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At least 163 records · Page 9

Physics Division Strategic Plan Fiscal Years 2020-2024

The vision of the Physics Division (PHY) at Argonne National Laboratory is to continue enhancing its role as a world-leading institution in basic nuclear physics research and its applications. Key to this vision is for PHY to continue to safely and effectively operate and evolve the capabilities of the Argonne Tandem Linac Accelerator System (ATLAS) facility to best serve its users. ATLAS is the Department of Energy (DOE) accelerator facility for low-energy nuclear physics research. The research carried out by PHY covers many themes in contemporary science but can be distilled into five areas of focus. These themes are interconnected, with continuously evolving synergies between the various groups and facilities in PHY and the broader Laboratory. This five-year strategic plan serves to illustrate our current capabilities and new directions related to these five areas of focus (ATLAS also develops an independent strategic plan): Accelerator research and design. The goal of this theme is to design, fabricate, test, and implement novel accelerator systems, with a focus on high-intensity ion and electron systems. These R&D activities have led to enhancements in the ATLAS accelerator system. Among others, the division’s accelerator systems are in use or planned for use at Fermilab, the Advanced Photon Source, and in a broad variety of applications at the Facility for Rare Isotope Beams (FRIB). Atom trapping and fundamental symmetries. The goal of this theme is to explore and exploit the uses of advanced laser cooling and trapping techniques to manipulate atoms. There are three main areas of focus. First is in the application of the atom trap trace analysis (ATTA) technique for age determination of groundwater and ice by using radio-krypton dating. The next two trapping-based programs involve tests of fundamental symmetries in nature: the cooling and trapping of radium-225 with the aim of determining limits on an observation of its electric dipole moment and precision measurements of the beta decay properties of helium-6 to set limits on the tensor coupling constant. This is complemented by measurements of similar properties in lithium-8 and boron-8. Nuclear astrophysics. The goal of this theme is to enhance our understanding of how elements are created in the universe via explosive nucleosynthesis and how stars evolve. To meet the challenges of this theme, many of the capabilities of ATLAS are being enhanced, including the development of new beams through a new in-flight separator (RAISOR) and the anticipated neutron-generator upgrade of the Californium Rare Isotope Breeder Upgrade facility (nuCARIBU). These are coupled to state-of-the-art instruments such as the Canadian Penning Trap, Helical Orbit Spectrometer, Gammasphere, GRETINA, Multi-Sampling Ionization Chamber, the Fragment Mass Analyzer, and Argonne Gas-filled Fragment Analyzer, and a new low-background experimental area for decay studies. Nuclear structure. The goal of this theme is to understand the structure of nuclei, both stable and radioactive, in terms of single-particle properties, their shapes, and the dynamics governing reactions between them. These include questions such as what are the limits of nuclear stability and what are the properties of super heavy nuclei. As with the nuclear astrophysics theme, the capabilities of ATLAS, guided by the ATLAS user community, are continuously being enhanced to this end. The Division has strategic initiatives to play a leading role in the development of instrumentation and research programs at the FRIB. Quantum chromodynamics (QCD) and hadron physics. The goal of this theme is to lead major research programs focused on revealing the quark and gluon structure of protons, neutrons, nuclei, and short-lived mesons and baryons. These involve major programs at Jefferson Lab, Fermilab, and smaller facilities. They are complemented by theoretical endeavors centered on the question of how hadrons and their properties emerge from QCD. Out of these activities arise strategic initiatives to play a major role in the forthcoming Electron-Ion Collider (EIC).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Evolution of Lidar Networks: A US Perspective

Atmospheric aerosols and clouds play an important role in climate by directly scattering and absorbing sunlight. Aerosol-cloud interactions modify the particle properties causing indirect effects, alter aerosol deposition and rainfall, and contribute substantially to the uncertainties in predicting climate effects. Aerosols also affect air quality and both constituents modulate boundary layer dynamics to a certain extent, in turn impacting aerosol transport and aerosol-cloud interactions. The spatiotemporal distribution of aerosol and cloud layers is thus important, and lidar remains the primary instrument for determining the vertical distribution of aerosols and thin clouds. Lidar still provides important information for opaque cloud layers by determining base heights. Combined lidar and radar data provide a comprehensive coverage of aerosol and cloud vertical distributions, and thus locations where and when they interact. Lidar data provide a means of constraining column aerosol loading observations (e.g. AOD) to vertical extents. In addition, lidar has proven effective at determining a proxy for boundary layer height by examining aerosol gradients and/or cloud base heights in lidar profiles. Polarized lidars provide additional information on particle shape, allowing estimates of cloud phase and separation of dust or smoke from sulfate and sea salt aerosols. Given the importance of lidar observations and a critical maturation in technology and retrieval techniques, several organizations began to build operational lidar networks around 2000. The European Aerosol Research Lidar Network (EARLINET) was started as a research focused network of advanced lidars across Europe. The Asian Dust Lidar Network (ADNET) was also developed as a regional network providing lidar profiles of dust and pollution across Eastern Asia. In the US, the NASA Micro Pulse Lidar Network (MPLNET) was created to provide global lidar profiling at key sites in the NASA Aerosol Robotic Network (AERONET). The Network for the Detection of Atmospheric Composition Change (NDACC) pre-dates these networks and many sites have lidar, but it is not strictly a lidar network and at the time focused less on the lower troposphere. Finally, there were already existing ceilometer networks operated by various meteorological agencies, but in particular here in the US the profile data has not been available. The ceilometer networks were used to provide only clouds base heights and estimates of PBL height. Thus, the distinguishing feature between lidar and ceilometer networks was historically the ability to actually provide profile information (in addition to differences in wavelength, and advanced retrievals such as the raman technique). As time progressed, each lidar network matured and developed more operational capabilities and data sets, coupled with viable data centers providing DAAC services and access to near-real-time (NRT) data. In 2008 under WMO guidance, the Global Atmospheric Watch (GAW) Aerosol Lidar Observation Network (GALION) was formed as a global network made up of the existing lidar networks. The goal was to share information, best practices, and develop frameworks and techniques for quality data. GALION grew to include several other regional lidar networks and this has led to a vast increase in quality lidar sites worldwide.

Welton, Ellsworth J.↗

Soot Superaggregates from Flaming Wildfires and Their Direct Radiative Forcing

Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension D(sub f) approximately equals 1.8 mobility diameter D(sub m) (is) less than or equal to 1 micron, and aerodynamic diameter D(sub a) (is) less than or equal to 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic D(sub f) approximately equals 2.6,D(sub m) (is) greater than 1 micron, and D(sub a) is less than or equal to 300 nm that form via the cluster-dense aggregation mechanism.We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. We estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (D(sub f) approximately equals 1.8) aggregates, and approximately equals 90% more warming than the volume-equivalent spherical soot particles simulated in climate models.

SAS↗

Very small-scale, segregating-fluidized-bed experiments: A dataset for CFD-DEM validation and uncertainty quantification

IWe report fluidization experiments were conducted on a small scale and with a rapid response (short duration) to enable corresponding simulations at low-computational cost. Rise times are reported for four or fewer polyethylene particles (intruders) in an air-fluidized bed of ~5000 group D glass beads. Experimental inputs were completely characterized—particle properties, system dimensions and operating conditions—which is necessary for validating computational fluid mechanics (CFD)-discrete element method (DEM) including a comprehensive uncertainty quantification (UQ) analysis. Input uncertainties are reported as bounds or cumulative distribution functions of measured values. The staggering number of simulations required to complete a UQ analysis (~O[10 4 ] simulations corresponding to ~5 uncertain inputs) motivates this study. These segregating-bed experiments are designed to permit analogous CFD-DEM simulations to complete in less than a day on a single (~2.5 GHz) computational processor unit (CPU). Segregation times are reported for several operating conditions, intruder sizes, and initial configurations, providing a rich dataset for numerical model testing, validation and UQ.

42 ENGINEERING↗

Model for Independent Particle Motion

Independent particle model in nuclear physics assumes that the nucleon in the nucleus moves in the average (mean field) potential generated by all other nucleons. This chapter gives a short overview of basic features of the independent particle motion in atomic nuclei and its theoretical realization in the framework of shell models for spherical, deformed, and rotating nuclei as well as in more sophisticated approaches such as microscopic+macroscopic model and density functional theories. Independent particle motion of nucleons leads to global and single-particle consequences. The global ones manifest themselves in the shell structure, and its consequences for the global structure of nuclear landscape, the existence of superheavy nuclei, and the superdeformation at high spin are briefly reviewed. Finally, the latter shows itself in the single-particle properties such as energies, alignments, and densities; their manifestations are illustrated on specific examples.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ponderomotive effects of ultralight dark matter

I exhibit a new class of quadratic effects of ultralight dark matter. Axions, dark photons, and dilatons can exert rapidly oscillating forces, torques, and mass shifts on Standard Model particles. These effects average to zero at first order, but shift particle properties at second order, in analogy to the ponderomotive force in optics. Remarkably, these effects scale with the square of the amplitude of the dark matter field, even when the field’s direct physical effects depend only on its derivatives. I calculate the resulting observables in electron ge – 2 experiments using classical mechanics, recovering results previously derived using field theory. When considered properly, these particular experiments do not beat astrophysical bounds, but other precision experiments may have interesting sensitivity.

Zhou, Kevin↗

Effect of Topology on Transient Dynamic and Shock Response of Polymeric Lattice Structures

Architected cellular materials, such as lattice structures, offer potential for tunable mechanical properties for dynamic applications of energy absorption and impact mitigation. In this work, the static and dynamic behavior of polymeric lattice structures was investigated through experiments on octet-truss, Kelvin, and cubic topologies with relative densities around 8%. Here, dynamic testing was conducted via direct impact experiments (25–70 m/s) with high-speed imaging coupled with digital image correlation and a polycarbonate Hopkinson pressure bar. Mechanical properties such as elastic wave speed, deformation modes, failure properties, particle velocities, and stress histories were extracted from experimental results. At low impact velocities, a transient dynamic response was observed which was composed of a compaction front initiating at the impact surface and additional deformation bands whose characteristics matched low strain-rate behavior. For higher impact velocities, shock analysis was carried out using compaction wave velocity and Eulerian Rankine–Hugoniot jump conditions with parameters determined from full-field measurements.

36 MATERIALS SCIENCE↗

Improving Aerosol Radiative Forcing and Climate in E3SM: Impacts of New Cloud Microphysics and Improved Wet Removal Treatments

Abstract Numerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m −2 , while the ZM_plus increases it by 0.27 W m −2 , resulting from excessive direct (0.31 W m −2 ) and indirect forcing (−1.79 W m −2 ). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m −2 ) and indirect aerosol forcing (−1.52 W m −2 ). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m −2 and −1.31 W m −2 , respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.

54 ENVIRONMENTAL SCIENCES↗

Understanding Biases in Simulated Cloud Radiative Effects in E3SMv3

This study systematically investigates biases in cloud radiative effects (CREs) within the recently released Energy Exascale Earth System Model version 3 (E3SMv3). Compared to its previous version (E3SMv2), E3SMv3 shows excessively strong shortwave CRE over tropical and subtropical oceans, the Southern Ocean, and the Northern Hemisphere storm tracks, which is primarily caused by an overestimation of optically intermediate low clouds. The model also displays excessive longwave CRE over the Maritime Continent and other tropical deep convection regions, resulting from an overestimation of optically thick high clouds. Implementing the Predicted Particle Properties (P3) scheme for stratiform clouds played the most significant role in these cloud changes. In addition, using a double-moment scheme for convective clouds contributed to the increase in intermediate low clouds and optically thick clouds in tropical deep convection regions. Error metrics for total cloud amount (E TCA ), cloud properties (E ctp-τ ), and cloud properties weighted by their SW and LW radiative impacts (E SW and E LW ) indicate that E3SMv3's ability to reproduce observed cloud radiative effect of low, middle, and high clouds has not been improved compared to E3SMv2. Nevertheless, the performance of E3SMv3 remains well within the spread of CMIP6 models, with E SW and E LW values smaller than those in most CMIP6 models. This study underscores the importance of integrating diverse satellite observations for robust cloud evaluation and using cloud-radiation relationships as consistency check for model errors. It suggests that further model developments focus on improving cloud microphysics and their interactions with radiation.

Environmental sciences↗

Synthetic antibodies against BRIL as universal fiducial marks for single-particle cryoEM structure determination of membrane proteins

We propose the concept of universal fiducials based on a set of pre-made semi-synthetic antibodies (sABs) generated by customized phage display selections against the fusion protein BRIL, an engineered variant of apocytochrome b562a. These sABs can bind to BRIL fused either into the loops or termini of different GPCRs, ion channels, receptors and transporters without disrupting their structure. A crystal structure of BRIL in complex with an affinity-matured sAB (BAG2) that bound to all systems tested delineates the footprint of interaction. Negative stain and cryoEM data of several examples of BRIL-membrane protein chimera highlight the effectiveness of the sABs as universal fiducial marks. Taken together with a cryoEM structure of sAB bound human nicotinic acetylcholine receptor, this work demonstrates that these anti-BRIL sABs can greatly enhance the particle properties leading to improved cryoEM outcomes, especially for challenging membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗

DC Hall coefficient of the strongly correlated Hubbard model

The Hall coefficient is related to the effective carrier density and Fermi surface topology in non-interacting and weakly interacting systems. In strongly correlated systems, the relation between the Hall coefficient and single-particle properties is less clear. Clarifying this relation would give insight into the nature of transport in strongly correlated materials that lack well-formed quasiparticles. In this work, we investigate the DC Hall coefficient of the Hubbard model using determinant quantum Monte Carlo in conjunction with a recently developed expansion of magneto-transport coefficients in terms of thermodynamic susceptibilities. At leading order in the expansion, we observe a change of sign in the Hall coefficient as a function of temperature and interaction strength, which we relate to a change in the topology of the apparent Fermi surface. We also combine our Hall coefficient results with optical conductivity values to evaluate the Hall angle, as well as effective mobility and effective mass based on Drude theory of metals.

36 MATERIALS SCIENCE↗

Photocatalyzed electron exchange between organic chromophores and hematite nanoparticles and the role of solid-state charge transport

Understanding photocatalyzed redox interactions between Fe(III)–(oxyhydr)oxide mineral nanoparticles and adsorbed chromophoric organic matter is critical for accurately predicting bioavailable iron fluxes in the euphotic zone of natural aquatic systems, and for improving the effectiveness of nano-iron-based water purification systems. However, the electron transfer processes that underpin photoreductive dissolution at particle/organic/solution interfaces occur on ultrafast timescales and thus remain difficult to probe. In this work, we report an ultrafast transient absorption spectroscopy (TAS) study of suspensions of hematite nanoplatelets (HNPs) sensitized by adsorbed rhodamine B (RhB) dye as a function of solution media and pH. The TAS results indicate a substantially longer fluorescence lifetime of RhB adsorbed on HNPs across a wide range of pH conditions, consistent with transient photoinduced electron transfer to the oxide with recombination kinetics controlled by electron migration back to the interface via small polaron hopping. Normalization of the observed kinetics to the measured surface loading of RhB at different pH values shows that the recombination rates are insensitive to environmental variables, likely controlled instead by particle properties that determine small polaron diffusion behavior.

54 ENVIRONMENTAL SCIENCES↗

On Alfvénic turbulence of solar wind streams observed by Solar Orbiter during March 2022 perihelion and their source regions

It has been recently accepted that the standard classification of the solar wind solely according to flow speed is outdated, and particular interest has been devoted to the study of the origin and evolution of so-called Alfvénic slow solar wind streams and to what extent such streams resemble or differ from fast wind. In March 2022, Solar Orbiter completed its first nominal phase perihelion passage. During this interval, it observed several Alfvénic streams, allowing for characterization of fluctuations in three slow wind intervals (AS1-AS3) and comparison with a fast wind stream (F) at almost the same heliocentric distance. This work makes use of Solar Orbiter plasma parameters from the Solar Wind Analyzer (SWA) and magnetic field measurements from the magnetometer (MAG). The magnetic connectivity to the solar sources of selected solar wind intervals was reconstructed using a ballistic extrapolation based on measured solar wind speed down to the (spherical) source surface at 2.5 R s below which a potential field extrapolation was used to map back to the Sun. The source regions were identified using SDO/AIA observations. A spectral analysis of in situ measured magnetic field and velocity fluctuations was performed to characterize correlations, Alfvénicity, normalized cross-helicity, and residual energy in the frequency domain as well as intermittency of the fluctuations and spectral energy transfer rate estimated via mixed third-order moments. A machine learning technique was used to separate proton core, proton beam, and alpha particles and to study v − b correlations for the different ion populations in order to evaluate the role played by each population in determining the Alfvénic content of solar wind fluctuations. The comparison between fast wind and Alfvénic slow wind intervals highlights the differences between the two solar wind regimes: The fast wind is characterized by larger amplitude fluctuations, and magnetic and velocity fluctuations are closer to equipartition of energy. In fact the Alfvénic slow wind streams appear to be on a spectrum of wind types, with AS1, originating from open field lines neighboring active regions and displaying similarities with the fast wind in terms of fluctuation amplitude and turbulence characteristics, but not with respect to the alpha particles and proton beams. The other two slow streams differed both in their sources as well as plasma characteristics, with AS2 coming from the expansion of a narrow coronal hole corridor and AS3 from a region straddling a pseudostreamer. The latter displayed the coldest and highest density but the slowest stream with the smallest fluctuation amplitude and greatest magnetic energy excess. It also showed the largest scatter in proton beam speeds and the greatest difference in speed between proton beam and alpha particles. This study shows how the old fast–slow solar wind dichotomy, already called into question by the observations of slower Alfvénic solar wind streams, should further be refined, as the Alfvénic slow wind, originating in different solar wind regions, show significant differences in density, temperature, and proton and alpha-particle properties in the inner heliosphere. The observations presented here provide the starting point for a better understanding of the origin and evolution of different solar wind streams as well as the evolving turbulence contained within.

magnetohydrodynamics (MHD)↗

Real-Time event reconstruction for Nuclear Physics Experiments using Artificial Intelligence

Charged track reconstruction is a critical task in nuclear physics experiments, enabling the identification and analysis of particles produced in high-energy collisions. Machine learning (ML) has emerged as a powerful tool for this purpose, addressing the challenges posed by complex detector geometries, high event multiplicities, and noisy data. Traditional methods rely on pattern recognition algorithms like the Kalman filter, but ML techniques, such as neural networks, graph neural networks (GNNs), and recurrent neural networks (RNNs), offer improved accuracy and scalability. By learning from simulated and real detector data, ML models can identify and classify tracks, predict trajectories, and handle ambiguities caused by overlapping or missing hits. Moreover, ML-based approaches can process data in near-real-time, enhancing the efficiency of experiments at large-scale facilities like the Large Hadron Collider (LHC) and Jefferson Lab (JLAB). As detector technologies and computational resources evolve, ML-driven charged track reconstruction continues to push the boundaries of precision and discovery in nuclear physics. In these proceedings, we highlight advancements in charged track identification leveraging Artificial Intelligence within the CLAS12 detector, achieving a notable enhancement in experimental statistics compared to traditional methods. Additionally, we showcase real-time event reconstruction capabilities, including the inference of charged particle properties, such as momentum, direction, and species identification, at speeds matching data acquisition rates. These innovations enable the extraction of physics observables directly from the experiment in real-time.

Gavalian, Gagik (ORCID:0000000267385457)↗

Magnetic phases of spatially modulated spin-1 chains in Rydberg excitons: Classical and quantum simulations

Here, in this work, we study the magnetic phases of a spatially modulated chain of spin-1 Rydberg excitons. Using the Density Matrix Renormalization Group (DMRG) technique, we study various magnetic and topologically nontrivial phases using both single-particle properties, such as local magnetization and quantum entropy, and many-body ones, such as pair-wise Néel and long-range string correlations. In particular, we investigate the emergence and robustness of the Haldane phase, a topological phase of anti-ferromagnetic spin-1 chains. Furthermore, we devise a hybrid quantum algorithm employing restricted Boltzmann machine to simulate the ground state of such a system that shows very good agreement with the results of exact diagonalization and DMRG.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ground-state phase diagram of the t-t ′ -J model

Significance Theoretical efforts to understand the superconducting cuprates have focused on a few simplified but challenging models: notably the Hubbard and the t - t ′ - J models. Using density matrix renormalization group (DMRG) simulations on width-8 cylinders, we study the ground-state phase diagram of the t - t ′- J model. The next nearest-neighbor hopping t ′ allows one to distinguish between hole ( t ′ < 0 ) and electron doping ( t ′ > 0 ). We find for the magnetic, charge, and single-particle properties that this model roughly captures the differences between the electron- and hole-doped cuprates. However, the superconducting properties differ. For hole doping ( t ′ < 0 ), there is an absence of superconductivity, while for electron doping ( t ′ > 0), we find d -wave superconductivity coexisting with antiferromagnetism and a secondary triplet p -wave pairing component.

Jiang, Shengtao↗

guppy i : a code for reducing the storage requirements of cosmological simulations

ABSTRACT As cosmological simulations have grown in size, the permanent storage requirements of their particle data have also grown. Even modest simulations present a major logistical challenge for the groups which run these boxes and researchers without access to high performance computing facilities often need to restrict their analysis to lower quality data. In this paper, we present guppy, a compression algorithm and code base tailored to reduce the sizes of dark matter-only cosmological simulations by approximately an order of magnitude. guppy is a ‘lossy’ algorithm, meaning that it injects a small amount of controlled and uncorrelated noise into particle properties. We perform extensive tests on the impact that this noise has on the internal structure of dark matter haloes, and identify conservative accuracy limits which ensure that compression has no practical impact on single-snapshot halo properties, profiles, and abundances. We also release functional prototype libraries in C, Python, and Go for reading and creating guppy data.

79 ASTRONOMY AND ASTROPHYSICS↗

The NASA ACTIVATE Mission

The NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) conducted 162 joint flights with two aircraft over the northwest Atlantic to study aerosol–cloud interactions (ACIs), which represent the largest uncertainty in estimating total anthropogenic radiative forcing. The combination of a high-flying King Air and low-flying HU-25 Falcon, equipped with remote sensing and in situ instruments, characterized trace gases, aerosol particles, clouds, and meteorological variables with data collected nearly simultaneously below, within, and above marine boundary layer (MBL) clouds. Flights spanning warm and cold seasons across 3 years (2020–22) provided a broad range of conditions associated with aerosol particles, cloud properties (including particle size and phase), and meteorology, ideally suited for robust ACI calculations and assessing how well models simulate a wide range of MBL clouds from stratiform to cumulus. ACTIVATE data suggest that drivers of cloud droplet number concentration N d , including aerosol particles and MBL dynamics, vary between winter and summer months with a stronger potential to convert aerosol particles into cloud droplets in winter. Models of varying complexity not only highlight some skills in simulating winter and summer cloud types but also identify challenges that still need to be addressed such as treatment of turbulence, wet scavenging, and mesoscale organization. Remote sensing advances range from new retrieval methods for N d , cloud phase classification, vertically resolved aerosol and cloud condensation nuclei number concentration, and ocean surface wind speed. This work describes these scientific and technological advances along with efforts in outreach and open data science.

aerosol indirect effect↗