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  1. Data from: C³ONTEXT: A Common Consensus on Convective OrgaNizaTion during...

    • zenodo.org
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    Updated Sep 30, 2022
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    Hauke Schulz; Hauke Schulz (2022). C³ONTEXT: A Common Consensus on Convective OrgaNizaTion during the EUREC⁴A eXperimenT [Dataset]. http://doi.org/10.5281/zenodo.5979718
    Explore at:
    zipAvailable download formats
    Unique identifier
    https://doi.org/10.5281/zenodo.5979718
    Dataset updated
    Sep 30, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Hauke Schulz; Hauke Schulz
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset contains the manual cloud classifications of the EUREC4A field campaign time period as well as the post-processed data.

    The dataset is organised as following:

    • zooniverse_raw: Originial output data from the platform zooniverse.org which has been used to create the classifications
    • processed_data:
      • Level1: EUREC4A_ManualClassifications_l1.nc: Geographical and Cartesian coordinates are added to each label

      • Level2: EUREC4A_ManualClassifications_l2.zarr: labels are converted to masks and combined for each classification

      • Level3: EUREC4A_ManualClassifications_l3_$WORKFLOW_$COMPOSITE.zarr: pixel-agreement among users/classifiers on each of the four meso-scale cloud patterns for daily composites and individual scenes.

    • auxiliary_data:

      • EUREC4A_AuxiliaryData_NeuralNetworkClassifications.zip/GOES16_CH13_classifications_EUREC4A_30min.zarr: neural network classifications based on GOES-16 Advanced Baseline Imager (ABI) channel 13 (infrared) @ 30 minute intervals.

      • EUREC4A_AuxiliaryData_IorgSMetrics.zip/GOES16_IR_nc_Iorg_EUREC4A_10-20_-58--48.nc: Organisation index (Iorg) and mean cloud cluster size (S) derived from GOES-16 ABI infrared images of the domain 10-20N 58-48W.

    An example how to use the data can be found at github.com/observingClouds/EUREC4A_manualclassifications.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Hauke Schulz; Hauke Schulz (2022). C³ONTEXT: A Common Consensus on Convective OrgaNizaTion during the EUREC⁴A eXperimenT [Dataset]. http://doi.org/10.5281/zenodo.5979718
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Data from: C³ONTEXT: A Common Consensus on Convective OrgaNizaTion during the EUREC⁴A eXperimenT

Related Article
Explore at:
3 scholarly articles cite this dataset (View in Google Scholar)
zipAvailable download formats
Unique identifier
https://doi.org/10.5281/zenodo.5979718
Dataset updated
Sep 30, 2022
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Hauke Schulz; Hauke Schulz
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

This dataset contains the manual cloud classifications of the EUREC4A field campaign time period as well as the post-processed data.

The dataset is organised as following:

  • zooniverse_raw: Originial output data from the platform zooniverse.org which has been used to create the classifications
  • processed_data:
    • Level1: EUREC4A_ManualClassifications_l1.nc: Geographical and Cartesian coordinates are added to each label

    • Level2: EUREC4A_ManualClassifications_l2.zarr: labels are converted to masks and combined for each classification

    • Level3: EUREC4A_ManualClassifications_l3_$WORKFLOW_$COMPOSITE.zarr: pixel-agreement among users/classifiers on each of the four meso-scale cloud patterns for daily composites and individual scenes.

  • auxiliary_data:

    • EUREC4A_AuxiliaryData_NeuralNetworkClassifications.zip/GOES16_CH13_classifications_EUREC4A_30min.zarr: neural network classifications based on GOES-16 Advanced Baseline Imager (ABI) channel 13 (infrared) @ 30 minute intervals.

    • EUREC4A_AuxiliaryData_IorgSMetrics.zip/GOES16_IR_nc_Iorg_EUREC4A_10-20_-58--48.nc: Organisation index (Iorg) and mean cloud cluster size (S) derived from GOES-16 ABI infrared images of the domain 10-20N 58-48W.

An example how to use the data can be found at github.com/observingClouds/EUREC4A_manualclassifications.

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