Do climate models predict extreme weather?
backreaction.blogspot.com
backreaction.blogspot.com
To give an example. Let's say there's a 1% chance every year that there will be a catastrophic wildfire in some particular area. Now let's say climate change increases a chance of drought in that area. Then we get a wildfire one year and the attribution is (say) "20% due to climate change" -- which I guess means there is now a 1.2% annual chance of a catastrophic fire.
But what if climate change causes more rain in the area? And, for the sake of argument, that causes the change of catastrophic fire to go down to say 0.8%. Then, in a given year, there is no fire. No one is going to bother doing an attribution study to say, "Climate change is 20% responsible for the fact that we didn't have a fire this year."
Or mudslides.
Of course that's true. What I guess I was trying to say is that a change in climate doesn't necessarily mean more extreme weather (in every instance, I mean). A change in climate could cause something to happen more or happen less. But no one is going to study a given year and a given place that doesn't have an extreme weather event.
> Paleoclimatological studies indicate that the last 150 years of California's history have been unusually wet compared to the previous 2000 years. Tree stumps found at the bottom of lakes and rivers in California indicate that many water features dried up during historical dry periods, allowing trees to grow there while the water was absent. These dry periods were associated with warm periods in Earth's history. During the Medieval Warm Period, there were at least two century-long megadroughts with only 60-70% of modern precipitation levels. Paleoclimatologists believe that higher temperatures due to global warming may cause California to enter another dry period, with significantly lower precipitation and snowpack levels than observed over the last 150 years.[7]
https://en.wikipedia.org/wiki/Climate_change_in_California#P...
That said personally I think that should be as far as the discussion goes, talking about a specific event and asking whether it's because of climate change is silly and leads to counter intuitive results because by nature extreme weather events are mostly caused by bad luck.
Climate changes the frequency of extreme events, but talking about the frequency of a singular specific event is impossible. And talking about just 1 or 2 of them isn't quite enough either, events will occur at a rate far above or below that predicted by the best weather models simply because of (bad) luck.
I sometimes get the feeling that people try to attribute extreme weather to climate change because it improves the narrative, or as proof that climate change has happened. But personally I find this a bit silly since the fact that the global average temperature has increased and the effects this has on weather shouldn't be all that controversial.
You seem to be suggesting there can be no causal inference where there are no control groups.
Both positions are wrong.
Weather is real. Weather has causes. We can and do reason about those causes all the time.
Plenty of companies have gotten away with bad practices by simply demanding proof for each individual case, the earlier we recognize this as a meaningless question the better.
I generally agree with you that this isn’t easy to do, the value isn’t clear, and whether we can say such things with the evidence we have for any particular event isn’t obvious.
When I say that this storm may have been enhanced by climate change, but it could also could have happened anyway, statistically: people hear natural variability, and that I don’t know for sure that climate change impacted their daily lives. And if I don’t know for sure, there must not be much of a case for climate change.
Most of the world is not HN, where nuanced discussions work. Most of the world does not give a shit about climate change unless they will personally suffer in some way. So I lie. So that even if this storm or that hurricane didn’t hurt them, they will have empathy for those who did suffer from a climate-enhanced storm. Because if we wait for everyone to feel the impact in earnest, it will be far too late.
A physicist actually explaining Magnetism takes years. If a PHD gives you a short answer their simply lying to you. For example, no ferromagnetic materials aren’t simply all atoms arranged in a specific fashion that’s a monumental simplification.
But that weather dude will lose his credibility, because his audience will feel deceived, not educated.
And it's not just this problem, it's all problems where people need to be convinced 'for the greater good'. I truly worry that the rightful distrust that those 'white lies' are causing is doing irreparable harm. It's also quite fragile since it opens room for people to point out the misleading or even false information, and in those cases people have a nasty tendency to assume the opposite must therefore be true.
You know where else I see this pattern? Digital forensics, my area of work. People have been selling snake oil all around for years, and know lawyers, attorneys and judges (in general, with some god particular exceptions) believe in whatever they've been seeing in CSI, or their "IT guy" convinced them as possible. Who cares that I'm one renowned expert in the field? _Their guy_ said this thing was possible, so I must be lying!
As it became obvious some officials were willing to lie, this opened the door to many people having no idea who to trust.
I believe public trust in leaders and institutions is at an incredible low, and I’m not sure how it can be repaired.
Regardless of whether you think people are capable of nuance, most people have people in their circle who they trust and do have that capacity. Meanwhile, keeping secrets on the internet is very hard.
I think a much better strategy is to explain honestly and with nuance, and hope that this will maintain your credibility in the face of an army of internet researchers who will probably do more to shape average people’s conception than you can ever hope to do directly.
I would say, please don’t lie.
I not sure it can be considered a lie though. Wrong, but at the time the precedent was pandemic flus and SARS-1, and there isn't much presymptomatic transmission of either. Quarantining once you have symptoms will do the job. SARS-2 is freakish in just how much it replicates in the nose for a couple days before symptoms. It was another 3 weeks before enough data coming out of China established there was likely an appreciable degree of presymptomatic transmission occuring and the CDC guideline was changed.
That said, he definitely should have expressed the reason he was making a stand either way, i.e. that healthcare workers needed the supplies more than folks in the street.
A better example of a lie was when he said he was titering up the number for what is required for herd immunity based on what he thinks will be publicly palatable, while that's dodgy imo it is kinda small potatoes.
Fauci later said that the reason they advised against masks was because of fears of a PPE shortage. So either Fauci admitted that his earlier position was a deception, or his later claim was itself deceptive.
GP gave an actual quote, can you provide one for this as well?
Maybe you think Fauci changed his mind based on new evidence on mask effectiveness, but he literally says they advised against masks due to a fear of PPE shortages, and not due to changing evidence. So either way he deceived: either he deceived about mask effectiveness thus spreading health misinformation, or he deceived about why he advised against wearing masks thus undermining public trust in his advice.
Fauci admits to moving the goalposts on vaccination rates and explains it's because of his "gut feeling that the country is finally ready to hear what he really thinks":
https://www.nytimes.com/2020/12/24/health/herd-immunity-covi...
I think public health officials like Fauci really shot themselves in the foot by undermining their credibility so early on. Public health officials in a public health crisis should be beyond reproach, but that's not how they've been acting, and continued partisan support of these figures only further deteriorates trust in scientific institutions and journalism.
The US pandemic response hasn’t been a Trump or Biden problem, it’s been a Fauci problem.
That has always been obvious horseshit to anyone who knows anything about biology. His later statement was that the "real reason" they advised people not to wear masks was not actually the stated reason, but a completely different reason. That's literally a deception, and it from Fauci's own words, it appears to have been an intentional deception.
Now you might be ok with public health officials deceiving the public about public health, but I am not. I think it's doubly important that such an official be above reproach in the midst of a pandemic.
Again, he didn't comment on the factual basis of the original mask guidance, only the reason why he made a proclamation one way or another. You are reading between the lines a bit too hard here I reckon.
> That has always been obvious horseshit to anyone who knows anything about biology.
With SARS-2 and hindsight, sure. But had it been like all previous pandemic respiratory viruses including the one most closely related to this virus, where the vast majority of transmission occurs only after a carrier is symptomatic, no, masks wouldn't do much for people in the street as long as anyone with symptoms stayed home.
I think the guidance was muddled and he could have explained the rationale re: healthcare workers. But Fauci didn't later admit deception and what he said at the time wasn't out of line with a reasonable interpretation of available evidence.
And those reasons contradict the earlier reasons he gave. How is this not a clear deception? Perhaps we should discuss the actual video evidence:
https://www.youtube.com/watch?v=kLXttHlUgK8
Furthermore, if the factual basis of the original recommendations were not false, why were masks mandated soon after shortages were no longer a concern? (and continue to be)
> But had it been like all previous pandemic respiratory viruses including the one most closely related to this virus, where the vast majority of transmission occurs only after a carrier is symptomatic
That's irrelevant to this topic. You don't know who else around you in public might be symptomatic, that's the whole point of wearing masks.
> But Fauci didn't later admit deception and what he said at the time wasn't out of line with a reasonable interpretation of available evidence.
Yes, he literally did. He said people should not be walking around wearing masks. He justified this recommendation by saying that it's because masks are not providing the protection people think they do, and that they might only stop a droplet or two (all clear nonsense). He even said that wearing a mask might be more dangerous than not wearing one. These are all claims he made in that interview.
When asked later why his advice around masks changed, he didn't say the understanding of the facts changed, he said that those original recommendations were made for reasons completely unrelated to effectiveness (fears of PPE shortages).
You can try to spin this however you want to suit your narrative, or try to be as charitable as you want to Fauci, but this was clearly deceptive messaging, and almost certainly intentionally deceptive. At the very least, this would make Fauci among the worst science communicators I've ever seen, at worst he violated the public trust, and is that really who you want communicating to the public in the midst of a public health emergency?
> why were masks mandated soon after shortages were no longer a concern? (and continue to be)
...because that is when the scientific evidence changed. Preprints from China were streaming in in March 2020 that were making a significant degree of presymptomatic transmission look increasingly likely.
Why would he even bring up PPE shortages in response to a question about changing mask recommendations? You've invented a charitable narrative in an attempt to explain the changing recommendations, but this narrative doesn't actually explain the available evidence.
Like I've been saying all along, he either very clearly lied, or he's literally the worst science communicator I've ever seen.
Either way he should not be the face of public health.
“When polls said only about half of all Americans would take a vaccine, I was saying herd immunity would take 70 to 75 percent,” Dr. Fauci said. “Then, when newer surveys said 60 percent or more would take it, I thought, ‘I can nudge this up a bit,’ so I went to 80, 85.”
“We need to have some humility here,” he added. “We really don’t know what the real number is. I think the real range is somewhere between 70 to 90 percent. But, I’m not going to say 90 percent.”
-- https://www.nytimes.com/2020/12/24/health/herd-immunity-covi...
Of course, the problem with people who don't believe in vaccination is not only due to their lack of statistical understanding, but it's massively enforced by politicians and "journalist" who spread those lies.
Both believers and non-believers tend to be immune - to any findings that run counter to their belief systems. Instead of objectively weighing up pros and cons they get rather heated and adopt binary thinking along pro- and anti-vaccination lines with some indulging in the same trap themselves.
A reasonable scenario that doesn't get bought up enough is that average people have a radically different risk tolerance than professionals working in the healthcare industry. 1 in 10,000 incidents mean very little to a person on the street but translate into actual work for a healthcare worker.
Now that it's becoming vaccinate every six months, the outlook of the cumulative probability of side effects doesn't look that good anymore.
And, going trough an inflammatory process every six months doesn't seem good on its own, even if the vaccine wouldn't have side effect.
Are you claiming this as a universal truth? Or your specific experience?
My experience and that of two of my three adult children is that it was like a slight bruise at the injection site for about 24 hours. The other child felt slightly under the weather for a couple of days, similar severity to having a cold. We all had Pfizer.
My impression is that my experience is the more common one, but it is not the one that grabs anyone's attention.
The more serious side effects seem to be vanishingly rare.
so, an inflammatory response.
Covid infection is “potentially” much worse, that’s true, but so is a drive to a vaccination site — the child might die or get seriously injured in a traffic accident. What matters is not the “potential” but rather the actual likelihood, the expected value. Has Covid been dangerous to children? The answer is, rather overwhelmingly, no.
It's actually quite common that vaccinations need to be done multiple times (up to 5 times for DPT) and to have boosters for these when traveling to certain countries.
There’s a similar meme going around the US, but I’ve yet to find any (except one, noted below) health expert who actually said “masks don’t work” rather than “we don’t know that masks work.”
The one exception I’ve been able to find was the US Surgeon General Jerome Adams.
This seems like a clear example of health authorities sharing a nuanced true-at-the-time message that got stripped of that nuance and rounded out to the nearest (false) simplified interpretation.
From the chief public health officer of Canada who is also a WHO advisor. She's also said other very questionable things (which are all Googleable and which pretty much every Canadian can tell you as it's been a bit of an ongoing scandal, among others...).
Not sure if that’s the same interview you linked though^
> I believe public trust in leaders and institutions is at an incredible low, and I’m not sure how it can be repaired.
I’m not sure you can conclude that the ability or willingness of people to trust anyone is the thing that has weakened when so many people who boastfully distrust traditional mainstream experts also do trust some extremely specific set of claims from some random YouTuber or talk show.
I'll phrase it another way: When you tell a lie, some people will see through it and some people will believe it. Of those who see through it, some will believe you had good intentions for lying, and some won't. These proportions all vary depending on the exact nature of the lie and the audience receiving it, but it's virtually always the case that [see through the lie] > [see through the lie AND believes it well intentioned]
Or put another way: Every time you tell a white lie, you burn your own credibility because some people will see through your lie and won't be inclined to excuse you for it.
This is fascinating. I would normally have written this off as a troll like a climate denier trying to discredit one side, but you seem to be well established here and quite possibly identifiable from your about page (not that I tried or am interested in trying to troll through it, just had a quick glance).
Don't get me wrong I absolutely accept that some scientists may take a bit of license with the truth when they say a particular weather event was caused or made more likely by climate change without having gone through a full analysis of that particular event and situation. And I even accept there is corruption and dishonesty all the way from a bit of unconscious bias to much worse.
It's quite amazing to see a scientist out and admit they lie about the science in order to try to influence public opinion in the hope of effecting the social or political change they want. I really admire and appreciate your honesty here, if nothing else. Can I ask whether you act in any professional or academic capacity as a climatologist? And what are the nature of the lies? Who are they to, how are they communicated?
The lie mainly has to do with people wanting to see the direct cause. But there is never a direct cause to weather. There’s a probability of enhanced storm intensity, because we observe storms getting more intense. Was it that last storm? Maybe. But the answer I give is yes. Because in all likelihood, there is some influence.
But climate change is in fact real, has in fact caused damages. If you are concerned about immigration in Europe, consider that a drought led to a famine led to a civil war led to mass migration. Are there a lot more causes here? Sure. What was the cause? Probably a lot of things. But the weather was surely one of them, and models tell us extreme events become more common under a warming Earth.
Climate change has already affected your life. Statistically, it must be so! Just because I cannot say how exactly it has done so, leads people to discount me. So let’s just pretend I know how, so I have a bare chance of being taken seriously. Else my hedging be mistaken for lack of certainty, by confirmation bias of people who yearn for my uncertainty.
I see it as akin to novels. The whole point of fiction is to create empathy for another point of view, though the method is a thicket of lies. The truth can very often not be looked at directly. Tell a teenager not to worry about what other people think — see if they get it. Tell a person that being racist is dumb, and see no behavior change. But a story might work, as a magick spell to get one to feel empathy, a lie that reveals truth.
As other people have stated, its not as simple as lie/don't lie.
Many people simply don't want to acknowledge certain realities:
There is an overwhelming majority of people who lack the capacity/ability/attention span to look clearly and rationally at a complex topic and evaluate the available evidence in anything remotely close to a nuanced, well educated fashion.
You then have to add to this that these same people are being mass manipulated by bad actors with nefarious agendas and large budgets and resources. And then there's the fact that the internet has allowed people to live with the illusion that their understanding parallels that of people with infinitely greater education and experience.
Any public communication has to take this in to account. Believing that the rubes will somehow find their way to a reliable conclusion if you simply tell them 'the truth', is a recipe for playing into the hands of the nefarious (who are more skilled at portraying their self-serving bullshit).
2. Of course they should be able to.
Yes, they are. Every election winter, or so, some performative artist shows up to Congress with a bag of ice, and announces in front of cameras something along the lines of "Checkmate, scientists, if global warming is real, why is it snowing in my congressional riding?"
What the "lie" "really" says is subtextural/etc: to those that need to hear it, it says what it needs to say to get them to understand what needs to be done (and, importantly, isn't wrong, just isn't the whole picture either); to those that already know the answer, you didn't need to hear the lie in the first place. There is no deceit.
Climate change needs participation from everyone, and, for better or worse, everyone includes a majority of, eh-hem, less-than brilliant people. We need them to understand regardless of our own righteousness.
This only works if truth is used. The labster seems to be assuming they have credibility; but if they're lying, or if they're associated with liars, they'll lose it (if they haven't already).
The lies are useful for making good decisions, though. I offer the same. A simplification that does not quite represent reality, but you should 100% consider it anyway if you build a bridge, because it will save you a world of hurt in the future.
If you want to communicate reality, you need to understand your intended audience. Finding what to emphasize and what to simplify will determine whether people understand you.
That's uncharitable and untrue.
> So I lie. So that even if this storm or that hurricane didn’t hurt them, they will have empathy for those who did suffer from a climate-enhanced storm.
People distrust science after decades of bad science journalism and bad science communication, and you think the solution is to outright lie and undermine all of your credibility.
I'm sure that'll work just great, and it won't at all simply reinforce the beliefs of those who already agree with you while arming those you were actually trying to reach with reasons to distrust you. Not like we didn't see exactly this sort of lie backfire during the pandemic.
This is a strange misconception about climate change, even among many of what should be the better educated and informed section of the population, at least on the issues of the science. The misconception is that more people need to be convinced about climate change and the need to take action.
Many climate change topics that come up even on here get well received comments about problem of the greedy selfish uneducated rednecks who are preventing climate change action, and the subsequent hand wringing about how to educate or scare or convince them into changing their minds.
The facts just don't support this outlandish idea though. Even in the country with the most climate deniers in the world, Indonesia, they number just about 21% of the population. In the USA, deniers are under 20% and a staggering two thirds of people and more than half of Republicans think the government should take more action on climate change. This is an overwhelming political mandate, it's not even a question.
The ruling class enacts far less popular policies and legislation all the time and doesn't bat an eye. You're telling me they'll go on expeditionary wars on flimsy pretexts that last decades and cost trillions of dollars and kill thousands of Americans, but they won't implement overhwelmingly popular policy that has bipartisan support of voters to address what they keep telling us they believe is the biggest and most important problem facing humanity? This is clearly utter bullshit.
And that's the way they like it. Their divisive propaganda (which includes seeding distrust in science) has worked extremely well. The facts show that they never had any intention to more about climate change, that they routinely lie about the political reasons for not doing more, and they're happy that the commoners are blaming one another for it instead of the robber barons who own them.
In the summer, we had an unprecedented heat wave which killed thousands of people. Seattle hit 108°F/42°C. The town of Lytton, BC, hit 118°F/48°C[0], and then completely burnt down in a 30 minute firestorm. More rain would have been great.
We didn't get it.
We got it in the winter, and it was absolutely devastating. [1] To cap the year off, we ended with a record-setting freeze (With, thankfully, comparatively moderate snowfalls).
So, yes, more rain, less rain, more heat, less heat, we got all that. Unfortunately, weather is not a bank account, and having your town burn down to the ground in the summer, followed by a flood in the winter doesn't tend to cancel things out.
[0] An all-time heat record for Canada.
[1] https://en.wikipedia.org/wiki/November_2021_Pacific_Northwes...
Well, I mean you would hope so since that would be honest science.
What is your actual point?
the more precise way to measure would be to increase the sample size by counting a precise metric like total acres burned per season, and measuring it over a longer period of time to determine whether or not forest fires are generally getting worse or not. and if they're getting worse, how much are they getting worse by, and how much of that trend can be attributed to climate change.
So, where models predict an increase in such events comes down to increasing probabilities of the individual events, kind of like throwing the dice twice as often as before, then you're going to get double sixes (i.e. extreme events) more frequently.
As far as the attribution of specific events, well, you can look back in history and say, historically we've had these events every 100 years or so, so we shouldn't expect three such events over a twenty-year period. This is similar to how a casino might suspect a player is using a loaded die.
However, for one specific event, is it possible? Plausibly you can examine the details of a single event and ask, okay, are there physical characteristics here directly related to climate change, in the same way one could examine a die to see if it was really symmetrical or not? One could perhaps use expectation results, i.e. "we expected this kind of extreme weather event to occur with greater frequency outside the regions where they normally take place, according to frequency results in models forced with extra CO2" etc.
Really though, it's when you get 500-year floods every 5-10 years in Europe, then you know you're 'testing the historical limits'.
I think most people just look around and see that things are changing. The attribution studies are sort of a moot point. It's the actual change that is going to make us act.
Already is, a little.
Nobody is going to understand all the weaseling around this could have occurred by chance but we think it's more likely to occur because we modeled it but our models can't predict those low frequency really severe events so we've modeled less severe events and are guessing. If we do start seeing more and more serious weather events (like we seem to be) there's going to be some drastic action (too late?) and if we won't then I guess we're ok by some luck.
---
Build a SIMCITY and use the ACTUAL policies and everything from actual cities... including infrastructure and have people game the city...
Have AIs do so as well... billions of times - and implement best options....
Develop the game such that one person could only focus on finance, or infra, or transit...
Wow this game exists!?? and its called .gov
but its running on windows 3.11 in my garage?
How fix?
This is not true. In fact, I'm aware of several papers that have made an argument that climate change will lead to more rain in California. They don't appear to be winning the argument but for many years this was a contentious discussion among atmospheric scientists. Academics absolutely do the research you are describing.
Would those papers make their way to mass media or social media discussions? Probably less so. But they are there amongst the communities that matter most in the conversation.
For example, see the graph in [1], and imagine we only have data up to 1999. The year 1998 sticks out like a sore thumb - it was a freak hot year. Except that it became the new normal temperature in the 2000s, and then the most recent six or seven years have handily beat it. It will be an unusually cool year if it happened now.
We are transitioning into a world where "worst since weather records began" is a regular phrase at evening news. When a town burns down, will its residents even care if the particular fire was linked to climate change or not?
[1] https://www.climate.gov/news-features/understanding-climate/...
A 2 degree change in average temperature doesn’t change how people live. A heat wave does.
Now I don’t know if it’s actually true or not but it feels like the frequency of extreme weather event has increased. It’s difficult to say because that’s something our grandparents already said 50 years ago.
But then there are 2 possibilities:
1. Either the frequency of extreme events has actually increased and it would be hard not to pin it down on climate change (despite our inability to do it scientifically).
2. Or it hasn’t changed significantly (statistically speaking), and it’s all a bit of mass hysteria.
Either way doesn’t actually matter. I personally don’t care if people are scared about the acidification of oceans or about rain for their next barbecue. As long as they vote for people who want to do something about it.
I personally have been criticized by friends for saying that we don’t know what the impact of climate change is on the weather. I don’t care anymore. It’s all about narrative. That one works, let’s not poke holes in it. It only benefits people running polluting industries.
There's also this naive commitment to truth. Yes, we want our mental models to be more accurate and predictive. What if a model results in an increase of net suffering? What is the role of a democratic government, to provide services to a society to lessen individual offering, or to pursue truth and align legislation at all costs?
The naive commitment to truth is the most fundamental requirement for the most basic freedom, the freedom to reason. To lie, to deceive someone means to take away that freedom.
I think the true danger is when there is little tension between government and the fourth estate. Government actions need interpretation and presentation, and when those functions lapse or are neglected, is when individuals begin losing the right to reason. To be able to make decisions presupposes that non-elites are presented with the decision in the first place. This is the context within which the naive commitment for truth is a virtue.
I get it. it's exhausting and usually pointless to make these sorts of arguments. I think it's fine to give up after a while, at least with certain people. every single issue can't be our hill to die on.
but this goes further than acceptance; we shouldn't go so far as to embrace obviously wrong narratives, however effective they may be in the moment. it really damages the trust we have in each other, which is already in short supply.
That's not true. It benefits anyone who can blame anything on climate change. For instance, decimation of fish stocks in the Pacific Northwest. Mostly due to dams and fish farming in the mouths of important rivers, and over fishing, but wild attributed to climate change. Massive forest fires in BC. Mostly due to forestry management practices where forests aren't allowed to burn, and any forests that do are quickly sprayed with Glyphosate so that Aspen don't grow (a natural firebreak species, but the lumber industry doesn't want it) and replanted with GMO pine. Monoculture forests have exacerbated Pine Beetle issues as well. Also largely attributed to climate change.
You take a locally solvable problem, and make it so that you can do nothing about it and the money continues to flow right in.
Honestly I’m amazed we can get the estimates we do, given that this particular field of analysis is so young. I’m not as pessimistic about the usefulness of this data though. Knowing that these events are becoming much more likely and having an understanding of why is useful work. There are always unknowns, and now there are fewer of them. That’s good.
Take the estimate that bush fires in Australia are now at least twice as likely than they were. Sure it would be better to know if they are twice, three times or 10x as likely, but knowing they are at least twice as likely and why that is the case is still useful data.
Something that was a lightbulb moment when someone was discussing professional baseball players. I forget the exact point the blog was making, but it came down to this: many things in life, like the ability to throw or hit a baseball, falls on a distribution that is close enough to a gaussian distribution. But when talking about professional baseball players, they represent just the very right hand tip of that distribution. Whatever intuitions you might have about gaussian distributions needs to be thought about in light of that.
The same applies with extreme weather events. It is easy to look at articles and headlines describing an exponential increase in the frequency of extreme weather events. But think for a second about the equation of a gaussian distribution. When you shift the offset by a small, fixed amount, the area under that right hand tip goes up exponentially.
No, one cannot point to climate change as the cause of any individual weather event. But it is a measured certainty that the warming is happening; the number of record high temperatures are a multiple higher than the number of record low temperatures every year for the past couple of decades. It would be weird if the temperature rose and the number of extreme events went up, say, linearly.
Its more than that. Large models have hundreds of adjustable parameters, which each may be tweaked within reasonable ranges to simultaneously backfit historic data and potentially get any kind of future result. It's very easy to get biased outputs which look totally reasonable, which is especially dangerous if the discipline is subject to a rigid orthodoxy.
Have you looked? Because the data is available.
https://e360.yale.edu/digest/extreme-weather-events-have-inc...
Additionally it’s not like these models are untested. Their predictions are continually compared to actual reality, including by taking know data, and asking the model to predict more known data. Pretty basic stuff for testing the capability of any model, and guess what, that data shows these models are pretty darn good.
Everything in this world is complex and chaotic, how cars behave in collisions is complex and chaotic. But no one doubts our ability to use computer models to design safer cars. Equally most people generally trust the one week weather forecast, despite the fact that it’s substantially more difficult to predict weather than it is to predict climate.
Just because weather is chaotic and unpredictable doesn't mean that climate is.
That's a good analogy of my skepticism for AGW. We are saying temps went up 1c over 100 years, taking daily measurements, and comparing them to ice cores which are our measurements of historic temps... Only those ice cores aren't daily- they're thousands of years apart. So the ice cores data is irreparably smoothed in a way the recent data is not.
It’s perfectly reasonable to take daily measurements, average them into yearly measurements. Then compare them to yearly averages taken from ice cores.
The only reason we can even use ice cores for temperature measurements is because they’re have high enough resolution that we’ve been able to observe the impact of global temperature on the most recent layers of ice. It’s not like someone drilled an ice core one day and discovered a bunch of temperatures sharpied down the side. They drilled many ice cores, then spent months correlating observed patterns to temperature records so they could build a model that allows them to understand the link between temperature and observed patterns in the ice.
Don’t mistake a record measuring thousands of years of history for a record that only records every thousand years.
What I am talking about is charts like this from the NOAA: http://www.climate.gov/media/5147
Thes resolution is yearly going back only about 2000 years. Everything beyond that, the resolution is much lower. Where is that data from and don't you see how much "smoother" it is?
The thrust of the underlying article is looking at the exact question you’re asking, can ancient ice records that have a more limited resolution of 20-500 years be compared to centennial or millennial scale data, and can you draw useful conclusions about time periods of that range.
Incidentally, the evidence for AGW, and indeed geologically sudden climate change without precedent, goes far beyond ice cores. Very little in science in predicated on lone observations that can't be cross checked. We have a wide variety of information sources that all paint a coherent picture:
https://en.wikipedia.org/wiki/Global_temperature_record
Measuring historical temperatures is not unlike measuring distance. We know, for instance, that the Andromeda galaxy is 2.537 million light years away. How can we possibly make such a precise assertion so confidently? We started by measuring small, earthly distances, and used those to triangulate larger ones. We worked our way up the distance scale by a series of inferences. Thus, we built up a model of how things look at various distances. It's more or less the same type of methodology - yet mysteriously, the anti-AGW pundits don't seem to have a problem with that.
https://en.wikipedia.org/wiki/Cosmic_distance_ladder
Climate scientists, believe it or not, know what they're doing. It is the height of arrogance to flippantly dismiss their efforts simply because you personally don't understand them, because you can't be bothered to research even basic things like the resolution of ice core data.
That said, we can predict, with some level of accuracy the stability of of orbits in a number of cases. Approximate solutions can be managed with various levels of theory, perturbations, and numerical simulation.
The difference is, Astronomical models can be simplified significantly, whereas climate models must be high fidelity to produce accurate results.
To me the critical question is at what fidelity are the models useful for our (humanities) purposes?
If our purpose is to predict climate and its impact we will need at least +/- 0.1C at a resolution of 100km at a timestep of 1 month. It must be possible to do mesh refinements to determine how accuracy changes with changing resolution, and then combine that with the prior resolution conditions to choose an appropriate mesh.
As far as I know most modern climate models are accurate to within a degree for at least a 30 year range. I haven't looked at the mesh sizes for a while but I'm sure someone has done something similar.
A climate model can’t you whether or not is going to rain in exactly 300 years time, but it can tell you how much rain will fall during an entire year, 300 years from now.
Climate modelling is macro scale modelling to weathers quantum scale modelling. You’re operating at entirely different scales, and further you zoom out, the more you can ignore the minutia and still produce useful predictions.
Additionally taking about absolute time periods is the wrong approach. The real question is now many time steps can your model take before it starts to significantly diverge from reality. A car collision simulation will be operating with time steps measured in milliseconds to nanoseconds, a climate model in time steps measured in days to weeks. Both of these models will probably be predicting a similar number of time steps into the future, and both will have a similar number of quantised simulation areas. For the car you’re simplifying cubes measured in millimetres, for climate, zones measured in km.
Again, climate models have been measured, tested and repeatedly proven their predictive power. If empirical results aren’t enough to convince you, then what is?
Perfect example of this is quantum effects. Zoom in far enough and quantum effects make the world entirely unpredictable, and yet I can still accurately predict where I throw is going to land with no knowledge of quantum effects. That doesn’t mean those effects don’t influence the ball, it just that noisy chaos of those influences is tightly bound enough that it doesn’t matter. Newtonian physics is enough to make a prediction, despite being an incomplete description of the physical system at play.
I.e. we can say thing X has a 90% probability of happening. But we can’t say thing X will happen.
And of course a strong probabilistic prediction is incredibly powerful and useful. I don’t want to suggest that it isn't, but it’s not an absolute prediction. And once again usefulness of a probabilistic prediction is almost always as useful as an absolute prediction (I would also argue that absolute prediction don’t really exist in the real world, they’re just extremely high confidence probabilistic predictions, but you haven’t bothered to model the actual noise).
You can't really model anything "accurately", but you can assign a subjective (probability is subjective) probability to certain outcomes based off an analysis of your model, and what in your best judgement are the correct parameters.
This is why the papers containing uncertainty analysis of varying quality, the press releases will have some handwaving, and the articles in the newspapers will contain nothing of the sort.
We can look at the predictions (inference) from older models and check how accurate they were at predicting the future. No back testing required. Those models have been very accurate. Current models have only improved and reduced error.
We can test the accuracy, you have to be honest about it.
https://www.science.org/content/article/even-50-year-old-cli...
If climate is only model able by chance, we got lucky a lot of times. Someone should be buying a lot of lottery tickets because the science community is way luckier than the expected value. That dozens of independent research teams were about to exactly cancel out errors in precisely the right way (but different from one another) to have good predictive power. Certainty too lucky for a purely random process. So what's the bound? Clearly this process is repeatable.
The models are accurate and science can deal with probabilities. Or rather that scientists (experts) know what they're doing.
The odds on the first conclusion are too high. The second is easier to justify. I think it's easier to justify that you're not as informed on the subject and that there's nuance you're missing that the experts know (I'm confident they know more than me).
If your model includes most of determining factors for the system your modelling, then it’s going to produce pretty good results. There will be places where the model drifts, but you still expect the model to be pointing in pretty much the right direction. As you introduce more factors, your model starts to model details with increasing accuracy, but again you don’t expect it to substantially change the macro result.
I’m short we’re perfectly capable of knowing that the warming will happen without knowing about aerosols, the direction of travel is perfectly predictable, aerosols will only change the amount of travel, and not by an order of magnitude.
It makes no sense to talk about the 'chaotic' nature of a system without relating to the scale and scope of the model. Weather is a chaotic system but this doesn't mean we can't predict it at all what it'll be like an hour later or tomorrow. As we scale it out further, the accuracy decreases but we can predict with high certainty that it's not going to snow in Los Angeles six months out from today.
That does not mean you cannot do it accurately. It means you have to continually refine and improve and throw out and restart and refine and....
Scientists as a group are by far the most honest group of people you can point at. No other profession comes even close. Alluding to some dishonesty in the work behind climate change is straight up denialism. Yes some of the science has not panned out. That's how science works. It's part of the bones.
The issue is that it's hard to get these across correctly to the general audience. It requires analytical thinking and patience and attention to details, which none are compatible with how today's media and social networks are incentivized and structured (short, catchy, flashy, clickbaity, infuriating, etc.)
For example, we have fairly detailed climate related data sets going back many thousands of years, coming from many different kinds of sources. You input these as starting conditions to a model, run the model forward, and then see how accurate its predictions are against later historical data.
Despite your feelings about is or is not possible, there is very strong research that shows that climate modeling works.
So ... "Do Climate Models predict Extreme Weather? ": yes, yes they do.
But .... "how much impact does climate change have on extreme weather?": hard to say with much accuracy, but the factor isn't negative!
How useful is it to note that the factor might 2 or 200 or 2 million?
Combine this with human psychology and you have a recipe for catastrophe -- literally. You get an extreme event, and then everything reverts to the mean and things seem normal for a while, and people assume that the extreme event was a fluke. It wasn't. It's the new normal, and the next extreme event will be even worse.
You see this playing out in California right now. Everyone thinks the drought is over because it rained last month. It's not over. It's just getting started.
the climate models stink, and everyone in the science understands this but has difficulty communicating this.
The real world is more extreme than the models. But we have no way to extend the models to cover the seen extremes, nor do we know how to cap the possible extremities in any model.
Do i have that right?
There are things we cannot (as it sits right now) without killing large numbers of people and possibly ending civilization as we know it.
What might happen isn't as important as what will happen. This isn't necessarily evading the problem but it's also inexcusable to not make the changes we can. Wasting non renewable fossil fuels and the amount of litter and pollution we are producing are horrible no matter the ultimate reality of climate change (which I maintain is poorly understood and over-hyped right now).
There are real problems that are well understood we aren't doing anything about while wringing our hands about that which we practically can't at this juncture.
Offhandedly portraying scientists and researchers as dishonest and conspirators in every opportunity possible seems the default here.
This is also done in weather forecasting, though maybe they run the model in reverse, I can't recall. Same idea though, verify with existing data before predicting.
> The question of whether the twentieth-century warming should be considered a target of model development or an emergent property is polarizing the climate modeling community, with 35% of modelers stating that twentieth-century warming was rated very important to decisive, whereas 30% would not consider it at all during development. Some view the temperature record as an independent evaluation dataset not to be used, while others view it as a valuable observational constraint on the model development. Likewise, opinions diverge as to which measures, either forcing or ECS, are legitimate means for improving the model match to observed warming. The question of developing toward the twentieth-century warming therefore is an area of vigorous debate within the community.
And do I read it right that 35% of scientists deem it important that a model indicates future warming? Science doesn’t work that way, you don’t get to choose a conclusion then model for it.
No, you read it wrong. 35% thinks it appropriate to fit to past warming. Of course nobody is suggesting to fit to future warming! But past warming is observed.
If you are familiar with training/test split in machine learning, some thinks past warming is in training set (and test with things like reproducing ENSO), and some thinks past warming is in test set. I think it boils down to disagreement over how determined was twentieth-century warming.
https://journals.ametsoc.org/view/journals/bams/98/3/bams-d-...
They test these models with other planets too. Set in parameters for Mars or Venus and they precinct pretty well how those climates behave.
It also has been and continues to be tremendously accurate and predictive.
I am unable to find any 1982 Exxon prediction that would meander like the line in that graph. The only plot I was able to find is this [1] from this 1982 Exxon report [2], which is just a slightly curved upward rising sketch, not nearly as detailed as in the xkcd graph.
> the Exxon model from 1982
I also failed to find any signs of there having been any "1982 Exxon model". What [2] is, is a 39-page report, a synthesis and review of publicly available climate research. The list of references is quite extensive: 10 pages.
[1] https://pbs.twimg.com/media/D6fbaqdWwAEPg5Z.png
[2] https://www.climatefiles.com/exxonmobil/1982-memo-to-exxon-m...
For all of us, myself included.
That said, even highly adversarial climate models greated almost half a century ago have tremendous predictive power.
Large systems are modelable. Not with any degree of precision, of course, but a high degree of accuracy.
Otherwise insurance companies wouldn’t exist.
Yes. About the warming effect of doubling the atmospheric CO2 (Equilibrium Climate Sensitivity):
Manabe and Wetherald 1967, said 2.3°C.
The Charney Report 1979, said 3.0 ± 1.5°C.
IPCC AR6 2021, says 3.0°C (2.5 to 4.0).
https://journals.ametsoc.org/view/journals/atsc/24/3/1520-04...
https://www.bnl.gov/envsci/schwartz/charney_report1979.pdf
https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6...
It's the very definition of how computer models work. The modeler writes the program, determines all the inputs, determines how the logic of the program will respond to the inputs, etc. The modeler is in complete control of the model, tells it how to behave, and thus the model says only what the modeler tells it to.
> Are you implying that climate change isn't happening?
Non sequitur.
For example, the recent fires in the Denver / Boulder. Have you been there? It's effectively a desert. Dry, very dry. Open. There are few natural barriers once a fire starts. Based on what I know of the area, those homes - God bless those families - were built in harm's way. That disaster - regardless of climate change - was inevitable. To suggest otherwise is simply irresponsible.
Not normally, so much, but yes, when the entire state ranges between “abnormally dry” and “extreme drought” [0], it probably seems desert-like.
But...how are those unusual and extreme conditions an argument against the events being a product of anthropogenic climate change?
[0] https://droughtmonitor.unl.edu/CurrentMap/StateDroughtMonito...
Humans love to build homes and structures where they probably should not. We have this false ideal that we're bigger, stronger, and faster than Mother Nature. And then when it goes sideways we blame MN. That's not working out well.
In general, any abstract model has the same relationships to actual reality as cartoons - they look sort of plausible and even convincing, even when a cat or a mouse speaks perfect English.
There should be a clear warning statement, like with GMO labeling, that models are astrology with numbers instead of planets and stars.
And no, no matter how sophisticated, a model will never be more than a cartoon, in the same way that a map would never be a territory.
If you're discounting a whole field of research, can you provide more reasoning for why it can't be improved from the current results?
>"And that is what I think is the biggest problem. The way that extreme event attributions are presented in the media conveys a false sense of accuracy. The probabilities that they quote could be orders of magnitude too small. The current climate models just aren’t good enough to give accurate estimates."
Of course, if your threshold for action on climate change is strong extreme weather attribution, then ok. But I think it's reasonable to also have lower or different thresholds for planning nad action.
I do feel queasy about the current phrasing of extreme weather attribution, especially as portrayed in the media.