This was the first meetup of SciML @ DMI. Below are notes on what we discussed. Feel free to make a pull-request to edit any inaccuracies - Leif Denby.

What’s new in ML?

What do we want SciML DMI to be?

mindmap
  SciML DMI
    getting practal advise on using "pascal"
    would like to learn about ML, have money
    brainstorm practical examples, feedback
    keep up to date with recent developments 
    pioneer new things at DMI
    have fun!
    go through interesting papers, show the front page
    tie in new people with ML experience, support network
    learn techniques being applied in group
    best practice for using ML in operations?
    existing projects, what ML is being used?
      DEODE
      DestineE
      emulation PhD student, innovation fund, Phillip Arestrup DTU
      data quality analysis for Danish APA
      sattellite data, sea ice mapping in radar images
      flood mapping, by external partners
      Anna, densification of shallow ice cores, DTU Space
    physical foundation of machine learning?
    use of ML at data assimilation?

GPUs?

  • platform name, hardware available, cost, how to get access

  • pascal.dmi.dk, 1x A100 80GB (paid for by IT during ASIP project, Tore Wulf) only available to ASIP group (Ask Tore Wulf twu@dmi.dk, Martin Koster mak@dmi.dk), cost ~ 100,000DKK
    • Tore Wulf: research group is pushing for more copies of pascal.dmi.dk
  • ATOS @ ECMWF: should be easy to get access (KAH)
  • European Weather Cloud
  • LUMI
  • EuroHPC: nvidia
  • upcoming project needs:
    • Ruth: emulate regional climate model over two ice sheets - do we need more GPUs?
    • Fabrizio (EUMETNET project)
  • no GPU UWC-W

Research projects

  • ASIP (Copernicus): sea ice mapping in radar images, convolutional neural networks,
  • ML (EumetSat fellowship): extending assimilation of sat microwave obs over seaice, fab@dmi.dk
  • PRECISE: emulate regional climate (surface mass balance model) over ice-sheets, collab with Northumberland (sea-ice caverns) - rum@dmi.dk
  • RopeWalk: digitising hand-written records of observations in ship-data tables - mas@dmi.dk
  • ACCORD: use of machine learning in LAM NWP (data assimulation, ensemble forecasting and everything you can think of) - Henrik
  • PhD:
    • TODO

Background