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| Titel |
Standard Dataset of Brightness Temperature Resampled by Antenna Pattern Matching for Microwave Radiometer AMSR2 on GCOM-W1 Satellite |
| VerfasserIn |
Takashi Maeda, Keiji Imaoka |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250097628
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| Publikation (Nr.) |
 EGU/EGU2014-13229.pdf |
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| Zusammenfassung |
| The operation of the Advanced Microwave Scanning Radiometer for Earth-Observation
System (AMSR-E) loaded on Aqua satellite stopped in October, 2011 after more than 9-years
observation. But after that, the successor of AMSR-E (AMSR2) was developed and loaded on
GCOM-W1 (Global Change Observation Mission 1st - Water) satellite. GCOM-W1 satellite
was successfully launched in May, 2012. AMSR2 is a microwave radiometer almost similar
to AMSR-E, but some important improvements are made (i.e., expansion of its main
reflector’s size, addition of 7.3-GHz channel to detect radio frequency interferences at
6.9 GHz). GCOM-W1 satellite is deployed into a sun-synchronous sub-recurrent
orbit, and AMSR2 observes microwave powers emitted from anywhere on the Earth
almost twice a day, daytime in an ascending track and nighttime in a descending
track.
When we use a satellite-borne microwave radiometer data that have a main reflector
shared by plural feed horns, there is an inevitable problem, the differences of footprints’ sizes
among frequencies. In case of AMSR2, the smallest footprint’s size of 89 GHz (3 x 5 km2)
has just one percent of the broadest one of 6.9 GHz (35 x 62 km2). Under the circumstance,
when brightness temperatures (Tb values) of plural frequencies are obtained from the same
geolocation, it is difficult to compare them one another because their observation areas are
absolutely different.
The concept to solve this problem is simple: actually, after a satellite-borne microwave
radiometer observed on the Earth’s surface, footprints which give brightness temperatures of
each frequency densely distribute on it with overlaps at several-kilometer intervals (i.e., 5 km
as for 89 GHz and 10 km as for other frequencies in AMSR2). The footprint is an antenna
pattern projected to the Earth’s surface. The antenna pattern’s shape is generally
like a 2-dimensional Gaussian distribution. The center of the antenna pattern has
strong sensitivity, and its circumjacent part has weak sensitivity. Here, it can be
assumed to synthesize small antenna patterns of high frequency densely distributing in
a large antenna pattern of low frequency in order to emulate it. If well-modified
weighting coefficients of synthesized small antenna patterns are calculated, the
large antenna pattern can be accurately emulated by the small antenna patterns with
the weighting coefficients. The Tb values of the high frequency corresponding
to the small antenna patterns are then averaged with the weighting coefficients.
This averaged Tb represents the ‘resampled’ Tb of the high frequency virtually
measured in the large antenna pattern. The methodology of resampling by antenna
pattern matching based on this concept is known as the Backus-Gilbert method.
Since this methodology was proposed, many studies have been performed until
now.
For AMSR2, the dataset of Tb calibrated from a microwave power measured in a
footprint for each frequency is defined as a level 1B (L1B) product. On the top of that, that of
Tb resampled based on the Backus-Gilbert method is newly defined as a level 1R (L1R)
product to be released to public. In this presentation, we show the details of the current
implementation of the L1R product, some improvements planned in the next version upgrade,
and the validation results for the L1R product. |
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