1 Vladimir G. Kossobokov Institute of Earthquake Prediction Theory & Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russian Federation Institut

11

Vladimir G. KossobokovVladimir G. KossobokovInstitute of Earthquake Prediction Theory & Mathematical Geophysics, Institute of Earthquake Prediction Theory & Mathematical Geophysics,

Russian Academy of Sciences, Moscow, Russian FederationRussian Academy of Sciences, Moscow, Russian Federation

Institut de Physique du Globe de Paris, Paris, FranceInstitut de Physique du Globe de Paris, Paris, France

International Seismic Safety Organization (ISSO)International Seismic Safety Organization (ISSO)

E-mail: E-mail: [email protected]@mitp.ru or or [email protected]@ipgp.fr

Predicting Predictable Predicting Predictable about Natural about Natural

Catastrophic ExtremesCatastrophic ExtremesЗЗ

♦ ♦ European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦♦

US3 Geophysics and Resilience, what is at stake?

The Inamori Foundation Kyoto Prize Commemorative Lecture of the 1989 Laureate in Basic Sciences

Izrail M. Gelfand, Two archetypes in the psychology of Man. Nonlinear Sci. Today 1 Izrail M. Gelfand, Two archetypes in the psychology of Man. Nonlinear Sci. Today 1 (1991), no. 4, 11(1991), no. 4, 11

It It is terrible that in our technocratic It It is terrible that in our technocratic age we do not doubt the initial basic age we do not doubt the initial basic

principles. But when these principles. But when these principles become the basis for principles become the basis for

constructing either a trivial or finely constructing either a trivial or finely developed model, then the model is developed model, then the model is viewed as a complete substitute for viewed as a complete substitute for

the natural phenomenon itself.the natural phenomenon itself.

Izrail Moiseevich

Gelfand(1913-2009)

And the better the model, the worse it becomes for its And the better the model, the worse it becomes for its applications. Indeed, the pressure of snatching “initial applications. Indeed, the pressure of snatching “initial

principles” will lead us to use the model well beyond the principles” will lead us to use the model well beyond the possibilities of its application..possibilities of its application..

♦ ♦ European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦ 22

Usually, forecast/prediction of Usually, forecast/prediction of extreme events is not an easy task. extreme events is not an easy task.

• By definition, an extreme event is rare one in a By definition, an extreme event is rare one in a series of kindred phenomena. Generally, it implies series of kindred phenomena. Generally, it implies investigating a small sample of case-histories with a investigating a small sample of case-histories with a help of delicate statistical methods and data of help of delicate statistical methods and data of different quality, collected in various conditions. different quality, collected in various conditions.

• Many extreme events are clustered (Many extreme events are clustered (far from far from independent, e.g., Poisson processindependent, e.g., Poisson process) and follow fractal or ) and follow fractal or some other “strange” distribution (some other “strange” distribution (far from uniformfar from uniform). ). Evidently, such an “unusual” situation complicates Evidently, such an “unusual” situation complicates search and definition of precursory behaviors to be search and definition of precursory behaviors to be used for forecast/prediction purposes. used for forecast/prediction purposes.


• Making forecast/prediction claims quantitatively Making forecast/prediction claims quantitatively probabilistic in the frames of the most popular probabilistic in the frames of the most popular objectivists’ viewpoint on probability requires a objectivists’ viewpoint on probability requires a long series of "yes/no" forecast/prediction long series of "yes/no" forecast/prediction outcomes, which cannot be obtained without an outcomes, which cannot be obtained without an extended rigorous test of the candidate method. extended rigorous test of the candidate method.

• The set of errors (“success/failure” scores and The set of errors (“success/failure” scores and space-time measure of alarms) and other space-time measure of alarms) and other information obtained in such a test supplies us information obtained in such a test supplies us with data necessary to judge the candidate’s with data necessary to judge the candidate’s potential as a forecast/prediction tool and, potential as a forecast/prediction tool and, eventually, to find its improvements. eventually, to find its improvements.

• This is to be done first in comparison against This is to be done first in comparison against random guessing, which results confidence random guessing, which results confidence ((measured in terms of statistical significancemeasured in terms of statistical significance). ).


• Note that an application of the forecast/prediction Note that an application of the forecast/prediction tools could be very different in cases of different tools could be very different in cases of different costs and benefits, and, therefore, requires costs and benefits, and, therefore, requires determination of different optimal strategies.determination of different optimal strategies.

• In their turn case specific costs and benefits may In their turn case specific costs and benefits may suggest a modification of the forecast/prediction suggest a modification of the forecast/prediction tools for a more adequate “optimal” application.tools for a more adequate “optimal” application.


♦ ♦ European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦

Error diagramError diagramMolchan, G.M. Earthquake Prediction as Molchan, G.M. Earthquake Prediction as Decision-making Problem. Pure Appl. Decision-making Problem. Pure Appl. Geoph, Geoph, 149149, 233-247, 1997. , 233-247, 1997.

Molchan, G.M. 5. Earthquake Prediction Molchan, G.M. 5. Earthquake Prediction Strategies: a theoretical analysis. Strategies: a theoretical analysis. In: Keilis-Borok, V.I., and A.A. Soloviev, In: Keilis-Borok, V.I., and A.A. Soloviev, (Editors). (Editors). Nonlinear Dynamics of the Nonlinear Dynamics of the Lithosphere and Earthquake PredictionLithosphere and Earthquake Prediction. . Springer, Heidelberg, 208-237, 2003. Springer, Heidelberg, 208-237, 2003.

66

Vincent Courtillot, Jean-Louis Le Mouël, Vladimir Kossobokov, Dominique Gibert, and Fernando Lopes (2013) Multi-decadal trends of global surface temperature: a broken line with alternating ~30 yr linear segments?

Atmospheric and Climate Sciences 3: 364-371


Polynomial Fit Polynomial Fit of the Hadley CRUTEM4of the Hadley CRUTEM4

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

1840 1860 1880 1900 1920 1940 1960 1980 2000 2020

C R U TE M 4vG L

n = 9n = 8n = 7n = 6n = 5n = 4n = 3n = 2n = 1

Berkley Earth Surface Temperatures, BESTBerkley Earth Surface Temperatures, BESTglobal variance adjusted monthly averageglobal variance adjusted monthly average

The NASA/MSFC Solar Cycle Prediction The NASA/MSFC Solar Cycle Prediction


Kossobokov, V., J.-L. Le Mouël, and V. Courtillot, 2012. On Solar Flares and Cycle 23. Solar Physics 276 (1-2), 383-394 (Online First™, 7 November 2011) DOI: 10.1007/s11207-011-9860-0

LMBY have erroneously reduced these numbers to LMBY have erroneously reduced these numbers to NH and NL, i.e. the numbers of years in the periods NH and NL, i.e. the numbers of years in the periods H and L, which leads them to use 21xNH² and H and L, which leads them to use 21xNH² and 21xNL² in estimating the standard error of the 21xNL² in estimating the standard error of the mean of the mean, E(E(Tik)). LMBY therefore mean of the mean, E(E(Tik)). LMBY therefore

overestimate confidence intervals overestimate confidence intervals by a factor of about square root of by a factor of about square root of 21.21.

In addition, as can be seen in their supplementary In addition, as can be seen in their supplementary material, when trying to account for dependencies material, when trying to account for dependencies in a 21-day interval (which we select), LMBY use in a 21-day interval (which we select), LMBY use 90- and 150-day intervals that naturally are 90- and 150-day intervals that naturally are affected by the seasonal variability of affected by the seasonal variability of temperatures (plot and output on page 21, SM to temperatures (plot and output on page 21, SM to LMBY). As the matter of fact, autocorrelations of LMBY). As the matter of fact, autocorrelations of the daily temperatures in 21-day intervals fall the daily temperatures in 21-day intervals fall below 0.2 in less than 3 days, while autocorrelation below 0.2 in less than 3 days, while autocorrelation for the daily range of temperatures ΔT (which for the daily range of temperatures ΔT (which LMBY fail to consider) falls below 0.2 on the second LMBY fail to consider) falls below 0.2 on the second day. As a consequence of their error, the attempts day. As a consequence of their error, the attempts of LMBY to use the T-test technique are biased by of LMBY to use the T-test technique are biased by the LMBY 90-day dependencies attributed to the LMBY 90-day dependencies attributed to weekly variability of air temperatures (LMBY page weekly variability of air temperatures (LMBY page

780 and supplementary material). 780 and supplementary material). Should this Should this 90-day correlation apply to our 90-day correlation apply to our Planet Earth, in our Solar System, Planet Earth, in our Solar System, weather forecasts would be greatly weather forecasts would be greatly improved...improved...


Le Mouël, J.-L., Blanter, E., Courtillot, V., Kossobokov, V., Shnirman, M.. A note on comments on papers published in Journal of Atmospheric and Solar-Terrestrial Physics and our responses. J. Atmos. Sol.-Terr. Phys.

73 (13), 2042-2042, 2011. DOI: 10.1016/j.jastp.2011.04.001

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Why earthquake occurrences bring us so many surprises?

The answer seems evident if we review the relationships that are commonly used

to assess seismic hazard.

Leon Knopoff (1925-2011)

J. K. Gardner and L. Knopoff

Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian? Bulletin of the Seismological Society of America, October 1974, v. 64, p. 1363

Abstract.

Yes.


Moreover, seismic evidences accumulated to-date demonstrate clearly that most of the empirical relations commonly accepted in the early history of instrumental seismology can be proved erroneous when testing statistical significance is applied.


““What do we know What do we know about earthquakes?about earthquakes?

Earthquakes are so Earthquakes are so complicated that we complicated that we

must apply some must apply some Statistics…” Statistics…”

Keiiti Keiiti Aki Aki (1930-2005)(1930-2005)

Seismic events, including mega-earthquakes, cluster displaying behaviors that are far from independent or periodic.


Year

Mag

nitu

de

Their distribution in space is possibly fractal, definitely, far from uniform even in a single segment of a fault zone.


Earthquakes evidently cascade into aftershocks that re-adjust the hierarchical system of blocks-and-faults in the locality of the main shock rupture. The majority of the great earthquakes show switching to higher activity level of recurrence; their aftershock number differs by factor 100 or more and their relaxation time varies up to 50 times (Romashkova, L., V. Kossobokov, and D. Turcotte, Seismic cascades prior to and after recent largest earthquakes worldwide. Eos Trans. AGU, 81 (48), Fall Meet. Suppl., Abstract NG62C-09, 2000: F564-F565. ).


TimeTime

Inte

r-ev

ent

tim

e, d

ays

Inte

r-ev

ent

tim

e, d

ays

0.0001

0.001

0.01

0.1

1

10

100

1000

2004/12/24 2005/01/23 2005/02/22 2005/03/24 2005/04/23 2005/05/23 2005/06/22

Lines are 20 per Lines are 20 per moving average moving average of the inter-event of the inter-event

time in an time in an aftershock zone: aftershock zone: 26 Dec 04 (red)26 Dec 04 (red)28 Mar 05 (blue)28 Mar 05 (blue)10 Apr 05 (10 Apr 05 (yellowyellow))

Such a situation contradicts generally accepted assumptions for analytically tractable or computer simulations and complicates design of reliable methodologies for realistic hazard assessment, as well as search and definition of precursory behaviors to be used for forecast/prediction purposes.


Regrettably, many branches of Natural Sciences today appear to belong to the ‘‘Pre-conceptual Sciences,’’ as defined and elaborated by Danae Pyle (a pre-adolescent girl with a pessimistic view of the world) to Lucy (a talking pygmy Clydesdale) in a series of the famous ‘‘Non Sequitur’’

comics by Wiley Miller.

As a result, the conclusions drawn from such simulations and analyses can MISLEAD TO SCIENTIFICALLY GROUNDLESS APPLICATION, which is unwise and extremely dangerous in assessing expected societal risks and losses.


Concluding the series dated June 06, 08, and 10, 2005, Danae answers with…

‘‘That’s where you come in…’’ when asked by Lucy how she is going to float across the ravine and dismiss ‘‘an unproven theory’’ of gravity.


SCIENCE SHOULD be able to warn people of looming SCIENCE SHOULD be able to warn people of looming disaster, Vladimir Keilis-Borok believes. disaster, Vladimir Keilis-Borok believes.

““My main trouble,” he says, “is feeling of responsibility.” My main trouble,” he says, “is feeling of responsibility.” ((Los Angeles TimesLos Angeles Times, 9 July 2012), 9 July 2012)

The Global Seismic Hazard Assessment

Program (GSHAP) was launched in 1992 by the International Lithosphere Program (ILP) with the

support of the International Council of

Scientific Unions (ICSU), and endorsed as a

demonstration program in the framework of the

United Nations International Decade for

Natural Disaster Reduction (UN/IDNDR).

The GSHAP project terminated in 1999 .Vladimir Isaacovich Vladimir Isaacovich Keilis-BorokKeilis-Borok (1921-2013) (1921-2013)

A systematic comparison of the GSHAP peak ground acceleration estimates with those related to actual strong earthquakes, unfortunately, discloses gross inadequacy of this “probabilistic” product, which appears UNACCEPTABLE FOR ANY KIND OF RESPONSIBLE SEISMIC RISK EVALUATION

AND KNOWLEDGEABLE DISASTER PREVENTION.


Each of 1181 strong crustal earthquakes in 2000-2009 has from 6 to 58 values of GSHAP PGA in the ¼° (1/4cos)° cell centered at its epicenter ().

The transformed values the GSHAP expected maximum, I0(mPGA), and the estimate of observed value, I0(M), allow to count the number of “surprises”, the average difference I0, and the median of I0 for earthquakes of different magnitude.

For example, each of the 59 magnitude 7.5 or larger earthquakes in 2000-2009 was a “surprise” for GSHAP Seismic Hazard Map; moreover, the minimum of the 59 values of I0 is 0.6.

The average and the median of I0 are about 2.

“One is well advised, when traveling to a new territory, to take a good map and then to check the map with the actual territory during the

journey” [Wasserburg, 2010].

The color coded discrepancy, The color coded discrepancy, II00, between actual and GSHAP , between actual and GSHAP predicted effect at epicenters of strong shallow earthquakes in predicted effect at epicenters of strong shallow earthquakes in

1900-2009. 1900-2009. “Surprises” dominate, while “big surprises” (i.e., “Surprises” dominate, while “big surprises” (i.e., II00 > 1) are > 1) are

widespread throughout all seismic regions worldwide. widespread throughout all seismic regions worldwide.

-160° -120° -80° -40° 0° 40° 80° 120° 160°-60°

-40°

-20°

0°

20°

40°

60°

0 0.0≤ 0.5 1.0 1.5 2.0 2.5 3.0 3.5 0

1919♦ ♦ European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦

The contributors to GSHAP could have evaluate the poor The contributors to GSHAP could have evaluate the poor performance of their product before its publication in performance of their product before its publication in

1999...1999...


Aptikaev et al, 2008 (2), Shteinberg et al, 1993 (3), Sauter and Shah, 1978 (4), and Murphy and O'Brien, 1977 (5)

“One is well advised, when traveling to a new territory, to take a good map and then to check the map with the actual territory during the

journey” [Wasserburg, 2010].

““Top Twelve Deadliest Earthquakes, 2000-2011”Top Twelve Deadliest Earthquakes, 2000-2011”Kossobokov, VG, Nekrasova, AK (2012) Global Seismic Hazard Assessment Program Maps are

Erroneous. Seismic Instruments 48 (2): 162-170; DOI: 10.3103/S0747923912020065

Region Date М Fatalities I0

Sumatra-Andaman “Indian Ocean Disaster”

26.12.2004

9.0 227898 4.0

Port-au-Prince (Haiti) 12.01.2010

7.3 222570 2.2

Wenchuan (Sichuan, China)

12.05.2008

8.1 87587 3.2

Kashmir (North India and Pakistan border region)

08.10.2005

7.7 ~86000 2.3

Bam (Iran) 26.12.2003

6.6 ~31000 0.2

Bhuj (Gujarat, India) 26.01.2001

8.0 20085 2.9

Off the Pacific coast of Tohoku (Japan)

11.03.2011

9.015870

(2814 missing)

3.2

Yogyakarta (Java, Indonesia)

26.05.2006

6.3 5749 0.3

Southern Qinghai (China) 13.04.2010

7.0 2698 2.1

Boumerdes (Algeria) 21.05.2003

6.8 2266 2.1

Nias (Sumatra, Indonesia) 28.03.2005

8.6 1313 3.3

Padang (Southern Sumatra, Indonesia)

30.09.2009

7.5 1117 1.8


““Top Twelve Deadliest Earthquakes, 2000-2011”Top Twelve Deadliest Earthquakes, 2000-2011”

M. Wyss, A. Nekrasova, V. Kossobokov (2012) Errors in Expected Human Losses Errors in Expected Human Losses Due to Incorrect Seismic Hazard Estimates.Due to Incorrect Seismic Hazard Estimates. Natural Hazards, Natural Hazards, 6262 (3): (3): 927-927-

935935

MagnitudeMagnitude II00 EEobsobs/E/EGSHAPGSHAP FFestest/F/FGSHAPGSHAP PPestest/P/PGSHAPGSHAP SSestest/S/SGSHAPGSHAP

6.3≤M≤6.8 0.3 2 2 1.5 1.5

6.9≤M≤8.6 1.5 350 160 10 3

M≥9 4 5,600 6,500 5,000,000 1,700

Summary of the difference between size and consequences of earthquakes observed and implied by GSHAP, measured by difference in ground shaking

intensity (Iobs-IGSHAP), ratio of radiated energy (Eobs/EGSHAP), ratio of fatalities

(Fest/FGSHAP), ratio of population affected (Pest/PGSHAP), and ratio of settlements

affected (Sest/SGSHAP).

2222♦ ♦ European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April -

Vienna, AUSTRIA ♦Vienna, AUSTRIA ♦

The self-evident shortcomings and failures of GSHAP appeals to all earthquake scientists and engineers for an urgent revision of the global seismic hazard maps from the first principles including background methodologies involved, such that there becomes:

(a) a demonstrated and sufficient justification of hazard assessment protocols;

(b) a more complete learning of the actual range of earthquake hazards to local communities and populations, and

(c) a more ethically responsible control over how seismic hazard and seismic risk is implemented to protect public safety.

It follows that the international project GEM is on the wrong track, if it continues to base seismic risk estimates on the standard method to assess seismic hazard.



A journey to the actual territory of earthquakes: are probabilistic hazard maps safe? Vladimir G. Kossobokov, Antonella Peresan, Giuliano F. Panza (accepted

for publication in Eos)

VI

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b

Ita ly: In tensity d istribu tions

Iobs

G SHA P

SHA RE10%

SHA RE2%

PG A 10%

PG A 2%

DG A

DG A10% *

DG A2% *

DBM I04

c

The situation is not hopeless and could be improved dramatically due to available geological, geomorphologic, seismic, and tectonic evidences and data combined with deterministic pattern recognition methodologies, specifically, when intending

to PREDICT PREDICTABLE, but not the exact size, site, date, and probability of a target event.


In fact, the modern methods for modeling realistic In fact, the modern methods for modeling realistic scenarios of earthquakes allow better scenarios of earthquakes allow better

Advanced Seismic Hazard AssessmentAdvanced Seismic Hazard Assessment , , Eds. G. Panza, K. Irikura, M. Kouteva-Guentcheva, A. Peresan, Z. Wang, R. Saragoni. Eds. G. Panza, K. Irikura, M. Kouteva-Guentcheva, A. Peresan, Z. Wang, R. Saragoni.

Pure Appl. Geophys. Pure Appl. Geophys. 168 (1-4), 1–752. (2011).168 (1-4), 1–752. (2011).

Understanding the complexity of non-linear dynamics of hierarchically organized systems of blocks-and-faults has led already to methodologies of neo-deterministic seismic hazard analysis and intermediate-term middle- to narrow-range earthquake prediction algorithms tested in real-time applications over the last decades.


The results of this truly global 20-year old experiment are indirect confirmations of the existing common features of both the predictability and the diverse behavior of the Earth’s naturally fractal lithosphere.

The statistics achieved to date prove (with confidence above 99%) rather high efficiency of the M8 and M8-MSc predictions limited to intermediate-term middle- and narrow-range accuracy.

Kossobokov V (2014) Chapter 18. Times of Increased probabilities for occurrence of catastrophic earthquakes: 25 years of hypothesis testing in

real time. In: Wyss M, Shroder J (eds) Earthquake Hazard, Risk, and Disasters. Elsevier, London, 477-504.

Kossobokov, VG (2012) Earthquake prediction: 20 years of global experiment. Natural Hazards; DOI 10.1007/s11069-012-0198-1


A simple answer exists to the question in the title of this chapter: most, if not all, the standard probabilistic methods to assess seismic hazard, namely PSHA, and associated risks are based on subjective, commonly unrealistic, and even erroneous assumptions about seismic recurrence. After years with many publications, we know that recurrent earthquake hazard results have failed us.

Minimum time windows required for ensuring a given uncertainty level on the estimated rate λ, COV(λ), versus return period, 1/λ.


Getting, experimentally, reasonable confidence limits on an objective estimate of recurrence rate of an earthquake requires a geologic span of time which is unreachable for instrumental, or even historical, seismology (see, e.g., Beauval et al., 2008). That is why probability estimates in Probabilistic Seismic Hazard Analysis remain subjective values from 0 to 1, derived from analytically tractable hypothetical models of seismicity.


Unified Scaling Law for Earthquakes (USLE) log log1010N = A + B·(5 - M) + C·logN = A + B·(5 - M) + C·log1010LL

where N = N(M, L) is the expected annual number of earthquakes with magnitude M in a seismic prone area of linear dimension L.

Kossobokov V.G. and Mazhkenov S.A. (1988) Spatial characteristics of similarity for earthquake sequences: Fractality of seismicity. Lecture Notes of the Workshop on Global Geophysical Informatics with Applications to Research in Earthquake Prediction and Reduction of Seismic Risk (15 Nov. 16 Dec., 1988), ICTP, Trieste, 15 p.

2929


a b c

PGA(g)

1/32

1/8

1/4

1/16

1/64

1/128

1/256

1/512

a b c

PGA(g)

1/32

1/8

1 /4

1 /16

1/64

1/128

1/256

1/512

Nekrasova, A, Kossobokov, V, Parvez, IA, Tao, X (2015) Seismic hazard and risk assessment based on the unified scaling law for earthquakes. Acta Geod Geophys 50:21-37

Neo-deterministic assessment based on USLE

GSHAP

Population

Risk

The USLE model outscore GSHAP in identifying correctly the sites of moderate, strong, and significant earthquakes. Specifically, the number of unacceptable errors, when PGA value on a map at epicenter of real earthquake is by factor 2 or greater less than attributed to this earthquake, is several times larger for the GSHAP map than for the USLE one (e.g., 11.4, 1.7, and 2.5 times for strong earthquakes in Himalayas and surroundings, Lake Baikal, and Central China region, respectively). This cannot be attributed to the difference of the empirical probability distributions of the model PGA values in a region, although evidently USLE model favors larger estimates in Baikal and Central China regions. Note that at the regional scale of investigation the GSHAP estimates of seismic hazard can be grossly underestimated in the areas of sparse explorations of seismically active faults, like those to the east of the upper segment of the Baikal rift zone.

How earthquake prediction methods work?How earthquake prediction methods work?

““Predicting earthquakes is as easy as one-two-three.Predicting earthquakes is as easy as one-two-three.

• Step 1: Deploy your precursor detection instruments Step 1: Deploy your precursor detection instruments at the site of the coming earthquake.at the site of the coming earthquake.

• Step 2: Detect and recognize the precursors.Step 2: Detect and recognize the precursors.

• Step 3: Get all your colleagues to agree and then Step 3: Get all your colleagues to agree and then publicly predict the earthquake through approved publicly predict the earthquake through approved channels.”channels.”

Scholz, C.H., 1997. Whatever happened to earthquake prediction. Geotimes, 42(3), 16-19


General Definition of General Definition of Earthquake PredictionEarthquake Prediction The United States National Research Council, Panel on Earthquake Prediction of the The United States National Research Council, Panel on Earthquake Prediction of the

Committee on Seismology suggested the following definition (1976, p.7):Committee on Seismology suggested the following definition (1976, p.7):

““An earthquake prediction must specify the An earthquake prediction must specify the expected magnitude range, the geographical area expected magnitude range, the geographical area within which it will occur, and the time interval within which it will occur, and the time interval within which it will happen with sufficient precision within which it will happen with sufficient precision so that the ultimate success or failure of the so that the ultimate success or failure of the prediction can readily be judged. Only by careful prediction can readily be judged. Only by careful recording and analysis of failures as well as recording and analysis of failures as well as successes can the eventual success of the total successes can the eventual success of the total effort be evaluated and future directions charted. effort be evaluated and future directions charted. Moreover, scientists should also assign a Moreover, scientists should also assign a confidence level to each prediction.”confidence level to each prediction.”


So far,

•none of the proposed earthquake precursory signals evaluated by the International Association for Seismology and Physics of the Earth’s Interior showed sufficient evidence to be used as a precursor (Wyss and Booth, 1997) and

•none of the gridded rate-based forecast models passed the rigid testing by Collaboratory for the Study of Earthquake Predictability (CSEP; http://www.cseptesting.org/; Jordan, 2006; Schorlemmer and Gerstenberger, 2014).



Usually, earthquake prediction is classified in respect to Usually, earthquake prediction is classified in respect to duration of expectation time while overlooking term-less duration of expectation time while overlooking term-less identification of earthquake prone areas, as well as the identification of earthquake prone areas, as well as the spatial accuracy of an earthquake prediction method. spatial accuracy of an earthquake prediction method.

• The 73 D-intersections of The 73 D-intersections of morphostructural lineaments in California morphostructural lineaments in California and Nevada determined by and Nevada determined by Gelfand et al.Gelfand et al. (1976) as earthquake-prone for (1976) as earthquake-prone for magnitude 6.5+ events. Since 1976 magnitude 6.5+ events. Since 1976 fifteen magnitude 6.5+ earthquakes fifteen magnitude 6.5+ earthquakes occurred, all in a narrow vicinity of the D-occurred, all in a narrow vicinity of the D-intersectionsintersections

3434


The linear dimensions of the target earthquake The linear dimensions of the target earthquake preparation zone of R = 10 preparation zone of R = 10 0.43 M0.43 M km ( km (Dobrovolsky et al., Dobrovolsky et al., 19791979) and are independently confirmed by ) and are independently confirmed by Bowman et al. Bowman et al. ((19981998), who claimed log), who claimed log1010R~0.44 M. R~0.44 M. [log [log1010e = 0.434…]e = 0.434…]

The forecasts are often made for a “cell” (Schorlemmer et al., 2010; The forecasts are often made for a “cell” (Schorlemmer et al., 2010; Lee et al., 2011) or “seismic region” (McCann et al., 1979; Kagan Lee et al., 2011) or “seismic region” (McCann et al., 1979; Kagan and Jackson, 1991, 1995) whose area is not linked to the size of and Jackson, 1991, 1995) whose area is not linked to the size of the target earthquake. This might be another source for making a the target earthquake. This might be another source for making a wrong choice in parameterization of a forecast / prediction wrong choice in parameterization of a forecast / prediction method and, eventually, for unsatisfactory performance in real-method and, eventually, for unsatisfactory performance in real-time applications.time applications.

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Prediction of time and location of an earthquake of a Prediction of time and location of an earthquake of a certain magnitude range can be classified into the certain magnitude range can be classified into the categories listed in the following Table –categories listed in the following Table –

Temporal, Temporal, in yearsin years Spatial, Spatial, in source zone size Lin source zone size L

Long-term 10Long-term 10

Intermediate-term 1Intermediate-term 1

Short-term 0.01-0.1Short-term 0.01-0.1

ImmediateImmediate 0.0010.001

Long-range up to 100Long-range up to 100

Middle-range 5-10Middle-range 5-10

Narrow 2-3Narrow 2-3

ExactExact 1 1

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Once I was walking in the forest, and saw tree after tree with a target drawn on it, and at the center of each target an arrow. I then came upon a little boy with a bow in his hand. "Are you the one who shot all these arrows", I asked. "Yes!" he replied. "Then how did you always hit the center of the target?" I asked. "Simple", said the boy, "first I shoot the arrow, then I draw the target".

Jacob ben Wolf Kranz of Dubno (1740-1804)

Peresan, A., Panza, G.F., 2012. Improving earthquake hazard assessment in Italy: an alternative to“Texas sharpshooting”. EOS Trans. Am. Geophys. Union 93 (51), 538-539.

The “advanced”

Texas sharpshooting

fallacy

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Real-time prediction of the world largest earthquakes: Real-time prediction of the world largest earthquakes: An experiment started in 1992 with a publication of An experiment started in 1992 with a publication of

[[Healy, J. H., V. G. Kossobokov, and J. W. Dewey. A test to evaluate the earthquake Healy, J. H., V. G. Kossobokov, and J. W. Dewey. A test to evaluate the earthquake prediction algorithm, M8, prediction algorithm, M8, U.S. Geol. Surv. Open-File ReportU.S. Geol. Surv. Open-File Report 92-40192-401, 23 p. with 6 , 23 p. with 6

Appendices, 1992Appendices, 1992]]

is going on.is going on.

Although the M8-MSc predictions are intermediate-term middle-range and by no

means imply any "red alert", some colleagues have expressed a legitimate concern about

maintaining necessary confidentiality. Therefore, the up-to-date predictions are not easily accessed, although available on the

password-protected web-pages

to about 150 Test Observers.


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Real-time prediction of the world largest earthquakes Real-time prediction of the world largest earthquakes ( ( http://www.mitp.ru))


http://www.mitp.ru/



To drive any of the achieved confidence levels below 95%, To drive any of the achieved confidence levels below 95%,

the Test should encounter ten failures-to-predict in a row. the Test should encounter ten failures-to-predict in a row.

Error Diagrams for the results of the Global Test of the Error Diagrams for the results of the Global Test of the M8-MSc predictions of the great (M8.0+) and M8-MSc predictions of the great (M8.0+) and

significant (M7.5+): significant (M7.5+): M8, 1985–2013 (1); 1992–2013 (2); M8–MSc, 1985–2013 (3), and 1992–2013 M8, 1985–2013 (1); 1992–2013 (2); M8–MSc, 1985–2013 (3), and 1992–2013

(4). (4). The “random guessing” is outlined with the 95 and 99% confidence level The “random guessing” is outlined with the 95 and 99% confidence level

curves curves (for 21 and 57 independent tests on the left and right).(for 21 and 57 independent tests on the left and right).


Kossobokov V, Soloviev A (2015). Evaluating the Results of Testing Algorithms for Prediction of Earthquakes. Doklady Earth Sciences, 2015, Vol. 460, Part 2, pp. 192–194

♦ ♦ European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA European Geosciences Union ♦ General Assembly 2015 ♦ 12-17 April - Vienna, AUSTRIA ♦♦

SeismicSeismic Roulette null-hypothesisRoulette null-hypothesis

Consider a roulette wheel with as many sectors as the number of Consider a roulette wheel with as many sectors as the number of events in a sample catalog of earthquakes, a sector per event.events in a sample catalog of earthquakes, a sector per event.

• Make your bet according to prediction: determine, which events Make your bet according to prediction: determine, which events

are inside area of alarm, and put one chip in each of the are inside area of alarm, and put one chip in each of the corresponding sectors. corresponding sectors.

• Nature turns the wheel. Nature turns the wheel. • If seismic roulette is not perfect… If seismic roulette is not perfect…

then then systematicallysystematically you can win! you can win! or lose … or lose …

If you are smart enough to know “antipodal strategy” (Molchan, 1994; 2003), If you are smart enough to know “antipodal strategy” (Molchan, 1994; 2003), make the predictions efficient ------make the predictions efficient ------

and your and your wins will outscore the losseswins will outscore the losses! !

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Seismic Seismic RouletteRoulette

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Conclusions – The Four Conclusions – The Four ParadigmsParadigms

Statistical validity of predictions demonstrated in more Statistical validity of predictions demonstrated in more than two decades of rigorous testing confirms the than two decades of rigorous testing confirms the underlying paradigms: underlying paradigms:

• Seismic premonitory patterns exist; Seismic premonitory patterns exist;

• Formation of earthquake precursors at scale of Formation of earthquake precursors at scale of years involves large size fault system; years involves large size fault system;

• The phenomena are similar in a wide range of The phenomena are similar in a wide range of tectonic environment…tectonic environment…

• … … and in other complex non-linear systems and in other complex non-linear systems (e.g., (e.g., Keilis-Borok, Gabrielov, and Soloviev, 2009;Keilis-Borok, Gabrielov, and Soloviev, 2009;

Keilis-Borok,Soloviev, and Lichtman, 2009). Keilis-Borok,Soloviev, and Lichtman, 2009).



Conclusion : Conclusion : Seismic Roulette is not Seismic Roulette is not

perfectperfectAre these predictions useful? Are these predictions useful?

• Yes, if used in a knowledgeable way. Yes, if used in a knowledgeable way.

• Their accuracy is already enough for Their accuracy is already enough for undertaking earthquake preparedness undertaking earthquake preparedness measures, which would prevent a measures, which would prevent a considerable part of damage and human considerable part of damage and human loss, although far from the total. loss, although far from the total.

• The methodology linking prediction with The methodology linking prediction with disaster management strategies does exist. disaster management strategies does exist.

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The earthquake detection could have been utilized to implement The earthquake detection could have been utilized to implement measures and improve earthquake preparedness in advance; measures and improve earthquake preparedness in advance;

unfortunately this was not done, in part due to the predictions’ limited unfortunately this was not done, in part due to the predictions’ limited distribution and the lack of applying existing methods for using distribution and the lack of applying existing methods for using

intermediate-term predictions to make decisions for taking action. intermediate-term predictions to make decisions for taking action.


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Process for determining actions to implement in response Process for determining actions to implement in response to an earthquake prediction. Smaller bold rectangular boxes to an earthquake prediction. Smaller bold rectangular boxes

provide specific information related to the larger boxes.provide specific information related to the larger boxes.


Contemporary Science can do a better job in disclosing Natural Hazards, assessing Risks, and delivering such info in advance extreme catastrophes, which are LOW PROBABILITY EVENTS THAT HAPPEN WITH CERTAINTY, i.e. 100%.

Geoscientists must initiate shifting the minds of community from pessimistic disbelieve to optimistic challenging issues of neo-deterministic Hazard Predictability.


Take back home: The principles to be Take back home: The principles to be followed in your research…followed in your research…


One could not argue that prediction research requires from a scientist a keen feeling of responsibility and rigid control of all conclusions. This responsibility requires as well the high standard of statistical analysis. It is well-known that improper use of statistical methods may lead to wrong, although desirable,

conclusions. This was often reminded by Prof. Andrei N. Kolmogorov (1903-1987) who modified for this purpose a

famous quotation attributed to Benjamin Disraeli: "There are three kinds of lies: lies, damned lies and political statistics." It would be also wrong to regard statistics as a tool for exercises in numerology by counting "descriptive" parameters. The essence of a valid statistical data analysis is summarized by Press et al. (1992) in the following three paragraphs


Data consist of numbers, of course. But these numbers are fed into the computer, not produced by it. These numbers to be treated with considerable respect, neither to be tampered with, nor subjected to a numerical process whose character you do not completely understand. You are well advised to acquire a reverence for data that is rather different from the "sporty" attitude that is sometimes allowable, or even commendable, in other numerical tasks. The analysis of data inevitably involves some trafficking with the field of statistics, that gray area which is not quite a branch of mathematics - and just as surely not quite a branch of science. In the following sections, you will repeatedly encounter the following paradigm:

• apply some formula to the data to compute "a statistic" • compute where the value of that statistic falls in a probability distribution that is computed on the basis of some "null hypothesis"• if it falls in a very unlikely spot, way out on a tail of the distribution, conclude that the null hypothesis is false for your data set

Press, W. H., S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery (1992) Numerical recipes in C: the art of scientific computing (2nd ed.). New York: Cambridge University Press, 994 p.



If a statistic falls in a reasonable part of the distribution, you must not make the mistake of concluding that the null hypothesis is "verified" or "proved". That is the curse of statistics, that it can never prove things, only disprove them! At best, you can substantiate a hypothesis by ruling out, statistically, a whole long list of competing hypotheses, every one that has ever been proposed. After a while your adversaries and competitors will give up trying to think of alternative hypotheses, or else they will grow old and die, and then your hypothesis will become accepted. Sounds crazy, we know, but that's how science works! Press, W. H., S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery (1992) Numerical recipes in C:

the art of scientific computing (2nd ed.). New York: Cambridge University Press, 994 p.


Thank you!Thank you! “When sorrows come, they come not single spies, but in “When sorrows come, they come not single spies, but in

battalions”battalions”(William Shakespeare, 1564-1616)(William Shakespeare, 1564-1616)


Documents

1 Vladimir G. Kossobokov Institute of Earthquake Prediction Theory & Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russian Federation Institut