We’ve been busy.
As the proprietor of “World’s Most Viewed Climate Related Website,” I have a mandate to keep that title. Today, two new permanent additions to the WUWT set of resources are now online. Both are unique, and both are exclusive, both are factually based. Even better, both will irritate climate alarmists.
#1 Earth’s Real-Time Temperature
The first is a really simple widget added to the right sidebar, seen below:
Whaaaat! you say? Real-Time Earth’s temperature – impossible! Only certified climate scientists can do that. Well, um….no. We can do it, and we did. Working with a friend of ours who runs a website https://temperature.global/ (who shall remain nameless) and our resident tech wizard, Eric Worrall, we have made use of their API (specially modified at my request) to display the real-time temperature of the Earth. Data has been recorded back to 2015, as you can see in the graph below. It will continue going forward.
How does it work? It is pretty simple really. Thanks to the Internet, all sorts of global temperature data in near real-time (hourly) is available.
Data sources – click links for details:
- NOAA global METARs 2015-current
- NDBC global buoy reports 2015-current
- MADIS Mesonet Data, NOAA OMOs
All that data is gathered hourly, put into a gridded average, computed and displayed. It is compared to the “normal” baseline temperature of 57.2°F.
In this calculation, the “normal” temperature of the Earth is assumed to be 57.2°F, and that is simply compared to temperature reported by all of the stations to obtain the absolute temperature deviation from “normal” at that moment.
The basis of this number comes from NASA GISS itself, from their FAQ page as seen in August 2016 as captured by the Wayback Machine.
Of course, they’ve removed it now, because well, they don’t want people like me doing this stuff. Only certified climate scientists can do that stuff. /sarc.
#2 Failed Predictions Timeline
We wanted a “one stop shop” that would display all of the bogus predictions (and outcomes) about climate, energy and the human condition all in one easy to use package.
This has been a work in progress over several months between myself, Charles Rotter, and Eric Worrall. At least two previous versions have been thrown out and redone (thank you Eric for your patience). We think we’ve got it right.
See it here: https://wattsupwiththat.com/failed-prediction-timeline/
Screencap below.
Note the search features. You can choose topic, person who made the prediction, and year to filter by. Once you do that, it will give you the result.
Most importantly, each entry comes with an “outcome” section. See below for an example.
Try it out, https://wattsupwiththat.com/failed-prediction-timeline/ and please be sure to let us know in comments what you think, and if we missed anything.
Mr. Watts,
On April 9, I mailed the following note, along with the subject article, to you at 3008 Cohassett Rd, Chico CA:
“The subject of failed climate predictions frequently comes up, with comments citing maybe two or three examples. The Epoch Times has just posted a list of about forty (devoting 3 full pages, plus a short article on their front page). I thought you might enjoy reading their review.”
The postal service just returned my mailing with the notation “insufficient address.” I’m not sure why it takes them 2 weeks to decide they can’t deliver a letter. But I still think you would find the article interesting if you can provide an appropriate address.
Suggest adding a category, with magnitudes for every climate action that shows the modeled reduction in world temperature and cost (all in) to achieve.
Category Temperature Effect (+/-) Cost …with footnotes on sources, etc
Electric Vehicles (USA, passenger only), CO2 reduction (model), World Temperature Reduction (modeled), Cost $ .
EV batteries: worldwide (China, etc)
Grid batteries:
eg CO2 credits( buy, sell), rebates(taxpayer),…
eg efficiency mandates:
refrigerators, LEDs, water heaters, heat pumps, insulation…..
Wind/Solar generation( with full make-up generation running and standby to provide 24/7 reliability, availability (local),
ETC….
Outstanding effort, but I have some constructive criticisms of the “Failed Prediction Timeline.” I hope you will take them seriously.
I will continue with criticisms as I go through. Again, these are intended in a constructive way. I think your compilation is utterly magnificent, and want only for it to be more useful.
Oops. The Ehrlich article from the Redmond Daily Facts appears twice on p. 3, not p. 2. My mistake.
The Washington Post article “U.S. Scientist Sees New Ice Age Coming,” appears on p. 1 and p. 10.
An article from Salon appears on p. 9 and p. 10
An article about people having to wear gask masks appears on p. 1 and p. 10
An article about the river fish dying appears on p. 1 and p. 10
An article titled “The Cooling” appears on p. 2 and p. 10
An article titled, “Prepare for long, hot summers” appears on p. 3 and p. 8
An article from the Guardian about giving up meat appears on p. 5 and p. 11
An article about the threat to the Maldives appears on p. 3, p. 4, and p. 9
An article from the Time magazine archives appears on p. 2 and p. 10
Letter from Brown University appears on p. 2 and p. 11.
I think there might be more repetitions, but my eyes were getting tired.
I want to recommend “Failed Prediction Timeline” on social media, but it’s kind of a mess. Some copy editing mistakes, deficient linking, and LOTS of repetition. These problems are easily fixed. I hope you will do so. No sense in going to all the trouble only to have a few easily repaired “gotchas” make it unshareable.
Excellent info for use debating the warmistas. I would like to see one other chart to challenge the warmistas with. How about adding the chart of the paleontology record of temperature vs CO2 over the millennia. That is a powerful picture with which to challenge their favorite trope that it has never been so warm and it is the fault of CO2.
Story Tip: Create an Opportunity Cost of the Green Economy
1) The benefits are hugely speculative and highly destructive to the environment. Nothing has changed in the trend of CO2
2) The costs are real and undeniable
3) $5 Trillion or 20% of GDP can build a huge number of roads, bridges, hospitals, cancer research, etc etc.
Put the cost of fighting climate change in terms the people can undersand
The Great Energy Deception: The Truth Behind the $5 Trillion Renewable Energy Scam
https://internationalman.com/articles/the-great-energy-deception-the-truth-behind-the-5-trillion-renewable-energy-scam/
So what you say about temperature.global is not correct. It does not give you a real-time global temperature, and it is not a gridded average. It is a running annual mean updated every hour or so, and the mean is a simple average of station readings with no grid, Tony Heller style. It claims to use a 30-year baseline, but it doesn’t have 30 years of data, so it uses an estimate from NASA instead.
I had some correspondence with the person who runs the site, who goes by TG, and he confirmed what I’m saying here. I summarized what I was able to find out from him and a bit of my own analysis here.
https://woodromances.blogspot.com/2022/02/the-marketing-of-alt-data-at.html
TG explained to me, “The[sic] is no gridding or weighing of data…. There are many organizations that already so[sic] this, like NOAA and NASA. Our project just takes the statistical mean of all available surface data. The intention is to get a different look of[sic] the data without manipulating it at all.”
TG also explained to me, “The data functions are algorithms that create the global mean. It calls the database for the last 12M of data. Some data functions also serve as an API for users to embed the data on their own webpages.” TG will only report a 12-month running average. The reason why is clear if you look closely at the data.
I asked for the actual data instead of annual means, and TG refused to give me that data. But using the data on the website and the information TG gave me, I was able to reconstruct what should be the monthly mean temperatures to produce the running 12 month averages that they report. See the graph of what should be their monthly values below. I describe the method I used to reconstruct this in the blogpost.
Do you really want to promote this on your blog? This is little better than a random number generator.
This is just a different assessment. If warming is global, i.e., not localized, then area weighting is meaningless. In other words, all stations should be showing warming regardless of where it is.
If warming IS NOT global, but localized, then climate science is causing global fear when it is not warranted!
Baselines should not affect the overall trend. A baseline will only cause the scaling factor to be different. You could even use a temperature of 0°C and only the values of the differences will change. The trend will not. The trend will just move up and down in relative values.
Climate wants to claim accuracy by using station baselines per month to arrive at an “accurate” change for each station. The true inaccuracy can be debated elsewhere, but by averaging all anomalies, local and regional information is destroyed. You can not evaluate where warming is occuring!
Don’t you find it funny that no climate scientist has ever posted a regional or local analysis of temperature? Several folks are staring to do this and can’t find the warming when looking station by station! Have you done that analysis?
It’s not just a different assessment. It’s complete incompetence, and what this blogpost said about it is objectively false. There’s no gridding here – it’s just a simple average of thermometers, and you’re not given real-time global temperatures. You’re given a 12-month running mean that is updated frequently.
The reason why they will not disclose their data or even their identities is because their method is completely wrong. You can tell because every year (according to TG), global temperatures change by 55 C every few months. There’s no way that can possibly be true, so TG covers this up by supplying only a 12-month running mean.
I didn’t say that their baseline affects the trend. Why would you think I said or implied that? What I said is that TG claims to compare their values to a 30 year baseline, but they don’t have a 30 year baseline. So that’s made up. Their 30 year baseline comes from NASA’s dataset, which means it’s arbitrary with respect to TG.
I don’t even find it truthful. Look at NASA’s website. They give you access to global, national, regional, and local temperature time series. And it’s not hard to find.
If you believe NASA’s data, that is on you. A NOAA scientist just validated UAH. Makes you wonder about the other databases doesn’t it.
Here is what I’m learning. Most the data bases trumpet their “accuracy” based on an SEM computation. Yet their calculation of it is hosed. They do not publish an experimental uncertainty based on the data because it is much higher.
My investigations are finding locations with little warming. I have yet to find locations with sufficient significant warming to justify the warming being trumpeted. Maybe you can post some since climate science seems to ignore such.
Whatever your feelings about NASA’s data, the temperature.global website is a glorified random number generator. It doesn’t tell you anything meaningful about global temperatures.
They are all hosed. UAH comes closest. Look at this image. Why do you think no one states experimental uncertainty as determined by the actual data. Practically all the anomalies lie within the experimental uncertainty. This is just one site. There are many more.
You may not like the running average but it is one way to look at the data. Ask yourself why it does what it does. Here is my look, if CO2 is well mixed then everywhere should experience the same growth. Why doesn’t this graph show it?
It shouldn’t matter if one “grid” has 20 stations and the next one has none, they should all be increasing, right?
Your graph is too small to read, nor have you supplied enough information about it for me to replicate it. The CIs for GMST datasets are published in the literature, and sometimes they are printed on the graphs. In recent decades, the 95% CIs are about 0.05 C for most GMST datasets, gradually increasing to about 0.15 C in the late 19th century.
That of course is not an argument for using the random number generator called temperature.global. The post here says that this dataset is gridded, but it is not. It does not even post real time temperatures. It posts a 12 month running average that gets updated frequently. And the reason is clear. Their monthly data varies by as much as 50 C over the course of a year, which stupid.
This is wrong:
No, that’s objectively false. Different parts of the globe receive different amounts of energy from the Sun, and thermal properties of land and water differ, such that land warms faster than the oceans. Warming affects albedo in the Arctic, as sea ice decreases, so warming in the Arctic is more rapid than elsewhere. And we have this thing call wind that blow air around distributing warmer area to different parts of the globe. We have ENSO that changes the rates at which heat that escapes the ocean, etc.
Tell you what, here is a link for some Japanese locations that show no warming.
Now to get 1.5C of warming, find a site that has 3.0C of warming over the same time frame. I can get more sites later.
Tokyo’s Coolest September In Over 30 Years…Hachijojima No Warming In 107 Years…Latest Forecast: Sharp La Niña! – Watts Up With That?
You are just making your task more complicated. If not all parts of the earth receive the same amount of insolation (and I do agree with that), then you should have no problem plenty of sites that can offset locations with little or no warming. If you can’t find sites with 3 and 4 degrees of warming you might want to ask yourself what these trends are doing.