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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Micro-spectroscopic and freezing characterization of ice-nucleating particles collected in the marine boundary layer in the eastern North Atlantic

Abstract. Formation of atmospheric ice plays a crucial role in the microphysical evolution of mixed-phase and cirrus clouds and thus climate. How aerosol particles impact ice crystal formation by acting as ice-nucleating particles (INPs) is a subject of intense research activities. To improve understanding of atmospheric INPs, we examined daytime and nighttime particles collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign conducted in summer 2017. Collected particles, representative of a remote marine environment, were investigated for their propensity to serve as INPs in the immersion freezing (IMF) and deposition ice nucleation (DIN) modes. The particle population was characterized by chemical imaging techniques such as computer-controlled scanning electron microscopy with energy-dispersive X-ray analysis (CCSEM/EDX) and scanning transmission X-ray microscopy with near-edge X-ray absorption fine-structure spectroscopy (STXM/NEXAFS). Four major particle-type classes were identified where internally mixed inorganic–organic particles make up the majority of the analyzed particles. Following ice nucleation experiments, individual INPs were identified and characterized by SEM/EDX. The identified INP types belong to the major particle-type classes consisting of fresh sea salt with organics or processed sea salt containing dust and sulfur with organics. Ice nucleation experiments show IMF events at temperatures as low as 231 K, including the subsaturated regime. DIN events were observed at lower temperatures of 210 to 231 K. IMF and DIN observations were analyzed with regard to activated INP fraction, ice-nucleation active site (INAS) densities, and a water activity-based immersion freezing model (ABIFM) yielding heterogeneous ice nucleation rate coefficients. Observed IMF and DIN events of ice formation and corresponding derived freezing rates demonstrate that the marine boundary layer aerosol particles can serve as INPs under typical mixed-phase and cirrus cloud conditions. The derived IMF and DIN parameterizations allow for implementation in cloud and climate models to evaluate predictive effects of atmospheric ice crystal formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimation of wintertime cloud radiative effects in the Western Arctic, a function of cloud-moisture-coupling and sea ice conditions

Cloud radiative effects are estimated using up- and downward ground-based observations of broadband thermal infrared sensors in cloudy conditions which are provided by the ARM data repository. The ARM Surface Radiation measurement is analyzed. To study the cloud radiative effects, the observed thermal infrared measurements under cloudy conditions are analyzed together with microphysical cloud properties like liquid and ice water path obtained from the CloudNet algorithms applied to the remote-sensing instrumentation suite at the ARM site in Utqiagvik. Cloud observations have been sorted depending on the coupling of the cloud with upwind water vapor transport events that can interact with sea ice upwind. Statistics of surface net thermal fluxes and cloud water/ice properties show a distinguished distribution for coupled and decoupled clouds. It was found that coupled clouds contain more liquid water and are more efficient reduce the cooling of surface LW radiation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving GCM Representation of Convective Cloud Microphysics by Using ARM Raman Lidar and Cloud Radar Observations

The overall objective of this Department of Energy (DOE) Atmospheric System Research (ASR) funded project is to improve the representation of convective cloud microphysics in global climate models (GCMs) and check it by comparing the model simulations with observations. We have derived the cloud ice water content by synthesizing ARM Raman lidar (RL) and cloud radar observations at the Atmospheric Radiation Measurement (ARM) sites. Noting that the simulated anvil clouds in terms of their macro- and micro-physical properties are sensitive to the parameterization of convective microphysical processes, observed ice water content in anvil clouds provides a useful constraint on these parameterizations. We have improved the convective microphysics parameterization scheme by (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. We have examined the impact of improved convective cloud microphysics parameterization on the simulated global climate from GCM simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A New Method for Ice-Ice Aggregation in the Adaptive Habit Model

In this paper, a novel methodology for modeling ice-ice aggregation is presented. This methodology combines a modified hydrodynamic collection algorithm with bulk aggregate characteristic information from an offline simulator that collects ice particles, namely, the Ice Particle and Aggregate Simulator, and has been implemented into the Adaptive Habit Microphysics scheme in the Weather Research and Forecasting Model. Aggregates, or snow, are formed via collection of cloud ice particles, where initial ice characteristics and the resulting geometry determine aggregate characteristics. Upon implementation, idealized squall-line simulations are performed to examine the new methodology in comparison with commonly used bulk microphysics schemes. It is found that the adaptive habit aggregation parameterization develops snow and reduces ice mass and number concentrations compared to other schemes. The development of aggregates through the new methodology cascades into other interesting effects, including enhancements in ice and snow growth, as well as homogeneous freezing. Further microphysical analyses reveal varying sensitivities, where snow processes are most sensitive to the new parameterization, followed by ice, then cloud, rain, and graupel processes. Further, the new scheme results in enhancements in surface precipitation due to the persistence of snow at lower altitudes. This persistence is a result of shape-dependent melting and sublimation, increasing the residence time. Moreover, these low-level enhancements are reflected in increases in radar reflectivity at the surface and its spatial distribution. Finally, the ability to predict snow shape and density allows for the simulation of polarimetric radar quantities, resulting in signature enhancements compared to schemes that do not consider spatial and temporal variations in snow shape and density.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ice nucleation by volcanic ash greatly alters cirrus cloud properties

The formation of ice crystals in the atmosphere strongly affects cloud properties and climate. While volcanic ash (VA) has been shown to nucleate ice crystals efficiently in laboratory settings, its importance for ice formation in the atmosphere remains elusive. Here, we show evidence of cirrus modification by volcanic eruptions through ice nucleation on VA, revealed by abrupt changes in cirrus properties following volcanic eruptions based on satellite measurements. The distinct changes captured are a phenomenal decrease in number, an increase in size of ice crystals in cirrus clouds, and an increase in cirrus occurrences after ash-rich volcanic eruptions. Conversely, no such changes were detected following the ash-poor eruption. We propose a cirrus formation mechanism where VA nucleates ice heterogeneously, suppressing homogeneous freezing and resulting in fewer but larger ice crystals. This suppression of homogeneous freezing by VA is supported by process-level cloud microphysical simulations. Our findings advance the understanding of aerosol–ice cloud interactions and illuminate cirrus geoengineering.

Lin, Lin [Texas A & M Univ., College Station, TX (↗
DOE OSTI2021

Survival of Snow in the Melting Layer: Relative Humidity Influence

This study quantifies how far snow can fall into the melting layer (ML) before all snow has melted by examining a combination of in-situ observations from aircraft measurements in Lagrangian spiral descents from above through the ML and descents and ascents into the ML, as well as an extensive database of NOAA surface observer reports during the past 50 years. The airborne data contain information on the particle phase (solid, mixed, or liquid), population size distributions and shapes, along with temperature, relative humidity, and vertical velocity. A wide range of temperatures and ambient relative humidities are used for both the airborne and ground-based data. It is shown that an ice bulb temperature of 0°C, together with the air temperature and pressure (altitude), are good first order predictors of the highest temperature snowflakes can survive in the melting layer before completely melting. Particle size is also important, as is whether the particles are graupel or hail. If the relative humidity is too low, the particles will sublimate completely as they fall into the melting layer. Snow as warm as +7°C is observed from aircraft measurements and surface observations. Snow pellets survive to even warmer temperatures. Relationships are developed to represent the primary findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Aerosol–Ice Formation Closure: A Southern Great Plains Field Campaign

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. Furthermore, the closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

58 GEOSCIENCES↗
DOE OSTI2025

An Improved Convection Parameterization with Detailed Aerosol–Cloud Microphysics for a Global Model

Abstract A new microphysical treatment that includes aerosol–cloud interactions and secondary ice production (SIP) mechanisms is implemented in the convection scheme of the Community Atmosphere Model, version 6 (CAM6). The approach is to embed a 1D Lagrangian parcel model in the bulk convective plume of the existing deep convection parameterization. Aerosol activation, growth processes including collision/coalescence, and three processes of SIP mechanisms, two of which are normally overlooked in atmospheric models, are represented in this embedded parcel model. These microphysical processes are treated with a hybrid bin/bulk scheme and a high spatial and temporal resolution for the integration of the embedded parcel in 1D, allowing vertical velocity to determine the microphysical evolution following the in-cloud motion during ascent. Simulations of an observed case (Midlatitude Continental Convective Clouds Experiment) of a mesoscale convective system in Oklahoma, United States, with a single-column model (SCAM) version of CAM, are compared with aircraft in situ and ground-based observations of microphysical properties from the convection and precipitation. Results from the validation show the new microphysical scheme has a good representation of the ice initiation in the bulk convective plume, including the known and empirically quantified pathways of primary and secondary initiation, with benefits for the accuracy of properties of its supercooled cloud liquid. The sensitivity simulations and use of tagging tracers for the validated simulation confirm that the newly included SIP mechanisms are of paramount importance for convective microphysics and can be successfully treated in the global model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Theory for the Balance between Warm Rain and Ice Crystal Processes of Precipitation in Mixed-Phase Clouds

Abstract Mixed-phase clouds contain both supercooled cloud liquid and ice crystals. In principle, precipitation may be initiated either by the liquid phase or by the ice phase. Ice crystals may grow by vapor diffusion to become snow (“ice crystal process”), forming “cold” precipitation. Equally, cloud droplets, when large enough, coalesce to form “warm” precipitation by the “warm rain process.” Warm rain could be supercooled and freeze as “warm” graupel. In the present paper, a new simplified theoretical analysis is provided to examine the microphysical system consisting of three species of hydrometeor, namely, cloud liquid, “cold ice” (crystals, snow), and “warm rain” (frozen or supercooled). This is obtained by nondimensionalizing and simplifying the evolution equations for the mass of each species. Analytical formulas are given for equilibria. Feedback analysis shows that the sign of the feedback is linked to the abundance of precipitation, with a neutral surface in the 3D phase space. The system’s precipitation amount explodes while in the initial unstable regime, crossing the neutral surface and approaching the equilibrium point that is a stable attractor. Positive and negative feedbacks are elucidated. In a standard case, the cold ice mass is about 1000 times larger than the warm rain mass. To illustrate the physical behavior of the theory, sensitivity tests are performed with respect to environmental conditions (e.g., aerosol, updraft speed) and microphysical parameters (e.g., riming and sedimentation rates for cold ice). Cold ice prevails, especially in fast ascent, due to its low bulk density, favoring slow sedimentation and a wide cross-sectional area for riming. Significance Statement The theory elucidates how the ice phase can prevail in the precipitation from any mixed-phase clouds with supercooled cloud liquid and crystals. The ice phase radically suppresses cloud liquid by riming when active and “wins” the competition against coalescence. This prevalence of ice is shown to arise from the low bulk density of snow. The cloud is viewed as a system of negative and positive feedbacks that prevail in realms of stability and instability in a 3D phase space.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Quantifying Uncertainty in Ice Particle Velocity–Dimension Relationships Using MC3E Observations

Abstract Ice particle terminal fall velocity ( V t ) is fundamental for determining microphysical processes, yet remains extremely challenging to measure. Current theoretical best estimates of V t are functions of Reynolds number. The Reynolds number is related to the Best number, which is a function of ice particle mass, area ratio ( A r ), and maximum dimension ( D max ). These estimates are not conducive for use in most models since model parameterizations often take the form , where ( α , β ) depend on habit and D max . A previously developed framework is used to determine surfaces of equally plausible ( α , β ) coefficients whereby ice particle size/shape distributions are combined with V t best estimates to determine mass- ( V M ) or reflectivity-weighted ( V Z ) velocities that closely match parameterized V M ,SD or V Z ,SD calculated using the ( α , β ) coefficients using two approaches. The first uses surfaces of equally plausible ( a , b ) coefficients describing mass ( M )–dimension relationships (i.e., ) to calculate mass- or reflectivity-weighted velocity from size/shape distributions that are then used to determine ( α , β ) coefficients. The second investigates how uncertainties in A r , D max , and size distribution N ( D ) affect V M or V Z . For seven of nine flight legs flown on 20 and 23 May 2011 during the Mesoscale Continental Convective Clouds Experiment (MC3E), uncertainty from natural parameter variability—namely, the variability in ice particle parameters in similar meteorological conditions—exceeds uncertainties arising from different A r assumptions or D max estimates. The combined uncertainty between A r , D max , and N ( D ) produced smaller variability in ( α , β ) compared to varying M ( D ), demonstrating M ( D ) must be accurately quantified for model fall velocities. Primary sources of uncertainty vary considerably depending on environmental conditions. Significance Statement Ice particle fall velocity is fundamental for numerous processes within clouds, and hence is a critical property that must be accurately represented in weather and climate models. Using aircraft observations of ice particle shapes and sizes obtained in clouds behind midlatitude thunderstorms, this work develops a new framework for estimating ice particle fall velocities and their uncertainty, including quantifying the importance of different uncertainty sources from cloud microphysics measurements. Natural parameter variability contributes the most uncertainty in ice particle fall velocity estimates, although other sources can also be important contributors to uncertainty in certain conditions. Additional work examining ice particle data is needed to further understand how dependent uncertainty in certain ice particle properties are to local environmental conditions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Modeling impacts of ice-nucleating particles from marine aerosols on mixed-phase orographic clouds during 2015 ACAPEX field campaign

Abstract. A large fraction of annual precipitation over the western United States comes from wintertime orographic clouds associated with atmospheric rivers (ARs). Transported African and Asian dust and marine aerosols from the Pacific Ocean may act as ice-nucleating particles (INPs) to affect cloud and precipitation properties over the region. Here we explored the effects of INPs from marine aerosols on orographic mixed-phase clouds and precipitation at different AR stages for an AR event observed during the 2015 ACAPEX field campaign under low dust (<0.02 cm−3) conditions. Simulations were conducted using the chemistry version of the Weather Research and Forecasting Model coupled with the spectral-bin microphysics at 1 km grid spacing, with ice nucleation connected with dust and marine aerosols. By comparing against airborne and ground-based observations, accounting for marine INP effects improves the simulation of AR-precipitation. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds, as well as to a large spillover effect of precipitation after AR landfall. The responses of cloud and precipitation to marine INPs vary with the AR stages, with more significant effects before AR landfall and post-AR than after AR landfall, mainly because the moisture and temperature conditions change with the AR evolution. This work suggests weather and climate models need to consider the impacts of marine INPs since their contribution is notable under low dust conditions despite the much lower relative ice nucleation efficiency of marine INPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

microbase.c1

MICROBASE is a baseline retrieval of cloud microphysical properties. It uses a combination of observations from the cloud radar, ceilometer, micropulse lidar, microwave radiometer, and balloon-borne radiosonde soundings in order to produce instantaneous vertical profiles of cloud liquid water content (LWC), cloud ice water content (IWC), liquid cloud particle effective radius (LIQRE), and ice cloud particle effective radius (ICERE). Uncertainites are also produced by the VAP. The inputs are by the following VAPs: Active Remote Sensing of Clouds (ARSCL) Merged Sounding (MERGESONDE) Microwave Radiometer Retrievals (MWRRET) The output are daily files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multiple Environmental Influences on the Lightning of Cold-Based Continental Convection. Part II: Sensitivity Tests for Its Charge Structure and Land–Ocean Contrast

In Part I, an electrification scheme was described and a simulation of an observed cold-based storm from the U.S. Great Plains was validated with electrical observations. Most charge in the storm was separated by rebounding collisions of secondary ice originating from prior graupel–snow collisions. In this Part II, sensitivity tests are performed with the control simulation (Part I) and influences from environmental factors (aerosols, temperature, moisture, and shear) on lightning are elucidated. Environmental factors [e.g., convective available potential energy (CAPE)] controlling updraft speed are salient. When ascent is reduced by 30% and 70%, flashes become 70% fewer and disappear, respectively; faster ascent promotes positive cloud-to-ground (+CGs) flashes. Since cloud base is too cold (1°C) for coalescence, cloud condensation nucleus aerosol concentrations do not influence the lightning appreciably. The electrical response to varying concentrations of active ice nuclei is limited by most ice particles being secondary and less sensitive—a natural “buffer.” Imposing a maritime sounding suggests that the land–sea contrast in lightning for such storms is due to the vertical structure of environmental temperature and humidity. Weak CAPE, and both entrainment and condensate weight from a low cloud base, suppress ascent and charging. Maritime thermodynamic conditions reduce simulated flash rates by two orders of magnitude. Reducing aerosol loadings from continental to maritime only slightly reinforces this suppression. Last, a conceptual model is provided for how any simulated storm is either normal because graupel/hail is mostly positively charged or else is inverted/anomalous because graupel/hail is mostly negatively charged, with environmental factors controlling the charging. Impacts from microphysical processes, including three processes of secondary ice production, on lightning are analyzed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment

Abstract. Mixed-phase clouds affect precipitation and radiation differently from liquid and ice clouds, posing greater challenges to their representation in numerical simulations. Recent laboratory experiments using the Pi Cloud Chamber explored cloud glaciation conditions based on increased injection of ice-nucleating particles. In this study, we use two approaches to reproduce the results of the laboratory experiments: a bulk scalar mixing model and large-eddy simulation (LES) with bin microphysics. The first approach assumes a well-mixed domain to provide an efficient assessment of the mean cloud properties for a wide range of conditions. The second approach resolves the energy-carrying turbulence, the particle size distribution, and their spatial distribution to provide more details. These modeling approaches enable a separate and detailed examination of liquid and ice properties, which is challenging in the laboratory. Both approaches demonstrate that, with an increased ice number concentration, the flow and microphysical properties exhibit the same changes in trends. Additionally, both approaches show that the ice integral radius reaches the theoretical glaciation threshold when the cloud is subsaturated with respect to liquid water. The main difference between the results of the two approaches is that the bulk model allows for the complete glaciation of the cloud. However, LES reveals that, in a dynamic system, the cloud is not completely glaciated as liquid water droplets are continuously produced near the warm lower boundary and subsequently mixed into the chamber interior. These results highlight the importance of the ice mass fraction in distinguishing the mixed-phase clouds and ice clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

On the Links Between Ice Nucleation, Cloud Phase, and Climate Sensitivity in CESM2

Ice nucleation in mixed-phase clouds has been identified as a critical factor in projections of future climate. Here we explore how this process influences climate sensitivity using the Community Earth System Model 2 (CESM2). We find that ice nucleation affects simulated cloud feedbacks over most regions and levels of the troposphere, not just extratropical low clouds. However, with present-day global mean cloud phase adjusted to replicate satellite retrievals, similar total cloud feedback is attained whether ice nucleation is simulated as aerosol-sensitive, insensitive, or absent. These model experiments all result in a strongly positive total cloud feedback, as in the default CESM2. A microphysics update from CESM1 to CESM2 had substantially weakened ice nucleation, due partly to a model issue. Our findings indicate that this update reduced global cloud phase bias, with CESM2's high climate sensitivity reflecting improved mixed-phase cloud representation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spanning the Gap From Bulk to Bin: A Novel Spectral Microphysics Method

Microphysics methods for climate models and numerical weather prediction typically track one, two, or three moments of a droplet size distribution for various categories of liquid, ice, and aerosol. Such methods rely on conversion parameters between these categories, which introduces uncertainty into predictions. While higher-fidelity options such as bin and Lagrangian schemes exist, they require too many degrees of freedom for climate modeling applications and introduce numerical challenges. Here we introduce a flexible spectral microphysics method based on collocation of basis functions. This method generalizes to a linear bulk scheme when using few basis functions and to a smoothed bin scheme with more degrees of freedom. Tested in an idealized box setting, the method improves spectral accuracy for droplet collision-coalescence and may eliminate the need for precipitation autoconversion rates required by bulk methods; furthermore, it generalizes well to multimodal distributions with less complexity than a bin method. The potential to extend this collocation representation to multiple hydrometeor classes suggests a path forward to unify liquid, ice, and aerosol microphysics in a single, flexible, computational framework for climate modeling.

54 ENVIRONMENTAL SCIENCES↗