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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Comparison of INP Parameterizations for Dust Minerals in Climatological Simulations With a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in weather and climate prediction. We utilize an improved sectional dust module in NASA GISS Earth System ModelE2.1, which distinguishes eight different mineral species and accretions between iron oxides and the other minerals. Simulations over a period of 20 years have been carried out with this model, and the mineral fields and other model variables (temperature, relative humidity) are used to calculate the ice nucleating particle (INP) number concentration, applying time-independent and time-dependent INP parameterizations, such as active site parameterization and water activity based immersion freezing model (ABIFM). We study how the dependence of the parameterizations on different model variables affects the mean INP number concentration. The sensitivity of the INP number concentration to fundamental dust properties such as emitted mineral size distributions and mixing state between minerals is also investigated. Results show that the sensitivity of the total INP number concentration to the emitted dust size distribution is rather small, but the sensitivity over the whole size range obscures offsetting differences in the magnitude and the sign of the sensitivity between smaller and larger particles.

INP Parameterizations↗
NASA NTRS2022

Importance of Different Parameterization Changes for the Updated Dust Cycle Modeling in the Community Atmosphere Model (Version 6.1)

The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.

mineral dust parameterizations↗
DOE OSTI2023

Simulating Southern Ocean Aerosol and Ice Nucleating Particles in the Community Earth System Model Version 2

Southern Ocean (SO) low-level mixed phase clouds have been a long-standing challenge for Earth system models to accurately represent. While improvements to the Community Earth System Model version 2 (CESM2) resulted in increased supercooled liquid in SO clouds and improved model radiative biases, simulated SO clouds in CESM2 now contain too little ice. Previous observational studies have indicated that marine particles are major contributor to SO low-level cloud heterogeneous ice nucleation, a process that initiates a number of cloud processes that govern cloud radiative properties. In this study, we utilize detailed aerosol and ice nucleating particle (INP) measurements from two recent measurement campaigns to assess simulated aerosol abundance, number size distributions, and composition and INP parameterizations for use in CESM2. Our results indicate that CESM2 has a positive bias in simulated surface-level total aerosol surface area at latitudes north of 58°S. Measured INP populations were dominated by marine INPs and we present evidence of refractory INPs present over the SO assumed here to be mineral dust INPs. Results highlight a critical need to assess simulated mineral dust number and size distributions in CESM2 in order to adequately represent SO INP populations and their response to long-term changes in atmospheric transport patterns and land use change. Furthermore, we also discuss important cautions and limitations in applying a commonly used mineral dust INP parameterization to remote regions like the pristine SO.

58 GEOSCIENCES↗
NASA NTRS2003

Modeling the Absorbing Aerosol Index

We propose a scheme to model the absorbing aerosol index and improve the biomass carbon inventories by optimizing the difference between TOMS aerosol index (AI) and modeled AI with an inverse model. Two absorbing aerosol types are considered, including biomass carbon and mineral dust. A priori biomass carbon source was generated by Liousse et al [1996]. Mineral dust emission is parameterized according to surface wind and soil moisture using the method developed by Ginoux [2000]. In this initial study, the coupled CCM1 and GRANTOUR model was used to determine the aerosol spatial and temporal distribution. With modeled aerosol concentrations and optical properties, we calculate the radiance at the top of the atmosphere at 340 nm and 380 nm with a radiative transfer model. The contrast of radiance at these two wavelengths will be used to calculate AI. Then we compare the modeled AI with TOMS AI. This paper reports our initial modeling for AI and its comparison with TOMS Nimbus 7 AI. For our follow-on project we will model the global AI with aerosol spatial and temporal distribution recomputed from the IMPACT model and DAO GEOS-1 meteorology fields. Then we will build an inverse model, which applies a Bayesian inverse technique to optimize the agreement of between model and observational data. The inverse model will tune the biomass burning source strength to reduce the difference between modelled AI and TOMS AI. Further simulations with a posteriori biomass carbon sources from the inverse model will be carried out. Results will be compared to available observations such as surface concentration and aerosol optical depth.

Penner, Joyce↗
NASA NTRS2003

Effects of Non-Sphericity on Mineral Dust Modeling

The dependency of non-sphericity on gravitational settling of mineral dust particles is parameterized for prolate ellipsoids and Reynolds number lower than 2. The settling speed is numerically solved from the momentum equation as a function of particle diameter and aspect ratio. The reduction of settling speed due to non-sphericity is included in the GO-CART model to simulate dust size distribution for April 2001. Two numerical schemes for solving sedimentation are compared. For particles of diameter greater than 5 micron the simulated size distribution is sensitive to the numerical sedimentation scheme. Changing the particle shape from spherical to non-spherical with lambda=2, makes little difference to the simulated surface concentration and size distribution except at the periphery of the dust sources. However, when very elongated particles (lambda=5) are simulated the differences between non-spherical and spherical particles are significant. With limited in-situ measurements reporting most frequent lambda around 1.5, the overall effects on global modeling is rather negligible and the essential benefit is to relax the CFL condition of Eulerian settling schemes.

Ginoux, Paul↗
DOE OSTI2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Mineral Dust Cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry Model (Monarch) Version 2.0

We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust–radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20 µm, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000 Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about −0.90 and −0.63 W m−2 and at the top of the atmosphere between −0.20 and −0.28 W m−2. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations.

Dust cycle↗
NASA NTRS2011

A Sensitivity Study on the Effects of Particle Chemistry, Asphericity and Size on the Mass Extinction Efficiency of Mineral Dust in the Earth's Atmosphere: From the Near to Thermal IR

To determine a plausible range of mass extinction efficiencies (MEE) of terrestrial atmospheric dust from the near to thermal IR, sensitivity analyses are performed over an extended range of dust microphysical and chemistry perturbations. The IR values are subsequently compared to those in the near-IR, to evaluate spectral relationships in their optical properties. Synthesized size distributions consistent with measurements, model particle size, while composition is defined by the refractive indices of minerals routinely observed in dust, including the widely used OPAC/Hess parameterization. Single-scattering properties of representative dust particle shapes are calculated using the T-matrix, Discrete Dipole Approximation and Lorenz-Mie light-scattering codes. For the parameterizations examined, MEE ranges from nearly zero to 1.2 square meters per gram, with the higher values associated with non-spheres composed of quartz and gypsum. At near-IR wavelengths, MEE for non-spheres generally exceeds those for spheres, while in the thermal IR, shape-induced changes in MEE strongly depend on volume median diameter (VMD) and wavelength, particularly for MEE evaluated at the mineral resonant frequencies. MEE spectral distributions appear to follow particle geometry and are evidence for shape dependency in the optical properties. It is also shown that non-spheres best reproduce the positions of prominent absorption peaks found in silicates. Generally, angular particles exhibit wider and more symmetric MEE spectral distribution patterns from 8-10 micrometers than those with smooth surfaces, likely due to their edge-effects. Lastly, MEE ratios allow for inferring dust optical properties across the visible-IR spectrum. We conclude the MEE of dust aerosol are significant for the parameter space investigated, and are a key component for remote sensing applications and the study of direct aerosol radiative effects.

Hansell, R. A., Jr.↗
NASA NTRS2016

A51F-0123: Model Analysis of Tropospheric Aerosol Variability and Sources over the North Atlantic During NAAMES 2015-2016

The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) is a five-year Earth-Venture Suborbital-2 Mission to characterize the plankton ecosystems and their influences on remote marine aerosols, boundary layer clouds, and their implications for climate in the North Atlantic. While marine-sourced aerosols have been shown to make important contributions to surface aerosol loading, cloud condensation nuclei and ice nuclei concentrations over remote marine and coastal regions, it is still a challenge to differentiate the marine biogenic aerosol signal from the strong influence of continental pollution outflow. We examine here the spatiotemporal variability and quantify the sources of tropospheric aerosols over the North Atlantic during the first two phases (November 2015 and May-June 2016) of NAAMES using a state-of-the-art chemical transport model (GEOS-Chem). The model is driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) from the NASA Global Modeling and Assimilation Office (GMAO). It includes sulfate-nitrate-ammonium aerosol thermodynamics coupled to ozone-NOx-hydrocarbon-aerosol chemistry, mineral dust, sea salt, elemental and organic carbon aerosols, and especially a recently implemented parameterization for the marine primary organic aerosol emission. The simulated aerosols over the North Atlantic are evaluated with available satellite (e.g., MODIS) observations of aerosol optical depths (AOD), and aircraft and ship aerosol measurements. We diagnose transport pathways for continental pollution outflow over the North Atlantic using carbon monoxide, an excellent tracer for anthropogenic pollution transport. We also conduct model perturbation experiments to quantify the relative contributions of terrestrial and oceanic sources to the aerosol loading, AOD, and their variability over the North Atlantic.

aerosols↗
NASA NTRS2015

Evaluation of the Global Aerosol Microphysical ModelE2-TOMAS Model Against Satellite and Ground-Based Observations

The TwO-Moment Aerosol Sectional (TOMAS) microphysics model has been integrated into the state-of-the- art general circulation model, GISS ModelE2. This paper provides a detailed description of the ModelE2-TOMAS model and evaluates the model against various observations including aerosol precursor gas concentrations, aerosol mass and number concentrations, and aerosol optical depths. Additionally, global budgets in ModelE2-TOMAS are compared with those of other global aerosol models, and the ModelE2-TOMAS model is compared to the default aerosol model in ModelE2, which is a one-moment aerosol (OMA) model (i.e. no aerosol microphysics). Overall, the ModelE2- TOMAS predictions are within the range of other global aerosol model predictions, and the model has a reasonable agreement (mostly within a factor of 2) with observations of sulfur species and other aerosol components as well as aerosol optical depth. However, ModelE2-TOMAS (as well as ModelE2-OMA) cannot capture the observed vertical distribution of sulfur dioxide over the Pacific Ocean, possibly due to overly strong convective transport and over-predicted precipitation. The ModelE2-TOMAS model simulates observed aerosol number concentrations and cloud condensation nuclei concentrations roughly within a factor of 2. Anthropogenic aerosol burdens in ModelE2-OMA differ from ModelE2-TOMAS by a few percent to a factor of 2 regionally, mainly due to differences in aerosol processes including deposition, cloud processing, and emission parameterizations. We observed larger differences for naturally emitted aerosols such as sea salt and mineral dust, as those emission rates are quite different due to different upper size cutoff assumptions.

Lee, Y. H.↗
DOE OSTI2022

Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)

Abstract. The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

How the Emitted Size Distribution and Mixing State of Feldspar Affect Ice Nucleating Particles in a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in climate prediction. We apply an improved dust mineral specific aerosol module in the NASA GISS Earth System ModelE, which takes into account soil aggregates and their fragmentation at emission as well as the emission of large particles. We calculate ice nucleating particle concentrations from K-feldspar abundance for an active site parameterization for a range of activation temperatures and external and internal mixing assumption. We find that the globally averaged INP concentration is reduced by a factor of two to three, compared to a simple assumption on the size distribution of emitted dust minerals. The decrease can amount to a factor of five in some geographical regions. The results vary little between external and internal mixing and different activation temperatures, except for the coldest temperatures. In the sectional size distribution, the size range 24 micrometer contributes the largest INP number.

Perlwitz, Jan P.↗
DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗
NASA NTRS2013

Saharan Dust Event Impacts on Cloud Formation and Radiation over Western Europe

We investigated the impact of mineral dust particles on clouds, radiation and atmospheric state during a strong Saharan dust event over Europe in May 2008, applying a comprehensive online-coupled regional model framework that explicitly treats particle-microphysics and chemical composition. Sophisticated parameterizations for aerosol activation and ice nucleation, together with two-moment cloud microphysics are used to calculate the interaction of the different particles with clouds depending on their physical and chemical properties. The impact of dust on cloud droplet number concentration was found to be low, with just a slight increase in cloud droplet number concentration for both uncoated and coated dust. For temperatures lower than the level of homogeneous freezing, no significant impact of dust on the number and mass concentration of ice crystals was found, though the concentration of frozen dust particles reached up to 100 l-1 during the ice nucleation events. Mineral dust particles were found to have the largest impact on clouds in a temperature range between freezing level and the level of homogeneous freezing, where they determined the number concentration of ice crystals due to efficient heterogeneous freezing of the dust particles and modified the glaciation of mixed phase clouds. Our simulations show that during the dust events, ice crystals concentrations were increased twofold in this temperature range (compared to if dust interactions are neglected). This had a significant impact on the cloud optical properties, causing a reduction in the incoming short-wave radiation at the surface up to -75Wm-2. Including the direct interaction of dust with radiation caused an additional reduction in the incoming short-wave radiation by 40 to 80Wm-2, and the incoming long-wave radiation at the surface was increased significantly in the order of +10Wm-2. The strong radiative forcings associated with dust caused a reduction in surface temperature in the order of -0.2 to -0.5K for most parts of France, Germany, and Italy during the dust event. The maximum difference in surface temperature was found in the East of France, the Benelux, and Western Germany with up to -1 K. This magnitude of temperature change was sufficient to explain a systematic bias in numerical weather forecasts during the period of the dust event.

Bangert, M.↗
NASA NTRS1994

Modeling of mineral dust in the atmosphere: Sources, transport, and optical thickness

A global three-dimensional model of the atmospheric mineral dust cycle is developed for the study of its impact on the radiative balance of the atmosphere. The model includes four size classes of minearl dust, whose source distributions are based on the distributions of vegetation, soil texture and soil moisture. Uplift and deposition are parameterized using analyzed winds and rainfall statistics that resolve high-frequency events. Dust transport in the atmosphere is simulated with the tracer transport model of the Goddard Institute for Space Studies. The simulated seasonal variations of dust concentrations show general reasonable agreement with the observed distributions, as do the size distributions at several observing sites. The discrepancies between the simulated and the observed dust concentrations point to regions of significant land surface modification. Monthly distribution of aerosol optical depths are calculated from the distribution of dust particle sizes. The maximum optical depth due to dust is 0.4-0.5 in the seasonal mean. The main uncertainties, about a factor of 3-5, in calculating optical thicknesses arise from the crude resolution of soil particle sizes, from insufficient constraint by the total dust loading in the atmosphere, and from our ignorance about adhesion, agglomeration, uplift, and size distributions of fine dust particles (less than 1 micrometer).

Tegen, Ina↗
NASA NTRS2010

Interactions Between Mineral Dust, Climate, and Ocean Ecosystems

Over the past decade, technological improvements in the chemical and physical characterization of dust have provided insights into a number of phenomena that were previously unknown or poorly understood. In addition, models are now incorporating a wider range of physical processes, which will allow us to better quantify the climatic and ecological impacts of dust. For example, some models include the effect of dust on oceanic photosynthesis and thus on atmospheric CO 2 (Friedlingstein et al. 2006). The impact of long-range dust transport, with its multiple forcings and feedbacks, is a relatively new and complex area of research, where input from several disciplines is needed. So far, many of these effects have only been parameterized in models in very simple terms. For example, the representation of dust sources remains a major uncertainty in dust modeling and estimates of the global mass of airborne dust. This is a problem where Earth scientists could make an important contribution, by working with climate scientists to determine the type of environments in which easily erodible soil particles might have accumulated over time. Geologists could also help to identify the predominant mineralogical composition of dust sources, which is crucial for calculating the radiative and chemical effects of dust but is currently known for only a few regions. Understanding how climate and geological processes control source extent and characterizing the mineral content of airborne dust are two of the fascinating challenges in future dust research.

Gasso, Santiago↗
DOE OSTI2023

Effects from Time Dependence of Ice Nucleus Activity for Contrasting Cloud Types

Abstract The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) supercooled, stratiform clouds over the United Kingdom, observed during the Aerosol Properties, Processes And Influences on the Earth’s climate (APPRAISE) campaign. AC uses the dynamical core of the WRF Model and has hybrid bin–bulk microphysics and a 3D mesoscale domain. AC is validated against coincident aircraft, ground-based, and satellite observations for all three cases. Filtered concentrations of ice (>0.1–0.2 mm) agree with those observed at all sampled levels. AC predicts the INP activity of various types of aerosol particles with an empirical parameterization (EP), which follows a singular approach (no time dependence). Here, the EP is modified to represent time-dependent INP activity by a purely empirical approach, using our published laboratory observations of time-dependent INP activity. In all simulated clouds, the inclusion of time dependence increases the predicted INP activity of mineral dust particles by 0.5–1 order of magnitude. However, there is little impact on the cloud glaciation because the total ice is mostly (80%–90%) from secondary ice production (SIP) at levels warmer than about −36°C. The Hallett–Mossop process and fragmentation in ice–ice collisions together initiate about 70% of the total ice, whereas fragmentation during both raindrop freezing and sublimation contributes <10%. Overall, total ice concentrations and SIP are unaffected by time-dependent INP activity. In the simulated APPRAISE case, the main causes of persistence of long-lived clouds and precipitation are predicted to be SIP in weak embedded convection and reactivation following recirculation of dust particles in supercooled layer cloud.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Implementation of a Comprehensive Ice Crystal Formation Parameterization for Cirrus and Mixed-Phase Clouds in the EMAC Model (Based on MESSy 2.53)

A comprehensive ice nucleation parameterization has been implemented in the global chemistry-climate model EMAC to realistically represent ice crystal number concentrations. The parameterization of Barahona and Nenes (2009, hereafter BN09) allows the treatment of ice nucleation, taking into account the competition for water vapour between homogeneous and heterogeneous nucleation and pre-existing ice crystals in cold clouds. Furthermore, the influence of chemically-heterogeneous, polydisperse aerosols is considered via multiple ice nucleating particle spectra, which are included in the parameterization to compute the heterogeneously formed ice crystals. BN09 has been implemented to operate both in the cirrus and in the mixed-phase regimes. Compared to the standard EMAC results, BN09 produces fewer ice crystals in the upper troposphere but higher ice crystal number concentrations in the middle troposphere, especially in the Northern Hemisphere where ice nucleating mineral dust particles are relatively abundant. The comparison with a climatological data set of aircraft measurements shows that BN09 used in the cirrus regime improves the model results and, therefore, is recommended for future EMAC simulations.

EMAC↗