Cloud-wind interactions play an important role in long-lived multiphase flows in various galaxy-related contexts (e.g., galactic fountains and winds, cosmological cold-mode accretion, or multiphase tails of satellites). These interactions occur when a volume-filling hot phase, the wind, moves relative to a cool pressure-confined body of gas, the cloud. The conditions necessary for clouds to survive the destructive effects of mixing and become entrained within the wind (i.e. for the relative velocity to be removed), has been a long-standing problem. This problem has received particular attention in the context of galactic winds: cloud entrainment is expected to play a critical role in explaining observed multiphase structure in these outflows. This thesis investigates a mechanism for facilitating cloud survival in the context of rapid cooling, which we hereafter term TRML (turbulent radiative mixing layer) entrainment. Our investigation leverages numerical (magneto)hydrodynamic ENZO-E simulations of a cool (≲10⁴𝐊) clouds that encounter a hot (≳10⁶𝐊), supersonic winds. We begin by introducing a simple entropy-based formalism to characterize the role of mixing in cloud-wind interactions, and demonstrate example applications using simulations. Under this formalism, the high-dimensional description of the interaction's state at a given time is simplified to the joint distribution of mass over pressure (𝑃 ) and entropy (𝐾=𝑃𝞀^-𝜸). As a result, this approach provides a way for (empirically and analytically) quantifying the impact of different initial conditions and sets of physics on the interaction's evolution. We find that mixing predominantly alters the distribution along the 𝐾 direction and illustrate how the formalism can be used to model mixing and cooling for fluid elements originating in the cloud. We further confirm and generalize a previously suggested survival criterion for clouds undergoing TRML entrainment, and demonstrate that the shape of the cooling curve, particularly at the low temperature end, can play an important role in controlling condensation. Moreover, we discuss the capacity of our approach to generalize such a criterion to apply to additional sets of physics, and to build intuition for the impact of subtle higher order effects not directly addressed by the criterion. Despite the fact that the competition the between turbulent mixing and radiative cooling dictate the outcome of the cloud-wind interaction (as well as many observable properties), turbulence in these interactions remains poorly understood. Thus, we next investigate the turbulence that arises for clouds undergoing TRML entrainment. To obtain robust results, we employ multiple metrics to characterize the turbulent velocity, 𝝂_turb. We find four primary results. First, 𝝂_turb manifests clear temperature dependence. Initially, 𝝂_turb roughly matches the scaling of sound speed on temperature. In gas hotter than the temperature where cooling peaks, this dependence weakens with time until 𝝂_turb is constant. Second, the relative velocity between the cloud and wind initially drives rapid growth of 𝝂_turb. As it drops (from entrainment), 𝝂_turb starts to decay before it stabilizes at roughly half its maximum. At late times cooling flows appear to support turbulence. Third, the magnitude of 𝝂_turb scales with the ratio between the hot phase sound crossing time and the minimum cooling time. Finally, we find tentative evidence for a length-scale associated with resolving turbulence. Under-resolving this scale may cause violent shattering and affect the cloud's large-scale morphological properties. Finally, we propose a new criterion for clouds to survive interactions with the wind in the via TRML entrainment, and validate it with simulations. Properties of TRML entrainment are generally understood to be controlled by ratio between the relevant dynamical and cooling timescales 𝝉_dyn / 𝝉_cool. Previously proposed survival criteria disagree about the size of the smallest surviving cloud by factors of up to ∼100. These criteria primarily differ in their choice of 𝝉_{\rm cool}$; perplexingly, the choices most consistent with the well-modeled micro-scale physics observed in shear-layer studies are associated with less-accurate criteria. We present a new criterion which agrees with previous fitting formulae but is based on a set of simple physical principles. Whereas prior criteria link 𝝉_dyn with the cloud destruction timescale, our new criterion links it to the characteristic cloud-crossing timescale of a hot-phase fluid element. This choice leads to scaling relations that are more physically consistent with shear-layer studies. Additionally, we illustrate that discrepancies among previous criteria primarily emerged due to the choices of simulation conditions, rather than commonly-cited differences in the definition of cloud destruction.

<p>  </p> <p>Rapid intensification of low-level rotation in non-classic tornadic storms in southeastern United States, often at time scales shorter than the volume updates from existing opera- tional radars, calls for a deeper understanding of storm-scale processes. There is growing evidence that the highly nonlinear interactions between vertical wind shear and cold pools regulate the intensity of downdrafts, low- and mid-level updrafts, and thus tornadic poten- tial in supercells. Tornado-strength circulations are more likely associated with cold pools of intermediate strength. The microphysical pathway leading to storm electrification also plays a major role in the regulation of cold pool intensity. Storm electrification and subsequent lightning initiation are a by-product of charging of ice hydrometeors in the mixed-phase updrafts. Lightning flashes frequently initiate along the periphery of turbulent updrafts and total flash rate is controlled by the updraft speed and volume.</p> <p><br></p> <p>In the first part of this work, polarimetric fingerprints like ZDR and KDP columns (proxies for mixed-phase updraft strength) are objectively identified to track rapid fluctuations in updraft intensity. We quantify the volume of ZDR and KDP columns to evaluate their utility in predicting temporal variability in lightning flash characteristics and the onset of severe weather. Using observational data from KTLX radar and Oklahoma Lightning Mapping Array, we had previously found evidence of temporal covariance between ZDR column volume and the total lightning flash rate in a tornadic supercell in Oklahoma. </p> <p><br></p> <p> Here, we extend our analysis to three high-shear low-CAPE (HSLC) cases observed during the 2016-17 VORTEX-SE field campaign in Northern Alabama. In all three scenarios (one tornadic and one nontornadic supercell, and a quasi-linear convective system), the KDP column volume had a stronger correlation with total flash rates than the ZDR column volume. We also found that all three storms maintained a normal tripole charge structure, with majority of the cloud-to-ground (CG) strikes lowering negative charge to the ground. The tornadic storm’s CG polarity changed from negative to positive at the same time it entered a region with higher surface equivalent potential temperature. In contrast to the Oklahoma storm, lightning flash initiations in HSLC storms occurred primarily outside the footprint of ZDR and KDP column objects.</p> <p><br></p> <p>Storm dynamics coupled with microphysical processes such as diabatic heating/cooling and advection/sedimentation of hydrometeors also plays a significant role in electrification of thunderstorms. Simulation of deep convection, therefore, needs to account for the feedback of microphysics to storm dynamics. In the second part of this work, the NSSL microphysics scheme is used to simulate ice mass fluxes, cold pool intensity, and noninductive charging rates. The scheme is run in its triple-moment configuration in order to provide a more realis- tic size-sorting process that avoids pathologies that arise in double-moment representations.</p> <p><br></p> <p>We examine the possible tertiary linkage between noninductive charging rates and cold pool through their dependence on mixed-phase microphysical processes. The Advanced Re- gional Prediction System (ARPS) model is used to simulate the same three HSLC cases from VORTEX-SE 2016-17 IOPs. WSR-88D radar reflectivity and Doppler velocity observations are assimilated in a 40-member ensemble using an ensemble Kalman filter (EnKF) filter.</p> <p><br></p> <p>In all three cases, the simulated charge separation is consistent with the observed normal tripole. Greater updraft mass flux, supercooled liquid water concentration, and nonprecip- itation mass flux explain the nontornadic supercell’s higher total flash rate compared to the tornadic supercell. Positive and negative graupel charging rates were found to have the greatest linear correlation with updraft mass flux, followed by precipitation mass flux in all three cases. At zero time lag, horizontal buoyancy gradients associated with a surface cold pool were not found to be correlated with either the charging rates or the updraft and precipitation mass flux. Total flash rate based on empirical relationships between simulated ice mass fluxes was lower than the observed values.</p>

Cirrus clouds cover between 20% - 50% of the globe and are an essential component in the climate. The improved understanding of ice cloud microphysical properties is contingent on acquiring and analyzing in-situ and remote sensing data from cirrus clouds. In ??u observations of microphysical properties of ice and mixed-phase clouds using the mini-Video Ice Particle Sizer (mini-VIPS) aboard robotic unmanned aerial vehicles (UAVs) provide a promising and powerful platform for obtaining valuable data in a cost-effective, safe, and long-term manner. The purpose of this study is to better understand cirrus microphysical properties by analyzing the effectiveness of the mini-VIPS/UAV in-situ platform. The specific goals include: (1) To validate the mini-VIPS performance by comparing the mini-VIPS data retrieved during an Artic UAV mission with data retrieved from the millimeterwavelength cloud radar (MMCR) at the Barrow ARM/CART site. (2) To analyze mini-VIPS data to survey the properties of high latitude mixedphase clouds The intercomparison between in-situ and remote sensing measurements was carried out by comparing reflectivity values calculated from in-situ measurements with observations from the MMCR facility. Good agreement between observations and measurements is obtained during the time frame where the sampled volume was saturated with respect to ice. We also have 1 2 shown that the degree of closure between calculated and observed reflectivity strongly correlates with the assumption of ice crystal geometry observed in the mini-VIPS images. The good correlation increases the confidence in mini-VIPS and MMCR measurements. Finally, the size distribution and ice crystal geometry obtained from the data analysis is consistent with published literature for similar conditions of temperature and ice supersaturation.

Anthropogenic atmospheric aerosols (suspended particulate matter) can modify the radiative balance (and climate) of the Earth by altering the properties and global distribution of clouds. Current climate models however cannot adequately account for many important aspects of these aerosol-cloud interactions, ultimately leading to a large uncertainty in the estimation of the magnitude of the effect of aerosols on climate. This thesis focuses on the development of physically-based descriptions of aerosol-cloud processes in climate models that help to address some of such predictive uncertainty. It includes the formulation of a new analytical parameterization for the formation of ice clouds, and the inclusion of the effects of mixing and kinetic limitations in existing liquid cloud parameterizations. The parameterizations are analytical solutions to the cloud ice and water particle nucleation problem, developed within a framework that considers the mass and energy balances associated with the freezing and droplet activation of aerosol particles. The new frameworks explicitly account for the impact of cloud formation dynamics, the aerosol size and composition, and the dominant freezing mechanism (homogeneous vs. heterogeneous) on the ice crystal and droplet concentration and size distribution. Application of the new parameterizations is demonstrated in the NASA Global Modeling Initiative atmospheric and chemical and transport model to study the effect of aerosol emissions on the global distribution of ice crystal concentration, and, the effect of entrainment during cloud droplet activation on the global cloud radiative properties. The ice cloud formation framework is also used within a parcel ensemble model to understand the microphysical structure of cirrus clouds at very low temperature. The frameworks developed in this work provide an efficient, yet rigorous, representation of cloud formation processes from precursor aerosol. They are suitable for the study of the effect of anthropogenic aerosol emissions on cloud formation, and can contribute to the improvement of the predictive ability of atmospheric models and to the understanding of the impact of human activities on climate.

This thesis addresses a series of questions related to the problem of achieving reliable and physically consistent representations of aerosol-cloud interaction in global circulation models (GCM). In-situ data and modeling tools are used to develop and evaluate novel parameterization schemes for the process of aerosol activation for applications in GCM simulations. Atmospheric models of different complexity were utilized, ranging from detailed Lagrangian parcel model simulations of the condensational growth of droplets, to one-dimensional single column model with aerosol and cloud microphysics, and finally GCM simulations performed with the Community Atmosphere Model (CAM). A scheme for mapping the sub-grid scale variability of cloud droplet number concentrations (CDNC) to a number of microphysical process rates in a GCM was tested, finding that neglecting this impact can have substantial influences in the integrated cloud properties. A comprehensive comparison and evaluation of two widely used, physically-based activation parameterizations was performed in the framework of CAM5.1. This was achieved by utilizing a numerical adjoint sensitivity approach to comprehensively investigate their response under the wide range of aerosol and dynamical conditions encountered in GCM simulations. As a result of this, the specific variables responsible for the observed differences in the physical response across parameterizations are encountered, leading to further parameterization improvement.

Aerosols have significant impacts on earth's climate and hydrological cycle. They can directly reflect the amount of incoming solar radiation into space; by acting as cloud condensation nuclei (CCN), they can indirectly impact climate by affecting cloud albedo. Our current assessment of the interactions of aerosols and clouds is uncertain and parameters used to estimate cloud droplet formation in global climate models are not well constrained. Organic aerosols attribute much of the uncertainty in these estimates and are known to affect the ability of aerosol to form cloud droplets (CCN Activity) by i) providing solute, thus reducing the equilibrium water vapor pressure of the droplet and ii) acting as surfactants capable of depressing surface tension, and potentially, growth kinetics. My thesis dissertation investigates various organic aerosol species (e.g., marine, urban, biomass burning, Humic-like Substances). An emphasis is placed on the water soluble components and secondary organic aerosols (SOA). In addition the sampled organic aerosols are acquired via different media; directly from in-situ ambient studies (TEXAQS 2006) environmental chamber experiments, regenerated from filters, and cloud water samples. Novel experimental methods and analyses to determine surface tension, molar volumes, and droplet growth rates are presented from nominal volumes of sample. These key parameters for cloud droplet formation incorporated into climate models will constrain aerosol-cloud interactions and provide a more accurate assessment for climate prediction.

Despite large efforts and decades of research, the scientific understanding of how aerosols impact climate by modulating microphysical cloud properties is still low and associated radiative forcing estimates (RFaci ) vary with a wide spread. But since anthropogenically forced aerosol-cloud interactions (ACI) are considered to oppose parts of the global warming, it is crucial to know their contribution to the total radiative forcing in order to improve climate predictions. To obtain a better understanding and quantification of ACI and the associated radiative effect it as been suggested to use concurrent measurements and observationally constrained model simulations. In this dissertation a joint satellite-reanalysis approach is introduced, bridging the gap between climate models and satellite observations in a bottom-up approach. This methodology involves an observationally constrained aerosol model, refined and concurrent multi-component satellite retrievals, a state-of-the-art aerosol activation parameteriza- tion as well as radiative transfer model. This methodology is shown here to be useful for a quantitative as well as qualitative analysis of ACI and for estimating RFaci . As a result, a 10-year long climatology of cloud condensation nuclei (CCN) (particles from which cloud droplets form) is produced and evaluated. It is the first of its kind providing 3-D CCN concentrations of global coverage for various supersaturations and aerosol species and offering the opportunity to be used for evaluation in models and ACI studies. Further, the distribution and variability of the resulting cloud droplet numbers and their susceptibility to changes in aerosols is explored and compared to previous estimates. In this context, an analysis by cloud regime has been proven useful. Last but not least, the computation and analysis of the present-day regime-based RFaci represents the final conclusion of the bottom-up methodology. Overall, this thesis provides a comprehensive assessment of interactions and uncertainties related to aerosols, clouds and radiation in regimes of liquid water clouds and helps to improve the level of scientific understanding.

Thesis (Ph. D.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2007. / Includes bibliographical references (p. 153-166). / The role of ocean dynamics in driving air-sea interaction is examined at two contrasting sites on 125°W in the eastern tropical Pacific Ocean using data from the Pan American Climate Study (PACS) field program. Analysis based on the PACS data set and satellite observations of sea surface temperature (SST) reveals marked differences in the role of ocean dynamics in modulating SST. At a near-equatorial site (3°S), the 1997-1998 El Nifio event dominated the evolution of SST and surface heat fluxes, and it is found that wind-driven southward Ekman transport was important in the local transition from El Nifio to La Nifia conditions. At a 10'N site near the summertime position of the Inter-tropical Convergence Zone, oceanic niesoscale motions played an important role in modulating SST at intraseasonal (50- to 100-day) timescales, and the buoy observations suggest that there are variations in surface solar radiation coupled to these mesoscale SST variations. This suggests that the mesoscale oceanic variability may influence the occurrence of clouds. The intraseasonal variability in currents, sea surface height, and SST at the northern site is examined within the broader spatial and temporal context afforded by satellite data. / (cont.) The oscillations have zonal wavelengths of 550-1650 km and propagate westward in a manner consistent with the dispersion relation for first baroclinic mode, free Rossby waves in the presenice of a, mean westward flow. The hypothesis that the intraseasonal variability and its annual cycle are associated with baroclinic instability of the North Equatorial Current is supported by a spatio-temporal correlation between the amplitude of intraseasonal variability and the occurrence of westward zonal flows meeting an approximate necessary condition for baroclinic instability. Focusing on 100N in the eastern tropical Pacific, the hypothesis that mesoscale oceanic SST variability can systematically influence cloud properties is investigated using several satellite data products. A statistically significant relationship between SST and columnar cloud liquid water (CLW), cloud reflectivity, and surface solar radiation is identified within the wavenumber-frequency band corresponding to oceanic Rossby waves. Analysis of seven years of CLW data and 20 years surface solar radiation data indicates that 10-20% of the variance of these cloud-related properties at intraseasonal periods and wavelengths on the order of 100 longitude can be ascribed to SST signals driven by oceanic Rossby waves. / by J. Thomas Farrar. / Ph.D.

<p> It has been hypothesized that some measurable properties of $Z_{DR}$ arcs in supercells may change in the minutes prior to tornadogenesis and tornadogenesis failure, and that $Z_{DR}$ arc area will change with SRH and can be used as a real-time proxy to estimate SRH. Output form the Cloud Model 1 (CM1) along with a polarimetric emulator is used to simulate $Z_{DR}$ arcs in 9 tornadic and 9 non-tornadic supercells. A random forest algorithm is used to automatically identify the $Z_{DR}$ arcs. Finally the inflow sector SRH is calculated at times when $Z_{DR}$ arcs are identified. To analyze the change in intensity and area a comparison between the average $Z_{DR}$ value inside and outside of the arc, as well as the spatial size of the arc and storm was done. Model calculated SRH is then compared to these metrics.</p> <p> </p> <p> It has also been observed that hail fallout complicates the automatic identification of $Z_{DR}$ arcs. In this study, three experiments are run where the simulated $Z_{DR}$ arcs are produced. One using all categories of hydrometeors, one where wet growth and melting of hail is excluded, and one excluding the contribution to $Z_{DR}$ from the hail hydrometeor category. The same analysis as above is repeated for all three experiments. Finally observed $Z_{DR}$ arcs are analyzed to see if these results are applicable to the real world. </p>

<p dir="ltr">It is known that tornadic storms favor environments characteristic of high values of thermal instability, adequate vertical wind shear, abundant near-surface moisture supply, and strong storm-relative helicity at the lowest 1-km boundary layer. These mesoscale environmental conditions and associated storm behaviors are strongly governed by large-scale synoptic patterns and sensitive to variabilities in near-surface characteristics, which are less known in the current research community. This study aims to advance the relatively underexplored area regarding the interaction between surface characteristics, mesoscale environmental conditions, and large-scale synoptic patterns driving tornadic storms in the U.S. </p><p dir="ltr">We first investigate the impact of surface drag on the structure and evolution of these boundaries, their associated distribution of near-surface vorticity, and tornadogenesis and maintenance. Comparisons between idealized simulations without and with drag introduced in the mature stage of the storm prior to tornadogenesis reveal that the inclusion of surface drag substantially alters the low-level structure, particularly with respect to the number, location, and intensity of surface convergence boundaries. Substantial drag-generated horizontal vorticity induces rotor structures near the surface associated with the convergence boundaries in both the forward and rear flanks of the storm. Stretching of horizontal vorticity and subsequent tilting into the vertical along the convergence boundaries lead to elongated positive vertical vorticity sheets on the ascending branch of the rotors and the opposite on the descending branch. The larger near-surface pressure deficit associated with the faster development of the near-surface cyclone when drag is active creates a downward dynamic vertical pressure gradient force that suppresses vertical growth, leading to a weaker and wider tornado detached from the surrounding convergence boundaries. A conceptual model of the low-level structure of the tornadic supercell is presented that focuses on the contribution of surface drag, with the aim of adding more insight and complexity to previous conceptual models.</p><p dir="ltr">We then examine the behaviors and dynamics of TLVs in response to a range of surface drag strengths in idealized simulations and explore their sensitivities to different storm environments. We find that the contribution of surface drag on TLV development is strongly governed by the interaction between surface rotation, surface convergence boundaries, and the low-level mesocyclone. Surface drag facilitates TLV formation by enhancing near-surface vortices and low-level lifting, mitigating the need for an intense updraft gradient developing close to the ground. As surface drag increases, a wider circulation near the surface blocks the inflow from directly reaching the rotating core, leading to a less tilted structure that allows the TLV position beneath the pressure minima aloft. Further increase in drag strength discourages TLV intensification by suppressing vertical stretching due to a negative vertical pressure perturbation gradient force, and it stops benefiting from the support of surrounding convergence boundaries and the overlying low-level updraft, instead becoming detached from them. We hence propose a favorable condition for TLV formation and duration where a TLV forms a less tilted structure directly beneath the low-level mesocyclone but also evolves near surrounding surface boundaries, which scenario strongly depends on underlying surface drag strength. </p><p dir="ltr">Beyond near-surface characteristics, we further explore how these storm-favorable environmental conditions may interact with the larger-scale synoptic patterns and how these interactions may affect the tornadic storm potential in the current warming climate. We employ hierarchical clustering analysis to classify the leading synoptic patterns driving tornadic storms across different geographic regions in the U.S. We find that the primary synoptic patterns are distinguishable across geographic regions and seasonalities. The intense upper-level jet streak described by the high values of eddy kinetic energy (EKE) associated with the dense distribution of Z500 contours dominates the tornado events in the southeast U.S. in the cold season (November-March). Late Spring and early Summer Tornado events in the central and south Great Plains are dominated by deep trough systems to the west axes of the tornado genesis position, while more summer events associated with weak synoptic forcing are positioned closer to the lee side of Rocky Mountain. Moreover, the increasing trend in tornado frequency in the southeastern U.S. is mainly driven by synoptic patterns with intense forcing, and the decreasing trends in portions of the Great Plains are associated with weak synoptic forcing. This finding indicates that the physical mechanisms driving the spatial trends of tornado occurrences differ across regions in the U.S.</p>