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IceCloudNet: 3D reconstruction of cloud ice from Meteosat SEVIRI - data

Identifier

Summary

IceCloudNet is a novel method based on machine learning able to obtain high-
quality vertically resolved predictions for ice water content and ice crystal number concentration of clouds containing ice.

Project

IceCloudNet (IceCloudNet: 3D reconstruction of tropical cloud ice from Meteosat SEVIRI)

Authors

Jeggle, Kai; Czerkawski, Mikolaj; Serva, Federico; Le Saux, Bertrand; Neubauer, David; Lohmann, Ulrike

Keywords

cirrus clouds
clouds
deep learning
deep learning-based 3D reconstruction
machine learning

Creation Date

2024-05-07

Temporal Coverage

2010-03 TO 2010-08

Spatial Coverage

Longitude: -30.00, 30.00 Latitude: -30.00, 30.00

Status

will be continued

[Entry acronym: IceCloudNet_3Drecon] [Entry id: 5275192] [ Score: 22.29712]

IceCloudNet: 3D reconstruction of tropical cloud ice from Meteosat SEVIRI (2010)

Dataset

Project

IceCloudNet (IceCloudNet: 3D reconstruction of tropical cloud ice from Meteosat SEVIRI)

Variables

mass_concentration_of_frozen_water_in_air
number_concentration_of_ice_crystals_in_air (larger than 5um)

Aggregation

15min

Creation Date

2024-05-07

Temporal Coverage

2010-03 TO 2010-08

Spatial Coverage

Longitude: -30.00, 30.00 Latitude: -30.00, 30.00

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Status

will be continued

Datasize

1.68 TiB (1844081239931 Byte)

Format

NetCDF

[Entry acronym: IceCloudNet_3Drecon_2010] [Entry id: 5275193] [ Score: 1.5891507]

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