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Lidar multiple scattering measurements provide the probability distribution of the distance laser light travels inside snow. Based on an analytic two-stream radiative transfer solution, the present study demonstrates why/how these lidar measurements can be used to derive snow depth and snow density. In particular, for a laser wavelength with little snow absorption, an analytical radiative transfer solution is leveraged to prove that the physical snow depth is half of the average distance photons travel inside snow and that the relationship linking lidar measurements and the extinction coefficient of the snow is valid. Theoretical formulas that link lidar measurements to the extinction coefficient and the effective grain size of snow are provided. Snow density can also be derived from the multi-wavelength lidar measurements of the snow extinction coefficient and snow effective grain size. Alternatively, lidars can provide the most direct snow density measurements and the effective discrimination between snow and trees by adding vibrational Raman scattering channels.

Abstract Remote sensing from Earth‐observing satellites is now providing valuable information about ocean phytoplankton distributions. This paper presents the new ocean subsurface optical properties obtained from two space‐based lidars: the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite and the Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and land Elevation Satellite‐2 satellite. Obtaining reliable estimates of subsurface biomass necessitates removing instrument artifacts peculiar to each sensor, that is, polarization crosstalk artifacts in the CALIOP signals and after pulsing effects arising from the ATLAS photodetectors. We validate the optical properties derived from the corrected lidar backscatter signals using MODerate‐resolution Imaging Spectroradiometer ocean color measurements and autonomous biogeochemical Argo float profiles. Our results support the continued use of present and future spaceborne lidars to study the global plankton system and characterize its vertical structures in the upper ocean.

A neural-network algorithm that uses CALIPSO lidar measurements to infer droplet effective radius, extinction coefficient, liquid-water content, and droplet number concentration for water clouds is described and assessed. These results are verified against values inferred from High-Spectral-Resolution Lidar (HSRL) and Research Scanning Polarimeter (RSP) measurements made on an aircraft that flew under CALIPSO. The global cloud microphysical properties are derived from 14+ years of CALIPSO lidar measurements, and the droplet sizes are compared to corresponding values inferred from MODIS passive imagery. This new product will provide constraints to improve modeling of Earth’s water cycle and cloud-climate interactions.

Abstract The Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and land Elevation Satellite‐2 (ICESat‐2) has been making very high resolution measurements of the Earth’s surface elevation since October 2018. ATLAS uses photomultiplier tubes (PMTs) as detectors in photon counting mode, so that a single photon reflected back to the receiver triggers a detection within the ICESat‐2 data acquisition system. However, one characteristic of ICESat‐2 detected photons is the possible presence of afterpulses, defined as small amplitude pulses occurring after the primary signal pulse due to photon arrival. The disadvantage of these afterpulses is that they often confound the accurate measurements of low level signals following a large amplitude of signal and can degrade energy resolution and cause errors in pulse counting applications. This paper discusses and summarizes the after‐pulsing effects exhibited by the ATLAS PMTs based on on‐orbit measurements over different seasons and geographic regions. The potential impacts of these after‐pulsing effects on altimetry and ocean subsurface retrievals are discussed.

Recent studies indicate that the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite provides valuable information about ocean phytoplankton distributions. CALIOP’s attenuated backscatter coefficients, measured at 532 nm in receiver channels oriented parallel and perpendicular to the laser’s linear polarization plane, are significantly improved in the Version 4 data product. However, due to non-ideal instrument effects, a small fraction of the backscattered optical power polarized parallel to the receiver polarization reference plane is misdirected into the perpendicular channel, and vice versa. This effect, known as polarization crosstalk, typically causes the measured perpendicular signal to be higher than its true value and the measured parallel signal to be lower than its true value. Therefore, the ocean optical properties derived directly from CALIOP’s measured signals will be biased if the polarization crosstalk effect is not taken into account. This paper presents methods that can be used to estimate the CALIOP crosstalk effects from on-orbit measurements. The global ocean depolarization ratios calculated both before and after removing the crosstalk effects are compared. Using CALIOP crosstalk-corrected signals is highly recommended for all ocean subsurface studies.