Characteristics and seasonal variations of cirrus clouds from ground-based lidar and satellite observations over Shouxian Area, China.

This study investigates the macroscopic and optical properties of cirrus clouds in the 32N region from July 2016 to May 2017, leveraging data from ground-based lidar observations and CALIOP to overcome the inconsistencies in detected cirrus cloud samples. Through extensive data analysis, statistical characteristics of cirrus clouds were discerned, revealing lidar ratio values of 28.5 ± 10.8 from ground-based lidar and 27.4 ± 11.2 from CALIOP. Validation with a decade of CALIOP data (2008-2018) confirmed these findings, presenting a consistent lidar ratio of 27.4 ± 12.0. A significant outcome of the analysis was the identification of a positive correlation between the lidar ratio and cloud centroid temperature, indicating a gradual decrease in the lidar ratio as temperatures dropped. The study established a fundamental consistency in their macroscopic properties, including cloud base height, cloud top height, cloud thickness, cloud centroid height, and cloud centroid temperature. The results for ground-based lidar (CALIOP) are: 10.0 ± 2.1 km (10.0 ± 2.2 km), 11.8 ± 2.1 km (11.5 ± 2.3 km), 1.87 ± 0.83 km (1.52 ± 0.71 km), and 10.5 ± 2.2 km, -46.9 ± 9.7°C (-47.1 ± 10.0°C).These properties exhibited seasonal variations, with cirrus clouds reaching higher altitudes in summer and lower in winter, influenced by the height of the tropopause. The optical properties of cirrus clouds were also analyzed, showing an annual average optical depth of 0.31 ± 0.35 for ground-based lidar and 0.32 ± 0.44 for CALIOP. The study highlighted the distribution of subvisible, thin, and thick cirrus clouds, with a notable prevalence of subvisible clouds during summer, suggesting their frequent formation above 14 km. Furthermore, the study observed linear growth in geometric thickness and optical depth up to 2.5 km from CALIOP and 2.9 km from ground-based lidar. Maximum optical depth was observed at cloud centroid temperatures of -35°C for CALIOP and -40°C for ground-based lidar, with optical depth decreasing as temperatures fell. This suggests that fully glaciated cirrus clouds exhibit the highest optical depth at warmer temperatures, within the complete glaciation temperature range of -35°C to -40°C.

Lidar signal processing method for atmospheric coherence length measurement based on the WD-ADMF.

A denoising method applied to atmospheric coherent length lidar is proposed. Wavelet decomposition (WD) and the adaptive median filter (ADMF) are combined in this method. In this research, the effectiveness of the WD-ADMF has been verified through simulation and measurement. The results show that this filter algorithm, when applied to lidar data, improves the average peak signal-to-noise ratio (PSNR) and centroid error while maintaining data integrity such that the measurement of coherence length or the inference of C n2 from coherence length more closely matches simulated truth and measured data.

Protocol for high-throughput single-cell patterning using a reusable ultrathin metal microstencil.

Exploiting convenient strategies for single-cell preparation while maintaining a high throughput remains challenging. This protocol describes a simple workflow for high-throughput single-cell patterning using a reusable ultrathin metal microstencil (UTmS). We describe UTmS-chip design, fabrication, and quality characterization. We then detail the preparation of flat substrates and chip assembly for single-cell patterning, followed by culturing of cells on a chip. Finally, we describe the evaluation of single-cell patterning and the downstream applications for studying single-cell calcium release and apoptosis. For complete details on the use and execution of this protocol, please refer to Song et al. (2021).1.