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Multi-satellite multi-instrument ionosphere probing

Neustrelitz, Germany, DLR Institute of Space Systems

[46157]
Field(s) of expertise
Information Technology
Job type
Contract
Education
Bachelor
Deadline
13/04/2020

About this job

Your mission:

At the Institute of Solar-Terrestrial Physics of the German Aerospace Center (DLR), solar-terrestrial relationships are studied with the focus on the ionosphere and their relation to phenomena and effects of space weather. Modern communication and navigation systems as well as high-resolution radar techniques of remote sensing work with radio waves whose propagation is significantly influenced by the electrically conductive part of the Earth’s atmosphere, the ionosphere. In view of constantly increasing demands on accuracy, availability and reliability of the radio signals used, it is necessary to have the most comprehensive knowledge possible of the propagation properties of the ionosphere. For this purpose and to understand the basic solar-terrestrial relationships, comprehensive observations of the state of the ionosphere and various space weather factors including solar wind as well as significant coupling processes with the magnetosphere, thermosphere, atmosphere and lithosphere are required.

With the modernization of GNSS, the use of multi-constellation, multi-frequency observations including new signals enables continuous monitoring of the Earth’s ionosphere using worldwide distributed sensor stations. The permanently growing number of GNSS receivers and associated networks essentially supports establishing high precision monitoring of ionospheric weather including perturbation tracking and forecasts usable in space weather services. Other ground based techniques such as vertical sounding (VS), Incoherent Scatter Radar (ISR), Very Low Frequency (VLF) or Radio Beacon (RB) measurements provide complementary data thus completing GNSS based data sets.

Such multi-sensor observations of ionospheric variables allow the reconstruction of the three-dimensional electron density distribution in regional and global scales, which is necessary for the assessment of radio wave propagation. For this purpose, data from different measurement techniques with different spatial and temporal scales have to be harmonized and merged to obtain a consistent specification of ionospheric electron density. The task includes data fusion as well as empirical modelling and prediction.

On the one hand ionospheric reconstructions from the direct and multi-sensor observations are valuable for independent scientific publications. On the other hand, they provide a valuable data basis for further theoretical studies on the behaviour of the ionosphere and its prediction as well as for a reliable operational space weather service via DLR’s Ionospheric Monitoring and Prediction Center (IMPC).

Responsibilities

The Institute for Solar-Terrestrial Physics is therefore looking for staff to work on the following topics:

  • Development of inversion techniques for deriving ionospheric variables from satellite and ground-based measurements, and reconstruction methods for 3D electron density distribution of geo-plasma by data fusion.
  • Literature research on ionospheric variability and dynamics.
  • Data sources such as IMAGE satellites, Van Alan probe data and DMSP data (Defense Meteorological Satellite Program) shall be investigated to capture and model ionospheric variability.
  • Trend analysis of ionospheric variability and dynamics using long-term space and ground-based data and determination of optimal model input parameters.
  • Development of robust, autonomous and fast running physically motivated empirical models to describe ionospheric variability and dynamics.
  • Investigation, evaluation and development of observation techniques for instrument calibration and ionosphere estimation using non-conventional data from new sensors such as smart phones, dust-like GNSS sensors, LOFAR, EISCAT.
  • Development of appropriate numerical and algebraic techniques for data fusion and assimilation of multi-instrument and multi-satellite data to generate highly accurate reconstructions of 3D geo-plasma.
  • The implementation of effective real-time processing systems is based on the programming languages C++, Python and Matlab on Linux and Microsoft Windows systems.
  • Documentation of work results in publications and project reports.
  • Responsible assumption of project tasks.

The staff of the institute has many years of experience in monitoring the ionosphere, in particular by means of satellite-based and ground-based GNSS techniques and empirical modelling of the ionosphere.

Profile

  • A very good scientific university degree (Master’s or diploma) in (geo-) physics or mathematics/information technology.
  • Very well completed doctorate in geophysics, physics or mathematics.
  • Practical experience in the empirical modelling of physical processes.
  • Many years of experience and sound specialist knowledge in the processing of remote sensing data, calibration, data assimilation with mathematical methods (e.g. Least Square Method, Kalman filter, machine learning techniques).
  • Very good knowledge of relevant programming languages (e.g. Fortran, Python, Matlab, C++) and common operating systems.
  • Experience in project acquisition and project management.
  • Excellent German and English knowledge in spoken and written.
  • Ability to work in a team as well as independent, creative and goal-oriented way of working.

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.