How can temperatures get cooler during global warming ?

When speaking of climate change, is often brought up the subject of the planet’s warming and the rise of global temperatures. However, some years are colder than others and global temperatures don’t go up regularly year by year.
To avoid confusions and misunderstanding, the term “global warming” has been switched to “climate change”. Indeed, for several reasons “climate change” does not necessarily and only mean fast rising temperatures all over the planet. One explanation to this is the existence of the natural climate phenomenon El Niño and La Niña.

What are these phenomena ?

El Niño and La Niña refer to opposite phases of the ENSO (El Niño-Southern Oscillation) cycle. They have large-scale impact on the weather and climate all over the globe.

Australian Government – Bureau of Meteorology : Pacific Ocean (1)

El Niño can be described as the periodic warming phase of sea surface temperatures across the central and east-central Equatorial Pacific.
It comes with high air surface pressure in the tropical western Pacific. 
El Niño generally brings milder weather to Northern U.S. areas and to western and central Canada. Wetter conditions are also expected in the South of North America. This warm phase also affects Australia and southeast Asia with drier conditions, and Pacific coastal South America with wetter conditions. 

On the contrary, La Niña refers to the cooling phase of the ENSO cycle, accompanied by low air surface pressure, and results in below-average sea surface temperatures across the east-central Equatorial Pacific.
This phase tends to have the opposite effects of the El Niño phase. 
Indeed, winter temperatures are generally warmer than average in the Southeast and cooler in the Northwest of the United States. Rainstorms and warm waters are driven towards the western equatorial Pacific over Indonesia.

These two periods last typically 9 to 12 months each and normally occur every 3 to 7 years. (2) It is also important to note that El Niño occurs more frequently than La Niña. (3)

Global Annual Temperature Anomalies showing El Niño and La Niña years, by the NOOA. (4)

A little history
El Niño means “The Little Boy” in Spanish. The original name, “El Niño de Navidad” in reference to the newborn christ, traces its origin centuries back to Peruvian fishermen. These used the term to describe the appearance of a warm ocean current off the South American coast around Christmas.
La Niña, chosen as the « opposite » of El Niño, refers to « The Little Girl ». (1)

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References (1) (2) (3) (4)ño–Southern_Oscillation

Is it dangerous or is it risky ?

These two terms are very important by their meaning but are too often confused. But if you want to keep a clear speech, you must know the difference. It’s pretty simple !

Danger :

The existence of a potential threat, harm or death.

Examples :
– Climbing a ladder is dangerous, because you could fall and harm yourself.
– Traveling by plane is dangerous, because you could die.
– Not being vaccinated is dangerous, because you could die and kill other people.

Risk :

The probability for a danger to happen.

Examples :
– It’s unlikely for you to fall from this ladder, it’s less likely to harm you and even less likely to kill you. So it’s not THAT risky, but hey, be careful anyway. 😉
– Traveling by plane is actually the safest way to travel, so it’s very very VERY unlikely for you to die because of it, but it might happen. So it’s not risky to take the plane (even though the risk is still real).
– Not being vaccinated is very risky because you could put yourself and others in real trouble very quickly depending on environmental factors (are the others vaccinated ? Is there any disease around that can contaminate you ? Will it kill you ? Put you in unbearable pain ? How old are you ? How vulnerable are you ? etc.).

Conclusion :

You can measure the probability of something bad to happen by using the risk and anytime you risk something is because of a potential danger.

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Consensus : how does science work ?

What does “consensus” mean ?

First things first, a consensus is “a generally accepted opinion or decision among a group of people” (1)

In the case of science, a consensus is made inside the “scientific sphere” and the general public can’t and won’t have a word to say about it.

Why ? Let us explain.

Elitism ?

The objective behind that “rule” isn’t to exclude the public from science debates or from any science related stuff at all.

The only objective is to find a conclusion about a subject that follows a very strict protocol called the “scientific method“.

Obviously, citizens are totally able to understand and to follow such a protocol but it’s very unlikely they can both have the expertise in a specific subject and the ability to follow very strict rules to stay as objective as possible if they’re not a scientist themselves.

What is so problematic ?

General public is very unaware of how science actually works. The main problem is that any “consensus” is taken as an opinion but it’s actually quite the opposite. A consensus is made by looking at a LOT of studies and their conclusions to be able to determine a potential final answer to a specific subject. This makes it a VERY objective conclusion, not an opinion.

For example : climate change.

The actual consensus on climate change is that it’s happening and it’s mainly caused by humanity.

This statement is NOT an opinion and is NOT subject to any debate outside of the scientific sphere.
Scientists agreed on this idea at a rate of around 90% and up to 98% since many years. (2)

Does that mean that it’s the very truth and that the scientific consensus will never change on this question ?
Absolutely not. It just means that with all the information we gathered to this day, we are not able to determine a potential other cause for the climate change.

But a consensus does not mean unanimity !

That’s totally right, actually, this is an other problem. Some people will use it as an argument and will try to convince you that some scientists will disagree with the actual consensus and it’s a proof that science is wrong.

First, this is very wrong to accept the opinion of a few scientists among a very very large majority of their pairs JUST BECAUSE they seem to agree with your opinion.

Most of the time, scientists who won’t agree with a consensus are NOT experts in the domain of the said consensus (for example a scientist that is not a climate expert doesn’t have the same impact as an expert on the “Human made” climate change consensus).

But some of them will be experts.
And this is where we enter an important part. It is essential for science to have people that will keep pushing to prove that the actual consensus is wrong as long as we still have things that don’t fit in the actual theory.

But these people are NOT saying that the consensus is false and are NOT a proof that the actual consensus isn’t serious, objective and scientific.

But in history, consensuses have already changed multiple time !

Absolutely, as we said before, a consensus is made with the materials we have gathered to this day. It means that it could potentially change. But for that, we don’t need only to find that one data is inexplicable or is against the actual consensus. Nope, you’ll need a LOT of data to start a scientific consensus shift.

A problem between a single data and the theory can have multiple causes and most of the time it’s caused by the way data has been gathered.

But it may occur that a data and the main theory don’t fit together for real. Does it mean the theory has to be thrown to junk ? Absolutely not. A theory isn’t perfect and can be completed by further discoveries !

But the final answer is : unless you’re a scientist, just believe the actual consensus and refer yourself to it. Understand why it’s believed to be the best theory and maybe even be curious about what doesn’t fit in the theory yet. Being skeptical is a very good thing, being curious too. But don’t fall into conspiracy theories. You can doubt a research’s results, you can doubt a few researches’ results, but you can’t doubt several thousands of studies made all around the world, by a ton of different people with a lot of different interests, that come to the exact same conclusions.

Trust the consensus. Don’t fall for Bullshit Science.

You can also check “To go further” at the end of our article, you may find very interesting material.

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References : (1) (2)

To go further :

List of scientists who disagree with the scientific consensus on global warming :

Scientific consensus on Wikipedia with a lot of sources, a MUST READ :

What’s a scientific theory ? :

Appeal to nature

“If it’s natural/organic, it’s good. If it’s chemical/synthetic, it’s bad”

You already heard that.

Let’s do this very quickly.

“If it’s natural/organic, it’s good” : In this sentence, we can define good as an ethnocentrism, so we will accept it as “good for survival or comfort of any human kind” and we can also define “natural/organic” as “anything that is untouched from Humanity”

With these two definitions, we can easily counter this argument : diseases are natural. It’s not good for you.

“If it’s chemical/synthetic, it’s bad” : “Chemical/synthetic”, in this sentence, is referenced as the opposite of “natural”.
Firstly, it’s highly probable that nothing remains untouched by Humanity. (1)
Secondly, both synthetic and natural chemicals can be bad or good.
Thirdly, most of the time, a synthetic chemical is exactly the same as a natural chemical (2)

It’s a very common sophism, that you can now avoid and counter.

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References – by DirtyBiology [Léo Grasset] (1) – by Dorea Reeser (2)

To go further :

Correlation or causality ?

Definitions :

Correlation :
Statistical tool used to measure the strength of a relationship between two (or more) variables.

A correlation can be :
– a coincidence.
Example : antibiotic consumption rate in United States correlated with violence in Bulgaria.

– caused by an other variable :
Examples :
– A and B are both affected by C.
– excellent grades in High school (A) and excellent grades in University (B) are both affected by continuously hard working (C).

– a negative correlation :
Example :
– when A increases then B decreases.

– a positive correlation :
Example :
– when A increases then B increases.

Causality :
Relation between a cause and it’s effect.
Examples :
– A causes B.
– On Earth, dropping an object (A) causes it to fall (B).

Sophism :

We often say “correlation doesn’t imply causality“, which means that most of correlations won’t be a cause-effect matter, and so, won’t imply a causality.
Cum hoc ergo propter hoc is very common sophism in which a correlation is mistook as a causality, this leads to huge mistakes in thinking and establishing conclusion.
It can be also used as a manipulation, “correlation” or “causality” have to be used very carefully.
A correlation is only a statistical tool and is not useful as an argument, but, it’s always very interesting to study its possible causal link as it could lead to an interesting finding, and then, to an interesting argument.

Note : A causality WILL imply a correlation, in any case.

More : Find on this website funny correlations that will show you how a correlation differs from any cause-effect relation, such as : “US spending on science, space and technology” correlates with “suicide by hanging, strangulation and suffocation”
It also shows how easily graphics can be manipulated to make you believe that two things that have NOTHING in common can be related.

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