Talks and Poster Presentations (with Proceedings-Entry):

W. Dorigo, K. Scipal, R. De Jeu, R. Parinussa, W. Wagner, V. Naeimi:
"Error characterisation of multiple sensor soil moisture data for improved long-term global soil moisture records";
Talk: Earth Observation and Water Cycle Science Symposium, Frascati, Italy; 2009-11-18 - 2009-11-20; in: "ESA Special Publications SP-674", (2009), ISBN: 978-92-9221-238-4; 6 pages.

English abstract:
In the framework of the Water Cycle Multi-mission
Observation Strategy (WACMOS) project of ESA, a
first multi-decadal (30+ years) global soil moisture
record is generated by merging data sets from various
active and passive microwave sensors. Combining
multiple data sets brings many advantages in terms of
enhanced temporal and spatial coverage and temporal
resolution. Nevertheless, to benefit from this strategy,
error budgets of the individual data sets have to be well
characterized, and apt strategies for reducing the errors
in the final product need to be developed.
This study exploits the triple collocation error
estimation technique to assess the error and systematic
biases between three different independent soil moisture
data sets: soil moisture data derived from the AMSR-E
radiometer, scatterometer based estimates from MetOp-
ASCAT, and modelled soil moisture from the ECMWF
ERA Interim reanalysis program. The results suggest
that the method provides realistic error estimates and
allow us to identify systematic differences between the
active and passive microwave derived soil moisture
products, e.g. with respect to varying land cover or
climatological zones. This in turn will help us in
developing adequate strategies for merging active and
passive observations for the generation of an accurate
long-term soil moisture data set.

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