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Talks and Poster Presentations (without Proceedings-Entry):

V. Naeimi, W. Wagner, Z. Bartalis, S. Hasenauer:
"One year of ASCAT soil moisture data";
Poster: Catchment-scale Hydrological Modelling & Data Assimilation International Workshop (CAHMDA-III Workshop), Melbourne, Australia; 2008-01-09 - 2008-01-11.



English abstract:
The ASCAT (Advanced SCATterometer) instrument onboard MetOp (Meteorological operational)
satellite series, which have jointly developed by ESA and EUMETSAT, is a real-aperture radar
operating at 5.255 GHz (C-band) with high radiometric resolution and stability. The ASCAT is in
the heritage of the successful scatterometers flown on the ERS-1 and ERS-2 satellites. Like the ERS
scatterometers, the ASCAT measures a triplet of averaged backscatter signals per each
measurement node from three different looking directions using vertically polarized antennas
oriented to broadside and 45 of broadside. The new instrument has the advantage of supplying
information more than twice as much as the previous scatterometers per orbit and will be able to
provide quasi-global data coverage over two swaths instead of one. Unlike passive instruments,
ASCAT performance is hardly affected by cloud cover or solar illumination so it can be used
effectively in all-weather conditions. The ASCAT offers a unique tool for operational meteorology
and long-term climate studies with a near global coverage within 24 hours, and mission continuity
for a minimum of 14 years (a series of three MetOp satellites was planned in EPS program1).
The primary objective of the ASCAT is to derive wind vectors over the ocean surface. In addition to
the classical wind product, scatterometer data has proved to be very useful in land surface studies
making this instrument of great importance for many purposes. An attractive land application of
scatterometers is their ability to detect soil moisture variations. The original product of
scatterometers is the radar backscattering coefficient of the earth surface. The backscattering
coefficient measured with scatterometers from the land surface depends on the surface roughness,
texture, soil moisture, vegetation cover, and the incidence angle. Water has a considerably high
dielectric constant in comparison to the other natural substances. Therefore increasing the fraction
of water contained in soil and vegetation increases the dielectric constant thereby alters significantly
the scattering behavior.
A soil moisture retrieval model using a change detection method based on a long-term scatterometer
time series was presented by Wagner 1999. On the basis of this model a processing software
package called WARP (soil WAter Retrieval Package) is developed at the Institute of
Photogrammetry and remote Sensing (IPF) at Vienna University of Technology (TU Wien). In TU
Wien model, ERS-1 and ERS-2 scatterometers historical data are used to model incidence angle
dependency of backscattering signal. Then the backscatter coefficients are extrapolated to a
reference incidence angle. In this way, the normalized backscattering coefficient will contain
information about soil state assuming that the surface roughness and texture are stable over time.
In this study we present recent improvements in WARP together with the results of relative surface
soil moisture derivation from one-year ASCAT data. An early validation of dataset illustrates good
potential of the ASCAT soil moisture measurements to detect several cases of drought and extreme
rainfall events. The long term availability of the ASCAT data with high daily coverage assures a
valuable soil moisture dataset for hydrological applications in near future.

Keywords:
ASCAT, scatterometer, soil moisture

Created from the Publication Database of the Vienna University of Technology.