Mukherjee et al. (2026) Estimating Cloud Base Height via Shadow-Based Remote Sensing

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Lipi Mukherjee, Dong L. Wu
• DOI: 10.3390/rs18010147

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study evaluates a shadow-based method for retrieving cloud base height (CBH) from MODIS satellite imagery, validating it against lidar measurements from MPLNET ground stations, and demonstrates strong agreement (R = 0.96) for shallow cumulus clouds.

Objective

• To evaluate a shadow-based cloud base height (CBH) retrieval method using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite visible imagery and compare the results against collocated lidar measurements from the Micro-Pulse Lidar Network (MPLNET) ground stations.

Study Configuration

• Spatial Scale: Global (potential for MODIS data), validated at specific ground station locations.
• Temporal Scale: Applicable for diurnal studies and across archived datasets.

Methodology and Data

• Models used: Shadow-based CBH retrieval method leveraging sun–sensor geometry.
• Data sources: Moderate Resolution Imaging Spectrospectroradiometer (MODIS) satellite visible imagery, Micro-Pulse Lidar Network (MPLNET) ground station lidar measurements.

Main Results

• The shadow-based CBH retrieval method showed strong agreement with lidar-derived CBH estimates.
• A high correlation coefficient (R) of 0.96 was found between the shadow-based and lidar-derived CBH estimates.
• The approach was confirmed to be robust for shallow, isolated cumulus clouds.
• Advantages include direct physical height estimation without reliance on cloud top heights or stereo imaging, applicability across archived datasets, and suitability for diurnal studies.

Contributions

• Validates a practical, high-resolution passive remote sensing technique for cloud base height estimation.
• Offers a reliable and cost-effective tool for global low cloud monitoring, particularly useful in regions lacking active sensors.
• Provides a method applicable to archived datasets, enabling historical and diurnal studies of low clouds.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Mukherjee2026Estimating,
  author = {Mukherjee, Lipi and Wu, Dong L.},
  title = {Estimating Cloud Base Height via Shadow-Based Remote Sensing},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18010147},
  url = {https://doi.org/10.3390/rs18010147}
}