USE CASES IN SEISMOLOGY. Alberto Michelini INGV

Transcription

1 USE CASES IN SEISMOLOGY Alberto Michelini INGV

2 PROJECTS NERA (Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation) VERCE (Virtual Earthquake and seismology Research Community in Europe e-science environment ) EPOS (European Plate Observing System) EUDAT (European Data)

3 PROJECTS NERA (Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation) Tools for Real Time seismology and Data Mining Web Services development VERCE (Virtual Earthquake and seismology Research Community in Europe e-science environment ) Architecture and framework for data- and cpu-intensive seismological applications EPOS (European Plate Observing System) e-science infrastructure design EUDAT (European Data) Development of core services for e-infrastructures

4 USE CASES Real-Time & Rapid Data analysis Platform for Data- and CPUintensive applications Seismological Solid Earth e-infrastructure Solid Earth Sciences Core Services for e- infrastructures Data IT

5 PROJECTS OVERLAP

6 PROJECTS OVERLAP

7 PROJECTS OVERLAP

8 PROJECTS OVERLAP

9 NERA - JRA2 - Why?

10 NERA - JRA2 - Why? When disastrous earthquakes occur, the population expects immediate knowledge of what goes on

11 NERA - JRA2 - Why? When disastrous earthquakes occur, the population expects immediate knowledge of what goes on News dissemination (e.g., social networks, twitter,...) is now so fast that any natural hazards monitoring system must cope with it

12 NERA - JRA2 - Why? When disastrous earthquakes occur, the population expects immediate knowledge of what goes on News dissemination (e.g., social networks, twitter,...) is now so fast that any natural hazards monitoring system must cope with it

13 NERA - JRA2 - Why? When disastrous earthquakes occur, the population expects immediate knowledge of what goes on News dissemination (e.g., social networks, twitter,...) is now so fast that any natural hazards monitoring system must cope with it Modern seismology requires very fast, accurate determinations of the main characteristics of a given earthquake and of its impact

14 NERA - JRA2 - Why? When disastrous earthquakes occur, the population expects immediate knowledge of what goes on News dissemination (e.g., social networks, twitter,...) is now so fast that any natural hazards monitoring system must cope with it Modern seismology requires very fast, accurate determinations of the main characteristics of a given earthquake and of its impact For scientists exposed to media coverage and working with civil protection authorities, it is essential to have prompt and accurate descriptions of what has occurred (and is occurring!)

15 JRA2 - Progressive information Seismic monitoring centres should respond in a transparent and progressive manner to a developing crisis, with updated and more refined information becoming available progressively (i.e., from fast but less reliable information based on an existing subset of data, to more sophisticated analysis based on a more complete dataset).

16 Progressive)informa.on)

17 Progressive)informa.on)

18 Real-Time & Rapid Data analysis Real-Time Stream Data Off-line Data

19 Seismologist s+desires+ (guidelines*for*designing*of*a*general*purpose*tool*box* for*off4line*and*rt*stream*data)* Transparent*download*of*data*according*to geographical+sta.on+selec.on.me+window SNCL QC+ Obtain*all*data*required*by*Apps*regardless(of*the*data*center* and*ready4to4use exact+start/end+(#samples)+.mes data+filtering Provide*data*input*to*Apps*in*different*standard*data*formats SAC,+MSEED,+GSE,+... Support*real4Cme*SL*data*streams Simple*command*line*request Script*procedure*easy*to*implement(on*user s*computer*

20 Tool)Box)General)scheme Output App*Results*to*Output*Box App 1 App 2... App N Data*to*ApplicaCons*Box Data

21 Aims: NERA%&%Use%cases Tools%for%Real+Time%seismology,%data%quality%checking%and%mining Use%cases: VS+EEW!(Virtual!Seismologist!Earthquake!Early!Warning!7!RT#data#stream) SCARDEC!(Moment!tensor!&!source!<me!func<on!7!Off-line#data) WaveLoc!(real7<me!loca<on!from!con<nuous!waveform!stream!data!7!RT#data#stream) Real7<me!mBc!(magnitude!calcula<on!7!RT#data#stream) Time%Domain%Moment%Tensor!!(TDMT!7!Off-line#data) MW+FMNEAR!(near7field!Magnitude!calcula<on!7!Off-line#data) EARLY+EST!(EArthquake!Rapid!Loca<on!sYstem!with!ES<ma<on!of!Tsunamigenesis!7!RT#data# stream)! What%has%been%done: They!all!require!interface!with!data!either!offline!or!in!streaming Prototype!tool7box!for!off7line!seamless!data!download!(in!Python!using!ObsPy) Real7<me!stream!analysis!of!miniseed!data!streams!coming!from!acquired!from!seedlink!(Python!using! ObsPy!and!addi<onal!development)!

22 VERCE seismological)research Make&it&feasible&scien/fic&calcula/ons&otherwise& impossible&on&standard&desktops,&laptops&or&small& clusters :&large&data&volumes&(e.g.,&data&mining) :&very&intensive&cpu&applica/ons&(e.g.,&forward&modelling& and&inversion)

23 NA2%&%Objec;ves Select&the&exis/ng&pilot&data:intensive&applica/ons&and&design& sound&use&case&scenarios Selec;on%Criteria scien;fic%impact!(i.e.,!top!level!research!since!verce!wants!to!drive!a! new!paradigm!in!data!and!cpu!intensive!analysis!in!seismology) challenge!(i.e.,!only!through!verce!it!is!possible!to!address!the!problem) existence!of!a!well%defined,%iden;fiable%group%of%people!working!on!the! specific!use!case!and!seeking!results!!this!is!essen<al!for!con<nuous! feedback!between!seismologists!and!ict achievable!(it!must!be!complex!but!achievable!in!the!<me!span) gain%from%factorizing%the%procedure/code%into%modules!that!can!be!re7 used!to!build!other!applica<ons!(e.g.,!cross7correla<on,!back7projec<on,! filtering,!other!types!of!pre7processing,!...)

24 VERCE%Consor;um%s/w Analysis%of%very%large%data%volumes!for: Velocity!structure!and!monitoring!changes!(IMCASN!7!IPGP!+!ISTERRE) Rapid!high,!resolu<on!loca<on!of!large!data!volumes!of!seismic!data! acquired!in!an!azershock!sequence!(wavehrl!ingv!+!eost). Modeling Visco7elas<c!anisotropic!3D!wave!propaga<on!simula<on!at!regional!scales! (SENUM3D,!SPECFEM3D,!DG3D7SEIsSOL) TSUnami!impact!MAPS!in!near!real7<me!(TSUMAPS!7!INGV) Modeling%and%inversion High!resolu<on!imaging!based!on!3D!full!waveforms!inversion!(SES3D)! Non7linear!Inversion!for!Kinema<c!Earthquake!Source!(NIKES!7!INGV) Data%analysis Seismic!Data!eXplora<on!and!visualiza<on!tool!(RapidSeis!?!7!SDX!7!ULIV)

25 Seismological Data used Desiderata Services to users Until recently The target earthquake Extraction and Download of time and spatial data windows Recently and onward The whole continuous Access and Analysis of huge (TBs) data volumes Selection of data based on quality (metadata) Selection of data based on characteristic features (metadata) Basic operations on data (e.g., application of transfer function, dominant period,...) Creation of data objects with assigned unique identification of data and permanent access to

26 EUDAT Infrastructure)(CDI)

27 EUDAT Infrastructure)(CDI)

28 EUDAT Core Service Areas Community-oriented services Simple Data Acces and upload Long term preservation Shared workspaces Execution and workflow (data mining, etc.) Joint metadata and data visibility Core services are building blocks of EUDAT s Common Data Infrastructure mainly included on bottom layer of data services Enabling services (making use of existing services where possible Persistent identifier service (EPIC, DataCite) Federated AAI service Network Services Monitoring and accounting

29 Research Communities

30 First Service Cases Shortlist of 6 service/use cases identified Safe replication: Allow communities to safely replicate data to selected data centers for storage and do this in a robust, reliable and highly available way. Dynamic replication: Perform (HPC) computations on the replicated data. Move (part of) the safely replicated data to a workspace close to powerful machines and move the results back into the archives. AAI: A solution for a working AAI system in a federation scenario. Metadata: A joint metadata domain for all data that is stored by EUDAT data centers by harvesting metadata records for all data objects from the communities. Allow to have a catalogue to demonstrate what EUDAT stores, and to have a registry which can be used for automatic operations such as data mining. PID: a robust, highly available and effective PID system that can be used within the communities and by EUDAT. Research data store: A function that will help researchers mediated by the participating communities to upload and store data which is not part of the officially handled data sets of the community. 24

31 Metadata!&!EPOS:! the!glue!and!the!mean EPOS%WG7%has%elaborated%a%proposal%for%the%metadata%definiNon.% 1. A!simple! flat!metadata!standard!for!discovery;!(flat!metadata!means!it!is!a!single! record!with!agributes!rather!than!a!group!of!linked!records!each!with!agributes!and! with!rela<onships!between!the!records) 2. A!structured!(linked!en<ty)!standard!for!context!(rela<ng!the!dataset!to!provenance,! purpose,!environment!in!which!generated!etc); 3. Detailed!metadata!standards!for!each!kind!of!data!to!be!co7processed And!the!following%standards%seem!the!most!appropriate!to!support!such!model: 1. Discovery:!DC 2. Contextual:!CERIF!(Common!European!Research!Informa<on!Format,!hgp:// en.wikipedia.org/wiki/cerif) 3. Detailed:!Individual!standards!depending!on!type!of!dataset;!for!research!datasets!from! large7scale!facili<es!csmd!(e.g.,!hgp:// see!also!pandata,!hgp:// _Photon_and_Neutron_Data_Infrastructure),!for!geospa<al!datasets!INSPIRE!1!(hgp:// inspire.jrc.ec.europa.eu/,!hgp://en.wikipedia.org/wiki/inspire!as!in!envri).

32 Projects)links

33 END