[ES_JOBS_NET] Job Vacancy at ECMWF for: Scientist - Post-processing to improve surface weather forecasts, closing date: 12 December 2019

Wed Oct 30 13:08:57 MDT 2019

Dear Mailing list,
Position information

Vacancy No.: VN19-44
Department: Forecast
Grade: A2
Section: Evaluation
Job Ref. No.: STF-PL/19-44
Reports to: Team Leader – Forecast Performance and Products
Publication Date: 24 October 2019
Closing Date: 12 December 2019
About ECMWF
ECMWF is an inter-governmental organisation supported by 34 Member and Co-operating States. It is both a research institute and a 24/7 operational service, producing and disseminating numerical weather predictions to its Member States. ECMWF carries out scientific and technical research directed to the improvement of its forecasts, collects and processes large amounts of observations, and manages a long-term archive of meteorological data. Satellite and in situ observations provide the information for up-to-date global analyses and climate reanalyses of the atmosphere, ocean and land surface.

For details, see www.ecmwf.int/<http://www.ecmwf.int/>.
Summary of the role
This position sits within the Forecast Performance Monitoring and Products team, within the Evaluation Section of the Forecast Department. To ensure its extended range and re-analysis products provide maximum benefit to society, ECMWF is exploring new ways in which post-processing can deliver added value for users. The successful candidate will test and explore a system to deliver improved probabilistic products for rainfall and temperature, for both extended range forecasts (in real-time), and for the ERA5 re-analysis (for 1950 to the present day). This will be achieved by applying a new downscaling technique (called “ecPoint”) to raw model output from ECMWF. The geographical focal point will be Italy, although global output will ultimately be provided.

This role is funded by the EU-financed HIGHLANDER project (HIGH performance computing to support smart LAND sERvices) (from call: “CEF-TC-2018-5 - Public Open Data”). The overarching objective of the ECMWF component of HIGHLANDER is to deliver societal benefits by improving probabilistic re-analysis and extended range predictions, and by delivering those predictions to the agricultural and land-use management sectors in real time. A key project resource is the CINECA supercomputing centre in Bologna, and the developed software will be run on this platform. There is an overlap with the ongoing EU-funded MISTRAL project. This also uses ecPoint for post-processing, but focusses on shorter ranges and targets improved flash flood prediction.

Activities will have three main components: (i) research and development that optimises ecPoint calibration for the agricultural and land-use management needs for the target domain, (ii) adaptation of pre-existing “ecPoint-rainfall” post-processing to apply to the differently-structured extended range and re-analysis model output, (iii) creation of new post-processed “ecPoint-temperature” output and (iv) operationalization of the production chain on the CINECA HPC facility, building on ECMWF experience using this during MISTRAL, and supporting a sustainable future beyond the project end date of 30 September 2022. The post-holder will be expected to work closely with HIGHLANDER project partners in Italy to understand the needs of customers, and to tailor and blend the output accordingly.

Main duties and key responsibilities
Adapting ecPoint code that currently runs on the CINECA platform with shorter range forecasts, to use instead as input ECMWF’s ERA5 re-analysis and Extended Range forecasts
Clarifying the main meteorological requirements of HIGHLANDER customers in agriculture and land-use management and collaborating throughout the project to ensure these needs are being met
Modifying ecPoint code to make it applicable to post-processing of 2m temperatures as well as rainfall, accounting for the different physical factors that affect temperature forecast skill
Optimising the way in which different post-processed components (deterministic and ensemble) of different re-analyses are blended, or used in isolation, to create the best possible reconstruction of past rainfall and temperature records and focusing on the meteo-geographical needs of customers in the primary target domain (Italy)
Collaborating on designing and implementing ways to convey the post-processed outputs to key customers, to include gridded datasets and innovative, user-oriented graphical formats
Pursuing a “data governance” process, together with other ECMWF staff, to enable post-processed output to be routinely stored on ECMWF’s archiving system (MARS), in a GRIB format sanctioned by the World Meteorological Organisation
Fulfilling additional contractual requirements pertaining to the HIGHLANDER project itself, such as documentation and collaborative work
Some travel to Italy is expected as part of this function, to attend project meetings and to collaborate with project partners
Personal attributes
·        Strong interest in achieving user-relevant improvements in the representation of surface weather in forecasts and re-analyses
·        Excellent analytical and problem-solving skills, with a proactive approach
·        Dedication and enthusiasm to work in a small team, and to promote international collaboration
·        Ability to engage with staff from other scientific backgrounds related to the project
·        Excellent interpersonal and communication skills, listening to and respecting the views of others
·        Ability to work to tight deadlines

Qualifications and experience required

Education
A university degree, or equivalent, in a discipline closely related to meteorology, physics or mathematics is required.
Experience
Experience of numerical weather prediction. (Essential)

Some experience with meteorological post-processing techniques. (Essential)

Experience of operational aspects. (Desirable)

Experience of UNIX, of scripting for UNIX systems, and of writing clear and resilient code. (Essential)

Experience in parallelising code to run on supercomputer architecture. (Desirable)

Experience with (i) ECMWF’s in-house Metview language, (ii) its MARS archiving system, (iii) Matlab, (iv) Python and (v) Jupyter notebooks would also be useful.
Knowledge and skills (including language)
Excellent meteorological knowledge, relating in particular to how well global numerical models represent 2m temperature and rainfall in different geographical settings. (Desirable)

Some knowledge of agriculture and land-use management (e.g. in Italy) and their meteorological needs. (Desirable)

Knowledge of different meteorological post-processing methods, particularly those suited to rainfall and to temperature. (Desirable)

Experience in the use of different verification metrics, for surface weather parameters. (Desirable)

Knowledge of agriculture, land-use management and hydrology. (Desirable)

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.
Other information
Grade remuneration
The successful candidate will be recruited at the A2 grade, according to the scales of the Co-ordinated Organisations and the annual basic salary will be £ 59,228.40 net of tax. This position is assigned to the employment category STF-PL as defined in the Staff Regulations.

Full details of salary scales and allowances are available on the ECMWF website at www.ecmwf.int/en/about/jobs, including the Centre’s Staff Regulations regarding the terms and conditions of employment.
Starting date: 1 April 2020, or as soon as possible thereafter.
Length of contract: 25 months.
Location: The position will be based in the Reading area, in Berkshire, United Kingdom.
Interviews for this position are expected to take place in Reading, Berkshire week commencing 3rd February 2020.
How to apply
Please apply by completing the online application form available at www.ecmwf.int/en/about/jobs.
To contact the ECMWF Recruitment Team, please email jobs at ecmwf.int
Please refer to the ECMWF Privacy Statement. For details of how we will handle your personal data for this purpose, see: https://www.ecmwf.int/en/privacy.
At ECMWF, we consider an inclusive environment as key for our success. We are dedicated to ensure 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, listed below, and all EU Member States.
Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland France, Hungary, Germany, Greece, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, North Macedonia, Norway, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom.
Applications from nationals from other countries may be considered in exceptional cases.

________________________________
Julie Palmer
Recruitment and Talent Management Officer
ECMWF | HR Section
e: julie.palmer at ecmwf.int<mailto:julie.palmer at ecmwf.int> t: +44 1189 49 9161

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