Speed
of Coriolis, The wind – A predictability equation
Felipe
Maya Muniz
felipemayamuniz82@gmail.com
Independent
student
“ We
can't say that if the wind is going left or right but we can try to
discover” - Felipe Maya Muniz
Abstract:
The
objetive of this article is to prove mathematically how to predict
events using Coriolis`s studies about winds, reaching a
predictability equation that comes with a cone of probability that
can be used by climate systems or any other area that has interest in
a predictability equation.
Keywords:
Predictability, Wind, Coriolis
1.
Introduction
At
first i was trying to equate the speed of a pair of scissors wire and
came to realize a equation of predictability of wind that can be used
in many other areas that work with movements. The first objetive is
to increase precision on systems that analyse systems with movement.
At final objetive is increasing precision of weather systems.
2.
Development
At
the start, i was trying to get the speed of a pair of scissors wire
precisely then i started with classical mechanics that give me a
reason four by phi the speed of the rods. But that was not enough, i
wanted to know exacly how much was that speed in relativity. Then i
started to study more physics, passing trought Lorentz
transformations, Ehrenfest Paradox and the constant of Feigenbaum
that i got the abstract equation of the wind itself by Coriolis. This
equation:
Where:
λ
= constant of feigenbaum
a
= diameter of observed object
c
= speed of light
w
= angular velocity in radians of the object
r
= radius of the object to be calculated
v
= Linear velocity of te object
u
= speed of secondary object (Ex. Fotons reflecting to the observer, a
satellite)
According
to Coriolis and meteorology, in the wind discipline, have the
Coriolis force that serves to make predictions of rotational objects
and it is a pseudo force that kinda pushes the clouds, This equation
results in that speed through the relation between linear velocity
and rotational, but "vulgarly" is the wind itself the
abstraction of this equation.
Well
this equation will work very well in meteorological satellites, since
measuring mass with light, but analyzing a video, frame by frame and
making the probability, in a computer with artificial intelligence,
of the earth could predict by the rotation of the masses the probable
area that the object to be pushed by the wind will be. And the wind
itself being abstract is the relation between the rotation of the
earth and the linear movement of the gaseous masses.
The
answers to this equation come as an equation of predictability, a
probability cone where the area of this cone gives the probability of
the clouds remaining.
The
Feigenbaum constant came as a number to justify the smoothness of the
system as the shortest length we have is plank length, but for
weather systems or at least with current technology, it may not be
necessary to use it, Feigenbaum is good enough for meteorological
systems.
Many
other systems that use rotational motion with linear motion will
increase their accuracy with this equation, by now I can only think
about climate systems.
3.
Conclusion
This
equation can increase largelly many systems as we can see in climate
systems and is now a new technology we can use to improve our lives
and wealth.
References:
Lorentz
Transformations:
Ehrenfest
Paradox:
Constant
of Feigenbaum`s:
Coriolis force:
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