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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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Atmos. Meas. Tech., 10, 3547-3573, 2017
https://doi.org/10.5194/amt-10-3547-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
29 Sep 2017
Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks
Johan Strandgren et al.

Data sets

CALIPSO/CALIOP Level 2, Lidar Cloud Layer Data, version 3.01
CALIPSO Science Team
https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmCLay-Prov-V3-01_L2-003.01
CALIPSO/CALIOP Level 2, Lidar Cloud Layer Data, version 3.02
CALIPSO Science Team
https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmCLay-Prov-V3-02_L2-003.02
CALIPSO/CALIOP Level 2, Lidar Aerosol Layer Data, version 3.01
CALIPSO Science Team
https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmALay-Prov-V3-01_L2-003.01
CALIPSO/CALIOP Level 2, Lidar Aerosol Layer Data, version 3.02
CALIPSO Science Team
https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_05kmALay-Prov-V3-02_L2-003.02
Publications Copernicus
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Short summary
The new algorithm CiPS is presented and validated. CiPS detects cirrus clouds, identifies opaque pixels and retrieves the corresponding optical thickness, cloud top height and ice water path from the geostationary imager MSG/SEVIRI. CiPS utilises a set of four artificial neural networks trained with space-borne lidar data, thermal MSG/SEVIRI observations, model data and auxiliary data. To demonstrate the capabilities of CiPS, the life cycle of a thin cirrus cloud is analysed.
The new algorithm CiPS is presented and validated. CiPS detects cirrus clouds, identifies opaque...
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