Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-267-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-267-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Department of Civil and Environmental Engineering, University of Perugia, Perugia, Italy
Christian Massari
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Luca Brocca
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
Alexander Gruber
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Department of Earth and Environmental Sciences, KU Leuven, Heverlee, 3001, Belgium
Christoph Reimer
Earth Observation Data Centre, Vienna, Austria
Sebastian Hahn
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Christoph Paulik
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Vandersat B.V., Haarlem, the Netherlands
Wouter Dorigo
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
Richard Kidd
Earth Observation Data Centre, Vienna, Austria
Wolfgang Wagner
Department of Geodesy and Geoinformation, TU Wien, Vienna, Austria
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Short summary
In this study, rainfall is estimated starting from satellite soil moisture observation on a global scale, using the ESA CCI soil moisture datasets. The new obtained rainfall product has proven to correctly identify rainfall events, showing performance sometimes higher than those obtained by using classical rainfall estimation approaches.
In this study, rainfall is estimated starting from satellite soil moisture observation on a...
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