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Etho-Geological Forecasting

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Interview with Marsha Adams

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David Jay Brown Bio

Animals and Earthquakes

Interview with Marsha Adams

By David Jay Brown

 

Marsha Adams, at the Time Research Institute in San Francisco, developed sensors that measure low-frequency electromagnetic signals, which, she says, allow her to predict earthquakes with over 90% accuracy. Adams set up a network of electromagnetic sensors along some of the major faultlines in California, and from the input she receives--which Is analyzed by specialized computer software--she issues weekly earthquake forecasts. Adams suspects that low-frequency electromagnetic signals-created by the fracturing of crystalline rock deep In the earth along fault lines can have biological consequences, and that her instruments are picking up the same signals that sensitive animals do.

 

As a result of this technology--which is supported by private subscription, not public funds--Adams says that her system makes unusual animal behavior observations obsolete. However, since It has not been clearly determined what it Is that the animals are picking up on, complete confidence in the electromagnetic sensors may be premature, and Adamsí 90% accuracy claim hasnít been confirmed by an Independent study.

As part of my research with Dr. Rupert Sheldrake we subscribed to Adamsí

earthquake prediction service for four months. Since there werenít any earthquakes during this period we canít confirm her accuracy rating.

However, she didnít make any false predictions. Adamsí work deserves more serious attention, and further support for her belief Is provided in the section below on electrical field theory.

 

This interview with Marsha occurred in 1997.

 

David: How did your career focus switch from biological research to studying earthquakes?

 

Marsha: When I was doing research at Stanford Medical School I had some experiments that I couldn't repeat, and some variability in the data that I couldn't explain. I was using chick embryo hearts-- from four day old chick embryos. These embryos were so tiny that had to be dissected under the microscope. We actually had to anchor the hearts with human hairs to string gauges in the basement of the building, because the vibrations from being on the upper floor of the building would swamp the effects that we were looking for, which was the contraction of these little hearts.

 

At about three to six days a chick embryo is nothing but really a blood spot with a little pumping heart. So, we were looking at how cardio-active drugs work, and we were testing drugs are used on the market today, and were in use then. Some of these drugs were supposed to stimulate the heart, and from time to time we would have days were the drugs didn't stimulate the heart, and we couldn't figure out why. I essentially dismantled the laboratory, and put it back together again, thinking, gee, maybe the stock solutions were bad or something of that nature. I even got as far out as thinking that the air solution that we bubbled through-an isolated muscle preparation-- to oxygenate the muscle had settled out, and that the heavier carbon dioxide had gone to the bottom.

 

But that's really grasping at straws, and nothing I could do would change that. Sometimes they just simply refused to work. But if I sat around long enough they would start to work again. It's kind of like when your car doesn't work right, and you take it to the repair shop, and all of a sudden it works fine. It's the same type of phenomenon. If I sat around long enough the experiment would start to work again.

 

So after going through several episodes of this I began to wonder what was going on, and I came to the conclusion that there was something in the environment that had a very strong effect on biological processes that we biologists were not accounting for in our experiments. I became very curious as to what that was, began reading up on it, and came to the opinion that the most likely candidate would be low frequency electromagnetic fields. I became more interested in so-called control experiments, looking at the variability that you get when you do nothing to a biological experiment-- looking at the variability that just occurs anyway.

 

David: How did you study that?

 

Marsha: I studied it in several different ways. I started collecting large data bases, at both the micro and the macro end of things, if you will. One of the other things that I did when I was at Stanford was animal surgery, and I experienced the same things with that basically.

On some days you'd see a lot of bleeding, and other days you'd see like no bleeding at all, even repeating things in the same animals. So I started collecting large databases. I collected 10,000 cases of surgical bleeding. I collected some human behavioral data eventually. I looked at crime statistics. I looked the incidence of deaths. I also looked at something called the humaticrit-- which is the percentage of red blood cells in the blood-- and looked at day-to-day variability.

 

While I was collecting these databases my plan was to-- and I did-correlate these with a lot of commercial, and not commercially, but federally available data sets of solar terrestrial data. But in the mean time I was giving an in-service at a clinic. I left Stanford and became the research director of a medical clinic. I was giving an in-service to the staff there, and said, gee, you know it's kind of strange that...

You remember last Thursday, when we had that high amount of bleeding?

This was followed by an earthquake. Isn't that curious?

 

And they saw that that wasn't all that happened. We noticed that the patients were having more allergic reactions to the drugs, and there even seemed to be a lot of chaos in the operating room. The doctors were dropping instruments. The patients were hard to manage. They were emotional. So and so forth. And they said, gee, we think we can predict earthquakes by looking at the behavior of the operating room. So I said, well, if you think you can, you tell me the next time that happens. When it happened again they told me, and sure enough another earthquake followed.

 

So with that I started to become more interested in looking at earthquakes, and including them in the data that I was screening and collecting at the time. "One of those days" is what would happen. So people became very interested having a place to report when they had some of the symptoms. And these were very clear symptoms. This was not psychic. It wasn't intuitive or anything of that sort. It was just clear malaise basically. People having headaches and acting irritable. That's when I started looking at the crime statistics and things like that.

 

David: What did you notice about the crime statistics?

 

Marsha: I did a lot of statistics screening. I think it was probably about at least six weather variables, and six geophysical variables. I found that correlations were easy to find. I think there were about twelve crime categories. I was particularly interested in the violent and spontaneous crimes. I found routinely that although the crime levels seemed to correlate with weather variables, the correlations to the geophysical variables, like the geomagnetic index, was stronger. And I found correlations to the geophysical variables more often than with the weather variables, with which we're more familiar.

 

And I did look at the incidence of earthquakes with regards to these data sets. Not as thorough as I would have liked to, but there was some indication that there was a connection there too. Seeing that both the medical data bases, and some of the human behavioral data bases, seemed to reflect odd activity at around the times of earthquakes, kind of stoked the fire, as far as my original hypothesis being correct of something electromagnetic in the environment. I came to the idea that there was probably a direct connection between the electromagnetic environment and earthquakes, and that earthquakes might even be contributing to the measurements that people make, which were thought at the time to be just strictly of solar origin.

 

David: What was the sample of people that you were using then? Was this just the people at this medical clinic, or was there a larger sample?

 

Marsha: Well, it started out with that, and one day I ended up with much more. I kind of straddled this medical clinic job and SRI at the same time. During the transition I worked at both places for awhile. I was on the governor's earthquake preparedness task force, and the head of the task force had become familiar with my work. He was impressed by it, and leaked it to the press.

 

So I ended up on the front page of the San Francisco Chronicle one morning, without even knowing about it, and as you know how things leapfrog, I ended up with people calling me saying that they also had symptoms from all over the world. And I did set up a hot line, and ran it for awhile with people calling in, mostly from the United States, and mostly from California, but basically from all over the United States.

So although I started with people in the clinic, my sample grew.

 

David: How did this lead up to the animal experiments that you were doing with Bill Kautz back in the seventies regarding earthquake prediction?

 

Marsha: Actually it didn't lead up to it at all. These were totally different studies. He and I had known each other for quite some time through SRI, being that we both worked there, and he was interested in earthquakes. He was interested in exploring the Chinese legends. The fact that the Chinese reported that they had used animals to forecast earthquakes. He wanted to quantify that, and was able to get a grant from the United States Geological Survey to set up a hot line call-in situation, where he could compare the number of call-ins to subsequent earthquakes. I did some statistics for Bill Kautz. I did some of the data analysis very late in the study.

 

David: What did his work involve?

 

Marsha: He had a hot line, and a number of volunteers throughout California that observed their pets. And whenever they noticed anomalous behavior they would call into his hot line and describe it-give the date, time, and description of the anomalous behavior. Then he would look for subsequent earthquakes, and he did find a statistically significant change in the animal behavior reports prior to some earthquakes.

 

David: How many volunteers were involved in this?

 

Marsha: I would say it was over a hundred, but I'm really not certain of that number. The study ran for around a year or two, something like that, and he did get positive results. But the USGS decided not to fund it, and not to continue it, even though he had positive results.

 

David: Did they say why?

 

Marsha: They may have told him why. I think they just thought that they had better things to do I guess, in spite of the fact that they never have had any positive results.

 

David What do you think causes the unusual animal behavior, the headaches, and irritability that people report prior to earthquakes?

 

Marsha: I think they're reactions to low-frequency electromagnetic signals. I think the electromagnetic fields are bio-active; that there is a biological effect to some frequencies, although maybe not all frequencies. If you look at the literature you can see that whether an organism or a biological process responds to electromagnetic energy, depends on the intensity and the frequency. It has to be right within a specific window in order to get a response. So I strongly suspect that it is a response to the electromagnetic energy.

 

David: Now, this is what you're measuring. How do you measure Low Frequency Electromagnetic signals?

 

Marsha: This is a privately funded research project, so I'm not at liberty to divulge what we would call trade secrets at this point in time. I'm happy to answer many questions, but I can't talk about the sensors, the technology, the range, how many sensors, that kind of thing. I can certainly talk about our performance, and the forecasts, and things like that.

 

David: Tell me about the performance and your success rate.

 

Marsha: Okay. We've been monitoring the m-field since 1981, and have a long data base. During that time we have received large signals prior to 93% of all of the earthquakes in California equal to or greater than magnitude 5.7, and since the Loma Prieta earthquake it's been 100%.

 

David: Do you get false alarms?

 

Marsha: There have been some false alarms. There was one period when we had a series of false alarms that drove me nuts. It turned out that it was during a period when St. Helen's was erupting. Evidently the system was picking up some of the e-m-energy that St. Helen's was emitting. So that was our main period of false alarms. We have had from time to time a couple of others. Not long false alarms, but, you know, gee, here's something that looks very suspicious, and that didn't produce an earthquake. But for the most part the system has been pretty accurate.

 

David: What kind of reaction have you gotten from the USGS with regard to your work?

 

Marsha: It depends on who you talk to. There's one person there who really knows about the system, and has actually seen some of the data, and he's very impressed. There are other people who are there doing earthquake forecasting research, and I think that they feel very competitive with any outsider that comes in with a new and different idea. So they react in a way that one would expect a person who feels competitive to react.

 

David: Have you ever approached them in a cooperative manner, and asked them for funding?

 

Marsha: Yes. I've written two proposals that were turned down on related topics. I attempted to get one of the main researchers interested in the work by sending him letters, and saying, I can't tell you about the technology, but let me share some of the impressions that are going on here with you. I wrote several letters. I found it was not a very fulfilling experience because the letters were misinterpreted.

 

David: With a success rate as high as the one you report, I have a very hard time understanding why they would just completely push it aside, when so much is at stake.

 

Marsha: Yeah, that is true. I find it difficult to believe too. I did this in about 1991, when I was just transitioning over to making my routine forecasts. It was at the end of the development period, and at the beginning of the actual production forecasting, if you will. It's still experimental. But I don't know, it's just that every contact that I've had with them has been discouraging.

 

David: Did you have those success rate figures that you quoted me back in 91?

 

Marsha: I had the figures, but there were fewer earthquakes. So it was high, but it wasn't as high. Because, you see, we've had thirty earthquakes in that time span, or a thirty earthquake series approximately, and at that time there had only been about maybe 15 earthquake series. So I basically missed one, and possibly two earthquakes. But one of the problems in the early development is-because I didn't have enough sensors and still don't-- I can't tell exactly where they're going to be, but I can tell if they're going to be in California.

 

You can calculate a statistical probability on whether a forecast will become true by accident, and you can tell if somebody's got something or not. I mean, in the very early stages, you don't expect a baby to jump out of the womb, and hit the floor running. It's got to learn to breath, and crawl, and go through all those stages. It's the same thing with any kind of early research. If it doesn't come out in the final form, it comes out in bits and pieces. The first bit was identifying signals that preceded a large earthquake in California.

 

I chose that rather odd 5.7 figure because statistically California has about one of those a year. So even if we see a precursor coming for a month, and we make a forecast for a month's time, the chances are only one in twelve that I would hit that particular month accurately. The odds are against my being able to successfully pick the right month in which the earthquake would occur. And, of course, if you repeatedly have successes the chances get smaller and smaller and smaller that you're just doing this by throwing darts at a map and calendar.

 

You can very easily calculate the odds of whether or not this process that I'm doing of watching the signals is something that's just random.

So this is the validation. But many scientists you find have a similar attitude to Galileo. This happened to Galileo. If you're a commercial person, if you've had no other alternative, if you can't get government funding to do a project, and you've gone and gotten private funding there are scientists that will not look at your data, unless you tell them exactly what the mechanisms are-- which nobody knows- and what the technology is.

 

David: So if you can't reveal the technology, then you can't have the results published in a scientific journal.

 

Marsha: That's right. So it's a Catch-22 situation. It's something that many of the scientists are quite well aware of. They say if someone won't publish it in a journal then we won't look at it.

 

David: But you can get around that by just publishing the data on the prediction.

 

Marsha: Yeah, and I have done that. I gave a talk at Stanford back in 1991, and I did publish my statistical methodology. I published the results to date, and that publication's essentially been ignored.

 

David: Where was it published?

 

Marsha: In The Journal for Scientific Exploration.

 

David: Have insurance companies expressed any interest in your work?

 

Marsha: Well, I have not done marketing per say. I find that because this is such a small organization that I'm just always pressed for time, and I have chosen to spend my time doing research and development rather than marketing. It's always a very difficult choice to make, because you're constantly balancing not having enough funding to get the equipment-computers and things like that-- versus analyzing the incoming data. For instance, keeping up with that, and doing the statistics that you need to do in order to do marketing. I mean, it's a humungous job for a small organization, and you're just always behind the power curve is what happens. So rather than going to the media, which I think you can understand if you do that, you end up spending an awful lot of time doing media things.

 

David: Sitting on the telephone and doing interviews, like we're doing now.

 

Marsha: Well, I don't mind it. Occasionally that's fine. But there are some people who have a success, and they run out to the media, and people get pretty tired of them first of all.

 

David: So, I guess you're saying that no insurance company ever found out about your research, and called you out of the blue?

 

Marsha: Well, I don't think they know about me. I have had publicity, but I have not promoted publicity. I've chosen to just do the work, and get to the place where I feel in a good and comfortable position. I think I'm very close to that now, where I have the statistics all nice and tied up in a package. But it's just a humungous effort to get to that place. To keep all the plates spinning at the same time is a real challenge.

 

David: I would think that the insurance companies would be the first to express an interest. They don't have any ego involvement; they're just concerned with the bottom line.

 

Marsha: Yeah. Well, insurance companies too, I think, are more interested in longer-term forecasting than short-term forecasting.

There's also a little bit of difficulty with a mindset, you might call it. People have been so convinced that earthquake forecasting is not possible, that they don't dare to even dream about what they could do if they had earthquake forecasting. So, when I talk to people I repeatedly hear them say, well, okay, if I had a forecast, so what? You know, what can I do with it? Of course, having given a lot of thought to this myself, I'm always a little incredulous with response. But it's a very normal and natural response.

 

David: What are the people who are funding your research doing with your predictions?

 

Marsha: They use them for their businesses and personally.

 

David: So, if there's a high percentage chance that this month there's going to be an earthquake, on a practical level, what would I really do differently?

 

Marsha: Okay, the system works this way. We get a long term warning, and then we get a short-term warning. So we can see it's coming. It's kind of like an ocean wave, like a huge tidal wave, or a tsunami. When you see it off shore, you can see maybe that there's a real big wave out there, but you can't tell how far away it is, because it's not close enough for your binocular vision to kick in. But you can see it, and so that would be the equivalent of the first warning. Then you watch it, and you watch it, and you watch it. And finally it gets close enough that you can start getting some triangulations, and getting some good data points.

 

Then you can start calculating about when it might hit the beach. It's the same kind of thing with the earthquake. We see the signals, and we watch, and we watch, and we watch, until we begin to see some changes that are consistent with eminent activity. So how people use this is that they use the long-term warning to get basically prepared. We give out to all the people who support the research a list of things to do at different stages. So for the long-term warning, we never know how long we have. We just know that it's not going to be in the next few days.

People can check their battery supply. They can check to see that their cans goods are still okay. They can be sure and keep gasoline in their cars.

 

There's just a number of things that people and businesses can do.

Businesses, for instance, can hold disaster drills during this time period to refresh people's memories. Then when the earthquake gets imminent, within a few days, sometimes we have some false alarms for this time period. We always warn people because the system isn't quite perfected, but it does almost always happen on one of these periods. We might go through a couple practice ones. At the end of the period, when we see it imminent, we start picking dates, and saying okay, we believe its going to be this date. We're still watching the data, but this is the target date, and sometimes we'll get maybe within a day of that target date, and push it up a little bit farther until we finally settle on a date, like we did with Northridge.

 

So during that time you behave a little bit differently. You might want to avoid freeways. Depending on your situation at work, if you work in high-rise, you might not want to be in a high-rise in the location that's earthquake prone. Some high-rises are better than others.

 

David: What area of California has the very highest frequency of earthquakes?

 

Marsha: That's a very good question. You know, I can tell you it changes over time. Certainly, the Mojave desert has been very very active lately. Of course, with the desert hot springs and the landers aftershocks series Mammoth lakes and the geysers are probably some of the most active areas, but they don't seem to have large earthquakes there.

 

David: What are some of the heavily populated areas that are especially prone?

 

Marsha: All of Los Angeles, and the Hayward Fault is of great concern. I think that those are the probably the two biggest concerns. There's so many faults underlying Los Angeles. They've recently found thrust faults right under the city that they didn't know about before. So the whole LA basin and surrounding area, I think, is of probably the most concern in California. The Hayward Fault is also great concern. There are hospitals that are built right on the fault. The San Andreas on the peninsula is also of pretty strong concern. So, I think those are the key areas.

 

David: What do you think is causing the electromagnetic signals that you're measuring?

 

Marsha: Well, nobody really knows. There have been several theories proposed. Water flowing, the dilitentsy theory. The one I like the best is based on the experiments done in laboratories. At the Colorado division of mines and geology Bran Brady did some experiments putting crystalline rock under hydraulic pressure. And just before the rock fractures it emits a burst of electromagnetic activity, a very broad spectrum, including light. And they have seen peruses of light around the core samples at the time that it fractures. So the theory that I'm partial to is that you're seeing the evidence of crystalline rock fracturing deep in the earth along the fault lines. But there are other theories that other people also like.

 

David: Are there other methods, or combinations of methods, besides monitoring electromagnetic signals, that you also think show promise for predicting earthquakes?

 

Marsha: Nobody has ever claimed reproducible success with any other method. There has been somebody from the USGS who was looking at the incidence, I think, of small earthquakes along near Hollaster, and had some success forecasting slightly larger earthquakes. But that section of the fault is fairly anomalous, in that it's always slipping and moving, where other faults are not doing that. So whether that technique is transferable to other faults is in question, And the man I don't believe has been doing this for a long enough time to really say that this always happens, but I'm not too sure. I just read one article about it

 

Let's put it this way, the USGS at Parkfield has the string gauges.

They've got creep meters and lasers down there. They're hooked into GPS system. You may want to check into the accuracy of my statement here, but they have issued some earthquake warnings down there, and to my knowledge they've never been based on readings from their instruments.

They were the result of statistical probabilities based on past earthquakes. Past earthquake activity has statistically been followed by other larger earthquakes. All of the alerts that they have issued have been because there's already been an earthquake, and not because of instrumentation. You may want to check me on that, because I'm not privy to all of their data. But I know that's true for a very high percentage, if not all .

 

David: If I gave you all the funding and manpower that you needed, what type prediction system would you ideally set up?

 

Marsha: Ah. Boy, that's a great question. Well, I would use it to first of all deploy a lot more sensors. Probably all over the western U.S. to start, and all over parts of the world.

 

David: Right now you're just measuring in California?

 

Marsha: California and vicinities. I go up a little bit into Oregon, especially the coastal waters of the Pacific Northwest, just offshore.

Occasionally we pick up something around the Vancouver Island area, but it's not reliable like California. We need much more staffing, programmers, statisticians, engineers, to really make this system work in a refined way, to refine the system that we have right now. We need a lot more computers, higher speed computers. I'm maxed out on the programming language that I use. I've used up the capacity of the programming language and the computer's. It takes hours to run a forecast now, because I'm using-- by modern standards-- fairly slow computers, and just software capabilities.

 

David: Let's say we were able to put the ideal prediction system into place, now how would California benefit?

 

Marsha: Mainly by saving lives and property. Most of the deaths that occur in earthquakes are simply because people are in the wrong place at the wrong time. If you could get people into safer, better places, you would automatically save most of the lives that are lost in an earthquake. At the Japan-U.S. conference I learned that, in California anyway, the freeways killed most of the people, and also some unsafe buildings. In Japan most of the deaths occurred in single-family houses that were not well built, that's not the case in California, but there are some buildings that are not well built, and people should know about those buildings. The University of California for instance, their buildings are fairly...

 

David: Fragile?

 

Marsha: I guess. And they know it. But those people who work in those buildings would benefit from a reliable earthquake forecast. It would take a highly reliable system, because you'd have to weigh the economics of evacuating, or having people stop work. There's tremendous economic consequences in taking these measures, So you'd have to get it to the point were it was reliable within hours; a specific day and reliable within hours. And tell people not to come to work. But also tell them what to do. That has to go hand-in-hand with a forecasting system, because if people don't know what to do they panic, and that could be a major liability. But if people feel that they're in control, and if they have something to do that they feel they can mitigate the circumstance, then they get busy and do it. Then you don't have this, for the most part, these Panic factors.

 

David: Take the day off work and celebrate with an earthquake party.

 

Marsha: Great. I think that's a wonderful idea. Yes, not going to work, taking alternative routes, avoiding, on your way to wherever you do have to go. Filling your bathtub with water, for instance, is another thing.

Sometimes it takes months to get water back. Sometimes it takes weeks, but if you do have spare water on hand, you're all the better off for it. You certainly won't mitigate a month's worth of a lack of water with a bathtub, but it'll certainly be very helpful in the first few days after an earthquake. Because systems do get in place; maybe a week later they'll have systems bringing in water and so on. But in the first few days you'll have to figure you're on your own.

 

So that can save lives and property. It all depends so much where you are in relation to the earthquake, and how badly you're damaged. If you're in a place where you're on the periphery, you might benefit from watering your landscape, for instance. Then if your water goes out for a few days, you've saved probably thousands of dollars worth of landscaping. If you're right at the epicenter, well, forget it. But there are just numerous things to do mainly to get people out of harm's way, and to get emergency response teams into the area.

 

You can bring emergency response teams into an area, or have them on standby. You could bring equipment in. You can bring supplies in advance of the earthquake. So much depends on timing right after an earthquake.

If you have somebody who's bleeding, and you get to them with a few minutes or hours, you could save their life, But if they sit there for three days then it's fatal. So to have some control over the timing and access to supplies. Fires-- to bring in mutual aid in advance would be very beneficial in saving property, and most of the damage. A lot of the damage in dollars is due to fires, and not directly to the earthquake.

And to have people do some fire damage mitigation before the earthquake.

They could shut off their gas supplies. But that's pretty drastic, and you have to have a very highly reliable system in order to take those drastic measures. You could close down bridges, and not have people in high-rise buildings. But it could just save billions of dollars, especially in the fire mitigation, and literally thousands of lives.

 

David: What are you currently working on?

 

Marsha: It's very mundane. I'm working on getting some marketing material together. I'm in the position that I have so many ideas that I want to test and I want to do. My head is just full of ideas, and it's tremendously frustrating because working in such a small capacity there's just no way that I can try to implement all of them. So I just kind of plod along, and test one idea after another. I have a huge backlog of ideas on how I might make the system better.

 

I write all of my own software, and to test and implement these ideas it usually requires writing another piece of software, and then after I've done that then I've got to test it, and see if that was a good or a bad idea. There are always some of each. So that's mainly what I do is I produce forecasts. That takes two days a week, and the rest of the time, the other five days, I usually work on weekends, I spend in development, and most of the activity is writing or running software.

 

There are three levels of people who are research supporters: personal, small business, and corporate. The personal, which receives one five-page forecast every week is $30 for the month. Small business contributors are $150 a month because they cover more people. For the corporate we ask $1000 a month.

 

Marsha Adams can be reached at:

 

Time Research Institute

P.O. Box 620198

Woodside, CA 94062



 

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