quote:

To: Senator James M. Inhofe
From: Drs. J. Scott Armstrong and Kesten C. Green
Re: Your Request for an Analysis of the U.S. Environmental Protection Agency’s Advanced Notice of Proposed Rulemaking for Greenhouse Gases
Statement
Scientific understanding about the Earth’s climate is tentative at best. As a result of uncertainties over what causes climate to change and how and when, there are rival theories and arguments among scientists about how to interpret the evidence.
Rather than join these arguments, we have examined the processes that have been used to analyze the available data in order to derive forecasts of climate over the 21st Century. We have concluded that the forecasting process reported on by the Intergovernmental Panel on Climate Change (IPCC) lacks a scientific basis.
1. No scientific forecasts of the changes in the Earth’s climate. Currently, the only forecasts are those based on the opinions of some scientists. Computer modeling was used to create scenarios (i.e., stories) to represent the scientists’ opinions about what might happen. The models were not intended as forecasting models (Trenberth 2007) and they have not been validated for that purpose. Since the publication of our paper, no one has provided evidence to refute our claim that there are no scientific forecasts to support global warming.
We conducted an audit of the procedures described in the IPCC report and found that they clearly violated 72 scientific principles of forecasting (Green and Armstrong 2008). (No justification was provided for any of these violations.) For important forecasts, we can see no reason why any principle should be violated. We draw analogies to flying an aircraft or building a bridge or performing heart surgery—given the potential cost of errors, it is not permissible to violate principles.
2. Improper peer review process. To our knowledge, papers claiming to forecast global warming have not been subject to peer review by experts in scientific forecasting.
3. Complexity and uncertainty of climate render expert opinions invalid for forecasting. Expert opinions are an inappropriate forecasting method in situations that involve high complexity and high uncertainty. This conclusion is based on over eight decades of research. Armstrong (1978) provided a review of the evidence and this was supported by Tetlock’s (2005) study that involved 82,361 forecasts by 284 experts over two decades.
Long-term climate changes are highly complex due to the many factors that affect climate and to their interactions. Uncertainty about long-term climate changes is high due to a lack of good knowledge about such things as:
a) causes of climate change,
b) direction, lag time, and effect size of causal factors related to climate change,
c) effects of changing temperatures, and
2
d) costs and benefits of alternative actions to deal with climate changes (e.g., CO2 markets). Given these conditions, expert opinions are not appropriate for long-term climate predictions.
4. Forecasts are needed for the effects of climate change. Even if it were possible to forecast climate changes, it would still be necessary to forecast the effects of climate changes. In other words, in what ways might the effects be beneficial or harmful? Here again, we have been unable to find any scientific forecasts—as opposed to speculation—despite our appeals for such studies.
We addressed this issue with respect to studies involving the possible classification of polar bears as threatened or endangered (Armstrong, Green, and Soon 2008). In our audits of two key papers to support the polar bear listing, 41 principles were clearly violated by the authors of one paper and 61 by the authors of the other. It is not proper from a scientific or from a practical viewpoint to violate any principles. Again, there was no sign that the forecasters realized that they were making mistakes.
5. Forecasts are needed of the costs and benefits of alternative actions that might be taken to combat climate change. Assuming that climate change could be accurately forecast, it would be necessary to forecast the costs and benefits of actions taken to reduce harmful effects, and to compare the net benefit with other feasible policies including taking no action. Here again we have been unable to find any scientific forecasts despite our appeals for such studies.
6. To justify using a climate forecasting model, one would need to test it against a relevant naïve model. We used the Forecasting Method Selection Tree to help determine which method is most appropriate for forecasting long-term climate change. A copy of the Tree is attached as Appendix 1. It is drawn from comparative empirical studies from all areas of forecasting. It suggests that extrapolation is appropriate, and we chose a naïve (no change) model as an appropriate benchmark. A forecasting model should not be used unless it can be shown to provide forecasts that are more accurate than those from this naïve model, as it would otherwise increase error. In Green, Armstrong and Soon (2008), we show that the mean absolute error of 108 naïve forecasts for 50 years in the future was 0.24°C.
7. The climate system is stable. To assess stability, we examined the errors from naïve forecasts for up to 100 years into the future. Using the U.K. Met Office Hadley Centre’s data, we started with 1850 and used that year’s average temperature as our forecast for the next 100 years. We then calculated the errors for each forecast horizon from 1 to 100. We repeated the process using the average temperature in 1851 as our naïve forecast for the next 100 years, and so on. This “successive updating” continued until year 2006, when we forecasted a single year ahead. This provided 157 one-year-ahead forecasts, 156 two-year-ahead and so on to 58 100-year-ahead forecasts. We then examined how many forecasts were further than 0.5°C from the observed value. Fewer than 13% of forecasts of up to 65-years-ahead had absolute errors larger than 0.5°C. For longer horizons, fewer than 33% had absolute errors larger than 0.5°C. Given the remarkable stability of global mean temperature, it is unlikely that there would be any practical benefits from a forecasting method that provided more accurate forecasts.
8. Be conservative and avoid the precautionary principle. One of the primary scientific principles in forecasting is to be conservative in the darkness of uncertainty. This principle also argues for the use of the naive no-change extrapolation. Some have argued for the
3
precautionary principle as a way to be conservative. It is a political, not a scientific principle. As we explain in our essay in Appendix 2, it is actually an anti-scientific principle in that it attempts to make decisions without using rational analyses. Instead, cost/benefit analyses are appropriate given the available evidence which suggests that temperature is just as likely to go up as down. However, these analyses should be supported by scientific forecasts.
References
Armstrong, J.S., (1978, 1985), Long-range Forecasting. New York: John Wiley. (In full text at http://jscottarmstrong.com)
Armstrong, J.S., K. C. Green, W. Soon, (2008), "Polar bear population forecasts: a public-policy forecasting audit," Interfaces, 38, 382-405. (Working paper with commentary in full text at http://publicpolicyforecasting.com)
Green, K.C. & J.S. Armstrong (2007), “Global warming: Forecasts by scientists versus scientific forecasts,” Energy & Environment, 18, 997-1022. (Working paper in full text at http://publicpolicyforecasting.com)
Green, K. C., J.S. Armstrong, W. Soon (2009), " Validity of Climate Change Forecasting for Public Policy Decision Making," forthcoming, International Journal of Forecasting (Working paper in full text at http://publicpolicyforecasting.com) Tetlock, P. E. (2005). Expert Political Judgment: How Good Is It? How Can We Know? Princeton Univ. Press.
Trenberth, K. (2007). Predictions of climate. [Retrieved June 2, 2008 from http://blogs.nature.com/climat...ons_of_climate.html]. Information on the authors
We are experts in scientific forecasting methods. Dr. Armstrong has been working in the field for 48 years. He is a founder of the International Journal of Forecasting, Journal of Forecasting, International Institute of Forecasters, and International Symposium on Forecasting, and the author of Long-range Forecasting (1978, 1985), the Principles of Forecasting Handbook, and over 70 papers on forecasting. Dr. Green has developed two important new forecasting methods and has published seven articles on forecasting. His first article was accompanied by six commentaries and was awarded Best Paper of 2002-2003 by the International Journal of Forecasting. Dr Green established publicpolicyforecasting.com to promote the use of scientific forecasting methods to help improve public policy decision making. Along with Dr. Armstrong, he is a director of forecastingprinciples.com. Original submission: November 20, 2008; reformatted and updated January 26, 2009
4
Appendix 1: Forecasting methods selection Tree
5
Appendix 2 Uncertainty, the Precautionary Principle, and Climate Change Kesten C. Green & J. Scott Armstrong August 9, 2008 The precautionary principle is a political principle, not a scientific one. The principle is used to urge the cessation or avoidance of a human activity in situations of uncertainty, just in case that activity might cause harm to human health or the natural environment. There is an interesting discussion of the history of the term in Wikipedia. In practice, the precautionary principle is invoked when an interest group identifies an issue that can help it to achieve its objectives. If the interest group is successful in its efforts to raise fears about the issue, the application of the scientific method is rejected and a new orthodoxy is imposed. Government dictates follow. People who dissent from the orthodox view are vilified, ostracized, and may have their livelihoods taken away from them. Consider the case of “climate change”. Warnings of dangerous manmade global warming from scientists, politicians, and celebrities have received much publicity. They admonish us to dramatically reduce emissions of CO2 in order to prevent disaster over the course of the 21st Century. Efforts have been made to stifle a scientific approach to the issue. In an article titled “Veteran climate scientist says 'lock up the oil men'”, James Hanson, who heads the NASA Goddard Institute for Space Studies, was quoted as suggesting that those who promote the ideas of global warming skeptics should be “put on trial for high crimes against humanity.” The skeptics themselves have been ejected from, for example, State Climatologist positions and prevented from publishing research in mainstream journals, and they and their views are routinely attacked. Much complexity and uncertainty surround climate change. The cumulative empirical evidence on proper forecasting procedures suggests that the most appropriate method in this case is naïve extrapolation. In simple terms, this means to forecast no change. Of course there will be change, but with current knowledge there is no more reason to expect warming than to expect cooling. As we describe in our paper, we have been unable to find any forecast derived from evidence-based (scientific) forecasting methods that supports the contention that the world faces dangerous manmade global warming. Appeals for urgent curtailment of human activity “just in case” are often couched in ways that imply that industrial societies are inherently sinful, rather than that there might be a problem to be dealt with. Indeed, interpretation of the precautionary principle is subjective and it is arguable that it is being misapplied to the issue of climate change. Firstly, even if forecasts of increasing temperatures turned out to be accurate, predicted temperatures and other conditions are within the range of variations that have been experienced in the past. There is no evidence that the natural environment “prefers” relatively cool to relatively warm average temperatures. In fact, life in general prefers warmth. Secondly, curtailing human activity would harm people’s health by making them poorer than they would otherwise have been. This is likely to be the case even if curtailing human activity happened to reduce global average temperatures. When the situation is framed in this way, the precautionary principle dictates that it is policies to curtail economically efficient human activity that should themselves be curtailed. The outlook for the climate over the 21st Century is highly uncertain. There is a word in the English language to express high uncertainty. That word is “ignorance”. And ignorance is not a basis for responsible government action. We should expect our politicians to have the courage to resist interest groups’ calls for action in the face of ignorance. The precautionary principle brings to mind the slogan on the Ministry of Truth building in George Orwell’s 1984: “Ignorance is Strength.” Instead of this political principle, we hope that politicians will turn to scientific principles for making public policy.

quote:

To: Senator James M. Inhofe
From: Drs. J. Scott Armstrong and Kesten C. Green
Re: Your Request for an Analysis of the U.S. Environmental Protection Agency’s Advanced Notice of Proposed Rulemaking for Greenhouse Gases
Statement
Scientific understanding about the Earth’s climate is tentative at best. As a result of uncertainties over what causes climate to change and how and when, there are rival theories and arguments among scientists about how to interpret the evidence.
Rather than join these arguments, we have examined the processes that have been used to analyze the available data in order to derive forecasts of climate over the 21st Century. We have concluded that the forecasting process reported on by the Intergovernmental Panel on Climate Change (IPCC) lacks a scientific basis.
1. No scientific forecasts of the changes in the Earth’s climate. Currently, the only forecasts are those based on the opinions of some scientists. Computer modeling was used to create scenarios (i.e., stories) to represent the scientists’ opinions about what might happen. The models were not intended as forecasting models (Trenberth 2007) and they have not been validated for that purpose. Since the publication of our paper, no one has provided evidence to refute our claim that there are no scientific forecasts to support global warming.
We conducted an audit of the procedures described in the IPCC report and found that they clearly violated 72 scientific principles of forecasting (Green and Armstrong 2008). (No justification was provided for any of these violations.) For important forecasts, we can see no reason why any principle should be violated. We draw analogies to flying an aircraft or building a bridge or performing heart surgery—given the potential cost of errors, it is not permissible to violate principles.
2. Improper peer review process. To our knowledge, papers claiming to forecast global warming have not been subject to peer review by experts in scientific forecasting.
3. Complexity and uncertainty of climate render expert opinions invalid for forecasting. Expert opinions are an inappropriate forecasting method in situations that involve high complexity and high uncertainty. This conclusion is based on over eight decades of research. Armstrong (1978) provided a review of the evidence and this was supported by Tetlock’s (2005) study that involved 82,361 forecasts by 284 experts over two decades.
Long-term climate changes are highly complex due to the many factors that affect climate and to their interactions. Uncertainty about long-term climate changes is high due to a lack of good knowledge about such things as:
a) causes of climate change,
b) direction, lag time, and effect size of causal factors related to climate change,
c) effects of changing temperatures, and
2
d) costs and benefits of alternative actions to deal with climate changes (e.g., CO2 markets). Given these conditions, expert opinions are not appropriate for long-term climate predictions.
4. Forecasts are needed for the effects of climate change. Even if it were possible to forecast climate changes, it would still be necessary to forecast the effects of climate changes. In other words, in what ways might the effects be beneficial or harmful? Here again, we have been unable to find any scientific forecasts—as opposed to speculation—despite our appeals for such studies.
We addressed this issue with respect to studies involving the possible classification of polar bears as threatened or endangered (Armstrong, Green, and Soon 2008). In our audits of two key papers to support the polar bear listing, 41 principles were clearly violated by the authors of one paper and 61 by the authors of the other. It is not proper from a scientific or from a practical viewpoint to violate any principles. Again, there was no sign that the forecasters realized that they were making mistakes.
5. Forecasts are needed of the costs and benefits of alternative actions that might be taken to combat climate change. Assuming that climate change could be accurately forecast, it would be necessary to forecast the costs and benefits of actions taken to reduce harmful effects, and to compare the net benefit with other feasible policies including taking no action. Here again we have been unable to find any scientific forecasts despite our appeals for such studies.
6. To justify using a climate forecasting model, one would need to test it against a relevant naïve model. We used the Forecasting Method Selection Tree to help determine which method is most appropriate for forecasting long-term climate change. A copy of the Tree is attached as Appendix 1. It is drawn from comparative empirical studies from all areas of forecasting. It suggests that extrapolation is appropriate, and we chose a naïve (no change) model as an appropriate benchmark. A forecasting model should not be used unless it can be shown to provide forecasts that are more accurate than those from this naïve model, as it would otherwise increase error. In Green, Armstrong and Soon (2008), we show that the mean absolute error of 108 naïve forecasts for 50 years in the future was 0.24°C.
7. The climate system is stable. To assess stability, we examined the errors from naïve forecasts for up to 100 years into the future. Using the U.K. Met Office Hadley Centre’s data, we started with 1850 and used that year’s average temperature as our forecast for the next 100 years. We then calculated the errors for each forecast horizon from 1 to 100. We repeated the process using the average temperature in 1851 as our naïve forecast for the next 100 years, and so on. This “successive updating” continued until year 2006, when we forecasted a single year ahead. This provided 157 one-year-ahead forecasts, 156 two-year-ahead and so on to 58 100-year-ahead forecasts. We then examined how many forecasts were further than 0.5°C from the observed value. Fewer than 13% of forecasts of up to 65-years-ahead had absolute errors larger than 0.5°C. For longer horizons, fewer than 33% had absolute errors larger than 0.5°C. Given the remarkable stability of global mean temperature, it is unlikely that there would be any practical benefits from a forecasting method that provided more accurate forecasts.
8. Be conservative and avoid the precautionary principle. One of the primary scientific principles in forecasting is to be conservative in the darkness of uncertainty. This principle also argues for the use of the naive no-change extrapolation. Some have argued for the
3
precautionary principle as a way to be conservative. It is a political, not a scientific principle. As we explain in our essay in Appendix 2, it is actually an anti-scientific principle in that it attempts to make decisions without using rational analyses. Instead, cost/benefit analyses are appropriate given the available evidence which suggests that temperature is just as likely to go up as down. However, these analyses should be supported by scientific forecasts.
References
Armstrong, J.S., (1978, 1985), Long-range Forecasting. New York: John Wiley. (In full text at http://jscottarmstrong.com)
Armstrong, J.S., K. C. Green, W. Soon, (2008), "Polar bear population forecasts: a public-policy forecasting audit," Interfaces, 38, 382-405. (Working paper with commentary in full text at http://publicpolicyforecasting.com)
Green, K.C. & J.S. Armstrong (2007), “Global warming: Forecasts by scientists versus scientific forecasts,” Energy & Environment, 18, 997-1022. (Working paper in full text at http://publicpolicyforecasting.com)
Green, K. C., J.S. Armstrong, W. Soon (2009), " Validity of Climate Change Forecasting for Public Policy Decision Making," forthcoming, International Journal of Forecasting (Working paper in full text at http://publicpolicyforecasting.com) Tetlock, P. E. (2005). Expert Political Judgment: How Good Is It? How Can We Know? Princeton Univ. Press.
Trenberth, K. (2007). Predictions of climate. [Retrieved June 2, 2008 from http://blogs.nature.com/climat...ons_of_climate.html]. Information on the authors
We are experts in scientific forecasting methods. Dr. Armstrong has been working in the field for 48 years. He is a founder of the International Journal of Forecasting, Journal of Forecasting, International Institute of Forecasters, and International Symposium on Forecasting, and the author of Long-range Forecasting (1978, 1985), the Principles of Forecasting Handbook, and over 70 papers on forecasting. Dr. Green has developed two important new forecasting methods and has published seven articles on forecasting. His first article was accompanied by six commentaries and was awarded Best Paper of 2002-2003 by the International Journal of Forecasting. Dr Green established publicpolicyforecasting.com to promote the use of scientific forecasting methods to help improve public policy decision making. Along with Dr. Armstrong, he is a director of forecastingprinciples.com. Original submission: November 20, 2008; reformatted and updated January 26, 2009
4
Appendix 1: Forecasting methods selection Tree
5
Appendix 2 Uncertainty, the Precautionary Principle, and Climate Change Kesten C. Green & J. Scott Armstrong August 9, 2008 The precautionary principle is a political principle, not a scientific one. The principle is used to urge the cessation or avoidance of a human activity in situations of uncertainty, just in case that activity might cause harm to human health or the natural environment. There is an interesting discussion of the history of the term in Wikipedia. In practice, the precautionary principle is invoked when an interest group identifies an issue that can help it to achieve its objectives. If the interest group is successful in its efforts to raise fears about the issue, the application of the scientific method is rejected and a new orthodoxy is imposed. Government dictates follow. People who dissent from the orthodox view are vilified, ostracized, and may have their livelihoods taken away from them. Consider the case of “climate change”. Warnings of dangerous manmade global warming from scientists, politicians, and celebrities have received much publicity. They admonish us to dramatically reduce emissions of CO2 in order to prevent disaster over the course of the 21st Century. Efforts have been made to stifle a scientific approach to the issue. In an article titled “Veteran climate scientist says 'lock up the oil men'”, James Hanson, who heads the NASA Goddard Institute for Space Studies, was quoted as suggesting that those who promote the ideas of global warming skeptics should be “put on trial for high crimes against humanity.” The skeptics themselves have been ejected from, for example, State Climatologist positions and prevented from publishing research in mainstream journals, and they and their views are routinely attacked. Much complexity and uncertainty surround climate change. The cumulative empirical evidence on proper forecasting procedures suggests that the most appropriate method in this case is naïve extrapolation. In simple terms, this means to forecast no change. Of course there will be change, but with current knowledge there is no more reason to expect warming than to expect cooling. As we describe in our paper, we have been unable to find any forecast derived from evidence-based (scientific) forecasting methods that supports the contention that the world faces dangerous manmade global warming. Appeals for urgent curtailment of human activity “just in case” are often couched in ways that imply that industrial societies are inherently sinful, rather than that there might be a problem to be dealt with. Indeed, interpretation of the precautionary principle is subjective and it is arguable that it is being misapplied to the issue of climate change. Firstly, even if forecasts of increasing temperatures turned out to be accurate, predicted temperatures and other conditions are within the range of variations that have been experienced in the past. There is no evidence that the natural environment “prefers” relatively cool to relatively warm average temperatures. In fact, life in general prefers warmth. Secondly, curtailing human activity would harm people’s health by making them poorer than they would otherwise have been. This is likely to be the case even if curtailing human activity happened to reduce global average temperatures. When the situation is framed in this way, the precautionary principle dictates that it is policies to curtail economically efficient human activity that should themselves be curtailed. The outlook for the climate over the 21st Century is highly uncertain. There is a word in the English language to express high uncertainty. That word is “ignorance”. And ignorance is not a basis for responsible government action. We should expect our politicians to have the courage to resist interest groups’ calls for action in the face of ignorance. The precautionary principle brings to mind the slogan on the Ministry of Truth building in George Orwell’s 1984: “Ignorance is Strength.” Instead of this political principle, we hope that politicians will turn to scientific principles for making public policy.

quote:

Originally posted by Bwana Bunduki:

quote:

Summarizing the Climate Debate

Lee C. Gerhard

In this time of a new administration, it is clear that the media and most of the recently elected members of Congress are unanimous in attacking global warming...

OK Brian, I'll start with this one...

Jeff

quote:

Originally posted by Bwana Bunduki:
Brian,

This was is kinda tough on your position...
I'll let you chew on this for a while before Ipost more...

All the Best

Jeff

quote:

Originally posted by Bwana Bunduki:
Keep Reading...

quote:

Citing data from the University of Illinois' Arctic Climate Research Center, as interpreted on Jan. 1 by Daily Tech, a technology and science news blog, the column said that since September "the increase in sea ice has been the fastest change, either up or down, since 1979, when satellite record-keeping began." According to the center, global sea ice levels at the end of 2008 were "near or slightly lower than" those of 1979. The center generally does not make its statistics available, but in a Jan. 12 statement the center confirmed that global sea ice levels were within a difference of less than 3 percent of the 1980 level.

quote:

Originally posted by Bwana Bunduki:
Op-Ed: Is Global Warming A Science, Theory, Religion Or Power Grab?
You can learn a lot from 'a child' about global warming

17,200 Scientists Dispute Global Warming
By Michael J Wagner.
Published Apr 9, 2007 by ■ Michael J Wagner Share:

Is there a scientific consensus on the topic of man made global warming? If you read the news in the major media you would have cause to believe that there is.

Most of the globe showing "downward trends?" Interesting. I will also tell you that by personal experience as a sailor, water levels aren't rising anywhere that I have sailed, and I have sailed from the Atlantic Ocean, to the Great Lakes to the Gulf of Mexico. The Great Lakes are actually falling significantly.


Better Reading even if slanted.

quote:

Originally posted by Bwana Bunduki:
And now all this damned dea ice has shown up...

quote:

Citing data from the University of Illinois' Arctic Climate Research Center, as interpreted on Jan. 1 by Daily Tech, a technology and science news blog, the column said that since September "the increase in sea ice has been the fastest change, either up or down, since 1979, when satellite record-keeping began." According to the center, global sea ice levels at the end of 2008 were "near or slightly lower than" those of 1979. The center generally does not make its statistics available, but in a Jan. 12 statement the center confirmed that global sea ice levels were within a difference of less than 3 percent of the 1980 level.

I am just sayin...

quote:

Study: Arctic sea ice melting faster than expected

WASHINGTON – Arctic sea ice is melting so fast most of it could be gone in 30 years. A new analysis of changing conditions in the region, using complex computer models of weather and climate, says conditions that had been forecast by the end of the century could occur much sooner.

A change in the amount of ice is important because the white surface reflects sunlight back into space. When ice is replaced by dark ocean water that sunlight can be absorbed, warming the water and increasing the warming of the planet.

The finding adds to concern about climate change caused by human activities such as burning fossil fuels, a problem that has begun receiving more attention in the Obama administration and is part of the G20 discussions under way in London.

"Due to the recent loss of sea ice, the 2005-2008 autumn central Arctic surface air temperatures were greater than 5 degrees Celsius (9 degrees Fahrenheit) above" what would be expected, the new study reports.

That amount of temperature increase had been expected by the year 2070.

The new report by Muyin Wang of the Joint Institute for the Study of Atmosphere and Ocean and James E. Overland of the National Oceanic and Atmospheric Administration's Pacific Marine Environmental Laboratory, appears in Friday's edition of the journal Geophysical Research Letters.

They expect the area covered by summer sea ice to decline from about 2.8 million square miles normally to 620,000 square miles within 30 years.

Last year's summer minimum was 1.8 million square miles in September, second lowest only to 2007 which had a minimum of 1.65 million square miles, according to the National Snow and Ice Data Center.

The Center said Arctic sea ice reached its winter maximum for this year at 5.8 million square miles on Feb. 28. That was 278,000 square miles below the 1979-2000 average making it the fifth lowest on record. The six lowest maximums since 1979 have all occurred in the last six years.

Overland and Wang combined sea-ice observations with six complex computer models used by the Intergovernmental Panel on Climate Change to reach their conclusions. Combining several computer models helps avoid uncertainties caused by natural variability.

Much of the remaining ice would be north of Canada and Greenland, with much less between Alaska and Russia in the Pacific Arctic.

"The Arctic is often called the Earth's refrigerator because the sea ice helps cool the planet by reflecting the sun's radiation back into space," Wang said in a statement. "With less ice, the sun's warmth is instead absorbed by the open water, contributing to warmer temperatures in the water and the air."

The study was supported by the NOAA Climate Change Program Office, the Institute for the Study of the Ocean and Atmosphere and the U.S. Department of Energy.

___

quote:

I have one simple question: Is man made CO2 the cause of the planet warming up until 1998 or was it heightened solar activity?

quote:

If we are in a run away man made CO2 generated warming trend, they why have the last 10-11 years shown no temperature increase?

Jim
"Life's hard; it's harder if you're stupid"
John Wayne