28 Oct
2021
28 Oct
'21
7:09 p.m.
Annonce postée par : SAUX PICART Stéphane (stephane.sauxpicart(a)meteo.fr)
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Title: Mitigating low signal-to-noise ratio in geostationary satellite ocean colour
observation.
Location: Méteo-France, CNRM, UMR 3589, Lannion, France.
Duration: 4 to 6 months beginning in early 2022. Legal compensation of about 500€/month.
Summary of the project:
Observation of the Ocean Colour (OC) using remote sensing techniques is possible since the
late 70’s from polar orbiting satellites with revisit time of typically one or two days.
Meteorological geostationary satellites offer the advantage of providing data at a very
high temporal frequency (typically every 10 to 15 minutes) necessary for meteorological
applications. High frequency observation is also key for observing rapidly varying surface
parameters (e.g. coastal dynamics) and to partially overcome the impossibility to observe
the surface under clouds in visible and infrared channels.
Currently only the Geostationary Ocean Colour Imager (GOCI), a Korean instrument, is a
geostationary satellite dedicated to observing the colour of water surfaces. Several
studies have demonstrated the potential of the instrument SEVIRI (on-board the satellites
of the EUMETSAT Meteosat Second Generation program) to observe water turbidity in highly
turbid areas. EUMETSAT is about to launch its new generation geostationary program
(Meteosat Third Generation): the first imager satellite will be launched in 2022. On-board
this platform is the visible and infra-red radiometer Flexible Combined Imager (FCI) which
has improved capabilities with respect to Ocean-Colour applications.
However, geostationary satellites like MTG are placed on a high orbit (altitude of about
36000 km) and their instrument’s radiometry is not defined considering Ocean Colour
specifications. Therefore, the quality of the acquisitions is poorer than those of
instruments on-board of dedicated low orbiting satellites. This represents a major
limitation in the process of retrieving Ocean Colour parameters from such observations.
Indeed, water constituents responsible for the colour of the ocean contribute to a small
extent to the overall top-of-atmosphere reflectance in the visible domain. A low
signal-to-noise ratio (S/N) therefore results in high uncertainties in the geophysical
parameters retrieved.
The objective of this internship is to explore ways of mitigating this effect. For
instance, this could be done by temporally and/or spatially averaging pixel values of
top-of-atmosphere reflectance, of water-leaving radiance or of geophysical parameter.
Methodology:
• Review the literature on Ocean Colour parameter retrieval from geostationary
observations.
• Design one or more methodologies to mitigate the effect of the low S/N.
• Implement them on MSG or GOES or other proposed satellite data.
• Validate them by comparison to well established higher resolution Ocean Colour
products (for example CCI or CMEMS data).
Requirements:
• Candidate should be in M2 or equivalent.
• Be experienced in using Linux environment and python scientific modules.
• Have some knowledge on remote sensing data processing.
• Have some knowledge about Ocean Colour remote sensing.
• Be highly motivated!
Supervisor: Dr Stéphane Saux Picart (stephane.sauxpicart(a)meteo.fr)
Co-supervisor: Dr Ewa Kwiatlowska (EUMETSAT)
To apply, please send a CV+Cover letter.
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