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At least 1,261 records · Page 70

Kronos: A Multiwavelength Observatory for Mapping Accretion-Driven Sources

Kronos is a multiwavelength observatory proposed as a NASA Medium Explorer. Kronos is designed to make use of the natural variability of accreting sources to create microarcsecond-resolution maps of the environments of supermassive black holes in active galaxies and stella-size black holes in binary systems and to characterize accretion processes in Galactic compact binaries. Kronos will obtain broad energy range spectroscopic data with co-aligned X-ray, ultraviolet, and optical spectrometers. The high-Earth orbit of Kronos enables well-sampled, high time-resolution observations, critical for the innovative and sophisticated methods that are used to understand the accretion flows, mass outflows, jets, and other phenomena found in accreting sources. By utilizing reverberation mapping analysis techniques, Kronos produces advanced high-resolution maps of unprecedented resolution of the extreme environment in the inner cores of active galaxies. Similarly, Doppler tomography and eclipse mapping techniques characterize and map Galactic binary systems, revealing the details of the physics of accretion processes in black hole, neutron star, and white dwarf binary systems. The Kronos instrument complement, sensitivity, and orbital environment make it suitable to aggressively address time variable phenomena in a wide range of astronomical objects from nearby flare stars to distant galaxies.

Peterson, Bradley M.↗

Ocean-Atmosphere Coupled Model Simulations of Precipitation in the Central Andes

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. In addition, South American meteorology and climate are also made further complicated by ENSO, a powerful coupled ocean-atmosphere phenomenon. Modelling studies in this region have typically resorted to either atmospheric mesoscale or atmosphere-ocean coupled global climate models. The latter offers full physics and high spatial resolution, but it is computationally inefficient typically lack an interactive ocean, whereas the former offers high computational efficiency and ocean-atmosphere coupling, but it lacks adequate spatial and temporal resolution to adequate resolve the complex orography and explicitly simulate precipitation. Explicit simulation of precipitation is vital in the Central Andes where rainfall rates are light (0.5-5 mm hr-1), there is strong seasonality, and most precipitation is associated with weak mesoscale-organized convection. Recent increases in both computational power and model development have led to the advent of coupled ocean-atmosphere mesoscale models for both weather and climate study applications. These modelling systems, while computationally expensive, include two-way ocean-atmosphere coupling, high resolution, and explicit simulation of precipitation. In this study, we use the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST), a fully-coupled mesoscale atmosphere-ocean modeling system. Previous work has shown COAWST to reasonably simulate the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data when ECMWF interim analysis data were used for boundary conditions on a 27-9-km grid configuration (Outer grid extent: 60.4S to 17.7N and 118.6W to 17.4W).

Regional Climate Model↗

GC31G-1182: Opennex, a Private-Public Partnership in Support of the National Climate Assessment

The NASA Earth Exchange (NEX) is a collaborative computing platform that has been developed with the objective of bringing scientists together with the software tools, massive global datasets, and supercomputing resources necessary to accelerate research in Earth systems science and global change. NEX is funded as an enabling tool for sustaining the national climate assessment. Over the past five years, researchers have used the NEX platform and produced a number of data sets highly relevant to the National Climate Assessment. These include high-resolution climate projections using different downscaling techniques and trends in historical climate from satellite data. To enable a broader community in exploiting the above datasets, the NEX team partnered with public cloud providers to create the OpenNEX platform. OpenNEX provides ready access to NEX data holdings on a number of public cloud platforms along with pertinent analysis tools and workflows in the form of Machine Images and Docker Containers, lectures and tutorials by experts. We will showcase some of the applications of OpenNEX data and tools by the community on Amazon Web Services, Google Cloud and the NEX Sandbox.

datasets↗

Fluid for Thought: SLS Rocket Aerodynamics featuring Pressure Sensitive Paint

Combining computer vision algorithms, state-of-the-art high-speed cameras, pressure sensitive paint (PSP) and transonic wind tunnel facilities, teams at NASA and Boeing study unsteady pressure over the Space Launch System (SLS) rocket model with unprecedented temporal and spatial data resolution. Post-processing visualizes pressure fluctuations over a 3D model by converting intensity data from videos of the wind tunnel test. Additionally, data analysis creates predictions of buffet forcing and aeroacoustic activity over the rocket body with the accuracy of a CFD model! The development of the technique will revolutionize aerodynamics research and reveal uncharted insights into fluid behavior and vehicle performance, enhancing aerospace technology and design as they advance. The talk will focus on the impact of the PSP technique on the SLS design and other potential aerospace applications, as well as lay out the experimental process, from wind tunnel test to insights from the data analysis.

Lucy Zhonghui Tang↗

Mercury Crustal and Lithospheric Properties from High-resolution Gravity Field Models

We have analyzed all the available tracking data from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission to determine high-resolution gravity field models. We have applied a technique based on line-of-sight accelerations that results in models with improved correlations with topography in areas where the spacecraft altitude was low. We have used these models in an analysis of admittance to determine properties of the crust and lithosphere. We focus on four areas where correlations between gravity and topography are high. These locations represent different areas on Mercury: the high-Mg region, the Strindberg crater plus some lobate scarps, heavily cratered terrain, and smooth plains (the northern rise). We find crustal densities around 2600 kg m-3 for the first three areas, and a higher density for the northern rise, indicative of volcanic materials. Elastic thickness is generally low and varies between 11 and 30 km.

Sander Johannes Goossens↗

Mapping National Forest Aboveground Biomass in Mexico by Integrating GEDI, Sentinel‐1 and Sentinel‐2 Data

Accurate mapping of forest aboveground biomass density (AGBD) is required to better understand the role of forests in the global carbon cycle and to support international policies for climate change mitigation and adaptation. Mexico is one of the countries having great potential for the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (or UN-REDD program) and there is a growing demand for unbiased Monitoring Reporting Verification systems at a national level. As an effort under NASA’s Carbon Monitoring System (CMS) program, we developed a machine learning model using multi-stream remote sensing measurements as well as topographic data to create a high spatial resolution AGBD map (~100 m) over Mexico (circa 2020). The remote sensing data includes Global Ecosystem Dynamic Investigation (GEDI) lidar, Sentinel 1 Synthetic-Aperture Radar (SAR), and Sentinel-2 multispectral imagery (MSI). GEDI onboard the International Space Station provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. Our analysis indicates that the developed random forest model can capture 63 % of the spatial variation (RMSE = 33.7 Mg/ha) of AGBD of Mexican forests. We find that shortwave infrared bands of Sentinel-2 MSI and topographical variables from elevation data are the most important variables in the developed AGBD model. Our study highlights methodological opportunities in synergistic uses of multiple sensors for large-scale forest AGBD mapping and shows potential for retrospective analysis and operational monitoring of forest AGBD and its dynamics.

Taejin Park↗

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Chandler, William S.↗

Combustion Synthesis of Fullerenes and Fullerenic Nanostructures In Microgravity

The objectives of the proposed research were to determine the effects of gravity on fullerenes formation in flames and, based on the observed effects, to develop fundamental understanding of fullerenes formation and to identify engineering principles for fullerenes production. The research method consisted of the operation of laminar diffusion flames under normal- and reduced-gravity conditions, and the collection from the flames and subsequent analysis of condensables including any fullerenes present, using coupled high performance liquid chromatography/mass spectrometry and high resolution transmission electron microscopy. The focus included fullerene molecules C60 and C70 and fullerenic nanostructures including tubes, spherules and other shapes. The normal-gravity experiments were performed at MIT and complementary reduced-gravity experiments were to have been contributed by NASA. The independent variables of interest are gravity, fuel type, fuel/oxygen ratio, pressure, gas velocity at burner, diluent type and concentration. Given the large number of variables and the absence of data on either fullerene formation in diffusion flames or gravitational effects on fullerene formation in diffusion or premixed flames, the first part of the work was exploratory while the later part involved detailed study of the most interesting mechanisms. Samples of condensable material from laminar low pressure benzene/argon/oxygen diffusion flames were collected and analyzed by high-performance liquid chromatography to determine the yields of fullerenes, and by high-resolution transmission electron microscopy (HRTEM) to characterize the fullerenic material, i.e., curved-layer nanostructures, on and within the soot particles. The highest concentration of fullerenes was always detected just above the visible stoichiometric surface of a flame. The percentage of fullerenes in the condensable material increases with decreasing pressure. The overall highest amount of fullerenes was found for a surprisingly high dilution fuel with argon. The maximum flame temperature seems to be of minor importance in fullerene formation. The HRTEM analysis of the soot showed an increase of the curvature of the carbon layers, and hence increased fullerenic character. After this maximum, the curvature decreases. In addition to the soot, the samples included fullerenic nanostructures, such as tubes and spheroids including highly-ordered multilayered or onion-like structures. The soot itself shows highly ordered regions that appear to have been cells of ongoing fullerenic nanostructure formation.

Howard, Jack B.↗

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)↗

Exploring the Limits of the Data-Model-Theory Synergy: “Hot” MW Transitions for Rovibrational IR Studies

In order to further improve the accuracy of rovibrational IR line lists generated from the “Best Theory +Reliable High-resolution Experiment” (BTRHE) strategy from 0.01-0.05 cm-1, or 300-1500 MHz, to ~10 MHz, we explore the current limits of the Data-Model-Theory synergy by examining the accuracy and consistency of existing data, then propose that “hot” bands in microwave (MW) spectra is the solution we need for future enhancements. The Ames SO2 J=0-20 rovibrational energy levels computed on the semi-empirically refined Ames-2 potential energy surface (PES) are fit to the Effective Hamiltonian (EH) model regularly used in the experimental infrared (IR) analysis for SO2 isotopologues. In the fitted EH(Ames) model, the rotational constants A/B/C and all 5 quartic centrifugal distortion constants display clear, systematic, and consistent patterns along the vibrational state energy or quanta. Such consistent patterns may facilitate the vibrational assignments for MW hot bands and extract more information from high temperature MW spectra. Some EH(Expt) analyses were carried out with the lowest order Coriolis Coupling term, C1. Their constants should not be directly compared with other EH(Expt) and EH(Ames) results. After excluding them, our  = EH(Ames)- EH(Expt) analyses for 5 isotopologues (626, 636, 646, 628 and 828) indicates some loss of accuracy and consistency starting from vibrational states as low as 22 or 1000 cm-1. Some EH parameters, e.g. K, may have relative deviations as large as 50-100% and totally lose any recognizable patterns. This simply means that current EH(Expt) models do not have the system-wide consistency we need to further refine the EH(Ames) and Ames rovibrational IR line lists. A large part of such defects are probably inherited from the limited precision of experimental line positions, i.e. 1E-3 ~ 1E-4 cm-1, or 3-30 MHz. This is confirmed in a series of truncation tests using the Ames data. Although the EH(Ames) consistency may help identify unreliable rovibrational EH(Expt) parameters, and make reliable predictions for minor isotopologues and unobserved vibrational bands, we believe only the highly accurate “hot” MW transitions can provide real enhancements for EH(Expt) accuracy and consistency. “Hot” MW spectra should play a more significant role in the future synergy of Data, Model, and Theory in the field of rovibrational IR studies.

Xinchuan Huang↗

A 30-yr high-resolution weather research and forecasting model downscaling data over California and Nevada

This dataset presents a 30-year high resolution meteorological dataset obtained using the WRF model (Advanced version Research WRF version 4.4). We used WRF and European Centre for Medium-Range Weather Forecasts Reanalysis v5 as initial and boundary conditions to generate gridded meteorological variables. A large number of surface weather stations was used for model validation. A multi-physics analysis was first developed to identify a good physics suite extended from 6 November 00 UTC to 10 November 23 UTC, 2018, which included the Camp Fire in northern California. Based on the best physics suite, the downscaling dataset extends from 1 December to 28 February, 1990–2021 and the horizontal domain has 1.5 km grid spacing covering the entire states of California and Nevada in the United States. Comparisons between hourly surface observations and WRF simulations of air temperature, relative humidity and wind speeds show mean absolute errors on the order of (1.6-2.0 C), (10 %) and 1.2–1.5 m s -1 , respectively.

54 ENVIRONMENTAL SCIENCES↗

Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case

As we enter the exascale computing regime, powerful supercomputers continue to produce much higher amounts of data than what can be stored for offline data processing. To utilize such high compute capabilities on these machines, much of the data processing needs to happen in situ, when the full high-resolution data is available at the supercomputer memory. In this article, we discuss our MFiX-Exa simulation, which models multiphase flow by tracking a very large number of particles through the simulation domain. In one of the use cases, the carbon particles interact with air to produce carbon dioxide bubbles from the reactor. These bubbles are of primary interest to the domain experts for these simulations. For this particle-based simulation, we propose a streaming technique that can be deployed in situ to efficiently identify the bubbles, track them over time, and use them to down-sample the data with minimal loss in these features.

97 MATHEMATICS AND COMPUTING↗

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗

Chandra HRC Observations of X-Rays from the Jupiter System

In support of the Cassini fly-by of Jupiter, the Chandra X-Ray Observatory's High Resolution Camera (HRC) was used to observe the Jovian system for a complete rotation of Jupiter on December 18, 2000, from 10-20 UT (Universal Time). The HRC is most sensitive to x-rays in the 0.1-10 keV range, with a peak sensitivity in the 1-1.5 keV range, and is a direct descendant of the imagers on the Einstein and ROSAT (Roentgen Satellite) satellites. Chandra differs from other x-ray observatories primarily by virtue of its remarkable 0.5 inch half-power PSF (Point Spread Function), which provides ten times the acuity of its nearest rival. Preliminary analysis of the December 18 data has yielded the following results: 1) a strong, high-latitude northern auroral 'hot spot,' which is relatively fixed near 60-70 degrees north latitude and 160-180 degrees system III longitude, and which pulsates with a period of about 40 minutes and has an average emitted power of about 1 GW; 2) relatively uniform low-latitude emissions, with a total power output of about 2 GW; 3) the first detection of x-ray emissions from the Io Plasma Torus, with a dusk/dawn brightness ratio of about 2.2 and a total emitted power of about 0.7 GW; and 4) the first detection of x-ray emissions from Io itself, with an emitted power of about 0.06 GW. These power estimates are based on an assumed emission wavelength of 653 eV (corresponding to the Lyman alpha line of OVIII ions), and is subject to revision as Chandra spectra of Jupiter are analyzed further. We will present these and other results from this unique data set.

Gladstone, G. R.↗

Correlative Surface Imaging Reveals Chemical Signatures for Bacterial Hotspots on Plant Roots

The rhizosphere is arguably the most complex microbial habitat on earth, comprising an integrated network of plant roots, soil and a highly diverse microbial community (the rhizosphere microbiome)1. Understanding, predicting and controlling plant-microbe interactions in the rhizosphere will allow us to harness the plant microbiome as a means to increase or restore plant ecosystem productivity, improve plant responses to a wide range of environmental perturbations, and mitigate effects of climate change by designing ecosystems for long-term soil carbon storage1. To this end, it is imperative to develop new molecular approaches with high spatial resolution to capture interactions at the plant-microbe, microbe-microbe, and plant-plant interfaces. In this work, we designed an imaging sample holder that allows integrated surface imaging tools to map the same locations of a plant root-microbe interface with submicron lateral resolutions, providing novel in vivo analysis of root-microbe interactions. Specifically, confocal fluorescence microscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS), and scanning electron microscope (SEM) were used for the first time for correlative imaging of the Brachypodium distachyon root and its interaction with Pseudomonas SW25, a typical plant growth-promoting soil bacterium. Imaging data suggest that the root surface is inhomogeneous and that the interaction between Pseudomonas and Brachypodium roots was confined to only few spots along the sampled root segments and that the bacterial attachment spots were enriched in Na- and S-related and high-mass organic species. We conclude that attachment of the Pseudomonas cells to the root surface is outcompeted by strong root-soil mineral interactions but facilitated by formation of extracellular polymeric substances (EPS).

Plant root, Plant growth-promoting bacteria, soil,↗

Decoupling electrode kinetics to elucidate reaction mechanisms in alkaline water electrolysis

Alkaline water electrolysis (AWE) presents key advantages, including reduced material costs, enhanced operational stability, and compatibility with non-precious metal catalysts, positioning it as a scalable route for hydrogen production. In this study, we introduce a minimally invasive single-cell configuration incorporating a reference electrode via diaphragm extension to form an internal ion channel. This setup, combined with an interfaced potentiostat and auxiliary electrometer, enables real-time, independent monitoring of anode and cathode behavior, offering high-resolution electrochemical diagnostics. While it is well established that the hydrogen evolution reaction (HER) exhibits sluggish kinetics in alkaline media, our study reveals that this limitation persists even in practical AWE systems where nickel-based substrates are used as electrodes. This observation is supported by both experimental data and voltage breakdown modeling. Arrhenius-type analysis reveals that localized electric fields induced by catalysts shift the reaction kinetics from classical Butler–Volmer behavior toward a Marcus-like regime, where interfacial molecular dynamics and bimolecular charge transfer dominate. We propose a semi-empirical model and a surficial reaction mechanism to describe these dynamics. This work underscores the critical need for cathode innovation and provides a rational framework for designing advanced catalysts and electrode architectures to optimize AWE performance.

08 HYDROGEN↗

eCounter: Inline Per-IP Network Monitoring at Millisecond Resolution via eBPF

Scientific data acquisition (SciDAQ) systems are shifting from archive-based workflows to streaming paradigms, where real-time, fine-grained network monitoring becomes essential. While P4-enabled devices offer per-packet in-band observability, they require specialized switches and routers. Host-side tools like Prometheus exporters lack sufficient temporal granularity. To bridge this gap, we present eCounter, a lightweight, hardware-agnostic, inline telemetry agent built on extended Berkeley Packet Filter (eBPF). eCounter captures per-interface ingress and egress traffic, categorized by IP address and protocol, at millisecond to sub-millisecond resolution. In a 100 Gbps environment, it continuously exports up to 3,257 time-series bins per second with only 4% CPU utilization at a 35¿KiB/s data rate. We evaluate eCounter across diverse NIC MTU settings, hook types, CPU architectures and operating systems, and observed negligible impact on concurrent high-throughput streaming applications. Complexity analysis confirms that it can be readily scaled to distributed SciDAQ deployments.

Mei, Xinxin [Computational Sciences and Technology↗

Entrainment and aerosol effects on marine boundary-layer clouds: An investigation using ACE-ENA data from HOLODEC, G1, Pico and ACTOS (Final Report on Project Activities)

Marine boundary-layer clouds cover large regions of the globe and are known to strongly influence radiative balances. The microphysical properties and persistence of these clouds are tightly coupled with cloud-top entrainment and aerosol properties within both the boundary layer and the overlying free troposphere. This work addressed the microphysical response to entrainment and aerosol properties in marine stratocumulus clouds, using data from the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) project. Specifically, emphasis was placed on 1. extensive in situ measurements taken with the Atmospheric Radiation Measurement (ARM) G1 aircraft using the Holographic Detector for Clouds (Holodec) instrument; 2. airborne measurements obtained with the helicopter-borne Airborne Cloud Turbulence Observation System (ACTOS) operated by the Leibniz Institute for Tropospheric Research (TROPOS) during the first phase of ACE-ENA; and 3. above-boundary-layer, mountain-top measurements taken at the Pico Mountain Observatory (OMP) by the research group of the co-investigator and scientists from TROPOS during the first phase of ACE-ENA. The work is aligned with the topic “Warm Boundary-Layer Atmospheric Processes.” Key results include the following. Data from the Holographic Detector for Clouds (Holodec) were reprocessed, refined, and validated through a careful instrument intercomparison, resulting in a high-quality dataset available on the ARM archive for ACE-ENA. High-resolution ACTOS measurements of thermodynamics, microphysical, and turbulence properties were analyzed to explore the behavior of the entrainment velocity at cloud top. Analysis of the vertical variability of cloud droplet size distribution shape suggests that mixing is more inhomogeneous near cloud top, and more homogeneous deeper into the cloud. Analysis of aerosol measurements from OMP explored the mixing state and cloud condensation nucleus properties, as well as the implications for radiative forcing. Finally, a machine learning algorithm was developed for identifying characteristic cloud droplet size distributions, and was employed to explore microphysical regimes in stratocumulus clouds observed during ACE-ENA. The characteristic size distributions are narrow, and only when spatially averaged do they produce the broad “gamma” distributions typically assumed in models. This implies that precipitation development should account for variability and correlations in the distribution shape as well as the number concentration of cloud droplets.

54 ENVIRONMENTAL SCIENCES↗