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NASA NTRS1999

Experimental Study of Unsupported Nonane fuel Droplet Combustion in Microgravity

Soot formation in droplet flames is the basic component of the particulate emission process that occurs in spray combustion. The complexity of soot formation motivates a one-dimensional transport condition which has obvious advantages in modeling. Recent models of spherically symmetric droplet combustion have made this assumption when incorporating such aspects as detailed chemistry and radiation. Interestingly, spherical symmetry does not necessarily restrict the results because it has been observed that the properties of carbon formed in flames are not strongly affected by the nature of the fuel or flaming configuration. What is affected, however, are the forces acting on the soot aggregates and where they are trapped by a balance of drag and thermophoretic forces. The distribution of these forces depends on the transport conditions of the flame. Prior studies of spherical droplet flames have examined the droplet burning history of alkanes, alcohols and aromatics. Data are typically the evolution of droplet, flame, extinction, and soot shell diameters. These data are only now just beginning to find their way into comprehensive numerical models of droplet combustion to test proposed oxidation schemes for fuels such as methanol and heptane. In the present study, we report new measurements on the burning history of unsupported nonane droplets in a convection-free environment to promote spherical symmetry. The far-field gas is atmospheric pressure air at room temperature. The evolution of droplet diameter was measured using high speed cine photography of a spark-ignited, droplet within a confined volume in a drop tower. The initial droplet diameters varied between 0.5 mm and 0.6 mm. The challenge of unsupported droplets is to form, deploy and ignite them with minimal disturbance, and then to keep them in the camera field of view. Because of the difficulty of this undertaking, more sophisticated diagnostics for studying soot than photographic were not used. Supporting the test droplet by a fiber fixes the droplet position but the fiber can perturb the burning process especially for a sooting fuel. Prior studies on heptane showed little evidence for soot formation due to g-droplets of similar size the relationship between sooting and droplet diameter. For nonane droplets we expect increased sooting due to the greater number of carbon atoms. As a sooting droplet burns and its diameter decreases, proportionally less soot should form. This reduced soot, as well as the influence of soot formed earlier in the burning process which collects in a 'shell', on heat transport to the flame offers the potential for a time-varying burning rate. Such an effect was investigated and revealed in results reported here. Speculation is offered for the cause of this effect and its possible relation to soot formation.

Callahan, B. J.↗

NASA NTRS1993

The electrospray: Fundamentals and combustion applications

Liquid fuel dispersion in practical systems is typically achieved by spraying the fuel into a polydisperse distribution of droplets evaporating and burning in a turbulent gaseous environment. In view of the nearly unsurmountable difficulties of this two-phase flow, it would be useful to use an experimental arrangement that allow a systematic study of spray evolution and burning in configurations of gradually increasing levels of complexity, starting from laminar sprays to fully turbulent ones. An Electrostatic Spray (ES) of charged droplets lends itself to this type of combustion experiments under well-defined conditions and can be used to synthesize gradually more complex spray environments. In its simplest configuration, a liquid is fed into a small metal tube maintained at several kilovolts relative to a ground electrode few centimeters away. Under the action of the electric field, the liquid meniscus at the outlet of the capillary takes a conical shape, with a thin jet emerging from the cone tip. This jet breaks up farther downstream into a fine spray of charged droplets. Several advantages distinguish the electrospray from alternative atomization techniques: the self-dispersion property of the spray due to coulombic repulsion; the absence of droplet coalescence; the potential control of the trajectories of charged droplets by suitable disposition of electrostatic fields; and the decoupling of atomization, which is strictly electrostatic, from gas flow processes. Furthermore, as recently shown in our laboratory, the electrospray can produce quasi-monodisperse droplets over a very broad size range (1-100 microns). The ultimate objective of this research project is to study the formation and burning of electrosprays of liquid fuels first in laminar regimes and then in turbulent ones. Combustion will eventually be investigated in conditions of three-dimensional droplet-droplet interaction, for which experimental studies have been limited to either qualitative observations in sprays or more quantitative observations on simplified systems consisting of a small number of droplets or droplet arrays. The compactness and potential controllability of this spray generaiton system makes it appealing for studies to be undertaken in the next two years on electrospray combustion in reduced-gravity environments such as those achievable at NASA microgravity test facilities.

Gomez, Alessandro↗

NASA NTRSDate not supplied

International Satellite Cloud Climatology Project (ISCCP) Stage B3 Reduced Radiances in Native (NAT) Format (ISCCP_B3_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=30 Km; Longitude_Resolution=30 Km; Temporal_Resolution=3 Hourly].

CLOUD PARTICLE SIZE↗

NASA NTRS2000

Global to Microscale Evolution of the Pinatubo Volcanic Aerosol Derived from Diverse Measurements and Analyses

We assemble data on the Pinatubo aerosol from space, air, and ground measurements, develop a composite picture, and assess the consistency and uncertainties of measurement and retrieval techniques. Satellite infrared spectroscopy, particle morphology, and evaporation temperature measurements agree with theoretical calculations in showing a dominant composition of H2SO4-H20 mixture, with H2SO4 weight fraction of 65-80% for most stratospheric temperatures and humidities. Important exceptions are (1) volcanic ash, present at all heights initially and just above the tropopause until at least March 1992, and (2) much smaller H2SO4 fractions at the low temperatures of high-latitude winters and the tropical tropopause. Laboratory spectroscopy and calculations yield wavelength- and temperature-dependent refractive indices for the H2SO4-H20 droplets. These permit derivation of particle size information from measured optical depth spectra, for comparison to impactor and optical-counter measurements. All three techniques paint a generally consistent picture of the evolution of R(sub eff), the effective radius. In the first month after the eruption, although particle numbers increased greatly, R(sub eff) outside the tropical core was similar to preeruption values of approx. 0.1 to 0.2 microns, because numbers of both small (r < 0.2 microns) and large (r > 0.6 microns) particles increased. In the next 3-6 months, extracore R(sub eff) increased to approx. 0.5 microns, reflecting particle growth through condensation and coagulation. Most data show that R(sub eff) continued to increase for about 1 year after the eruption. R(sub eff) values up to 0.6 - 0.8 microns or more are consistent with 0.38 - 1 micron optical depth spectra in middle to late 1992 and even later. However, in this period, values from in situ measurements are somewhat less. The difference might reflect in situ undersampling of the very few largest particles, insensitivity of optical depth spectra to the smallest particles, or the inability of flat spectra to place an upper limit on particle size. Optical depth spectra extending to wavelengths lambda > 1 micron are required to better constrain R(sub eff), especially for R(sub eff) > 0.4 microns. Extinction spectra computed from in situ size distributions are consistent with optical depth measurements; both show initial spectra with lambda(sub max) <= 0.42 microns, thereafter increasing to 0.78 <= lambda(sub max) <= 1 micron. Not until 1993 do spectra begin to show a clear return to the preeruption signature of lambda(sub max) <= 0.42 microns. The twin signatures of large R(sub eff) (> 0.3 microns) and relatively flat extinction spectra (0.4 - 1 microns) are among the longest-lived indicators of Pinatubo volcanic influence. They persist for years after the peaks in number, mass, surface area, and optical depth at all wavelengths <= 1 microns. This coupled evolution in particle size distribution and optical depth spectra helps explain the relationship between global maps of 0.5- and 1.0-micron optical depth derived from the Advanced Very High Resolution Radiometer (AVHRR) and Stratospheric Aerosol and Gas Experiment (SAGE) satellite sensors. However, there are important differences between the AVHRR and SAGE midvisible optical thickness products. We discuss possible reasons for these differences and how they might be resolved.

Russell, P. B.↗

DOE OSTI2022

Small field campaign: aerosol – ice formation closure pilot study. Final Report

Prediction of atmospheric ice formation from aerosol particles by heterogeneous nucleation represents one of the grand challenges in atmospheric science. Our insufficient predictive understanding of primary ice formation is the reason that climate models typically do not include heterogeneous ice nucleation with subsequent effects on climate uncertainty. Mixed-phase clouds, where supercooled water droplets and ice crystals coexist play globally an important role regulating climate. This is especially the case for the Arctic region that experiences the greatest warming due to climate change compared to other regions in the world. Immersion freezing initiated by ice-nucleating particles (INPs) in supercooled water droplets is recognized as the dominant primary ice formation pathway in mixed-phase cloud regimes. For this reason, it is crucial to evaluate our capability to predict immersion freezing for a given ambient aerosol population. The goal of this project is conducting a field-based pilot study at the U.S. DOE Atmospheric Radiation Measurement (ARM) user facility at Southern Great Plains (SGP) to evaluate our capability to predict the number concentration of aerosol particles that serve as INPs in the immersion freezing mode. Successful prediction of INP number concentrations is also termed “closure”. This field-observational approach represents a first-of-its kind attempt of an aerosol–ice formation closure study (AEROICESTUDY). Very few closure studies related to INPs have been conducted, and to our knowledge, none using robust size-resolved ambient aerosol composition measurements as a starting point. Achievement of aerosol–ice formation closure relies on our ability to characterize the ambient aerosol population with respect to particles size and composition and to determine INP number concentrations for specified freezing temperatures. This requires numerous online and offline instrumentation resulting in this pilot field campaign being a multi-institutional and community-collaborative effort. We chose the ARM SGP megasite for this first aerosol-ice formation closure pilot study due to its significant measurement capabilities available to obtain detailed physical characterization of the local aerosol population including size distribution, mass loading, and chemical composition of non-refractory aerosol particles. The overall objective of this project is to identify ice nucleation parameterizations that produce the most robust predictions of INP numbers and thus are best suited to be included in cloud and climate models. This objective includes the following goals for this field and laboratory-based project: i) What are the crucial aerosol physicochemical property measurements needed to accurately guide ice nucleation representations in models and long-term INP measurements? ii) What level of parameter details needs to be known to achieve aerosol–ice formation closure? iii) What are the leading causes for climate model bias in INP predictions? We found that the advances in our understanding of immersion freezing garnered over the last 20 years allowed us to yield partial and full closures of atmospheric immersion freezing from ambient aerosol particles. When the aerosol population is physicochemically complex and parameterizations for representative INP types are not yet available, we still struggle to accurately predict INP number concentrations. This project clearly demonstrates that with more laboratory and field measurements that are accompanied by particle composition analysis, the necessary datasets to achieve aerosol–ice formation closure for various locations will emerge, thus providing a robust foundation for guiding the representation of INPs in cloud and climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Constraining the Twomey effect from satellite observations: issues and perspectives

Abstract. The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd, ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd, ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, ΔNd, ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of metres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining ΔNd, ant, namely the quantification of (i) the cloud-active aerosol – the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-to-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Constraining the Twomey effect from satellite observations: Issues and perspectives

The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (ΔNd,ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol–cloud interactions which also comprises rapid adjustments. These adjustments are essentially the responses of cloud fraction and liquid water path to ΔNd,ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large scale (hundreds of kilometres) ΔNd,ant remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and vertical wind and by droplet sink processes. These operate at scales on the order of 10s of metres at which only localized observations are available and at which no approach exists yet to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are three key uncertainties in determining ΔNd,ant, namely the quantification (i) of the cloud-active aerosol – the cloud condensation nuclei concentrations (CCN) at or above cloud base –, (ii) of Nd, as well as (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data. A fourth uncertainty, the anthropogenic perturbation to CCN concentrations, is also not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: In terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, the non-direct relation to the concentration of aerosols, the impossibility to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilizing colocated polarimeter and lidar instruments, ideally including high spectral resolution lidar capability at two wavelengths to maximize vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity, and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd – to – CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect.

Twomey effect↗

NASA NTRSDate not supplied

International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Native (NAT) Format (ISCCP_DX_NAT)

CLOUD ICE↗

DOE OSTI2024

EPCAPE-PT-LANL Measurements: Scanning Mobility Particle Sizer

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Scanning Mobility Particle Sizer (TSI), DMA Classifier Model 3082 + CPC Detector Model 3752. Data Notes: The SMPS dataset is limited due to necessary instrument maintenance and subsequent extensive downtime. Data is only available from October 21 to November 8, 2023. Post November 22, 2023, the NanoScan instrument provided coverage for the latter half of the campaign. To ensure consistency, the data was resampled into uniform size bins ranging from 15 nm to 667 nm. This adjustment was required due to changes in size bins and the maximum diameter that occurred after maintenance and repairs. Multiple Charge Correction applied, Nanoparticle Agglomerate Mobility Analysis not applied, and Diffusion Correction applied. Header: - List [15 nm to 667 nm] middle of the size bin in nanometers: Data reports the concentration particles in this size bin per cubic centimeter, dN/dLog(dp). - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Influenza A viral burst size from thousands of infected single cells using droplet quantitative PCR (dqPCR)

An important aspect of how viruses spread and infect is the viral burst size, or the number of new viruses produced by each infected cell. Surprisingly, this value remains poorly characterized for influenza A virus (IAV), commonly known as the flu. In this study, we screened tens of thousands of cells using a microfluidic method called droplet quantitative PCR (dqPCR). The high-throughput capability of dqPCR enabled the measurement of a large population of infected cells producing progeny virus. By measuring the fully assembled and successfully released viruses from these infected cells, we discover that the viral burst sizes for both the seasonal H3N2 and the 2009 pandemic H1N1 strains vary significantly, with H3N2 ranging from 10 1 to 10 4 viruses per cell, and H1N1 ranging from 10 1 to 10 3 viruses per cell. Some infected cells produce average numbers of new viruses, while others generate extensive number of viruses. In fact, we find that only 10% of the single-cell infections are responsible for creating a significant portion of all the viruses. This small fraction produced approximately 60% of new viruses for H3N2 and 40% for H1N1. On average, each infected cell of the H3N2 flu strain produced 709 new viruses, whereas for H1N1, each infected cell produced 358 viruses. This novel method reveals insights into the flu virus and can lead to improved strategies for managing and preventing the spread of viruses.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns

Abstract. A large part of the uncertainty in climate projections comes from uncertain aerosol properties and aerosol–cloud interactions as well as the difficulty in remotely sensing them. The southeastern Atlantic functions as a natural laboratory to study biomass-burning smoke and to constrain this uncertainty. We address these gaps by comparing the Weather Research and Forecasting with Chemistry Community Atmosphere Model (WRF-CAM5) to the multi-campaign observations ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing), and LASIC (Layered Atlantic Smoke Interactions with Clouds) in the southeastern Atlantic in August 2017 to evaluate a large range of the model's aerosol chemical properties, size distributions, processes, and transport, as well as aerosol–cloud interactions. Overall, while WRF-CAM5 is able to represent smoke properties and transport, some key discrepancies highlight the need for further analysis. Observations of smoke composition show an overall decrease in aerosol mean diameter as smoke ages over 4–12 d, while the model lacks this trend. A decrease in the mass ratio of organic aerosol (OA) to black carbon (BC), OA:BC, and the OA mass to carbon monoxide (CO) mixing ratio, OA:CO, suggests that the model is missing processes that selectively remove OA from the particle phase, such as photolysis and heterogeneous aerosol chemistry. A large (factor of ∼2.5) enhancement in sulfate from the free troposphere (FT) to the boundary layer (BL) in observations is not present in the model, pointing to the importance of properly representing secondary sulfate aerosol formation from marine dimethyl sulfide and gaseous SO2 smoke emissions. The model shows a persistent overprediction of aerosols in the marine boundary layer (MBL), especially for clean conditions, which multiple pieces of evidence link to weaker aerosol removal in the modeled MBL than reality. This evidence includes several model features, such as not representing observed shifts towards smaller aerosol diameters, inaccurate concentration ratios of carbon monoxide and black carbon, underprediction of heavy rain events, and little evidence of persistent biases in modeled entrainment. The average below-cloud aerosol activation fraction (NCLD/NAER) remains relatively constant in WRF-CAM5 between field campaigns (∼0.65), while it decreases substantially in observations from ORACLES (∼0.78) to CLARIFY (∼0.5), which could be due to the model misrepresentation of clean aerosol conditions. WRF-CAM5 also overshoots an observed upper limit on liquid cloud droplet concentration around NCLD= 400–500 cm−3 and overpredicts the spread in NCLD. This could be related to the model often drastically overestimating the strength of boundary layer vertical turbulence by up to a factor of 10. We expect these results to motivate similar evaluations of other modeling systems and promote model development to reduce critical uncertainties in climate simulations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm

In this study we developed a neural network (NN) that can be used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. This effort builds upon our previous work, which explored the sensitivity of neural network input, architecture, and other design requirements for this type of remote sensing problem. In particular this work introduces a framework for appropriately weighting total and polarized reflectances, which have vastly different magnitudes and measurement uncertainties. The NN is trained using an artificial training set and applied to research scanning polarimeter (RSP) data obtained during the ORACLES field campaign (ObseRvations of Aerosols above CLouds and their intEractionS). The polarimetric RSP observations are unique in that they observe the same cloud from a very large number of angles within a variety of spectral bands, resulting in a large dataset that can be explored rapidly with a NN approach. The usefulness of applying a NN to a dataset such as this one stems from the possibility of rapidly obtaining a retrieval that could be subsequently applied as a first guess for slower but more rigorous physical-based retrieval algorithms. This approach could be particularly advantageous for more complicated atmospheric retrievals – such as when an aerosol layer lies above clouds like in ORACLES. For RSP observations obtained during ORACLES 2016, comparisons between the NN and standard parametric polarimetric (PP) cloud retrieval give reasonable results for droplet effective radius (r(e): R=0.756, RMSE=1.74 µm) and cloud optical thickness (τ: R=0.950, RMSE=1.82). This level of statistical agreement is shown to be similar to comparisons between the two most well-established cloud retrievals, namely, the polarimetric and the bispectral total reflectance cloud retrievals. The NN retrievals from the ORACLES 2017 dataset result in retrievals of r(e) (R=0.54, RMSE=4.77 µm) and τ (R=0.785, RMSE=5.61) that behave much more poorly. In particular we found that our NN retrieval approach does not perform well for thin (τ<3), inhomogeneous, or broken clouds. We also found that correction for above-cloud atmospheric absorption improved the NN retrievals moderately – but retrievals without this correction still behaved similarly to existing cloud retrievals with a slight systematic offset.

SPECTRAL-RESOLUTION LIDAR↗

NASA NTRS2004

Bubble Combustion

A method of energy production that is capable of low pollutant emissions is fundamental to one of the four pillars of NASA s Aeronautics Blueprint: Revolutionary Vehicles. Bubble combustion, a new engine technology currently being developed at Glenn Research Center promises to provide low emissions combustion in support of NASA s vision under the Emissions Element because it generates power, while minimizing the production of carbon dioxide (CO2) and nitrous oxides (NOx), both known to be Greenhouse gases. and allows the use of alternative fuels such as corn oil, low-grade fuels, and even used motor oil. Bubble combustion is analogous to the inverse of spray combustion: the difference between bubble and spray combustion is that spray combustion is spraying a liquid in to a gas to form droplets, whereas bubble combustion involves injecting a gas into a liquid to form gaseous bubbles. In bubble combustion, the process for the ignition of the bubbles takes place on a time scale of less than a nanosecond and begins with acoustic waves perturbing each bubble. This perturbation causes the local pressure to drop below the vapor pressure of the liquid thus producing cavitation in which the bubble diameter grows, and upon reversal of the oscillating pressure field, the bubble then collapses rapidly with the aid of the high surface tension forces acting on the wall of the bubble. The rapid and violent collapse causes the temperatures inside the bubbles to soar as a result of adiabatic heating. As the temperatures rise, the gaseous contents of the bubble ignite with the bubble itself serving as its own combustion chamber. After ignition, this is the time in the bubble s life cycle where power is generated, and CO2, and NOx among other species, are produced. However, the pollutants CO2 and NOx are absorbed into the surrounding liquid. The importance of bubble combustion is that it generates power using a simple and compact device. We conducted a parametric study using CAVCHEM, a computational model developed at Glenn, that simulates the cavitational collapse of a single bubble in a liquid (water) and the subsequent combustion of the gaseous contents inside the bubble. The model solves the time-dependent, compressible Navier-Stokes equations in one-dimension with finite-rate chemical kinetics using the CHEMKIN package. Specifically, parameters such as frequency, pressure, bubble radius, and the equivalence ratio were varied while examining their effect on the maximum temperature, radius, and chemical species. These studies indicate that the radius of the bubble is perhaps the most critical parameter governing bubble combustion dynamics and its efficiency. Based on the results of the parametric studies, we plan on conducting experiments to study the effect of ultrasonic perturbations on the bubble generation process with respect to the bubble radius and size distribution.

Corrigan, Jackie↗

DOE OSTI2021

C-FOG: Life of Coastal Fog

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp . An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

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