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Faculty of Mathematics and Natural SciencesInstitute of Geophysics and Meteorology

MN-GM-METRS

Elective: Advanced Remote Sensing
Identification number

MN-GM-METRS		Workload

180 h		Credits

6 		Term of studying
1. -3. Semester		Frequency of
occurrence
Summer term
Duration

1 semester
1 Type of lessons
a) Lectures
b) Project Work 		Contact times
45 h
30 h		Self-study times
45 h
60 h		Intended group size
15
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
  • of remote sensing instrumentation and the global meteorological observation network
  • the principles, development and application of retrieval algorithms

Skills:
  • 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 Contents of the module
  • 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 with cloud and precipitation radar, lidar, wind profiler, sodar 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 (SAR, NDVI)
  • Hands-on training with ground-based remote sensing instrumentation at the Jülich Observatory for Cloud Evolution (JOYCE), at the Environmental Research Station Schneefernerhaus on Mt. Zugspitze and/or the polarimetric radar Bonn
  • Application of remote sensing data for evaluation of reanalysis and dynamic models, e.g. COSMO and ICON
  • Excursion to ESA, EUMETSAT or DWD
4 Teaching/Learning methods

Lecture and project work including remote sensing measurements at ground-based sites: set-up, calibrate & carry out; interpretation and presentation of remote sensing measurements (satellite & ground-based) and model forecasts; PC-exercises on radiative transfer & remote sensing;
5 Requirements for participation

Formal: none

With regards to content: Basics of mathematics, physics, experience in programming (mandatory)
6

Type of module examinations

Oral examination (graded) and written report (graded)

7 Requisites for the allocation of credits

Successful participation in the project work documented by a written report marked equal or better than 4.0 and passing the oral examination. The examination part may be repeated once during the semester.

A failed examination may be repeated twice. Additional possibilities to repeat an examination exist according to the examination regulations (§ 20 section 1).
8 Compatibility with other Curricula
  • Other modules of equal value can be admitted and announced by the examination board after agreement.
  • Suitable as an elective course for mathematics, physics and geoscience students.
9 Significance of the module mark for the overall grade

6/120
10 Module coordinator

S. Crewell
11 Additional information

Recommended literature:

Kidder, S.Q. and von der Haar, T.H.; 1995: Satellite Meteorology: An Introduction, Academic Press, 466 pp.
Rodgers, C.D.; 2000: Inverse methods for atmospheric sounding: Theory and practice. World Scientific, 238 pp.