Data Assimilation Scientist: 2DEnVar for Land Temp in NWP

Meteo France; Toulouse; Hybrid; EUR 48,000 - 60,000; Full time

Benefits offered by this job

Remote work 1 day/week

Job summary

Météo-France is seeking a qualified researcher to join the Observations team within GMAP at Toulouse, focusing on advanced data assimilation for numerical weather prediction. The role involves integrating satellite and surface observations into the ARPEGE model and developing ensemble variational techniques to improve forecast skill.

The successful candidate will hold a Master’s or PhD, have experience in data assimilation, and be proficient in Fortran/C++/Python.

Qualifications

• Master's degree or PhD in a relevant field.
• Experience with data assimilation is required.
• Proficiency in scientific programming languages (Fortran/C++/Python).

Responsibilities

• Develop and implement data assimilation for ARPEGE using 2DEnVar in a GMAP context.
• Ingest and assimilate diverse observations from satellites and ground systems.
• Evaluate results and perform sensitivity analyses to improve forecasts.
• Prepare reports and contribute to scientific publications for CHERRI.

Skills

Autonomy

Teamwork

Analytical abilities

Rigour

English proficiency

Education

Master's degree or Doctorate

Tools

Fortran

C++

Python

Job description

Météo-France is seeking a qualified researcher to join the Observations team within GMAP at Toulouse, focusing on advanced data assimilation for numerical weather prediction. The role involves integrating satellite and surface observations into the ARPEGE model and developing ensemble variational techniques to improve forecast skill.

The successful candidate will hold a Master’s or PhD, have experience in data assimilation, and be proficient in Fortran/C++/Python.