Newsgroups: alt.paranet.ufo
From: kymhorsell@gmail.com
Subject: UFO's and ocean moons

[uploaded 35 times; last 17/10/2024]

EXECUTIVE SUMMARY:
- We find that "fingerprints" of the motion of certain solar system
  moons are also found inside certain UFO observations made on Earth
  some days later.
- It turns out a small number of moons seem to robustly explain or
  predict day to day variations in certain UFO activity.
- Given the list of R2 "explanation power" statistics for the
  different cases we can ask what quality of the relevant moons
  explains the link found. It turns out in a natural way those moons
  suspected of having oceans are the ones that are found to predict
  UFO activity on Earth some number of days later.
- The speed of propagation of change of position of moon to UFO
  observation is around 1 AU per day -- a reasonable "average"
  interplanetary speed.
- The moon with the best explanation power is also the one with the
  largest suspected ocean in the solar system -- Ganymede.

I re-ran an old study on comparing "fingerprints" of various moons
with the noise hidden inside certain UFO reports. The mental model of
a "fingerprint" is that traces of one type of data are often visible
in a statistically robust way somewhere else if 2 systems somehow
"came into contact" at somewhere.  E.g. if an airliner crossed the US
and overflew Louisiana then tiny variations in air temperature and
precipitation will "imprint" on the flight characteristics of the
aircraft and provided measurements can be made precisely enough --
e.g. if they can be repeated many many times and averaged out -- those
tiny variations should be detectable in e.g.  the arrival time of the
aircraft at its various destinations.

In the case of UFO's we're dealing with reports mostly from average
folks who may or may not understand what they are seeing. But given
enough data even some tiny part of it that may correspond to what
Congress is now tending to insist are "non human created aircraft" (if
they are human-created Congress has ruled that case is handled by
another department but not the Pentagon's UFO department) should have
traces of places they have been and maybe even link back with some
kind of "home location".

With the aid of a fairly straightforward software that has enough
smarts to be able to run statistical tests and interpret the results
we can check off each "home location" against different types of UFO
reports (the NUFORC database can be easily divided up into about 250
types of object by shape, color, time and location seen, direction of
motion, and certain other keyword-based characteristics e.g. whether
they were observed interacting with a military aircraft).

We can then ensure each type of UFO tested and each possible "home
location" assumed result in highly robust predictions by using an
appropriate combination of statistical tests that ensures the number
of "false hits" is below 1 in 1000. As part of the output from the
procedure we not only see that some home location seems to imprint
some part of itself on unusual objects that are later seen on Earth,
but we can determine what kind of lag (in the case here that is
limited to whole number of days) gets the best match, as well as a
summary "match percentage" that describes what fraction of the
relevant UFO reports seem to vary in direct parallel with a parameter
related to the "home location".

The next step in the process will check whether there is some
characteristic of the relevant "home locations" that somehow is
peculiar to those that relate strongly with some kind of UFO activity
seen in Earth.  The s/w will attempt to explain what is unusual about
"home locations" versus all the other places that might have turned up
as significant but didn't.

As usual with these studies there is plenty of noise to go around so
we do expect some spurious results that don't mean anything.  But the
overall pattern should show up something statistically significant
after allowing for remaining noise in the system. A crude method we
shall use here simply will discard results that are furthest away from
the common baseline of all results, provided that no more than 25% of
the results are discarded.

So the first part of the results will line various moons up with
various types of UFO activity and determine whether there is a strong
statistical link between some parameter of the moon's motion and that
activity, what kind of lag/delay best matches the 2 things up, and
what percent of the activity is finally explained by the relevant
motion of the moon in question.

The summary table I have here looks like:

Moon	Param	Lag	UFOtype	Filter	R2
		(days)		(sd's)	(% y explained by x)
503	angsep	11	pale	o1	0.30654435
502	defillu	17	pale	o1	0.17788930
501	satx	6	pale	o1	0.17229421
701	satpang	18	pale	o1	0.14159575
504	satx	15	pale	o2	0.13129106
801	saty	8	pale	o1	0.12317738
601	angsep	2	pale	o1	0.11928895
606	saty	2	pink	o1	0.09388933
902	satx	12	grey	o1	0.08963227
703	angsep	10	gold	o1	0.06135808
901	satpang	5	pale	o1	0.06120898
704	angsep	7	pale	o1	0.04220981
705	angsep	17	gold	o1	0.04151140
802	saty	16	grey	o2	0.03456327
602	defillu	15	Cross	o1	0.02846995

The "moons" are numbers from JPL's Horizons system. 5xx are Jovian moons,
6xx Saturnian; 7, 8 and 9 resp Uranus, Neptune and Pluto.

The "Param" column gives the parameter of position or movement that
was found to be present in the relevant UFO activity. "Angsep" is the
angular separation in arcseconds between the center of the moon and
its primary, as seen from Earth. SatX and SatY are the angular distance
in the "X" and "Y" directions in arcseconds between the moon and its
primary. defillu is the fraction of moon that is not illuminated by
the sun. and satpang is the counterclockwise position of the moon with
the primary's N pole as 0.

The "UFOtype" column is the section of NUFORC data -- typically a
color or Shape of the objects in question. For this study only the
NUFORC data from 2006 onwards was used. This corresponds with the
period when a web report system was created leading to a 10x increase
in reports as well as a change in the character of some of the objects
reported.

The "Filter" column shows how much outlier data was discarded to
obtain a statistically robust result. The robust result must pass a
T-test and Rank test both at better than 95% significance.  Items
marked with "o1" discarded up to 25% of the data to find a significant
result. "o2" lines discarded only 5% of the data to get a significant result.

Finally, the R2 column estimates what percent of the day-to-day
variation in UFO activity matches the day-to-day variation in motion
of the relevant moon however many days earlier. We see e.g. the
"angular separation in seconds" of moon 503 (Ganymede) from its
primary matches about 31% of the day to day variation in UFO's
described as "pale" 11 days later. Typically it's believed only 1-10%
of UFO reports are anything other than mis-identified mundane
phenomena.  But, typically, when certain specialised types of
descriptions (e.g. "pale") are used the interesting percent seems to be
significantly higher.

Now comes the interesting part. Is there anything peculiar about the
list of moons the procedure has come up with. Particularly, is there
some factor that explains the "R2" numbers -- the so-called
"explanation power" of the relevant moon parameters related with the
specific type of UFO report.

Well one thing the s/w immediately notes is that some moons are
suspected or once had some kind of subterranean ocean.

The list I'm using here looks like:

Planet		Moon		Remarks					ID
jupiter		europa		twice vol of earth liquid water		502
jupiter		ganymede	largest ocean in solar system		503
saturn		enceledus						602
saturn		titan							606
uranus		titania 	(maybe enough heat to maintain ocean)	703
		oberon 		(maybe enough heat to maintain ocean)	704
neptune		triton		(potential)				801
pluto		charon	 	(once had ocean; now frozen)		901


So we can take our list of "R2 results" above and see whether moons
with suspected oceans have some predictive power about how well the
relevant moon explains the selected UFO activity.

That table looks like:

Moon Params		R2		Ocean yes/no
angsep503L11paleo1 	0.30654435	1
defillu502L17paleo1 	0.17788930	1
satx501L6paleo1 	0.17229421	0
satpang701L18paleo1 	0.14159575	0
satx504L15paleo2 	0.13129106	0
saty801L8paleo1 	0.12317738	1
angsep601L2paleo1 	0.11928895	0
saty606L2pinko1 	0.09388933	1
satx902L12greyo1 	0.08963227	0
angsep703L10goldo1 	0.06135808	1
satpang901L5paleo1 	0.06120898	0
angsep704L7paleo1 	0.04220981	1
angsep705L17goldo1 	0.04151140	0
saty802L16greyo2 	0.03456327	0
defillu602L15Crosso1 	0.02846995	1

We can now ask does the suspected or (in some cases) potential
existence of a moon's ocean have something to do with the "R2" value?

And the relevant Rank test looks like:

calculated Spearman corr = 0.492857
Critical Spearman = 0.440500 2-sided at 5%; reject H0:not_connected


Which says there is good chance (95% or better) that the presence or
suspected presence of an ocean on a moon predicts larger values of R2
than smaller values of R2.

Not only has the AI discovered links between certain types of motion
of certain moons and days-later observation of various objects whizzing
around the Earth's atm, but it has determined fairly rigorously
that those moons having a subterranean ocean are most likely
the moons involved rather than others.

We also see the biggest R2 found links the angular separation of
Ganymede from Jupiter as seen from earth to 30% of the day-to-day
variation in reports of "pale UFO" after a lag by 11 days.  And
Ganymede is suspected of having the largest ocean in the solar
system.  Even Europa has an ocean 2x the mass of Earth's.

Many previous calculations have also found a kind of "average speed"
of propagation of (whatever) from near Jupiter to near Planet Dirt
happens around 1AU per day.

--
"Nothing in life is to be feared, it is only to be understood.
Now is the time to understand more, so that we may fear less."
- Marie Curie

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