Research scientist position for a statistician in climate science (R2/R3)

Barcelona Supercomputing Center
October 11 2017
Position Type
Full Time
Organization Type

About BSC

The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, and is a hosting member of the PRACE European distributed supercomputing infrastructure.

 Context and Mission

Within the Earth Sciences Department of Barcelona Supercomputing Center (BSC-ES), led by Prof Francisco Doblas-Reyes, the climate prediction group, led Dr. Pablo Ortega and Dr. Louis-Philippe Caron, aims at developing climate prediction capability for time scales ranging from a few weeks to a few decades (sub-seasonal to decadal climate prediction) and from regional to global scales. H2020 Program

Key Duties


    Implement and develop bias correction and forecast calibration methods for seasonal and decadal forecasts

    Develop both deterministic and probabilistic multivariable user-driven forecast scores

    Estimate the added value of combining climate predictions compared to non-initialized forced-only simulations

    Combine multiple forecast systems using methodologies based on past performance

    Explore the relative merits of different calibration approaches and evaluate the advantages of single-model calibration versus the multi-model in terms of forecast quality

    Improve the decadal climate predictions over land areas

    Test methods traditionally used in climate projections to i) quantify uncertainty and to ii) combine different members to assess and improve the forecast quality of climate predictions

    Develop procedures for observational uncertainty propagation in model assessment at different time and spatial scale and evaluate

    Develop methodologies to combine ensemble climate predictions with climate projections

    Assess the observational error correlation scale for different climate variables

    Improve the representation of observational uncertainty in the computation of verification metrics

This job comes from a partnership with Science Magazine and Euraxess