Our team and mission

The Earth and Mission Science Division, of the Climate Action, Sustainability and Science Department, Earth Observation Programmes Directorate, is based at the European Space Research and Technology Centre. The Earth and Mission Science Division provides the creative vision for innovation and new discoveries in Earth system science, using Earth Observation (EO) in close cooperation with the scientific community.

The Earth and Mission Science Division team:

Bridges science and technology by translating ideas and concepts into technical reality and scientific success. It does this by defining, consolidating and managing scientific mission requirements throughout all phases of a mission, and by measuring the maturity of the resulting mission concept.
Manages scientific research-based studies, providing the scientific foundation for mission concepts and approval, supports the successful development of space and ground segment, in-orbit satellite commissioning and in-orbit scientific achievements.
Undertakes airborne, marine and terrestrial campaigns contributing the development of new technologies, mission feasibility assessments, calibration/validation and application development.

You will work in the Earth and Mission Science Division, whose role is to provide broad mission science support throughout the preparation and development of Earth Observation missions. Your activities will contribute to and benefit from a diverse and international team of scientists working across a variety of Earth Science disciplines.

Field(s) of activity for the internshipTopic of the internship: Earth Explorer 11 WIVERN End-to-End Simulation

WIVERN is ESA’s 11th Earth Explorer Mission. It will provide the first-ever wind measurements within clouds, along with simultaneous observations of cloud and precipitation properties. These data products are expected to make a major contribution to improving weather forecasting.Physical model studies have already shown that WIVERN can significantly reduce numerical weather forecast errors. With artificial intelligence rapidly advancing in the field of forecasting, WIVERN data are also expected to play an important role in this domain. One key objectives is to assess the contribution of WIVERN data to reducing forecast errors using AI methods. To achieve this, we need to generate simulated WIVERN data for implementation in an AI-based forecasting environment.

Key Responsibilities:

identify and suggest improvements to existing simulation tools, both in terms of methodology and user-friendliness;
run simulations to generate the required WIVERN data products for use in AI-based forecasting experiments;
apply performance evaluations to construct, assess, and quantify science data (Level-2) error budgets.