Please be aware that nobody claims to predict the weather years in advance. Climate and weather are related but distinct concepts.
Consider a grossly simplified analogy: if you have a good random number generator, you can not predict what any single output may be, although you can learn trends like the maximum and minimum range it operates within, and you can observe the average result.
If you modify the code by adding what for the sake of similar terms I will call a “forcing factor,” which multiplies the random number by a non-random number, the effect is predictable even though specific numbers still are not. The minimum, maximum, and average will all be affected proportionate to that forcing factor.
When talking about climate research, the forcing factor is not easy to determine, but it does relate to several fairly well known physical effects that we can attempt to quantify. There is uncertainty, so the research concludes there is range of possible results, not a single fixed prediction, but the overall range indicates positive, non-zero forcing.
The end of life as we know it is actually is not a predicted effect for what you’re getting at, although politicians often make such a claim, and journalists sometimes do.
The distinction between what scientists predict and what others say is a source of sometimes serious trouble for researchers. A meteorologist in my area recently had his job threatened, partially as a result. One of his colleagues was previously kicked off a state government advisory board after proceeding to publish research showing one of the board’s talking points was over-stated. Note, in both these cases, the researchers concurred with others about the reality of the effect they were discussing, but the magnitude was different between their data showed and what others expected.
I think it would be more accurate to say it is not a flaw because accepting something true or not is not what science does.
Science is the method. Accepting something as true or not is an individual decision that can be guided by science as long as a way of applying science to the question can be identified.
I was basically making that point - except that I would say hypothesis testing is what the method does, and hypothesis testing does test whether a hypothesis is true or not true under the test conditions.
The old “weatherman can’t predict …. how can climate scientists” question is pretty well answered in a number of sites. That search will find quite a few of them.
Strictly speaking, hypothesis testing does not accept claims as true. It either rejects claims or fails to reject them.
That’s “true” in the mathematical sense, which means true for all possible cases. The results of hypothesis tests and the scientific method will often be true for all practical intents and purposes in that the result is known with a high degree of confidence. But there is an important logical/philosophical distinction.
“Philosophy” being used as a not-quite-insult toward modern science is the perfect demonstration of so many people not understanding what epistemology is in a general sense, how important to our understanding of the world it is, and how it interacts (and is intertwined) with linguistics, sociology and psychology.
40 years ago scientists/experts were predicting large increases in human population. That turned out to be true. At that time they were predicted that we would run out of crude oil in about 20 or so years, as in 20 years ago. That turned out to be a very bad prediction. If that prediction had not been so wrong it’s possible that other scientists would have been predicting global warming long before they started to. It was clear to me that massive population growth would cause pollution of streams, rivers oceans and certainly air, and also consume large quantities of many of the Earth’s natural resources. I value science/scientists and believe that most scientists are working in good faith. I’m simply pointing out that some variables are always going to be wrong in predicting the future. Always. I’m not suggesting that they should stop trying because of that.
And? For some reason this is a surprise to those who don’t understand that knowledge is incremental and asymptotic. Or those who expect certainty.
More importantly, we need to be clear on what is meant by wrong, and have a sense of proportionality. Wrong in what way and by how much? A great saying is “”All models are wrong, but some are useful.“:https://en.wikipedia.org/wiki/All_models_are_wrong”
The only absolutely correct model for a dataset is the dataset itself, i.e. a model that has as many variables as data points in the dataset. But at that point why bother modeling? Trying to describe a tendency with fewer variables means some approximations are made. That’s not an “error”, it’s a practical strategy for making a problem tractable. It makes it possible to get a useful answer instead of no answer or a simple but useless answer. Incrementally improving a model could be seen as admitting that all previous models were “wrong”, but that’s misleading.
PV=nRT is wrong. F=ma is wrong. It does not detract from their usefulness.
“”I wasn’t trying to predict the future”:To prevent the future Bradbury told John Miller in a 2003 Wall Street Journal interview, “I was trying to prevent it.”
I think “if this goes on” was the key consideration that first Earth Day of 1970. A question basic to most science fiction.
And now? ” Almost half the songbirds”:| Nature of Things are gone. Who knew?
Clickbait/misleading title. Unfortunately no links to actual papers/models.
For the most part, the models “failed” for the best possible reason: people reacted and changed behavior: increasing agricultural output (GMOs!), banning certain pesticides and chemicals, regulating pollution, developing new techniques for exploiting resources previously not feasible, etc.
It would be best to see the actual papers, which almost surely have phrasing like “if the present rate of X continues… then Y”. Since the condition fortunately became false, it’s not that the predictions were wrong, they served their purpose!
The other example is just terrible:
That is not a prediction from science, but a personal opinion/bet!
This former science journalist does a good job of presenting what the science (papers) actually says, and clearing up misleading cr@p from clickbait articles, politicians, and “personalities” on all sides of debates:
If you read my post again, you’ll see that I didn’t assert that hypothesis testing accepts claims as true or not true. And I understand confidence intervals and probability, which are beyond the scope of the post I was addressing with my comments.
I can offer you my opinion on that. I have a PhD and worked in academic research for years. I participated on many research project, including medical/clinical research. My PhD is in technical field.
I dont know what people mean when they say “scientific community”. Wast majority of scientists are very narrowly specialised. We all have areas where we are considered “expersts” and unimginably more areas where our knowledge is either superficial or equal to common knowledge. If you ask my opinion on some geological or sociological phenomenon, you likely wont get better answer than if you asked random person.
Now if a comunity of specialists, for example molecular biologist agree on somenthing, it doesnt mean its true. Their idea of what it really is will very likely be much more probable than someones who is not specialist, but it will not necessarily be true.
But wait, there is more. It gets even more complicated when it gets beyond numbers and raw data. As soon as you make a theory, you will definately find other scientists who can have a different explaination that will make as much sense and maybe even more. Doesnt mean any of you is right. I never met a fellow scientist (specialist in my field) with whom I would agree 100% on everything we researched.
So I would be very carefull about putting words like “scientific”, “community” and “consensus” together.
I do believe in research, discovering new things, finding new explanation for old things. I believe in publishing results and data, in reproducibility of results. I believe in truthful and honest diacussion. And I believe in mistakes. Because I sure as hell have made many.
Way before Science exist, we used to believe in obsolete medical theory called the Miasma theory which most people believed that infections were caused by foul odors. Centurys later, the scientific theory called ’Germ theory of disease became
During the Miasama Era, Hand washing washing wasn’t the norm until the 19th century which is the effective way of prevents the spread of many diseases. ”
The guy who discover hand washing effectiveness Ignaz Semmelweis
“Despite various publications of results where hand washing reduced mortality to below 1%, Semmelweis’s observations conflicted with the established scientific and medical opinions of the time and his ideas were rejected by the medical community. Semmelweis could offer no acceptable scientific explanation for his findings, and some doctors were offended at the suggestion that they should wash their hands and mocked him for it. In 1865, the increasingly outspoken Semmelweis supposedly suffered a nervous breakdown and was treacherously committed to an asylum by his colleague. He died a mere 14 days later, at the age of 47, after being beaten by the guards, from a gangrenous wound on his right hand which might have been caused by the beating. Semmelweis’s practice earned widespread acceptance only years after his death, when Louis Pasteur confirmed the germ theory, and Joseph Lister, acting on the French microbiologist’s research, practised and operated using hygienic methods, with great success.”
