Logonna-Daoulas (France)

17-22 sept. 2012

Time-series analysis in

Marine science and applications for industry

I. PuillatIfremer/RDTipuillat@ifremer.fr

Time series analysis in Marine Sciences:

a challenge at the crossroads ofmarine observatories’ data

EMSO meeting, Roma, 12-14 nov. 2013

ContextObservatories and big data: the ¿expected? challenge

1D: Eulerian time series: moorings, model runs, repeat transects.

2D: Satellite Images, photos, videos, …

and lagrangian series: ex: floats, gliders

physical oceanography, bio-geochemistry, ecology, geophysics, offshore industry, acoustics, seismology …

Yearly number of data locations recorded by Coriolisdata system. A data location

is a measurement point defined by latitude, longitude,

date and time, but can include several depths

More and more marine data are safely archived

Forecasts:- Neptune Canada: 60.1012 bytes per year

(https://marinemetadata.org/news/neptunenature)- OOI: 3.1015 bytes per year)- Satellites ex:CERSAT (Laboratory of Oceanography From Space in

IFREMER); 100.1012 bytes per year1 sentinel sat: 1015 bytes per year each sat…

Marine data are going into the CLOUD! But…it is not only an IT problem

We need marine expert scientists to analyse and interpret the data

ContextObservatories and big data: the ¿expected? challenge

QUESTION: how to analyse a so big data flow? What capabilities?

?

Need of common tools, based on robust

mathematical methods,and high level knowledge

(training!!!)

How to fill in gappy records?How to quantify and analyse the

variability? How to interpret extreme values?

The best methods according to the scientific questions and mathematical

context?

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Training and international conference the 17-21 sept. 2012 near Brest

2-day training part:• Introductory course on time-series analysis and applications (J.M. Boucher, Telecom Bretagne)• Temporal eigenfunction methods for multiscale analysis of community contributions in coastal ecosystems composition and other multivariate data (P. Legendre, Montreal univ.)• Spectral analysis, soundscape description, application to the observation of benthic, climatic and anthropogenic (C. Gervaise and L. di Iorio, GIPSAand ENSTA Bretagne)• Detection, spectrogram analysis applied to marine mammal detection content (C. Gervaise and L. di Iorio, GIPSAand ENSTA Bretagne)• Extreme value theory in environmental sciences (Ph. Naveau, CNRS/LSCE)

« Time series analysis in marine science and applications for industry »

Training and international conference the 17-21 sept. 2012 near Brest

• 3-day conference part: 27 presentations for 4 sessions• Low to high frequency signals in oceanography• Geosciences and seismic monitoring• Marine ecology from coastal to deep-sea ecosystems and

acoustic monitoring• Applications for industry

• Round tables discussions: needs and next steps• ~ 100 participants from 54 institutions• ~ 24 countries• ~ 30 speakers• 36 posters

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Main outcomes

• Proceedings, movie, slideshttp://www.europolemer.eu/time series-analysis.phpand soon on http://wwz.ifremer.fr/rd_technologiques/Projets/Time-series-analysis

Available in the room

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Main outcomes

• A special edition in Journal of Marine Systems: « Times-series analysis at the crossroads of Marine Sciences» in press, 12 articles

Baptista, V., Leitão, F. Commercial catch rates of the clam Spisula solidareflect local environmental coastal conditions.Doya, C., Aguzzi, J., Pardo, M., Matabos, M., Company, J.B., Costa, C., Mihaly, S., Canals, M. Diel behavioral rhythms in sablefish (Anoplopomafimbria) and other benthic species, as recorded by the Deep-sea cabled observatories in Barkley canyon (NEPTUNE-Canada). Dragon, A.-C., Houssais, M.-N., Herbaut, C., Charrassin, J.-B. A note on the intraseasonal variability in an Antarctic polynia: Prior to and after the Mertz Glacier calving. Ewans, K., Jonathan, P. Evaluating environmental joint extremes for the offshore industry using the conditional extremes model.Huang, Y., Schmitt, F.G. Time dependent intrinsic correlation analysis of temperature and dissolved oxygen time series using empirical mode decomposition.

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Main outcomes

• A special edition in Journal of Marine Systems: « Times-series analysis at the crossroads of Marine Sciences» in press, 12 articles

Lorentzen, T. Statistical analysis of temperature data sampled at station-m in the Norwegian sea.Matabos, M., Bui, A.O.V., Mihály, S., Aguzzi, J., Juniper, S.K., Ajayamohan, R.S., 2013. High-frequency study of epibenthic megafaunal community dynamics in Barkley Canyon: A multi-disciplinary approach using the NEPTUNE Canada network.Monna, S., Falcone, G., Beranzoli, L., Chierici, F., Cianchini, G., De Caro, M., De Santis, A., Embriaco, D., Frugoni, F., Marinaro, G., Montuori, C., Pignagnoli, L., Qamili, E., Sgroi, T., Favali, P., 2013. Underwater geophysical monitoring for European Multidisciplinary Seafloor and water column Observatories.Olagnon, M., Kpogo-Nuwoklo, K.A., Guédé, Z., 2013. Statistical processing of West Africa wave directional spectra time-series into a climatology of swell events.

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Main outcomes

• A special edition in Journal of Marine Systems: « Times-series analysis at the crossroads of Marine Sciences» in press, 12 articles

Podgórski, K., Rychlik, I., 2013. A model of significant wave height for reliability assessment of a ship.Puillat, I., Prévosto M., Mercier, H., Thomas, S., 2013. Time series analysis of marine data: A key knowledge at the crossroads of marine sciences.van der Schaar, M., Ainslie, M.A., Robinson, S.P., Prior, M.K., André, M., 2013. Changes in 63 Hz third-octave band sound levels over 42 months recorded at four deep-ocean observatories.

• Movie: to watch here!!!

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Main conclusions: Printed version available in the room!!

Amongst a set of key-actions to be considered: The most suitable methods addressing specific scientific questions

should be determined. Robustness of each method, more specifically regarding data

characteristics needs to be addressed Regular basis for meetings is needed with a strong interest in organizing

summer schools or intense short courses applying numerical methods to actual data.

A handbook dedicated to time series analysis in marine science is needed to address the robustness of methods.

Need to promote mobility and training, and to set up dissemination tools.

Give the possibility to welcome participants with their own data sets to work them during several days.

First step toward a solution: let’s share the question!

« Time series analysis in marine science and applications for industry »

Main conclusions

• Improve links to industries:- Transition of sensors from academic labs to non-expert users is really

difficult: can industry help with this?

- Industry has lots of data and expertise, but does not have a strongmandate or ressources to put the work into sharing it, even if it's notproprietary, how to encourage this?

meeting platforms, involving industry, small companies (some of themissued from research labs), and research institutes are needed.

RecommendationRecommendation: to organize a conference of similar type to performscientific analysis of data made accessible by the industry by severalmethods and disciplinary approaches.

First step toward a solution: let’s share the question!

Next steps: what’s in the tube? What’s to discuss?

Possible targetMethod sharing: handbook + demonstration software

and training workshops:With an industrial as coleader in the organisation?

2 post-doc positions in Ifremer• Post-doc : application of extreme value theory to the design of

offshore and coastal structures, to prevent from floodingevents…

• Post-doc: characterisation of signal contents: variability time scales, correlations etc. Gaps filling methods.

Framework for upcoming projects to discuss• H2020• National projects• ESONET-Vi ... What’s that?????????????????

•How to?ESONET-Vi : a possible virtual institute for

observatories

Links with ESONET-Vi

How to drive science R&D in a sustained entity & consortium?

Needs• Focus on networked activitites• A recognised consortium with

ability to develop the networks• Capability to fund joint

activities (training, conference, doctoral network)

Example of the Time Seriesconference

• A common scientific topic• Large audience, potential

for a large consortium• 6 main funding sources for

training and conference

•EMSO consortium: the infrastructure providers, 1 representinginstitution PER involved European COUNTRY

•ESONET-Vi consortium: the community of observatoriesusers: scientists, stakeholders, companies. Larger consortium,open. An exchange platform to manage science, to train scientists,etc.

Open sea and coastal observatories : Long term and high frequency time series

Time series analysis can be a common scientific topic of ESONET-Vi

How to?

Links with ESONET-Vi

•How to?ESONET-Vi can be an AISBL: international association on Belgium law, a legal institution that can apply to calls and independently manage funds.

• Why it is a good solution?- the heavy example of conference organisation by way of a

traditional and institutional management: Applications to 4 call for proposals + institutions funds= 78k€ Management of 6 fundings sources, in both Ifremer and

University

complex management involving 2 institutions, several management and administration levels, difficulties to get the funds opened by the institution (because not forecasted in the yearly budget)

- the right solution: AISBL an independent management!!!!

Links with ESONET-Vi

• Observatory products are Time Series-type data

• Needs of the community: data products such as partly analysedtime series

o Need to have time series archived in data centers with capabilities to deliver first level analysed time series: data producto Need of a legal framework to disseminate knowledge, organisetraining workshops and conferences, stay in the loop, …

• Industry involvement is requested

Thank you.

Conclusions

Example of MyOcean TAC and observatories?Moorings…

About 850 mooring points provide data to the in situ Thematic Assembly

Centre (in situ TAC) of MyOCEAN between 2009 and 2012 around the word. Here are only the European

mooring points

Marine observatories: the Real time kingdom

Real time and technology of observatories

ContextObservatories and big data: the ¿expected? challenge

And…. We have to face the"The Fourth Paradigm: Data-Intensive Scientific Discovery" (Hey et al., 2009))

????

ContextObservatories and big data: the ¿expected? challenge

Yearly number of data locations recorded by Coriolis data system. A data location is a measurement point defined by latitude, longitude,

date and time, but can include several depths.

History in data acquisition and archiving

ContextObservatories and big data: the ¿expected? challenge

More and more marine data are safely archived