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Min Deng
,
Jeffrey French
,
Bart Geerts
,
Samuel Haimov
,
Larry Oolman
,
Dave Plummer
, and
Zhien Wang

Abstract

As part of the analysis following the Seeded and Natural Orographic Wintertime Storms (SNOWIE) project, the ice water content (IWC) in ice and mixed-phase clouds is retrieved from airborne Wyoming Cloud Radar (WCR) measurements aboard the University of Wyoming King Air (UWKA), which has a suite of integrated in situ IWC, optical array probes, and remote sensing measurements, and it provides a unique dataset for this algorithm development and evaluation. A sensitivity study with different idealized ice particle habits shows that the retrieved IWC with aggregate ice particle habit agrees the best with the in situ measurement, especially in ice or ice-dominated mixed-phase clouds with a correlation coefficient (rr) of 0.91 and a bias of close to 0. For mixed-phase clouds with ice fraction ratio less than 0.8, the variances of IWC estimates increase (rr = 0.76) and the retrieved mean IWC is larger than in situ IWC by a factor of 2. This is found to be related to the uncertainty of in situ measurements, the large cloud inhomogeneity, and the retrieval assumption uncertainty. The simulated reflectivity Ze and IWC relationships assuming three idealized ice particle habits and measured particle size distributions show that hexagonal columns with the same Ze have a lower IWC than aggregates, whose Ze–IWC relation is more consistent with the observed WCR Ze and in situ IWC relation in those clouds. The 2D stereo probe (2DS) images also indicate that ice particle habit transition occurs in orographic mixed-phase clouds; hence, the retrieved IWC assuming modified gamma particle size distribution (PSD) of aggregate particles tends to have a greater bias in this kind of clouds.

Open access
Guo Lin
,
Zhien Wang
,
Conrad Ziegler
,
Xiao-Ming Hu
,
Ming Xue
,
Bart Geerts
, and
Yufei Chu

Abstract

The magnitude of water vapor content within the near-storm inflow can either support or deter the storm’s upscale growth and maintenance. However, the heterogeneity of the moisture field near storms remains poorly understood because the operational observation network lacks detail. This observational study illustrates that near-storm inflow water vapor environments are both significantly heterogeneous and different than the far-inflow storm environment. This study also depicts the importance of temporal variation of water vapor mixing ratio (WVMR) to instability during the peak tornadic seasons in the U.S. Southeast and Great Plains regions during the Verification of the Origins of Rotation in Tornadoes Experiment Southeast 2018 (VSE18) campaign and the Targeted Observation by Radar and UAS of Supercells (TORUS) campaign, respectively. VSE18 results suggest that the surface processes control WVMR variation significantly in lower levels, with the highest WVMR mainly located near the surface in inflows in the southeast region. In contrast, TORUS results show more vertically homogeneous WVMR profiles and rather uniform water vapor distribution variation occurring in deep, moist stratified inflows in the Great Plains region. Temporal water vapor variations within 5-min periods could lead to over 1000 J kg−1 CAPE changes in both VSE18 and TORUS, which represent significant potential buoyancy perturbations for storms to intensify or decay. These temporal water vapor and instability evolutions of moving storms remain difficult to capture via radiosondes and fixed in situ or profiling instrumentation, yet may exert a strong impact on storm evolution. This study suggests that improving observations of the variability of near-storm inflow moisture can accurately refine a potential severe weather threat.

Significance Statement

It has long been recognized that better observations of the planetary boundary layer (PBL) inflow near convective storms are needed to improve severe weather forecasting. The current operational networks essentially do not provide profile measurements of the PBL, except for the sparsely spaced 12-hourly sounding network. More frequent geostationary satellite observations do not provide adequately high vertical resolution in the PBL. This study uses airborne lidar profiler measurements to examine moisture in the inflow region of convective storms in the Great Plains and the southeastern United States during their respective tornadic seasons. Rapid PBL water vapor variations on a ∼5 min time scale can lead to CAPE perturbations exceeding 1000 J kg−1, representing significant perturbations that could promote storm intensification or decay. Severe thunderstorms may generate high-impact weather phenomena, such as tornadoes, high winds, hail, and heavy rainfall, which have substantial socioeconomic impacts. Ultimately, by contrasting characteristics of the convective storm inflow in the two regions, this study may lead to a more accurate assessment of severe weather threats.

Free access
Min Deng
,
Rainer M. Volkamer
,
Zhien Wang
,
Jefferson R. Snider
,
Natalie Kille
, and
Leidy J. Romero-Alvarez

Abstract

The western U.S. wildfire smoke plumes observed by the upward-pointing Wyoming Cloud Lidar (WCL) during the Biomass Burning Fluxes of Trace Gases and Aerosols (BB-FLUX) project are investigated in a two-part paper. Part II here presents the reconstructed vertical structures of seven plumes from airborne WCL measurements. The vertical structures evident in the fire plume cross sections, supported by in situ measurements, showed that the fire plumes had distinct macrophysical and microphysical properties, which are closely related to the plume transport, fire emission intensity, and thermodynamic structure in the boundary layer. All plumes had an injection layer between 2.8 and 4.0 km above mean sea level, which is generally below the identified boundary layer top height. Plumes that transported upward out of the boundary layer, such as the Rabbit Foot and Pole Creek fires, formed a higher plume at around 5.5 km. The largest and highest Pole Creek fire plume was transported farthest and was sampled by University of Wyoming King Air aircraft at 170 km, or 2.3 h, downwind. It was associated with the warmest, driest, deepest boundary layer and the highest wind speed and turbulence. The Watson Creek fire plume intensified in the afternoon with stronger CO emission and larger smoke plume height than in the morning, indicating a fire diurnal cycle, but some fire plumes did not intensify in the afternoon. There were pockets of relatively large irregular aerosol particles at the tops of plumes from active fires. In less-active fire plumes, the WCL depolarization ratio and passive cavity aerosol spectrometer probe mass mean diameter maximized at a height that was low in the plume.

Full access
Min Deng
,
Zhien Wang
,
Rainer Volkamer
,
Jefferson R. Snider
,
Larry Oolman
,
David M. Plummer
,
Natalie Kille
,
Kyle J. Zarzana
,
Christopher F. Lee
,
Teresa Campos
,
Nicholas Ryan Mahon
,
Brent Glover
,
Matthew D. Burkhart
, and
Austin Morgan

Abstract

During the summer of 2018, the upward-pointing Wyoming Cloud Lidar (WCL) was deployed on board the University of Wyoming King Air (UWKA) research aircraft for the Biomass Burning Flux Measurements of Trace Gases and Aerosols (BB-FLUX) field campaign. This paper describes the generation of calibrated attenuated backscatter coefficients and aerosol extinction coefficients from the WCL measurements. The retrieved aerosol extinction coefficients at the flight level strongly correlate (correlation coefficient, rr > 0.8) with in situ aerosol concentration and carbon monoxide (CO) concentration, providing a first-order estimate for converting WCL extinction coefficients into vertically resolved CO and aerosol concentration within wildfire smoke plumes. The integrated CO column concentrations from the WCL data in nonextinguished profiles also correlate (rr = 0.7) with column measurements by the University of Colorado Airborne Solar Occultation Flux instrument, indicating the validity of WCL-derived extinction coefficients. During BB-FLUX, the UWKA sampled smoke plumes from more than 20 wildfires during 35 flights over the western United States. Seventy percent of flight time was spent below 3 km above ground level (AGL) altitude, although the UWKA ascended up to 6 km AGL to sample the top of some deep smoke plumes. The upward-pointing WCL observed a nearly equal amount of thin and dense smoke below 2 km and above 5 km due to the flight purpose of targeted fresh fire smoke. Between 2 and 5 km, where most of the wildfire smoke resided, the WCL observed slightly more thin smoke than dense smoke due to smoke spreading. Extinction coefficients in dense smoke were 2–10 times stronger, and dense smoke tended to have larger depolarization ratio, associated with irregular aerosol particles.

Full access
Yongxiang Hu
,
David Winker
,
Mark Vaughan
,
Bing Lin
,
Ali Omar
,
Charles Trepte
,
David Flittner
,
Ping Yang
,
Shaima L. Nasiri
,
Bryan Baum
,
Robert Holz
,
Wenbo Sun
,
Zhaoyan Liu
,
Zhien Wang
,
Stuart Young
,
Knut Stamnes
,
Jianping Huang
, and
Ralph Kuehn

Abstract

The current cloud thermodynamic phase discrimination by Cloud-Aerosol Lidar Pathfinder Satellite Observations (CALIPSO) is based on the depolarization of backscattered light measured by its lidar [Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)]. It assumes that backscattered light from ice crystals is depolarizing, whereas water clouds, being spherical, result in minimal depolarization. However, because of the relationship between the CALIOP field of view (FOV) and the large distance between the satellite and clouds and because of the frequent presence of oriented ice crystals, there is often a weak correlation between measured depolarization and phase, which thereby creates significant uncertainties in the current CALIOP phase retrieval. For water clouds, the CALIOP-measured depolarization can be large because of multiple scattering, whereas horizontally oriented ice particles depolarize only weakly and behave similarly to water clouds. Because of the nonunique depolarization–cloud phase relationship, more constraints are necessary to uniquely determine cloud phase. Based on theoretical and modeling studies, an improved cloud phase determination algorithm has been developed. Instead of depending primarily on layer-integrated depolarization ratios, this algorithm differentiates cloud phases by using the spatial correlation of layer-integrated attenuated backscatter and layer-integrated particulate depolarization ratio. This approach includes a two-step process: 1) use of a simple two-dimensional threshold method to provide a preliminary identification of ice clouds containing randomly oriented particles, ice clouds with horizontally oriented particles, and possible water clouds and 2) application of a spatial coherence analysis technique to separate water clouds from ice clouds containing horizontally oriented ice particles. Other information, such as temperature, color ratio, and vertical variation of depolarization ratio, is also considered. The algorithm works well for both the 0.3° and 3° off-nadir lidar pointing geometry. When the lidar is pointed at 0.3° off nadir, half of the opaque ice clouds and about one-third of all ice clouds have a significant lidar backscatter contribution from specular reflections from horizontally oriented particles. At 3° off nadir, the lidar backscatter signals for roughly 30% of opaque ice clouds and 20% of all observed ice clouds are contaminated by horizontally oriented crystals.

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