Search for: All records

Abstract. 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. 

Abstract. The micropulse differential absorption lidar (MPD) was developed at Montana State University (MSU) and the National Center for Atmospheric Research (NCAR) to perform range-resolved water vapor (WV) measurements using low-power lasers and photon-counting detectors. The MPD has proven to produce accurate WV measurements up to 6 km altitude. However, the MPD's ability to produce accurate higher-altitude WV measurements is impeded by the current standard differential absorption lidar (DIAL) retrieval methods. These methods are built upon a fundamental methodology that algebraically solves for the WV using the MPD forward models and noisy observations, which exacerbates any random noise in the lidar observations. The work in this paper introduces the adapted Poisson total variation (PTV) specifically for the MPD instrument. PTV was originally developed for a ground-based high spectral resolution lidar, and this paper reports on the adaptations that were required in order to apply PTV on MPD WV observations. The adapted PTV method, coined PTV-MPD, extends the maximum altitude of the MPD from 6 to 8 km and substantially increases the accuracy of the WV retrievals starting above 2 km. PTV-MPD achieves the improvement by simultaneously denoising the MPD noisy observations and inferring the WV by separating the random noise from the non-random WV. An analysis with 130 radiosonde (RS) comparisons shows that the relative root-mean-square difference (RRMSE) of WV measurements between RS and PTV-MPD exceeds 100 % between 6 and 8 km, whereas the RRMSE between RS and the standard method exceeds 100 % near 3 km. In addition, we show that by employing PTV-MPD, the MPD is able to extend its useful range of WV estimates beyond that of the ARM Southern Great Plains Raman lidar (RRMSE exceeding 100 % between 3 and 4 km); the Raman lidar has a power-aperture product 500 times greater than that of the MPD. 

Abstract For a given cloud, whether the cloud top is predominately made up of ice crystals or supercooled liquid droplets plays a large role in the clouds overall radiative effects. This study uses collocated airborne radar, lidar, and thermodynamic data from 12 high‐altitude flight legs during the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) to characterize Southern Ocean (SO) cold sector cloud top phase (i.e., within 96 m of top) as a function of cloud top temperature (CTT). A training data set was developed to create probabilistic phase classifications based on High Spectral Resolution Lidar data and Cloud Radar data. These classifications were then used to identify dominant cloud top phase. Case studies are presented illustrating examples of supercooled liquid water at cloud top at different CTT ranges over the SO (−3°C < CTTs < −28°C). During SOCRATES, 67.4% of sampled cloud top had CTTs less than 0°C. Of the subfreezing cloud tops sampled, 91.7% had supercooled liquid water present in the top 96 m and 74.9% were classified entirely as liquid‐bearing. Liquid‐bearing cloud tops were found at CTTs as cold as −30°C. Horizontal cloud extent was also determined as a function of median cloud top height.