http://www.ottawacitizen.com/mobile/...tml?id=5847032
Just how does a "Hurricane forecaster" forecast? An MIT website explains it:
Notice how absolute the article puts it: "Scientists can predict..."
So, despite their skill in applying the best computer modeling using the best mathematical models that were worked out by tuning them to previous years ("hindcast"), they admit that their 20 year record for predicting how many hurricanes will occur in a given year, or the current year, "has no value".
Using "hindcasts" is what the climate modelers are doing, which is why they collected the tree-ring, ice cores, temperature and other historical data. Applying their assumptions and interpretations to that data they then "tuned" their mathematical models to replicate the historical "climate", and on that basis run their models forward 50 years into the future.
The AGW people, however, make a distinction between "weather" and "climate". So, while Chaos renders predicting weather impossible, they claim it does not hinder climate predictions:
We've always known that AGW was a statistical trick. and statistician Steve McIntyre showed in the FOIA files of 2009 how they did it:
McIntyre's quotes are from those 1,072 released emails, along with the very informative HARRY_README.TXT file.
The "long term means and other moments are stable" means that no matter where one starts, or with what precision the initial conditions are, the end result always end somewhere on the Butterfly curve. What they don't say is that contrary to their assumption NO ONE can predict that a particular set of conditions will end up at a particular point in the chaotic region or in the attractor region. IF one could predict that then Chaos would be ... NOT be chaotic.
Hurricane predictors admit they can’t predict hurricanes
Monday, December 12, 2011
By Tom Spears
Two top U.S. hurricane forecasters, revered like rock stars in Deep South hurricane country, are quitting the practice because it doesn’t work.
William Gray and Phil Klotzbach say a look back shows their past 20 years of forecasts had no value.
The two scientists from Colorado State University will still discuss different probabilities as hurricane seasons approach — a much more cautious approach. But the shift signals how far humans are, even with supercomputers, from truly knowing what our weather will do next.
Gray, recently joined by Klotzbach, has been known for decades for an annual forecast of how many hurricanes can be expected each official hurricane season (which runs from June to November.) Southerners hang on his words, as even a mid-sized hurricane can cause billions in damage.
Last week, the pair dropped this announcement out of a clear, blue sky:
“We are discontinuing our early December quantitative hurricane forecast for the next year ... Our early December Atlantic basin seasonal hurricane forecasts of the last 20 years have not shown real-time forecast skill even though the hindcast studies on which they were based had considerable skill.”
Monday, December 12, 2011
By Tom Spears
Two top U.S. hurricane forecasters, revered like rock stars in Deep South hurricane country, are quitting the practice because it doesn’t work.
William Gray and Phil Klotzbach say a look back shows their past 20 years of forecasts had no value.
The two scientists from Colorado State University will still discuss different probabilities as hurricane seasons approach — a much more cautious approach. But the shift signals how far humans are, even with supercomputers, from truly knowing what our weather will do next.
Gray, recently joined by Klotzbach, has been known for decades for an annual forecast of how many hurricanes can be expected each official hurricane season (which runs from June to November.) Southerners hang on his words, as even a mid-sized hurricane can cause billions in damage.
Last week, the pair dropped this announcement out of a clear, blue sky:
“We are discontinuing our early December quantitative hurricane forecast for the next year ... Our early December Atlantic basin seasonal hurricane forecasts of the last 20 years have not shown real-time forecast skill even though the hindcast studies on which they were based had considerable skill.”
Predicting Hurricanes: A Not So Exact Science
Written by Aubrey Samost
Predicting the weather has come a long way in just the last century. Today’s meteorologist no longer looks into his crystal ball. He has far more sophisticated tools available to him, from satellite images to Doppler radar. He can make a fairly accurate prediction for the weather up to a week in advance, and yet, with all of this early warning, the coast still sustains a lot of damage whenever a hurricane comes through because there is simply no time to fully prepare. A meteorologist can only make a guess, and a guess can always be wrong.
How do meteorologists predict hurricanes?
Hurricane predictions can fall into two categories: seasonal probabilities and the track of a current hurricane. These two fields are very different in their methods and approaches.
Predicting Hurricane Activity in a Season
Every year around April the meteorologist on the news starts talking about how many named storms are predicted for the season and how many hurricanes are expected to make landfall. Scientists can predict the number of named storms and their breakdown by intensity (i.e. the number of hurricanes, tropical storms, intense hurricanes, etc.). They can also predict approximate wind speeds and intensity for sustained winds. These can be easily calculated using elementary statistics. Compared to past seasons, the sustained wind speed follows the Poisson Distribution with fairly consistent accuracy. Named storms are typically predicted based on past occurrences and current measures of factors in the climate. At the beginning of the season these are only labeled as probabilities (Gray, 2006). Scientists cannot say that the third named storm of the season will hit Florida on June 30th. They can only say that there is a five percent chance of a major hurricane hitting the coast from April to November.
...
(commentary on predicting paths not included)
Written by Aubrey Samost
Predicting the weather has come a long way in just the last century. Today’s meteorologist no longer looks into his crystal ball. He has far more sophisticated tools available to him, from satellite images to Doppler radar. He can make a fairly accurate prediction for the weather up to a week in advance, and yet, with all of this early warning, the coast still sustains a lot of damage whenever a hurricane comes through because there is simply no time to fully prepare. A meteorologist can only make a guess, and a guess can always be wrong.
How do meteorologists predict hurricanes?
Hurricane predictions can fall into two categories: seasonal probabilities and the track of a current hurricane. These two fields are very different in their methods and approaches.
Predicting Hurricane Activity in a Season
Every year around April the meteorologist on the news starts talking about how many named storms are predicted for the season and how many hurricanes are expected to make landfall. Scientists can predict the number of named storms and their breakdown by intensity (i.e. the number of hurricanes, tropical storms, intense hurricanes, etc.). They can also predict approximate wind speeds and intensity for sustained winds. These can be easily calculated using elementary statistics. Compared to past seasons, the sustained wind speed follows the Poisson Distribution with fairly consistent accuracy. Named storms are typically predicted based on past occurrences and current measures of factors in the climate. At the beginning of the season these are only labeled as probabilities (Gray, 2006). Scientists cannot say that the third named storm of the season will hit Florida on June 30th. They can only say that there is a five percent chance of a major hurricane hitting the coast from April to November.
...
(commentary on predicting paths not included)
So, despite their skill in applying the best computer modeling using the best mathematical models that were worked out by tuning them to previous years ("hindcast"), they admit that their 20 year record for predicting how many hurricanes will occur in a given year, or the current year, "has no value".
Using "hindcasts" is what the climate modelers are doing, which is why they collected the tree-ring, ice cores, temperature and other historical data. Applying their assumptions and interpretations to that data they then "tuned" their mathematical models to replicate the historical "climate", and on that basis run their models forward 50 years into the future.
The AGW people, however, make a distinction between "weather" and "climate". So, while Chaos renders predicting weather impossible, they claim it does not hinder climate predictions:
But how can climate be predictable if weather is chaotic? The trick lies in the statistics. In those same models that demonstrate the extreme sensitivity to initial conditions, it turns out that the long term means and other moments are stable. This is equivalent to the ‘butterfly’ pattern seen in the figure above being statistically independent of how you started the calculation. The lobes and their relative position don’t change if you run the model long enough. Climate change then is equivalent seeing how the structure changes, while not being too concerned about the specific trajectory you are on.
Climategate Letters, Sep 22-23, 1999
The Climategate Letters contain a flurry of correspondence between Mann, Briffa, Jones and Folland (copy to Tom Karl of NOAA) on Sep 22-23, 1999, shedding light on how the authors responded to the stone in IPCC’s shoe. By this time, it appears that each of the three authors (Jones, Mann and Briffa) had experimented with different approaches to the “problem” of the decline.
The Climategate Letters contain a flurry of correspondence between Mann, Briffa, Jones and Folland (copy to Tom Karl of NOAA) on Sep 22-23, 1999, shedding light on how the authors responded to the stone in IPCC’s shoe. By this time, it appears that each of the three authors (Jones, Mann and Briffa) had experimented with different approaches to the “problem” of the decline.
The "long term means and other moments are stable" means that no matter where one starts, or with what precision the initial conditions are, the end result always end somewhere on the Butterfly curve. What they don't say is that contrary to their assumption NO ONE can predict that a particular set of conditions will end up at a particular point in the chaotic region or in the attractor region. IF one could predict that then Chaos would be ... NOT be chaotic.
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