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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Karhunen-Loeve expansion analysis of uncertainties in cloud microphysical property retrievals

Here, this study proposes a methodology of quantifying uncertainties for cloud retrievals on model resolution to facilitate the comparison with model outputs. Primary component analysis is applied to reduce the dimension of random variables (up to a factor of 50) and reveal the cross correlations in the input data, making large sampling computationally feasible and uncertainty quantification accurate and reliable. Our approach has the capability of parameterizing input uncertainties and attributing the uncertainties in the retrieval output to each individual source, which allows sensitivity analysis of cloud retrieval algorithms and provides directions for improving observation instruments as well as strategies. We applied the method to characterize uncertainties in cloud ice water content (IWC) retrieved from the DOE Atmospheric Radiation Measurement (ARM) programs baseline cloud microphysical retrieval algorithm (MICROBASE). We test it with a selected ice cloud case observed on 9 March 2000 at the ARM Southern Great Plains site during its 2000 cloud intensive observing period. The test results indicate that (1) uncertainties in the output retrieved by MICROBASE are comparable amongst different retrievals; (2) The mean values obtained by our UQ method are closer to the aircraft data with less errors compared to the direct ensemble average; (3) Ice water path (IWP) generally incurred larger uncertainty in optically thin ice clouds and there was more variability in vertical in the retrieved IWC; and (4) Uncertainties in the output are mainly due to the interactions among different modes of ARM radar pro files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Stochastic Parcel Model: A deterministic parameterization of stochastically entraining convection

Convective entrainment is a process that is poorly represented in existing convective parameterizations. By many estimates, convective entrainment is the leading source of error in global climate models. As a potential remedy, an Eulerian implementation of the Stochastic Parcel Model (SPM) is presented here as a convective parameterization that treats entrainment in a physically realistic and computationally efficient way. Drawing on evidence that convecting clouds comprise air parcels subject to Poisson-process entrainment events, the SPM calculates the deterministic limit of an infinite number of such parcels. For computational efficiency, the SPM groups parcels at each height by their purity, which is a measure of their total entrainment up to that height. This reduces the calculation of convective fluxes to a sequence of matrix multiplications. The SPM is implemented in a single-column model and compared with a large-eddy simulation of deep convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Time Evolution and Diurnal Variability of the Parametric Sensitivity of Turbine-Height Winds in the MYNN-EDMF Parameterization

The Mellor-Yamada-Nakanishi-Niino (MYNN) parameterization applied in the Weather Research and Forecasting (WRF) model has been augmented to include the Eddy-Diffusion Mass-Flux (EDMF) approach to better represent transport by boundary-layer eddies. This change includes the addition of new parameters associated with convective updrafts and boundary-layer clouds. These additions lead to new parametric sensitivities in the hub-height wind speed compared to simulations using the standard MYNN parameterization that were explored previously. This work builds on efforts focused on WRF’s MYNN parameterization by examining the sensitivity of hub-height wind speed to parameters in the MYNN-EDMF parameterization as a function of simulation lead time. Summer and winter periods were selected from the second Wind Forecast Improvement Project (WFIP2). Five sets of simulations were completed for each season, with lead times ranging from 2 to 6 days. The results show that the sensitivity to the new parameters associated with the EDMF scheme is generally small compared to other parameters, with the largest impact in convective boundary layers. The spread in the perturbed parameter ensembles was found to grow quickly over the first 8 to 19 hours in the summer simulations and 17 to 24 hours in the winter simulations with little change after that, regardless of the simulation length. A strong diurnal cycle in the parameter sensitivity was also found associated with changes in the atmospheric stability, as well as an increase in the sensitivity to the entrainment parameter used in the EDMF parameterization that is associated with increasing fractional areas covered by plumes.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2015

The parametric sensitivity of CAM5's MJO

Abstract We systematically explore the ability of the Community Atmospheric Model version 5 (CAM5) to simulate the Madden‐Julian Oscillation (MJO), through an analysis of MJO metrics calculated from a 1100‐member perturbed parameter ensemble of 5 year simulations with observed sea surface temperatures. Parameters from the deep convection scheme make the greatest contribution to the variance in MJO simulation quality with a much smaller contribution from parameters in the large‐scale cloud, shallow convection, and boundary layer turbulence schemes. Improved MJO variability results from a larger lateral entrainment rate and a reduction in the precipitation efficiency of deep convection that was achieved by a smaller autoconversion of cloud to rainwater and a larger evaporation of convective precipitation. Unfortunately, simulations with an improved MJO also have a significant negative impact on the climatological values of low‐level cloud and absorbed shortwave radiation, suggesting that structural in addition to parametric modifications to CAM5's parameterization suite are needed in order to simultaneously well simulate the MJO and mean‐state climate.

Boyle, J. S.↗
DOE OSTI2026

Tendencies of Soil Microbial NO Emissions During HI‐SCALE as Predicted by a Nitrification/Denitrification Scheme

Many atmospheric chemical processes, including the formation of secondary organic aerosol (SOA), are strongly modulated by the reactions of NO and NO 2 (NO x ). Though NO x is controlled by anthropogenic emissions near urban areas, in rural areas soil microbes can be a significant contribution to NO emission globally. The relative rates of emissions of different nitrogen-containing species (e.g., NO, N 2 O, HONO, and N 2 ) are strong functions of soil properties such as temperature, moisture content, pH, and soil carbon and nitrogen pools. However, typical large-scale biogeochemical models either express these emissions simplistically, or not at all. Here we investigate the potential impact of soil NO emissions on atmospheric chemistry and SOA formation over regional and monthly time scales, specifically the 2016 spring and summer Intensive Observational Periods (IOPs) of the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign. We implement the soil NO nitrification/denitrification parameterization of Rasool et al. (2019) into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), supplemented by a 1-km soil moisture analysis. We then simulate both IOPs over the U.S. Great Plains, evaluating against ground stations and flight data. We show that soil NO emissions can account for a large fraction of total NO x and locally increase O 3 concentrations by up to 25%, while alleviating negative biases of gases and aerosols toward observations. Soil moisture and temperature changes between IOP1 and IOP2 lead to overall differences in emissions, but with large regional variability due to heterogeneous surface characteristics.

Atmoshpheric Chemistry↗
DOE OSTI2025

Dark magnetohydrodynamics: Black hole accretion in superradiant dark photon clouds

Black holes threaded by massive vector fields can be subject to a superradiant instability, growing a cloud of massive vector particles around it. In this work, we consider what happens if such a dark matter candidate field mimicking a dark photon interacts with an accretion flow onto the black hole. By including a kinetic mixing term with the standard model photon, we extend the commonly used equations of general-relativistic magnetohydrodynamics to a dark photon constituent. The coupling to the dark photon then appears as an effective dynamo term together with a dark Lorentz force acting on the accreting matter. We numerically study the interactions between the superradiant dark photon cloud and the inner accretion flow by solving the coupled system in full numerical relativity. By parameterically varying the mixing parameter between the dark and standard model sector, we provide a first investigation of how the accretion flow could be modified. In conclusion, depending on the coupling strength, our solutions exhibit increased wind launching, as well as oscillation modes in the disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Can general circulation models (GCMs) represent cloud liquid water path adjustments to aerosol–cloud interactions?

Abstract. General circulation models (GCMs), unlike other lines of evidence, indicate that anthropogenic aerosols cause a global-mean increase in cloud liquid water path (ℒ) and thus a negative adjustment to radiative forcing of the climate by aerosol–cloud interactions. In part 1 of this series of papers, we showed that this is true even in models that reproduce the negative correlation observed in present-day internal variability in ℒ and cloud droplet number concentration (Nd). We studied several possible confounding mechanisms that could explain the noncausal cloud–aerosol correlations in GCMs and that possibly contaminate observational estimates of radiative adjustments. Here, we perform single-column and full-atmosphere GCM experiments to investigate the causal model-physics mechanisms underlying the model radiative adjustment estimate. We find that both aerosol–cloud interaction mechanisms thought to be operating in real clouds – precipitation suppression and entrainment evaporation enhancement – are active in GCMs and behave qualitatively in agreement with physical process understanding. However, the modeled entrainment enhancement has a negligible global-mean effect. This raises the question of whether the GCM estimate is incorrect due to parametric or base-state representation errors or whether the process understanding gleaned from a limited set of canonical cloud cases is insufficiently representative of the diversity of clouds in the real climate. Regardless, even at limited resolution, the GCM physics appears able to parameterize the small-scale microphysics–turbulence interplay responsible for the entrainment enhancement mechanism. We suggest ways to resolve tension between current and future (storm-resolving) global modeling systems and other lines of evidence in synthesis climate projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Marine Ice Nuclei Collections – MAGIC (MAGIC-IN) Final Campaign Summary

This campaign augmented measurements obtained via deployment of the Atmospheric Radiation Measurement (ARM) Climate Research Facility’s ARM Mobile Facility (AMF) in the Marine ARM GPCI1 Investigation of Clouds (MAGIC) field campaign. The measurements, comprised of shipboard aerosol collections obtained during the five legs of the summer 2013 cruises, were sent for offline processing to measure ice nucleating particle (INP) number concentrations. The forty-three sample periods each represented, nominally, 24-hour segments during outbound and inbound transits of the Horizon Spirit. The samples were collected at locations between Los Angeles and Hawaii. Eight samples have been analyzed for immersion freezing temperature spectra thus far, using funding from other grants. Remaining samples are being frozen until support for further processing is obtained. Future analyses will investigate the inorganic/organic proportions of ice nuclei, in addition to determining the genetic composition of the overall biological community associated with INPs. Resulting correlations will be compared with other archived aerosol quantities, meteorological and ocean data (e.g., temperature, wind speed, sea surface temperature, etc…) and satellite ocean color products. These findings will ultimately aid in parameterizing oceanic (e.g., sea spray) INP emissions in regional and global scale models, when illustrating aerosol connections to cloud phases and properties. Independent future analyses of frozen filter samples, as proposed by collaborating investigators at the time of this report, will include single particle analyses of marine boundary layer aerosol compositions and morphology. The MAGIC-IN data are considered representative of the oligotrophic, low Chlorophyll-a (with the exception of near-shore) ocean regions, which exist along the MAGIC transect. Current analyses suggest that INP numbers in the marine boundary layer over this region are typically low, compared to existing measurements over marine areas and those collected in the laboratory as the result of realistic sea spray particle generation. These findings, along with separate studies, confirm the existence of highly variable emission sources for INP from oceans, (though weaker than land-based emissions at modestly cooled temperatures).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Cloud microphysical response to entrainment and mixing is locally inhomogeneous and globally homogeneous: Evidence from the lab

Entrainment of dry air into clouds strongly influences cloud optical and precipitation properties and the response of clouds to aerosol perturbations. The response of cloud droplet size distributions to entrainment–mixing is examined in the Pi convection-cloud chamber that creates a turbulent, steady-state cloud. The experiments are conducted by injecting dry air with temperature (T e ) and flow rate (Q e ) through a flange in the top boundary, into the otherwise well-mixed cloud, to mimic the entrainment–mixing process. Due to the large-scale circulation, the downwind region is directly affected by entrained dry air, whereas the upwind region is representative of the background conditions. Droplet concentration (Cn) and liquid water content (L) decrease in the downwind region, but the difference in the mean diameter of droplets (D m ) is small. The shape of cloud droplet size distributions relative to the injection point is unchanged, to within statistical uncertainty, resulting in a signature of inhomogeneous mixing, as expected for droplet evaporation times small compared to mixing time scales. As T e and Q e of entrained air increase, however, Cn, L, and D m of the whole cloud system decrease, resulting in a signature of homogeneous mixing. The apparent contradiction is understood as the cloud microphysical responses to entrainment and mixing differing on local and global scales: locally inhomogeneous and globally homogeneous. This implies that global versus local sampling of clouds can lead to seemingly contradictory results for mixing, which informs the long-standing debate about the microphysical response to entrainment and the parameterization of this process for coarse-resolution models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Semi-Analytic Functions to Calculate the Deposition Coefficients for Ice Crystal Vapor Growth in Bin and Bulk Microphysical Models

Numerical cloud models require estimates of the vapor growth rate for ice crystals. Current bulk and bin microphysical parameterizations generally assume that vapor growth is diffusion limited, though some parameterizations include the influence of surface attachment kinetics through a constant deposition coefficient. A parameterization for variable deposition coefficients is provided herein. The parameterization is an explicit function of the ambient ice supersaturation and temperature, and an implicit function of crystal dimensions and pressure. The parameterization is valid for variable surface types including growth by dislocations and growth by step nucleation. Deposition coefficients are predicted for the two primary growth directions of crystals, allowing for the evolution of the primary habits. Comparisons with benchmark calculations of instantaneous mass growth indicate that the parameterization is accurate to within a relative error of 1%. Parcel model simulations using Lagrangian microphysics as a benchmark indicate that the bulk parameterization captures the evolution of mass mixing ratio and fall speed with typical relative errors of less than 10%, whereas the average axis lengths can have errors of up to 20%. The bin model produces greater accuracy with relative errors often less that 10%. The deposition coefficient parameterization can be used in any bulk and bin scheme, with low error, if an equivalent volume spherical radius is provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.

Stanford, McKenna Wallace [Columbia Univ., New Yor↗
DOE OSTI2022

OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) sea spray organic aerosol emissions – implementation in a global climate model and impacts on clouds

Sea spray aerosol is one of the major sources of atmospheric particulate matter globally. It has increasingly been recognized that organic matter derived from ocean biological precursors contributes significantly to the composition of submicron sea spray and may modify sea spray aerosol impacts on clouds and climate. This paper describes the implementation of the OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) parameterization for sea spray organic aerosol emissions in a global Earth system model, the Energy Exascale Earth System Model (E3SM). OCEANFILMS is a physically based model that links sea spray chemistry with ocean biogeochemistry using a Langmuir partitioning approach. We describe the implementation details of OCEANFILMS within E3SM, compare simulated aerosol fields with observations, and investigate impacts on simulated clouds and climate. Four sensitivity cases are tested, in which organic emissions either strictly add to or strictly replace sea salt emissions (in mass and number) and are either fully internally or fully externally mixed with sea salt. The simulation with internally mixed, added organics agrees reasonably well with observed seasonal cycles of organic matter in marine aerosol and has been selected as the default configuration of the E3SM. In this configuration, sea spray organic aerosol contributes an additional source of cloud condensation nuclei, adding up to 30 cm -3 to Southern Ocean boundary-layer cloud condensation nuclei concentrations (supersaturation = 0.1 %). The addition of this new aerosol source strengthens shortwave radiative cooling by clouds by -0.36 W m -2 in the global annual mean and contributes more than -3.5 W m -2 to summertime zonal mean cloud forcing in the Southern Ocean, with maximum zonal mean impacts of about -4 W m -2 around 50–60°S. This is consistent with a previous top-down, satellite-based empirical estimate of the radiative forcing by sea spray organic aerosol over the Southern Ocean. Through its mechanistic approach, OCEANFILMS offers a path towards improved understanding of the feedbacks between ocean biology, sea spray organic matter, and climate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 1: Deep Convective Updraft Properties

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observed radar reflectivity fields and dual-Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias. Snow reflectivity can exceed 40 dBZ in a two-moment scheme when a constant bulk density of 100 kg m-3 is used. Making snow mass more realistically proportional to area rather than volume should somewhat alleviate this problem. Graupel, unlike snow, produces high biased reflectivity in all simulations. This is associated with large amounts of liquid water above the freezing level in updraft cores. Peak vertical velocities in deep convective updrafts are greater than dual-Doppler retrieved values, especially in the upper troposphere. Freezing of large rainwater contents lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. Strong simulated updraft cores are nearly undiluted, with some showing supercell characteristics. Decreasing horizontal grid spacing from 900 meters to 100 meters weakens strong updrafts, but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may partly be a product of interactions between convective dynamics, parameterized microphysics, and large-scale environmental biases that promote different convective modes and strengths than observed.

clould-resolving↗
DOE OSTI2020

Ice Nucleating Particles, Aerosols and Clouds over the Higher Latitude Southern Ocean

Improved understanding of aerosol-cloud-precipitation interactions is a key goal of the DOE-ASR program. Ice Nucleating Particles (INPs) are rare aerosol particles that trigger ice formation in clouds. By doing so they may initiate precipitation in clouds, and this impacts cloud lifetime. Nowhere may the role of INPs be manifested so dramatically as in the Southern Ocean (SO). This vast region was the focus of the DOE-ARM MARCUS (Measurement of Aerosols, Radiation and CloUds over the Southern Oceans) and MICRE (Macquarie Island Cloud and Radiation Experiment) campaigns. In the SO, a deficit of INPs has been a leading hypothesis for why liquid clouds persist, which underlays the bias of global climate models in predicting excess shortwave radiation reaching the ocean surface between 55°S and Antarctica. In this study, we used the 6-month acquisition of INP data on four MARCUS cruises from Hobart, Tasmania, to Antarctica, and the single-location full annual INP cycle observed in MICRE, to gain a holistic, quantitative picture of the INP number concentrations as a function of temperature and their variability over SO latitudes from 43°S to Antarctica. Augmenting initial processing of filter collections of aerosol particles during MARCUS and MICRE, additional freezing studies following thermal treatment (to removes INPs associated with microbes) and peroxide treatment (to remove all organics), as well as ionic chemistry and total organic carbon analysis, were applied to samples to improve time and space resolution, and differentiate marine from terrestrial contributions. We also performed Next Generation Sequencing to determine that bacterial composition can tag periods of enhanced and degraded marine organic INPs and the relative lack of occurrence of land-sourced bio-particles. Through these and other analyses, INP data were categorized into representative source types (e.g., marine versus terrestrially-influenced). The products of our analyses are being used to parameterize ice formation for use in numerical modeling studies to determine if, and when, ocean-derived INPs control the microphysical composition and radiative balance of SO clouds in a manner not presently captured by global models. The specific objectives and approaches proposed were largely accomplished, including: 1) Additional and value-added chemical and biological analyses of archived samples of aerosols were completed to categorize and quantify INP types and concentrations over the SO. 2) Analyses were completed to place INP data in meteorological and aerosol context. 3) Sea spray aerosol INPs were demonstrated to dominate the SO region in all but episodic events. 4) New parameterizations for INP sources relevant to the SO were constructed. 5) Collaborative modeling studies demonstrating the crucial role of INPs in determining cloud radiative and precipitation properties were conducted with MARCUS and MICRE partners. Collaborative publication submissions in this regard ensued within the two year study. This work will advance the science of interactions of aerosols, clouds and precipitation, to improve their representation in regional and global climate models. Results have informed representation of primary ice crystal nucleation, give inference to the role of secondary processes, and improve investigations of aerosol influences on clouds via ice nucleation over SO high latitudes and similar vast ocean regions. Application will improve representation of such interactions for clouds in both regional and global climate models. The data base and analyses methods applied will continue to serve research studies in the future.

58 GEOSCIENCES↗
DOE OSTI2015

Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2 , SO 2 , PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Nonparametric, data-based kernel interpolation for particle-tracking simulations and kernel density estimation

Traditional interpolation techniques for particle tracking include binning and convolutional formulas that use pre-determined (i.e., closed-form, parameteric) kernels. In many instances, the particles are introduced as point sources in time and space, so the cloud of particles (either in space or time) is a discrete representation of the Green’s function of an underlying PDE. As such, each particle is a sample from the Green’s function; therefore, each particle should be distributed according to the Green’s function. In short, the kernel of a convolutional interpolation of the particle sample “cloud” should be a replica of the cloud itself. This idea gives rise to an iterative method by which the form of the kernel may be discerned in the process of interpolating the Green’s function. When the Green’s function is a density, this method is broadly applicable to interpolating a kernel density estimate based on random data drawn from a single distribution. We formulate and construct the algorithm and demonstrate its ability to perform kernel density estimation of skewed and/or heavy-tailed data including breakthrough curves.

42 ENGINEERING↗