Enabling High-Resolution Measurements at Cloud Boundaries Using Photon Counting

Measurements of atmospheric targets that exhibit high-density backscatter intensities, like those observed at cloud boundaries, are very challenging for lidars that employ photon counting. This is because photon counting detectors exhibit a nonlinear bias known as deadtime, in which high-density backscatter signals can saturate the detector. Unfortunately, the traditional deadtime correction used in atmospheric lidar is limited to scenes that are (1) acquired using coarse sampling bins (> 10 m, typically) and (2) uniform over the sampling bin, meaning it fails to accurately recover the dynamics and heterogeneity that cloud boundaries exhibit, posing a significant challenge.

We present a novel deadtime correction technique (DCT) that overcomes these limitations, permitting high spatial- and temporal-resolution measurements at high (and low) flux. By combining the DCT with a fast pulse-rate transmitter (15 kHz) and ultra-high-resolution time-tag acquisition system (25 ps), lidar now has the potential to provide observations at unprecedented spatial and temporal scales required to investigate cloud structure and dynamics. In this study, we seek to assess the impact that over-smoothing (in time and range) has on accuracy and quantify the required precision to accurately interrogate cloud boundary structure, which will help inform and constrain cloud formation processes.

This novel approach will be evaluated through simulations of backscatter measurements of cloud boundaries that exhibit realistic dynamics and heterogeneity. The technique will also be shown on actual cloud measurements at ultra-high range and temporal resolution, using an elastic backscatter lidar system at CU Boulder. We will also discuss future development of the system and technique.