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Aerosol And Cloud Classification With Layered Analysis.pdf

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Preview of Aerosol and Cloud Classification with Layered Analysis
🔗 Source: amt.copernicus.org
📊 Size: 55 KB
👤 Author: David Donovan
⬇️ Downloads: 24

Summary

The process involves iterating through multiple layers:

1. Layer Iteration: Loop through a specified number of layers.
2. Calculate Statistics: Calculate the mean and standard deviation (std) of all ATBs, scattering ratio, and depolarization ratio for each layer.
3. Aerosol and Cloud Flags:
- Set aerosol flags based on calculations.
- Classify layers as clouds and set confidence flags accordingly.
4. Temperature Checks:
- If average Ravg is greater than a threshold (mincloudRratio), and temperature T is above the melting point: set ice flag.
- If T is below the homogeneous freezing point, set water flag.
5. Depolarization Check: If internal depolarization/beta ratio falls below a threshold, perform further actions.
6. Tropopause Height Adjustment:
- Shift local tropopause height to the top or split layers if attached to a lower layer.
- Alternatively, shift it to the bottom layer or split if not attached.
7. Stratospheric Feature Setting: For layers above the tropopause height, set stratospheric feature flags.
8. Tropopause Proximity Check: Determine if a layer is close to the tropopause and adjust flags accordingly.

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Description

Iterate through layers, calculating mean ATB, std, scattering, and depolarization ratios. Set flags for cloud, ice, water, and stratospheric features based on temperature, optical depth, and tropopause proximity. Adjust tropopause height if layer is attached or close to it.

Technical Information

  • File Format: PDF
  • File Size: 55 KB
  • Pages: 1
  • Language: EN
  • Author: David Donovan
  • Total Downloads: 24
  • Last Updated: 11 hours ago

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This PDF document about Aerosol and Cloud Classification with Layered Analysis provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Aerosol and Cloud Classification with Layered Analysis.

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