Research Engineer (M/F) on the tracking of meteorological objects in models and satellite observations

Job Description

Missions

The Laboratory of Dynamic Meteorology (LMD) is seeking a Research Engineer on a fixed-term contract to detect and track meteorological features in model data and satellite observations. The Lagrangian tracking of coherent structures is of major importance for understanding the spatiotemporal organization of mesoscale convection, which directly affects the energy balance and precipitation intensity. A successful example is the tracking of thunderstorm systems using the TOOCAN algorithm (Fiolleau et al. 2013), which is applicable to both satellite observations (Fiolleau et al. 2020) and kilometer-scale climate models (Feng et al. 2023). The challenge is to generalize this approach for the identification and tracking of thermals, cold pools, precipitation features, updrafts, subsidence, and coherent clusters of larger-scale thunderstorm systems.

Activity

The work aims at generalizing existing methods for detecting and tracking coherent atmospheric structures and implementing them on HPC systems.

Details of activities:
- Extending existing methods for detecting cold pools (Rochetin et al. 2021) to enable temporal tracking using watershed-type methods (in kilometer-resolution Meso-NH simulations);
- Application of detection and tracking methods for deep convective updrafts and subsidence, convective precipitation zones (3D structures), cloud anvil structures, and convective aggregates (2D structures) in kilometer-resolution Meso-NH simulations;
- Application of methods for detecting coherent boundary layer structures in hectometer-scale Meso-NH simulations (Brient et al. 2019), and extension of the method to Lagrangian tracking of these structures;
- Adapting the new method for detecting and tracking cold pools for operational use over large domains: dividing the domain into blocks, labeling structures, and unifying labels across blocks to enable parallel computation on large volumes of data. Prototyping in DYAMOND Summer's gSAM simulations or simulations from the ORCESTRA observation campaign (Fiévet et al. 2026);
- Creation of a multi-year database for convective aggregates (Fildier et Saba, 2026), precipitation zones (Bauer et al. 2025), and cold pools (Rochetin et al. 2021) in kilometer-resolution global model data (DYAMOND Summer, Stevens et al. (2019); DYAMOND Winter, Klocke et al. (2020), and NetxGEMS) and satellite observations (infrared measurements from geostationary satellites and IMERG combined products).

Your Profil

Skills

- Engineering school or master's-level university degree in Environmental and Space Sciences, with training in atmospheric physics
- Solid experience in scientific computing
- Excellent knowledge of scientific programming (an interpreted language such as Python, a compiled language such as C++)
- Knowledge of the Linux environment
- Experience working with large datasets and statistical methods
- Strong written and oral communication skills in French and English
- Ability to work independently and take initiative, strong interpersonal skills, and the ability to work effectively in a team

Your Work Environment

The LMD's EMC3 team (Climate and Climate Change Research and Modeling) plays a leading role in the analysis of convective processes (cloud formation and spatial organization) associated with small-scale structures (thermals, thunderstorm cells, mesoscale circulations, etc.) that can be simulated by kilometer- or hectometer-scale models. These research topics are becoming increasingly important within the laboratory, following on from the ERC projects EUREC4A (2016–2021) and MAESTRO (2023–2028). Tools for the temporal tracking of large-scale organized convective structures are also being developed as part of the ERC RECONCILE project in the DPA team (Dynamics and Physics of the Atmosphere) to understand the emergence of precipitation extremes.
The analysis of convective processes requires post-processing of data from these models and observations, which consists primarily of developing methodologies for detecting and tracking objects (associated with the processes mentioned above), as well as automated diagnostics related to the statistical properties of these objects (number, size, shape, lifetime, inter-object distances, etc.), as well as thermodynamic (temperature, humidity, etc.) and dynamic (velocity, vorticity, divergence, etc.) properties.

Constraints and risks

-

Compensation and benefits

Compensation

Following CNRS rules and experience, from 3,237.95€/month before tax.

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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