Abstract

Environmental sciences have experienced a data deluge with the explosion in the amount of data produced by sensors and models that monitor, measure and forecast the Earth system. This exponential trend in data availability is expected to continue in the future thereby creating many new opportunities, needs and challenges. On the other hand, data science has emerged as a wide multidisciplinary dynamic which addresses challenges associated to large and complex data and encompasses diverse fields in applied mathematics and computer science.


Aim

The conference will gather researchers that have an expertise in one of the two areas (data science, environmental data) and some interest for the other. Its main goal is to explore the fruitful interplay between the two areas, and ultimately to help create new connections and collaborations between the scientific communities involved. Another objective is to propose some high level courses and practices at the interaction of these two areas.


Confirmed speakers

  • Marcelo Barreiro (Univ. Montevideo, Uruguay)
  • Dorit Hammerling (IMAGe-NCAR, USA)
  • Alexis Hannart (Ouranos, Canada)
  • Ibrahim Hoteit (KAUST, Saudi Arabia)
  • Erwan Le Pennec (Ecole Polytechnique, France)
  • Pierre-Yves Le Traon (MERCATOR, France)
  • Olivier Mestre (Météo-France, France)
  • Takemasa Miyoshi (RIKEN, Japan)
  • Douglas Nychka (IMAGe-NCAR, USA)
  • Thierry Penduff (IGE, France)
  • Eniko Szekely (CIMS-NYU, USA)
  • Christopher Wikle (Univ. Missouri, USA)

Schedule

The conference will be in two parts:

  • summer school (two days, 3-7 July) with high level courses and practices for PhD students, with possible travel fellowship
  • workshop (three days, 4-5-6 July) with invited speakers and selected presentations/posters based on abstract submissions

Themes

Diverse themes will be treated:

  • data acquisition and visualization
  • in situ monitoring, remote sensing data, numerical simulations
  • physical modeling (parameterizations and model selection)
  • data analysis (machine learning, statistical models and stochastic processes)
  • data assimilation (high dimensionality, error covariance estimation)
  • climate (detection/attribution, extremes)
  • etc...

A special focus will be given to oceanographic data and related problems. Other fields of interest related to environment like meteorology, climate, biogeochemistry, geographic information system, are also welcome.


Important dates

  • March 15, 2017: poster/talk abstracts due
  • March 15, 2017: travel support forms due
  • March 31, 2017: author notification
  • March 31, 2017: travel fellowship notification
  • July 3 & 7, 2017: summer school
  • July 4-5-6, 2017: workshop

Contact

Please contact pierre.tandeo@imt-atlantique.fr for more details.


Sponsors