Modelling of Weather-Forecast Data Processing Workflow

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Supervisor Dr. Julian Kunkel
Collaboration ECMWF

This work will be embedded in the ACES research group and conducted in tight collaboration with ECMWF.

If you are interested in this topic or similar topics, contact Dr. Julian Kunkel.

In the weather prediction workflow, sensor data from instruments like satellites is ingested into a data center where weather models derive various predictions that are finally processed to generate relevant products. The efficient execution of the workflow is important to minimize costs and time for generating a prediction. In this work, we collaborate with ECMWF to model their workflow and derive performance and cost models for alternative execution or running the workflow on alternative systems.

Firstly, the current workflow is documented together with its performance behavior. Secondly, a simplified performance model for the workflow execution on different systems is developed and implemented. Then, this model is validated on the current system/workflow. Finally, the execution of alternative workflows on various systems is explored to derive potential candidates.

While all skills needed to complete this project can be obtained during the time of the project, some skills are beneficial:

  • Programming languages: Python (intermediate level)
  • Knowledge about Weather Forecast domain

An MSc candidate is expected to bring soft skills (in decreasing order of importance):

  • Communication
  • Problem-Solving
  • Time management
  • Impressum
  • Privacy
  • research/open-theses/msc/modelling-processing-workflows.txt
  • Last modified: 2019-02-24 12:20
  • (external edit)