Climate Change - The Scientific Debate (Vol. II)
Discussion
durbster said:
Globs said:
To track the climate you need to follow the clouds so you can determine the variation in albedo: the primary force of earth climate.
Because the models cannot do this (as amply demonstrated by the failure noted above) ALL climate models are a fiction.
Then how do you explain the fact that the predictions about climate have been largely proven right consistently since the mid 20th century? Do you consider it no more than a massive coincidence, rather than vindication of the science? Because the models cannot do this (as amply demonstrated by the failure noted above) ALL climate models are a fiction.
PRTVR said:
Coincidence, no, models are just predictions, if you make enough of them some will be right, do you not find it strange that clouds are not fully understood and were originally ignored in climate models, mainly due to their complexity , think about that for one moment, something that has a visible and recordable change to the earth's temperature is ignored, now you want me to believe the so called science that they put out, come back to me when clouds are fully understood and all variables are fully understood, solar activity etc. Till that time it is a belief system that I don't subscribe to.
A little unfair the models are incomplete and a work in progress, however there is science involved in creating them. I agree that cherry picking models that match the data you have is not science, but you never know at some point one of them might actually begin to track reality.durbster said:
Globs said:
To track the climate you need to follow the clouds so you can determine the variation in albedo: the primary force of earth climate.
Because the models cannot do this (as amply demonstrated by the failure noted above) ALL climate models are a fiction.
Then how do you explain the fact that the predictions about climate have been largely proven right consistently since the mid 20th century? Do you consider it no more than a massive coincidence, rather than vindication of the science? Because the models cannot do this (as amply demonstrated by the failure noted above) ALL climate models are a fiction.
Submitted by Ø on February 10, 2017
IPCC admits himself that climate models fail...climate change by consensus...
Clouds and Climate Professor Henrik Svensmark:
https://www.youtube.com/watch?v=EgA8zSSC0zI
Svensmark: The Cloud Mystery
https://www.youtube.com/watch?v=ANMTPF1blpQ
The IPCC concluded even as early as 2001 that their research and climate modeling can not be used for long-term predictions of the future climate. For the Panel's Third Assessment Report, paragraph 14.2.2.2 page 774 it says in my translation: "In research and modeling of the climate, we should be aware that we are dealing with a chaotic, nonlinear coupled system, and that long-term predictions of future climate states is not possible. " This I have already mentioned above.
This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
PS
1. Biologist Paul Ehrlich predicted in the 1970s that: “Population will inevitably and completely outstrip whatever small increases in food supplies we make,” and that “The death rate will increase until at least 100-200 million people per year will be starving to death during the next ten years.”
2. In January 1970, Life reported, “Scientists have solid experimental and theoretical evidence to support…the following predictions: In a decade, urban dwellers will have to wear gas masks to survive air pollution…by 1985 air pollution will have reduced the amount of sunlight reaching earth by one half….”
3. In January 2006 Al Gore predicted that we had ten years left before the planet turned into a “total frying pan.” We made it.
4. In 2008, a segment aired on ABC News predicted that NYC would be under water by June 2015.
5. In 1970, ecologist Kenneth E.F. Watt predicted that “If present trends continue, the world will be about four degrees colder for the global mean temperature in 1990, but 11 degrees colder by the year 2000, This is about twice what it would take to put us in an ice age.”
6. In 2008, Al Gore predicted that there is a 75% chance that the entire north polar ice cap would be completely melted within 5-7 years. He at least hedged that prediction by giving himself “75%” certainty.
7. On May 13th 2014 France’s foreign minister said that we only have 500 days to stop “climate chaos.” The recent Paris climate summit met 565 days after his remark.
8. In 2009, National Aeronautics and Space Administration Goddard Space Flight Center head James Wassen warned that Obama only had four years left to save the earth.
9. On the first Earth Day its sponsor warned that “in 25 years, somewhere between 75 and 80 percent of all the species of living animals will be extinct.”
10. And another Earth Day prediction from Kenneth Watt: “At the present rate of nitrogen buildup, it’s only a matter of time before light will be filtered out of the atmosphere and none of our land will be usable.”
Edited by robinessex on Wednesday 13th September 07:17
Toltec said:
PRTVR said:
Coincidence, no, models are just predictions, if you make enough of them some will be right, do you not find it strange that clouds are not fully understood and were originally ignored in climate models, mainly due to their complexity , think about that for one moment, something that has a visible and recordable change to the earth's temperature is ignored, now you want me to believe the so called science that they put out, come back to me when clouds are fully understood and all variables are fully understood, solar activity etc. Till that time it is a belief system that I don't subscribe to.
A little unfair the models are incomplete and a work in progress, however there is science involved in creating them. I agree that cherry picking models that match the data you have is not science, but you never know at some point one of them might actually begin to track reality.PRTVR said:
Coincidence, no, models are just predictions, if you make enough of them some will be right, do you not find it strange that clouds are not fully understood and were originally ignored in climate models, mainly due to their complexity , think about that for one moment, something that has a visible and recordable change to the earth's temperature is ignored,
There's nothing strange about it at all. There wasn't enough computing power to predict cloud formations. Even now they struggle. Also, you're talking about weather.
PRTVR said:
now you want me to believe the so called science that they put out, come back to me when clouds are fully understood
I suspect you'll be waiting a long time. All science is a work in progress; nothing more than what we understand so far. That doesn't mean it doesn't work. The only explanations that are "fully understood" belong to religions.
We don't "fully understand" time, for example, so are you dismissive when somebody tells you it's half past two?
Can you share an example of science you do accept that is fully understood?
Toltec said:
A little unfair the models are incomplete and a work in progress, however there is science involved in creating them. I agree that cherry picking models that match the data you have is not science, but you never know at some point one of them might actually begin to track reality.
Bizarre statement. They already do.Edited by durbster on Wednesday 13th September 07:49
robinessex said:
The IPCC concluded even as early as 2001 that their research and climate modeling can not be used for long-term predictions of the future climate. For the Panel's Third Assessment Report, paragraph 14.2.2.2 page 774 it says in my translation: "In research and modeling of the climate, we should be aware that we are dealing with a chaotic, nonlinear coupled system, and that long-term predictions of future climate states is not possible. " This I have already mentioned above.
This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
The full part of the report that your cut and paste quotes, in context;This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
IPCC said:
In sum, a strategy must recognise what is possible. In climate
research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
Anyone claiming that this statement alone means IPCC modeling is no use for a practical climate policy is either an idiot or pushing an agenda. research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
Jinx said:
DapperDanMan said:
So thousands of PHD's throughout the world say CO2 is an issue but you know for sure it isn't but there is an issue you just don't know what it is. Would you rather drive across a bridge designed and constructed by experts or one done by a bunch of internet googlers?
There is no monomania about CO2. There is loads of work going on to reduce our impact on the planet. Just lately there has been a campaign push about the amount of plastic being dumped in the worlds oceans as just one example. But of course using that word points towards an obsession and obsession is seen as a negative thing.
As I said before science is politically neutral in itself. Stick to the science and don't concern yourself with us and them.
FFs not the bridge analogy again - would I drive over a bridge that thousands of PhD modelers claim has already fallen down years ago and yet I have crossed it every day for the last 10 years?There is no monomania about CO2. There is loads of work going on to reduce our impact on the planet. Just lately there has been a campaign push about the amount of plastic being dumped in the worlds oceans as just one example. But of course using that word points towards an obsession and obsession is seen as a negative thing.
As I said before science is politically neutral in itself. Stick to the science and don't concern yourself with us and them.
You are just some bloke on the internet and yet you seem to have an insight into climate modelling that decades of work has not got. Do you write software for a living? Do you know how that process works? Do you understand iteration?
hairykrishna said:
robinessex said:
The IPCC concluded even as early as 2001 that their research and climate modeling can not be used for long-term predictions of the future climate. For the Panel's Third Assessment Report, paragraph 14.2.2.2 page 774 it says in my translation: "In research and modeling of the climate, we should be aware that we are dealing with a chaotic, nonlinear coupled system, and that long-term predictions of future climate states is not possible. " This I have already mentioned above.
This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
The full part of the report that your cut and paste quotes, in context;This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
IPCC said:
In sum, a strategy must recognise what is possible. In climate
research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
Anyone claiming that this statement alone means IPCC modeling is no use for a practical climate policy is either an idiot or pushing an agenda. research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
To a denier it shows that modelling is full of holes and is a con/lie/conspiracy. The example given showing the deliberate chopping of the paragraph to only support what the poster was pushing and then the leap from that to 'This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.' is just astounding.
durbster said:
There's nothing strange about it at all. There wasn't enough computing power to predict cloud formations. Even now they struggle.
Also, you're talking about weather.
All science is a work in progress; nothing more than what we understand so far. That doesn't mean it doesn't work. The only explanations that are "fully understood" belong to religions.
We don't "fully understand" time, for example, so are you dismissive when somebody tells you it's half past two?
Can you share an example of science you do accept that is fully understood?
Has there ever been a science that has been so heavily politicized ? Climate science appears driven by political objectives, can you tell me of another incomplete and not fully understood science that has worldwide political objectives attached to it ?Also, you're talking about weather.
PRTVR said:
now you want me to believe the so called science that they put out, come back to me when clouds are fully understood
I suspect you'll be waiting a long time. All science is a work in progress; nothing more than what we understand so far. That doesn't mean it doesn't work. The only explanations that are "fully understood" belong to religions.
We don't "fully understand" time, for example, so are you dismissive when somebody tells you it's half past two?
Can you share an example of science you do accept that is fully understood?
Clouds are not just weather, they are a major driver of our climate, but hey let's just ignore it because it's complicated and focus on a minute addition to a trace gas.
DapperDanMan said:
hairykrishna said:
robinessex said:
The IPCC concluded even as early as 2001 that their research and climate modeling can not be used for long-term predictions of the future climate. For the Panel's Third Assessment Report, paragraph 14.2.2.2 page 774 it says in my translation: "In research and modeling of the climate, we should be aware that we are dealing with a chaotic, nonlinear coupled system, and that long-term predictions of future climate states is not possible. " This I have already mentioned above.
This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
The full part of the report that your cut and paste quotes, in context;This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
IPCC said:
In sum, a strategy must recognise what is possible. In climate
research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
Anyone claiming that this statement alone means IPCC modeling is no use for a practical climate policy is either an idiot or pushing an agenda. research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
To a denier it shows that modelling is full of holes and is a con/lie/conspiracy. The example given showing the deliberate chopping of the paragraph to only support what the poster was pushing and then the leap from that to 'This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.' is just astounding.
https://forums.tesla.com/forum/forums/ipcc-admits-...
It is a statement that says, in essence, "Prediction of a single future state is impossible because it's a chaotic system. We therefore have to predict a probability distribution of future states and see how the distribution changes."
Are you trying to claim that leaving out the second part isn't selective?
Are you trying to claim that leaving out the second part isn't selective?
robinessex said:
DapperDanMan said:
hairykrishna said:
robinessex said:
The IPCC concluded even as early as 2001 that their research and climate modeling can not be used for long-term predictions of the future climate. For the Panel's Third Assessment Report, paragraph 14.2.2.2 page 774 it says in my translation: "In research and modeling of the climate, we should be aware that we are dealing with a chaotic, nonlinear coupled system, and that long-term predictions of future climate states is not possible. " This I have already mentioned above.
This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
The full part of the report that your cut and paste quotes, in context;This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.
IPCC said:
In sum, a strategy must recognise what is possible. In climate
research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
Anyone claiming that this statement alone means IPCC modeling is no use for a practical climate policy is either an idiot or pushing an agenda. research and modelling, we should recognise that we are dealing
with a coupled non-linear chaotic system, and therefore that the
long-term prediction of future climate states is not possible. The
most we can expect to achieve is the prediction of the probability
distribution of the system’s future possible states by the genera-
tion of ensembles of model solutions. This reduces climate
change to the discernment of significant differences in the statis-
tics of such ensembles. The generation of such model ensembles
will require the dedication of greatly increased computer
resources and the application of new methods of model
diagnosis. Addressing adequately the statistical nature of climate
is computationally intensive, but such statistical information is essential.
To a denier it shows that modelling is full of holes and is a con/lie/conspiracy. The example given showing the deliberate chopping of the paragraph to only support what the poster was pushing and then the leap from that to 'This little known and surprising fact alone disqualifies large parts of the IPCC's work as a basis for practical climate policy.' is just astounding.
https://forums.tesla.com/forum/forums/ipcc-admits-...
You quoted from another forum and whoever wrote that was selective. So are you being selective or was it an honest misunderstanding?
Toltec said:
PRTVR said:
Coincidence, no, models are just predictions, if you make enough of them some will be right, do you not find it strange that clouds are not fully understood and were originally ignored in climate models, mainly due to their complexity , think about that for one moment, something that has a visible and recordable change to the earth's temperature is ignored, now you want me to believe the so called science that they put out, come back to me when clouds are fully understood and all variables are fully understood, solar activity etc. Till that time it is a belief system that I don't subscribe to.
A little unfair the models are incomplete and a work in progress, however there is science involved in creating them. I agree that cherry picking models that match the data you have is not science, but you never know at some point one of them might actually begin to track reality.Secondly also nice if the actions proposed to solve one perceived problem were fully and scientifically assessed for the suitability of their outcomes in the long term. It appears that this is not a normal situation in science where some sort of socio-political urgency, real or imagined, is invoked.
In the short relatively short life time of active political uptake of the CAGW meme we have, for example, large increases in the cost of energy and farce of the encouragement of diesel powered personal transport based on "sound" science. Those are the most obvious effects in the past decade. The economic effect in terms of the wasted investment due to the early scrapping of electricity generation plant and vehicles has very likely eradicated any gains there may have been towards the original objectives (whether they were valid or not).
If you consider that many would identify the late 1980s and James Hansen's notorious presentation to the US Senate on a very hot day in Washington in June 1988.
Hansen, a scientist in the area of Climate Change, a relatively young branch of science at the time, later turned out to have a personal objective to eradicate the use of coal in favour of Nuclear power. Nationally, in the USA, ha will no doubt be somewhat content to see the use of coal declining rapidly but perhaps disappointed at the lack of nuclear.
Globally I suspect he will be very disappointed in the progress of his ideas in the past 30 years. The ball that he helped to start rolling back then seems to have been re-directed at some point, heading off into less considered directions as it splits through lack of core structural integrity.
No. Chaotic mathematical system can never be solved in the sense of an explicit result. Thus any result derived must by inference be an approximation/assumption.
Chaos theory is a branch of mathematics focused on the behavior of dynamical systems that are highly sensitive to initial conditions. 'Chaos' is an interdisciplinary theory stating that within the apparent randomness of chaotic complex systems, there are underlying patterns, constant feedback loops, repetition, self-similarity, fractals, self-organization, and reliance on programming at the initial point known as sensitive dependence on initial conditions. The butterfly effect describes how a small change in one state of a deterministic nonlinear system can result in large differences in a later state, e.g. a butterfly flapping its wings in Brazil can cause a tornado in Texas.
Small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for such dynamical systems ( a response popularly referred to as the butterfly effect ) rendering long-term prediction of their behavior impossible in general. This happens even though these systems are deterministic, meaning that their future behavior is fully determined by their initial conditions, with no random elements involved. In other words, the deterministic nature of these systems does not make them predictable. This behavior is known as deterministic chaos, or simply chaos. The theory was summarized by Edward Lorenz as:
Chaos: When the present determines the future, but the approximate present does not approximately determine the future.
Chaotic behavior exists in many natural systems, such as weather and climate. It also occurs spontaneously in some systems with artificial components, such as road traffic. This behavior can be studied through analysis of a chaotic mathematical model, or through analytical techniques such as recurrence plots and Poincaré maps. Chaos theory has applications in several disciplines, including meteorology, sociology, physics, environmental science, computer science, engineering, economics, biology, ecology, and philosophy. The theory formed the basis for such fields of study as complex dynamical systems, edge of chaos theory, self-assembly process.
Chaos theory is a branch of mathematics focused on the behavior of dynamical systems that are highly sensitive to initial conditions. 'Chaos' is an interdisciplinary theory stating that within the apparent randomness of chaotic complex systems, there are underlying patterns, constant feedback loops, repetition, self-similarity, fractals, self-organization, and reliance on programming at the initial point known as sensitive dependence on initial conditions. The butterfly effect describes how a small change in one state of a deterministic nonlinear system can result in large differences in a later state, e.g. a butterfly flapping its wings in Brazil can cause a tornado in Texas.
Small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for such dynamical systems ( a response popularly referred to as the butterfly effect ) rendering long-term prediction of their behavior impossible in general. This happens even though these systems are deterministic, meaning that their future behavior is fully determined by their initial conditions, with no random elements involved. In other words, the deterministic nature of these systems does not make them predictable. This behavior is known as deterministic chaos, or simply chaos. The theory was summarized by Edward Lorenz as:
Chaos: When the present determines the future, but the approximate present does not approximately determine the future.
Chaotic behavior exists in many natural systems, such as weather and climate. It also occurs spontaneously in some systems with artificial components, such as road traffic. This behavior can be studied through analysis of a chaotic mathematical model, or through analytical techniques such as recurrence plots and Poincaré maps. Chaos theory has applications in several disciplines, including meteorology, sociology, physics, environmental science, computer science, engineering, economics, biology, ecology, and philosophy. The theory formed the basis for such fields of study as complex dynamical systems, edge of chaos theory, self-assembly process.
PRTVR said:
durbster said:
Globs said:
To track the climate you need to follow the clouds so you can determine the variation in albedo: the primary force of earth climate.
Because the models cannot do this (as amply demonstrated by the failure noted above) ALL climate models are a fiction.
Then how do you explain the fact that the predictions about climate have been largely proven right consistently since the mid 20th century? Do you consider it no more than a massive coincidence, rather than vindication of the science? Because the models cannot do this (as amply demonstrated by the failure noted above) ALL climate models are a fiction.
TX.
PRTVR said:
Toltec said:
PRTVR said:
Coincidence, no, models are just predictions, if you make enough of them some will be right, do you not find it strange that clouds are not fully understood and were originally ignored in climate models, mainly due to their complexity , think about that for one moment, something that has a visible and recordable change to the earth's temperature is ignored, now you want me to believe the so called science that they put out, come back to me when clouds are fully understood and all variables are fully understood, solar activity etc. Till that time it is a belief system that I don't subscribe to.
A little unfair the models are incomplete and a work in progress, however there is science involved in creating them. I agree that cherry picking models that match the data you have is not science, but you never know at some point one of them might actually begin to track reality.robinessex said:
NOAA, great big might, maybe, possiblely, hence a fairy story. Thought this was the Science forum !!!
robinessex said:
No. Chaotic mathematical system can never be solved in the sense of an explicit result. Thus any result derived must by inference be an approximation/assumption.
You dismiss all evidence that uses the language of probability, but also understand that it's impossible to reach absolute conclusions. 
durbster said:
robinessex said:
NOAA, great big might, maybe, possiblely, hence a fairy story. Thought this was the Science forum !!!
robinessex said:
No. Chaotic mathematical system can never be solved in the sense of an explicit result. Thus any result derived must by inference be an approximation/assumption.
You dismiss all evidence that uses the language of probability, but also understand that it's impossible to reach absolute conclusions. Gassing Station | Science! | Top of Page | What's New | My Stuff