Approved For Release ON CLASSIFIED. (U) the ELF environment only 20 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 0 to 5.12 V. The output digital value is in the range of 0 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 2 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 10 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 2CpNe LASSTEHER 800270001-4 (u) preamplifier/amplifier was installed in August 1984, Some differences were immediately seen between the SRI and the TRE Los Altos stations. ‘The de 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 electrically-noisier 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. 2. (U) Satellite Downlink Geophysical Data-Acquisition System 2a ea eopnysica’ vata~Acquisition 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-terrestrial data; without the downlink, delays of 10 days to 6 months are standard.) 11 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release UN CEASSTFIED Cu) 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 CONTROLLER IBM PC JR. — DATA DISKETTE IBM XT COMPUTER BURROUGHS 6925 COMPUTER FIGURE 2. (U) REAL-TIME GEOPHYSICAL DATA ACQUISTION VIA WESTAR IV DOWNLINK we (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. 12 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 24 NCEE DESsrpr-) & {BR001800270001-4 (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-Acquisition 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-Acquisition System. Figure 3 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 13 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 20008 FREE LWOSIFIED 800270001-4 LOS ALTOS STATION SRI STATION ee WESTAR IV DOWNLINK ELF DATA IBM PC JR. No. 1 IBM PC JR. No. 3 a ——- DATA DATA DISKETTE DISKETTE ELF DATA IBM PC JR. No. 2 DATA DISKETTE IBM XT COMPUTER | BURROUGHS 6925 COMPUTER FIGURE 3. (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. 14 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 200g NIC LBSS IEE ER 1800270001-4 Cc. (U) Data Analysis 1. (U) Integrated Data-Analysis System (U) Statistical analyses are performed on the data bases described above, preferably on the IBM XT for cost effectiveness. Figure 4 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 (GEOPHYSICAL DATA) GEO- PHYSICAL DATA PERFORM- ANCE DATA BURROUGHS 6925 COMPUTER ANALYSIS REQUIRING LARGE MAINFRAME (e.g, MULTIVARIATE ANALYSIS) IBM XT COMPUTER GEMENT SYSTEM |g MANAGEMENT SYSTEM STATISTICAL ANALYSIS GRAPHS/ STATISTICS STATISTICS AND GRAPHS EPOCH ANALYSIS MANUAL ANALYSIS GRAPHS/ STATISTICS FIGURE 4 (U) GEOPHYSICAL/PERFORMANCE DATA-ANALYSIS SYSTEM 15 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release UN CLASSIFIED 800270001-4 (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 Pp 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. 16 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 20E9 FYE oA S5 IP PE F900 1800270001-4 (U) * 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 1 to 30 Hz. 3. (U) Summary of Data Unanalyzed (U) Certain geophysical data were not analyzed for the following reasons: * Magnetic Intensities at Satellite Altitudes, Solar Protons-- Although 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 20 of these tapes for a complete analysis of the RV data. Obtaining data by this means was impractical from the data-processing and tape-expense standpoints. * Solar Wind--Only 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 17 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 2000/08/08 : CIA-RDP96-0078 i—eD SSIFI (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 each 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 "Solar-Geophysical Data Prompt Reports," they are evidently not available on magnetic tape. D. (U) Analysis Techniques and Data Preparation 1. (U) Techniques Used (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, 18 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4 ne eal
Approved For Release 29NCE ROCF PE fhR001800270001-4 (u) execution of this program was generally very costly (up to $150 per run), so such regressions were done sparingly. 2. (U) Description of Techniques eke pe ron 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 regressions--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. (U) As an 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. 19 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release ONC. OCvFIED 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 (Uu) 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 2 shows the name, number of samples, and begin- and end-date for each data 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. cu) 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 20 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4 _——————— ee el
Approved For Release 2p AVE LSS PHIERRO 800270001-4 Table 2 (U) DESCRIPTION OF RV DATA Sample Number Comments 36 6 x 6 orientation 97 48 79 80 81 84 (I1) 84 (1) 05/14/79 01/18/80 07/30/81 01/12/84 03/19/84 08/03/79 12/14/81 10/21/81 08/17/84 07/10/84 RVer I.8., Class B Targeting RV Training (II) 103 RV Training (1) UNCLASSIFIED b. (U) Geophysical Data * (U) 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. * (U) NOAA Data--These data required extensive preprocessing and specialized software to be written. For example, two of the data sets, Sudden Lonospheric 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 1 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. ee 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. 21 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release ON CLASSIFIED" (U) 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 cross-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 cross-tabulated on a daily basis by the intensity of the disturbance. The same was done for VLF Sudden Enhancements (SES). 22 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 2p PE LARS 8 PF IE Bp001800270001-4 V RESULTS (U) A. (U) Results of Geophysical Analysis a pysica’ Analysis 1. (U) Introduction (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 in 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 Flux (U) The solar flux is a measurement of the electromagnetic output of the sun at several different frequencies in the megahertz range. 23 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release UN CLASSIFIED 800270001 -4 (U) The measurement values are in units of 10 22 -3 W me 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(1) 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 then statistically significant), there was great variability between the individuals, and no definable pattern emerged. 3. (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 25 to 28 days. A low trough occurred 19 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: 27 to 30 days, 16 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 * (U) 84(1L) data were not processed, 24 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4
Approved For Release 29NE EAESSPEIE pro 1800270001-4 (U) to occur by chance. Fifty-six correlations were observed, or about 50 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 27 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 16 to 19 days prior to the sessions yielded eight significant correlations ranging from p < 0.047 to 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 25 UNCLASSIFIED Approved For Release 2000/08/08 : CIA-RDP96-00788R001800270001-4