Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks

Strandgren, Johan; Bugliaro, Luca; Sehnke, Frank; Schröder, Leon

doi:https://doi.org/10.5194/amt-10-3547-2017

Articles | Volume 10, issue 9

https://doi.org/10.5194/amt-10-3547-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/amt-10-3547-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 9

Research article

|

29 Sep 2017

Research article |

| 29 Sep 2017

Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks

Johan Strandgren, Luca Bugliaro, Frank Sehnke, and Leon Schröder

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

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.