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Scientist - Land Surface Assimilation

ECMWF - European Centre for Medium-Range Weather Forecasts

Reading, United Kingdom

Summary of the role

This position is in the Coupled Assimilation Team of the Earth System Assimilation Section (ESAS) of the Research Department.

The Scientist will support research developments targeted toward enhancing the ECMWF land surface data assimilation system, by contributing to methodological and technical developments and evaluation activities. He or she will work closely with other teams of the Earth System Assimilation, Modelling and Predictability Sections.

Main Duties and key responsibilities

  • Building and maintaining the off-line surface analysis infrastructure used for H-SAF soil moisture analysis products and for land surface assimilation research developments, in collaboration with the Earth System Modelling and Predictability Sections;
  • Developing and maintaining soil moisture evaluation and land surface evaluation tools in collaboration with the ECMWF Evaluation Section;
  • Performing the production of H-SAF root zone soil moisture products, their evaluation and documentation and contributing to international collaboration with EUMETSAT H-SAF partners and ESA SMOS partners;
  • Providing support for ECMWF coupled reanalysis activities on land surface diagnostics;
  • Assisting with forecast impact diagnostic studies;
  • Assisting with studies related to new observations.

Personal attributes

  • Good interpersonal and communication skills;
  • Excellent analytical and problem-solving skills with a proactive approach;
  • Self-motivated and able to work with minimal supervision;
  • Dedication and enthusiasm to work in a small team;
  • Ability to work efficiently and complete diverse tasks in a timely manner.

6. Qualifications and experience required

Education

  • A university degree or equivalent in atmospheric science, hydrometeorology or related areas of physics;
  • A PhD is desirable but not essential.

Experience

  • Experience in meteorology and/or land surface processes is required;
  • Experience in handling Earth observation datasets;
  • Experience in land surface data assimilation is highly desirable;
  • Experience with developing and contributing to complex shared code is highly desirable;
  • Experience with high-performance computing platforms is desirable.

Knowledge and skills (including language)

  • Excellent programming skills in a high-level programming language (e.g. Fortran, C++, python) and UNIX scripting is essential;
  • Candidates must be able to work effectively in English and interviews will be conducted in English;
  • A good knowledge of one of the Centre’s other working languages (French or German) would be an advantage.

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