An extended lidar-based cirrus cloud retrieval scheme: first application over an Arctic site

Area of Science:

• Atmospheric Science
• Remote Sensing
• Cloud Physics

Background:

• Accurate characterization of cirrus cloud geometrical and optical properties is vital for refining climate models.
• Existing lidar-based methods face challenges in robustly detecting thin cirrus and precisely retrieving optical properties.
• The cirrus lidar ratio (LRci) is a critical parameter for aerosol-cloud discrimination, but its accurate determination is challenging.

Purpose of the Study:

• To propose and validate a novel lidar-based retrieval scheme for enhanced cirrus cloud characterization.
• To improve the detection of thin cirrus layers using a dynamic Wavelet Covariance Transform (WCT) method.
• To develop a constrained Klett retrieval for more accurate cirrus optical depth (COD) and lidar ratio (LRci) estimation.

Main Methods:

• Employed a dynamic Wavelet Covariance Transform (WCT) for improved cirrus cloud detection, particularly for thin layers.
• Developed a constrained Klett iterative scheme to determine the cirrus lidar ratio (LRci), using a reference value derived from clear or low cloud profiles.
• Assessed the performance of the proposed scheme using fine spatio-temporal lidar observations from Ny-Ålesund, Svalbard, and corrected for multiple scattering effects.

Main Results:

• The dynamic WCT significantly improved the detection of thin cirrus clouds compared to the classical WCT.
• The constrained Klett method yielded COD and LRci uncertainties below 10% (15%) for opaque cirrus, and within 50% (60-74%) for optically thin cirrus.
• The constrained Klett method showed high agreement with established double-ended Klett and Raman retrievals, outperforming the classical aerosol-free assumption which overestimated LRci.

Conclusions:

• The proposed dynamic WCT and constrained Klett retrieval scheme offer a more robust and accurate method for cirrus cloud characterization using lidar.
• The approach for determining the reference value in the constrained Klett method can enhance the accuracy of established retrieval techniques.
• Accurate cirrus property retrievals are essential for improving the representation of their radiative footprint in climate models.