And, frankly, if you're going to produce a model that simulates something that is measuring risk (i.e., global warming), then I'd much prefer you leave out features that would understate the risk. Give me an upper bound on risk so we can see how bad it could get. If the worst isn't worth worrying about, well, then that missing feature didn't really matter. If it is worth worrying about, we can improve the model.
What is reasonable to demand, and in fact fundamental to the institution of science itself, is that scientists operate with the humility necessary for a discipline that is fundamentally open to new evidence and revised theories.
Instead what we are treated with (from climate science in particular) is “Science”, supposedly ordained as hard truth by an infallible “peer review”, and we are told we may not question the data itself, nor the statistical models, not even the draconian government interference into our lives conveniently suggested by the government sponsored “Science”, lest we be castigated as knuckle dragging “science deniers” with some secretive motivation to defend the fossil fuel industry or some other conspiratorial accusation based on zero evidence.
The Science part was full of error bars and "probably" and "estimated". Generally good science being done by people trying to discover the truth, though there was a noticeable hesitance about publishing any implication that the models might be wrong.
The Political part was full of certainty and unambiguous calls to action in the face of overwhelming evidence that the world was going to hell in a decade.
The media only ever reported on the Political part. The Science part was worth reading to get some perspective.
Moreover, climate science is in the hard science phase of maturity now. Which means that its unlikely that new data or new theories will results in major changes to what we think will happen. In other words, new data and new theories will only make minor course corrections to what we predict about the future. Earth's climate is still headed towards catastrophic changes due to human activity and anyone sane should be willing to bet their live savings on this.
Um. Well. I'm glad you said that. It's not any more stupid than ignoring data sources and producing model after model that only aimed to confirmed the prevailing narrative. "See we were right" but failing to list the caveats - as ALL data has - is negligence. With that said, I'm not going to bother with your second paragraph. It's absurd.
Science's #1 job is to ask "What did we miss?" Failure to intentionally not do so - so that hard becomes easy, my peers remain esteemed, my career nudges upward - isn't only stupid, it's lazy and actually violates the definition of Science. You just can't act like a hobbyist and demand the respect of a scientist. That's unreasonable, at best.
Yes. I think it's perfectly fine not to trust someone who deceived me, is lazy and is unapologetic on both accounts. As good Science already tells us: Trust is earned.
Perhaps we could plant Azolla in some big enclosed water bodies like the Black Sea?
en.m.wikipedia.org/wiki/Azolla_event
Azolla uses only the upper two cm of the water but takes all the light and 'kills' the 99,9999% of the water volume for other purposes. Would be like painting a building with a glowing paint and then stop people to enter and use the whole building so they do not damage the paint layer.
If we block the light we are excluding the effect of 5m of algae for example, killing the fishes that need this algae as larvae and also messing with the oxigen interchange in the water. Is not the perfect solution that we need
If I were to model the solar system and leave out the sun, it would be laughable and I would quickly find myself out of funding.
https://www.ipcc.ch/publications_and_data/publications_and_d...
Also note that as the AR reports get published, the models consistently get more complicated and improve. It turns out that you can get a fair amount of headway with a simplistic model (CO2 will generally drive the temperature up), but if you want to explain the variation that is observed, it gets more complicated. Given that the amount of warming has been consistently underestimated by the IPCC reports[1], it's fair to say that, for the most part, scientists are aware of the failings of their models and are being cautious in how dangerous the potential outcomes are.
The press, being the press, tends to sensationalize science with "Conflict! Intrigue! Breakthrough! Physicists vs Biologists! SUNDAY! SUNDAY! SUNDAY!". I suspect that these misleading characterizations have a bigger impact on people's perception of Science than the actions of scientists themselves.
[1] https://en.wikipedia.org/wiki/Intergovernmental_Panel_on_Cli...
I think you mean overestimated. The IPCC reports have consistently predicted more warming than has actually occurred; by now the actual warming is outside the lower end of the IPCC's confidence interval. The IPCC AR5 responded to this by no longer claiming that its predictions of warming were based on climate models; instead it said they were based on, in effect, the personal opinions of the report writers. This does not strike me as a valid scientific method.
> The press, being the press, tends to sensationalize science with "Conflict! Intrigue! Breakthrough! Physicists vs Biologists! SUNDAY! SUNDAY! SUNDAY!". I suspect that these misleading characterizations have a bigger impact on people's perception of Science than the actions of scientists themselves.
While I agree that the press likes to blow everything out of proportion, I think scientists have to bear the blame as well. Scientists do not do a good job of conveying the relative levels of confidence in different claims; to the public, they portray every claim as being made by Science, with the same authority, regardless of how solid it actually is. It is hard to blame lay people for losing trust in science when so many of these claims turn out to be wrong. What scientists should have done is to not have made those claims with the authority of Science in the first place.
The recent "replication crisis" is an example of this. The reason all those findings weren't replicated is that they weren't valid in the first place; they were only indications that needed further investigation. The scientists publishing them should have known that and should have said so. The narrative that should have been given to the public is "these are interesting indications but that's all, they might not pan out, more research is needed...well, we did more research and it didn't pan out.". But the narrative that was actually given to the public was "WoW! Great new finding! Everybody change everything you're doing!...oh, wait, turns out it wasn't true after all." After enough iterations of this, naturally nobody trusts what scientists say any more.
What confidence interval is that? What prediction was much higher than the +1C that has occurred? Looking up the 1990 IPCC report I see +1.5 to +4.5 between 2025 and 2050. We seem to be within that prediction.
http://www.ipcc.ch/ipccreports/1992%20IPCC%20Supplement/IPCC...
+1 C from 1990 to now? It's not +1C, it's +0.61C, according to NASA's smoothed data:
https://climate.nasa.gov/vital-signs/global-temperature/
The temperature anomaly (quoted on that page as 0.9C) is not based on 1990 as the zero point, so that's not the relevant number. The actual numbers are in the data behind the smoothed curve shown on the right of the page (click the "HTTP" link next to "Get Data").
> Looking up the 1990 IPCC report...
The relevant prediction in that report is for the "business as usual" scenario for CO2 increase, since that matches pretty closely how CO2 has actually increased since 1990. The prediction for that scenario is +0.3C per decade.
However, there are other comparisons that can be made, which make the models look even worse. See, for example, here:
https://judithcurry.com/2015/12/17/climate-models-versus-cli...
This is comparing the IPCC AR5 model runs with balloon and satellite data. (And note that, unlike the comparison I did above, the "model runs" curve in this graph averages models for all of the CO2 increase scenarios, not just the "business as usual" one; just showing the "business as usual" model prediction curve would increase the gap between the models and the data.
+1C from pre-industrial times. Apparently we are at +0.8-1.2 in that measure.
>The prediction for that scenario is +0.3C per decade.
The report says 0.2-0.5. The +0.6 from 1990 to today is at the lower end of that range. It seems to me you're splitting hairs when the models are doing alright.
Which all depends on how you choose "pre-industrial times" and how accurate you think temperature readings from those times are. Since even today's thermometers are only accurate to within half a degree or so, I'm not sure how we can even know the change from "pre-industrial times" to within less than half a degree (four tenths of a degree according to your statement).
> The report says 0.2-0.5. The +0.6 from 1990 to today is at the lower end of that range.
Yes, that's true. But as I noted, that's not the only comparison between models and data. Looking at comparisons overall, the statement I made, that the data is outside the lower end of the models' confidence interval, is correct.
The predictions of doom that are driving the public policy changes being demanded by climate change alarmists do. And the models are wrong.
This is because the climate has gone through major changes before, and we can see how much of an initial push it took, and what happened afterwards.
Trending to a local minimum or maximum in modeling can be caused by small changes at certain points dependent on time and be completely negligible at other points. Without understanding the model: 1. We can't even pretend to understand causality 2. We can't infer the complex state at an individual time or even the magnitude of a push.
This is not correct. There is plenty of data in climate science. There just isn't a good enough understanding of the underlying mechanisms to make predictions that are accurate enough to drive multi-trillion-dollar public policy decisions.
If the unaccounted for factor starts changing significantly over the time frame you are modelling, this will not work well and then you have to understand that factor and build it in.
From the article, the impression I get is that we are now learning the trees and other plants affect climate more than we might have thought, but I don't see anything suggesting that the amount of the affect is changing much and so it would likely be the kind of thing that gets accounted for in the tunable parameters of the climate models.
They don’t know everything but their approximations are really good for getting a lot of stuff done. That we know more and more over time is why they keep getting smaller.
If you want to reject how far we’ve come, that’s fine, but it’s a bit hypocritical to use all the medicines and high speed travel and telecommunications and the pocket supercomputer.
It is easy enough to make the assumption that technological advancement comes out of the study of science. However, if one looks back at history, one sees that technological advancement was the driver for science and not the other way around.
When it boils down to it, the more we learn about the universe around us, the less we really know. There are more and more areas which we are finding that just don't fit into the existing models.
I believe that our current climate modelling efforts leave much to be desired. Planetary climate is an incredibly complex set of interactions and we have only just started to scratch the surface of those interactions. Let alone understanding what all the relationships are and how they affect all the various feedback circuits (both positive and negative feedback).
Frankly, I'm stunned. How can you stand behind the integrity of your model(s) knowing that you excluded key components? Mind you, you could argue that they weren't aware. But that makes it an known unknown, not a false assumption.
Editorial: This is a perfect reason why "science" is trusted less and less. You cannot pound fist to desk demanding respect for your authority and then be intentionally negligent (just so your paper fits a narrative on the path to being published).