According to the media and climate alarmists, winters like we used to have in the global cooling days of the a970s were supposed to be disappearing due to increasing warming from rising CO2.
But that hasn’t really been happening. For example, Stefan Kämpfe at the European Institute for Climate and Energy (EIKE) plotted Germany’s mean January temperature going back to 1988:
Chart: Stefan Kämpfe, English headings added by NTZ.
The data source for the above chart is the DWD German national weather services, and the NOAA for Co2.
Obviously January mean temperatures in Germany have been falling for quite some time now, thus contradicting the often heard claims of warming.
22 responses to “Germany January Mean Temperatures Falling Since 1988, Contradicting Claims Of Warming”
Actually, I wouldn’t agree with the contention that the temperatures are falling – as the linear regression has produced a slope that is way too trivial to matter. The standard deviations are obviously huge, much bigger than what a linear regression “finds” for a slope. (Linear regression is an overused method because it’s so easy, but that also makes it easy to find “trends” where none exist.)
Looking at the data, there is no trend either up or down. It’s basically doing absolutely nothing – the system is statistically stable with just statistical noise around the statistical mean.
That last paragraph applies to basically all temperature data over the past c. 140 years (when data collection really started in earnest) anywhere in the world. No underlying trend, all variations over time readily explained by statistical noise.
Mr. Gosselin’s big point remains valid. NO warming since 1988, despite rising CO2.
I agree with your conclusion, and it is mine as well. I disagree with doing a linear regression to noisy data like that, since variability is clearly caused by statistical noise with no underlying trend. The easy ability to do linear regressions has made it easy to generate a “trend” which isn’t in fact there.
If you want to do a good experiment, generate some “data” by sequentially rolling a pair of playing dice (30 or 35 times, to be like the data shown above) and treating those numbers as data with time with each roll being a time step. Then do a linear regression on that data – it will show a small rising or falling trend, even though the system has no trend.
We just need to accurate in our assessments and methods – because we can (the other side can’t, they have to play games).
Yes. I agree that while the data doesn’t show any clear cooling, it also shows no clear warming, which is more than sufficient to disprove warmists’ hysteria.
In fact, I would rather see it warm than cool, but at least stasis is an acceptable alternative to cooling.
[…] Germany January Mean Temperatures Falling Since 1988, Contradicting Claims Of Warming […]
Excellent choice of 1988 for the start point!
[…] von Meereis in Griechenland ein „einmaliges Phänomen“. Deutschland: Januartemperaturen mit negativem Trend seit […]
On the right side of the chart: “ 2022 estimate 2.8°C ”
What am I missing?
It’s the difference from end of 2017 to end of 2022.
Just to illustrate the difference from bottom to top in the curve.
Did it help Your understanding?
Hello, This article is genuinely nice and I have learned lot of things from it about blogging. thanks
Mr. Ph.D., obviously a professional nitpicker, misses all the important criticisms. Just nitpicking in his comment — Piled High and Deep.
Here are all the problems this post:
The world is facing doom and this talks only about one nation, Germany, and only about past Januaries. How about the other 11 months of the year?
Climate doom is coming in 10 to 20 years, and always has been.
Climate science is about THE FUTURE — only old fogies reminisce about the past climate.
There are no data for the future, so climate models require computer models.
Those computer models must provide scary predictions of climate doom in 10 to 20 years.
Most predictions have only one decimal place.
One decimal place is not real science.
One decimal place is for losers.
Real science requires three decimal places.
No one cares about the January temperature
in Germany in the past few decades.
SUMMARY OF REAL CLIMATE SCIENCE:
No data. Can’t trust data.
Climate model predictions of climate doom.
Global average temperature predictions to three decimal places.
Claims that the current predictions are worse than we thought.
Or even worse than worse than we thought.
Shouting and arm waving are mandatory if presentation is on video.
Richard, there’s no need to indulge in childish insults.
It’s not nitpicking. As I said above, the ability to do linear regressions has become so easy that it makes it possible to find phantom “trends” that do not in fact exist. That’s very important to understand, particularly with systems like the climate system.
It’s a shame that practically everyone knows how to do linear regressions these days, but knowledge of how to do statistical analysis of a sequentially-sampled system (while very easy to understand and to do) is lacking.
Proper statistical analysis absolutely destroys the warmest argument; would be nice to see more of it.
You completely missed the point of my comment
Mr. Piled High and Deep.
We are most interested in the future climate,
which we do not have the ability to predict.
We do have 110 years of global average temperature
statistics, of varying quality, that show
four different CO2 vs. global average temperature
1910 to 1940 global warming with little CO2 increase
1940 to 1975 global cooling with moderate CO2 increase
1975 to 2003 global warming with relatively fast CO2 increase.
200- to mid-2015 flat trend with relatively fast CO2 increase.
Mid 2015 through 2020 global warming with relatively fast CO2 increase.
Extrapolating each of these trends
would have failed to predict the next trend.
The actual climate change in the past has
NOT predicted the climate change
in the future, during those 110 years.
We have some measurements of the past climate,
with lower data quality as we go back in time.
So what possible purpose does it serve
to look at one nation, only for one month
of the year, and only 35 years of the
available national data,
that are presented here?
Then declaring a linear trend
for the non-linear cherry picked
national temperature data.
THIS ARTICLE IS DATA MINING
AND SERVES NO PURPOSE
FOR CLIMATE SCIENCE.
I tried to say that without
insulting the author too much,
by using satire in my first comment.
I compared the article with the
also worthless usual (always wrong)
wild guesses of the future climate.
You appear to lack common sense,
that does not come with a Ph.D.
This data mining article
serves no purpose.
That was my key point.
A nearly flat
national weather trend
in one month of the year,
over 35 years,in on country,
may not even be of much interest
to people who live in Germany.
Your claim that
‘Proper statistical analysis
absolutely destroys the warmest argument”
makes absolutely no sense.
You don’t seem to get
what the warmist argument is.
Their argument is that future global warming
will be rapid and dangerous, completely unlike
past climate change in the age
of fossil fuel CO2 emissions.
Just predictions, not reality.
Wrong predictions for the past 65 years,
although at least stated with uncertainty
65 years ago — uncertainty seems
to have disappeared in the 1980s.
Now hear this (and get mad
at me again, I can take it):
Statistical analyses requires data.
There are no data for the future climate.
You can not perform statistical analyses on
data free climate predictions.
The predictions consist of assumption
based on unproven theories and speculation.
“Climate astrology” would be a better definition,
considering the poor track record of predictions
of environmental doom in the past 65 years
(100% wrong predictions of doom)
You can’t destroy predictions with
“Proper statistical analysis”.
You can point out how wrong
the climate predictions have been
for the past 65 years, but even that
sorry track record can’t prove
today’s climate predictions
are wrong too.
That’s the magic
of scary predictions.
There are no data to analyze
the current predictions.
It will take decades to collect data
that show today’s predictions were wrong.
We have such data since the climate doom
predictions began with oceanographer
Roger Revelle in 1957, but few people care.
They have been brainwashed to believe
government bureaucrat “experts” with
science degrees. And never mind always
wrong past predictions of doom.
I’m with “Mr. PhD” on this. Real science demands critical thinking, as much w/r to over interpretation of data as with anything else. What he wrote about was the first thing that came to my mind when I saw the graph. If it had allegedly showed just as much “warming” as it appears “cooling”, I’d have had the same objection.
I’m not sure what your complaining about. One thing the article addresses is the warmists’ claims that…
“…winters like we used to have in the global cooling days of the 1970s were supposed to be disappearing…”
How else is an article about disappearing winters supposed to address that claim but to present data from past to present winters (Januaries). And Germany is selected, presumably because that’s where the readership is located. It’s often best to refute a claim by contrasting readers’ experience with assertions not supported by that experience.
Also, many of your other points, while potentially interesting, don’t seem to be articulated clearly enough for me to follow.
I think you’re being the nit picker here.
That makes YOU wrong too.
My first comment was satire.
In general the six coldest months of the year have warmer nights, since 1975, in the Northern half of the Northern Hemisphere.
January is not the entire six coldest months of the year.
35 years is not the entire 47 years of global warming since 1975
Germany represents a tiny percentage of the total land global surface area, and does not represent any of the 70% that are oceans.
THIS ARTICLE IS MEANINGLESS DATA MINING.
That’s not nitpicking.
That’s a fact.
“That’s not nitpicking.” – RG
Yeah, it is.
Of course, if you want to be less strident and clearer, as well as provide links to back up you assertions, that might help make your arguments more persuasive.
[…] “Germany January Mean Temperatures Falling Since 1988, Contradicting Claims Of Warming” – More off-message data from Pierre Gosselin in the No Tricks Zone. […]
Plase extend the data beyond 1988. Why 1988? Surely, there must be data going back a century?
And why only Januaries?
And why only Germany?
I answered your “why Germany,” on 2 Feb, above.
As to “why January,” in addition what I wrote above, it’s also usually the coldest month of the year in the northern hemisphere. If the world is warming faster than ever lately, that should be where you would expect to see it, in a warming of the coolest month.
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