Scientist - Seasonal Forecasting - Tenders Global

Scientist – Seasonal Forecasting

ECMWF - European Centre for Medium-Range Weather Forecasts

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Job reference:
VN24-90
Salary and Grade:
Grade A2 EUR 86,824 NET annual basic salary + other benefits
Deadline for applications:
27/10/2024
Department:
Research
Location:
Bonn, Germany
Contract type:
STF-PL
Publication date:
25/09/2024
Contract Duration:
Approx. 3.5 years until June 2028, with possibility of extension

Job Description

The role 

We are looking for a motivated scientist to help us drive forward improvements in multi-system seasonal forecasts for climate services.

You will join a team at ECMWF and collaborate with colleagues from Member States, other partners and the wider scientific community to help us make further progress in the accuracy and reliability of seasonal forecast systems. Design and development of ensemble seasonal forecasting systems is complex and involves the scientific and computational balance of multiple components, including initialization, suitability of the forecast model, boundary conditions, ensemble generation and verification techniques. The very limited number of past cases available for model assessment, and the non-stationarity of the climate are serious challenges when it comes to evaluation and system design. The work is becoming ever more important as the impacts of climate change grow and past experience becomes an increasingly poor guide as to what weather to expect for the coming season.

Your work will focus on research to guide the design and evolution of future seasonal forecasting systems. This includes exploring hypotheses using numerical experimentation, diagnosing the performance of individual forecasting systems and developing additional metrics for system performance. Further research will include methods to extract predictable signals from the multi-system ensemble, and study of the impact of climate non-stationarity on climate predictability and methods to account for this.

This position is funded as part of the Copernicus Climate Change Service (C3S), and your work will support both the ECMWF contribution to the multi-system seasonal forecast ensemble and the wider development of C3S seasonal forecast activities.

The team

The Long-range Forecasting Team, part of the Earth System Predictability Section, is responsible for the design and scientific underpinnings of the ECMWF seasonal prediction configuration, which is expected to cover the forecast ranges from one month to two years ahead. The team conducts predictability research to improve our understanding and representation of sources of seasonal predictability. The team also provides scientific support to the C3S multi-system seasonal forecast component.

The Earth System Predictability Section is part of ECMWF’s Research Department. The Section explores relevant directions to improve the skill of the ECMWF forecasting system across timescales. This involves both exploring the Earth-system predictability horizon and identifying elements limiting present-day forecast skill.

About ECMWF 

The European Centre for Medium-Range Weather Forecasts (ECMWF) is a world-leader in weather and environmental forecasting. As an international organisation, we serve our members and the wider community with global weather predictions and data that is critical for understanding and solving the climate crisis. We function as a 24/7 research and operational centre with a focus on medium and long-range predictions, holding one of the largest meteorological data archives in the world. The success of our activities builds on the talent of our scientists and experts, strong partnerships with 35 Member and Co-operating States and the international community, some of the most powerful supercomputers in the world, and the use of innovative technologies and machine learning across our operations. ECMWF is a multi-site organisation, with a main office in Reading, UK, a data centre/supercomputer in Bologna, Italy, and a large presence in Bonn, Germany. 

ECMWF is a global leader in machine learning for Earth system application and investigates machine learning throughout the weather forecast value chain including for observation processing, data assimilation, forecasting and post-processing. ECMWF has also developed a machine learned global forecast model – the Artificial Intelligence Forecasting System (AIFS) – that is used for daily weather predictions.

ECMWF has also developed a strong partnership with the European Union and has been entrusted with the implementation and operation of the Destination Earth Initiative and the Climate Change and Atmosphere Monitoring Services of the Copernicus Programme. Other areas of work include High Performance Computing and the development of digital tools that enable ECMWF to extend provision of data and products covering weather, climate, air quality, fire and flood prediction and monitoring.

See   for more info about what we do. 

The Copernicus Programme

Copernicus is the earth observation component of the European Union (EU) space programme. Based on the exploitation of spaced based and in situ (earth-based) observations and scientific models, Copernicus provides information services for land, marine, atmospheric and climate monitoring, as well as emergency management and security. These services, and their free, open and quality assured data and tools, support a range of environmental and security applications across sectors and policy domains. For details, see

The Copernicus Atmosphere Monitoring Service (CAMS) service provides consistent and quality-controlled information related to air pollution and health, solar energy, greenhouse gases and climate forcing, everywhere in the world. For details, see 

The Copernicus Climate Change Service (C3S) service provides authoritative information about the past, present and future climate, as well as tools to enable climate change mitigation and adaptation strategies by policy makers and businesses. For details, see

Main duties and responsibilities 

  • To share in the scientific and technical activities of the long-range team, and to explore possible innovations to enhance the seasonal forecasting system
  • To conduct numerical experimentation to advance the understanding of predictability at the seasonal time scale, and to test hypotheses related to improving forecast systems
  • To develop and implement appropriate additional diagnostics to enhance performance metrics for model and forecast assessment
  • To participate in research on the representation of climate non-stationarity in seasonal forecast systems, and methods to account for this in the creation of products
  • To contribute to research on the predictable signals contained within model forecasts, and methods to extract these from the C3S multi-system ensemble
  • To support users in the appropriate use and interpretation of seasonal model outputs and products

What we’re looking for

  • Strong analytical and problem-solving skills, with a proactive approach
  • Attention to detail but capability of, and focus on, understanding the overarching problems
  • Demonstrated curiosity, drive and ability to perform novel research of international standing
  • Passion, self-motivation and the ability to work independently
  • Excellent interpersonal and communication skills

Education

  • A very good university degree and doctorate degree in climate science, mathematics, physics or a related field

Knowledge, skills and experience

  • Sound knowledge of meteorology, climate dynamics, climate variability and change
  • Knowledge of concepts of predictability of weather and climate
  • Experience with statistical techniques, including evaluation of ensemble simulations
  • Ability to conduct numerical experimentation with GCMs in HPC environments
  • Strong programming and scripting skills (python, bash, ideally also fortran)
  • Experience working with large datasets, familiarity with ECMWF data formats

You must be able to work effectively in English and interviews will be conducted in English

Other information 

Grade remuneration:  The successful candidates will be recruited at Grade A2, according to the scales of the Co-ordinated Organisations and the annual basic salary will be EUR 86,824 NET annual basic salary (ECMWF salaries are exempt of national income tax). In addition to basic salary, ECMWF also offers an attractive package of benefits and entitlements. This position is assigned to the employment category  STF-PL  as defined in the ECMWF Staff Regulations. To find out more about working with us and for full details of salary scales and allowances, please visit . 

Starting date:                as soon as possible

Length of contract:     The contract duration is expected to be 3.5 years with possibility of extension

Location:                         Bonn, Germany

Remote work:          As a multi-site organisation, ECMWF has adopted a hybrid organisation model which allows flexibility to staff to mix office working and teleworking. We allow for remote work 10 days/month away from the office, including up to 80 days/year away from the duty station country (within the area of our member states and co-operating states).

Interviews by videoconference (MS Teams) are expected to take place during the second half of October  2024. If you require any special accommodations in order to participate fully in our recruitment process, please let us know. 

To contact the ECMWF Recruitment Team, please email [email protected].

Who can apply 

Applicants are invited to complete the online application form by clicking on the apply button below. 

At ECMWF, we consider an inclusive environment as key for our success. We are dedicated to ensuring a workplace that embraces diversity and provides equal opportunities for all, without distinction as to race, gender, age, marital status, social status, disability, sexual orientation, religion, personality, ethnicity and culture. We value the benefits derived from a diverse workforce and are committed to having staff that reflect the diversity of the countries that are part of our community, in an environment that nurtures equality and inclusion. 

Applications are invited from nationals from ECMWF Member States and Co-operating States, as well as from all EU Member States. 

ECMWF Member and Co-operating States are: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, Norway, North Macedonia, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and the United Kingdom. 

In these exceptional times, we also welcome applications from Ukrainian nationals for this vacancy.  

Applications from nationals from other countries may be considered in exceptional cases. 

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