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1 Valerio Tramutoli 1,2 1 University of Basilicata, Potenza – Italy 2 Institute of Methodologies.

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Presentation on theme: "1 Valerio Tramutoli 1,2 1 University of Basilicata, Potenza – Italy 2 Institute of Methodologies."— Presentation transcript:

1 1 Valerio Tramutoli 1,2 1 University of Basilicata, Potenza – Italy 2 Institute of Methodologies of Environmental Analysis, CNR, Tito Scalo – Potenza – Italy On the potential of satellite TIR surveys for a Dynamic Assessment of (short-term) Seismic Risk: some examples from the EU-FP7 PRE-EARTHQUAKES Project Valerio Tramutoli 1,2 1 University of Basilicata, Potenza – Italy 2 Institute of Methodologies of Environmental Analysis, CNR, Tito Scalo – Potenza – Italy SCEC CSEP Workshop on Testing External Forecasts and Predictions Los Angeles 7-8 May 2013

2 TIR SIGNAL surface T S : surface temperature : spectral emissivity NOAA-16 July, 22, GMT AVHRR Channel 4 total atmospheric transmittance and profile which depends on physical (mainly T(h) temperature profile) and chemical (mainly H2O, CO2, NH4) properties of the atmosphere atmosphere

3 Data Analysis: the noise ! (natural/observational) surface atmospere Atmospheric transmittance Surface temperature Spectral emissivity orography Atmospheric temperature profile Atmospheric humidity profile Time of day Season Satellite view angle Satellite spatial resolution Satellite TIR signal TIR signal is strongly variable depending on the observation time t and place r.

4 TIR Anomaly Monitoring by RST (Robust Satellite Technique): the RETIRA ( Robust Estimator of TIR Anomalies ) index (Tramutoli et al., RSE, 2005) t y x reducing site effects Signal time-average µ ΔT (x,y) and standard deviation ΔT (x,y) are computed at the pixel level in similar observational conditions (same month of the year, same time slot, etc.) reducing year-to-year variability and seasonal-drift effects The local signal excess T(x,y,τ) = T(x,y,τ) - (compared with the spatial average on the scene) is the considered signal instead of its absolute local value T (x,y,τ) Validation/confutation approach always applied T (x,y,τ) V(x,y,τ) = T(x,y,τ); T(x,y,τ) = T(x,y,τ) - space-time persistence required known spurious effects discarded ( Filizzola et al., 2004, Aliano et al., 2008, Genzano et al., 2009 ) RST derives from RAT (Robust AVHRR Approach) (Tramutoli, 1998)

5 A posteriori Validation/Confutation Analyses (5.7 – 9.0) MAGNITUDE EQs EVENTTECHNIQUE 23 November 1980, Irpinia-Basilicata-Italy, M s =6.9 AVHRR TIR (Tramutoli et al., Annals of Geophysics, 2001) 23 November 1980, Irpinia-Basilicata-Italy, M s =6.9 AVHRR LST (Di Bello et al., Annals of Geophysics, 2004) 26 September 1997, Umbria, Italy M s =5.9 to 6.4 METEOSAT TIR (Aliano et al., Annals of Geophysics, 2008) October 1997, Umbria, Italy M s =5.7 max METEOSAT TIR (Aliano et al., Annals of Geophysics, 2008) 17 August 1999, Kocaeli-Izmit, Turkey, M s =7,4 METEOSAT TIR (Aliano et al., Annals of Geophysics, 2008) 17 August 1999, Kocaeli-Izmit, Turkey, M s =7,4 METEOSAT TIR (Tramutoli et al., Rem. Sens. Env. 2005) 7 September 1999 Athens M s =5.9 AVHRR LST (Filizzola et al., Phys. Chem. Earth, 2004) 7 September 1999 Athens M s =5.9 METEOSAT TIR (Filizzola et al., Phys. Chem. Earth, 2004) 16 October 1999, Hector Mine, CA, M s =7,4 GOES TIR (Aliano et al., Annals of Geophysics, 2008) 26 January 2001 Gujarat, India M s =7.7 METEOSAT TIR (Genzano et al., Tectonophysics, 2006) 21 May 2003 Zemmouri, Algery M s =6.9 METEOSAT TIR (Aliano et al., IEEE, Multi-Temp, 2007) 6 April 2009, Abruzzo, Italy M=6.3 AVHRR TIR, MODIS TIR, METEOSAT TIR (NHESS,Genzano et al., 2009, Pergola et al., 2010, Lisi et al., 2010) 11 March, 2011 Tohoku, Japan M=9 MTG TIR (Genzano et al., AGU, 2011)

6 The method has been independently evaluated by two projects funded by two National Space Agencies (NASA and DLR) Greece-Turkey AVHRR 6 YEARS California MODIS 7 YEARS

7 7 V.Tramutoli__ EMSEV 2010 ___Chapman University, Orange, CA, USA Moving to multiparametric observations (Abruzzo-LAquila April 6 th 2009 EQ) TIR anomalies MODIS-AVHRR-SEVIRI 30/3/09 Number of EQ January 1 up to April 6, 2009 CO2 fluxes Martinelli, /3/09 Uranium groundwater Plastino et al 2010 Genzano et al; NHESS; 2009 Lisi et al; NHESS; 2010 Pergola et al; NHESS; 2010 Vp/Vs anomalies Lucente et al, (Geology, 2010) G. Papadopoulos et al., 2010 VLF radio anomalies Rozhnoi et al 2009 De Santis et al., /3/09 TEC anomalies Akhoondzadeh et al., 2010

8 8 Laboratoire the Physique et de Chimie de lEnvironment and de lEspace - CNRS Partners WD IZMIRAN FIAG UNIBAS DLR TUBITAK MAM RSS GSI LPC2/CNRS CHAP NOA (increasing through Networking Membership) National Observatory of Athens Chapman University

9 Strategy independent observations Integration tool: Pre-Earthquakes Geoportal (PEG) 1. Learning Off-line integration on past events over 3 main testing areas/events 2. Apply in Real Time: PRIME (Pre-earthquakes Real-time Integration and Monitoring Exercise) Real time integration over 2 selected wide areas Jul– Nov 2012 and tools

10 From a posteriori to real time validation/confutation PRIME The Pre-earthquakes Real-time Integration and Monitoring Experiment (July-November 2012)

11 18-JUL-2012 DECISION: To locally look to the data, Blue (Only Local) Alert Level

12 19-JUL-2012 DECISION:, REQUEST OF ATTENTION BY PARTNERS ! Yellow Alert Level

13

14 20-JUL-2012 DECISION:, MOVE TO RED ALERT

15

16 20-JUL July :26:02 UTC M=5 ANDIRIN – KHARANMANMARA event occurred (4 days after the first anomaly observed on July 18)

17 PRIME results Example 2 K.Maras-Pazarcik event (16/10/2012 M 4.6) The game of responsibility a real time experiment Presented at the EMSEV 2012 Conference Gotemba Japan 3 October 10:45 LT

18 28-SEPTEMBER-2012 non persistent anomalies DECISION: To Locally look to the data, Blue (Only Local) Alert Level

19 29-SEPTEMBER persistences close to faults DECISION:, REQUEST OF ATTENTION BY PARTNERS ! Yellow Alert Level

20 DECISION:, MOVE TO RED ALERT 30-SEPTEMBER persistent high intensity close to the fault

21 01-OCTOBER-2012 no anomalies (but the alert status should be mantained for the next 6-7 days)

22 OCTOBER 1, 2012 (18:17 Rome time) Why ? DECISION:, MOVE TO RED ALERT

23 WHY ? 20 July 2012 (2 days before the M5 EQ) Same shape, same place than in the previously predicted event (22 July 2012, M=5) 22 July :26:02 UTC M=5 29 September September 2012

24 WHY ? 29 September September 2012 Anomalies (again) following the main fault systems

25 OCTOBER 1, 2012 (19:43 Moscow time) PRE-EARTHQUAKES collaboration (FIAG, Sergey Pulinets) PRE-EARTHQUAKES final review meeting - Brussels - 15 March 2013

26 OTHER AVAILABLE INFO Medium term forecast (e.g. M8+, Kossobokov)

27 OCTOBER 2, 2012 (13:29 Berlin time) PRE-EARTHQUAKES collaboration (DLR, Norbert Jakowski) :25:00 UT :25:00 UT :05:00 UT :05:00 UT :45:00 UT More than 10 hours/day of anomaly on Sept (see Tiger Lee speach) continuing 30 sept and Oct 1 but with geomagnetic storms VIOLET ALERT

28 Participants to the EMSEV 2012 Conference Gotemba (Japan) 3 October 2012

29 2 weeks later EMSEV presentation 16 October :25:05 UTC M L 4,5 Depth 39.4 Km :16:02 UTC M L 4,6 Depth 9.2 Km

30 Conclusions (? only 4 months of test ) During PRIME experiment significantly persistent TIR anomalies were observed only in few cases (very often in apparent relation with earthquakes occurred within 2 weeks later). Integration with ancillary information and/or observations allowed to increase the number of pre-alerted events Very few earthquakes with M>4 (not necessarily the most important) have been pre-alerted compared with their total number (>60, clouds coverage playing the major preventing role). The repetition of pre-seismic TIR anomalies with similar characteristic in the same place strongly increases reliability of the alerts (shared with the EMSEV community 2 weeks before)

31 The italian (DPC-INGV-S3) project on short-term earthquakes prediction (Coord. Prof. Dario Albarello)

32 32 1.Describe a typical forecast: Space-time persistent TIR anomalies (not associated to known and verifiable spurious effects) can contribute to increase the alert level in the framework of a DASR System. In association with other information quality of the forecast strongly increase (no apparent relations with magnitude). 2.What area do they cover? variable from 10 6 up to 10 6 km 2 a.What is the magnitude range? >4 (possible relationships among affected area and M still under study) b.How long is the time period? from 30 to few days before the EQ, co-seismic and after-seismic (until few days after the EQ) observed (and expected) c.Do you include a probability of an event during the forecast? only Low, High, Very High alert levels are given always in conjunction with other independent observations. Relative intensity of RETIRA index can offer (if time series are sufficiently long to justify a Gaussian-like distribution) an indication on the rarity of the anomalies. Space-time persistence, shapes, spatial relations with other static (e.g. fault system) or dynamic (e.g. seismicity) factors are also considered. d.Do you include a confidence level in the forecast? see before 3.Describe the process for making a forecast: a.Is it automatic or manual? Automatic for TIR anomalies generation. Partly automatic for the analysis of spurious effect and space-time persistence. b.What data are used? Thermal Infrared Radiances (10-12 micron) from different satellite sensors onboard geostationary platforms (like MSG, GOES, MTSAT, etc.) is today preferred. Passive MWs sensors (not yet available) on geostationary satellite should significantly improve negative effects due to cloud presence and distribution (spurious effects) 4.Do you have a preference for which earthquake data should be used to test your forecasts? No 1.Do you have a preferred testing method? Real-time release of (different level of) alerts in the framework of a PRE- EARTHQUAKES like collaboration. 2.What physical hypotheses about earthquake predictability have motivated your research? Like all physical processes earthquakes (and their preparation phases) can be studied, modeled and then predicted (as it is already done at least on the long terms). No scientific proofs exists demonstrating an intrinsic EQ unpredictability. Main problem is, presently the accuracy of predictions and the poorness of the observation systems.. Forecast Summary Questions TIR anomalies by RST approach and RETIRA index (Tramutoli et al., 2005)

33 33 RAT/RST people Thanks


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