
Climate models are running red hot, and scientists don’t know why - montalbano
https://www.bloomberg.com/news/features/2020-02-03/climate-models-are-running-red-hot-and-scientists-don-t-know-why
======
leifdenby
There is a big observational campaign happening right now that is trying to
get to the heart of this called EUREC4A (main website:
[http://eurec4a.eu](http://eurec4a.eu) and information sheet:
[http://eurec4a.eu/fileadmin/user_upload/eurec4a/2019/Press/E...](http://eurec4a.eu/fileadmin/user_upload/eurec4a/2019/Press/EURECA4A_factsheet_uk_10_12_2019.pdf)).
The key uncertainty between different climate models is whether shallow clouds
in the tropics (which in general cool the Earth through radiation) will
disappear or not and make our planet even warmer - some models predict this
(!)

We are 100s of individuals from more than 30 national and international
partner institutions with planes, drones, ships, ground stations and
autonomous buoys trying to understand how and why these clouds form, how that
links to their environment, dust from Africa, the ocean current, the jetstream
aloft, etc. The positions of the different platforms can be seen live on the
main website and the data we are producing is appearing on there too.

If you have any questions about what we're doing I'd be very happy to help or
point you towards the right people :)

~~~
Angostura
I suppose my immediate question is - is there any way for an non-professional
with a pair of eyes and a smartphone to contribute in a crowd-sourcy way?

~~~
monkeynotes
Seems like a recipe for bad data and undiscoverable flaws.

~~~
derefr
Not really; you'd probably take the Folding@Home approach† to work
distribution: assign each small piece as a job to N non-trustworthy "workers"
(humans, computers), and then trust the results if all N results concur. If
they don't, fail the job back into the work queue to be tried again later with
different workers. (And maybe give the workers a reputation score, kicking out
the ones who participate in enough failed jobs.)

† does this general strategy have a name?

~~~
xvilka
Yes, it's called BOINC[1] platform. And as another comment mentioned there is
already a climate prediction project[2] based on that platform.

[1] [https://boinc.berkeley.edu/](https://boinc.berkeley.edu/)

[2] [https://www.cpdn.org](https://www.cpdn.org)

------
samatman
I'm reminded of Feynman's famous anecdote about the Millikan oil drop
experiment: Millikan underestimated the charge of the electron, and over the
ensuing years, subsequent measurements slowly but surely converged on the
correct value.

Why? Because experimenters who got the correct value figured it must be too
high, and ran the experiment again until they got a more-erroneous value, one
that was nonetheless higher. Eventually it worked itself out.

But climate modeling isn't measuring something objective and static like the
charge of the electron. It's prediction. I'm afraid that the incentives are to
credit models that predict more warming _just a bit_ more than those which
predict less; the expected effect would be that the predicted warming effect
would get larger over time.

Please note that I'm not calling climate science a "Cargo Cult", as Feynman
put it; I accept the basic premise of anthropogenic warming on first
principles, and see that historic measurements (not to speak of recent ones)
show a warming trend. There is cause to be concerned.

Nonetheless, it would be surprising if climate modeling, which is inherently
inexact and involves irreducible guesswork, _didn 't_ drift toward the more
alarming, due to similar social forces to those identified in Feynman's essay.

~~~
jellicle
So close, but not quite.

The oil drop results (Millikan was less than 1% off, by the way) show the
pressure on scientists to conform with the current status quo, the pressure
NOT to release shocking or unexpected results. In climate science, that means
underplaying the results, biasing them towards less catastrophic findings, and
there's a great deal of evidence that that is what has been happening. For
instance, the gold standard climate documents, the IPCC reports, represent a
consensus and therefore if 99% of scientists believe 100 units of climate
change is coming, and 1% of scientists believe no more than 30 units of
climate change is coming, 30 units is what is reported (the amount everyone
can agree on). This is a huge underreporting bias, only slowly corrected with
each new report.

Good on you for your scientific approach, you just basically reversed the
signs in your equation.

~~~
samatman
I've read the AR5 synthesis report, and your description is simply inaccurate.

To use your numbers, the IPCC reports that 99% of scientists believe 100 units
of climate change is coming, and 1% believe no more than 30.

It's less than 200 pages, I recommend actually reading it, rather than just
guessing how the sausage is made, as you've done here.

------
fabian2k
The title seems like clickbait, and the last part of the article does explain
that the scientists actually know that new cloud models are mostly responsible
for the change.

The big question is then of course whether the new cloud model is wrong and
the temperature increase therefore as well, or whether the new cloud model is
more accurate than previous ones and the temperature increase is a real
effect.

I found another article that looks at this in a bit more detail:

[https://news.ucar.edu/132678/ncars-new-climate-model-
running...](https://news.ucar.edu/132678/ncars-new-climate-model-running-hot)

The linked paper this is based on has the following as the last sentence:

> What scares us is not that the CESM2ECS is wrong (all models are wrong,
> [Box, 1976]) but that it might be right.

~~~
klodolph
Or a third, frustrating possibility—the new cloud model is more accurate, but
some other inaccuracy in the model used to be balanced out by the inaccurate
cloud model.

~~~
Accujack
Or that there are multiple inaccuracies in the model which interact, so
finding and correcting each one makes progress but still doesn't improve the
model overall.

~~~
cryptica
Having built some models to simulate very basic things myself, I've seen
first-hand how the slightest deviation of the model from reality can
completely invalidate the entire output of the model.

For this reason, I'm skeptical of models that try to simulate very complex
systems with a lot of variables and feedback loops. Models that have a large
number of variables are particularly difficult to get right because different
tiny mistakes in various parts of the model can compound and yield completely
arbitrary and contradictory results. Approximating the reality in software is
almost impossible.

~~~
willyt
It's not impossible. Listen to this podcast, it's a discussion about weather
forecasting models with the scientists that create them. They discuss model
verification for weather models and they touch how this also applies to
climate modelling. [http://omegataupodcast.net/326-weather-forecasting-at-the-
ec...](http://omegataupodcast.net/326-weather-forecasting-at-the-ecmwf/)

------
justadudeama
I am not a climate change denier by a long shot, but stories like these give a
ding to the credibility of climate scientists.

> "So we can't throw them out yet."

This might be an elementary view of science, but I think there is a danger
here that while everyone is making their models, if anyone is an outlier they
go and tweak their model to match the patterns of others: 'Klaus Wyser’s group
"switched off" some of the new cloud and aerosol settings in their model, he
said, and that sent climate sensitivity back down to previous levels'. That
seems to me a questionable reason to "switch off" part of the model - you
should create the most accurate simulation possible and trust the output, not
tweak the inputs to match literature data.

~~~
orev
Tweaking the inputs would help one to identify what factor is causing the
difference, which allows you to focus on that. It doesn’t mean you permanently
leave it out.

And it does not make a credibility issue. This is how science works — it is a
_process_ that strives to be as accurate as possible, not come up with a
static answer and stick to it (that’s what religion does).

The ability for science to change and adapt is what makes it so strong. That
is the message that needs to always be driven when discussing science; not
throwing hands in the air and saying “why do these scientists keep changing
their answers? They obviously don’t know what they’re doing”

~~~
protanopia
It certainly does hurt the credibility of people saying we need drastic
changes now based upon the models. If the answer might change next year, then
making a drastic change based upon the current projections seems foolhardy.

~~~
lucisferre
Yes it would be terribly foolhardy for us to stop polluting the atmosphere
prematurely.

~~~
zaroth
This isn’t really a helpful reply, because of course it’s not a question of
magically reducing pollution.

There are two basic modes of reducing pollution. Technological advancement,
and conservation.

In the case of technological advancement, you get less pollution per unit of
output as the same or lower cost. As long as capital is fairly cheap, these
advances tend to propagate quickly through a competitive market.

In the case of conservation, it’s more a question of which groups of people
should conserve (i.e. suffer) for this outcome, and by how much.

~~~
imtringued
Why do governments fail to take advantage of this opportunity to inject money
into their economy? Didn't Trump promise to bring the manufacturing jobs back?
How is he going to achieve that if he's not going to rebuild the current power
infrastructure or discourages companies from investing into the lucrative EV
market?

I'm seriously wondering why there is any reason to oppose technological
progress at all. What can they possibly gain by sticking to the old
technology? Who's going to benefit from something so short sighted?

------
adrianN
Well, politicians aren't doing anything anyway, whether the models predict
catastrophe or CATASTROPHE. Already according to the 3° sensitivity
predictions we would need an effort that rivals WW2 to stay below 1.5°. Yet
major countries are led by climate denialists.

~~~
derg
Can you even imagine how a Total War economy/society based on transitioning to
greener energies, cutting emissions and pollutants, and working on
improvements to housing and urban planning would end up looking?

Like ignoring the whole climate change thing for a moment (though we
absolutely should not do that), just the quality of life improvements to our
health and well being this kind of mobilization would bring would be
astonishing.

~~~
rayiner
> Total War economy/society > quality of life improvements to our health and
> well being this kind of mobilization would bring would be astonishing.

The impact on quality of life and society would be "astonishing," but they
won't be improvements. The Soviets and Chinese tried similar "mobilization[s]"
for food production. The idea was to direct society's efforts to producing
enough food for everybody. _Tens of millions of people_ died of starvation as
a result. It turns out that governments are bad at running economies.

I don't know why so many people think that the same _mechanism_ (a command-
and-control economy) will lead to a different result just because you change
the _goal_ from food or industrial production to climate change mitigation.

~~~
nesyt
Thanks for the straw man. American WW2 mobilization didn't kill ten million
people - that's not an intrinsic attribute of a country focusing on something.

Think also new deal / public works projects like the Hoover Dam (many died
working on the Dam but not because it was a government mobilization project).
Just the government spending a bunch of money on environmentally focused
projects could happen and could be good.

~~~
nate_meurer
It's not a straw man, and your examples are no more apt than Rayiner's.

America's WWII mobilization is really nothing like the Green New Deal. The
total cost of the U.S. war effort is estimated at around $300 B (adjusted for
2009 dollars) [1]. The lowest realistic estimates for the cost of an effective
Green New Deal are around double that amount _every year_ , and lasting for
decades [2].

It's true that WWII cost far more relative to GDP (over a third, versus 2% for
the New Green Deal estimate above), but expressing the cost relative to GDP is
not very useful in this context; in 1945 the U.S. was poised to enter a period
of ten percent annual GDP growth at a time that military spending was
plunging. The situation now is completely opposite; the U.S. will possibly
never sustain greater than 2% GDP growth, and the Green New Deal proposes to
pull money out of that for decades to come.

The character of WWII spending was also completely different. That money was
largely spent on things that were pretty much guaranteed to help the war
effort; materiel, industrial infrastructure, and troops. There was little risk
of misallocation.

In contrast, the Green New Deal is fraught with misallocation risk. In that
way, I suppose that a comparison to _modern_ military spending is actually
quite appropriate.

1 - [https://eh.net/encyclopedia/the-american-economy-during-
worl...](https://eh.net/encyclopedia/the-american-economy-during-world-war-
ii/)

2 - [https://newleftreview.org/issues/II112/articles/robert-
polli...](https://newleftreview.org/issues/II112/articles/robert-pollin-de-
growth-vs-a-green-new-deal)

------
allovernow
>The scientists went on to try 300 configurations of rain, pollution, and heat
flows—something they can do as gods of their own digital earth—before matching
the model to history.

Having worked with complex geologic (not climate) models in the past, this is
the part that gives me pause. The scientists have set out as a first principle
to _find warming_ and then are working backwards and, ostensibly, everything
is legitimate because model results are calibrated to previous real data.

But here's the problem. When you have complex, chaotic models with hundreds of
freely tweekable parameters, it's fairly easy to fit data and simultaneously
get any future prediction you (or your bias) want. Even when individually each
variable is within a reasonable range.

We arguably have proof of this happening - climate models have been
consistently overpredicting dT for what, 10 years now? There is an
institutional problem with climate science, in that there is no real penalty
for being wrong, and in fact the more aggressive results probably get the most
attention. Because the modeling is so far removed from any sort of
experimental or observational data collection, I think the field is
dangerously susceptible to institutional bias.

~~~
ilkan
As to your first point, I believe they are looking for the best fit to decades
of data, not to a single point in time. As to your second argument, both
historically and presently in science the tall nail gets hammered, it's a very
conservative field. They look for a consensus (agreed minimum warming of x)
rather than (an expected average warming of x).

------
nharada
It's disheartening to read some of the comments here. Scientists are basically
saying "we're not sure if it's going to be a disaster or a catastrophe", and
some folk's response seems to be "see! scientists don't know! why should we
listen to them?"

~~~
viburnum
Some people will do anything to change the subject when the subject makes them
uncomfortable. Better to quibble about models than to confront the disaster.

------
gbasin
Does anyone know if this is actually true? I was under the impression that
climate models have been mostly overshooting reality over the past 40 years

> One question modeling can help answer is called “climate sensitivity,” an
> estimate of how much warmer the planet will be once it has adjusted to
> atmospheric CO₂ at double the pre-industrial level. (At current rates, CO₂
> could reach a doubling point in the last decades of this century.) This is
> the old, reliable number that’s come out to 3°C for 40 years. It was as
> close as anything gets to certainty.

~~~
wbeckler
Here's a systematic comparison of climate model predictions vs reality, since
the 1970s. It turns out that the models have done a great job of predicting
reality. [https://www.carbonbrief.org/analysis-how-well-have-
climate-m...](https://www.carbonbrief.org/analysis-how-well-have-climate-
models-projected-global-warming)

I'd be curious where your impression comes from, in terms of what sources of
information you're receiving.

~~~
gbasin
I was thinking of the same data, I guess it's not quite as clear as I thought,
but the majority are overestimating the warming:
[https://www.carbonbrief.org/wp-
content/uploads/2017/10/Scree...](https://www.carbonbrief.org/wp-
content/uploads/2017/10/Screen-Shot-2017-10-05-at-16.49.21.png)

~~~
SiempreViernes
If the idea is that the error in estimation is random around 0, you would
expect about half to be overestimating.

I think 5 out of 8 is not a very strong difference from 4 out of 8, which is
the comparison that makes sense in this context.

------
qubex
It seems to me that the problem has never been a “lack of Science”, but rather
a lack of political wherewithal to actually implement the drastic, necessary
steps.

There’s probably been a collective tendency to (try) to view what was coming
our way through rose-tinted glasses, some unconscious effort to lowball the
projections in order to have a less catastrophic outlook. Maybe the computers
models are finally beginning to converge on a more realistic scenario as they
factor in the actual changes that have occurred so far.

It has never ceased to amaze me how we have oodles of science fiction films
that feature a lone astronomer spotting an incoming asteroid and that then
segue into the whole of humanity pulling together to build a fleet of
spacecraft to flee on or thermonuclear weapons to blast the thing out of the
sky with, but in reality we’ve had people warning us of approaching doom for
seventy years and haven’t managed much more than a collective “YOLO LOL”.

I have some experience in sensitivity analysis on stochastic systems such as
climate models, and it seems to me that feedback loops are probably becoming
increasingly tightly correlated, which in my field (macroeconomics) tends to
herald massive discontinuities.

I am not at all happy about this. At all.

------
giarc
If you are like me, you hate reading articles like this. You know there is a
problem but you feel like you can't do anything about it. You recycle, you
turn off lights, you have a programmable thermostat but you know it's a drop
in the ocean.

I finally decided to do something about it last fall. I researched and have
committed to purchasing green power. Every month I purchase 850 kWh for $22
from Bullfrog Power (a Canadian company, I have no affiliation). It's much
more reasonable than I thought. I still conserve as much as I can but
$22/month allows me to feel like I am doing something. If in 40 years, my kids
ask me what I did to prevent climate change, I feel like I'll have an answer
I'll be proud of.

~~~
0xffff2
There is a problem and _you_ can't do anything about it. We are way past the
point where individual action is going to cut it. You have to vote. _No other
action_ is going to have a meaningful impact and you shouldn't pretend
otherwise because it makes you feel better about yourself.

~~~
chrisco255
You going to vote out Xi Jinping?

~~~
WA
China is actually also doing a lot pro-climate. Also, reading this as a
German: I think the U. S. can do a lot first, before pointing their finger to
China. Same for Germany btw., because we have similar discussions here as well
like "why should we do anything? The US and China are the culprits".

You can follow this logic all the way down to an individual level.

If China doesn't do anyting, the US doesn't have to do anything either. If the
US doesn't do anything, Germany doesn't have to do anything either. If not
Germany, then not Munich. If not Munich, then not our little town. If not our
neighbor, then me neither.

Everybody and every country should do whatever they can. Will it be enough?
Probably not. But you gotta start where you actually have some control.

------
pjkundert
> Those now attempting to figure out the mystery of the hot climate models
> think one factor might have caused the recent unusual results: clouds. It
> turns out simulated clouds often cause headaches for climate modelers.

The impact of cloud cover in these models has been incorrect, and has such a
large impact. Doesn't this strike anyone as a major problem?

We're burning about 100 billion gallons of aviation fuel per year.

> This means each gallon of jet fuel (6.5lbs) will combine with 23lbs of
> Oxygen and turn into twenty pounds of CO2, and just over nine pounds of
> water! (see: [https://paullaherty.com/2015/01/10/calculating-aircraft-
> co2-...](https://paullaherty.com/2015/01/10/calculating-aircraft-
> co2-emissions/)).

So that's 100B gallons * 9lbs is about a half a billion metric tons of water
vapor going into the dry upper troposphere annually from commercial aviation.

Which, evidence would seem to suggest, has _not_ been modeled properly (at
all?) by these climate models?

If I was producing these models, I would be embarassed.

~~~
tomaskafka
Rough estimate: There are 1.4 × 10^17 liters of water in atmosphere
([https://whyfiles.org/2010/how-much-water-is-in-the-
atmospher...](https://whyfiles.org/2010/how-much-water-is-in-the-
atmosphere/index.html)).

Your number "about a half a billion metric tons" is 0.5 × 10^12 liters of
water, which is 5 orders of magnitude lower number. Or, less than 1/10 000 of
atmospheric water.

To say in your words, "If I was quoting this number as a significant
contribution, I would be embarassed."

~~~
pjkundert
The atmosphere at FL300 is _super_ cold and dry. Injecting water _there_ has
an enormous impact -- much greater than at lower altitudes, where the bulk of
atmospheric water resides.

------
sbussard
I'd like to know others' thoughts on this talk/discussion

[https://www.ted.com/talks/allan_savory_how_to_fight_desertif...](https://www.ted.com/talks/allan_savory_how_to_fight_desertification_and_reverse_climate_change/discussion?language=en)

~~~
andersha
legit. He's trying to mimic nature and keep the photosynthesis running by
using ruminants to speed up the decomposition of organic matter and by timely
management, have the regrowth sequester more atmospheric CO2 without
overgrazing and compromising the grass plant or ecosystem.

------
aazaa
It's surprising the article doesn't mention CFCs:

> The simulations showed that the rate of Arctic warming in a world without
> CFCs would be cut in half – a striking effect for a category of substances
> that are only present in small quantities to begin with. To ensure the
> result was not simply a quirk of the simulation, the researchers ran the
> experiment using two different climate models and arrived at a similar
> outcome.

[https://www.theglobeandmail.com/canada/article-cfcs-are-a-
ma...](https://www.theglobeandmail.com/canada/article-cfcs-are-a-major-driver-
of-arctic-warming-study-finds/)

The danger here is that there's something else we fundamentally don't
understand about the atmosphere.

------
pdkl95
Does anyone know if these models use floating point? If the do, are they
properly handling the many subtleties[1] of IEEE 754 (and other floating point
implementations)? Many years ago I read something about a model that produced
very different results depending on the hardware architecture. If a model is
sometimes chaotically sensitive to initial conditions, improper handling of
rounding could be catastrophic.

[1]
[https://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.h...](https://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.html)

~~~
cjbillington
No doubt they are using floats (well, doubles) - these models are usually
coupled partial differential equations, propagated forward through time over
the earth's surface using finite-difference or finite-element methods.

It's unlikely IMHO that floating point rounding oddities would cause
catastrophically erroneous results. In my experience from other physics
simulations, you usually validate some known behaviour you're not trying to
predict, e.g. that energy is conserved, or that total mass of fluid is
conserved. Bad numerics will usually violate these conservation laws, so you
can use the fact that they are conserved as some evidence that your numerics
are actually solving the differential equation relatively correctly.

Basically, people would notice broken numerics in this case.

There are situations where it is harder to validate numerics (e.g. if your
numerics _inherently_ conserve some quantity by construction, then you can't
use it to validate the behaviour of the numerics), and to be sure, a
concerning fraction of all publications with numerical results contain
mistakes.

But I don't think floating point rounding is near the top of the list of
issues to go looking for in these models.

------
jokoon
I live in a small, old apartment in the EU, without proper AC. I'm pretty
worried about the next summer. I can crash at a friend where the temperature
never went above 26C last summer, despite a heatwave.

I always hope that if heatwaves keep coming summer after summer,
governments/the UN will take tough decisions.

If nothing is done and summers are too hot, I clearly see people
protesting/striking/blocking roads/etc until governments concede. My biggest
fear are consumers that will refuse to adapt their consumption because they
will see this as unfair rich-vs-poor restrictions. People addicted to
consumerism would easily riot to denounce how capitalism ruined their living
standard.

~~~
HenryKissinger
You should get an AC unit. A window one if you have the right kind of window,
or a larger, mobile one.

~~~
danieldk
More AC units are going to make the problem worse as long as we are not using
solar/wind/hydro/nuclear-power.

Last summer when there was a heat wave here, lot of people bought ACs. Next
year, they are also switching them on when it's 30 degrees Celsius outside.

The irony.

------
sbussard
[https://www.ted.com/talks/allan_savory_how_to_fight_desertif...](https://www.ted.com/talks/allan_savory_how_to_fight_desertification_and_reverse_climate_change/discussion?language=en)

------
ipnon
The 27-model average referenced in this article is 3.86 degrees C.

------
GrumpyNl
Just a question, does the temperature of the core of the earth have any
influence?

~~~
strainer
Its a quite small influence, about 50 milliWatts per square meter iirc.
Overall we are well insulated from heat circulating inside the Earth (by miles
of rock) while hundreds of watts per square meter enters the atmosphere from
solar radiation.

------
bentona
Is it not possible to backtest these sorts of things? If it were, I would
assume results would be the first bullet point on articles like this, but I
also don't understand why it wouldn't be possible.

~~~
makomk
The article does sort of address this for one of the models: "The model run by
NCAR, one of American’s main climate-science institutions, started producing
unusual data last year while trying to reproduce the recent past. “We got some
really strange results,” Gettelman said. The scientists went on to try 300
configurations of rain, pollution, and heat flows—something they can do as
gods of their own digital earth—before matching the model to history. But by
solving that puzzle, Gettelman’s team sent future projections upward at an
unheard-of rate."

Basically, the backtesting failed to match reality for the recent past, they
tweaked parameters to get it to fit, and that produced surprisingly high
predictions for the future. I don't think that would leave them anything to
backtest on, since they'd used effectively all their historical data to fit
the model to.

------
mirthandmadness
Why the heck are we debating about 1 degree or 2 degrees or whatever. The
imperative should be to reduce emisssions as much as possible as soon as
possible.

~~~
yifanl
Its just easier to think about a concrete number.

------
trevyn
At the end of the article, apparently it has something to do with clouds.

~~~
docdeek
I’ve read a few times that clouds are a big problem for climate modelers as
they are far more complex in their implications for the climate than my grade
school planet heats > evaporation > cloud forms > rain falls understanding of
them suggests.

There’s a nice article here on the issue and frustration of clouds for climate
modelers by the head of the Royal Meteorological Society here:
[https://www.carbonbrief.org/guest-post-why-clouds-hold-
key-b...](https://www.carbonbrief.org/guest-post-why-clouds-hold-key-better-
climate-models)

~~~
mattrp
Yes water vapor specifically has been a big asterisk for a long time.

------
aszantu
wasn'T there something called global dimming which counters global warming?
Since we do filter out more of those particles, we allow for more global
warming?

------
iongoatb
...

~~~
screye
I don't see how you brought socialism into any of this.

Ironically, socialism is being sold as a solution that you yourself make very
clear. That, the pace of scientific progress is really fast ,and automation is
going to make a lot of jobs obsolete.

Socialism (in the nordic sense, ie. capitalism with social welfare) is being
proposed as a solution to rising inequality and unregulated for-profit forces
in the free market of industries where the consumer has no choice. (medicine,
education)

~~~
iongoatb
Unbelievable that people believe that the Nordic model of capitalism is
"socialism". Capitalism with social welfare is not socialism.

~~~
the_gastropod
Socialism isn't as narrow a term as you seem to think it is... It's quite a
broad concept that can (and does) coexist with Capitalism.

------
throw7363
Could it be a selection bias?

~~~
makomk
"In all, as many as a fifth of new results published in the last year have
come in with anomalously high climate sensitivity." The article suggests that
a consensus may well form around the new, higher estimates. So, quite
possibly.

------
trekrich
If they are based on models, then you can get any result you want!

------
grandridge
Not a good title when the "science is settled"

------
vincent-toups
I guess climate scientists don't use version control?

~~~
norswap
The article isn't very precise, but my understanding was that the run some
kind of machine learning based on past data. Adding in the more recent data
changed the predictions dramatically.

So it's not an issue of versioning (I assume they could reproduce the old
results using the old data).

~~~
whatshisface
It's not machine learning, it's a physical model. Computers solve a big
differential equation that takes in all of the physical things we know about
the Earth's climate system and runs them forward in time. The increase in
thermal predictions are due to changes in the cloud and aerosol models which
were made due to an improved understanding of the physics involved.

~~~
cultus
The line can be a bit blurry, because they are actually running inverse
problems with the PDEs to fit the data. This needs regularization just like
statistical ML models. Usually this amounts to solving an iterated least
square problem, just like logistic regression. Bayesian methods are becoming
more popular, though.

~~~
dls2016
> because they are actually running inverse problems with the PDEs to fit the
> data

Could you explain this a bit more? Are you talking about data assimilation?

~~~
cultus
Yes, that's right. The issue is that systems like these have a lot of free
parameters that have to be estimated from the data. This is basically because
you have to make assumptions if you don't want to simulate Earth's systems
down to the subatomic level. The inferred values of these parameters are
usually very important as well for interpretation.

All PDEs are solved numerically by discretizing them into linear or nonlinear
systems. If it's convex enough, Tikhonov regularization is often used.

Linear PDEs, where the solution depends only linearly on its derivatives, can
be discretized into matrices. This gives a system like A m = d, where A is the
discretized PDE, m is the "model" or parameter values, and d is the data. This
is usually over or under-determined from the data, so it has to be solved by
least squares. Since the resulting system is usually almost singular,
regularization is applied, usually by penalizing the L2 norm of the model:

min || A m -d || + r ||m||^2

If it's nonlinear but convex enough, one can just solve it by fixed point
iteration, with the above linear equation being solved at every step (Newton's
method often doesn't work well). If it's too nonconvex, then MCMC or other
Bayesian methods are better, since a single solution is useless if the
parameter values could plausibly around widely separated minima.

------
zmoreira
I saw that chart in the article and thought "the predicted warming correlates
with the level of wokeness of the country" From Russia 1.83 to Canada 5.64.

------
novaRom
"You are in private mode. Subscribe to continue reading." Ok, that's one more
I will not open anymore; seems Bloomberg started using similar "privacy mode"
detection as NYT.

~~~
saamm
If you happen to be on Firefox, you can use this extension to get around it:

[https://addons.mozilla.org/en-US/firefox/addon/temporary-
con...](https://addons.mozilla.org/en-US/firefox/addon/temporary-containers/)

------
macinjosh
scientific models != scientific facts.

They are educate guesses or educated estimates to be more charitable. Our
computing capabilities are much too weak to accurately model systems as
complex as the entire earth's climate.

------
lazyjones
Because they're made by alarmists who are trying to increase political
pressure.

------
tu7001
Hold my beer :)
[http://climatechangereconsidered.org/](http://climatechangereconsidered.org/)

------
aldoushuxley001
Scientists making the models prly thought the politicans needed a helping
hand.

------
chrisco255
A model isn't reality. A lot of climate research is based entirely on
experimenting with these climate models. Of course, the climate is a non-
linear dynamic system, so even if you had a perfect model (we don't), if your
input parameters were off by the slightest bit, reality would veer off wildly
from your prediction within a short time. This is why weather forecasts don't
work beyond 10 days.

~~~
danieldk
_A lot of climate research is based entirely on experimenting with these
climate models._

We have a lot of data measured at many points on Earth spanning many decades.
The data clearly shows that our planet is warming up and that there is a
strong correlation with greenhouse gasses. One can extrapolate from these data
points with certain reliability.

What is hard is to take into account are tipping points (which is why the IPCC
excludes them in their projections), such as the effects of methane release
from warming tundra soil. As far as I understand, most known possible tipping
points only make things worse, not better.

At this point the question is not if climate change is happening (there is
near universal agreement on that among climatologists), but whether it will be
_bad, but manageable_ , _it will be ugly_ , or _life-threatening to mankind_.
In any of these cases, we have to act now.

~~~
chrisco255
We have data that shows warming in the early 20th century, cooling in the mid
20th century (through the 70s) and warming in the decades after that. CO2 ppm
was increasing steadily through those ups and downs, so it's not correlated
perfectly. Meanwhile there are natural phenomenon like the Atlantic Multi-
decadal Oscillation, the Pacific Decadal Oscillation, ENSO, NAO, etc that also
correlate quite well with climate change.

In the terms of "bad, unmanageable" climate change, I would invite you to
research the early Holocene, which had temps as much as 7 degrees hotter than
modern temps. The early Holocene began about 12K years ago and ended about 6K
years ago. The warm temperatures correlate with boom times for humanity.

See: Early Holocene Temperature Oscillations Exceed Amplitude of Observed and
Projected Warming in Svalbard Lakes

[https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/201...](https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL084384)

------
lbsnake7
I’m a climate change skeptic almost entirely because I don’t trust models. I
believe there are too many dynamic things happening in the world for anyone to
be able to predict accurately say the next 100 years (solar, earthquakes,
volcanoes etc). One way to make me a believer though is an experiment: if I
were to give you a 100 year stretch of history and you were able to accurately
predict with the models what exactly happened in those 100 years.

The article talks about it a little bit about how the models are used to
predict the 19th century to see if they are correct. But the models use the
last 100 years as input so of course it will give you accurate output. But the
real challenge of the models would be to accurately predict things that are
not part of the inputs into the model. I don’t believe that these models can
do this and are thus an exercise in straight extrapolation based on very
complex and interconnected inputs.

~~~
jknoepfler
So if I asked you to bet at 50/50 odds that next year would be colder on
average than this year, you'd take the bet?

~~~
lazyjones
That's not what climate is about. Also, it depends on location, in many places
it was colder in 2019 than in 2018. If you're talking about some calculated
"global" temperature, it doesn't exist in a valid form.

~~~
bannable
Are you claiming that it is not possible to find a trend in a mean temperature
of a great many points across the globe, over a long period of time?

What makes such a measurement an "invalid form"?

~~~
lazyjones
It is not possible if there aren't valid temperature measurements available
for all points throughout the measured period of time, so that many
temperatures are "interpolated", estimated etc.

~~~
bannable
Except that we do have a massive number of recorded temperatures across a
massive number of locations in the last 100 years. Climate models, some dating
back to the 1970s, have correctly predicted global temperature changes in the
50 years since based on this data.

The measurements are real, and there is an established history of the models
being generally correct (if not in specific details) by now. Climate study is
not the new science you seem to think it is.

~~~
lazyjones
> _Climate models, some dating back to the 1970s, have correctly predicted
> global temperature changes in the 50 years since based on this data._

Can you point me to one such model? One that actually predicted temperatures
correctly back in the 1970s and not after various recent "adaptations" like
"corrected" emission data?

> _The measurements are real_

Yes, measurements are real. Interpolations, resulting "global" temperatures
and predictions aren't.

------
GrayTextIsTruth
So, holistically, it would seem like warming (a fever) or Coronavirus (anti-
bodies) is part of the planets immune system, but humans are too advanced.

~~~
ddalex
Let's not anthropomorphize things, they don't like it.

~~~
GrayTextIsTruth
Animals have immune systems too. It’s not a phenomenon unique to humans, as
Anthropomorphism would suggest.

> they don’t like it

Who? HNers? I don’t care. I think it more that people don’t like seeing
themselves as the virus or cancer, when we could easily change our behavior
and we wouldn’t be.

