Robust calibration method for pure rotational Raman lidar temperature measurement

Area of Science:

• Atmospheric Science
• Remote Sensing
• Spectroscopy

Background:

• Accurate atmospheric temperature profiles are crucial for weather forecasting and climate monitoring.
• Pure rotational Raman lidar is a valuable remote sensing technique for temperature measurements.
• Existing calibration methods can be limited, especially under challenging signal conditions.

Purpose of the Study:

• To introduce and validate a new calibration method for pure rotational Raman lidar temperature measurements.
• To enhance the accuracy and reliability of lidar-derived temperature data.
• To reduce the performance demands on lidar systems for effective temperature retrieval.

Main Methods:

• Development of a calibration method incorporating a temperature-dependent term derived from radiosonde data.
• Calculation of a calibration factor to enable temperature retrieval from lidar signal intensity.
• Validation through simulations and experimental comparisons with existing techniques.

Main Results:

• The proposed method demonstrates improved calibration accuracy, particularly under low signal-to-noise ratio (SNR) conditions.
• Simulations and experiments confirm the effectiveness of the new calibration approach.
• The method successfully reduces the lidar system's performance requirements for accurate temperature retrieval.

Conclusions:

• The new calibration method offers a significant advancement for pure rotational Raman lidar temperature measurements.
• It enhances the applicability of lidar technology in environments with lower signal quality.
• This approach contributes to more robust and accessible atmospheric temperature profiling.