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Karlis

Former NASA Scientists, Astronauts Criticize

103 posts in this topic

Alrighty, glad we got that one narrowed down. Yep, those are the ones.

Eh, not 100 percent. I don't know how you're taking all geologic hypotheses as gospel...probably because you're not a geologist. It's called multiple working hypotheses for a reason.

On the plus side, your paper does note that a methane doomsday scenario is highly unlikely, which is a good thing.

We are in substantial agreement.

I got that doomsday scenario from Hansen's "Storms of My Grandchildren." It was written about 2007 or 2008, so he may not have been aware of this when he wrote it. At the moment, even if the gun fires, life will survive it whether we do or not - there isn't enough CO2 in the air to set off an irreversible greenhouse effect. But that's at the moment; we are adding to what's there all the time and we will reach the point where such a disaster becomes possible in a few more decades. I, for one, would prefer to run no risk at all. Any chance of destroying all life, no matter how small, is unacceptable.

Doug

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1. Biological

Which type of analysis do you use when you want to singal out environmental signals in tree ring series which are in an unobersrved, uncontrolled and steadily changing enviroment?

Sounds like you write a lot of exam questions.

That depends on whether you are looking at weather (short term) or climate (long term). The Ouachita Chronology was developed from growth-and-yield studies for which we have blow-by-blow descriptions back to 1985, including ice storms, loggings, thinnings and a fire. Response to logging and thinning follows a classic logistic growth curve that lasts about a decade before suppression sets in. Fire has the same effect over longer time spans, but is marked by an abrupt termination of large, thin-walled cells, development of "box" cells, and a sudden decrease in growth at the point of the fire. When detrending, one must choose a spline longer than the expected growth response one is looking at: for ice storms, that's usually three years; for thinnings, logging and fire it's ten years.

For long-term chronologies, like a temperature series going back 100 years or more, the best model seems to be RCS, though there are others. RCS does not have "the segment length curse" and it is based on actual measurements, not estimates of measurements. The inflection point on the regional growth model for shortleaf pine is in year 5; anything older than that could be detrended with a negative logarythm without removing temperature INCREASES. Unfortunately, a negative logarythm could remove a long-term temperature DECREASE, so one has to watch out for it. Should this happen, the regression coefficient becomes positive, so it's easy to spot.

So the anser to your questions is: "that depends."

2. Statistical

Would you agree the use of EPS, SSS and RBAR statistics in dendroclimatology tell us nothing about the TRUE strength of environmental signals?

No. Those are estimates of signal strength, so they had better tell you something about true signal strength. If not, why use them? These are all pointing at the issue of sample size. In most chronologies, it is standard practice to publish everything down to the last tree ring and let the reader decide for himself if the signal is strong enough for his purposes. The minimum standard chronology size these days is 20 series, but there is a trend toward chronologies containing hundreds of series. But no matter how many series you have, the farther back you go, the less data you have until you either reach a cutoff point, or you run out of series. I use an eight-series minimum because that is the minimum needed to get a good cross-date. To detect an ice storm, you need 2/p, where p is the proportion of series with growth responses less than a pre-determined index value, usually 0.3 to 0.4. If you have more data, use it.

3. Emergence

When it comes to the principles of emergence in biological systems, has any exquisite mathematical models been devolped? If not, wouldn't you say its a fundamental flaw in our biological theory?

I am not aware of any. But, then, I am a forester-turned-dendrochronologist. I know it says "biologist" in my job description, but my concentration is applications more than theory.

Doug

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We are in substantial agreement.

I got that doomsday scenario from Hansen's "Storms of My Grandchildren." It was written about 2007 or 2008, so he may not have been aware of this when he wrote it. At the moment, even if the gun fires, life will survive it whether we do or not - there isn't enough CO2 in the air to set off an irreversible greenhouse effect. But that's at the moment; we are adding to what's there all the time and we will reach the point where such a disaster becomes possible in a few more decades. I, for one, would prefer to run no risk at all. Any chance of destroying all life, no matter how small, is unacceptable.

Doug

Alrighty, I see what you mean. I'm also not in favor of all life being destroyed.

Where I have a problem with a lot of the standard AGW fare, is that it tends to sensationalize itself. That tends to cripple meaningful dialogue, and alienates me. I do believe that pumping CO2 into the atmosphere is doing nothing helpful for us long term. We really should get our act together, and fix our infrastructure and culture. On the other hand, we really shouldn't view any point in Earth's climate as being "ideal" because it'll change on us regardless of our actions. That our actions are exacerbating it at this point is almost undeniable. So, we should fix the problem. We should minimize our impact on the climate, and make ourselves adaptable to it. This should come with renewable energy, and an end on fossil fuel dependence.

Also, wind turbines just look frickin' cool.

Well that's my two cents on AGW. Fairly moderate, I think.

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Alrighty, I see what you mean. I'm also not in favor of all life being destroyed.

Protection of life no matter what it is. That's also why I defend the cause.

Where I have a problem with a lot of the standard AGW fare, is that it tends to sensationalize itself. That tends to cripple meaningful dialogue, and alienates me.

I understand. Really. Can't blame you for that at all because I also feel this way about people like this group "Plants Need CO2" that put up so much crap and act as if AGW is a pure myth whth rediculous "facts" and false information. This is for me a form of sensationalization as well. Not only that, but allegedly lying about it is scientificaly and moraly wrong. We are talking about scientists, some of which are well known, that get paied to lie. As simple as that.

We really should get our act together, and fix our infrastructure and culture. On the other hand, we really shouldn't view any point in Earth's climate as being "ideal" because it'll change on us regardless of our actions. That our actions are exacerbating it at this point is almost undeniable. So, we should fix the problem. We should minimize our impact on the climate, and make ourselves adaptable to it. This should come with renewable energy, and an end on fossil fuel dependence.

Also, wind turbines just look frickin' cool.

Very well said. The point is indeed adaptation here. With current trends, climate will change anyways. Question is; how far are we willing to take the risk?

Peace.

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Posted (edited)

Where I have a problem with a lot of the standard AGW fare, is that it tends to sensationalize itself.

Do you recognize the name Gilbert White? He was an ecology professor at CU Boulder. He's the one who came up with the proposal that floods are not natural disasters: they're man-made disasters. We know about how often they happen, how deep the water will be and where. All we have to do to avoid them is build our houses, businesses, etc. somewhere else (or flood-proof them). But we don't.

Boulder ("Four square miles surrounded by reality") has a lot of eco-freaks: people who talk a good line, but don't really understand what they're talking about and want somebody - anybody - other than them, to do the work and pay the cost. How effective the talkers are may be judged from the fact that Boulder, in 25 years of "ecology" activism, has yet to synchronize its traffic lights along Broadway, Arapahoe, Canyon, 28th and 30th. Every morning, cars by the hundreds sit there belching exhaust.

Gilbert, a professional ecologist, dealt with those issues daily and had little respect for the talkers. And that seems to be the problem: the professionals can't get a word in edge-wise because the know-nothings are monopolizing the dialogue. That is happening on both sides.

Also, wind turbines just look frickin' cool.

I think so too, but just try to get a wind farm put in offshore near Hyanisport.

Doug

Edited by Doug1o29

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Posted (edited)

Sounds like you write a lot of exam questions.

Thank you Doug for taking the time to answer my questions.

That depends on whether you are looking at weather (short term) or climate (long term). The Ouachita Chronology was developed from growth-and-yield studies for which we have blow-by-blow descriptions back to 1985, including ice storms, loggings, thinnings and a fire. Response to logging and thinning follows a classic logistic growth curve that lasts about a decade before suppression sets in. Fire has the same effect over longer time spans, but is marked by an abrupt termination of large, thin-walled cells, development of "box" cells, and a sudden decrease in growth at the point of the fire. When detrending, one must choose a spline longer than the expected growth response one is looking at: for ice storms, that's usually three years; for thinnings, logging and fire it's ten years.

For long-term chronologies, like a temperature series going back 100 years or more, the best model seems to be RCS, though there are others. RCS does not have "the segment length curse" and it is based on actual measurements, not estimates of measurements. The inflection point on the regional growth model for shortleaf pine is in year 5; anything older than that could be detrended with a negative logarythm without removing temperature INCREASES. Unfortunately, a negative logarythm could remove a long-term temperature DECREASE, so one has to watch out for it. Should this happen, the regression coefficient becomes positive, so it's easy to spot.

So the anser to your questions is: "that depends."

Looking at climate.

What if it's fast climatic changes, instead of very slow climatic changes? As i understand (i may be incorrect) RCS can't be applied when it's fast changes, right?

What type of analysis do you use then?

No. Those are estimates of signal strength, so they had better tell you something about true signal strength. If not, why use them? These are all pointing at the issue of sample size. In most chronologies, it is standard practice to publish everything down to the last tree ring and let the reader decide for himself if the signal is strong enough for his purposes. The minimum standard chronology size these days is 20 series, but there is a trend toward chronologies containing hundreds of series. But no matter how many series you have, the farther back you go, the less data you have until you either reach a cutoff point, or you run out of series. I use an eight-series minimum because that is the minimum needed to get a good cross-date. To detect an ice storm, you need 2/p, where p is the proportion of series with growth responses less than a pre-determined index value, usually 0.3 to 0.4. If you have more data, use it.

Thank you very much!

I am not aware of any. But, then, I am a forester-turned-dendrochronologist. I know it says "biologist" in my job description, but my concentration is applications more than theory.

Doug

Regarding the current state of biological theory.

If that's* the case (there aren't any exquisite mathematical models) then you work in an interesting field! Surprises and new dicoveries could happen in tomorrow's study. Must be really exciting knowing that in your next study you might do a new discovery!

* - Edit

Edited by BFB

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Looking at climate.

There are really only two techniques for excorsizing "the segment length curse." RCS is one. LaMarche's method is another. In it, you develope two chronologies each near the opposite physiological limit for the species. Simply average the two. The limiting physiological factor controlling ring width cancels itself out. Ring widths that don't cancel out are presumed to be due to another cause. LaMarche applied the method to altitude-limited bristlecone pine. As a result, his chronology reflects precipitation very well, but doesn't tell us much about temperatures. This method requires sites from both extremes. It won't work if either extreme site can't be found. Example: Arkansas shortleaf pine is not limited by elevation; in McCurtain County, it gets close to sea level and it does just fine, thank you, on top of Mount Magazine. As a result, the LaMarche method won't work in this case.

Every statistical method relies on underlying assumptions to be true. If one or more are not true, then the results are questionable. We measure forest growth on the assumption that all trees are independent samples. But what about root-grafting? I have two trees in my dataset that broke off below the crown in the Christmas 2000 ice storm. One had no crown at all left and the other had a single three-foot branch 30 feet up. Their prospects looked so bad that the measurement crew recorded them as dead. Seven years later I cored them. Both had continued to grow, albeit very slowly. The one with no crown still had no crown. The other was gradually regrowing its crown. Root-grafting is the only explanation I can think of and it very definitely means the assumption of independence is not true, at least, within plots.

RCS, likewise has a set of assumptions needed to make it work. Chief among these is that the chronology is all-aged. If the stand is even-aged, then events like drought will result in segments of the standardized curve with depressed growth rates. This, in turn, produces a bias in the climate signal. There are other causes of bias, like "trend-in-signal" that applies to chronologies longer than the segment length, "differing contemporaneous growth rate" bias, "modern sample" (living tree) bias and relationships between growth rate and longevity. Each must be corrected; if not correctable, a climate signal may not be extractable.

The Ouachita Chronology consists of a collection of cores from mostly, even-aged stands. You can't use any single sub-chronology to extract a climate signal. But you can put the sub-chronologies together in a way that produces an RCS curve that is free of the climate signal. That, in turn, can be used to extract an unbiased climate signal.

What if it's fast climatic changes, instead of very slow climatic changes? As i understand (i may be incorrect) RCS can't be applied when it's fast changes, right?

If I had an entire forest with one tree of each age, when I aligned tree rings by age, the sudden change in ring width in a given year(s) would average out over the entire population; it would be invisible in the Regionally Standardized Curve. It would not show any climate-related change. But when the component standardized series are realigned by year, that change would be obvious. So I see no reason that RCS wouldn't work for a rapid climate change.

In dendrochronology, it would be "rapid" if it happened within a single tree's lifespan. "Rapid" climate change might take 60 or 70 years by this definition.

What type of analysis do you use then?

For a change that happens within a single series, fit a model to the series, like a negative logarithm. Then use the residuals to detect the change. In other words: conventional regression will work on short-term changes. Just be careful that the change in question doesn't overlap segment ends; if it does, you're back to RCS.

You could also use a smoothing operation like departures from a seven-year running average to detect storms, for example. Brauning, A. 1994. Dendrochronology for the last 1400 years in eastern Tibet. GeoJournal 34.1 75-95 has a neat way of identifying pointer years. Pointer years with significant negative values indicate some sort of short-term disturbance, like a drought, an ice storm, etc.

Regarding the current state of biological theory.

If that's* the case (there aren't any exquisite mathematical models) then you work in an interesting field! Surprises and new dicoveries could happen in tomorrow's study. Must be really exciting knowing that in your next study you might do a new discovery!

I am mostly concentrating on ways to identify disturbances of different types in the ring patterns created when the tree recovers. That's where the ice storm thing comes in. But it is pretty nifty to be able to look at Brauning's data and identify ice storms in eastern Tibet (The 1962 signal in Figure 2 is probably an ice storm and Figure 3B is the classic ice storm signal.).

Doug

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There are really only two techniques for excorsizing "the segment length curse." RCS is one. LaMarche's method is another. In it, you develope two chronologies each near the opposite physiological limit for the species. Simply average the two. The limiting physiological factor controlling ring width cancels itself out. Ring widths that don't cancel out are presumed to be due to another cause. LaMarche applied the method to altitude-limited bristlecone pine. As a result, his chronology reflects precipitation very well, but doesn't tell us much about temperatures. This method requires sites from both extremes. It won't work if either extreme site can't be found. Example: Arkansas shortleaf pine is not limited by elevation; in McCurtain County, it gets close to sea level and it does just fine, thank you, on top of Mount Magazine. As a result, the LaMarche method won't work in this case.

Every statistical method relies on underlying assumptions to be true. If one or more are not true, then the results are questionable. We measure forest growth on the assumption that all trees are independent samples. But what about root-grafting? I have two trees in my dataset that broke off below the crown in the Christmas 2000 ice storm. One had no crown at all left and the other had a single three-foot branch 30 feet up. Their prospects looked so bad that the measurement crew recorded them as dead. Seven years later I cored them. Both had continued to grow, albeit very slowly. The one with no crown still had no crown. The other was gradually regrowing its crown. Root-grafting is the only explanation I can think of and it very definitely means the assumption of independence is not true, at least, within plots.

RCS, likewise has a set of assumptions needed to make it work. Chief among these is that the chronology is all-aged. If the stand is even-aged, then events like drought will result in segments of the standardized curve with depressed growth rates. This, in turn, produces a bias in the climate signal. There are other causes of bias, like "trend-in-signal" that applies to chronologies longer than the segment length, "differing contemporaneous growth rate" bias, "modern sample" (living tree) bias and relationships between growth rate and longevity. Each must be corrected; if not correctable, a climate signal may not be extractable.

The Ouachita Chronology consists of a collection of cores from mostly, even-aged stands. You can't use any single sub-chronology to extract a climate signal. But you can put the sub-chronologies together in a way that produces an RCS curve that is free of the climate signal. That, in turn, can be used to extract an unbiased climate signal.

If I had an entire forest with one tree of each age, when I aligned tree rings by age, the sudden change in ring width in a given year(s) would average out over the entire population; it would be invisible in the Regionally Standardized Curve. It would not show any climate-related change. But when the component standardized series are realigned by year, that change would be obvious. So I see no reason that RCS wouldn't work for a rapid climate change.

In dendrochronology, it would be "rapid" if it happened within a single tree's lifespan. "Rapid" climate change might take 60 or 70 years by this definition.

For a change that happens within a single series, fit a model to the series, like a negative logarithm. Then use the residuals to detect the change. In other words: conventional regression will work on short-term changes. Just be careful that the change in question doesn't overlap segment ends; if it does, you're back to RCS.

You could also use a smoothing operation like departures from a seven-year running average to detect storms, for example. Brauning, A. 1994. Dendrochronology for the last 1400 years in eastern Tibet. GeoJournal 34.1 75-95 has a neat way of identifying pointer years. Pointer years with significant negative values indicate some sort of short-term disturbance, like a drought, an ice storm, etc.

I am mostly concentrating on ways to identify disturbances of different types in the ring patterns created when the tree recovers. That's where the ice storm thing comes in. But it is pretty nifty to be able to look at Brauning's data and identify ice storms in eastern Tibet (The 1962 signal in Figure 2 is probably an ice storm and Figure 3B is the classic ice storm signal.).

Doug

Thank you very much for the comprehensive answers!

I have been reading a book about dendroclimatology, which left me with some unanswered questions. Always a pleasure knowing you can answer these!

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Thank you very much for the comprehensive answers!

I have been reading a book about dendroclimatology, which left me with some unanswered questions. Always a pleasure knowing you can answer these!

Was it Speer's "Fundamentals of Tree-Ring Research"? It's a good book, but is doesn't give you the nitty-gritty on how to do things.

Doug

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Posted (edited)

Was it Speer's "Fundamentals of Tree-Ring Research"? It's a good book, but is doesn't give you the nitty-gritty on how to do things.

Doug

Hahaha how did you know? That and a book called "dendroclimatology: progress and prospects"

Yes a pretty good books if you want the basics, but i do feel the authors sometimes raises more questions than he answers.

Edited by BFB

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Well like I said I still personally feel that there are flaws with RCS and will continue that opinion, some of which is clearly illustrated but you feel I misunderstand the process, we could go around in circles with this but I think we have made our points. You sir are welcome to your research and I gracefully bow out of the thread and wish you well my friend.

I will look to your published findings with interest, at least in saying I disagree with what you are trying to prove, I am willing, and I would hope educated enough, to read the findings to the contrary and hear what you have to say, only then can someone genuinely say they disagree even though I have read many like it before.

Forgive me for missing this earlier, but I think I know some of what is bothering you about RCS. The deniers have tried to make a big issue of the pitfalls listed in Briffa and Melvin's* paper, forgetting that each problem listed has a solution (The paper isn't real clear about some of them.).

One problem is that if you have a lot of trees of the same age, then some years tend to be heavily represented in the sample, while others are lightly represented. This allows a climate signal to leak into the standardized curve. There is no solution to this problem if you have a small sample (You may not be able to do your climate study.), but with a large, all-aged sample it is soluble: using only reliably-dated trees (pith dates), select equal numbers of series from each age class (decades). Try to spread the sample as evenly as possible through the class, giving priority to series with the highest inter-correlation values. From this group, use only ring-widths from a specific span of tree pith ages (like 10 to 40 years). Do not use data from later or earlier rings, even if it's present. Build your standardized curve from this data. This eliminates the uneven-sampling problem and ensures that dates of approximately the same age are used in all parts of the standaridized curve, eliminating tree age as a variable.

You can use the standarized curve without smoothing it, you can smooth it with something like a running average or cubic spline, or you can model it: the model that is best-able to capture the shape of these curves is the Hugershoff model. That's the purpose it was created for. It's major drawback is that it is too flexible: it can take on many different shapes, including ones that trees can't. But with a large sample (at least 100 series in the first 100 years) the shape of the sample will dictate the shape of the curve. Divide each value in the dated series by the corresponding value from the standardized curve. Realign the observation by date and average them. That's the growth signal without tree age in it.

The problems of trend-in-bias, differing-contemporaneous-growth-rate, modern-sample bias, etc. can be solved by modelling. First create a general model to "explain" as many non-climate variables as possible, then use dummy variables to adapt it to each series. If you have a general model with six variables and 100 series, you can end up with 606 terms in your model. Use a step-wise regression to eliminate the insignificant terms. The residuals from this process are your climate signal.

A storm that broke off branches will leave narrow rings that aren't related to climate. Use the published signatures and/or a pointer process to identify these rings and delete them from your data set before you fit climate data. Also, if you have sufficient data, you may want to model the effects of competition and remove those from the data.

Now, fit climate data like temperature or PDSI values to your climate signal. Use this model to predict values of temperature, etc. going back as far as your ring-width data will allow.

The results will be climate indices that are derived using different models: a term that is signifcant in one dataset may not be so in another. This seems to be one of the things you are complaining about in RCS: there are no standard models for eliminating the effects of all non-climate varibales. And each known variable can have a different effect in a different species: oaks are less-sensitive to short-term precipitation changes than are pines. Medicine has it easy: it only deals with one species with one set of responses.

There are also some philosophical issues: is a volcanic eruption that cools the entire earth for three years a "climate variable" or not? But these problems come up in every science.

I hope that better-explains RCS.

Doug

*Briffa, Keith R. and Thomas M. Melvin. 1995. A closer look at regional curve standardization of tree-ring records: justification of the need, a warning of some pitfalls, and suggested improvements in its application In Hughes, M. K. H. F. Diaz and T. W. Swetnam, eds., Dendroclimatology: progress and prospects. Springer Verlag

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In an unprecedented slap at NASA’s endorsement of global warming science, nearly 50 former astronauts and scientists--including the ex-boss of the Johnson Space Center--claim the agency is on the wrong side of science and must change course or ruin the reputation of the world’s top space agency.

Challenging statements from NASA that man is causing climate change, the former NASA executives demanded in a letter to Administrator Charles Bolden that he and the agency “refrain from including unproven remarks” supporting global warming in the media.

NASA had no immediate comment.

http://washingtonexaminer.com/politics/washington-secrets/2012/04/astronauts-condemn-nasa%E2%80%99s-global-warming-endorsement/469366

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4th thread on this, now can we consolidate it all in one?

1 person likes this

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Posted (edited)

4th thread on this, now can we consolidate it all in one?

Yeah, how many times must it be pointed out none of them are climateologists?

Or that 50 from NASA is a very small number compared to the rest of the organization?

Edited by ShadowSot

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Yeah, how many times must it be pointed out none of them are climateologists?

Or that 50 from NASA is a very small number compared to the rest of the organization?

Do you not see why it is of some importance that, "nearly 50 former astronauts and scientists--including the ex-boss of the Johnson Space Center--claim the agency is on the wrong side of science and must change course or ruin the reputation of the world’s top space agency"?

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Do you not see why it is of some importance that, "nearly 50 former astronauts and scientists--including the ex-boss of the Johnson Space Center--claim the agency is on the wrong side of science and must change course or ruin the reputation of the world’s top space agency"?

no. please explain why 50 non-climatologists opinion matters to climate change and 50 being a vanishingly small percentage of the organization. And obviously THOUSANDS of people who work for NASA disagree with these shrubs.

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no. please explain why 50 non-climatologists opinion matters to climate change and 50 being a vanishingly small percentage of the organization. And obviously THOUSANDS of people who work for NASA disagree with these shrubs.

50 NASA people think about what NASA is all about, I guess.

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Could it be because NASA had to come to an intimate understanding of the dangers of "groupthink" and maybe they are looking at climate science through just such a prism?

Please don't beat me, I'm not a scientist.....

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Could it be because NASA had to come to an intimate understanding of the dangers of "groupthink" and maybe they are looking at climate science through just such a prism?

Please don't beat me, I'm not a scientist.....

I thought that the article was of interest, "simply because" NASA personnel thought it worth making such a statement, which they must have known would attract a lot of attention.

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One comment here while I figure out this new format:

Would Karlis get his annual health physical from an astronaut? How about getting a cancer treatment from his local dendrochronologist? These are scientists every bit as much as his medical doctor.

So why not go to them for an opinion? BECAUSE THEY DON'T KNOW ANYTHING ABOUT THE TOPIC.

There are a lot of folks out there who think that a Ph.D. in something makes them experts on everything, especially subjects they know nothing about.

Doug

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One comment here while I figure out this new format:

Would Karlis get his annual health physical from an astronaut? How about getting a cancer treatment from his local dendrochronologist? These are scientists every bit as much as his medical doctor.

So why not go to them for an opinion? BECAUSE THEY DON'T KNOW ANYTHING ABOUT THE TOPIC.

There are a lot of folks out there who think that a Ph.D. in something makes them experts on everything, especially subjects they know nothing about.

Doug

That was a straw man post, Doug. Consider this excerpt from the OP article.

In their letter, the group said that thousands of years of data challenge modern-day claims that man-made carbon dioxide is causing climate change. “With hundreds of well-known climate scientists and tens of thousands of other scientists publicly declaring their disbelief in the catastrophic forecasts, coming particularly from (NASA’s) Goddard Institute for Space Studies leadership, it is clear that the science is NOT settled,” they wrote.

...

“The unbridled advocacy of CO2 being the major cause of climate change is unbecoming of NASA’s history of making an objective assessment of all available scientific data prior to making decision or public statements,” the critics added.

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Karlis, the greater consensus is anthropomorphic climate change. We're talking millions of scientists trained in climate study versus a few thousand of various unrelated or related fields. Ashas been pointed out in threads on evolution we can lists hundreds of scientists with the name "Steve."

As far as the thread, why've you made another thread on the same subject? Why not just bump one of the existing thread(s)?

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Karlis, the greater consensus is anthropomorphic climate change. We're talking millions of scientists trained in climate study versus a few thousand of various unrelated or related fields. Ashas been pointed out in threads on evolution we can lists hundreds of scientists with the name "Steve."

As you yourself just stated, there is a multiplicity of opinions concerning Global Warming.

As far as the thread, why've you made another thread on the same subject? Why not just bump one of the existing thread(s)?

This thread concerns opinions held by specific NASA people. It's not related to other topics.

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Posted (edited)

That was a straw man post, Doug. Consider this excerpt from the OP article.

OK. It was a straw-man post. But it's not like these guys are actually qualified climate scientists.

In their letter, the group said that thousands of years of data challenge modern-day claims that man-made carbon dioxide is causing climate change. “With hundreds of well-known climate scientists and tens of thousands of other scientists publicly declaring their disbelief in the catastrophic forecasts, coming particuThis isn't rocklarly from (NASA’s) Goddard Institute for Space Studies leadership, it is clear that the science is NOT settled,” they wrote.

What "thousands of years of data"? APG has only been around, since 1908 or so. Before that it was indistinguishable from background. It wasn't even detected until the 1960s. To get "thousands of years" of data, you have to rely on proxies - and it's those proxies that are telling us we've got a problem: If you want to know how hot it will be when CO2 levels reach 800 ppm, you look at how hot it was last time they reached 800 ppm.

This isn't rocket science.

Doug

Edited by Doug1o29

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As you yourself just stated, there is a multiplicity of opinions concerning Global Warming.

This thread concerns opinions held by specific NASA people. It's not related to other topics.

There's also many opinions about wether or not the Earth is round, rotating around the sun, ect. Surprisingly many of these people share a similar issue of having no relevamt skill in the field. My point with the scientists named Steve is you are talking about a very minor amount of scientists who are well... Irrelevant to this disscusion.

These specific Nasa people have an opinion as good as a layman in this situation. To give an example, einstein was brilliant. However he rejected quantum mechanics and plate tectonics and was sympathetic towards Velikovsky. A scientist speaking outside of his field is as much a fool as the next man.

And this some multiple of the exact same topic dealing with related to Nasa dissentimg from AGC.

For example, this thread posted by you on the exact same topic: here

In this same forum.

Can we at least get them merged?

Edited by ShadowSot

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