Thermal Land-surface Variables From METEOSATIR Data
F. Gottsche, F.-S. Olesen
Abstract
There are two series of satellites that provide long and continuous series of
data for the Mediterranean Basin: NOAA and METEOSAT. While
NOAA! A VHRR has 5 window channels (1 visible, 1 near IR, 1 water vapour
(WV; 3.7 Jll ), and 2 terrestrial IR (8-13Jll) ), METEOSAT is limited to 3
channels (1 visible, I WV, and I terrestrial IR). On the other hand,
METEOSAT resolves dynamic processes with 48 measurements per day
while A VHRR performs 4 measurements per day for a given location. In the
framework of climate analyses of surface properties the vegetation cover and
the albedo must be derived from A VHRR (spectral capabilities), while the
thermal properties must be derived from METEOSAT (temporal resolution).
Therefore, only a combined evaluation of many years of A VHRR and
METEOSAT can reveal climatic effects.
The large amount of data and the high degree of automation that is
required poses a technical challenge, while the development of adequate
algorithms and their application are scientific challenges. In order to respond
to these challenges best, the Forschungszentrum Karlsruhe and the FU-Berlin
agreed to join forces and to share the tasks according to their respective foci
of research. The FU-Berlin provides archived satellite data and derives the
Normalized Difference Vegetation Index (NDVI) and albedo from A VHRR.
The Forschungszentrum Karlsruhe - IMK determines thermal land surface
properties from METEOSAT IR data and provides access to an automatic
mass storage system. The determination of thermal surface parameters is
designed for METEOSAT's temporal and spectral capabilities and consists
of the following components:
The IR measurements are calibrated and satellite instruments are intercalibrated.
Cloud covered pixels are detected using dynamic thresholds.
A neural network is used to determine the atmospheric influence on IR
measurements at satellite level. The network is about 5.000 times faster
than MODTRAN and uses ECMWF atmospheric data as input. The
processing includes the inversion of satellite brightness temperatures to
F. Gottsche, F.-S. Olesen
Abstract
There are two series of satellites that provide long and continuous series of
data for the Mediterranean Basin: NOAA and METEOSAT. While
NOAA! A VHRR has 5 window channels (1 visible, 1 near IR, 1 water vapour
(WV; 3.7 Jll ), and 2 terrestrial IR (8-13Jll) ), METEOSAT is limited to 3
channels (1 visible, I WV, and I terrestrial IR). On the other hand,
METEOSAT resolves dynamic processes with 48 measurements per day
while A VHRR performs 4 measurements per day for a given location. In the
framework of climate analyses of surface properties the vegetation cover and
the albedo must be derived from A VHRR (spectral capabilities), while the
thermal properties must be derived from METEOSAT (temporal resolution).
Therefore, only a combined evaluation of many years of A VHRR and
METEOSAT can reveal climatic effects.
The large amount of data and the high degree of automation that is
required poses a technical challenge, while the development of adequate
algorithms and their application are scientific challenges. In order to respond
to these challenges best, the Forschungszentrum Karlsruhe and the FU-Berlin
agreed to join forces and to share the tasks according to their respective foci
of research. The FU-Berlin provides archived satellite data and derives the
Normalized Difference Vegetation Index (NDVI) and albedo from A VHRR.
The Forschungszentrum Karlsruhe - IMK determines thermal land surface
properties from METEOSAT IR data and provides access to an automatic
mass storage system. The determination of thermal surface parameters is
designed for METEOSAT's temporal and spectral capabilities and consists
of the following components:
The IR measurements are calibrated and satellite instruments are intercalibrated.
Cloud covered pixels are detected using dynamic thresholds.
A neural network is used to determine the atmospheric influence on IR
measurements at satellite level. The network is about 5.000 times faster
than MODTRAN and uses ECMWF atmospheric data as input. The
processing includes the inversion of satellite brightness temperatures to