the Arctic millions of years ago. But critical misconceptions, fallacies, and disinformation abound regarding Arctic sea ice and polar bear survival. Ahead of Arctic Sea Ice Day (15 July), here are 10 fallacies that teachers and parents especially need to know about.

Polar_Bear_Summer_2 FINAL (2)

The cartoon above was done by Josh: you can drop off the price of a beer (or more) for his efforts here.

As always, please contact me if you would like to examine any of the references included in this post. These references are what make my efforts different from the activist organization Polar Bears International. PBI virtually never provide references within the content it provides, including material it presents as ‘educational’. Links to previous posts of mine that provide expanded explanations, images, and…

View original post 3,839 more words

Leftist Agenda and Climate Change Linked by Indoctrination Tactics

PA Pundits - International

Why is the same age group that helped to tear down the Iron Curtain now advocating for policies that would reduce freedoms? ~

Joe Bastardi ~    

As a meteorologist in the private sector, wherein success is largely determined by forecasting skill, I cannot afford to be wrong. I was taught that studying the past helps one predict the future. This is the origin of my involvement in the climate debate, since the “worst ever” bloviating we see today can easily be challenged through examination of the past.

My politics are simple. I believe one should have as much freedom as possible to enjoy life, liberty, and pursue happiness. In my opinion, the role of government is to establish standards to maximize these freedoms. I assume no one has anything against life, liberty, and the pursuit of happiness. I also assume there is a large population of young people…

View original post 677 more words

Himalayan Glaciers–The Story The BBC Refuse To Tell You


By Paul Homewood


Images from Cold War spy satellites have revealed the dramatic extent of ice loss in the Himalayan glaciers.

Scientists compared photographs taken by a US reconnaissance programme with recent spacecraft observations and found that melting in the region has doubled over the last 40 years.

The study shows that since 2000, glaciers heights have been shrinking by an average of 0.5m per year.

The researchers say that climate change is the main cause.

“From this study, we really see the clearest picture yet of how Himalayan glaciers have changed,” Joshua Maurer, from Columbia University’s Lamont-Doherty Earth Observatory in New York, told BBC News.

As usual the BBC fail to explain the wider picture.

View original post 503 more words

Climate science’s ‘masking bias’ problem

Climate Etc.

by Judith Curry

How valid conclusions often lay hidden within research reports, masked by plausible but unjustified conclusions reached in those reports.  And how the IPCC institutionalizes such masking errors in climate science.

View original post 2,521 more words

Ice Melting In Greenland? That’s What It Does In Summer!


By Paul Homewood

h/t Joe Public

I’ve been away cycling in Norfolk for the last few days, even though it was apparently shut!

While away, this familiarly hysterical story appeared in the “Independent”:


An extraordinary photograph of huskies pulling sleds through ankle-deep meltwaters on top of an ice sheet in Greenland has brought attention to the uncharacteristically warm temperatures affecting the Arctic.

Danish climatologist Steffen M Olsen took the picture on 13 June while on a routine mission through the Inglefield Gulf in northwest Greenland.

The rapidly melting ice caused difficult and dangerous conditions for the team of climatologists who were retrieving weather station equipment from the area.

The thin layer of water was standing on top of an ice sheet around 1.2 metres deep, Dr Olsen said on Twitter.

“We know the ice is around 1.2m thick and that we have about 870m [of] water below us…

View original post 540 more words

Activists who use polar bears as a symbol of climate change are out of touch with reality


Young activists like Ollie Nancarrow from the UK need to find another symbol for their messages of climate change. Polar bears are thriving despite recent dramatic declines in summer sea ice: they have not been devastated as predicted by declining summer sea ice blamed on climate change. Anyone who uses a polar bear image to further a message of climate change, as Ollie has done, is simply out of touch with reality.

Standing bear_shutterstock_751891378_cropped web sizedHere are the facts, references provided.

In September 2007, Arctic sea ice hit a low never before seen since 1979 and panic set in about the future of polar bears. Biologists from the US Geological Survey had just insisted that when sea ice declined 42% below 1979 levels, which was expected at mid-century, 2/3 of the world’s polar bears would be gone (Amstrup et al. 2007; USGS 2007) – a drop from about 24,500 to only 8,100.

View original post 749 more words

Al Gore Serial Science Denier

Science Matters

Everett Piper writes in the Washington Post Times The party of science deniers. Excerpts In italics with my bolds.

This past Wednesday, May 29, former Vice President Al Gore spoke to the graduating seniors at Harvard University. A summary of his talk? There is an “assault on science” that threatens “the capacity of the human species to endure” on planet Earth.

Mr. Gore proceeded to warn both students and faculty at Wednesday’s annual Class Day convocation, stressing that “reason” and “rational debate” were under threat from what he called “ideology of authoritarianism” by those who disagree with him and his political agenda.

Science “is now being slandered as a conspiracy based on a hoax,” Mr. Gore said. “The subordination of the best scientific evidence is yet another strategy for controlling policy by distorting and suppressing the best available information.”

This is the man who told us in 2006 that…

View original post 667 more words