Wednesday, May 15, 2013
Good news: This week I submitted a 350 page for printing. It is a complete explanation of the concept and its potential. It should be available by August 2013. Will provide more informaion as it becomes available. I hope that people will understand my writing and realize that nature and civilization do have a chance. When Pluvinergy is appreciated a new era will begin. It will be a new beginning for Civilization and for nature: Humanity will be in harmony with nature once again.
Friday, November 27, 2009
Tronedogenesis theory is hidden
Correct Tornadogenesis theory is hidden from the public by the American Meteorological Society (AMS). They don't mean the harm that they cause, just like they did not mean to kill hundreds of people by delaying acceptance of Ted Fujita's Microburst theory for the crashing of airliners caught in downdrafts.
It is too hard to have one single mathematical model to explain all tornado formation processes (tornadogenesis) because there are many conditions in a dynamic atmosphere which change the process. Tornadoes are necessarily the result of extreme dynamic conditions so the process varies too much for simple, or even complex mathematical models to explain. So the result is that decades of study on the subject are held hidden for to two reasons. First, an antiquated peer review process that is much to slow in today's world. Second, and much more important, but harder to understand: tornadogenesis must be modeled using stochastic models based on probability functions.
We, at Pluvinergy recommend a simplified model on which probability functions can be improved with incremental studies. Here are same examples: The probability of tornadoes increases with the proximity of downdrafts asymptotically near a probability of 1. Formation of downdrafts near tornadogenesis point increases as shaft of dry air is pulled (translated) into the area. This is the famous hook-echo in messocyclones associated with tornadoes. The probability of dry air shaft formation in the northern hemisphere increases with the speed of South-East cold front advancement into humid air.
These along with hundreds of patterns that we are aware of, when reduced to probability functions can be handled by a small computer such as a PC to produce tornado forecasts with minimal information readings from field sensors.
The result will be much better tornado prediction. For Pluvinergy, such a simple model is critical for incorporating the vast wealth of knowledge cloistered in private conversations among students of the porocess be denied tothe pubic. Thus we can advane better models for the operation and development of Pluvinergy systems. Please see www.pluvinergy.com, science page, tornado theory.pdf link.
It is too hard to have one single mathematical model to explain all tornado formation processes (tornadogenesis) because there are many conditions in a dynamic atmosphere which change the process. Tornadoes are necessarily the result of extreme dynamic conditions so the process varies too much for simple, or even complex mathematical models to explain. So the result is that decades of study on the subject are held hidden for to two reasons. First, an antiquated peer review process that is much to slow in today's world. Second, and much more important, but harder to understand: tornadogenesis must be modeled using stochastic models based on probability functions.
We, at Pluvinergy recommend a simplified model on which probability functions can be improved with incremental studies. Here are same examples: The probability of tornadoes increases with the proximity of downdrafts asymptotically near a probability of 1. Formation of downdrafts near tornadogenesis point increases as shaft of dry air is pulled (translated) into the area. This is the famous hook-echo in messocyclones associated with tornadoes. The probability of dry air shaft formation in the northern hemisphere increases with the speed of South-East cold front advancement into humid air.
These along with hundreds of patterns that we are aware of, when reduced to probability functions can be handled by a small computer such as a PC to produce tornado forecasts with minimal information readings from field sensors.
The result will be much better tornado prediction. For Pluvinergy, such a simple model is critical for incorporating the vast wealth of knowledge cloistered in private conversations among students of the porocess be denied tothe pubic. Thus we can advane better models for the operation and development of Pluvinergy systems. Please see www.pluvinergy.com, science page, tornado theory.pdf link.
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