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Optical properties and precipitation efficiency of atmospheric clouds are largely determined by turbulent mixing with their environment. When cloud liquid water is reduced upon mixing, droplets may evaporate uniformly across the population or, in the other extreme, a subset of droplets may evaporate completely, leaving the remaining drops unaffected. Here, we use airborne holographic imaging to visualize the spatial structure and droplet size distribution at the smallest turbulent scales, thereby observing their response to entrainment and mixing with clear air. The measurements reveal that turbulent clouds are inhomogeneous, with sharp transitions between cloud and clear air properties persisting to dissipative scales (<1 centimeter). The local droplet size distribution fluctuates strongly in number density but with a nearly unchanging mean droplet diameter.

A water vapor micropulse differential absorption lidar (DIAL) instrument was developed collaboratively by the National Center for Atmospheric Research (NCAR) and Montana State University (MSU). This innovative, eye-safe, low-power, diode-laser-based system has demonstrated the ability to obtain unattended continuous observations in both day and night. Data comparisons with well-established water vapor observing systems, including radiosondes, Atmospheric Emitted Radiance Interferometers (AERIs), microwave radiometer profilers (MWRPs), and ground-based global positioning system (GPS) receivers, show excellent agreement. The Pearson’s correlation coefficient for the DIAL and radiosondes is consistently greater than 0.6 from 300 m up to 4.5 km AGL at night and up to 3.5 km AGL during the day. The Pearson’s correlation coefficient for the DIAL and AERI is greater than 0.6 from 300 m up to 2.25 km at night and from 300 m up to 2.0 km during the day. Further comparison with the continuously operating GPS instrumentation illustrates consistent temporal trends when integrating the DIAL measurements up to 6 km AGL.

Accurate measurement of the mixed layer height (MLH) is a key observational capability necessary for many studies in weather forecasting, air quality assessment, and surface-atmosphere exchange. However, continuous MLH monitoring with backscatter lidars remains challenging under complex atmospheric conditions, including cloudy conditions and in the presence of residual layers. This study evaluates two complementary MLH retrieval algorithms using a single MicroPulse Differential Absorption Lidar (MPD): an aerosol-based approach that analyzes aerosol backscatter gradients with a wavelet technique and a thermodynamic technique based on the vertical structure of virtual potential temperature profiles. Both techniques were compared against MLH estimates from radiosondes, a Doppler wind lidar, and a high-resolution weather model using data from the M2HATS field campaign in Tonopah, NV, USA, supplemented by a smaller dataset from Boulder, CO, USA. The aerosol method achieved high temporal resolution and agreement with radiosonde MLH estimates under convective conditions (R2= 0.819–0.919), but its MLH estimates deviated from other methods during morning and evening transitions due to residual layer interference. The thermodynamic method avoided these problems but had coarser resolution and degraded instrument performance beneath clouds (R2= 0.661–0.845). Because lidar generally cannot penetrate clouds, conditions with clouds at or below the MLH are not considered, while those with clouds above the MLH are retained. The study highlights the strengths and weaknesses of each method. Together, they offer a path toward more reliable automatic MLH monitoring with a single instrument by capturing when different MLH definitions converge.

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 adapt the Poisson Total Variation processing technique to cater to this application. By assuming a Poisson noise model for the photon count observations, our approach yields denoised estimates of backscatter photon flux and related parameters. This facilitates the processing of raw photon counting signals with exceptionally high temporal and range resolutions (demonstrated here to 50 Hz and 75 cm resolutions), including data acquired through time-correlated single photon counting, without significant sacrifice of resolution. Through examination involving both simulated and real-world 2D atmospheric data, our method consistently demonstrates superior accuracy in signal recovery compared to the conventional histogram-based approach commonly employed in distributed target lidar applications.

A method for expanding the observational capabilities of diode-laser-based atmospheric lidar is discussed. A straightforward test, consisting of interleaved “Long” and “Short” laser pulses, is developed to demonstrate how shot-to-shot modification of laser pulse characteristics can enhance the performance of low-power, diode-laser-based lidar and could benefit atmospheric observations. Two examples are given to demonstrate the technique. In the first, water vapor profiling is extended closer to the surface while simultaneously maintaining sufficient far-range performance. These results are verified with collocated measurements. In the second example, clouds are resolved at high vertical spatial resolution with a high signal-to-noise ratio. Details of the lidar instrument hardware and the method to combine the laser pulses of different durations are given.

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.

Continuous water vapor and temperature profiles are critically needed for improved understanding of the lower atmosphere and potential advances in weather forecasting skill. Ground-based, national-scale profiling networks are part of a suite of instruments to provide such observations; however, the technological method must be cost-effective and quantitative. We have been developing an active remote sensing technology based on a diode-laser-based lidar technology to address this observational need. Narrowband, high-spectral-fidelity diode lasers enable accurate and calibration-free measurements requiring a minimal set of assumptions based on direct absorption (Beer–Lambert law) and a ratio of two signals. These well-proven quantitative methods are known as differential absorption lidar (DIAL) and high-spectral-resolution lidar (HSRL). This diode-laser-based architecture, characterized by less powerful laser transmitters than those historically used for atmospheric studies, can be made eye-safe and robust. Nevertheless, it also requires solar background suppression techniques such as narrow-field-of-view receivers with an ultra-narrow bandpass to observe individual photons backscattered from the atmosphere. We discuss this diode-laser-based lidar architecture's latest generation and analyze how it addresses a national-scale profiling network's need to provide continuous thermodynamic observations. The work presented focuses on general architecture changes that pertain to both the water vapor and the temperature profiling capabilities of the MicroPulse DIAL (MPD). However, the specific subcomponent testing and instrument validation presented are for the water vapor measurements only. A fiber-coupled seed laser transmitter optimization is performed and shown to meet all of the requirements for the DIAL technique. Further improvements – such as a fiber-coupled near-range receiver, the ability to perform quality control via automatic receiver scanning, advanced multi-channel scalar capabilities, and advanced processing techniques – are discussed. These new developments increase narrowband DIAL technology readiness and are shown to allow higher-quality water vapor measurements closer to the surface via preliminary intercomparisons within the MPD network itself and with radiosondes.

It has generally been assumed that differential absorption lidar (DIAL) systems are incapable of measuring atmospheric temperature with useful accuracy. This assumption is a direct result of errors that arise in standard DIAL retrievals due to differential Rayleigh-Doppler broadening from aerosols and molecules. We present here, a combined high spectral resolution (HSRL) and DIAL system that addresses this identified source of uncertainty by measuring quantitative aerosol parameters as well as oxygen absorption parameters. This system, in combination with a perturbative retrieval method, accounts for the Rayleigh-Doppler broadening effects on the oxygen absorption. We describe this combined DIAL/HSRL system and retrieval to evaluate the first retrieval parameters exploring the likelihood that it is possible to measure atmospheric temperature using a DIAL system.

The Canopy Horizontal Array Turbulence Study (CHATS) took place in spring 2007 and is the third in the series of Horizontal Array Turbulence Study (HATS) experiments. The HATS experiments have been instrumental in testing and developing subfilterscale (SFS) models for large-eddy simulation (LES) of planetary boundary layer (PBL) turbulence. The CHATS campaign took place in a deciduous walnut orchard near Dixon, California, and was designed to examine the impacts of vegetation on SFS turbulence. Measurements were collected both prior to and following leafout to capture the impact of leaves on the turbulence, stratification, and scalar source/sink distribution. CHATS utilized crosswind arrays of fast-response instrumentation to investigate the impact of the canopy-imposed distribution of momentum extraction and scalar sources on SFS transport of momentum, energy, and three scalars. To directly test and link with PBL parameterizations of canopy-modified turbulent exchange, CHATS also included a 30-m profile tower instrumented with turbulence instrumentation, fast and slow chemical sensors, aerosol samplers, and radiation instrumentation. A highresolution scanning backscatter lidar characterized the turbulence structure above and within the canopy; a scanning Doppler lidar, mini sodar/radio acoustic sounding system (RASS), and a new helicopter-observing platform provided details of the PBL-scale flow. Ultimately, the CHATS dataset will lead to improved parameterizations of energy and scalar transport to and from vegetation, which are a critical component of global and regional land, atmosphere, and chemical models. This manuscript presents an overview of the experiment, documents the regime sampled, and highlights some preliminary key findings.

A field-deployable scanning direct-detection elastic backscatter lidar system that is eye safe at all ranges is presented. The first two-dimensional spatial images created by scanning this new 1.54-μm wavelength system, and time-lapse animations (viewable in the online version of this article) of those spatial images, are shown. The system has a useful range from approximately 500 m to several kilometers or more (depending on weather conditions) with 3-m range resolution. The time-lapse animations reveal the advection of the macroscopic structure of aerosol scattering due to atmospheric motion. The images and animations are ideal for the location of sources of pollutants and their dispersal and the elucidation of structure in the cloud-free atmosphere. Most importantly, the data presented were collected in a populated area, which would have not been possible with a non-eye-safe system.