Continuous water vapor and temperature profiles are critically needed for improved
understanding of the lower atmosphere and potential advances in weather forecasting skill …

The lidar is susceptible to the dark current of the detector and the background light during
the measuring process, which results in a significant amount of noise in the lidar return …

In this study, we explore the utilization of penalized likelihood estimation for the analysis of
sparse photon counting data obtained from distributed target lidar systems. Specifically, we …

We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse
DIAL such that the retrieval is entirely self contained. The only external input is surface …

The micropulse differential absorption lidar (MPD) was developed at Montana State
University (MSU) and the National Center for Atmospheric Research (NCAR) to perform …

Repetitive, high spatial resolution measurements of water vapor are highly desirable for a
range of critical applications, including quantitative forecasts of wildfire risk forecasting …

The pure rotational Raman (PRR) lidar technique relies on calibration functions (CFs) to
extract temperature information from raw detection data. The choice of CF significantly …

In response to a community-identified need for ground-based thermodynamic (TD) profiling
of the troposphere, we present the further development and validation of a differential …

To reduce noise in the lidar return signal, an improved deep belief network (DBN) denoising
algorithm is proposed in this study. In the traditional implementation process of DBN, a multi …