www.geodatenkatalog.de (S1L)
IceCloudNet: 3D reconstruction of cloud ice from Meteosat SEVIRI - data
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. The predictions come at the spatio-temporal coverage and resolution of Meteosat SEVIRI and the vertical resolution of DARDAR. IceCloudNet consists of a ConvNeXt-based U-Net and a 3D PatchGAN discriminator model and is trained by predicting DARDAR profiles from co-located SEVIRI images. Despite the sparse availability of DARDAR data due to its narrow overpass, IceCloudNet is able to predict cloud occurrence, macrophysical shape, and microphysical properties with high precision.
We release 5 years of vertically resolved ice water content (IWC) and ice crystal number concentration (Nice) of clouds containing ice with a 3 km×3 km×240 m×15 minute resolution on a spatial domain of 30°W to 30°E and 30°S to 30°N. The resulting data set increases the availability of vertical cloud profiles for the period when DARDAR is available by more than six orders of magnitude and moreover, is able to provide vertical cloud profiles beyond the lifetime of the recently ended satellite missions underlying DARDAR.
|
|
Citation proposal
(2024) . IceCloudNet: 3D reconstruction of cloud ice from Meteosat SEVIRI - data. https://gdk.gdi-de.org/geonetwork/srv/api/records/wdc-climate.de:5275192 |
INSPIRE
Identification
- File identifier
- wdc-climate.de:5275192 XML
- Hierarchy level
- collection collection
Online resource
Resource identifier
- code
- IceCloudNet_3Drecon
- code
- doi:10.26050/WDCC/IceCloudNet_3Drecon
- Metadata language
- eng; USA
Encoding
- Format
- NetCDF
Projection
Classification of data and services
Classification of data and services
Coupled resource
Coupled resource
Classification of data and services
Coupled resource
Coupled resource
Keywords
Other keywords
- Keywords
-
- cirrus clouds
- Keywords
-
- clouds
- Keywords
-
- deep learning
- Keywords
-
- deep learning-based 3D reconstruction
- Keywords
-
- machine learning
- Keywords
-
- mixed-phase clouds
- Keywords
-
- neural rendering
- Keywords
-
- remote sensing
- Keywords
-
- vertical reconstruction
Geographic coverage
))
Temporal reference
Temporal extent
Temporal extent
- Date ( Publication )
- 2024-10-09
Quality and validity
Conformity
Conformity
Conformity
Conformity
Conformity
Conformity
Restrictions on access and use
Restrictions on access and use
Responsible organization (s)
Contact for the resource
- Organisation name
- ETH Zürich
- Organisation name
- ETH Zürich
Responsible organization (s)
Contact for the resource
- Organisation name
- ETH Zürich
- Organisation name
- ETH Zürich
Metadata information
Contact for the metadata
- Organisation name
- ETH Zürich
- Organisation name
- ETH Zürich
- Date stamp
- 2024-05-07T10:54:06
- Metadata language
- eng; USA
SDS
Conformance class 1: invocable
Access Point URL
Endpoint URL
Technical specification
Conformance class 2: interoperable
Coordinate reference system
Quality of Service
Access constraints
Limitation
Use constraints
Limitation
Responsible custodian
Contact for the resource
Conformance class 3: harmonized
Overviews
Provided by
