Approved For Release 2000/08/08
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0001-4
CENTER LANE-3
Final Report
December 1984
GEOPHYSICAL EFFECTS STUDY
(U)
By:
MARSHA ADAMS
HAROLD
E. PUTHOFF
TIME RESEARCH INSTITUTE
SRI INTERNATIONAL
Prepared
for:
DEPARTMENT OF THE ARMY
USAINSCOM
FORT GEORGE
G. MEADE, MARYLAND
20755
Attention:
LT. COL. BRIAN BUZBY
WARNING NOTICE
CENTER LANE SPECIAL ACCESS PROGRAM.
RESTRICT DISSEMINATION TO THOSE WITH VERIFIED ACCESS.
CATEGORY 3
333 Ravenswood Avenue
Menlo
Park,
California
94025
U.S.A.
(415) 326-6200
Cable:
SRI
INTL MPK
TWX:
910-373-2046
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NOT RELEASABLE TO
4 FOREIGN NATIONALS
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V
RESULTS
A.
Results
of Geophysical Analysis
1.
Introduction
2.
Solar Flux
.
Sunspot Number
4.
Solar Flares
5.
Magnetic
Indices
6.
sids
!!!!!!!
B.
Results Pertaining
to
ELF
3]_
.
Introduction
2.
Intercomparison of
ELF System
3.
ELF/RV Comparison
VI
EVALUATION AND RECOMMENDATIONS
VII
SUMMARY
REFERENCES
BIBLIOGRAPHY
iv
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ILLUSTRATIONS
ELF Data-Acquis i tion System.
.
Real-Time Geophysical Data Acquisition via Westar
IV
Downlink
Real-Time Geophysical Data-Acquis i tion System
Geophysical/Performance Data-Analys is
System
TABLES
Geophysical Data
Bases
Description
of
RV Data
v
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CENTER LANE-3/N0F0RN
I
OBJECTIVE
(U)
(S/CL-3/NF)
The objective
of
this
effort
is
to
investigate
the
possible
effects
of
ambient geophy s ical / ex treme ly
low-frequency electro-
magnetic
factors on remote viewing
(RV)
performance
as
a potential
aid
to increasing
the performance
levels
of Army
INSCOM remote viewers.
(U)
RV
(remote viewing)
is
the acquisition and description,
by mental
means
,
of
information blocked
from ordinary perception by distance
or
shielding.
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CENTER LANE-3 /NOFORN
II
EXECUTIVE SUMMARY
(U)
(S/CL-3/NF)
SRI
International was
tasked
to conduct
a
study
for Army
INSCOM
to
investigate
a potential
correlation between remote viewing
(RV)
performance
and ambient geophys ica 1 / extreme ly- low- frequency electromagnetic
(ELF)
activity.
The possibility of
such correlation
is
indicated,
for
example,
by studies
showing
ps ychophys io logica 1
effects
’
and
behavioral
changes3
’
associated with
ELF electromagnetic
fields.
The geophysical
variables
of
interest
include
such
factors
as
ELF
intens i ty / f luc tuat ions
,
ionospheric
conditions,
geomagnetic
indices,
sunspot number,
and
solar-
flare characteristics.
The questions addressed
in
this program are
•
Do geophysical/performance
correlations
exist
such
that
measurement
of
the
ambient geophysical variables
could
be used
as
an
indicator
of expected performance?
•
If
so,
can optimum performance windows
be
identified?
(U)
The
structure
of
the program
to
investigate
the above
issues
consists
of
•
A literature
search
•
Real-time
ELF measurements
SRI
International
(Menlo Park,
California
location)
Time Research
Institute
(Los Altos,
California
f ield
station)
.
•
Real-time
geophysical
data acquisition via
the National
Oceanic
and Atmospheric Administration
(NOAA) Westar
IV
satellite downlink
.
•
Computer correlation
studies
of RV performance versus
variables
of
interest.
(U)
In
this
report,
we present
findings
from our over- s ix-year
analysis
of
scored RV sessions— as
they relate
to geophysical environmental
(u)
References
are
listed at
the
end of
this
report.
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(u)
conditions during
the
times
the
sessions were
in progress.
These corre-
lations have yielded
positive
results,
indicating
that geophysical
processes may play
a role
in determining
RV performance,
and may,
with
further effort,
lead
to
the
forecasting
of
RV performance.
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III
INTRODUCTION
(U)
A.
(U)
General
(U)
In order
to accomplish
the
goals
listed
in
the Executive Summary,
this program was designed
to be
a joint effort between
SRI
International
and Time Research
Institute
(TRI)
of
Los
Altos,
California, with
SRI
as
the
prime contractor.
Time Research
Institute
is
a research organization
that
specializes
in temporal
analysis
of
geophysical variables
and
their potential
correlation with phenomena
of
interest,
such
as weather patterns,
earth-
quakes,
and
the
like.
(U)
Time Research
Institute was
responsible
for establishing
the
appropriate hardware
and
software
systems
for collecting and analyzing data
on environmental conditions
and
their correlation with
RV performance.
The
purpose
of
the
correlation
study was
to determine whether
RV performance
is
enhanced
or degraded
by measurable
changes
occurring
in
the geophysical
(including solar- terres trial )
environments.
The
specific geophysical data
bases examined
in
this
effort
are
given
in Table
1.
(U)
Should correlations between geophysical variables
and
RV per-
formance
be rigorously established over
time,
the application potential
of
the
effort
is
twofold:
#
Time
periods
in which enhanced
RV performance might
be
expected could
be
identified,
resulting
in increased
quality and accuracy
of
information obtained
through
such channels;
similarly,
time periods
in which degraded
RV performance might be expected could
be avoided.
Thus,
optimum performance windows would
be
identified.
*
An
increased understanding of
the
types
of environmental
changes
that correlate with
RV performance
could provide
clues
as
to
the mechanisms
involved
in
RV functioning.
Such knowledge would
lead
to
a more
focussed research
on
factors
that could enhance
RV performance,
and would
also provide
information critical
to
the development of
defensive countermeasures
against RV
.
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V-RQ
Table
(U)
GEOPHYSICAL DATA BASES
•
Solar
terrestrial
- Geomagnetic--ground-measured
indices A
,
sum of K
,
C
,
C9
P
P
P
-
Solar
flux
(MHz):
15,400,
8,800,
4,995,
2,800,
2,695,
1,415,
606,
410,
245
-
Sunspot number
-
Solar
flares
•
Ionospheric measurements
- Sudden
ionospheric disturbances
(SID)
-
Sudden enhancements
of
signal
strength
(SES)
•
ULF/ELF
-
frequencies
(from
to
30 Hz)
UNCLASSIFIED
B.
(U)
Report Organization
(U)
The remainder
of
this
report
is organized
to
include:
Method
of
Approach
(Section
IV )
,
Results
(V),
Evaluation and Recommendations
(VI)
,
and
Summary
(VII).
The Method
of Approach
section contains
descriptions
of
the project
tasks,
which
include
Time Research
Institute’s data acqui-
sition systems,
other
sources
of geophysical data acquisition,
lists
of
geophysical
data
that have been analyzed,
and
the analysis
technique
employed.
The Results
section contains
the
findings
from
the comparisons
of
both
the
ELF data
sets
among themselves,
and
the comparisons
of
RV
performance data with
the
ELF
and other geophysical data.
The Evaluation
and Recommendations
section summarizes
the
findings
and
possible applica-
tions
of
our research,
and
identifies areas where
further .investigation
is
needed.
The
Summary section summarizes
the overall
effort
and
its
impli-
cations with regard
to RV performance enhancement and countermeasures
development.
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IV
METHOD OF APPROACH
(U)
A .
( U )
Literature
Searc h
(U)
A literature search
into
the areas
of known effects
of
static
and
low-frequency magnetic and electric
fields
on biological processes
was
carried out.
Much
of
the
literature available
in
the ELF range dealt
with
the
effects
(or
lack
thereof)
of 60-Hz
fields.
Papers were sought
that described both
the
gross effects
of
these
fields
and
the mechanisms
by which
they could affect biological organisms.
Some
reports
describing
higher electromagnetic
frequencies
(e.g.,
microwave)
were
also
included
for
their
inferential value.
(A bibliography appears
as
an appendix
to
this
report
.
)
B -
(U)
Data Acquisition
1*
(U)
ELF Measuremen ts
a.
(U)
Introduction
(u)
Although
the
ELF range
(3
to
300
Hz)
has
been
studied
in
some detail, many unknowns
remain.
Although
it
is known
that extremely-
low frequencies generated by geophysical means
(e.g.,
electrical-storm
activity)
tend
to distribute
themselves
globally,
little
information
is
available on
the variation
of
the
ELF environment
from location
to
loca-
tion.
Therefore,
local variations may exist
that are caused
by both man-
made
sources,
and by
the
geological
structure
of
the area.
In
the
San Francisco Bay Area, man-made
sources
that generate
ELF on
a
local
scale
include motors,
telephone
lines,
power
lines,
and electrical
subways
[Bay Area Rapid Transit
(BART)];
it needed
to be determined whether
the
emission from such
sources constitutes
a significant contribution
to
the
omnipresent global
ELF
field.
(U)
In order
to address
the above
issue,
two ELF monitoring
stations were
set up--one
at SRI Menlo Park
(the RV
laboratory),
the
other
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(u)
at
the TRI
field
station,
17 km distant.
It was anticipated
that
the
SRI
environment might be
an electrically
"noisy"
one
due
to
the
large amount
of electrical
and electronics
activity
in
the area— a hypothesis
that was
verified.
With
the
requirement
that
two
ELF monitoring sites
be
implemented
for
the
program,
it was decided
that
the
two systems would
be made
identical.
In
this way,
differences between
the systems would be minimized,
thus
reducing
the opportunity
for artifactual differences
between
the outputs.
b.
(u)
Los Altos
Site
(TRI)
(U)
Since May
1982,
TRI
has been operating
a prototype
ELF
monitoring
site
in Los Altos, where data have been collected
twice daily
for
the purpose
of correlating ELF disturbances against various phenomena
of
interest.
In
this period,
analysis
techniques were developed
that were
directly applicable
to
the present
task.
(U)
One
of
the
first
tasks was
the upgrading of
the Los
Altos ELF monitoring site
to provide coverage during power
interrupts.
Details
of
this
effort can be
found
in
an
interim report prepared by SRI
International
,
(U)
The second
task was
the development of
an upgraded high-
data-rate ELF
system
(in duplicate)
to
be
installed
at
the TRI
and
the
SRI
sites.
Figure
is
a block diagram
of
the basic upgraded ELF data-rate
ELF system
(in duplicate)
to be
installed
at
the
TRI
and
the
SRI
sites.
Figure
is
a block diagram of
the basic upgraded
ELF data-acquis ition
system.
The ELF
signal
is collected by an antenna,
amplified,
and
then
digitized by an analog— to-digital
(A/D)
converter
so
that
the
signal can
be
input
into
a computer
for
the purpose of analysis.
(U)
The antenna
is
a "bioantenna"
(a Live
Oak
tree).
This
procedure was based
on one recommended
by
the Radioscience Laboratory at
Stanford University.
The detected
signal
is
the voltage measured across
a pair
of electrodes
implanted vertically approximately
six
feet apart
along the
lower
tree
trunk.
A full
description of
the method
is
given
in
Reference
6,
a reprint of which
is
included
in
the
interim report mentioned
above
.
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INCREASES SIGNAL STRENGTH
MAKES SIGNAL READABLE
BY
COMPUTER
DETERMINES INTENSITY OF SIGNAL
FREQUENCY COMPONENTS
FLOPPY
DISKETTES TRANSPORTED
TO
IBM XT COMPUTER
FIGURE
(U)
ELF DATA-ACQUISITION SYSTEM
(U)
The
system
is
configured around an
IBM PC
jr. micro-
processor,
which
is
not only cost-effective,
but
is
compatible with an
IBM XT computer where much
of
the ELF analysis
is
done.
Data transfer
and reduction
is
simple;
floppy diskettes
are
transferable
from one computer
to
the other.
(U)
Software has been developed
for
the
IBM PC
jr.
that
reads
input data
from the A/D converter,
performs
a fast-Fourier
transform
(FFT)
,
then outputs
seven data
files
of
19 frequencies each
to
a
floppy
diskette.
The
system operates
on universal
time
(UT), writing records
of
the means
and standard deviations
of
19 frequencies
in
the
l-to-30-Hz
range— each half
hour,
half-UT day,
UT day,
and half Pacific-time
day.
This
system
is
far superior
in speed
and accuracy
to
the prototype
system.
In
the upgraded
system,
approximately 318
ELF samples
are recorded each
half hour.
By comparison,
the prototype ELF
system sampled and processed
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(u)
the
ELF environment only
times
in
an equivalent period,
for
a
total
of about 420
samples
in
an entire
day.
(U)
The overall
system calibration
is
as
follows.
A com-
bined amplification of
the
signal
is
1000X;
the
signal
is
amplified
10X
in
a preamplifier
located
at
the antenna,
and
100X
in
a main amplifier.
This
presents
a maximum 5-V peak-to-peak
signal
at
the A/D converter.
The A/D converter operates on an
input voltage
in
the
range
of
to
5.12
V.
The output digital value
is
in
the
range
of
to
256.
Thus,
each count
on
the digital output represents
20 mV at
the
input.
The FFT algorithm
converts
the digital
sample
inputs
into coefficients
that
are proportional
to
this
input.
A value
of
100 counts
at
the frequency
1.6
Hz,
for example,
would
be
interpreted
as
indicating
that
the
1.6-Hz component
of
the measured
signal has
a voltage amplitude
of
V at
input
to
the A/D converter.
The
input signal having been amplified
1000X,
this represents
a
2-mV component
at
the antenna
input.
(U)
Further details
concerning measurement
and
calibration,
including special requirements
in amplifier design,
isolation circuit
diagrams,
and
so
forth,
are available
in
the
TRI
subcontractor
final
report
to
SRI
International
.
(U)
The
first new ELF data acquisition began
five months
after
the
start
of
the
TRI
subcontract with
SRI
International.
TRI was
able
to
initiate
the
first generation of
the upgraded
system
in only
five
months
in spite
of delays
in ordering specialized components
for
the new
systems,
and delays
in
the
fabrication
of
the circuitry of
the
systems
themselves.
Further delays were
experienced
in ordering additional
specialized components
and
in fabrication of
a needed second-generation
preamplifier.
Final
data acquisition was begun seven months
after
initia-
tion
of
the
subcontract.
c.
(U)
SRI
Site
(U)
The
SRI
ELF
system was
implemented after extensive
testing of
the upgraded
system at
Los Altos.
A second-generation
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(u)
pr eamp 1 i f i e r / amp 1 i f i er was
installed
in August
1984,
Some
differences were
immediately
seen between
the
SRI
and
the
TRI
Los Altos
stations.
The
dc
output
of
the
oak
tree
that was
selected
to be
the
ELF antenna
at
SRI was
twice
the
level
of
the
oak
at
Los
Altos.
It
is
a
larger
tree,
and
its
dc
potential with equivalent electrode
spacing
(300 mV)
was
twice
that
of
the
Los Altos
site.
This
caused
the amplified
dc measurement component
to
exceed
the
limits
of
the A/D converter.
Hence,
no
dc measurements
are
presently being made
at
the
SRI
site.
(U)
As
expected,
the
SRI
location was
found
to be
in an
electr ically-nois ier area
than
the
Los Altos
station.
The
60-Hz
signal
from power
lines
(and
the
like)
at
SRI
was
strong enough
to approach
the
limits
of
the A/D converter when
the amplification was
adequate
for
ELF
signal
detection.
The system software has
been designed
to omit data
that
exceed
the A/D converter
limits,
then record
the
fact.
To date,
the
system has operated successfully without
losing data because
limits were
exceeded.
There was
a concern,
however,
that
some
large-amplitude
ELF
anomalies
could cause
the
limits
of
the amplifier
and
the A/D converter
to
be exceeded,
in which case data would
be
lost.
A third-generation
preamplifier has
been designed, which contains
the attributes
of previous
preamplifiers,
but,
a
60-Hz
filter has
been specially designed and
added
to
the circuitry.
This
enables
greater amplification of
the
ELF
components
of
the
signal without risk
of exceeding
the
input
limits
to
the A/D con-
verter.
The
third-generation preamplifier
is presently being
fabricated
and will
be used
in
follow-on work.
(u)
Satellite Downlink Geophysical
Data-Acqui s i tion System
(U)
A near-real
time
satellite downlink
system
for
solar-
terrestrial data has recently become available
from
the National Oceanic
and Atmospheric Administration
(NOAA)
.
With
this
unit,
it
is
possible
to provide
immediate
feedback and/or
analysis
in conjunction with RV
sessions.
(Normally,
there are
long delays
in procuring solar- ter res tr ia
data; without
the downlink,
delays
of
10 days
to
6 months
are
standard.)
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(u)
By means
of
software developed
at
TRI
,
the downlink
system provides
for
accumulation of
a detailed data base directly
on computer diskettes.
(U)
A satellite controller
and
a disk antenna
for
the downlink
system were ordered
and
installed
at
the
Los Altos
site early
in
the
project.
The downlink
system
is configured around an
IBM PC
jr
. micro-
processor,
as
shown
in Figure
2.
Data
transfer
is
accomplished
by means
ANTENNA
FIGURE
(U)
REAL-TIME GEOPHYSICAL DATA
ACQUISTION VIA WESTAR
IV
DOWNLINK
(U)
The
format
of
the NOAA downlink
is oriented
toward
text transmission,
and
is not well
suited
to data-base acquisition.
Software
for recording
the data
is not provided by NOAA.
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(u)
similar
to
that of
the
ELF
system;
that
is,
by transport
of
floppy diskettes
from
the downlink computer
to
the
larger
IBM XT analysis
computer.
(U)
The
geophysical
data downlink began data acquisition
in
the
third month
of
the
TRI
subcontract.
The
initial data were
in
the
form
of
a direct recording,
which was
received
from
the
satellite,
on
to
com-
puter diskettes.
The
intent was
to acquire
as
long
a data base
as possible
by acquiring raw data at
the
same
time we were developing
the software
to
reduce
it.
The kernel around which
the
software was written was
a BASIC
program from NOAA.
The original NOAA software
supplied
the
text data
(received
from
the downlink)
in
the
form of
tabular
summaries
on
a monitor.
This
software
did not have
the capability
to
store
or record data
to
any
medium.
TRI made extensive modifications
so
that
the numerical data could
be
stored onto computer diskettes
for
inclusion
into
a data base.
The
software
is
capable
of averaging and
storing about
20 geophysical variables
at multiples
of
five-min
intervals
(e.g.,
10-
or
25-min averages), which
were defined
at
the
time
the program was
run.
It writes
six separate data
files
to
the diskette.
(U)
Initially,
the program was
set
to average
and write
the data
at
five-min
intervals.
After
a
few months
of operation,
it was
found
that
the disk drive
of
the
PC
jr.
tended
to
fail with
such
frequent operation.
The
time-averaging
span was
changed
to half-hourly
intervals
to
save wear
on
the disk drive.
This
is
the
same
time
increment used
for
the
ELF data.
The
two
systems now operate
in synchronization.
3.
(U)
Data-Acquis i t ion System
(U)
The
three
systems described above
(the
Los Altos
and
the
SRI
ELF
stations,
and
the Geophysical Data downlink),
operate
in concert,
forming
the Geophysical Data-Acquis ition System.
Figure
shows
the
system components
and their relationship
to one another.
Three
IBM PC
jrs.
operate
24 hours
a day collecting ELF
and downlink
solar- terrestrial
data.
Data
from these microcomputers
are processed
in
the
IBM XT
to
form con-
tinuous data bases.
Copies
of
these data bases
are
sent
to
the
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LOS ALTOS STATION
SRI
STATION
FIGURE
(U)
REAL-TIME GEOPHYSICAL DATA-ACQUISITION SYSTEM
(U)
Burroughs
6925 computer
for use
in
that analysis requiring high-speed
or
large memory capacity.
4.
(U)
Magnetic
Data Tapes
from NOAA
(U)
In addition
to
the above data collection
from ELF
and down-
link systems,
archived solar-geophysical data
of
interest were
selected.
Two criteria
in this
selection were
used:
first,
the
theoretical
likelihood
the data might correlate with
RV performance,
and
second,
its availability--
based on appearance
in
the regularly published NOAA bulletin "Solar-
Geophysical Data Prompt Reports."
The
data were ordered
from
the National
Environmental
Satellite Data
and
Information Service
at
the National Geo-
physical Data Center
in Boulder,
Colorado.
Of
12 data
sets
requested,
only
7 could
be
supplied;
several
of
the data sets,
although published
in
the "Solar-Geophysical
Data Prompt Reports," were not available on
magnetic
tape.
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C.
(U)
Data Analysts
1.
(U)
Integrated Data-Analys is
System
(U)
Statist ical analyses
are
performed on
the data bases
described above,
preferably
on
the
IBM XT
for cost effectiveness.
Figure
shows
the Geophysical Data/Performance Analysis System.
Data
from
all
direct geophysical
sources
are
input
into
the
IBM XT,
where
they are
preprocessed
into continuous
data bases
stored
on
floppy diskettes.
Some
data extractions
are also performed
at
this
time.
The
data bases
and
the
extracted data are
read
into
the
Burroughs
6925 computer.
The data
tapes
from NOAA are also
read directly
into
the
Burroughs computer.
The NOAA
data
files
are
long
(16,000 records
per
year
is
common),
and
require
the
high
speed
of
the mainframe computer
(and
our existing
software residing
there)
to correct,
process,
and
extract
the geophysical data
in usable
form.
NOAA data were
further processed
to extract
subsets
of
data
of
FIGURE 4
(U)
GEOPHYSICAL/PERFORMANCE DATA-ANALYSIS SYSTEM
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-RDP9B-C
(u)
interest,
and
to
summarize
the daily number
of occurrences
of event-type
data,
e.g.,
solar
flares
(see analysis
section below
for details).
These
extracted and
summarized data were down-loaded
from
the Burroughs
by modem
connection
to
the
IBM XT,
where
statistical processing was
performed.
2.
(U)
Summary
of Data Analyzed
(U)
Data were
of
two
types:
RV performance
scores
and
geo-
physical.
A detailed description of
the analysis
techniques
appears
in
Section
IV-D.
In brief,
the
RV data were
analyzed
in
five
separate
groups
according
to
their generation
in separate experimental
series.
These
five
groups were divided
into highest-
and
lowest-score categories
,
and epoch
analysis was performed on
the
eight subdivisions
against
each
of
the
following geophysical variables:
•
Geomagnetic
indices:
A
P
Sum
of K
P
C
P
C9
•
Solar
flux
at
the
following
frequencies:
15,400 MHz
8,800
4,995
2,800
2,695
1,415
606
410
245
•
International Relative
Sunspot numbers
(Ri)
or
Zurich
Sunspot
numbers prior
to
1981
(Rz).
•
Sudden
Ionospheric Disturbances partitioned
by:
Sudden enhancement
or decrease
of
LF atmospherics
at approximately
27 kHz;
further partitioned
by
the
intensity of
the disturbance.
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•
Solar Flares partitioned
as
follows:
All reported
flares
Area
of
flares
Brilliance
of
flares
10-deg segments
of
longitude
Flares
larger
than Sub-Brilliant
(SB)
Area
of
flares
Brilliance
of
flares
10-deg segments
of
longitude
•
ELF Data:
19 frequencies
from
to
30 Hz.
3.
(U)
Summary of Data Unanalyze d
(U)
Certain geophysical data were
not analyzed
for
the
following
reasons
:
*
Magnetic
Intensities
at Satellite Altitudes,
Solar Protons-
A1 though
the Downlink system
is operational,
and
the
soft-
ware
functions well,
there
is
a difficulty that
is
inherent
to
the Downlink
system.
The
transmission error
rate
is
exceedingly high;
erroneous characters
are
transmitted
frequently
in
the data,
and would require hand editing
a
time-consuming and
labor-intensive
task.
Obtaining
these
data elsewhere was discussed with
individuals
at
the SELDADS
system,
who were
the data source.
It was
found
that
summaries
of
these data do not
exist,
and
that
the data are
archived
in
a
3-s
interval
on magnetic
tape.
One month's
data require
an entire
tape,
at
a cost
of
$120 per
tape.
We would require about
of
these
tapes
for
a complete
analysis
of
the
RV data.
Obtaining data by
this means was
impractical
from
the data-process ing and
tape-expense
standpoints.
*
Solar Wind --0nly fragmentary
time
spans
of
these data were
available
from NOAA.
It was
explained
that
the antennas
used
to receive data
from Pioneer XII
and
its predecessor
satellites were redirected
to receive
signals
from
the
Martian satellites.
*
Radio Propagation Quality
Indices --These data were not
available
on magnetic
tape
from NOAA.
‘
Stanford Mean Magnetic Field --These data were not available
on magnetic
tape
from NOAA,
however,
partial analysis was
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(u)
performed on data entered
by hand
at TRI.
About half of
the data were analyzed before
software difficulties
prevented completion.
Auroral
Electrojet,
Equatorial Dst Values - -Auroral
electro-
jet data were not available
for
the entire
time
period.
Existing data
for
Dst values were
sent with
an explanation
that
the Japanese were now
in charge
of acquisition
of
this
data
set,
but had not
submitted data
since
1981.
Dst values
ended
in December
of
1983.
Three
of
the
RV data
sets
could
have been analyzed,
but
format problems prevented
it.
Most
of
the NOAA data received
on
the
tapes were
in formats
suitable
for direct publication, with
titles,
headings,
monthly averages,
and comments occurring after edch month's
daily data.
In
some
cases,
the day or month was
given
only
in
the
test heading.
This
format was unsuitable
for
computer
data analysis,
and
extensive
software had
to
be
written
to reorganize
the data
into
a usable
format.
Although
such software was written
to
extract data from
many
of
the NOAA data
sets,
this
one was bypassed because
the data were
incomplete.
Cosmic Ray Indices--These data were
sent by NOAA
in
a
format
that would have required extensive
software
development
to extract daily values.
Although daily
values
are published
in
the
ff Solar-Geophys ical Data Prompt
Reports,"
they are evidently not available on magnetic
tape
.
D.
(U)
Analysis
Techniques
and Data Preparation
.
( U )
Techniques
Use d
(U)
The
analysis was performed
on
two computers:
an
IBM XT and
a Burroughs
6925.
All analyses
that did not require
the
large memory and
high
speed
of
a mainframe were performed on
the
IBM XT,
at
a substantial
cost
savings.
In particular,
an epoch analysis program was
translated
from ALGOL
to
C
for use
on
the XT.
The
C version
for
the XT has
enhanced
capabilities
not available
on
the ALGOL version.
(U)
Two
statistical
techniques were used
in screening
the data
(1)
epoch analysis,
and
(2)
time-lag
linear regression and correlation
coefficients.
The epoch analysis was performed primarily
on
the
IBM XT
machine;
the
time-lag regressions were done on
the Burroughs.
While
the
time-lag regressions
allowed definitive statistical
statements
to be made,
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(u)
execution
of
this program was generally very costly
(up
to
$150 per
run),
so such regressions were done sparingly.
2.
(U)
De scription of Techniques
a
*
(U)
Epoch Analysis
(U)
The primary statistical program used
to
scan
the data
for
possible relationships
is
called
"epoch analysis."
The purpose
of epoch
analysis
is
to detect time-lag relationships
in noncontinuous
,
or nonscalar
data
sets
of
interest,
such as
"high-scoring viewing days."
It will
also
show areas
of nonexact
time-lag relationships, where correlations will
not
(without further data manipulation such
as
running averages,
and
so
forth).
An overview of
time periods
that may relate
to
the data of
interest
is given
in
a quick and cost-effective way.
Epoch analysis has
been used here
to indicate which
time
intervals will
be appropriate
to
run time-lag regress ions--a technique
that
is
costly and
frequently
inaccurate
if
the
timed relationships
are approximate rather
than exact.
(U)
The epoch analysis
technique compares
events with
other
timed data sets
(such
as
sunspot number)
at
intervals preceding and
following
the event.
The program reads
two
files
simultaneously.
The
first
file
is
an event
file,
the
second
a data
file.
The program first
reads
an event,
then
scans
the data temporally backward and
forward
in
time around
the event.
This
information
is
stored,
a second
event
is
read,
and
so
forth.
When all
the
events
and
surrounding data have been
read,
a printout
is
created
that
lists
appropriate cross-correlation
statistics between
the
event and data elements.
^ ^
A®
example,
the program calculates
the average values
of
a variable,
such
as
sunspot number,
for discrete
time
intervals before
or after
a
set of
RV events
of
interest--say
, high-scoring days.
For all
days
,
the
technique determines
the
sunspot number one day prior
to high-
performance
RV sessions
(the events),
the day
of,
the day after,
and
so
forth.
It will
then calculate
the average value
for each day
(e.g.,
-1,
0,
+1),
then tabulate and graph
the
results.
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b
.
( U )
Time-Lag Regression
(U)
This
is
a
standard regression analysis, which offsets
the
time
base
of
the data
in specified
intervals.
This program may
be
instructed
to perform sets
of
regressions
of many
time
lags
at
a
time,
even with data
that are not continuous.
Time
lags
are
frequently encountered
when analyzing solar-terrestrial data with respect
to
terrestrial
events.
For
instance,
approximately
two
to
four
days may elapse before magnetic
storms resulting
from solar
flares
are detected
on
earth.
Assuming such
mechanisms may also operate with respect
to RV data,
all geophysical
correlations were
carried
out
for
a
time-lag range
of
at
least plus
or
minus
five days.
3.
(U)
Description
of Analysis Methods
a.
(U)
RV Data
(U)
In order
to determine whether
RV performance correlates
with geophysical activity,
it
is necessary
to have access
to RV data bases
that have been quantified.
Data bases
that meet
this
criterion,
both
archival
and
those generated during
the subcontract period, were made
available
to TRI
for analysis.
(U)
Four
sets
of
RV data were analyzed
initially;
they
constitute
the primary data base.
Each data
set
is referred
to by
the
year
in which most of
the data were
gathered.
Table
shows
the name,
number
of
samples
,
and begin-
and
end— date
for each dafa
set.
The
RV
data were processed
for
the
epoch analysis
by selecting
the dates
of
the
highest
and
lowest
scores
or
ratings
for
each data
set.
"(U)
A fifth
RV data base was
examined near
the
end
of
the program,
generally confirming
the conclusions
reached on
the
basis
of
the primary
RV data base.
+ (U)
Selection was
done by finding high
and
low scores
in which
the value
range contained approximately one-third or
less
of
the
total data
set.
In most data
sets, more
than one
session occurred on
a given day--
frequently with different
individuals.
In
some
cases,
two
individuals
had extremely high
or
low scores
on
a given day (there
are
comments
later
about individual variability).
These data were
left
intact,
e.g.,
if
two
individuals both
scored high or
low
on
the
same day
,
those data were
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Table
(U)
DESCRIPTION OF RV DATA
Name
Sample
Number
Begin
Date
End
Date
Comments
05/14/79
08/03/79
6x6 orientation
01/18/80
12/14/81
RVer
I.S.,
Class
B
07/30/81
10/21/81
Targeting
(11)
231
01/12/84
08/17/84
RV Training
( 1 1
)
(I)
103
03/19/84
07/10/84
RV Training
(l)
UNCLASSIFIED
t> .
( U )
Geophysical Data
ELF Data --ELF data
sets were prepared
by concatenating
the
data
from several
diskettes
into
a
single,
long-
term file
for both
the upgraded
Los Altos
and
the
SRI
data.
This was
done
for daily,
half-daily,
and half-
hourly data
.
NOAA Data --fhese data required extensive preprocessing
and
specialized
software
to be written.
For
example,
two
of
the data
sets,
Sudden Ionospheric Disturbances
(SID)
and
Solar Flares,
contained multiple reports
of
the
same event observed
from different
stations.
Indices
of
location and magnitude
of
the event
fre-
quently do not agree
from station
to
station.
Software
was written
to eliminate duplicate reports
by extracting
the
single
largest report
for each event.
Extractions
of
single
events were done when appropriate.
Data
files
were constructed
that contained
the number
or value
of
the events
of
interest
for each calendar day,
from
January
1978 until
the
end of
the available data--
usually
31 August
1984.
The dates were checked
for
order and continuity.
In event-oriented data
files
such
as
SID and Flares,
events
did not occur every day.
entered
twice
in
the high
or
low data
sets
.
If
one
individual
scored
extremely high,
and another extremely
low
(on
the
same day),
that
day
was
entered
in both
the high and
low data
sets.
The exception
to
this
was
the data
set
of
RVer
I.S.,
Class
B sessions.
Several
sessions were
carried
out on
a single
day.
To create
the corresponding high and
low
data
files,
the mean score
for each day was determined,
and
the high
and
low days were
selected using
the mean scores.
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Records
containing
the appropriate null dates were
inserted
in
these data
files.
Files were also
prepared
that were
subsets
of
the event-type data
files.
Solar-flare data were cros s - tabulated
in
10-deg
longitude
segments
by daily dates.
Flares
larger
than Sub-Brilliant were
cross - tabulated
on
a daily basis
by area,
brilliance,
and
longitude
measurements.
SIDs were extracted by LF Atmospherics
and
cros s- tabulated on
a daily basis
by
the
intensity
of
the disturbance.
The
same was
done
for
VLF Sudden
Enhancements
(SES).
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V
RESULTS
(U)
A -
(U)
Results
of Geophysical Analysis
1-
(U)
Introduct ion
(U)
For many years man has speculated
that relationships exist
between various
biological
functions
and
solar activity
or
its resulting
geophysical activity.
Some empirical observations on
the quality of
RV
sessions during periods
of known
solar activity
led
to
the
idea
that
a
screening
of solar-geophysical variables
for
correlations might be
fruitful.
If,
indeed,
measurable
geophysical disturbances affect
RV
performance,
and
these relationships
could
be defined,
the reliability
of
RV-derived
information could
be determined
by considering
the
geo-
physical
environment at
the
times
of
RV sessions,
and possibly enhanced
by scheduling.
(U)
This
screening of geophysical variables
in
this
report appears
m
the order of gross measurements
to refined measurements,
which may
be
closer
to
the actual mechanisms
involved
in influencing RV performance.
Because
of
the
fact
that changes
in most measurable geophysical
data are
initiated
by solar activity,
geophysical data
sets
co-vary.
Hence,
relationships were
found
in several
data
sets
simultaneously.
These
correlations
are most
likely not due
to cause and effect relationship
between
the covarying variables,
but rather are
the result of one
or more
of
the geophysical
processes
that are driven by solar activity.
Although
correlations
to noncausative variables may
be useful
for
forecasting
purposes,
forecasts will
be greatly enhanced when
the correlations
used
are closest
to
the actual geophysical-biological mechanisms
involved.
2.
(U)
Solar
FI u
x
(U)
The
solar
flux
is
a measurement of
the electromagnetic
output
of
the
sun at several different
frequencies
in
the megahertz
range.
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(U)
223
The measurement values
are
in units
of
W m
Hz
.
These measure-
ments
are
a gross
indicator
of
the activity on the
solar; disk.
Epoch
analysis was performed
for
the high
and
the
low scoring days
of each
of
three RV data
sets.
(No solar-flux values were
recorded
for most
of
1979
in the NOAA data,
and
the 84(l)
data were not yet available when
this
analysis was performed.)
The relationships
found by epoch analysis
in
these data were generally unimpressive.
(U)
Time
lag correlations were run on
two individuals
from the
1981 experiment.
Again,
although certain correlations were
found among
the mass
of
data
(some
of
them statistically significant),
there was
great variability between
the individuals,
and no definable pattern emerged.
.
( U )
Sunspot Number
(U)
Epoch analysis
of
RV versus
sunspot number was performed.
A low peak was
found between
29 and
35 days
prior
to each of
the
four
sets
of high
scoring sessions,
and
a high peak preceded each
of
these
sessions
by
to
28 days,
A
low trough occurred
to
23 days
before
low-scoring sessions
in each
of
the
four data sets.
On
the day of
the
session,
the
sunspot number was
at
or above
the epoch mean
in each
of
the
four
low-data
sets.
Out
of
this
analysis
emerged
three
time
intervals
that may enable
forecasting:
to
30 days,
to
19 days prior
to
the
sessions,
and
(for
theoretical
reasons addressed
later)
two
to
four
days
after
the
sessions.
(U)
To examine
the
time
lags where possible correlations might
exist,
time
lag correlations were performed
for each
individual
in
the
groups
from
1979,
1980,
and
1984.
Both positive
and negative correlations
to sunspot number were
found.
These results
also
indicated
that clustering
of correlations
occurs near
the
time
intervals both preceding and
following
session dates
found
in the epoch analysis.
Overall,
779 correlations were
performed.
Up
to
38 correlations
at
the
p
= 0.05
level would
be
expected
v?
(U)
84(l)
data were not processed.
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to occur
by chance.
Fifty-six correlations were observed,
or about
percent over what would
be expected
by chance.
(U)
Three
time clusters were observed
in
the significant cor-
relations.
in
a four-day
interval,
where
76 correlations
are
represented,
the chance number
of
significant correlations
at
the
p
= 0.05
level
is
estimated
to
be
3.8.
The
interval
from
to
30 days prior
to
the session
(perhaps
reflecting
the solar-rotation rate)
had eight
individuals having
significant correlations
at
p
< 0.05;
two other
individuals were very
close
to significance.
Another
interval
from
to
19 days prior
to
the
sessions
yielded eight significant correlations ranging
from p
< 0.047
t°
P
<
0 .0003
.
A third period appeared
two
to four days
after
the sessions
This
three-day
interval
yielded
five
individuals having significant cor-
relations,
and
four others having near-significant correlations.
(U)
It
can
be surmised
that because
these correlations
exist
in patterns,
there may be
some phenomenon associated with sunspots
that
could be more closely
linked
to
the actual mechanisms
that
influences
RV performance.
A likely candidate
is
the phenomenon of
solar
flaring,
and
its
resulting effect on
the
terrestrial geomagnetic
field.
In par-
ticular,
the
finding
that
the
strongest correlations
to sunspot number
consistently occurred
two
to
three
days
after
the
sessions,
points
to
flaring.
At
first one might dismiss observation of
RV performance
apparently forecasting sunspot number.
However,
if one considers
that
large
flares
from active regions
on
the
sun
(sunspots)
can frequently be
seen before
the
region rotates
onto
the
solar disk,
a hypothesis
could
be
formed
that
incorporates
flaring as
a possible mechanism,
because
indeed,
one
can predict
increases
in sunspot numbers
by observing
flares
on the east
solar
limb.
4.
(U)
Solar Flares
(U)
Solar
flares usually occur near sunspot groups called active
regions.
The
sizes
of
these
flares
are classified
in several ways
by
the
intensity of various
characteristics associated with
them,
i.e.,
according
to
their X-ray
intensity,
optical brilliance,
area,
and radio-wave
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signatures.
There does
not
seem
to
be
a
read i ly-avai lab le comprehensive
index
that
takes
all
of
the
their
characteristics
into account.
For
this
reason,
flares were subdivided
into several
data
sets prior
to analysis:
•
The
first
set was
the
total daily number
of
all recorded
flares;
these
flares were further
subdivided
into
location of origin
in
10-deg
longitudinal
segments
from
the central meridian
of
the
solar disk.
•
The
second data
set was
an extraction
of
the
larger
flares
from
the data.
These
flares were
selected
for
their classification
of both
size and brilliance.
Those classified
as
sub-brilliant
or
larger were
used.
(The
flares were divided
by
longitude because
flaring
at certain
longitudes
on
the solar
disk
is
known
to
produce
greater
terrestrial
effects
than at other
longitudes.
For
instance,
relativistic energy showers
most frequently originate
from the northwest quadrant
of
the
sun.)
(U)
In exploring
the
theory
that
limb
flaring
(flares
on
the
edge
of
the
solar
disk) may play
a role
in RV performance,
special
attention was
given
to
this
area
of
the
sun.
Indeed,
as anticipated,
significantly higher
rates
of
limb
flaring were
found pn
the day of
(or
j
*
just before)
four
of
five
of
the high^scoring data
sets,
and on
the day
it
of
(or
just after)
low-scoring data
sets
in
four
of
five
cases.
What
this
implies
is
that
some confidence
can be placed
on
the validity of
relationship between
solar
flaring and
RV performance.
(U)
Of key
interest
is
the
finding
that
the
flares occurring
on
the
solar
limbs
(80
to
89 deg)
tend
to group with respect
to
highl-
and
low-performance
data
sets.
Large
flares occurred on
the
limbs
the
day
of
sessions
in
three
of
four
of
the
low-scoring data sets.
In
the
fourth
set,
a flaring peak occurred
three
days
later.
The number
of
flares
was
significantly greater on
low-scoring session days
(more
than
two
standard deviations
above
the epoch period mean)
in each case.
The days
following
low-scoring sessions
continued
to have high
flare
rates
across
the
solar
disk.
(On
the other hand,
in three
of
four
cases, high-scoring
*(U)
84(1)
data were
included
.
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data
sets were preceded by
an increase
in
limb
flaring by one
day.
These
values were near-significant.
We
shall
return
to
this
point below.)
In
addition
to
the
tendency of
flares
to cluster
on poor performance
days,
the numbers
of
flares was more
than double
the daily expected value
for
three
of
the
low-scoring RV data sets.
(d)
A speculation
from the data
is
that
low— viewing scores might
be associated with
flares
(occurring on
the east
limb)
rotating onto
the
solar disk
(because
of
the numerous
flare
peaks observed at all
locations
on
the disk
following poor RV sessions).
By contrast,
high scoring might
be associated with regions
rotating off
the west
limb of
the
solar disk
because
of
the
fewer
flare
peaks
following good
sessions.
Indeed,
when
diagrams
of
solar-active regions were examined
for
the
first
set of
1984
data,
nine
of
ten of
the
low-scoring days
showed active regions
near
the
east
limb.
On
the
other hand,
eight of
ten of
the high-scoring days
showed active regions
near
the west
limb.
(U)
Based
on
the observation
that,
statistically,
limb
flares
coincide with and
follow degraded
RV sessions,
but precede enhanced RV
performance
by one
day,
a speculation could
be made
that
there may
be
a
close
time relationship
for enhanced
and degraded
RV sessions.
In
hypothesizing which solar- terres trial changes could cause changes
in RV
performance,
the observed rapidity of change
and
the reversal
of
the
character
of
the
effect must be
taken
into consideration.
The
following
scenario
is
suggested.
As
a new active
flaring region rotates
over
the
solar
limb,
associated with
it
is
some kind of
a fast-acting phenomenon
that requires
a day
or
less
to produce
terrestrial effects.
The
terrestrial
effect must be relatively brief,
and
of
a character
that
is capable
of
both degrading and enhancing RV performance.
An example
of
one
such
phenomenon
is
the Sudden Ionospheric Disturbances
(SID)
caused by X-ray
and other electromagnetic-radiation bursts associated with
the
flaring
process.
SIDs
can both enhance and decrease
the quality
of global
electromagnetic
signal propagation--poss ib ly at biologically-active
fre-
quencies.
A specific
type
of
SID,
a direct solar-flare effect
(SFE),
causes
geomagnetic effects observed
simultaneously with
solar
flares.
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Another mechanism could
be
proton
storms resulting
from high-energy
flares.
Ver y-high-energy
flares
can accelerate particles
at near-
relativistic
speeds;
these
particles
are
capable
of reaching earth
in
a
matter
of
a
few hours.
Magnetic
storms may accompany
the arrival
of
this high-speed
solar wind.
Either
of
these
two mechanisms
could explain
the
immediacy
of
the
observed effect.
(U)
With regard
to
the
tendency
for
RV performance
to
first
be
degraded
then enhanced,
one might speculate
on possible mechanisms
for
bipolar behavior based
on,
for
instance,
known patterns
of magnetic
storms.
If
RV performance were correlated with
the
intensity
of
the earth’s
magnetic
field,
then
the
following known variations
that occur
as
part
of
the magnetic
storm process might
be capable
of
introducing
the observed
patterns
into
RV performance.
Typically,
the
storms
that begin suddenly
start with.
(1)
A sudden
increase
in
the horizontal
(H)
component
of
the earth's magnetic
field;
they
then
(2)
Have
an
initial
phase
lasting
a
few minutes
to
a
few
hours,
during which
H decays
to prestorm values;
(3)
This
is
followed by
a main phase
lasting about one
to
three days
in which H
is below
the prestorm value,
first decreasing,
then increasing more
slowly toward
the prestorm value-many
large random variations
occur during
this
phase;
(4)
There
is
a postperturbation period after
the
end
of
the main phase,
in which
the value
of
H continues
to
rise
toward,
or perhaps
above
the prestorm value;
(5)
The
last phase
is
an
increase
in
the daily variation
of
H, which
increases with
increasing
latitude.
If
RV performance correlated with magnetic
intensity,
patterns would certainly be
found during
the magnetic
storm
.
5.
(u)
Magnetic
Indices
(u)
Four magnetic
indices,
the
sum
of
K
A
,
C
.
P
P
and
C9 were
screened with respect
to RV performance.
is
a quas i- logarithmic
index
of geomagnetic
stations between
latitudes 47 and
deg.
is
specifically designed
to measure
solar particle
radiation by
its magnetic
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effects.
A
p
is
a daily
index
of magnetic activity on
a
linear
scale
rather
than on
the quas i-logar ithmic
scale
of
the K indices.
It
is
the
average of
the eight values
of
an
intermediate
three-hourly
index A
,
defined
as approximately one-half- the average
gamma range
of
the most
disturbed
of
the
three
force components
D,
H,
and
Z,
in
the
three-hour
interval
at standard
stations.
The
C
index
is derived
from
the
K
.
P
p
indices
by converting
the daily sum
of A
p
into
the range
of
to
2.5.
The
C9
index
is
a geomagnetic character
figure obtained
from
the
C
index
by reducing
the
C
p values
to
integers between
0 and
9 according
to certain
keys.
All
these
values
are closely related,
and,
not surprisingly,
gave
similar results
in
the epoch analysis comparing them
to RV performance.
(U)
The
four
sets
of RV scores
yielded remarkably similar
patterns with respect
to K
and corroborated
the
solar
flare
findings
extremely well.
In each
case,
values were
above
the
epoch mean
the day
preceding
low RV scores,
decreasing
in all
cases
on
the day of
the sessions
In
three
sets,
the decrease
fell below
the mean;
in
the
fourth
case,
the
value dropped considerably and was only slightly above
the mean.
The
next day's values
of
this
data set continued
to decrease and were below
the mean.
Conversely,
in the
sets
of high-scoring days,
all
four
sets
showed K
p
indices
that were below
the epoch mean
the day before
the
sessions
and
increased
to values above
the mean
in
three
of
the
four data
sets.
The
fact
that
these patterns were replicated
in
the majority of
the
test data
sets,
and
that high-
and
low-scoring data
sets yielded
inverse patterns with respect
to K
p
is
a strong
indication of
a valid
phenomenon existing.
Therefore,
what we
found were
strong similar patterns
in
the geomagnetic data with respect
to RV performance.
The geomagnetic
field was quiet just before
all high-scoring sessions,
then became more
active
the day of
the
session.
Magnetic activity was higher
than normal
one
to
five days
prior
to
low-scoring sessions.
This would suggest
that
RV sessions
be performed when
the activity of
the geomagnetic
field
is
on
the
increase after
a quiet period.
(U)
Comparing
these consistent results with
the results
of
the
solar
flare analysis
shows
that
there
is evidence
for
the
standard
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one-to-four day
time
lag between
flare
and subsequent magnetic activity.
The magnetic
indices
are
increasing on Day
(the
day of
the
sessions),
they continue
to
increase
the
day after
the
statistical
flaring,
then
decrease
in
two
to
five
days.
Results using A^
,
,
and
C9
indices were
similar;
the best definition appeared
to
be
seen with
the
index
followed by A
,
C
,
and
C9
.
For
forecasting purposes
this
is
fortunate.
P
P
The K
(and A
)
are
readily available
by means
of
the
satellite downlink,
P
P
C
and
C9
are
not.
P
6.
(U)
SIDs
(U)
Sudden
ionospheric disturbances
result mostly from flaring
of
the
sun,
although not
all
flares
cause SIDs,
and
SIDs
can also result
from unknown causes.
SIDs
are basically
a disturbance
of
the upper
ionized
layer
of
the atmosphere called
the
ionosphere,
specifically
in
the
D region.
During SIDs,
radio waves
at medium frequencies
are
strongly absorbed
and
long-distance
communications
fade out.
Cosmic radio noise
at
to
25 MHz
is
absorbed
and
also
fades.
At very
low frequencies
(15
to 40 kHz),
however,
the
D region becomes
a reflector,
and atmospheric radio noise
is
enhanced.
A SID
is marked also by
a sharp brief geomagnetic disturbance
that behaves
differently from
a magnetic
storm.
SIDs
are classified
according
to
their
intensity
and
types
of
terrestrial
effects.
(U)
Although many classifications
exist,
the
two most common
(known
to enhance
low-frequency transmission) were extracted
from
the
data base;
i.e.,
those classified
as
enhancing atmospherics,
as measured
at
27 kHz
(SEA),
and
those which enhance
signal
strength
in VLF
trans-
missions
(SES).
(The effects
of
SIDs
on ELF
is not monitored
and
is
unknown „
)
(U)
The
results
of
the epoch analysis
on SIDs correspond well
to
the
results
of
the
solar-flare and
the magnetic analyses.
While
the
SEAs
showed
some corroborative
patterns,
the
results
of
the
analysis
on
the
SESs were
remarkable.
The results
of
the
SIDs analysis
are
similar
to
the analysis
of
the occurrence
of peaks
of
solar
flares.
That
is,
there
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are
fewer
peaks
occurring around
the
times
of high-scoring sessions
than
low-scoring
sessions.
There
are more
strong SIDs
peaks
on
the day of,
and after
low-scoring sessions.
A SIDs
peak
of
importance
(magnitude)
"1"
or greater occurs
on
the
day of
the
low-scoring sessions
in
four
of
the data
sets.
Peaks
of
SIDs
also occurred
on
the day of
the session
in
four
of
five
years
of
the high-scoring data
sets,
and
on
the day prior
to
the
sessions
in
the other data
set
(1979).
Therefore,
nine
of
ten of
the data
sets
had
an SES-type
SID occurring on
the day of
the
session.
The remaining data
set had
a peak
in SIDs occurring
in close proximity
to
the session--on
the day before.
(U)
It appears
that SES-type
SIDs
are
a
good candidate
for
the
previously hypothesized
fast-acting result
of
solar activity
that could
influence
RV performance.
A peak
of
SES-type
SIDs
have occurred
on
or
near
every case
of
RV extreme-score
sets.
We
speculate
that
there
is
some
quality
of
the
SID
that
is associated with
the observed bipolar
effect,
resulting
in both high-
and
low-quality RV performance.
A quality
of
SIDs
that might produce bipolar
effects
could
be
selective
electromagnetic
propagation.
If
SIDs
selectively propagate
certain VLF
or
ELF
frequencies,
it would not
be
surprising
to
find differing biological responses
to
frequency and
intensity changes--assuming biological
responses
to ELF
exist.
Laboratory
studies
of
ELF magnetic
and electric
fields
(see
references
to work
of Adey
and others
in Bibliography)
suggest
such ELF-
biological
relationships.
An additional possibility
to account
for bipolar
behavior might
be
the
frequency characteristics
of
the atypical magnetic
activity that accompanies
SIDs.
This
can
be accomplished
by direct measure-
ment
of geomagnetic
ELF,
described
in
the section below.
B.
(U)
Results Pertaining
to
ELF
1.
(U)
Introduction
(U)
The
ELF environment,
both naturally-occurring and man-made,
is
one
good
candidate
for
the mechanism by which many
types
of biological
responses
are produced.
Laboratory
studies have
shown both sensitivity
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and selectivity
in biological
responses
to
specific
frequency and
intensity
windows.
The
intensities
found
to
be biologically active
are very weak,
and
fall
in
the
same
ranges
as naturally-occurring magnetic
and electrical
fields.
For our
initial
effort,
we
selected
the
frequency window of
to
30 Hz
for
two reasons,
one pedagogical
and one
practical:
•
It
is
the
frequency range
of
the known electrical activity
of
a human be ing--par t icular ly brainwave
frequencies.
•
It
is necessary
to
filter
out 60-Hz power-line noise,
and simple electronic
60-Hz
filters begin cutoff
at
about
30 Hz
.
With regard
to
the
latter point,
although sharper
filters
are available,
they
are elaborate
and expensive.
For
this
exploratory
investigation,
the most cost-
and
time-effective
route was
chosen.
2.
(U)
Intercomparison of
ELF Systems
(U)
A number
of comparisons between
the various
components
of
the
ELF monitoring system have been made.
The
systems
compared
include
the prototype
system at TRI
involving
the
use
of
the oak-tree bioantenna,
the upgraded
system at
TRI
involving use of both
the
oak
tree
and
a coil
antenna
on
loan
from
the Radioscience Laboratory
at Stanford University,
and
a duplicate upgraded
system at
SRI
involving use
of an oak
tree.
(U)
Correlations were performed between ELF data
sets
generated
on each
of
the
systems.
Although variations
existed,
by and
large
the
correlations
indicated
s tatis tically-s ignif icant
tracking between
the
various
systems,
including
the comparison of key concern-- tracking between
the duplicate upgraded systems
at
TRI and
SRI,
17 km distant.
In
fact,
tracking between
the
separated
TRI
and
SRI
systems,
both utilizing oak-
tree antenna,
was
somewhat better
than tracking between
the oak-tree
and
coil antennas,
both
at
the
TRI
site.
3.
(U)
ELF/RV Comparison
(U)
Epoch analyses were carried
out
to determine correlations
between ELF
and
RV data
sets
for
those periods
of overlap
in operation.
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(u)
With regard
to
the prototype
ELF
system,
whose data base began
in May of
1982,
the
1984 data base
(before
the
fifth data
base was
added)
was
the
only
one available
for
comparison.
Examination of
the correlation graphs
in
the epoch analysis
revealed
some
tendency
(over
time
spans
on
the order
of
days)
to
inverse
relationship between ELF
and
RV
;
that
is,
a
tendency
for ELF
to
be
low
in
the vicinity of high-scoring days,
and
vice versa.
There were
not
sufficient data
of
sufficient definition,
however,
to permit
statistically-signif icant conclusions
to
be
drawn.
(U)
Beginning
in June
1984,
the upgraded
ELF
system became
operational.
RV data
collected
from then
through August provided
an
opportunity
to perform preliminary epoch analyses
for
a
small
sample
of
RV data
(four
cases
each
for high
and
low scores)
on
a half-hourly basis.
(This
is
to
be compared with
the half-daily basis
of
the
prototype
ELF
system.)
An apparently consistent pattern
that emerged
in
these analyses
was
a change
from low-scoring sessions
to high-scoring sessions during
a
rapid rise
in ELF values;
the separation between
the
two was
on
the order
of
an hour
and
a half
(range one-half
to
two hours
and
a half).
This
appears
as
another
example
of bipolar effect mentioned earlier with
respect
to geomagnetic activity,
where rapid crossing from below-
to above-
average activity on
the
days
of extreme-scoring sessions was
also observed.
The time/funding
scope
of
this
leve 1-of-ef for t project
did not permit
further exploration of
this
emerging relationship between
ELF
(and other
geophysical activity)
and potential rate-of-change effects
on
RV per-
formance.
This
area appears
to show exceptional promise,
however,
and will
be
pursued
in
a follow-on program.
(U)
The
emergence
of
a possible relationship between
a period
of
time when
the
data are changing at
a rapid rate
(rather
than peaking)
is
not surprising
in
light
of known mechanism of biological processes.
Several biological processes
function by means
of rates-of-change
of
stimuli
in preference
to any particular
absolute values
of
those stimuli—
if
the
intensity of
the stimuli
fall within certain ranges.
UNCLASSIFIED
Approved For Release 2000/08/08
: CIA-RDP96-00788R001 800270001 -4
Approved For Release 2000/08/08
: CIA-RDP96-00788R001 800270001 -4
Approved For Release 2000/08/08
: CIA-RDP96-00788R001 800270001 -4