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Reference : UMR8539-ISARIC-059
Workplace : PALAISEAU
Date of publication : Thursday, September 2, 2021
Scientific Responsible name : CREVOISIER Cyril
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2021
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
Methane (CH4) is the second main greenhouse gas influenced by human activities. In the context of monitoring future emissions of this gas, particularly in connection with emission reduction policies linked to the Paris Climate Agreement, the creation of an integrated emissions monitoring system is crucial. An essential element of this system, the space component is being defined, in particular at European level through the Sentinel and Copernicus programs.
The majority of space missions dedicated to the observation of CH4 which are planned for the near future make observations in the near infrared (SWIR) domain. This is particularly the case of ESA's UVNS / Sentinel 5 mission (launch planned for 2023) on the 3 Metop-SG-A platforms. Sentinel-5P precursor mission was launched at the end of 2018 and is starting to provide data. These missions provide information on the total column of CH4 with a non-zero sensitivity close to the surface but they are also sensitive to the entire free troposphere and to the stratosphere.
The CNES IASI mission carries out observations in another spectral domain, that of thermal infrared (TIR). In the TIR, the observations give access to a weighted column of CH4 on the mid-troposphere. Already 14 years of observation of CH4 have been obtained from IASI. Tthese measurements mainly provide information of the background value of the gas concentration in the troposphere.
The information provided by the 2 spectral bands TIR and SWIR are thus very strongly complementary. The synergistic use of these 2 spectral bands will allow the extraction of information on several layers of altitude, which will strengthen the monitoring of the lowest layers of the atmosphere, where the emission signal is strongest. This is precisely one of the possibilities that will be offered by the Metop-SG-A platform which, from 2023, will embark both the UVNS / Sentinel5 mission and IASI-NG, the successor to IASI.
The objective of the thesis is to study the contribution of a coupling between the two spectral bands SWIR and TIR by establishing the merits of a joint SWIR / TIR operation and by applying it to the existing IASI and Sentinel-5P missions. whose data are already available. The results obtained will make it possible to prepare the joint IASI-NG / Sentinel-5 measures which will be available from the start of 2024. The different stages will focus on the study of the information content of the 2 bands by direct and inverse simulation of radiative transfer, on the study of their vertical sensitivities to CH4 variations and on the achievable accuracies.
This work will be based on the use of the radiative transfer code 4A / OP developed at LMD and reference code from IASI and IASI-NG. Two approaches will be used for the estimation: a Bayesian approach and a machine learning approach based on artificial neural approach. The contribution of a vertical characterization of anthropogenic greenhouse gases over several atmospheric layers to the estimation of emissions and gas sinks at the surface will be studied using an approach called atmospheric inversion, or top-down, which relies on the use of atmospheric chemistry-transport models.
LMD studies climate, air quality, and changes in planetary atmospheres, through a combination of theoretical approaches, instrumental innovations, collection of observations, analysis of data, in particular satellite data, conceptual developments, and numerical modeling. The successful candidate will join the ABC(t) team of LMD, which is involved in instrumental research and development, and specializes in the analysis of space missions, both passive (IASI, IASI-NG, AIRS, IIR, Flex, MicroCarb) and active (Merlin). Over the years, the team has developed a full processing chain for satellite data that comprises: (i) the management and development of the spectroscopic database GEISA; (ii) the management and development of forward radiative transfer models); (iii) the development of inverse radiative transfer codes for retrieving Essential Climate Variables (ECVs): clouds, aerosols, surface properties, and greenhouse gases (CO2, CH4, CO and N2O); (iv) validation activities, which are essential for providing robust long-term time series of ECVs.
Constraints and risks
- master (M2) in atmospheric sciences, remote sensing, measurement physics or applied mathematics
- knowledge of inverse problem would be an asset
- programming language: Fortran, C, python
- the ability to work in a team
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