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January 2019
Message 90

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[Met-jobs] 2yrs Post Doc Position at LOCEAN/IPSL on decadal predictions analysis (H2020-EUCP)

From "Juliette.Mignot" <Juliette.Mignot@locean-ipsl.upmc.fr>
To met-jobs@lists.reading.ac.uk
Cc Didier Swingedouw <didier.swingedouw@u-bordeaux.fr>
Date Wed, 23 Jan 2019 10:29:17 +0000



24-month postdoctoral position

 

IPSL/LOCEAN laboratory

 

Analysis of decadal prediction in the North Atlantic

 

H2020-EUCP project

 

This fellowship aims at understanding the physical mechanisms causing variability and predictability in the climate system using several decadal climate predictability systems and identifying potential avenues for the improvement of the skill of decadal prediction systems in particular using observational emergent constraints.

 

Decadal prediction represents a recent challenge in the climate community, especially with the development of climate services. It consists in using observations to constrain the initial conditions of the climate projections, in order to initialise the phase from the natural modes of climate variability and thereby provide a forecast at the decadal timescale. Within CMIP6 exercise, different modelling centres are preparing  decadal predictions over the period 1960-2015. These different systems will have to be intensively compared and the link between their skills and their representation of the subpolar gyre, a key region for predictability has not been assessed yet.

 

The successful candidate will analyse different climate prediction systems involved within the project and will evaluate their skills over Europe. The novelty of the work proposed here will be firstly to evaluate the evolution of this skill for different time periods, searching for the existence of some windows of opportunity. Furthermore, we will analyse the potential linkages between their skill and the realism of the mean state and variability of the considered system in terms of salinity and temperature in the subpolar and subtropical gyres over the period 1960-2015. From there, he/she could develop a statistical method, based on the so-called emergent constraints, to provide improved predictions for the past and the near future, based on this multiple climate prediction systems.

 

The postdoctoral fellowship will be located at IPSL/LOCEAN laboratory located in the heart of Paris, with close collaboration with the EPOC laboratory The IPSL-EPOC decadal prediction team is composed of four permanent researchers. Four other postdoctoral fellows are also part the team at the same time as the present proposal, one involved in the same EU-H2020 project (EUCP) and the other one in the EU-H2020 Blue-Action project. This will ensure stimulating interactions within and outside the research group. The IPSL-EPOC decadal prediction team also benefits from the enthusiastic scientific environment both in Paris and Bordeaux, notably both the NEMO and the IPSL coupled model developing teams, both of which will be key within the fellowship.

 

We expect a PhD in oceanography, meteorology, environmental sciences or similar research experience. The position is offered for 12 months renewable once. Payment will be in accordance with French public service salaries (between 2500 and 3000 Euros before taxes, depending on experience). The ideal starting date is for coming Autumn.

 

The postdoctoral fellowship will be primarily supervised by Didier Swingedouw and Juliette Mignot, with strong involvement of Eric Guilyardi and Guillaume Gastineau.

Applications should comprise scientific experience, a letter of motivation with availability date, and some referee name(s). They should be submitted on the CNRS web portal: https://emploi.cnrs.fr/Offres/CDD/FR636-ALERUB-011/Default.aspx?lang=EN and sent by email to the following e-mail addresses before 1st March 2019.

 

-- 
Juliette Mignot
Locean
Universite Pierre et Marie Curie, Case courrier 100 
4 place Jussieu, 75252 Paris Cedex 05,  France
phone/fax : +33 1 4427 3304 / 7159 

Attachment: PostDocPosition24mth_LOCEAN_Decadal_EUCP.pdf
Description: Adobe PDF document



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