nasa / nasa/HyperCP

Anomalous radiance bump at 620 nm in cloudy conditions

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Dominant language
Python
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Description

Our research group uses a pySAS system with HyperOCR radiometers in the Laurentian Great Lakes. After the 2025 field season, we had our radiometers calibrated and characterized at the University of Tartu. When re-processing the 2025 data, we still observed the anomalous radiance bumps around 620 nm that had previously been brought up in #345. They only seem to appear in the more oligotrophic waters that we sample in and only when the L_sky sensor shows cloud contamination.

We have processed the data with HyperCP using both the class-based and sensor-specific processing regimes, and the feature is visible in both with the sensor-specific processing appearing slightly worse. Here is an example showing the derived reflectance using the class-based approach (CS pySAS), the sensor-specific approach (SS pySAS), and the reflectance from our handheld radiometer (ASD FieldSpec 4) at one discrete station from April 2025.
Image

I have put the raw file, HyperCP config file, and .sip used as inputs to HyperCP, as well as the generated reports for both class-based and sensor-specific runs, in a Drive folder available here:
https://drive.google.com/drive/folders/1uGs-wDUiU2q2sdMpnJAMD0bxZLPdJ0HO?usp=sharing

Thanks,
Karl

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the supplied raw file, HyperCP configuration, .sip input, and generated reports, then compare the class-based and sensor-specific results around 620 nm under cloud-contaminated L_sky conditions. Review issue #345 for prior investigation and use the ASD FieldSpec 4 comparison as the reference; done means identifying the processing cause and confirming the anomalous bump is resolved or consistently explained in both regimes.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
45/100

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