Spaceborne Lidar Estimates of PBL Height Over the Continental US

Understanding the global diurnal variation of the Planetary Boundary Layer Height (PBLH) poses a significant challenge due to the need for extensive observations and adaptable retrieval algorithms capable of handling diverse thermodynamic and dynamic conditions. This study leveraged data from the Cloud-Aerosol Transport System (CATS), a spaceborne backscatter lidar that operated on the International Space Station (ISS), enabling the statistical retrieval of the PBLH diurnal variability on a near-global scale. By utilizing a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm and a machine learning denoising technique on the CATS data, we analyzed the diurnal variation of the PBLH in the U.S. Southern Great Plains. The PBLH calculated with DTDS using CATS closely corresponded with retrievals from ground-based lidar and radiosonde measurements, indicating a strong correlation. The diurnal variability of CATS DTDS-PBLH and ground-based DTDS-PBLH aligned well, albeit with a slight overestimation during nighttime. Comparison of the CATS PBLH product against radiosonde estimates showed similar diurnal variations but with a slightly higher overestimation at nighttime. Additionally, the study investigated the importance of integrating simultaneous meteorological information with lidar signals and underscored the significance of incorporating meteorological information with spaceborne lidar signals to achieve more accurate and robust PBLH diurnal variation estimates.