Earth Science VRC Monique Petitdidier 1 & Horst Schwichtenberg 2 - - PowerPoint PPT Presentation

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Earth Science VRC Monique Petitdidier 1 & Horst Schwichtenberg 2 - - PowerPoint PPT Presentation

Mar 25, 2023 237 likes •418 views

Universit de Versailles -Saint- Quentin en Yvelines Earth Science VRC Monique Petitdidier 1 & Horst Schwichtenberg 2 1- IPSL/LATMOS, CNRS,UVSQ, UPMC, Paris, France 2- SCAI/Fraunhofer, Sankt Augustin, Germany Earth Science Mosaic of

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SLIDE 1

Earth Science VRC

Monique Petitdidier1 & Horst Schwichtenberg2

1- IPSL/LATMOS, CNRS,UVSQ, UPMC, Paris, France 2- SCAI/Fraunhofer, Sankt Augustin, Germany

Université de Versailles -Saint- Quentin en Yvelines

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SLIDE 2

Earth Science

  • Mosaic of disciplines and actors (academia, industry,

national surveys, international organizations,….)…

  • Role: Research and answer societal questions

– Global approach of the earth-sun system

  • observations and models

– Industrial and Natural Risk assesment

  • Strong meteorological events (storms, hurricane…)
  • Flood, Earthquake, Tsunami, Pollution

– Prediction: Now casting of industrial and natural risk – Climate Change

  • Climatology i.e. trend of parameter variations like temperature,

precipitations….

  • Impact on agriculture, and various other domains

– Research of new energy, and reservoir – New Developments

  • New instruments and infrastructures

– Education from pupils to all publics

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SLIDE 3

Virtual ES Grid Community

OGC INSPIRE GMES Civil Protection GEOSS Meteorology

Greece: AUTH, IASA, NOA; SRI (Ukraine), GCRAS (Russia)

Climate - GRelC

CMCC (Italy), IPSL (France), Univ Cantabria (Spain), SCAI (Germany)

Flood

EMA (France), IISAS (Slovakia), SRI (Ukraine)

Flood map for Normanton area, Queensland, Australia derived from RADARSAT-2 14-17 Feb 2009 (SRI)

SEIS Geosciences- Geocluster

CGGVeritas (France), DSI-IRD, Geoazur, IPGP, IPGS, ISTEP, Sisyphe, UBO

Climate - El Niño

  • Univ. Cantabria – EELA2

IEEE CODATA WDCS ERCIM Biodiversity

BRGM (France), Footways(France),JKI (Germany) Scenarios climatological

Hydrology

CRS4 (Italy), Univ. Genève, Univ. Neuchâtel,INHGA ( Romania), Institute for Water Resources "Jaroslav Cerni", Belgrade and CSASA at University of Kragujevac, Serbia

Geospatial platform

IMAA(Italy), INFN(Italy), EMA (France), IMHO(Portugal)

ds ds CYCLOPS Platform CYCLOPS Infrastructure CYCLOPS Infrastructure Environmental Monitoring Resource Infrastructure Processing Systems Infrastructure Data Systems GRID Platform (EGEE) Sensor systems Security Infrastructure Security Infrastructure Interoperability Platform Interoperability Platform Business logic Services Presentation and Fruition Services Real Time and Near Real Time Applications for Civil Protection (Data integration, high-performance computing and distributed environment for simulations) Spatial Data Infrastructure Services Spatial Data Infrastructure Services Advanced Grid Services Geospatial Resources Services Forecasting seawater intrusion in a coastal aquifer From J. Kerrou Univ. Neuchâtel

UN-SPIDER ESA NASA EGU Pollution

  • a. Basic scenario
  • b. 50% r eduction
  • f NO
x

IPP-BAS (Bulgaria), IASA (Greece), EnvVO-SEEGRID

IPGP- E.Clévédé

Seismology

AUTH (Greece), IPGP (France), AUTH (Greece), Tubitak Ulakbim (Turkey), Univ. patras (Greece), INFP (Romania)

From
  • E. Clévédé -
IPGP

G-OWS INSPIRE Civil Protection CODATA ERCIM NASA OGC SEIS IEEE ESA GMES GEOSS WDC EGU

From IASA
  • EGEE, SEEGRid, linked with

EELA, EUASIA, EUMEDGrid….. 20-25 European or associated Countries Various disciplines

  • Distributed expertise
  • Synergy among various and

technical ES disciplines and among various domains

  • Importance of e-collaboration
  • Sharing resources
  • Sharing expertise and

experience

  • Knowledge transfer
  • Sharing data and results
  • Decrease technology divide
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SLIDE 4

e-collaboration issues

  • Grid session in European Geosciences Union since 2008

Special issues

  • (1) Grid in Earth Sciences

– Earth Science Informatics 2009-2010-13 papers – Eds:M. Petitdidier, R. Cossu, P. Fox, P. Mazzetti, H. Schwichtenberg, W. Som de Cerff

  • (2) Development of virtual organizations, applications and services

for earth science on grid e-infrastructure – Earth Science informatics 2010 -11 papers – Eds: C. Özturan, V. Kotroni, E. Atanassov

  • Renard et al., Grid computing for Earth Sciences, EoS, 7 April 2009.
  • Lecca et al., Grid technology for hydrological applications (5),

accepted for publication in Journal of Hydrology, 2011 There are also knowledge and application transfer, PhDs, publications

  • f scientific and technical papers…..
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SLIDE 5

ES in GISELA & Chain

GISELA

  • Climate application – Univ. of Cantabria, A. Cofiño
  • Seismology applications. IPGP
  • Possibility to contact members of the VRC to know if they have

contacts

  • Y. Font (GeoAzur) will submit a paper:

– A priori 3D geo-realistic velocity model and MAXI technique to improve earthquake location in subduction zone (Ecuador)

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SLIDE 6

ES - CHAIN -Africa

  • Egypt: Call IRD&STDF submisson of the proposal « GPS Network

for Environment and Space Science » with a part of data infrastructure and computing- real time elaborated data distribution. – Not funded this year due to the situation

  • Organisation of a day on HPC and Grid technology during a school
  • n space weather with local and foreign people

– University Helwan, Egypt- September 2010 – University of Kinshasa, RDC- september 2011

  • Participation (MP) to eGY-Africa: for a better cyberinfrastructure
  • Grid with Globus installed in RDC and RC

Compute resources need users …. In many African countries there is no user community even if some individual scientists exist, then no needs First step: Create or consolidate user community (ICT and others)

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SLIDE 7

Students & researchers in Africa

Universities in Africa

Number of researchers Expenses for research and development

~2% In Europe and USA

  • G. Boetsch, H. Charton, E. Ficquet, V. Rivasseau,

Africa, a continent with thousand faces, (in French) CNRS Journal, 244, may 2010.

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SLIDE 8

ES Requirements

  • Data intensive computation
  • Access to external database and data infrastructure from

the Grid – Authentification and Authorization different from EGI

  • Earth System Grid (Climate), Genesi (satellite

data)….

– Transfer time

  • Real-time execution jobs

– Weather prediction – Natural risk survey and warning

  • MPI jobs for simulation
  • Parametric jobs
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SLIDE 9

Earth Observation by Satellite: Atmosphere

  • Inter-Comparaison of Parasol data with

Lidar data aboard Calipso and Modis algorithm validation

  • Full resolution processing of the Parasol data
  • n EGEE by F. Ducos (LOA, Univ. Lille,

France)

  • Support from D. Weissenbach (IPGP, France)
  • Input: 12,4TB Output: 1,7TB
  • 3-4 months instead of ~18 months

Infrared Atmospheric Sounding Interferometer

Studies of photochemical pollution processes in the lower and medium- range troposphere.

  • Analyse of twice-a-day data on EGEE by
  • M. Eremenko (IPSL/ LISA -France)
  • Support from D. Weissenbach
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SLIDE 10

Climate simulation with Earth-System-Grid Climate data

Goal: Testbed to connect ESG to EGI for parametric and regional climate applications

  • First application:

– multi-parameter MPI simulation about precipitation – ESG data retrieved by simple approach

  • Perspectives:

–Interoperation between ESG and EGI security mechanisms (under discussion) –Data policy –Various simple to complex scenarios –Interface for end-users Climate data ESG EGI- UI CE SE X509 Proxy Cert, VOMS Compute Nodes OpenID,Role, private Cert

Ask for Data transfer Redirect Transfer

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SLIDE 11

HYDROLOGY

Survey/ Water Management GANGA Independent Jobs (Monte Carlo) Local SWAT Hydrology Catchment Water Management No Distributed Job (MPI), + Parametric analysis Local LizzaPAKP Subsurface hydrology Water Resources management GRIDA3 AQUAGRID Portal + Web-GIS Independent Jobs (Monte Carlo) Local and Distributed CODESA3D Subsurface hydrology Real time Warning service Portal + Web-GIS Independent Jobs (scenario analysis) Local data + prediction

  • utputs

ALTHAIR Flash flood Real time Portal + Web- GIS Distributed Jobs (OpenMP) Satellite data NO Flood Demonstration Portal Distributed Job (MPI) meteorology Prevision

  • utputs

Multi-model Flood Goal Web interface Parallel system Data Model Domain

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SLIDE 12
  • Delivered within 24 h after data

acquisition

  • Satellite synthetic-a perture radar

(SAR) instruments

– ERS-2/SAR – ENVISAT/ASAR – RADARSAT-1/2

  • Ground validation

– Chinese territory on river Huaihe 2008 => 95% match

  • f satellite observations

against field measurements

  • Output format

– OGC-compatible: WMS, WCS, KML etc

Processing workflow

Rapid flood mapping from SAR satellite imagery in Grids

Space Research Institute, Kiev, Ukrainia

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SLIDE 13

India and Nepal, river Koshi, 2008 Zambia, river Zambezi, 2009 Australia, river Norman, 2009 China, river Huaihe, 2007 Mozambique, river Zambezi, 2008 Vietnam, 2008

Rapid flood mapping from SAR satellite imagery in Grids (cont.)

End-users: UN-SPIDER - UN Platform for Space-based Information for Disaster Management and Emergency Response

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SLIDE 14

gCSMT: Grid earthquake CMT determination

  • Operational platform in production in the French data centre

GEOSCOPE: E. Clévédé (IPGP), G. Patau (IPGP)

  • Embarrassingly parallel inversion with parameter space exploration
  • Synthetic seismograms database dynamically built and

stored on the Grid (GRelC data service software)

  • Support: D. Weissenbach (IPGP)
  • Operating since 2004, and continuous developments since
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SLIDE 15

15

Seismology Applications

GEOCLUSTER GEOSCOPE SENU3D software platform for seismic data processing, imaging and reservoir characterization 30 years of continuous records (~30 stations, ~2 TB) Data curation: Daily noise average analysis of the continuous seismic records archived in the Geoscope Data centers

  • E. Stutzman (IPGP)

Support: D. Weissenbach

3D seismic waves Propagation in complex geological media on a local scale and ground motion prediction MPI job

  • E. Delavaud & J.P.

Vilotte -IPGP Support: G. Moguilny

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SLIDE 16

MSACM Grid-mode: Structure of the Air Quality forecasting system

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SLIDE 17

How e-collaboration, a solution

Face-to-Face meeting

Virtual teams: ES and ICT people Discovery and relationship building

  • Information flow
  • Face to face meetings
  • Phone or video conference
  • Web site – forum
  • e-mail

Collaboration management support for

  • Sharing knowledge, best pratices
  • Collaborative work
  • Requirements
  • Strategy
  • Outputs: help to access data in different

compute architecture and port applications

COST ACTION «European Network for improving scientific and technical e- collaboration in Earth System Sciences” submitted 25 March in ESSEM – answer for a full proposal on mid-may Horst Telco!