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@ARTICLE{Sakai:820885,
author = {Sakai, Toru and Iizumi, Toshichika and Okada, Masashi and
Nishimori, Motoki and Grünwald, Thomas and Prueger, John
and Cescatti, Alessandro and Korres, Wolfgang and Schmidt,
Marius and Carrara, Arnaud and Loubet, Benjamin and Ceschia,
Eric},
title = {{V}arying applicability of four different satellite-derived
soil moisture products to global gridded crop model
evaluation},
journal = {International journal of applied earth observation and
geoinformation},
volume = {48},
issn = {0303-2434},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2016-06149},
pages = {51 - 60},
year = {2016},
abstract = {Satellite-derived daily surface soil moisture products have
been increasingly available, but their applicability to
global gridded crop model (GGCM) evaluation is unclear. This
study compares four different soil moisture products with
the flux tower site observation at 18 cropland sites across
the world where either of maize, soybean, rice and wheat is
grown. These products include the first and second versions
of Climate Change Initiative Soil Moisture (CCISM-1 and
CCISM-2) datasets distributed by the European Space Agency
and two different AMSR-E (Advanced Microwave Scanning
Radiometer–Earth Observing System)-derived soil moisture
datasets, separately provided by the Japan Aerospace
Exploration Agency (AMSRE-J) and U.S. National Aeronautics
and Space Administration (AMSRE-N). The comparison
demonstrates varying reliability of these products in
representing major characteristics of temporal pattern of
cropland soil moisture by product and crop. Possible reasons
for the varying reliability include the differences in
sensors, algorithms, bands and criteria used when estimating
soil moisture. Both the CCISM-1 and CCISM-2 products appear
the most reliable for soybean- and wheat-growing area.
However, the percentage of valid data of these products is
always lower than other products due to relatively strict
criteria when merging data derived from multiple sources,
although the CCISM-2 product has much more data with valid
retrievals than the CCISM-1 product. The reliability of the
AMSRE-J product is the highest for maize- and rice-growing
areas and comparable to or slightly lower than the CCISM
products for soybean- and wheat-growing areas. The AMSRE-N
is the least reliable in most location-crop combinations.
The reliability of the products for rice-growing area is far
lower than that of other upland crops likely due to the
extensive use of irrigation and patch distribution of rice
paddy in the area examined here. We conclude that the
CCISM-1, CCISM-2 and AMSRE-J products are applicable to GGCM
evaluation, while the AMSRE-N product is not. However, we
encourage users to integrate these products with in situ
soil moisture data especially when GGCMs simulations for
rice are evaluated.},
cin = {IBG-3},
ddc = {550},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {255 - Terrestrial Systems: From Observation to Prediction
(POF3-255)},
pid = {G:(DE-HGF)POF3-255},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000372682300006},
doi = {10.1016/j.jag.2015.09.011},
url = {https://juser.fz-juelich.de/record/820885},
}