AR4 WG1 Chapter 9 Figure 9.1 has a collection of Figures showing at what altitudes and latitudes AOGCMs expect temperature change in response to various individual forcings and one for all combined forcing. (Link to figure https://www.ipcc.ch/report/ar4/wg1/understanding-and-attributing-climate-change/fig-9-01-2/r.) Solar forcing warms both the stratosphere and troposphere, because SWR is absorbed in both locations. Rising GHGs characteristically cause warming in the troposphere and cooling in the stratosphere, for reasons one can rationalize using the Schwarzschild equation. However, the Figure for all forcings infamously also shows more warming in the upper tropical troposphere that at the surface, a phenomena not directly related to warming caused by rising GHGs. For several decades now, observations (which are not necessarily definitive) have failed show enhanced or "amplified" warming in the upper tropical troposphere compared with the surface below. This discredits convection in climate models, and the theory that a moist adiabatic lapse rate controls temperature in the upper tropical troposphere, but NOT the theory that GHGs cause warming by reducing radiative cooling to space. Santer has a paper showing the warming in the upper tropical troposphere is amplified during short warming events like El Ninos as would be expected for an atmosphere controlled by a moist adiabatic lapse rate, so the problem may be our inability to accurately measure temperature change high in the tropical tropical troposphere over several decades. This subject was debated in 2013 here:
More warming higher in the troposphere than at the surface is technically called lapse rate feedback, which is a negative feedback that limits the warming associated with any positive forcing. Surface warming by any mechanism is expected to result in higher absolute humidity in the troposphere: causing positive water vapor feedback by WV acting as a greenhouse gas and negative lapse rate feedback by increasing heat capacity. If the upper troposphere troposphere warms more than the surface, that it a good thing, since that allows a warming planet to radiate more heat to space for a given amount of surface warming than for a planet that warms equally everywhere in the troposphere. Observations of less-than expected warming in the upper tropical troposphere mean our warming planet is radiating less heat to space than expected based on observed surface warming. (That's bad.)
However, if the upper tropical troposphere is warming less than expected, this is almost certainly because less water vapor is reaching higher altitudes and releasing less latent heat. Less water vapor means water vapor feedback. Combined water vapor plus lapse rate feedback from increasing absolute humidity is positive, so the failure to observed amplified warming in the upper tropical troposphere meaning that we can INFER that WV+LR feedback is less positive and climate sensitivity is lower than models predict.
Finally, amplified warming in the upper tropical troposphere means that clouds won't form until convection reaches higher altitudes and their tops will be colder and therefore radiate less heat to space. This mechanism produces some positive LWR cloud feedback. If the upper tropical troposphere isn't amplified as much as expected, we can INFER that this could feedback is less positive than expected and climate sensitivity a little lower.
As for ECS, Knutti et al. 2017 compiled over 200 ECS studies. The range of estimated warming from doubling CO₂ went from a low of 0°C to a high of 10°C. Carbonbrief came up with the same range in their compilation of 142 ECS studies. Of those 142 studies, 141 had different results.
No result refuted any other results, it's simply throwing darts at a wall and calling it a "scientific study"
Why is there such a huge range in models - from 0°C to 10°C?
Why does every modeler come up with a different result?
No result can dispute, refute or debunk any other results, pulling numbers from a 100 ball [1/1 of every degree between 0° &10°] lottery machine is just as valid as simulations by models.
If there's no way to validate a calculation, what value is the calculation wrt reality?
Multi-model means - Zeke Hausfathers stated that it's used to hide the profound discrepancies of model results. IIRC, Ben Santer was the first to devise this 'hide the profound discrepancies' tool by using a multi-model means.
The null hypothesis is an ESC of 0°C. NOAA's Tom Karl stated [1989] global temps cooled from 1921 to 1979 while CO₂ increased, the 0°C ESC might even be on the high side. 58 years of cooling shouldn't be ignored in ECS studies. 1981, Dr Hansen stated the major difficulty in accepting AGW was the absence of observed warming coincident with the rise in CO₂ levels. ECS above 0°C is basically a simulation that can't be validated or invalidated. That's why every study gets a different result. No one's right, no one's wrong. Averaging doesn't lend credence if the resulting calculation of the multi-midel mean can't be validated or invalidated any more or less than any individual calculation that runs anywhere from of 0°C to 10°C.
Why did the global climate cool from 1921 to 1979 [1989]? Hansen admitted absence of evidence of AGW [1981] as well as little evidence of any global warming outside of UHI [Eichner et al. 2003]
None of those scientists would be considered skeptics.
Can anyone demonstrate the calculations are real - in any physics lab experiment? Of course not.
That's why ESC studies cover all the bases, they're simply guessing and everyone has their own calculated guesses. Identical authors publish a subsequent ECS *studies* and they have different results everytime. The major datasets show cooling for the last 8 years - if ECS has any credibility - what causes the cooling?
Simply saying CO₂ causes warming but the hypothesis can't explain the cooling/pauses. There's been cooling/pauses in warming for 74 of the years from 1921 to 2015 and it's cooling again for last 8 years.
Even the most ardent scientists & modellers [eg Schmidt, Rahmstorf, Hausfather, Fyfe, Mears, von Storch, Mann] have criticized CMIP model results. The equations have to be invalid if they don't match reality. I understand the explanations but reality says otherwise. Prof Kandlikar [UBC] has stated that GCM models - the physics are fudged to try to make the results appear to be similar to observations. The more I study [12+ years] the more I believe that what we're seeing is simply natural climate variability.
You don't seem to understand what the null hypothesis means.
The null hypothesis regard CO₂ is that it has no impact on temperature.
Then experiments are designed to test the hypothesis.
Since there's no lab experiment possible, then we look at the data - CO₂ increased and what happened to global temperatures:
1981 : NASA-GISS [Hansen et al.1981] "the difficulty in accepting this theory is the absence of warming coincident to increase in CO₂"
1988 NASA-GISS [Hansen] : Global Average Temperature [1950-1980 baseline] to determine temperature variation is 15°C. Not one year since 2000 has gone above 15°C
1989 : NOAA [Thomas Karl] the climate cooled from 1921-1979
2003 : Eichner et al 2003 "in the vast majority of stations we did not see indications for a global warming of the atmosphere" then it goes on to state that warming is mainly in urban areas (UHI)
1998 - 2018 : the hiatus/slowdown in warming. 100s of peer-reviewed papers come up with multiple dozens of possible explanations for the lack of warming that was predicted/projected in the climate models
Fyfe et al 2013 : the climate models have overestimated warming since 1992.
The was some slight warming between 1979 & 1998 - is that sufficient to declare CO₂ is causing temperatures to rise when the vast majority of the data vs time shows cooling & hiatus/slowdown of warming?
To declare *CO₂ causes warming* has a very difficult burden of proof to overcome - the evidence just isn't there.
The null hypothesis [adding CO₂ doesn't effect temperature] hasn't been refuted, in fact, it's a very solid position to take and the only one that's supported by a century of observations and measurements of CO₂ (since the 1950s)
Science can do as many calculations as it wants, but the data has unequivocally falsified the calculations - as of this point in time.
Did you look at natural variability in the last 100,000 years - 23 abrupt climate changes with temperature variations of 10°C to 15°C (and more) many of which happened within a decade?
Rahmstorf, Severinghaus, Alley and numerous others concur. Abrupt changes can be far more extreme than what is seen today. IPCC reports also support abrupt climate change although the latest reports are less likely to acknowledge these abrupt changes.
My recollection from a number of papers was - as you say - abrupt climate change of large magnitude - often called Dansgaard-Oeschger events. I think the large temperature variation was regional.
According to Stefan Rahmstorf (Postdam Institute) the variation was world-wide. 170+ locations including New Zealand and Antarctica. The multi-coauthored book 'Abrupt Climate Change' also stated it was a global phenomenon. I don't recall off the top of my head what Alley (Two Mile Time Machine etc) or others have stated, it's been a while since I read that research.
They're referring to 23 abrupt image changes in the last 100,000 years.
Prof Rahmstorf (Potsdam Institute) stated that these abrupt climate changes have been validated as 𝙜𝙡𝙤𝙗𝙖𝙡 at more than 170 locations around the world - including New Zealand and Antarctica.
[Munich Re, Weather catastrophes and climate change: Abrupt Climate Change 2004]
I'm simply confused by why you're willing to take it as a given that the 1980(ish) data was wrong, but you're convinced that the modern temperature data series is correct.
The 2015 changes became known as the 'Pause Buster' so it was indeed very significant. One contributor to SKS was consolidating a list of 'hiatus' papers. The last I checked (couple of years ago) he was expecting to top 300 peer-reviewed papers.
If you read those papers, there's more than FIVE DOZEN varying opinions at to why the hiatus - Yet another indication of a very significant deviation from the models and the theory.
As for "waaaay overblown" Michael E Mann stated that it was very significant - he argued quite strongly that we "shouldn't sweep it under the rug"
I've yet to see evidence of CO₂ induced warming, I hope it will happen but I'm not not convinced it has. Are you aware of Dr Hansen's take on CO₂ correlation to temp, namely that the trends may appear similar but that doesn't mean CO₂ caused the changes (IIRC, it was Hansen et al. 1981)
So can you definitively identify the cause of the hiatus (aka warming slowdown)?
I understand a willingness to discount something out-of-hand that can't be explained as "waaay overblown"
When a person uses that rhetoric, they've identified a fault that they won't acknowledge.
The hotspot does not derive from "CO2 theory"; it comes from *any* tropical warming under a strict adherence to the moist adiabatic lapse rate.
And, strictly speaking, it's a negative feedback, as it involves lofting heat higher into the troposphere where that heat can then more easily radiate to space.
But, point is: this isn't a problem for the idea of CO2-induced warming. It has to do with modeling convection in the tropical mid/upper-troposphere under surface warming in general.
The cold bias is in the integrated SST data, from how the ship and buoy data combine. Granted, those two lines you quoted together could use some editing, but that isn’t a peer-reviewed paper. (And that kind of word-slip can and does show up in peer-reviewed papers, when everyone understands the point being made, simply by context alone).
From the same article:
“But the buoys report slightly cooler temperatures because they measure water directly from the ocean instead of after a trip through a warm engine room.”
Which is a more accurate reading of the ocean temperatures? Measuring water directly from the ocean, or measuring it after a trip through the warm engine room?
So which source would be more considered more accurate - the buoys that measure the water directly, or the thermometers that measure water temps after that water has gone through an engine room?
Similarly, look at the first chart in this article. Does the line on the chart for “buoys” line up more with the older NOAA data, or the newer, more-accurate NOAA data?
(It lines up with the newer data)
Or consider this quote from Karl (2015):
> More generally, buoy data have been proven to be more accurate and reliable than ship data, with better known instrument characteristics and automated sampling.
The engine intake data had already been considered and accounted for in previous SST analyses. You're simply making nonsensical excuses because you don't like what they stated.
Facts are facts regardless of your feelings.
You have no intention of participating in an honest discussion.
> The engine intake data had already been considered and accounted for in previous SST analyses. You’re simply making nonsensical excuses…
Hey, do you remember when you referenced Karl et al (2015)? They directly addressed this counterargument you just made. Here’s a quote:
“Second, there was a large change in ship observations (i.e., from buckets to engine intake thermometers) that peaked immediately prior to World War II. The previous version of ERSST assumed that no ship corrections were necessary after this time, but recently improved metadata (18) reveal that some ships continued to take bucket observations even up to the present day. Therefore, one of the improvements to ERSST version 4 is extending the ship-bias correction to the present, based on information derived from comparisons with night marine air temperatures.”
——
I figured you were already aware of this point, since you keep talking about this paper. I’m kinda surprised that you call this a “nonsensical excuse” when it’s in the paper you referenced.
But Karl (2015) is a great, short, to-the-point paper. Thanks for bringing it to my attention, Ted!
But your continuous deflections & moving the goalposts is exactly would I would expect.
Now you're arguing that the people that wrote the paper and the article on Berkeley Earth have no idea how to write what they mean, they need to rely on your interpretation.
Not at all. They say that the buoy data measures the sea directly, and that’s what they mean. And this, plainly, means that buoy data is more accurate, particularly when they’re also saying that the ship-engine data, for contrast, is warmed by virtue of passing through the engine room.
Or, here’s a quote from the Science Advances article that the Berkeley News article is sourced from:
> Modern ship-based measurements … tend to generate temperature readings around 0.12°C higher than those of buoys, whose sensors are directly in contact with the ocean’s surface. … Although buoy records are **widely considered to be more accurate** than ship-based measurements, their integration with ship records into longer SST series poses a number of challenges. [emph added]
“widely considered to be more accurate”. There it is. In a peer-reviewed scientific article in a top journal, scientists state that the buoy data is widely considered to be more accurate. A direct quote, if the other direct quotes weren’t enough.
So, again, the scientists say that the buoy records are more accurate. Why would it be otherwise? We know they’re switching from ship data to buoy data - why would they be preferring to use *less* accurate data?
Stratosphere cooling. Ok. What about troposphere warming over the tropics? Does the model align with measurements there? Not so much I have heard.
Thomas,
That's one I haven't looked at for a lot of years. Do you have a paper or two in mind? I'd like to refresh my memory.
Here's what I remember from a long time ago:
1. Measurements of trends are a challenge
2. The prediction of tropical tropospheric warming isn't specifically about CO2 induced warming
But I haven't checked anything for this (except my memory).
AR4 WG1 Chapter 9 Figure 9.1 has a collection of Figures showing at what altitudes and latitudes AOGCMs expect temperature change in response to various individual forcings and one for all combined forcing. (Link to figure https://www.ipcc.ch/report/ar4/wg1/understanding-and-attributing-climate-change/fig-9-01-2/r.) Solar forcing warms both the stratosphere and troposphere, because SWR is absorbed in both locations. Rising GHGs characteristically cause warming in the troposphere and cooling in the stratosphere, for reasons one can rationalize using the Schwarzschild equation. However, the Figure for all forcings infamously also shows more warming in the upper tropical troposphere that at the surface, a phenomena not directly related to warming caused by rising GHGs. For several decades now, observations (which are not necessarily definitive) have failed show enhanced or "amplified" warming in the upper tropical troposphere compared with the surface below. This discredits convection in climate models, and the theory that a moist adiabatic lapse rate controls temperature in the upper tropical troposphere, but NOT the theory that GHGs cause warming by reducing radiative cooling to space. Santer has a paper showing the warming in the upper tropical troposphere is amplified during short warming events like El Ninos as would be expected for an atmosphere controlled by a moist adiabatic lapse rate, so the problem may be our inability to accurately measure temperature change high in the tropical tropical troposphere over several decades. This subject was debated in 2013 here:
https://mwenb.nl/the-missing-tropical-hot-spot/
More warming higher in the troposphere than at the surface is technically called lapse rate feedback, which is a negative feedback that limits the warming associated with any positive forcing. Surface warming by any mechanism is expected to result in higher absolute humidity in the troposphere: causing positive water vapor feedback by WV acting as a greenhouse gas and negative lapse rate feedback by increasing heat capacity. If the upper troposphere troposphere warms more than the surface, that it a good thing, since that allows a warming planet to radiate more heat to space for a given amount of surface warming than for a planet that warms equally everywhere in the troposphere. Observations of less-than expected warming in the upper tropical troposphere mean our warming planet is radiating less heat to space than expected based on observed surface warming. (That's bad.)
However, if the upper tropical troposphere is warming less than expected, this is almost certainly because less water vapor is reaching higher altitudes and releasing less latent heat. Less water vapor means water vapor feedback. Combined water vapor plus lapse rate feedback from increasing absolute humidity is positive, so the failure to observed amplified warming in the upper tropical troposphere meaning that we can INFER that WV+LR feedback is less positive and climate sensitivity is lower than models predict.
Finally, amplified warming in the upper tropical troposphere means that clouds won't form until convection reaches higher altitudes and their tops will be colder and therefore radiate less heat to space. This mechanism produces some positive LWR cloud feedback. If the upper tropical troposphere isn't amplified as much as expected, we can INFER that this could feedback is less positive than expected and climate sensitivity a little lower.
As for ECS, Knutti et al. 2017 compiled over 200 ECS studies. The range of estimated warming from doubling CO₂ went from a low of 0°C to a high of 10°C. Carbonbrief came up with the same range in their compilation of 142 ECS studies. Of those 142 studies, 141 had different results.
No result refuted any other results, it's simply throwing darts at a wall and calling it a "scientific study"
Ted,
I'll be writing some more about climate model results. There's a very wide range of equilibrium temperatures for doubling CO2 from climate models.
Is the paper you are thinking of "Beyond equilibrium climate sensitivity" or another one?
Yes, that's Knutti et al. 2017
Carbon Brief link is https://www.carbonbrief.org/explainer-how-scientists-estimate-climate-sensitivity/
Why is there such a huge range in models - from 0°C to 10°C?
Why does every modeler come up with a different result?
No result can dispute, refute or debunk any other results, pulling numbers from a 100 ball [1/1 of every degree between 0° &10°] lottery machine is just as valid as simulations by models.
If there's no way to validate a calculation, what value is the calculation wrt reality?
Multi-model means - Zeke Hausfathers stated that it's used to hide the profound discrepancies of model results. IIRC, Ben Santer was the first to devise this 'hide the profound discrepancies' tool by using a multi-model means.
The idea has been around for a long time. Whether it's a good idea or not is a big subject. Bit of an intro here:
https://scienceofdoom.com/2014/07/08/ensemble-forecasting/
The null hypothesis is an ESC of 0°C. NOAA's Tom Karl stated [1989] global temps cooled from 1921 to 1979 while CO₂ increased, the 0°C ESC might even be on the high side. 58 years of cooling shouldn't be ignored in ECS studies. 1981, Dr Hansen stated the major difficulty in accepting AGW was the absence of observed warming coincident with the rise in CO₂ levels. ECS above 0°C is basically a simulation that can't be validated or invalidated. That's why every study gets a different result. No one's right, no one's wrong. Averaging doesn't lend credence if the resulting calculation of the multi-midel mean can't be validated or invalidated any more or less than any individual calculation that runs anywhere from of 0°C to 10°C.
Why did you decide the null hypothesis is an ECS of 0°C?
It's clear from the equations of radiative transfer that more CO2 in the atmosphere reduces the outgoing longwave radiation (OLR).
For example:
1. Opinions and Perspectives – 7 – Global Temperature Change from Doubling CO2 - https://scienceofdoom.com/2019/01/10/opinions-and-perspectives-7-global-temperature-change-from-doubling-co2/
2. Understanding Atmospheric Radiation and the “Greenhouse” Effect – Part Six – The Equations - https://scienceofdoom.com/2011/02/07/understanding-atmospheric-radiation-and-the-%e2%80%9cgreenhouse%e2%80%9d-effect-%e2%80%93-part-six-the-equations/
The only way I can see an ECS of 0°C as a "null hypothesis" is:
a) you don't believe the equations of radiative transfer.
b) you have strong evidence that negative feedbacks reduce this effect to almost zero
Equations are contradicted by reality.
If ESC is greater than 0°C
Why did the global climate cool from 1921 to 1979 [1989]? Hansen admitted absence of evidence of AGW [1981] as well as little evidence of any global warming outside of UHI [Eichner et al. 2003]
None of those scientists would be considered skeptics.
Can anyone demonstrate the calculations are real - in any physics lab experiment? Of course not.
That's why ESC studies cover all the bases, they're simply guessing and everyone has their own calculated guesses. Identical authors publish a subsequent ECS *studies* and they have different results everytime. The major datasets show cooling for the last 8 years - if ECS has any credibility - what causes the cooling?
Simply saying CO₂ causes warming but the hypothesis can't explain the cooling/pauses. There's been cooling/pauses in warming for 74 of the years from 1921 to 2015 and it's cooling again for last 8 years.
Even the most ardent scientists & modellers [eg Schmidt, Rahmstorf, Hausfather, Fyfe, Mears, von Storch, Mann] have criticized CMIP model results. The equations have to be invalid if they don't match reality. I understand the explanations but reality says otherwise. Prof Kandlikar [UBC] has stated that GCM models - the physics are fudged to try to make the results appear to be similar to observations. The more I study [12+ years] the more I believe that what we're seeing is simply natural climate variability.
You don't seem to understand what the null hypothesis means.
The null hypothesis regard CO₂ is that it has no impact on temperature.
Then experiments are designed to test the hypothesis.
Since there's no lab experiment possible, then we look at the data - CO₂ increased and what happened to global temperatures:
1981 : NASA-GISS [Hansen et al.1981] "the difficulty in accepting this theory is the absence of warming coincident to increase in CO₂"
1988 NASA-GISS [Hansen] : Global Average Temperature [1950-1980 baseline] to determine temperature variation is 15°C. Not one year since 2000 has gone above 15°C
1989 : NOAA [Thomas Karl] the climate cooled from 1921-1979
2003 : Eichner et al 2003 "in the vast majority of stations we did not see indications for a global warming of the atmosphere" then it goes on to state that warming is mainly in urban areas (UHI)
1998 - 2018 : the hiatus/slowdown in warming. 100s of peer-reviewed papers come up with multiple dozens of possible explanations for the lack of warming that was predicted/projected in the climate models
Fyfe et al 2013 : the climate models have overestimated warming since 1992.
The was some slight warming between 1979 & 1998 - is that sufficient to declare CO₂ is causing temperatures to rise when the vast majority of the data vs time shows cooling & hiatus/slowdown of warming?
To declare *CO₂ causes warming* has a very difficult burden of proof to overcome - the evidence just isn't there.
The null hypothesis [adding CO₂ doesn't effect temperature] hasn't been refuted, in fact, it's a very solid position to take and the only one that's supported by a century of observations and measurements of CO₂ (since the 1950s)
Science can do as many calculations as it wants, but the data has unequivocally falsified the calculations - as of this point in time.
Did you look at natural variability in the last 100,000 years - 23 abrupt climate changes with temperature variations of 10°C to 15°C (and more) many of which happened within a decade?
Rahmstorf, Severinghaus, Alley and numerous others concur. Abrupt changes can be far more extreme than what is seen today. IPCC reports also support abrupt climate change although the latest reports are less likely to acknowledge these abrupt changes.
Ted,
A while back I looked at ice ages - Ghosts of Climates Past series - https://scienceofdoom.com/roadmap/ghosts-of-climates-past/
My recollection from a number of papers was - as you say - abrupt climate change of large magnitude - often called Dansgaard-Oeschger events. I think the large temperature variation was regional.
According to Stefan Rahmstorf (Postdam Institute) the variation was world-wide. 170+ locations including New Zealand and Antarctica. The multi-coauthored book 'Abrupt Climate Change' also stated it was a global phenomenon. I don't recall off the top of my head what Alley (Two Mile Time Machine etc) or others have stated, it's been a while since I read that research.
Ted, how did they conclude that it was a global phenomenon? Global paleoclimate reconstructions don't currently go back that far.
They're referring to 23 abrupt image changes in the last 100,000 years.
Prof Rahmstorf (Potsdam Institute) stated that these abrupt climate changes have been validated as 𝙜𝙡𝙤𝙗𝙖𝙡 at more than 170 locations around the world - including New Zealand and Antarctica.
[Munich Re, Weather catastrophes and climate change: Abrupt Climate Change 2004]
Bob,
Ages ago I banned you at the original blog for non-stop repetition and failing to engage with the argument. So I'm banning you again. Anyone interested in Bob's words of wisdom can find them, for example, at https://scienceofdoom.com/2014/06/26/the-greenhouse-effect-explained-in-simple-terms/ - just search for his name.
I'm simply confused by why you're willing to take it as a given that the 1980(ish) data was wrong, but you're convinced that the modern temperature data series is correct.
The 2015 changes became known as the 'Pause Buster' so it was indeed very significant. One contributor to SKS was consolidating a list of 'hiatus' papers. The last I checked (couple of years ago) he was expecting to top 300 peer-reviewed papers.
If you read those papers, there's more than FIVE DOZEN varying opinions at to why the hiatus - Yet another indication of a very significant deviation from the models and the theory.
As for "waaaay overblown" Michael E Mann stated that it was very significant - he argued quite strongly that we "shouldn't sweep it under the rug"
I've yet to see evidence of CO₂ induced warming, I hope it will happen but I'm not not convinced it has. Are you aware of Dr Hansen's take on CO₂ correlation to temp, namely that the trends may appear similar but that doesn't mean CO₂ caused the changes (IIRC, it was Hansen et al. 1981)
So can you definitively identify the cause of the hiatus (aka warming slowdown)?
I understand a willingness to discount something out-of-hand that can't be explained as "waaay overblown"
When a person uses that rhetoric, they've identified a fault that they won't acknowledge.
Where is the hotspot for the CO2 theory. It hasn't been found.
The hotspot does not derive from "CO2 theory"; it comes from *any* tropical warming under a strict adherence to the moist adiabatic lapse rate.
And, strictly speaking, it's a negative feedback, as it involves lofting heat higher into the troposphere where that heat can then more easily radiate to space.
But, point is: this isn't a problem for the idea of CO2-induced warming. It has to do with modeling convection in the tropical mid/upper-troposphere under surface warming in general.
Berkeley Earth link:
"As 𝙗𝙪𝙤𝙮 𝙢𝙚𝙖𝙨𝙪𝙧𝙚𝙢𝙚𝙣𝙩𝙨 have replaced ship measurements, this had hidden some of the real-world warming.
After correcting for this “𝙘𝙤𝙡𝙙 𝙗𝙞𝙖𝙨,”
https://news.berkeley.edu/2017/01/04/global-warming-hiatus-disproved-again/
The cold bias is in the integrated SST data, from how the ship and buoy data combine. Granted, those two lines you quoted together could use some editing, but that isn’t a peer-reviewed paper. (And that kind of word-slip can and does show up in peer-reviewed papers, when everyone understands the point being made, simply by context alone).
From the same article:
“But the buoys report slightly cooler temperatures because they measure water directly from the ocean instead of after a trip through a warm engine room.”
Which is a more accurate reading of the ocean temperatures? Measuring water directly from the ocean, or measuring it after a trip through the warm engine room?
So which source would be more considered more accurate - the buoys that measure the water directly, or the thermometers that measure water temps after that water has gone through an engine room?
Similarly, look at the first chart in this article. Does the line on the chart for “buoys” line up more with the older NOAA data, or the newer, more-accurate NOAA data?
(It lines up with the newer data)
Or consider this quote from Karl (2015):
> More generally, buoy data have been proven to be more accurate and reliable than ship data, with better known instrument characteristics and automated sampling.
The engine intake data had already been considered and accounted for in previous SST analyses. You're simply making nonsensical excuses because you don't like what they stated.
Facts are facts regardless of your feelings.
You have no intention of participating in an honest discussion.
Stop replying. You're biased AF.
> The engine intake data had already been considered and accounted for in previous SST analyses. You’re simply making nonsensical excuses…
Hey, do you remember when you referenced Karl et al (2015)? They directly addressed this counterargument you just made. Here’s a quote:
“Second, there was a large change in ship observations (i.e., from buckets to engine intake thermometers) that peaked immediately prior to World War II. The previous version of ERSST assumed that no ship corrections were necessary after this time, but recently improved metadata (18) reveal that some ships continued to take bucket observations even up to the present day. Therefore, one of the improvements to ERSST version 4 is extending the ship-bias correction to the present, based on information derived from comparisons with night marine air temperatures.”
——
I figured you were already aware of this point, since you keep talking about this paper. I’m kinda surprised that you call this a “nonsensical excuse” when it’s in the paper you referenced.
But Karl (2015) is a great, short, to-the-point paper. Thanks for bringing it to my attention, Ted!
You're not entitled to make up your own facts.
But your continuous deflections & moving the goalposts is exactly would I would expect.
Now you're arguing that the people that wrote the paper and the article on Berkeley Earth have no idea how to write what they mean, they need to rely on your interpretation.
😂
Not at all. They say that the buoy data measures the sea directly, and that’s what they mean. And this, plainly, means that buoy data is more accurate, particularly when they’re also saying that the ship-engine data, for contrast, is warmed by virtue of passing through the engine room.
Or, here’s a quote from the Science Advances article that the Berkeley News article is sourced from:
> Modern ship-based measurements … tend to generate temperature readings around 0.12°C higher than those of buoys, whose sensors are directly in contact with the ocean’s surface. … Although buoy records are **widely considered to be more accurate** than ship-based measurements, their integration with ship records into longer SST series poses a number of challenges. [emph added]
“widely considered to be more accurate”. There it is. In a peer-reviewed scientific article in a top journal, scientists state that the buoy data is widely considered to be more accurate. A direct quote, if the other direct quotes weren’t enough.
So, again, the scientists say that the buoy records are more accurate. Why would it be otherwise? We know they’re switching from ship data to buoy data - why would they be preferring to use *less* accurate data?
https://www.science.org/doi/10.1126/sciadv.1601207
Agree. Failed modelling outputs that predicted a hotspot.