GNSS deep SNR retrievals of marine atmosphere boundary layer (MABL) specific humidity
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https://zenodo.org/record/13946111
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资源简介：
This folder contains 5 prediction files ended with *_v2.h5. These files can be loaded using the provided code "prediction_data_loader.py". All variables are in their respective physical units.
The *.tgz file contains the training and validation codes as well as sample training and validation datasets from METOP-B satellite. Please refer to the paper for details. All variables had been normalized in the training and validation datasets so no real physical meaning attached.
Reference:
Gong, J., Wu, D. L., Badalov, M., Ganeshan, M., and Zheng, M.: A Machine-learning Based Marine Planetary Boundary Layer (MPBL) Moisture Profile Retrieval Product from GNSS-RO Deep Refraction Signals, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-973, 2024.
NOTE: This paper is under revision for AMT. Please refer to the final publication for the most accurate details. The final paper link and doi will be updated in the top of the above egusphere publication.
POC: Jie.Gong@nasa.gov
10/17/2024
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创建时间：
2024-10-17
