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Faculty of Mathematics and Natural SciencesInstitute of Geophysics and Meteorology

MN-GM-METRS

Specialisation Module: Advanced Remote Sensing
Identification number
MN-GM-METRS		 Workload

180 h		 Credit Points

6		 Term
1st - 3rd Semester		 Offered Every

year		 Start

SuSe		 Duration

1 semester
1 Course types
a) Lecture
b) Project		 Contact time
45 h
30 h		 Private study
45 h
60 h
2 Aims of the module and acquired skills

To create understanding of:
  • the remote sensing principles that enable remote sensing of atmospheric and Earth surface characteristics
  • the use of different spectral ranges of electromagnetic radiation in remote sensing
  • remote sensing instrumentation and the global meteorological observation network
  • the principles, development and application of retrieval algorithms
Skills to be aquired:
  • Ability to interpret and to quantitatively analyse remote sensing observations
  • Development and assessment of statistical assumptions, numerical complexities and practical limits of retrieval and assimilation techniques
  • Programming experience, presentation skills, team work in hands-on-training
3 Module content
  • Remote sensing principles, meteorological satellites and orbits
  • Principles of retrieval algorithms for the inversion from radiances to geophysical parameters
  • Passive remote sensing of the atmosphere at visible, infrared and microwave wavelengths for temperature, humidity, clouds and aerosol
  • Active remote sensing of the atmosphere including for example cloud and precipitation radar, lidar, wind profiler, and GPS, use of polarimetric techniques
  • Remote sensing of the ocean (temperature, color, wind, waves) with passive instrumentation, altimeter and scatterometer
  • Remote sensing of Earth surface and vegetation
  • Hands-on training with data from satellite, aircraft or ground-based remote sensing instrumentation of e. g.  the Jülich Observatory for Cloud Evolution (JOYCE) or the AWIPEV Arctic research site
  • Possibly an excursion to JOYCE, ESA, EUMETSAT or DWD
4 Teaching methods

Lecture and project. The project encompasses the analysis and remote sensing measurements (satellite & ground-based) and model forecasts. The results of the project will be summarized in a presentation. Possibly hands-on remote sensing measurements at ground-based sites: set-up, calibration & execution.
5 Prerequisites (for the module)

Formal: None.
The content of the course requires the undergraduate knowledge of mathematics, physics, and experience in programming.
6 Type of examination

Oral Examination (graded)
At the end of the semester or the beginning of the following semester a possibility to repeat the examination is offered.
7 Credits awarded

The module is passed, and the credit points will be awarded, if
  1. the oral examination is passed, and
  2. the project is passed; for this, the successful presentation of the results is sufficient.
8 Compatibility with other curricula

Suitable as an elective course for physics students.
9 Proportion of final grade

Weight of the module grade in the overall grade: 6/150 (4 %)
10 Module coordinator

Kerstin Ebell
11 Further information

Version: 2023-03-28