General information
Offer title : (M/F) 8-month post-doc followship on “Assessing Global Climate Models using Earth Observation Data with a focus on atmospheric water cycle” (H/F)
Reference : UMR8212-HELBRO-002
Number of position : 1
Workplace : ST AUBIN
Date of publication : 04 November 2024
Type of Contract : FTC Scientist
Contract Period : 8 months
Expected date of employment : 10 January 2025
Proportion of work : Full time
Remuneration : gross monthly salary at minimum 3081 euros, commensurate with experience
Desired level of education : Niveau 8 – (Doctorat)
Experience required : Indifferent
Section(s) CN : Earth System: superficial envelopes
Missions
The work will be conducted as part of Phase 2 of the ESA Water Vapor CCI project. A study in 2021 (Hé et al, 2022) focusing on the inter-tropical band and a set of 7 global climate models, showed that there are strong divergences in the observed interannual variability of atmospheric water vapor with very strong disparities over the continents. These individual divergences are partly related to the sub-mesh patterns of parameterization of convective processes (involving cloud formation) and surface moisture fluxes (involving surface temperature).
The objective of the project will be to study the co-variations of the water vapor, clouds and surface temperature parameters in the inter-tropical band both in the time series observed by satellites and made available by ESA and in the global climate models.
Activities
the candidate will rely on “multi-resolution” statistical analysis in order to decompose the signal of interest at different time scales (e.g.: Oh et al, 2003). The aim will be to develop a metric based on the reproduction of the characteristic temporal frequencies of the variables studied. The work will specifically consist of:
– Manipulating the long series produced in the framework of the ESA Climate Change Initiative projects, including error budgets, technical specifications, etc.
– Use the discrete wavelet approach to decompose the time series into frequency bands and study correlations between variables
– Transfer these metrics to different numerical models (IPSL, CNRM, UKMO, …) and to reanalysis models (ERA-Interim, ERA-5) and analyze the results.
– Communicate the results through international conferences and write at least one scientific paper in a peer-reviewed journal
Skills
A PhD is required, preferably in remote sensing, atmospheric or climate science, with experience in statistical analysis. Facility with UNIX, shell scripts, and other programming languages (ideally R or python) is required, as well as teamwork skills
Work Context
Multiple physical processes contribute to the redistribution of water from the oceans to the land, involving cloud formation, precipitation and extreme weather events. Within the hydrological cycle, water vapor has a special place since it is the most important natural greenhouse gas in the atmosphere and generates a strong positive feedback to the anthropogenic climate forcing due to carbon gases (CO2, CH4, …). It is because of its importance that the Global Climate Observing System (GCOS, co-sponsored by the WMO) has identified water vapor as a key climate variable.
However, understanding the evolution of the Earth’s atmospheric water cycle under forcing (natural or anthropogenic) is a challenge given the spatial and temporal scales involved, ranging from the global scale (such as the inter-tropical convergence zone) to the local turbulent flows that cause instabilities.
The ESA Water Vapor CCI project aims to generate high-quality global time series of vertically resolved total column and water vapor data that are spatially and temporally homogeneous to meet the needs of users in the climate research community in the best possible way (spatial and temporal resolution, error documentation, homogeneity). The present fellowship is part of this international project that started in May 2019, coordinated by the University of Reading, and involving 11 partners.
