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

Accurate and precise characterization of cirrus cloud geometrical and optical properties is essential for better constraining their radiative footprint. A lidar-based retrieval scheme is proposed here, with its performance assessed on fine spatio-temporal observations over the Arctic site of Ny-Ålesund, Svalbard. Two contributions related to cirrus geometrical (dynamic Wavelet Covariance Transform (WCT)) and optical properties (constrained Klett) are reported. The dynamic WCT rendered cirrus detection more robust, especially for thin cirrus layers that frequently remained undetected by the classical WCT method. Regarding optical characterization, we developed an iterative scheme for determining the cirrus lidar ratio (LRci) that is a crucial parameter for aerosol - cloud discrimination. Building upon the Klett-Fernald method, the LRci was constrained by an additional reference value. In established methods, such as the double-ended Klett, an aerosol-free reference value is applied. In the proposed constrained Klett, however, the reference value was approximated from cloud-free or low cloud optical depth (COD up to 0.2) profiles and proved to agree with independent Raman estimates. For optically thin cirrus, the constrained Klett inherent uncertainties reached 50% (60-74%) in terms of COD (LRci). However, for opaque cirrus COD (LRci) uncertainties were lower than 10% (15%). The detection method discrepancies (dynamic versus static WCT) had a higher impact on the optical properties of low COD layers (up to 90%) compared to optically thicker ones (less than 10%). The constrained Klett presented high agreement with two established retrievals. For an exemplary cirrus cloud, the constrained Klett estimated the COD355 (LRci355) at 0.28 ± 0.17 (29 ± 4 sr), the double-ended Klett at 0.27 ± 0.15 (32 ± 4 sr) and the Raman retrievals at 0.22 ± 0.12 (26 ± 11 sr). Our approach to determine