Snowy123 wrote:
I haven't been posting much on this board lately, and I'm starting to think about posting more here again.
Wayne Stollings wrote:
No, it is clear the issues of seasonal variation in the areas where actual warming would be expected to be the greatest is "too noisy" for some reason, such as the conclusions are not supported.
Why would one pick the regions that would have the most contamination in their dataset instead of the less contaminated Tropical Regions, which do not have the albedo contamination and the seasonal variation contamination?
For one thing, those are the areas with the greatest increase in temperatures and if you are trying to prove the global temperature correlation they are the critical areas to include.
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The Tropics are a good place to measure changes in OLR, VS. The Globe, because changes in Tropical OLR have major implications for Earth's Energy Budget.
So they ignore the rest of the globe and assume there is a correlation based on the area they do use even if the temperature increases are greater in the rest of the globe?
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Comparing apples to oranges does what exactly here? Is that graph even from a paper or is it an interoretation based on a paper as we see from CO2 Science?
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The decrease in Tropical Cloud Cover has significant implications for the Global Energy Budget, because this is where heat is redistributed all throughout the globe through oceanic currents and advecting air masses. A change in heat in the tropics has significant implications for the Global temperature, as El Nino and La Nina clearly demonstrate. A decrease in Tropical Cloud Cover which allows for more ISR to reach the Tropics is extremely crucial, because then that extra heat gets distributed throughout the entire globe. Global Warming, if you will.
Implications, possilby, but evidence of global impact is another case. The cloud cover at night retains heat while cloud cover during the day restricts the amount of incoming ISR reaching the ground. High level clouds also have a different impact than low level clouds. So why assume tropical clouds indicate a total global impact?
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In the polar regions, the extra energy recieved would decrease the albedo associated with ice and snow, and you get a positive feedback, where the polar region warms the fastest.
Which supports the conclusion of tropical clouds affecting global temperatures how?
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This change in this Global Cloud Forcing (with most of it coming from the decrease in Tropical Cloud Cover) has allowed for 7 w/m^2 of energy to be added to Earth's Energy Budget over a 21 year timeframe.
If you follow the assumptions presented, which the experts in that field do not seem to do.
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Again, is this from a real paper or someone's interpretation?
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Yes, that would be a good reason to ignore actual changes ......
We're trying to calculate the radiative forcings that have impacted Earth's Energy Budget, not radiative feedbacks. That is a whole another issue.
Then why compare the cloud cover in the tropics to the global temperature, which clearly would include the radiative feedbacks?
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Where the actual warming is not a great too. The picture would come closer to cherry picking as you claim from the use of a complete data set.
Because the extra surplus energy gets distributed from the Tropics to the Mid Latitudes and Polar Regions.
And if there is additional surplus energy directly added in those areas, how is that accounted in this calculation?
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Hurricanes are excellent examples of this.
As is the Gulf current to name just one.
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Their primary function is to remove heat from the Tropical Regions and redistribute them to the temperate and mid latitude regions.
Along with other mechanisms, but that still does not address the energy budget for those regions, which can be different from the tropics in many ways.
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So you are claiming there can be no increase in OLR due to a temperature increase after an increase in water vapor?
In order for there to be an increase in OLR, you would need a SIGNIFICANT change in ISR to increase the OLR, because H2O, even though it is a feedback, has a tremendous implication for the Global Energy Flows.
Not really, as the simple example of a cloudy day with a cloudless night shows. The ISR does not change, although the OLR will compared to a clear day and a cloudy night.
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Yet you seem to claim it is a fait accompli of new science.
The data can speak for itself.
It does and it says it is not complete enough to make such a claim, which was my point concernign your apparant claim.
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Did it help you at all? I hope you noticed there was no energy added from the CO2, water vapor, or clouds because they do not produce energy.
To claim otherwise would just be stupid... the only 'thing' that produces energy is the sun.
Actually, no, the earth and humans add a very small amount of energy to the system. Since I pointed out the more correct reference of energy retention, I assume you now agree with my point.
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The incoming energy not energy added by components within the system
The incoming energy is made up of those components.
No, that is incorrect. The incoming energy is one component, the rest are retention and reflection components within the system which impacts the amount of energy available at the surface.
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First there is no "statistically insignificant cooling" if something is statistically insignificant is is neither cooling nor warming. If it is staitstically significant it will either be cooling or warming, nothing else can be claimed. You claim the clouds are the "main driver" even after admitting "cloud feedback and the cloud forcing are still the most uncertain aspects in Climate Science, and it is a basic given"? The assumptions are rampant and all unsupported by the evidence.
In statistics, something that is statistically insignificant means that it has not met the 95% Confidence Level yet.
The confidence level can be adjusted lower or higher than 95%, the that is the more common level used. There is no warming nor cooling trend if the statistics do not indicate it. The proper position is to extend the time to a point where the trend is statistically significant and use that trend unless and until another trend can be shown to be significant. Thus, you cannot claim a statistically insignificant trqnd. You may hold a belief a trend may show a trend in the future, but without the statistical support you are only looking at noise.
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Thus, it could appear to have a positive or negative slope, while not actually being significant. This would be called a "statistically insignificant cooling or warming."
No, it would be called noise if one were properly looking at the trend. Short term time frames do not show trends easily and you are trying to deal with very short frames.
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Take this HadCrut graph for example. Over the last 10 years there was a negative slope in the temperature, but it has not met the 95% Signficance quite yet.
A statistically insignificant cooling.
How far from showing a statistical trend is it exactly? You will notice several periods of similar dips over the years, but the actual statistical trend is warming once you do the calculations.
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Why try to use statisically insignificant data if the goal is not to attempt to cherry pick?
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I did note the potential effects of a possible link that could .....
Yes, so essentially they say that a solar influence on Climate Change does not directly need to come from TSI alone. Changes in Cloud Cover could significantly alter the climate on Earth.
They state the POTENTIAL effects of a POSSIBLE link COULD have SOME effect, which leaves the probability of significance at a low level. Anything is possible, but most things are not probable and science deals with probabilities.
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There is a basic problem using third party interpretations of data .... it cannot be confirmed the data was properly used.
Huh? The graph sources when the algorithm changes due to a switch in satellites and possible errors in the data.
The third party does not provide what data was actually used for the graph or whether any adjustments were made nor whether the adjustments were consistent with the information the originating source had or provided. That is a problem with third party sources of graphs, especially if the graph was not part of a published paper by the originators of the data. I have seen this too many times from sources like CO2 Science, where they interpret the data themselves to create graphs which may not be as accurate as they appear.
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Yes, and once equilibrium is approached the rate would be similar to the prior level. The rate of evaporation would be locally dependent and may merely be extended for a longer period to approach the new equilibrium.
Once equilibrium is met, we would stop warming, because the amount of OLR leaving Earth would be equal to the amount of ISR reaching Earth.
No, I was speaking of temperature induced atmospheric moisture content, thus the reference to evaporation. The energy buget might not remain balanced at that point due to the localized changes.
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No, the data seems to show a connection, if the data is correct. The causation is still far from proven, however.
Heh? Are you arguing that the decrease in Global aerosoles at the same time GCRs decrease is not enough to say that GCRs are the causation?
Yes. The cause of one may also be the cause of the other, thus a connection but not a cause and effect. I may have a party which cause me to put out copious amounts of food and drink in addition to having large numbers of people showing up. The cause is the party yet there is a connection between the amount of people showing up and the amount of food and drink being made available. Thus, if I assumed the cause of the people showing up was the amount of food and drink being made available I would be surprised if I randomly put out similar amounts of food and drink expecting people to show up. That is correlation not causation and it applies in both cases unless and until the mechanisms are clearly determined and confirmed.
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Take this paper, which shows that GCRs have a significant impact on the diurnal temperature range during FDs, when they have the most evident effect on Climate.
No, it shows correlation as the mechanism is still uncertain.
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They found that within a few days of the Forbush Decrease, (which is a small lag) the diurnal temperature substantially deviates from the normal diurnal temperature mean.
The diurnal temperature mean can be best described as the difference between the daytime and nightime temperatures.
The reason for why the diurnal temperature range would increase right after a FD, indicates not only that GCRs can influence the atmospheric processes on Earth substantially, but they also do so through Cloud Cover changes.
No, it shows there seems to be a link, which is far removed from proof of cause. The CERN experiments clearly showed that GCR was not sufficient to expalin the changes proposed in this case.
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A sudden reduction in GCRs would substanitally lower Cloud Cover for those few days, which would substantially increase the difference in nighttime and daytime temperatures, since Clouds reflect ISR and trap OLR, reducing the diurnal temperature range.
http://www.astrophys-space-sci-trans...7-315-2011.pdf
Except the mechanism assumed is not known and what is known does not support the conclusion. The correlation is apparent, but it does not rise to the level of evidence of causation.
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Quoting Paper
The result strongly supports the idea that
cosmic rays influence the atmospheric processes and climate.
The CERN data shows the probability of an influence too, just not the level you seem to believe is being shown.
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Or take this paper, which also finds a strong correlation between FDs and Global aerosoles, the "seeds" for the Clouds.
http://www.deas.harvard.edu/climate/eli/Courses/F RSEMR22l/Sources/03-Cosmic-rays/3-Svensmark-et-al- 2009-GRL.pdf
Correlation is still not causation and the mechanisms still need to be sufficiently determined.
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The dashed line is the GCR count and the solid blue line is the aerosol number. A short lag in Global aersoles can clearly be seen right after a Forbush Decrease, which indicates a significant CR-Influence on climate, if Forbush Decreases can have that much of an impact on aerosoles.
Or that the same cause affects both data sets, but at different rates. Correlation is not causation unless the mechanisms can be described and confirmed.
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Or take this study which highlights GCRs being a "plausable" Climate Driver:
http://cc.oulu.fi/~usoskin/personal/usoskin_CR_20 08.pdf
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In conclusion, a CR–climate link seems to be a
plausible climate driver, as supported by the bulk of
statistical studies and existing theoretical models.
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I would have to question how a link could be a driver given the CERN data.
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Low Level Cloud Cover and GCRs for Europe as presented by Usoskin et. al 2008.

The evidence from Dragic et. al, Svensmark et. al and Usoskin et. al are enough to convince an objective researcher that GCRs impact the Climate through Cloud Cover changes.
Only if the objective researcher is not familiar with basic science.
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Even if the data they use does not really support that stance .....
The data from CERN does not support the sole impact of GCR on cloud formation nor even the sole cause of the formation of nuclei. That data is critical in showing the mechanism needed to move from correlation to causation.