Researcher on greenhouse gas emissions estimates from atmospheric measurements in support of the Paris agreement
Monitoring emissions and sinks of the main greenhouse gases CO2, CH4 and N2O is essential for
tracking the effectiveness of mitigation actions for the Paris Agreement on Climate, now more than
ever, with recent pledges made in Glasgow and the upcoming Global Stock Take. We are looking for a
motivated young researcher to analyze atmospheric inversions results for the three greenhouse
gases, in particular the inversions recently synthesized by the Global Carbon Project in the CO2
budget, the CH4 budget and forthcoming N2O budget publications.
The goal is to develop new tools and analysis methods to estimate regional and national budgets of
these greenhouse gases. Comparison between atmospheric inversions and inventories was
pioneered in our recent research by Deng et al. 2022 whose results attracted a wide interest from
the media at the COP26. The outcome of the research will the development of new approaches for
the separation of natural and anthropogenic emissions, the separation of fluxes between managed
and un-managed land and policy relevant information on anthropogenic emissions per sector.
This work will be performed as part of the RECCAP2 project of the ESA Climate Change Initiative and
will involve a dialogue with national inventory agencies, with a special focus to support the provision
of improved estimates of emissions in developing countries. At least one high impact publication is
foreseen from this work in the course of the global-stock take of the Paris Agreement, to bring to
policy the latest atmospheric research.
The successful candidate will work closely with Philippe Ciais, Marielle Saunois and Frederic
Chevallier in Gif sur Yvette, France, with the other members of the project, and several students.
Specific aims and working steps
– Analyze results of atmospheric inversions for CO2, CH4 and N2O emissions Develop a framework
(geo-statistics & spatial analyses) to separate trends from natural variability,
– Combine inversion results with other datasets to separate anthropogenic and natural fluxes
– Share results and perform analysis with partner national inventory agencies
– Publications, presentations at international scientific conferences and during policy dialogues
organized by the European Space Agency (ESA)
– Programming skills, preferably in Python or R
– Knowledge of statistics and data analysis
– Communication skills, clear diagrams and interest for science and climate policy
Philippe Ciais , Marielle Saunois , Frédéric
– PhD or MSc. in modeling, atmospheric science, data science or another relevant field
– Autonomy, ability to work in a team and time management skills
– Experienced in multidisciplinary team-based activities with the ability to effectively communicate
with colleagues and with staff from the partners of a project.
Laboratoire des Science du Climat et de l’Environnement (https://www.lsce.ipsl.fr) located about 20
km from the heart of Paris in the Orme des Merisiers green area. LSCE is a world-class research laboratory
established and a collaboration between CEA, CNRS and the University of Versailles Saint-Quentin (UVSQ). It is part of the Institute Pierre Simon Laplace (IPSL). LSCE hosts approximately 300 researchers, engineers and administrative staff including many PhD and master’s students. This project will provide the employee with the opportunity to work directly on advanced methods with researchers from the LSCE and other institutions
Contract duration: up to 24 months
Starting date: The position is available from June 2022 and will remain open until filled.
Salary: Competitive salary with full social and health benefits, commensurate with work experience.
How to apply: Applicants should submit a complete application package by email. The application package
should include (1) a curriculum vitae including most important recent publications, (2) statement of motivation (3) answers to the selection criteria above (4) names, addresses, phone numbers, and email addresses of at least two references.
Programming skills, preferably in Python or R
Knowledge of statistics and data analysis
Communication skills, clear diagrams and interest for science and climate policy