Stage - Analyse Du Changement Climatique

Job Description

It takes the brightest minds to be a technology leader. It takes imagination to create green energy for the generations to come. At Siemens Gamesa we make real what matters, join our global team.

The global wind energy sector, both onshore and offshore, is experiencing rapid growth and is playing a key role in the energy transition. However, long-term shifts in wind resource patterns due to climate change are becoming an increasingly important concern. Siemens Gamesa Renewable Energy (SGRE), a Siemens Energy business unit and world leader in wind turbine manufacturing and maintenance, is launching a collaboration with the Dynamic Meteorology Laboratory (LMD) at École Polytechnique to address this issue.

The goal of this internship is to analyze SCADA wind data — including 10-minute average wind speed, wind direction, and turbulence intensity — collected from thousands of SGRE turbines located on all five continents over the past 20+ years. This work will assess long-term trends and interannual variability of wind characteristics and investigate their links with large-scale climate dynamics, such as ENSO (El Niño / La Niña), the North Atlantic Oscillation (NAO), and others.

This project sits at the intersection of industrial data science, fluid dynamics, and climate research, and is co-supervised by experts at SGRE and researchers at LMD.

Internship Objectives

• Process, structure, and analyze large-scale SCADA datasets focused on wind characteristics.
• Identify long-term trends in wind speed, direction, and turbulence intensity across different regions and time scales (seasonal, annual, decadal).
• Detect and characterize interannual to decadal variability, and assess links with known climate modes (ENSO, NAO, MJO, etc.).
• Compare local SCADA-derived wind data with outputs from reanalysis datasets and climate model simulations.
• Investigate the potential impacts of extreme climate events (e.g., strong El Niño years) on wind patterns in specific regions.
• Apply statistical and data science tools to reveal meaningful patterns and build robust visualizations.
• Contribute to the understanding of how wind energy resource is evolving in a changing climate.

Candidate Profile

• Final-year Master's student or engineering school student (M2 or equivalent).
• Background in fluid mechanics, climate science, data science, energy systems, or related fields.
• Strong skills in statistics, data analysis, and time series processing.
• Proficiency in Python and MATLAB (mandatory).
• Solid knowledge of atmospheric dynamics, climate variability, and climate indices (ENSO, NAO, etc.).
• Interest in wind energy, renewable resources, and climate impacts.
• Scientific curiosity, critical thinking, and ability to work independently.
• Comfortable working in an interdisciplinary and international environment.

Supervision & Work Environment

• Joint supervision by:
  • SGRE engineering and data teams (based in Paris La Défense)
  • Researchers from the Dynamic Meteorology Laboratory (LMD) at École Polytechnique (Palaiseau)
• Access to a unique global-scale SCADA database
• Opportunity to work across the industry-research interface
• Possibility of scientific publication or continuation into a CIFRE PhD

Working Languages

French and English (documentation and communication in both)