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| '''Earthquake prediction''' is much like taking on the |
'''Earthquake prediction''' is much like taking on the ]; you can see patterns, you have an idea what is going on, but can you make a profit? For stocks it is a purely a matter of money, for a social benefit like earthquake prediction, it is a matter of whether the prediction truly helps anybody. | ||
| ]s were once thought to be random geologic events without cycle or pattern, and in a behave exactly a lot like stocks, wind bursts, solar flares, whatever. The method of attempting to predict the stock market by direct examination of of historic price swings has its adherents, and its detractors. In fact, wherever, there are fundamental laws working at the smallest to largest scale, we have what is called a power law. For stocks, there is a pattern that the number of daily price-swings of 1%, is, perhaps, 8 times the number of days when the swing is 2%, which is eight times the number of days at 4%. Once in a while, there is a major 'stock-quake' with a big swing! | ]s were once thought to be random geologic events without cycle or pattern, and in a behave exactly a lot like stocks, wind bursts, solar flares, whatever. The method of attempting to predict the stock market by direct examination of of historic price swings has its adherents, and its detractors. In fact, wherever, there are fundamental laws working at the smallest to largest scale, we have what is called a power law. For stocks, there is a pattern that the number of daily price-swings of 1%, is, perhaps, 8 times the number of days when the swing is 2%, which is eight times the number of days at 4%. Once in a while, there is a major 'stock-quake' with a big swing! | ||
| The number of earthquakes generally follow a power law, as well. They are rated in size by a logarithmic scale: Magnitude (calculated in different ways). An M3 earthquake has about 30 times more energy than an M2. Also, M2 earthquakes occur 10 times more often than M3's, which are 10 times more frequent than M4's, etc. Some natural phenomena follows power laws because it is ], self-similar over all scales. As a result of this ubiquity, people generally see 'patterns' or 'things' in any fractal distribution. Thus, the background of stars has its constellations, or you may see a duck in a fluffy cloud. One branch of mathematics that deals with pattern analysis explicitly is called ]. | The number of earthquakes generally follow a power law, as well (see ]). They are rated in size by a logarithmic scale: Magnitude (calculated in different ways). An M3 earthquake has about 30 times more energy than an M2. Also, M2 earthquakes occur 10 times more often than M3's, which are 10 times more frequent than M4's, etc. Some natural phenomena follows power laws because it is ], self-similar over all scales. As a result of this ubiquity, people generally see 'patterns' or 'things' in any fractal distribution. Thus, the background of stars has its constellations, or you may see a duck in a fluffy cloud. One branch of mathematics that deals with pattern analysis explicitly is called ]. | ||
| Like stocks, the pattern of earthquakes is quite capable of being correlated with anything -- once! People have 'associated' the onset of an earthquake with such things as animal behavior, the weather, motion in the level of water wells, etc. Unfortunately, unlike clouds, patterns which might be useful in predicting quakes are not as evident as that rain is more likely when it is cloudy than when it is not. The science of ] is primarily concerned with discovering patterns and quantifying evidence of associations or correlations in data, regardless of cause. For example, a statistical link may be established between consumption of fatty food and ] disease, just as there is a statistical link between ] smoking and various illnesses. | Like stocks, the pattern of earthquakes is quite capable of being correlated with anything -- once! People have 'associated' the onset of an earthquake with such things as animal behavior, the weather, motion in the level of water wells, etc. Unfortunately, unlike clouds, patterns which might be useful in predicting quakes are not as evident as that rain is more likely when it is cloudy than when it is not. The science of ] is primarily concerned with discovering patterns and quantifying evidence of associations or correlations in data, regardless of cause. For example, a statistical link may be established between consumption of fatty food and ] disease, just as there is a statistical link between ] smoking and various illnesses. | ||
| To be socially useful, earthquake predictions do not have to be ultra precise in magnitude, time and place. Even predictions of a general nature can be quite useful if they are based on scientific principles. For example, the ] region of |
To be socially useful, earthquake predictions do not have to be ultra precise in magnitude, time and place. Even predictions of a general nature can be quite useful if they are based on scientific principles. For example, the ] region of C] has experienced a magnitude 6 earthquake approximately every 22 years since some time in the 1800s. This led reseachers to predict that a similar quake would hit the region in the mid-1980s. Because of the potential value of the scientific data that could be obtained from monitoring seismic data prior to a quake, and because the Parkfield area is relativly quiet - in comparison to most urban areas with respect to man made siesmic activity, the region was heavilly instrumented with all varieties of monitoring equipment. | ||
| The predicted quake failed to materialize on the expected fault, however a sizable quake did occur in nearby ] in ]. Perhaps the Coalinga quake released some of the stress on ] near Parkfield, and was in effect a |
The predicted quake failed to materialize on the expected ], however a sizable quake did occur in nearby ] in ]. Perhaps the ] quake released some of the stress on ] near Parkfield, and was in effect a substitute for the missing quake. If that is the case, then one would have expected that the next quake in the Parkfield region would be sometime in the mid 2000s. Indeed another killer quake occurred near Parkfield, this time in ] in ] ]. Regrettably, the ] quake of December 2003 produced two fatalities in the town of ]. | ||
| While it might be desireable to be able to predict a specific quake, of a particular magnitude on a given day, the more socially useful predictions in fact are the predictions that a particular geographic region might be espescially likely to have a major siesmic event within a particular time frame. That is because if it could be determined that a killer quake was definitely going to hit an area, even as vaguely as 'soon', then it becomes possible for regional planners to allocate resources for such projects as ubran redevolpment, retrofitting, etc., in those areas where the commitment of a portion of otherwise finite public capital will have the greatest public benifet. | While it might be desireable to be able to predict a specific quake, of a particular magnitude on a given day, the more socially useful predictions in fact are the predictions that a particular geographic region might be espescially likely to have a major siesmic event within a particular time frame. That is because if it could be determined that a killer quake was definitely going to hit an area, even as vaguely as 'soon', then it becomes possible for regional planners to allocate resources for such projects as ubran redevolpment, retrofitting, etc., in those areas where the commitment of a portion of otherwise finite public capital will have the greatest public benifet. | ||
Revision as of 04:50, 12 October 2004
Earthquake prediction is much like taking on the stock market; you can see patterns, you have an idea what is going on, but can you make a profit? For stocks it is a purely a matter of money, for a social benefit like earthquake prediction, it is a matter of whether the prediction truly helps anybody.
Earthquakes were once thought to be random geologic events without cycle or pattern, and in a behave exactly a lot like stocks, wind bursts, solar flares, whatever. The method of attempting to predict the stock market by direct examination of of historic price swings has its adherents, and its detractors. In fact, wherever, there are fundamental laws working at the smallest to largest scale, we have what is called a power law. For stocks, there is a pattern that the number of daily price-swings of 1%, is, perhaps, 8 times the number of days when the swing is 2%, which is eight times the number of days at 4%. Once in a while, there is a major 'stock-quake' with a big swing!
The number of earthquakes generally follow a power law, as well (see Zipf's law). They are rated in size by a logarithmic scale: Magnitude (calculated in different ways). An M3 earthquake has about 30 times more energy than an M2. Also, M2 earthquakes occur 10 times more often than M3's, which are 10 times more frequent than M4's, etc. Some natural phenomena follows power laws because it is fractal, self-similar over all scales. As a result of this ubiquity, people generally see 'patterns' or 'things' in any fractal distribution. Thus, the background of stars has its constellations, or you may see a duck in a fluffy cloud. One branch of mathematics that deals with pattern analysis explicitly is called Ramsey Theory.
Like stocks, the pattern of earthquakes is quite capable of being correlated with anything -- once! People have 'associated' the onset of an earthquake with such things as animal behavior, the weather, motion in the level of water wells, etc. Unfortunately, unlike clouds, patterns which might be useful in predicting quakes are not as evident as that rain is more likely when it is cloudy than when it is not. The science of statistics is primarily concerned with discovering patterns and quantifying evidence of associations or correlations in data, regardless of cause. For example, a statistical link may be established between consumption of fatty food and cardiovascular disease, just as there is a statistical link between cigarette smoking and various illnesses.
To be socially useful, earthquake predictions do not have to be ultra precise in magnitude, time and place. Even predictions of a general nature can be quite useful if they are based on scientific principles. For example, the Parkfield region of California has experienced a magnitude 6 earthquake approximately every 22 years since some time in the 1800s. This led reseachers to predict that a similar quake would hit the region in the mid-1980s. Because of the potential value of the scientific data that could be obtained from monitoring seismic data prior to a quake, and because the Parkfield area is relativly quiet - in comparison to most urban areas with respect to man made siesmic activity, the region was heavilly instrumented with all varieties of monitoring equipment.
The predicted quake failed to materialize on the expected fault, however a sizable quake did occur in nearby Coalinga, California in 1983. Perhaps the Coalinga quake released some of the stress on San Andreas Fault near Parkfield, and was in effect a substitute for the missing quake. If that is the case, then one would have expected that the next quake in the Parkfield region would be sometime in the mid 2000s. Indeed another killer quake occurred near Parkfield, this time in San Simeon, California in December 2003. Regrettably, the San Simeon quake of December 2003 produced two fatalities in the town of Paso Robles.
While it might be desireable to be able to predict a specific quake, of a particular magnitude on a given day, the more socially useful predictions in fact are the predictions that a particular geographic region might be espescially likely to have a major siesmic event within a particular time frame. That is because if it could be determined that a killer quake was definitely going to hit an area, even as vaguely as 'soon', then it becomes possible for regional planners to allocate resources for such projects as ubran redevolpment, retrofitting, etc., in those areas where the commitment of a portion of otherwise finite public capital will have the greatest public benifet.
Predicting such things as a small earthquake in California 'any day now', might be somewhat like saying a horse will win the Kentucky Derby - in fact a group of scientists at the University of California, Los Angeles, lead by Dr. Vladimir Keilis-Borok, predicted that a quake similar to the Paso Robles quake would strike in a 12,000 square mile (31,100 km) area of Southern California within a time frame of a few months. However, this predicted earthquake never materialized.
As scientists study earthquakes they will become more precise in their estimates of seismic hazard, using such advanced tools as real-time GPS.
External link
- The USGS view on earthquake prediction http://www.geophys.washington.edu/SEIS/PNSN/INFO_GENERAL/eq_prediction.html