Dr. Jordan B Peterson has 3 episodes about Climate Change peddling outmoded or inccorect models-of-assumptions.
Those helped me track what you laid out here briefly about modeling.
— Dr Jordan B Peterson and Dr. Richard Lindzen dive into the facts of climate change, the models used to predict it, the dismal state of academia, and the politicized world of “professional” science.
— Dr Jordan B Peterson and Alex Epstein discuss the undeniable need for fossil fuels, the toxic underlying nihilism of the “climate concerned” left, the need for balance between conservation and human progress, and the unexplored worth of wild potential.
.
Alex Epstein is a philosopher and energy expert who argues that "human flourishing" should be the guiding principle of energy and environmental progress.
— Dr Jordan B Peterson and Dr. Judith Curry discuss climate change, the major error in current models and future predictions, academic fraud, and the need for dissenting opinions.
.
Dr. Judith Curry is an American climatologist with a Bachelor’s degree in geography from Northern Illinois University, and a geophysical sciences Ph.D. from the University of Chicago.
In Appendix A1 you can see they are trying to create an uncertainty model. The paper itself laments the limitations that the data has. Which would also mean it can't be used for what it's intended to be used for.
Looking at the Summary, the paper seems to disqualify itself in each paragraph, relentlessly. (I don't quite follow along, it sounds like the paper used different models to cover gaps in duration).
Summary:
"While these biases are expected to be smaller than those in SST measurements from ships, they are nonetheless significant on longer time and space scales. Adjustments for these biases are themselves uncertain and an active area of research (Abraham et al., 2013; Cheng et al., 2016).
. . .
The work we present here is . . . partly offsetting larger biases associated with uninsulated buckets and an earlier change to insulated bucket use.
. . .
Important uncertainties likely remain.
. . .
However, it is important to note that the sampling of both these data sets changes at this point. . . . However, comparisons . . . suggest that the NMAT, and hence ERSST, is artificially warm during the war years despite the adjustments that have been applied for nonstandard exposure (Kent et al., 2013).
. . .
These lines of evidence suggest that at least some of the drop is artificial, but they do not help to understand which of the data sets provides a better estimate.
. . .
Consequently, considerable uncertainty remains regarding SST during the Second World War. This uncertainty is partly reflected in the wide uncertainty ranges given . . . a more satisfactory solution is needed. Users of the data set should be wary of drawing strong conclusions based on trends that start or end during the war years until this is resolved.
. . .
Although HadSST.4.0.0.0 and ERSSTv5 show reasonable agreement in the overall evolution of global average SST, there are some interesting differences between the trends . . . The discrepancy between HadNMAT.2.0.1.0 and HadSST.4.0.0.0 suggests that there is either a large-scale change in atmospheric circulation in the early 1990s that modified the air-sea temperature difference throughout the tropics or that undetected biases remain in one or the other of the marine temperature (SST or NMAT) data sets considered here.
. . .
Because of the strong links between SST and MAT and between systematic errors in SST and MAT, a fuller understanding of marine temperatures in general can only be achieved by studying both in greater detail along with metadata and other relevant marine variables such as humidity (Willett et al., 2008) and winds. While measurements of SST are now more numerous than ever thanks to the wealth of satellite data and autonomous platforms such as drifting buoys, there has been a marked continuing decline in the MAT observing system which relies on shipborne instruments and is currently far below the level of adequacy as judged by a number of criteria (Berry & Kent, 2017)."
My Favorite Quotes:
— Adjustments for these biases are themselves uncertain and an active area of research
— [these biases are] significant on longer time and space scales.
— Important uncertainties likely remain.
— [data] is artificially warm during the war years despite the adjustments that have been applied
— Consequently, considerable uncertainty remains
— a more satisfactory solution is needed.
— Users of the data set should be wary of drawing strong conclusions based on trends
— This uncertainty is partly reflected in the wide uncertainty ranges given
— [highly likely that] undetected biases remain in one or the other of the marine temperature (SST or NMAT) data sets considered here.
— is currently far below the level of adequacy as judged by a number of criteria (Berry & Kent, 2017).
Or did You mean, in the Appendix as you said, the variability ought to be low?
"The covariances vary in character from place to place (see Figure A1).
. . .
Over the western boundary currents, the length scales are short and variability is high"
Either way, people are using ChatGPT to help with legal scensrios, and summary text.
**Tenant enlists ChatGPT to draft legal-sounding letters, avoids rent hike**
Simple question, and obscuring answer. Nobody in UK government has a clue, they just do what they’re told by the unelected super national bodies (WHO, UN..)
In any other safety critical engineering field such vagueness and still trying to apply it to the real world would result in firings and possible jail time. What surprises me is that no one has raised a lawsuit for deceit or fraud.
Dr. Jordan B Peterson has 3 episodes about Climate Change peddling outmoded or inccorect models-of-assumptions.
Those helped me track what you laid out here briefly about modeling.
— Dr Jordan B Peterson and Dr. Richard Lindzen dive into the facts of climate change, the models used to predict it, the dismal state of academia, and the politicized world of “professional” science.
Richard Lindzen is a dynamical meteorologist.
.
https://www.youtube.com/watch?v=7LVSrTZDopM
— Dr Jordan B Peterson and Alex Epstein discuss the undeniable need for fossil fuels, the toxic underlying nihilism of the “climate concerned” left, the need for balance between conservation and human progress, and the unexplored worth of wild potential.
.
Alex Epstein is a philosopher and energy expert who argues that "human flourishing" should be the guiding principle of energy and environmental progress.
.
https://www.youtube.com/watch?v=eDWq7-eP5sE
— Dr Jordan B Peterson and Dr. Judith Curry discuss climate change, the major error in current models and future predictions, academic fraud, and the need for dissenting opinions.
.
Dr. Judith Curry is an American climatologist with a Bachelor’s degree in geography from Northern Illinois University, and a geophysical sciences Ph.D. from the University of Chicago.
.
https://www.youtube.com/watch?v=9Q2YHGIlUDk
You write with helpful analogies. I take it to mean you write to help laymen keep track of what's going on.
In this spirit,
— can you add screenshots of those cited academic papers with your comment of what those lack (within your context of validating assumptions).
And DM me the update so I don't miss out :)
With regards to temperatures this is a good paper by the Met Office:
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018JD029867
In Appendix A1 you can see they are trying to create an uncertainty model. The paper itself laments the limitations that the data has. Which would also mean it can't be used for what it's intended to be used for.
Looking at the Summary, the paper seems to disqualify itself in each paragraph, relentlessly. (I don't quite follow along, it sounds like the paper used different models to cover gaps in duration).
Summary:
"While these biases are expected to be smaller than those in SST measurements from ships, they are nonetheless significant on longer time and space scales. Adjustments for these biases are themselves uncertain and an active area of research (Abraham et al., 2013; Cheng et al., 2016).
. . .
The work we present here is . . . partly offsetting larger biases associated with uninsulated buckets and an earlier change to insulated bucket use.
. . .
Important uncertainties likely remain.
. . .
However, it is important to note that the sampling of both these data sets changes at this point. . . . However, comparisons . . . suggest that the NMAT, and hence ERSST, is artificially warm during the war years despite the adjustments that have been applied for nonstandard exposure (Kent et al., 2013).
. . .
These lines of evidence suggest that at least some of the drop is artificial, but they do not help to understand which of the data sets provides a better estimate.
. . .
Consequently, considerable uncertainty remains regarding SST during the Second World War. This uncertainty is partly reflected in the wide uncertainty ranges given . . . a more satisfactory solution is needed. Users of the data set should be wary of drawing strong conclusions based on trends that start or end during the war years until this is resolved.
. . .
Although HadSST.4.0.0.0 and ERSSTv5 show reasonable agreement in the overall evolution of global average SST, there are some interesting differences between the trends . . . The discrepancy between HadNMAT.2.0.1.0 and HadSST.4.0.0.0 suggests that there is either a large-scale change in atmospheric circulation in the early 1990s that modified the air-sea temperature difference throughout the tropics or that undetected biases remain in one or the other of the marine temperature (SST or NMAT) data sets considered here.
. . .
Because of the strong links between SST and MAT and between systematic errors in SST and MAT, a fuller understanding of marine temperatures in general can only be achieved by studying both in greater detail along with metadata and other relevant marine variables such as humidity (Willett et al., 2008) and winds. While measurements of SST are now more numerous than ever thanks to the wealth of satellite data and autonomous platforms such as drifting buoys, there has been a marked continuing decline in the MAT observing system which relies on shipborne instruments and is currently far below the level of adequacy as judged by a number of criteria (Berry & Kent, 2017)."
My Favorite Quotes:
— Adjustments for these biases are themselves uncertain and an active area of research
— [these biases are] significant on longer time and space scales.
— Important uncertainties likely remain.
— [data] is artificially warm during the war years despite the adjustments that have been applied
— Consequently, considerable uncertainty remains
— a more satisfactory solution is needed.
— Users of the data set should be wary of drawing strong conclusions based on trends
— This uncertainty is partly reflected in the wide uncertainty ranges given
— [highly likely that] undetected biases remain in one or the other of the marine temperature (SST or NMAT) data sets considered here.
— is currently far below the level of adequacy as judged by a number of criteria (Berry & Kent, 2017).
Or did You mean, in the Appendix as you said, the variability ought to be low?
"The covariances vary in character from place to place (see Figure A1).
. . .
Over the western boundary currents, the length scales are short and variability is high"
Either way, people are using ChatGPT to help with legal scensrios, and summary text.
**Tenant enlists ChatGPT to draft legal-sounding letters, avoids rent hike**
https://web.archive.org/web/20240712170858/https://thepostmillennial.com/tenant-enlists-chatgpt-to-draft-legal-sounding-letters-avoids-rent-hike
Surely there's orgs willing to fund what seems like an low-hanging fruit win as you portrayed it.
1 Someone wants to take this on,
2 Make an information packet with those quotes,
3 Deligently apply a consumable framing,
— Orgs (or people) be viable solution for finances, time-management, and pushing this forward.
BTW, that wasn't even me using LLM's to find those quotes. Those are just glaring at the reader. 😅
— Can you provide those hyperlinks links into your posts so I can follow along?
"Or putting a spacecraft into space with by shaking, thermal or electrical checkout using vague data well above required precision."
— was there a typo here? I'm not sure what is being said. With or without?
I expanded this a bit
🙏 thank you. That makes sense to me.
Simple question, and obscuring answer. Nobody in UK government has a clue, they just do what they’re told by the unelected super national bodies (WHO, UN..)
In any other safety critical engineering field such vagueness and still trying to apply it to the real world would result in firings and possible jail time. What surprises me is that no one has raised a lawsuit for deceit or fraud.
This adds to the use of LLM to help,
Comment here ,
https://overhead.substack.com/p/when-i-asked-a-simple-question-about/comment/76901570
I wonder if LLM can help parse for the orgs that won related cases/crimes/challenges to reach out to for taking this on.