RESUMEN
Atmospheric lidar observations provide a unique capability to directly observe the vertical column of cloud and aerosol scattering properties. Detector and solar-background noise, however, hinder the ability of lidar systems to provide reliable backscatter and extinction cross-section estimates. Standard methods for solving this inverse problem are most effective with high signal-to-noise ratio observations that are only available at low resolution in uniform scenes. This paper describes a novel method for solving the inverse problem with high-resolution, lower signal-to-noise ratio observations that are effective in non-uniform scenes. The novelty is twofold. First, the inferences of the backscatter and extinction are applied to images, whereas current lidar algorithms only use the information content of single profiles. Hence, the latent spatial and temporal information in noisy images are utilized to infer the cross-sections. Second, the noise associated with photon-counting lidar observations can be modeled using a Poisson distribution, and state-of-the-art tools for solving Poisson inverse problems are adapted to the atmospheric lidar problem. It is demonstrated through photon-counting high spectral resolution lidar (HSRL) simulations that the proposed algorithm yields inverted backscatter and extinction cross-sections (per unit volume) with smaller mean squared error values at higher spatial and temporal resolutions, compared to the standard approach. Two case studies of real experimental data are also provided where the proposed algorithm is applied on HSRL observations and the inverted backscatter and extinction cross-sections are compared against the standard approach.
RESUMEN
Iodine is an atmospheric trace element emitted from oceans that efficiently destroys ozone (O3). Low O3 in airborne dust layers is frequently observed but poorly understood. We show that dust is a source of gas-phase iodine, indicated by aircraft observations of iodine monoxide (IO) radicals inside lofted dust layers from the Atacama and Sechura Deserts that are up to a factor of 10 enhanced over background. Gas-phase iodine photochemistry, commensurate with observed IO, is needed to explain the low O3 inside these dust layers (below 15 ppbv; up to 75% depleted). The added dust iodine can explain decreases in O3 of 8% regionally and affects surface air quality. Our data suggest that iodate reduction to form volatile iodine species is a missing process in the geochemical iodine cycle and presents an unrecognized aeolian source of iodine. Atmospheric iodine has tripled since 1950 and affects ozone layer recovery and particle formation.
RESUMEN
The rarity of reports in the literature of brief and spatially limited observations of drizzle at temperatures below -20°C suggest that riming and other temperature-dependent cloud microphysical processes such as heterogeneous ice nucleation and ice crystal depositional growth prevent drizzle persistence in cold environments. In this study, we report on a persistent drizzle event observed by ground-based remote-sensing measurements at McMurdo Station, Antarctica. The temperatures in the drizzle-producing cloud were below -25°C and the drizzle persisted for a period exceeding 7.5 hours. Using ground-based, satellite, and reanalysis data we conclude that drizzle was likely present in parts of a widespread cloud field, which stretched more than ~1000 km along the Ross Ice Shelf coast. Parameter space sensitivity tests using two-moment bulk microphysics in large-eddy simulations constrained by the observations suggest that activated ice freezing nuclei (IFN) and accumulation-mode aerosol number concentrations aloft during this persistent drizzle period were likely on the order of 0.2 L-1 and 20 cm-3, respectively. In such constrained simulations, the drizzle moisture flux through cloud base exceeds that of ice. The simulations also indicate that drizzle can lead to the formation of multiple peaks in cloud water content profiles. This study suggests that persistent drizzle at these low temperatures may be common at the low aerosol concentrations typical of the Antarctic and Southern Ocean atmospheres.
RESUMEN
The Cloud System Evolution in the Trades (CSET) study was designed to describe and explain the evolution of the boundary layer aerosol, cloud, and thermodynamic structures along trajectories within the north-Pacific trade-winds. The study centered on 7 round-trips of the NSF NCAR Gulfstream V (GV) between Sacramento, CA and Kona, Hawaii between 1 July and 15 August 2015. The CSET observing strategy was to sample aerosol, cloud, and boundary layer properties upwind from the transition zone over the North Pacific and to resample these areas two days later. GFS forecast trajectories were used to plan the outbound flight to Hawaii with updated forecast trajectories setting the return flight plan two days later. Two key elements of the CSET observing system were the newly developed HIAPER Cloud Radar (HCR) and the High Spectral Resolution Lidar (HSRL). Together they provided unprecedented characterizations of aerosol, cloud and precipitation structures that were combined with in situ measurements of aerosol, cloud, precipitation, and turbulence properties. The cloud systems sampled included solid stratocumulus infused with smoke from Canadian wildfires, mesoscale cloud-precipitation complexes, and patches of shallow cumuli in very clean environments. Ultra-clean layers observed frequently near the top of the boundary layer were often associated with shallow, optically thin, layered veil clouds. The extensive aerosol, cloud, drizzle and boundary layer sampling made over open areas of the Northeast Pacific along 2-day trajectories during CSET is unprecedented and will enable modeling studies of boundary layer cloud system evolution and the role of different processes in that evolution.