'I thought climate change was a hoax. Now I've changed my mind'(bbc.com)
bbc.com
'I thought climate change was a hoax. Now I've changed my mind'
https://www.bbc.com/news/science-environment-67483064
19 comments
She changed her tribe. Until her whole ex-peer group believes, changing her mind hardly helps. From article:
influenced by friends at church in the US south. I spent years doubting the science of climate change and spending time with people who didn't believe in the science either.
* To move away from those people meant leaving behind an entire community *> influenced by friends at church in the US south
The article doesn't really touch on this much.
I don't know what church culture is like outside the U.S. South, but here in the South its... weird. It's not like Donald Trump is a holy figure or anti-vax is scripture, but at the same time political memes and secular conservative culture have become remarkably entwined with the religious side. Obviously church has a long (sometimes problematic) history in U.S. Southern culture, but not quite like this. Not at such scale, diverging from the central moral/religious teachings and the culture of southern hospitality so much.
This Atlantic piece is based in Michigan, but it similar to what I've seen in the states between Texas and Florida:
https://www.theatlantic.com/magazine/archive/2022/06/evangel...
The article doesn't really touch on this much.
I don't know what church culture is like outside the U.S. South, but here in the South its... weird. It's not like Donald Trump is a holy figure or anti-vax is scripture, but at the same time political memes and secular conservative culture have become remarkably entwined with the religious side. Obviously church has a long (sometimes problematic) history in U.S. Southern culture, but not quite like this. Not at such scale, diverging from the central moral/religious teachings and the culture of southern hospitality so much.
This Atlantic piece is based in Michigan, but it similar to what I've seen in the states between Texas and Florida:
https://www.theatlantic.com/magazine/archive/2022/06/evangel...
I'm surprised that you're surprised.
Southern Christianity has always reached deep into secular politics and government. The entire Southern Baptist religion was founded to protect slavery, which certainly isn't an imperative from scripture.
I believe you that things are changing and perhaps becoming less subtle, but there never was a strong connection between Christian scripture and the behavior of Southern Christians.
Southern Christianity has always reached deep into secular politics and government. The entire Southern Baptist religion was founded to protect slavery, which certainly isn't an imperative from scripture.
I believe you that things are changing and perhaps becoming less subtle, but there never was a strong connection between Christian scripture and the behavior of Southern Christians.
Yeah, but its so... secular now. And blunt. I can't believe how direct some of my family+acquaintances are now in their mixed up religious/political talk, it's totally out of character.
Instead of being introduced as a pretense, its like the fundamental religious pretense is getting thrown out, along with the tendency to use euphemisms.
Instead of being introduced as a pretense, its like the fundamental religious pretense is getting thrown out, along with the tendency to use euphemisms.
"I was in middle school in the late 1990s and I read an article about rising temperatures."
I also read about rising temperatures as far back as the 70s. There were decades where the temperate never rose. But this is cherry-picked and ignored in articles like this.
The goal post keeps moving and we still aren't under water. Wealthy people and insurance companies still insure houses on the coasts. When you follow the people that want to protect their own interests (especially money), you get closer to the truth.
This entire article is about someone that was a 'denier' based on nothing but religious reasons and now believes in climate change..still not based on science , facts, or critical thinking.
"An independent enquiry cleared the UEA scientists of wrongdoing and concluded that "their rigour and honesty are not in doubt"."
I stopped reading here. It was in doubt and should be. Lots of universities apologized after climate gate because they were, in fact, using the same exact, data. The emails leaked were also damning.
This should have been a moment where we opened our eyes to how easy data can be manipulated and attempt to get the actual truth. Instead? Unless you are stating that climate change is 100% real and go along with the status quo, you will be banned, ignored, and in some cases, lose your job.
This is the exact opposite of science and is the definition of anti-intellectual.
Update: Downvotes on this proved my point. Thank you.
I also read about rising temperatures as far back as the 70s. There were decades where the temperate never rose. But this is cherry-picked and ignored in articles like this.
The goal post keeps moving and we still aren't under water. Wealthy people and insurance companies still insure houses on the coasts. When you follow the people that want to protect their own interests (especially money), you get closer to the truth.
This entire article is about someone that was a 'denier' based on nothing but religious reasons and now believes in climate change..still not based on science , facts, or critical thinking.
"An independent enquiry cleared the UEA scientists of wrongdoing and concluded that "their rigour and honesty are not in doubt"."
I stopped reading here. It was in doubt and should be. Lots of universities apologized after climate gate because they were, in fact, using the same exact, data. The emails leaked were also damning.
This should have been a moment where we opened our eyes to how easy data can be manipulated and attempt to get the actual truth. Instead? Unless you are stating that climate change is 100% real and go along with the status quo, you will be banned, ignored, and in some cases, lose your job.
This is the exact opposite of science and is the definition of anti-intellectual.
Update: Downvotes on this proved my point. Thank you.
People are free to believe whatever they want. I have no problem with that. But the time where denying climate change was easy because visible signs were weak, trends too shallow, effects basically invisible, is coming to an end.
I have lived 50+y in my home country, the NL. And starting (I'd say roughly 10y ago), I can see weather patterns changing with my own eyes.
'Tropical' ~20°C nights in summer were once rare. Often a whole year would pass without one. Now: I have experienced these year-on-year, sometimes 4..5 nights in a row. Or in multiple events across summer. Would expect such nights to re-occur next year with confidence.
The past month, it has been raining solid. Every single day. Can't remember ever having seen that before. This was 1 prediction from climate models btw: winters in the NL getting wetter.
Fall / early winter storms: nothing special here. Used to be: 1 or 2 days storm, then quiet again.
Past month: almost every day strong winds. Day before yesterday it was like storm. Many fallen tree branches on the roads. Just 1 week before, similar.
No pause, strong winds keep going.
Some news items this year: the Canada wildfires, around Phoenix (AZ) cacti losing limbs from the heat stress, people getting 2nd/3rd burns simply because they fell on glowing hot asphalt. Multiple sustained heatwaves in many areas around the world. 'Winter' in Latin America being warmer / much longer than before. The list goes on & on.
At this point, imho the only people denying climate change are stupid, brainwashed, have blindfolds on somehow, or don't want to know it. Whatever.
But it is. So obvious to see. Becoming more obvious & less subtle with each day that passes, and each megaton of CO2 humanity adds to the atmosphere.
Be an idiot if you want, I don't care. Just don't get in the way of people working to tackle the problem.
I have lived 50+y in my home country, the NL. And starting (I'd say roughly 10y ago), I can see weather patterns changing with my own eyes.
'Tropical' ~20°C nights in summer were once rare. Often a whole year would pass without one. Now: I have experienced these year-on-year, sometimes 4..5 nights in a row. Or in multiple events across summer. Would expect such nights to re-occur next year with confidence.
The past month, it has been raining solid. Every single day. Can't remember ever having seen that before. This was 1 prediction from climate models btw: winters in the NL getting wetter.
Fall / early winter storms: nothing special here. Used to be: 1 or 2 days storm, then quiet again.
Past month: almost every day strong winds. Day before yesterday it was like storm. Many fallen tree branches on the roads. Just 1 week before, similar.
No pause, strong winds keep going.
Some news items this year: the Canada wildfires, around Phoenix (AZ) cacti losing limbs from the heat stress, people getting 2nd/3rd burns simply because they fell on glowing hot asphalt. Multiple sustained heatwaves in many areas around the world. 'Winter' in Latin America being warmer / much longer than before. The list goes on & on.
At this point, imho the only people denying climate change are stupid, brainwashed, have blindfolds on somehow, or don't want to know it. Whatever.
But it is. So obvious to see. Becoming more obvious & less subtle with each day that passes, and each megaton of CO2 humanity adds to the atmosphere.
Be an idiot if you want, I don't care. Just don't get in the way of people working to tackle the problem.
> There were decades where the temperate never rose.
What, you expect a perfect line without variation? Accumulating a lot of cumulative temperature increase is the signal we're looking for...
> The goal post keeps moving and we still aren't under water.
Significant sea level rise has always been decades out.
You look back to early 80's papers, and the consensus was that you'd get 13-55cm of sea level rise by 2025; we've gotten about 15cm (a bit above the low end of the range), but the current slope is now pretty close to the middle of the range.
https://www.google.com/books/edition/Projecting_Future_Sea_L...
What, you expect a perfect line without variation? Accumulating a lot of cumulative temperature increase is the signal we're looking for...
> The goal post keeps moving and we still aren't under water.
Significant sea level rise has always been decades out.
You look back to early 80's papers, and the consensus was that you'd get 13-55cm of sea level rise by 2025; we've gotten about 15cm (a bit above the low end of the range), but the current slope is now pretty close to the middle of the range.
https://www.google.com/books/edition/Projecting_Future_Sea_L...
You’re absolutely right! It feels like an appeal to emotion more than any academic revelation. And the “rigor and honesty are not in doubt” part… really the conclusion of that episode was the beginning of the end of “trust the science!” for me.
I think the saying is “don’t piss on my leg and tell me it’s raining”. Since then things have only gotten worse. In the climate industry you publish or you starve and you can only publish if your paper agrees with the “narrative” not where science leads you.
And computer scientists like myself are told computer models are the gold standard of climate prediction but I know that’s technically absurd!
Computers are complete garbage at predicting! Even things you have control over! It’s just math, it’s not magic. You would have to disbelieve the domain of math “chaos” which was founded based on climate studies!
When I point that out I’m told I just am not smart enough to understand, and neither is anyone in the debate stage, we just need to trust the science.
We’re well into emperor’s new clothes territory and anyone pointing this out is not debated with but given a high tech lynching.
This really is the dark age of science. I would love for someone to explain to me the usefulness of climate models that are always wrong, that require constant variable clamps and run out of control without exception.
Reviewing climate model code should give anyone a great deal of concern that anything is derivative of that garbage.
I think the saying is “don’t piss on my leg and tell me it’s raining”. Since then things have only gotten worse. In the climate industry you publish or you starve and you can only publish if your paper agrees with the “narrative” not where science leads you.
And computer scientists like myself are told computer models are the gold standard of climate prediction but I know that’s technically absurd!
Computers are complete garbage at predicting! Even things you have control over! It’s just math, it’s not magic. You would have to disbelieve the domain of math “chaos” which was founded based on climate studies!
When I point that out I’m told I just am not smart enough to understand, and neither is anyone in the debate stage, we just need to trust the science.
We’re well into emperor’s new clothes territory and anyone pointing this out is not debated with but given a high tech lynching.
This really is the dark age of science. I would love for someone to explain to me the usefulness of climate models that are always wrong, that require constant variable clamps and run out of control without exception.
Reviewing climate model code should give anyone a great deal of concern that anything is derivative of that garbage.
You've written a dense "paragraph" that doesn't really lead itself to argument or even... reading it.
> You would have to disbelieve the domain of math “chaos” which was founded based on climate studies!
Actually, it was just Lorenz's work on garden-variety weather forecasting with computers that accidentally identified that many processes are chaotic. Not climate studies.
But chaos often doesn't affect long term predictions of characteristics like averages and periodic variation in a system. Whether it will rain on July 4, 2025 is foiled by chaos; whether it will rain less in July 2025 than in February 2025 here less so; whether it will rain less on average in Julys for the next decade than Februarys basically has nothing to do with chaos.
(It doesn't rain much in July here, so those answers are pretty much -- probably not, very likely, almost certainly).
> You would have to disbelieve the domain of math “chaos” which was founded based on climate studies!
Actually, it was just Lorenz's work on garden-variety weather forecasting with computers that accidentally identified that many processes are chaotic. Not climate studies.
But chaos often doesn't affect long term predictions of characteristics like averages and periodic variation in a system. Whether it will rain on July 4, 2025 is foiled by chaos; whether it will rain less in July 2025 than in February 2025 here less so; whether it will rain less on average in Julys for the next decade than Februarys basically has nothing to do with chaos.
(It doesn't rain much in July here, so those answers are pretty much -- probably not, very likely, almost certainly).
> You've written a dense "paragraph" that doesn't really lead itself to argument or even... reading it.
Writing on some mobile devices does not lend itself to proper formatting. I tend to write when and where I feel compelled to write, I apologize for the difficulty reading.
I asked a few questions there that should be compelling. "Why do we trust computer models?" is a central one. "How can be be unbiased with publish or perish?" is another.
I'm not sure why you clamped onto "climate" vs "weather" in chaos. Chaotic variables stack over iterations, it's the entire basis for the butterfly effect, and yes, that does have follow on effect to the climate at large. Climate models themselves are VERY subject to initial state, this again is characteristic of a chaotic system. And just because Lorenz worked on weather does not make chaos theory _not_ a major, if not the biggest, contributor to climate science.
> But chaos often doesn't affect long term predictions of characteristics like averages and periodic variation in a system.
That's a very bold statement with no way to falsify it. I think it's better stated "we currently don't possess enough computing power to accurately predict climate long term".
Wouldn't it be a shame if compounded variables DID in fact have an effect on long term climate? Which they clearly MUST since there's an actual mechanism vs. "ahh it just kinda averages together so we don't have to worry about it". All changes have a follow on change in a block universe, you can't just average them out in a 64bit float and stick a clamp function on it to stop it from going out of control. Which is EXACTLY what climate models do.
Writing on some mobile devices does not lend itself to proper formatting. I tend to write when and where I feel compelled to write, I apologize for the difficulty reading.
I asked a few questions there that should be compelling. "Why do we trust computer models?" is a central one. "How can be be unbiased with publish or perish?" is another.
I'm not sure why you clamped onto "climate" vs "weather" in chaos. Chaotic variables stack over iterations, it's the entire basis for the butterfly effect, and yes, that does have follow on effect to the climate at large. Climate models themselves are VERY subject to initial state, this again is characteristic of a chaotic system. And just because Lorenz worked on weather does not make chaos theory _not_ a major, if not the biggest, contributor to climate science.
> But chaos often doesn't affect long term predictions of characteristics like averages and periodic variation in a system.
That's a very bold statement with no way to falsify it. I think it's better stated "we currently don't possess enough computing power to accurately predict climate long term".
Wouldn't it be a shame if compounded variables DID in fact have an effect on long term climate? Which they clearly MUST since there's an actual mechanism vs. "ahh it just kinda averages together so we don't have to worry about it". All changes have a follow on change in a block universe, you can't just average them out in a 64bit float and stick a clamp function on it to stop it from going out of control. Which is EXACTLY what climate models do.
> I'm not sure why you clamped onto "climate" vs "weather" in chaos.
Because you (falsely) said that Lorenz was studying climate when he discovered chaos; instead, he was studying medium-term weather forecasting.
> That's a very bold statement with no way to falsify it.
https://en.wikipedia.org/wiki/Lorenz_system#/media/File:A_Tr...
If we look at Lorenz attractors, which is where you're pointing... note that the overall means, typical period, etc, of this system are stable. But predicting exactly where we'll be a moderate number of timesteps out is hard. That's what chaos does-- it's all about dense periodic orbits in state, and that's where the sensitivity in initial conditions comes from.
> I think it's better stated "we currently don't possess enough computing power to accurately predict climate long term".
We have enough computing power to produce pretty good climate predictions: predictions of long term averages.
Chaos means we don't have enough sensing, nor could we ever have enough sensing, to predict weather in the intermediate term.
These are different things.
Because you (falsely) said that Lorenz was studying climate when he discovered chaos; instead, he was studying medium-term weather forecasting.
> That's a very bold statement with no way to falsify it.
https://en.wikipedia.org/wiki/Lorenz_system#/media/File:A_Tr...
If we look at Lorenz attractors, which is where you're pointing... note that the overall means, typical period, etc, of this system are stable. But predicting exactly where we'll be a moderate number of timesteps out is hard. That's what chaos does-- it's all about dense periodic orbits in state, and that's where the sensitivity in initial conditions comes from.
> I think it's better stated "we currently don't possess enough computing power to accurately predict climate long term".
We have enough computing power to produce pretty good climate predictions: predictions of long term averages.
Chaos means we don't have enough sensing, nor could we ever have enough sensing, to predict weather in the intermediate term.
These are different things.
> Chaotic variables stack over iterations, it's the entire basis for the butterfly effect, and yes, that does have follow on effect to the climate at large. Climate models themselves are VERY subject to initial state
I took a semester-long course in chaotic dynamical systems, and one of the insights I got from that is that initial state is most important at edges[1]. Attractors can pull fairly broad initial states to the same course, and the opposite of attractors[1] can cause huge divergences in trajectory[1] of some very close initial states. This makes it practically impossible to determine which deviations of initial states are important, without iterating the model, but it definitively does not mean that all deviations in initial states are important.
[1] - It's been over ten years and nomenclature has never been my strength, so pardon the names I'm using to refer to these technical ideas.
> > But chaos often doesn't affect long term predictions of characteristics like averages and periodic variation in a system.
> That's a very bold statement with no way to falsify it. I think it's better stated "we currently don't possess enough computing power to accurately predict climate long term".
Supporting evidence is gained by reanalyzing old models, and comparing them to each other and the current state. This can show that even old models run on much slower computers still often gave decent predictions within their limitations: https://eapsweb.mit.edu/news/2019/historical-climate-models-...
: the performance of these models could now be assessed for their accuracy. Enough time had likely passed since these historical projections were published that their warming signals would have emerged, and we could now evaluate them against several decades of global temperature measurements.
: The first result we found is that all of the 17 models correctly projected global warming (as opposed to either no warming or even cooling). While this is so unsurprising to climate scientists that it is not even mentioned in the paper, it may be surprising to non-experts. The second result is that most of the model projections (10 out of 17) published between 1970 and 2000 produced global average surface warming projections that were quantitatively consistent with the observed warming rate.
> Wouldn't it be a shame if compounded variables DID in fact have an effect on long term climate?
: simply comparing the warming rates between simulations and reality could be misleading, if the simulated emissions scenario and historical emissions were dramatically different. To account for differences in emissions between the simulations and reality, we calculated the warming rates with respect to anthropogenic radiative forcing, the rate at which human emissions trap energy at Earth’s surface, instead of calculating them with respect to time. Using this novel metric of the warming rate, we found that the model projections were even more consistent with reality (14 out of 17 models captured this).
(Emphasis mine, to address your point about initial states and stacking over iterations. While climate projections may be incorrect because human emissions aren't fully predictable over decades, the models themselves, when these variations are input, seem to do an okay job of modeling the basic physical parameters they incorporate, at least at the global scale.)
> Climate models themselves are VERY subject to initial state
: Additionally, climate science is based on more than just state-of-the-art computer models: measurements of the present climate, paleoproxy evidence from past climates, and fundamental theory provide additional constraints on future warming and bolster our confidence in the field’s findings. However, future climate change will not be experienced the same around the world—this is next frontier for climate researchers. Climate impacts are nuanced and are experienced at smaller, regional scales, for which different models often still disagree.
I took a semester-long course in chaotic dynamical systems, and one of the insights I got from that is that initial state is most important at edges[1]. Attractors can pull fairly broad initial states to the same course, and the opposite of attractors[1] can cause huge divergences in trajectory[1] of some very close initial states. This makes it practically impossible to determine which deviations of initial states are important, without iterating the model, but it definitively does not mean that all deviations in initial states are important.
[1] - It's been over ten years and nomenclature has never been my strength, so pardon the names I'm using to refer to these technical ideas.
> > But chaos often doesn't affect long term predictions of characteristics like averages and periodic variation in a system.
> That's a very bold statement with no way to falsify it. I think it's better stated "we currently don't possess enough computing power to accurately predict climate long term".
Supporting evidence is gained by reanalyzing old models, and comparing them to each other and the current state. This can show that even old models run on much slower computers still often gave decent predictions within their limitations: https://eapsweb.mit.edu/news/2019/historical-climate-models-...
: the performance of these models could now be assessed for their accuracy. Enough time had likely passed since these historical projections were published that their warming signals would have emerged, and we could now evaluate them against several decades of global temperature measurements.
: The first result we found is that all of the 17 models correctly projected global warming (as opposed to either no warming or even cooling). While this is so unsurprising to climate scientists that it is not even mentioned in the paper, it may be surprising to non-experts. The second result is that most of the model projections (10 out of 17) published between 1970 and 2000 produced global average surface warming projections that were quantitatively consistent with the observed warming rate.
> Wouldn't it be a shame if compounded variables DID in fact have an effect on long term climate?
: simply comparing the warming rates between simulations and reality could be misleading, if the simulated emissions scenario and historical emissions were dramatically different. To account for differences in emissions between the simulations and reality, we calculated the warming rates with respect to anthropogenic radiative forcing, the rate at which human emissions trap energy at Earth’s surface, instead of calculating them with respect to time. Using this novel metric of the warming rate, we found that the model projections were even more consistent with reality (14 out of 17 models captured this).
(Emphasis mine, to address your point about initial states and stacking over iterations. While climate projections may be incorrect because human emissions aren't fully predictable over decades, the models themselves, when these variations are input, seem to do an okay job of modeling the basic physical parameters they incorporate, at least at the global scale.)
> Climate models themselves are VERY subject to initial state
: Additionally, climate science is based on more than just state-of-the-art computer models: measurements of the present climate, paleoproxy evidence from past climates, and fundamental theory provide additional constraints on future warming and bolster our confidence in the field’s findings. However, future climate change will not be experienced the same around the world—this is next frontier for climate researchers. Climate impacts are nuanced and are experienced at smaller, regional scales, for which different models often still disagree.
From what I read about "climate gate", I took home:
The "data manipulation" was the use of standard data analysis tactics on genuine data. Yes, everyone "used the same data" because the data was good. The data analysis was also fine, it's just that a bunch of partisans saw the word "trick" and thought "lie".
The "data manipulation" was the use of standard data analysis tactics on genuine data. Yes, everyone "used the same data" because the data was good. The data analysis was also fine, it's just that a bunch of partisans saw the word "trick" and thought "lie".
I too believe in climate change, but there is an insane amount of FUD and missinfo supporting it. I have seen so many smart and detail oriented people become more skeptical over time due to sloppy facts or "well intended" lies.
The latest fad seems to be making claims are specific weather events are attributable to climate change using methods that would make any real statistician scream.
The latest fad seems to be making claims are specific weather events are attributable to climate change using methods that would make any real statistician scream.
> The latest fad seems to be making claims are specific weather events
I read these same news articles, and usually they're quoting a scientist saying that no specific "weather event" can be attributed to climate change, but that a general increase in severity or fluctuations between extremes is likely the result of climate change.
Why the heck do supposedly "smart and detail oriented" people pay more attention to scare quotes from journalists and policy makers than to nuanced quotes from actual scientists?
https://eapsweb.mit.edu/news/2019/historical-climate-models-...
> Climate impacts are nuanced and are experienced at smaller, regional scales, for which different models often still disagree. This is because different models may contain slightly different characterizations of the Earth’s physics, particularly small-scale features that do not last long but can make a big impact, like clouds. These slight differences in calculations, when spread over time and space, have the potential to cancel out or amplify other climate effects.
> The results from this paper increase our confidence in climate models in that they have accurately projected the most basic climate metric through history: global warming. By many measures, today’s climate models are much more useful and skillful than the historical models reviewed here. This adds to our confidence in today’s state-of-the-art model projections, which climate scientists will continue to improve upon and use to pin down the specifics of climate change’s effects.
I read these same news articles, and usually they're quoting a scientist saying that no specific "weather event" can be attributed to climate change, but that a general increase in severity or fluctuations between extremes is likely the result of climate change.
Why the heck do supposedly "smart and detail oriented" people pay more attention to scare quotes from journalists and policy makers than to nuanced quotes from actual scientists?
https://eapsweb.mit.edu/news/2019/historical-climate-models-...
> Climate impacts are nuanced and are experienced at smaller, regional scales, for which different models often still disagree. This is because different models may contain slightly different characterizations of the Earth’s physics, particularly small-scale features that do not last long but can make a big impact, like clouds. These slight differences in calculations, when spread over time and space, have the potential to cancel out or amplify other climate effects.
> The results from this paper increase our confidence in climate models in that they have accurately projected the most basic climate metric through history: global warming. By many measures, today’s climate models are much more useful and skillful than the historical models reviewed here. This adds to our confidence in today’s state-of-the-art model projections, which climate scientists will continue to improve upon and use to pin down the specifics of climate change’s effects.
I don't disagree and think that illustrates my point.
If you're used to one or two levels of exaggeration or deception from alleged authorities like politicians, news, or other groups, then you start to discount everything you hear on the topic.
The even bigger problem comes up for some people is that if every claim you investigate is false, why think the primary science is free from lies and exaggeration just because you can't repeat the work.
Like I said, I personally believe in climate change in general, but have seen a ton of bad primary science in the areas I am capable of scrutinizing.
As a result, my default assumption is that the field is toxic and news is more likely to distort than enlighten.
If you're used to one or two levels of exaggeration or deception from alleged authorities like politicians, news, or other groups, then you start to discount everything you hear on the topic.
The even bigger problem comes up for some people is that if every claim you investigate is false, why think the primary science is free from lies and exaggeration just because you can't repeat the work.
Like I said, I personally believe in climate change in general, but have seen a ton of bad primary science in the areas I am capable of scrutinizing.
As a result, my default assumption is that the field is toxic and news is more likely to distort than enlighten.
So the question a skeptic should answer is what would be preventing this increase if climate change was a hoax?