Signal processing to denoise and retrieve water vapor from multi-pulse-length lidar data

Recent hardware developments for the MicroPulse DIAL enable the transmitter to switch between output pulses that are “longer” (higher pulse energy) and “shorter” (low pulse energy) in duration on a shot-to-shot basis. While the longer laser pulses broadly result in higher signal-to-noise ratio, they have the shortcoming of blanking the detector in the lowest ranges and smearing out the scene in range. Conversely, shorter pulses enable observations closer to the instrument, smear the scene relatively little, but have low signal-to-noise ratio. In this work, we show that leveraging Poisson Total Variation with forward modeling enables merged estimates of backscatter and water vapor. This signal processing technique leverages the advantages of each pulse length configuration, providing better data availability and higher resolution over a broader altitude range than data processed using only one of the pulse lengths. An intercomparison with radiosondes demonstrates that this new hardware configuration and processing approach enable retrievals of absolute humidity starting at 100 m extending up to 6 km, capturing complex water vapor structure throughout this range. The retrievals are also contrasted with ERA5 reanalysis which suggests that there are instances where the model and reanalysis products are unlikely to produce accurate representation of water vapor fields in the atmosphere, thus emphasizing the value of continuous, high-vertical-resolution active thermodynamic profiling observations.