Newsgroups: alt.paranet.ufo,alt.ufo.reports
From: kymhorsell@gmail.com
Subject: ufos and seaice: alaska chapter

[uploaded 64 times; last 17/10/2024]

EXECUTIVE SUMMARY:
- Seaice in key areas around Alaska seem to predict daily UFO
  sightings some time later.
- The biggest association comes from the Bering Straight and some
  large areas along longitude 170W.
- A small region appears in the Mackenzie Bay nr the AK/YT border.
- Given other data associated with UFO sightings nr the Bering Sea and
  Aleutians we might suspect UFOs regularly travel via air or water
  along 170W perhaps on their way to visit the US or other points S.
- Basic images and plots at <kym.massbus.org/UFO/Alaska>.

We've seen in a previous post that certain key regions have an
affinity or predictive power for UFO sightings.

We might interpret a region where e.g. thickness of sea ice is
negatively correlated with daily UFO sightings across the US 30 days
later as somehow "encouraging" more UFO sightings when sea ice
disappears.

The distribution of these particular regions has a pattern we might
expect from other "folkloric" information going back decades.  It turns
out not just any region that is subject to seasonal seaice can closely
predict UFO activity.

We've seen that seaice across the Arctic Ocean contains key regions
where the correlation between seaice and UFO sightings seems to go
very high (~90%). From the very rough map of the region posted
previously we could almost see a path from N Russia across to N America 
where the data suggested a UFO flight route might be highly probable.

Here we'll zoom in on at least part of the "destination" region in
question and look at the satellite radar data gathered around Alaska.

As before the s/w has gathered together daily NOAA radar maps for the
region from 2010 to the present. For each smaller 100x100 pixel area
of each image a time series is created and correlated against daily
NUFORC sightings data. The s/w finds an optimum lag (days) that
maximize the R2 statistic -- the fraction of day-to-day variation in
UFO sightings that seem to exactly correspond with similar day-to-day
variations in radar returns (aka "sea ice proxy") from each area
across the Alaska region.

Big surprise, a lot of the AK region shows no association whatever.
Seaice across most of the Pacific off Alaska has no predictive power
for UFO sightings across N Am.

But equally no surprise, some key regions "light up" as if they were
key flight or submarine routes between (wherever) and N Am,
particularly the USA.

The biggest "lit up" area is along longitude 170W starting at the
Bering Straight.

It's as if UFO's normally travel along this route and are inhibited
(maybe ever so slightly :) by the presence of icebergs or seasonal seaice.

The best areas have about an 80% R2. For example the model for one of
the "best" predictive areas along 170W looks like:

(Log transform enabled).
(58 day lag).
(No serial corr detected).
y = 12.0597*exp(-0.128055*x)
Doubling Rate -5.41
beta in -0.128055 +- 0.0179935  90% CI (42 df)
alpha in 2.48987 +- 0.0203901 
P(beta<0.000000) = 1.000000
r2 = 0.77331859

Binned data:

Bin label             av radar return   av daily UFO  predicted UFO
                                        sightings     sightings
2010209                 -0.642513           12      13.0939* (+1sd over obs)
2015141                  0.799166      10.6667      10.8866
2018061                 -0.121636      11.3333       12.249
2018194                  -2.03485           15      15.6495
2018273                  -1.08003      13.2381      13.8484
2019056                  0.477173        11.75      11.3449
2019078                   1.00353         10.4      10.6054
2019101                   2.25662          9.5      9.03311
2019132                  0.693845           13      11.0344**(-2sd)
2019228                  -1.40318        13.45      14.4335
2019232                   -1.2387           13      14.1327*(+1sd)
2019288                  -1.75659      17.4286      15.1017*(-1)
2019318                   1.31776            9      10.1871*(+1)
2019358                   1.64419        9.375      9.77005
2020022                 -0.266284       13.125       12.478
2020033                    1.3734         10.5      10.1148
2020048                 -0.710915         14.2      13.2091
2020053               0.000560869        14.25      12.0588**(-2)
2020112                  0.928496        11.45      10.7078
2020128                 0.0698588         12.4      11.9523
2020138                   1.08781      10.7778      10.4915
2020148                   1.56027      9.16667      9.87561
2020153                   1.16237      10.1333      10.3918
2020157                   1.70302          9.5      9.69672
2020161                  0.750138      11.2593      10.9551
2020188                   1.27131       9.7619      10.2479
2020198                  0.624474           11      11.1329
2020201                 -0.361818        13.72      12.6316*(-1)
2020218                  -1.34287           13      14.3225*(+1)
2020228                  -1.85943         13.9      15.3019*(+1)
2020237                  -1.18838      12.0526      14.0419*(+1)
2020250                  -1.68671           17      14.9672*(-1)
2020254                 -0.815058      13.7391      13.3864
2020274                  0.425204      12.5667      11.4206*(-1)
2020293                 -0.618811         12.5      13.0542
2020298                  -1.29014           16      14.2261*(-1)
2020305                  -1.52538      13.8889      14.6612
2020315                  0.851102      9.80645      10.8144*(+1)
2020325                 -0.429844        13.25      12.7421
2020335                  0.150114         11.7      11.8301
2020345                  0.538486       10.186      11.2561*(+1)
2020347                 -0.504824      13.7368       12.865
2020355                   1.47428          9.9      9.98496
2020365                -0.0701027      12.4286      12.1684

This is a binned time-series regression. Datapoints are assigned to
bins that contain "similar" points. The average X and Y is computed
for each bin and those numbers passed to a time-series sensitive
regression. The final statistics are from that regression.  In this
case the time-series regression found no problems with serial/auto
correlation so the output is "the same" as an OLS for the same dataset
(with a log transform on the Y data).

The X data is a "normalized" version of the radar return data.  Bright
areas on the radar image represent points that have a large
return. These might be flat areas of land or ocean, or sea ice.  By
tuning the model to ignore certain signal strengths some of the
clutter (e.g. land or missing satellite data) can be ignored.  The
normalization involves translating the return strength into "Z scores"
that have an average of 0 and standard deviation of 1.  I.e. a value
of -1 represents a signal around the 16% weakest level detected in the
dataset and +1 represents a signal around the 16% strongest in the dataset.

On that basis the model finds a reduction in signal of 5.4 is
associated with a doubling of daily UFO sightings over average levels.

All other models for each small 100x100 pixel area across the
Alaska region is treated similarly.

A rough ASCII map of the region where the reader's imagination can
fill in the outline of the Bering Straight and Alaska is as follows:

180W                                             130W
  -  -  -  - 45 47 55 40 40 35 60 73< -  -  -  -  -	73N
  -  -  - 61 48 74<59  - 44 36 56 58 36  -  -  -  -
  -  -  - 30 56 72<75<19 15 68 57 43  -  -  -  -  -
  -  -  - 14 50 67 29  -  -  - 10  -  -  -  -  -  -
  -  - 66 27 29 69  6  -  6 14  -  -  - 14  -  -  -
  -  - 73<69 36 71<11  -  -  6  - 16  5 31  -  -  -
  -  - 70<74<63 54 38  -  -  -  - 19  -  -  -  -  -
  - 60 73<71<77<67  6  -  -  9  5  -  -  - 32  -  -
  - 54 63 64 71<56  -  - 19 20 57 17  5 10 28  -  -
  - 63 65 61 64 53 11 19 39 34 58 58 70<37 30  -  -
  - 60 69 50 61 60 54 12 63 55 55 54 64 37 21 26  -
 61 71<76<73<62 58 49 61 61 62 51 42 50 62 42 21  -
 70<70<67 69 63 54 56 53 49 42 45 42 47 58 56 50  -
 73<75<70<61 61 57 48 42 57 48 59 64 41 69 41 40  -
 73<67 61 60 43 63 43 48 45 61 59 53 42 63 41 60  -
  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -
  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  - 	50N

NOTES: 
"<" == R2 immed to right is >=70%
Some areas to the left and right of the original image of the
radar data are black because of the relevant equal-area projection used.

A sample radar image and the density plot of the R2's showing where
the "most significant" association between the presence of seaice and
later UFO daily sightings is at <kym.massbus.org/UFO/Alaska/>.


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