Having worked in data science you just described all of science. It's extremely difficult to get good data so you can build decent models. Weather forecasting abd climate science will always be wrong.
Fuck, this reminded me of a PHD student I tried to help with their thesis project. It was apparently too hard to get good data for their proposed model (lazy & would take time). So, find any old data and jam it into their model and voila, thesis done. I stopped helping before that point.
It’s honestly not his fault either. Science is publish or die these days. Taking your time to craft an excellent paper is rewarded less than the shotgun approach of firing off like 15 that barely meet the most basic requirements
Dr. Mototaka Nakamura (nasa jpl, mit, international pacific research center, etc) wrote a book a year or two ago called “confessions of a climate scientist” that basically explains how climate modeling is complete junk science and that there are very many important aspects to the climate that we barely understand at all and don’t even include in modeling. Most of the book is in Japanese, but he goes over the important stuff in English. Think it costs $1 on kindle, well worth the read.
It seems like it ought to be possible, but Navier-Stokes shows that you simply cannot.
If you don't understand differential equations and how to solve them, and you don't know what the Navier-Stokes equation is, then you won't be able to fully grasp the futility of weather forecasting and climate science.
I can't give you a full education in physics and such, but let me break it down for you.
We have discovered "laws" of nature that describe, perfectly, the behavior of matter and energy in all circumstances.
These laws are entirely consistent and not in any way contradictory.
The laws give rise to mathematical formula that aren't just difficult to solve, but provably IMPOSSIBLE to solve.
Except in some extraordinary circumstances, we cannot make any predictions at all about the behavior of matter and energy. These extraordinary circumstances are so rare that in order to achieve them we must build purpose-built machines designed to create the conditions. (IE, laminar flow.)
Whether or not you can exactly measure the initial conditions -- the state of matter before you make your predictions -- is largely irrelevant. You can't measure anything exactly (error is everywhere) and that in and of itself means you can never make any meaningful predictions.
That said, there are certain broad and general observations we can make. IE, heat flows from hot to cold, etc... We can definitely measure temperature and heat flow and indeed, it will always flow hot to cold, even though we cannot predict everything about the flow.
“Always” has a caveat of “under these conditions” and you agree that we don’t perfectly know our conditions.
So I guess we would both agree then that we can learn more about what is occurring but what you’re saying more precisely is that we’ll never be able to predict exactly what happens.
Rather than using your imagination, use the measured properties of fluids. Use physics. See how the Navier-Stokes equations are? They describe ALL motion of all fluids (gasses and liquids) for all time. Nothing can move or stay motionless without conforming to those equations.
Yet, we cannot predict, in the slightest, what will happen in the next moment, let alone the next day or year.
Smoke predictions in San Francisco have reported with a footnote stating that due to limitations of weather prediction models they cannot accurately predict whether smoke would remain elevated above the city, or come down to ground level.
It makes sense from consideration of model development that only the most important parameter features would be included. Important meaning shows a statistically significant impact on what the weather would be on a given day in the future. Smoke is a rare event thus there is less data available to dial in on. Location and severity of the blaze need to be considered.
A rapid development team could cobble together a model enhancement, but the accuracy would be pretty low improving over time.
In short, shitty models, shitty data in the shitty models, shitty people putting shitty data in shitty models. When it's shitty across the board you don't even get a footnote explaining why predictions may be inaccurate.
“Any exposure to the air can lead to severe health effects”
So what the fuck are you supposed to do about it? It’s not like dust can’t get in your house? The fuck is with this retarded fear mongering?
You think they’d jump on this if it was such a. Big concern. And it probably is a big concern. But what.the.fuck.are people supposed to do about it? Anybody?
I don't know, but if it keeps going up like this the people are going to experience some serious health issues. The gases in the air are essentially poison.
It’s the same way you can predict your wife will love you in ten years probably if you married a good woman but you don’t know what her mood will be today
Chaos Theory exists, in part, because it is impossible to make accurate long range weather predictions without it. Whenever your field needs a theory literally called "Chaos Theory" to make predictions, you're pretty fucked.
This is not a great argument. Making long term predictions is far easier since there's more actual data cancelling out the noise. For example nobody has any fucking clue what the stock market will do in the next 3 days, but any idiot can tell you that it'll probably trend upward over the next 10 years.
Maybe a better example is that it's really hard to predict how many heads and tails will show up when I flip a fair coin 10 times vs if I flip it 10,000 times.
That being said, climate change predictions are fucked.
I agree with the spirit of this, but there is a difference between weather and climate, meteorologist ≠ climatologist. this is something of a false equivalence.
And I assume they got this wrong probably because antifa lit yet more fires.
Don't let that stop you though, climate change catastrophism is absolute bullshit and we should believe none of their retarded models.
That's your own assumption, I simply stated that they're different. Which they are.
Saying a theory on climate is wrong (regardless of what it is) because of a wrong prediction of 12 hours of weather is like saying Florida is a desert because it hasn't rained in a week.
Weather is what clothes you should wear today; climate is what clothes you should have in your closet.
Meteorology and climatology aren't even the same field of study...
Could be, you're right. It's bad science though and a pet peeve of mine. Like when there's a random cold day in the summer and a layman says SO MUCH FOR THAT GLOBAL WARMING!
There's plenty of legitimate rebuttals against climate change.... A random weather anomaly isn't one of them.
Beating a dead horse at this point though. Have a good one, pede
Climate is weather over a long period of time. Thirty years, fifty years are typical windows of observation. It's not entirely illogical to question global long-term models, when local short-term models are so often wrong.
Saying meteorology and climatology aren't the same field strikes me as short-sighted, since they're related. Climate study encompasses many fields, but weather patterns and potential feedback mechanisms are pretty important.
As an example: Clouds, because of both upwards radiation and downward cooling, are extremely important to the global temperature, but we don't yet know enough to quantify their impact. Some argue the total radiative forcing from clouds is a net positive, some argue net negative. Some argue for or against certain positive/negative feedback mechanisms. It's not settled.
After being disabused of some of my more popular beliefs about this subject, and listening to people who actually do the science, the only thing I know for certain is that the people making grand declarations of doomsday are jumping the gun. Human CO2 has definitely been a minor contributor to global mean temperature, but no solid evidence of current or impending catastrophe exists.
Shitty models, shitty data in the shitty models, shitty people putting shitty data in shitty models.
“Reality must take precedence over public relations for nature cannot be fooled.”
Having worked in data science you just described all of science. It's extremely difficult to get good data so you can build decent models. Weather forecasting abd climate science will always be wrong.
Fuck, this reminded me of a PHD student I tried to help with their thesis project. It was apparently too hard to get good data for their proposed model (lazy & would take time). So, find any old data and jam it into their model and voila, thesis done. I stopped helping before that point.
It’s honestly not his fault either. Science is publish or die these days. Taking your time to craft an excellent paper is rewarded less than the shotgun approach of firing off like 15 that barely meet the most basic requirements
Ha yes this is true. The field was computer vision and AI, which is evolving so rapidly you'd see many papers published every week.
Dr. Mototaka Nakamura (nasa jpl, mit, international pacific research center, etc) wrote a book a year or two ago called “confessions of a climate scientist” that basically explains how climate modeling is complete junk science and that there are very many important aspects to the climate that we barely understand at all and don’t even include in modeling. Most of the book is in Japanese, but he goes over the important stuff in English. Think it costs $1 on kindle, well worth the read.
No they won’t, we already know that all things interact with some convergent plane. We know that all changes cause a propagation of interactions.
It ought to be possible to analyze the entire atmosphere as well as the external forces acting on it.
Gravoscope WIP.
It seems like it ought to be possible, but Navier-Stokes shows that you simply cannot.
If you don't understand differential equations and how to solve them, and you don't know what the Navier-Stokes equation is, then you won't be able to fully grasp the futility of weather forecasting and climate science.
So basically energy can’t be predictable enough in any space because from any point it will never be consistent?
I can't give you a full education in physics and such, but let me break it down for you.
Whether or not you can exactly measure the initial conditions -- the state of matter before you make your predictions -- is largely irrelevant. You can't measure anything exactly (error is everywhere) and that in and of itself means you can never make any meaningful predictions.
That said, there are certain broad and general observations we can make. IE, heat flows from hot to cold, etc... We can definitely measure temperature and heat flow and indeed, it will always flow hot to cold, even though we cannot predict everything about the flow.
“Always” has a caveat of “under these conditions” and you agree that we don’t perfectly know our conditions.
So I guess we would both agree then that we can learn more about what is occurring but what you’re saying more precisely is that we’ll never be able to predict exactly what happens.
Cool thanks
My imagination figures that just because you’re inside the fluid doesn’t mean you can’t view the whole container.
Rather than using your imagination, use the measured properties of fluids. Use physics. See how the Navier-Stokes equations are? They describe ALL motion of all fluids (gasses and liquids) for all time. Nothing can move or stay motionless without conforming to those equations.
Yet, we cannot predict, in the slightest, what will happen in the next moment, let alone the next day or year.
Maybe if you can’t predict it and there’s huge holes in the equation then the equation is wrong.
I’m saving this comment for later because it captures the idiocy perfectly
Smoke predictions in San Francisco have reported with a footnote stating that due to limitations of weather prediction models they cannot accurately predict whether smoke would remain elevated above the city, or come down to ground level.
It makes sense from consideration of model development that only the most important parameter features would be included. Important meaning shows a statistically significant impact on what the weather would be on a given day in the future. Smoke is a rare event thus there is less data available to dial in on. Location and severity of the blaze need to be considered.
A rapid development team could cobble together a model enhancement, but the accuracy would be pretty low improving over time.
In short, shitty models, shitty data in the shitty models, shitty people putting shitty data in shitty models. When it's shitty across the board you don't even get a footnote explaining why predictions may be inaccurate.
GIGO
If words had defined meanings all of the democrat platform would be seen for what it is.
Anti-Americanism
“Any exposure to the air can lead to severe health effects”
So what the fuck are you supposed to do about it? It’s not like dust can’t get in your house? The fuck is with this retarded fear mongering?
You think they’d jump on this if it was such a. Big concern. And it probably is a big concern. But what.the.fuck.are people supposed to do about it? Anybody?
I don't know, but if it keeps going up like this the people are going to experience some serious health issues. The gases in the air are essentially poison.
Climate cultist: "Herp derp, the climate is not the same as the weather, science denier!"
Also climate cultist: "This severe weather is due to muh climate change!"
Oxygen deprival can lead to tumors. California is collecting all the cancers right now.
This question always stumps then, 10 thousand years ago, the earth went through an ice age, what happened?
every single forecast the weather service app built into my phone has put out this year has been wrong it's almost comedic
Damn, that's China levels of bad!
Two words: fucking millennials.
It’s the same way you can predict your wife will love you in ten years probably if you married a good woman but you don’t know what her mood will be today
Chaos Theory exists, in part, because it is impossible to make accurate long range weather predictions without it. Whenever your field needs a theory literally called "Chaos Theory" to make predictions, you're pretty fucked.
This is not a great argument. Making long term predictions is far easier since there's more actual data cancelling out the noise. For example nobody has any fucking clue what the stock market will do in the next 3 days, but any idiot can tell you that it'll probably trend upward over the next 10 years.
Maybe a better example is that it's really hard to predict how many heads and tails will show up when I flip a fair coin 10 times vs if I flip it 10,000 times.
That being said, climate change predictions are fucked.
I agree with the spirit of this, but there is a difference between weather and climate, meteorologist ≠ climatologist. this is something of a false equivalence.
And I assume they got this wrong probably because antifa lit yet more fires.
Don't let that stop you though, climate change catastrophism is absolute bullshit and we should believe none of their retarded models.
Weather isn't the same as climate brah
Is your point that climate change predictions are true because they are different from weather? Because if you are.....
That's your own assumption, I simply stated that they're different. Which they are.
Saying a theory on climate is wrong (regardless of what it is) because of a wrong prediction of 12 hours of weather is like saying Florida is a desert because it hasn't rained in a week.
Weather is what clothes you should wear today; climate is what clothes you should have in your closet.
Meteorology and climatology aren't even the same field of study...
I assumed that about you because it's easy to understand that both are different. It's also easy to understand OP's comparison can both be true.
Could be, you're right. It's bad science though and a pet peeve of mine. Like when there's a random cold day in the summer and a layman says SO MUCH FOR THAT GLOBAL WARMING!
There's plenty of legitimate rebuttals against climate change.... A random weather anomaly isn't one of them.
Beating a dead horse at this point though. Have a good one, pede
Climate is weather over a long period of time. Thirty years, fifty years are typical windows of observation. It's not entirely illogical to question global long-term models, when local short-term models are so often wrong.
Saying meteorology and climatology aren't the same field strikes me as short-sighted, since they're related. Climate study encompasses many fields, but weather patterns and potential feedback mechanisms are pretty important.
As an example: Clouds, because of both upwards radiation and downward cooling, are extremely important to the global temperature, but we don't yet know enough to quantify their impact. Some argue the total radiative forcing from clouds is a net positive, some argue net negative. Some argue for or against certain positive/negative feedback mechanisms. It's not settled.
After being disabused of some of my more popular beliefs about this subject, and listening to people who actually do the science, the only thing I know for certain is that the people making grand declarations of doomsday are jumping the gun. Human CO2 has definitely been a minor contributor to global mean temperature, but no solid evidence of current or impending catastrophe exists.