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Masanori Saito
and
Ping Yang

Abstract

Atmospheric particles exhibit various sizes and nonspherical shapes, which are factors that primarily determine the physical–optical properties of particles. The “sizes” of nonspherical particles can be specified based on various size descriptors, such as those defined with respect to a volume-equivalent spherical radius, projected-area-equivalent spherical radius, geometric radius, or effective radius. Microphysical and radiative transfer simulations as well as remote sensing implementations often require the conversions of particle size distributions (PSDs) in terms of the number concentration, projected area, and volume. The various size descriptors cause ambiguity in the PSD interconversion, and thereby result in potentially misleading quantification of the physical–optical properties of atmospheric nonspherical particles. The present study aims to provide a generalized formula for interconversions of PSDs in terms of physical variables and size descriptors for arbitrary nonspherical particles with lognormal and gamma distributions. In contrast to previous studies, no empirical parameters are included, allowing intrinsic understanding of the nonspherical particle effects on the PSD interconversion. In addition, we investigate the impact of different size descriptors on the single-scattering properties of nonspherical particles. Consistent single-scattering properties among different nonspherical particles with the same size parameter are found when the size descriptor is the effective radius, whereby their mechanisms are suggested based on a modified anomalous diffraction theory. The overarching goal of this work is to eliminate the ambiguity associated with a choice of the size descriptor of nonspherical particles for Earth-atmosphere system models, cloud–aerosol remote sensing, and analyses of in situ measured atmospheric particles.

Significance Statement

Atmospheric dust and ice crystals have various sizes and mostly nonspherical shapes. Different definitions of these particle sizes and shapes cause uncertainties and even result in misleading solutions in the numerical modeling and remote sensing of atmospheric properties. We derived generalized analytical formulas to rigorously treat the sizes and shapes of particles in the atmosphere, and also investigated the importance of the treatment of particle sizes on the particle properties essential to the Earth–atmospheric climate system. This study aims to eliminate the ambiguity associated with particle sizes and shapes in atmospheric research.

Restricted access
Leonardo Alcayaga
,
Gunner Chr. Larsen
,
Mark Kelly
, and
Jakob Mann

Abstract

We investigate characteristics of large-scale coherent motions in the atmospheric boundary layer using field measurements made with two long-range scanning wind lidars. The joint scans provide quasi-instantaneous wind fields over a domain of ∼50 km2, at two heights above flat but partially forested terrain. Along with the two-dimensional wind fields, two-point statistics and spectra are used to identify and characterize the scales, shape, and anisotropy of coherent structures—as well as their influence on wind field homogeneity. For moderate to high wind speeds in near-neutral conditions, most of the observed structures correspond to narrow streaks of low streamwise momentum near the surface, extending several hundred meters in the streamwise direction; these are associated with positive vertical velocity ejections. For unstable conditions and moderate winds, these structures become large-scale rolls, with longitudinal extent exceeding the measuring domain (>∼5 km); they dominate the conventional surface-layer structures in terms of both physical scale and relative size of velocity-component variances, appearing as quasi-two-dimensional structures throughout the entire boundary layer. The observations shown here are consistent with numerical simulations of atmospheric flows, field observations, and laboratory experiments under similar conditions.

Significance Statement

Coherent structures have attracted the interest of researchers for decades, being viewed as the closest to “order” that we can find within the chaos of turbulence. In the turbulent atmospheric boundary layer, micro- and mesoscale coherent structures come in many shapes and sizes, such as convective cells, rolls, or streaks. In this study we used dual lidars (remote sensing measurements), developing analysis of their tandem usage to characterize in detail some of the large-scale coherent structures generated over flat terrain. This allowed us to better understand the mechanisms that generate such structures and describe their influence on the morphology of the turbulent atmospheric boundary layer across a good deal of its depth.

Open access
Mikhail D. Alexandrov
,
Alexander Marshak
,
Brian Cairns
, and
Andrew S. Ackerman

Abstract

We present a generalization of the binary-value Markovian model previously used for statistical characterization of cloud masks to a continuous-value model describing 1D fields of cloud optical thickness (COT). This model has simple functional expressions and is specified by four parameters: the cloud fraction, the autocorrelation (scale) length, and the two parameters of the normalized probability density function of (nonzero) COT values (this PDF is assumed to have gamma-distribution form). Cloud masks derived from this model by separation between the values above and below some threshold in COT appear to have the same statistical properties as in binary-value model described in our previous publications. We demonstrate the ability of our model to generate examples of various cloud-field types by using it to statistically imitate actual cloud observations made by the Research Scanning Polarimeter (RSP) during two field experiments.

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Pengcheng Zhang
and
Nicholas J. Lutsko

Abstract

Although Earth’s troposphere does not superrotate in the annual mean, for most of the year—from October to May—the winds of the tropical upper troposphere are westerly. We investigate this seasonal superrotation using reanalysis data and a single-layer model for the winds of the tropical upper troposphere. We characterize the temporal and spatial structures of the tropospheric superrotation, and quantify the relationships between the superrotation and the leading modes of tropical interannual variability. We also find that the strength of the superrotation has remained roughly constant over the past few decades, despite the winds of the tropical upper troposphere decelerating (becoming more easterly) in other months. We analyze the monthly zonal-mean zonal momentum budget and use numerical simulations with an axisymmetric, single-layer model of the tropical upper troposphere to study the underlying dynamics of the seasonal superrotation. Momentum flux convergence by stationary eddies accelerates the superrotation, while cross-equatorial easterly momentum transport associated with the Hadley circulation decelerates the superrotation. The seasonal modulations of these two competing factors shape the superrotation. The single-layer model is able to qualitatively reproduce the seasonal progression of the winds in the tropical upper troposphere, and highlights the northward displacement of the intertropical convergence zone in the annual mean as a key factor responsible for the annual cycle of the tropical winds.

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Lucas A. McMichael
,
David B. Mechem
, and
Thijs Heus

Abstract

Vertical wind shear has long been known to tilt convective towers and reduce thermal ascent rates. The purpose of this study is to better understand the physical mechanisms responsible for reduced ascent rates in shallow convection. In particular, the study focuses on cloud-edge mass flux to assess how shear impacts mass-flux profiles of both the ensemble and individual clouds of various depths. A compositing algorithm is used to distill large-eddy simulation (LES) output to focus on up- and down-shear cloud edges that are not influenced by complex cloud geometry or nearby clouds. A direct entrainment algorithm is used to estimate the mass flux through the cloud surface. We find that the dynamics on the up- and down-shear sides are fundamentally different, with the entrainment of environmental momentum and dilution of buoyancy being primarily responsible for the reduced down-shear ascent rates. Direct estimates of fluid flow through the cloud interface indicate a counter-shear organized flow pattern that entrains on the down-shear side and detrains on the up-shear side, resulting from the subcloud shear being lifted into the cloud layer by the updraft. In spite of organized regions of entrainment and detrainment, the overall net lateral mass flux remains unchanged with respect to the no shear run, with weak detrainment present throughout cloud depth.

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Israel Weinberger
,
Chaim I. Garfinkel
,
Nili Harnik
, and
Nathan Paldor

Abstract

Extreme stratospheric vortex states are often associated with extreme heat flux and upward wave propagation in the troposphere and lower stratosphere; however, the factors that dictate whether an upward-directed wave in the troposphere will reach the bottom of the vortex versus being reflected back to the troposphere are not fully understood. Following Charney and Drazin, an analytical quasigeostrophic planetary-scale model is used to examine the role of the tropopause inversion layer (TIL) in wave propagation and reflection. The model consists of three different layers: troposphere, TIL, and stratosphere. It is shown that a larger buoyancy frequency in the TIL leads to weaker upward transmission to the stratosphere and enhanced reflection back to the troposphere, and thus reflection of wave packets is sensitive not just to the zonal wind but also to the TIL’s buoyancy frequency. The vertical–zonal cross section of a wave packet for a more prominent TIL in the analytical model is similar to the corresponding wave packet for observational events in which the wave amplitude decays rapidly just above the tropopause. Similarly, a less prominent TIL both in the model and in reanalysis data is associated with enhanced wave transmission and a weak change in wave phase above the tropopause. These results imply that models with a poor representation of the TIL will suffer from a bias in both the strength and phase of waves that transit the tropopause region.

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Mengjuan Liu
and
Bowen Zhou

Abstract

In the numerical gray zone of the convective boundary layer (CBL), the horizontal resolution is comparable to the size of organized convective circulation. As turbulence becomes partially resolved, gridscale variations of the subgrid-scale (SGS) turbulent fluxes become significant compared to the mean. Previously, such variations have often been ignored in scale-adaptive planetary boundary layer (PBL) schemes developed for the gray zone. This study investigates these variations with respect to height and resolution based on large-eddy simulations. It is found that SGS fluxes exhibit maximum variability at the center of the gray zone, where the resolved and the SGS mean fluxes are approximately equal. A simple analytical model is used to associate such characteristic variations to the nonlinear interactions of the dominant energy-containing mode of CBL turbulence. Examination of the horizontal distribution of the SGS fluxes reveals their preferential location over the updraft edges surrounding the core. A priori analysis further suggests the ability of a scale-similarity closure to reproduce the unique spatial patterns of the SGS fluxes at gray zone resolutions. Four scale-adaptive PBL schemes are evaluated focusing on their representations of the modeled SGS flux variability. Their shared shortcomings as a result of their gradient diffusion–based formulation are exposed. This study suggests that a mixed model consisting of a scale-adaptive PBL scheme to represent the mean, and a scale-similarity component to account for gridscale variability to be advantageous for the gray zone.

Significance Statement

As Gresho and Lee’s famous quote on numerical schemes goes, “Don’t suppress the wiggles. They’re telling you something!” In the numerical gray zone, where the grid spacing is comparable to the characteristic length scale of the flow, turbulence is partially resolved. The “wiggles” (or gridscale variability) reflecting the resolved heterogeneity of turbulent fluxes is an outstanding feature of the gray zone. However, they are often overlooked as error bars to the mean. This study uncovers the significance of these error bars, and characterizes and explains their variations with height and grid spacing. A suitable model that captures such variations is investigated to help build better planetary boundary layer schemes.

Open access
Dana M. Tobin
,
Matthew R. Kumjian
,
Mariko Oue
, and
Pavlos Kollias

Abstract

The discovery of a polarimetric radar signature indicative of hydrometeor refreezing has shown promise in its utility to identify periods of ice pellet production. Uniquely characterized well-below the melting layer by locally enhanced values of differential reflectivity (ZDR) within a layer of decreasing radar reflectivity factor at horizontal polarization (ZH), the signature has been documented in cases where hydrometeors were completely melted prior to refreezing. However, polarimetric radar features associated with the refreezing of partially melted hydrometeors have not been examined as rigorously in either an observational or microphysical modeling framework. Here, polarimetric radar data – including vertically-pointing Doppler spectral data from the Ka-band Scanning Polarimetric Radar (KASPR) – are analyzed for an ice pellets and rain mixture event where the ice pellets formed via the refreezing of partially melted hydrometeors. Observations show that no such distinct localized ZDR enhancement is present, and that values instead decrease directly beneath enhanced values associated with melting.

A simplified, explicit bin microphysical model is then developed to simulate the refreezing of partially melted hydrometeors, and coupled to a polarimetric radar forward operator to examine the impacts of such refreezing on simulated radar variables. Simulated vertical profiles of polarimetric radar variables and Doppler spectra have similar features to observations, and confirm that a ZDR enhancement is not produced. This suggests the possibility of two distinct polarimetric features of hydrometeor refreezing: ones associated with refreezing of completely melted hydrometeors, and those associated with refreezing of partially melted hydrometeors.

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Jennie Bukowski
and
Susan C. van den Heever

Abstract

Haboobs are dust storms formed by strong surface winds in convective storm outflow boundaries, or cold pools, which can loft large quantities of mineral dust as they propagate. Both cold pools and the dust they loft are impacted by land surface properties resulting in complex surface interactions on haboobs. As a result of these additional complexities brought about by surface interactions, it is unclear which surface parameters and physical processes are important for predicting haboob intensity and dust concentrations. Here we applied the Morris one-at-a-time (MOAT) global sensitivity statistical method to an ensemble of 120 idealized simulations of daytime and nighttime haboobs to investigate the land surface properties that affect both dust mobilization and cold pool dynamics. MOAT identifies and ranks the importance of different input factors, which for the prediction of haboob strength and dust concentrations are 1) initial cold pool temperature, 2) surface type (vegetation), 3) soil type (clay content), and 4) soil moisture. The underlying physical mechanisms driving these feedbacks were then analyzed using a traditional one-at-a-time factor analysis. Time of day is significant for determining boundary layer height and dissipation via surface fluxes, leading to shallower, more intense cold pools/haboobs at night. Most of the land parameters modify the cold pool through impacts on surface fluxes, while surface type is dominated by roughness length effects. By ranking the importance of these surface factors, we have identified which variables are most sensitive and must be constrained via observations and data assimilation in numerical dust prediction models.

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Elisa M. Murillo
and
Cameron R. Homeyer

Abstract

Above-anvil cirrus plumes (AACPs) in midlatitude convection are important indicators of severe storms and stratospheric hydration events. Recent studies of AACPs have shown large variability in their characteristics, although many of the causes remain unknown. Notably, some AACPs appear equally as cold (or colder) than the broader storm top when compared to the more frequently observed warm AACP feature in infrared satellite imagery. To confidently identify the presence of an AACP, trained experts utilize infrared imagery to support the primary source of AACP identification, visible imagery. Thus, nighttime AACPs are often left unidentified due to unavailable visible imagery, especially for cold AACPs. In this study, 89 warm and 89 cold AACPs from 1-min GOES-16 satellite imagery coupled with ground-based radar observations and reanalysis data are comparatively evaluated to answer the following research questions: 1) Why do some AACPs exhibit a warm feature in infrared imagery while others do not, and 2) what observable storm and environment differences exist between warm and cold AACPs? It is found that cold AACPs tend to occur in tropical environments, which feature higher, cold-point tropopauses. Conversely, warm AACPs tend to occur in midlatitude environments, with lower tropopauses accompanied by an isothermal region (or tropopause inversion layer) in the lower stratosphere. Similar storm characteristics are found for warm and cold AACP events, implying that infrared temperature variability is driven by environmental differences. Together, these results suggest that cold AACPs are predominantly tropospheric phenomena, while warm AACPs reside in the lower stratosphere.

Significance Statement

The purpose of this study is to determine why some storms with a specific cloud-top feature exhibit a broad warm spot in infrared satellite imagery while others appear cold. This is important because storms with this specific cloud-top feature, whether warm or cold, produce much more severe weather than most other storms. These cloud-top features are also potentially indicative of increased water vapor in the stratosphere, which results in warming of Earth’s climate. Our results help us better understand storms that are frequently severe and suggest that the storms with cold features are less important to understanding stratospheric water vapor and climate change.

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