Reference : UMR5566-THOFIO-001
Workplace : TOULOUSE
Date of publication : Monday, November 14, 2022
Type of Contract : FTC Technical / Administrative
Contract Period : 12 months
Expected date of employment : 1 February 2023
Proportion of work : Full time
Remuneration : Monthly Gross salary between 2583 and 3140 euros
Desired level of education : Engineer
Experience required : Indifferent
Deep convection is at the heart of the key processes for climate change both at the societal level in relation to the extremes of intense precipitation and, at the scientific level in relation to the climatic feedbacks of the high clouds associated with it. Deep convection is organized in convective storms identifiable from space, and which play a crucial role in the energy and water budget at the global scale through the vertical transport of mass, water and momentum. Despite being studied for a long time, deep convection remains a strong source of uncertainty on the future evolution of the water and energy cycle in response to climate change.
The objective of this work is to exploit satellite data to improve our understanding of deep convection.
- The candidate will have the task to pursue the studies on the life cycle of convective storms, by using and developing merging methodologies of infrared observation from geostationary satellites and precipitating observation from Low Earth Orbit (Megha-Tropiques, TRMM, GPM, CloudSat). For that, he/she may rely on the 2012-2020 convective storm database, which has been already produced by applying a cloud pattern recognition algorithm on infrared geostationary observation over the entire tropics, as well as the climatological 40-year convective storm database built from the long-term METEOSAT observation over Africa and the Atlantic Ocean.
- He/She will be in charge of the management and processing of historical geostationary data by applying the convective storm tracking algorithm, and will participate to the analysis of the results. He/She will also contribute to the studies on the refinement of the description of the cloud shield associated to the convective storms, thanks to the arrival of new generation of geostationary satellites with enriched spectral specifications and an increased spatio-temporal resolution.
- The candidate will also contribute to explore the numerical simulations of deep convection from various high-resolution atmospheric models.
Particular attention will be devoted to the documentation of developped tools.
- Engineering or doctoral degree in atmospheric science with significant experience in scientific computing and image processing
- Required excellent knowledge in scientific programming language (IDL, Python, Matlab), as well as in C language
- Linux environment
- Experience in manipulating large amount of volume of data and using statistical methods
- Skills of communication, written and oral
- Autonomy, interpersonal skills and ability to work in a team
This project is part of a dynamic scientific research sustained by new high-resolution modeling projects, which resolve deep convection. Substantial efforts are indeed underway, particularly in Europe, to produce a new generation of climate models better able to represent this deep convection and its organization (Digital Twin, DestinE). Similarly, new international satellite missions, C2OMODO/AOS (Atmospheric Observing Systems), or INCUS (Investigation of Convective Updrafts) are planned to be launched in the next decade, which will give us observational constraints on simulating of deep convective processes.
This work will take place at LEGOS (Laboratoire d'Etudes en Géophysique et Océanographie Spatiales), a French laboratory with 130 employees, on the campus of the Observatoire Midi-Pyrénées in Toulouse. The Research engineer will join in particular the EMC2 team, whose objective is to understand the variation of water and energy cycle in response to climate change. The candidate will take advantage of a rich national and international environment and will may interact with engineers, researchers and PhD students from the team and other laboratories.
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