Saito (2026) A Pathway Toward the Retrievals of the Microphysical Properties of Mixed-Phase Clouds Using Airborne Radar-Lidar Observation

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Identification

• Journal: Springer Link (Chiba Institute of Technology)
• Year: 2026
• Date: 2026-04-09
• Authors: Masanori Saito
• DOI: 10.1051/epjconf/202636210005/pdf

Research Groups

Not explicitly stated in the provided text.

Short Summary

This study develops a radar-lidar remote sensing algorithm, incorporating a robust optical property model, to characterize mixed-phase clouds, demonstrating its ability to accurately determine ice/liquid fraction, total water content, and effective radii of hydrometeors.

Objective

• To develop and evaluate a radar-lidar remote sensing algorithm, enhanced by a new optical property model, for the characterization of mixed-phase cloud hydrometeor properties.

Study Configuration

• Spatial Scale: Not explicitly stated in the provided text, but implies atmospheric column measurements.
• Temporal Scale: Not explicitly stated in the provided text, but implies instantaneous or short-term characterization for algorithm development and testing.

Methodology and Data

• Models used: Optical property model of mixed-phase cloud hydrometeors, Radar-lidar remote sensing algorithm.
• Data sources: Radar measurements, Lidar measurements (used for algorithm development and sensitivity tests).

Main Results

• A robust optical property model for mixed-phase cloud hydrometeors was developed and integrated into a radar-lidar remote sensing algorithm.
• Sensitivity tests demonstrated that the algorithm can characterize ice/liquid fraction, total water content, and ice crystal effective radius with reasonable accuracy.
• The algorithm can characterize liquid droplet effective radius with fair accuracy.

Contributions

• Development of a novel radar-lidar remote sensing algorithm that integrates a robust optical property model based on advanced light-scattering theory.
• Enables improved characterization of mixed-phase cloud hydrometeor properties (ice/liquid fraction, total water content, and effective radii) with quantified accuracy.
• Advances the interpretation of combined radar-lidar signals for mixed-phase clouds, addressing challenges in climate projections.

Funding

Not explicitly stated in the provided text.

Citation

@article{Saito2026Pathway,
  author = {Saito, Masanori},
  title = {A Pathway Toward the Retrievals of the Microphysical Properties of Mixed-Phase Clouds Using Airborne Radar-Lidar Observation},
  journal = {Springer Link (Chiba Institute of Technology)},
  year = {2026},
  doi = {10.1051/epjconf/202636210005/pdf},
  url = {https://doi.org/10.1051/epjconf/202636210005/pdf}
}