Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “parameterization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

CALIBRATION OF THE MIXING-LENGTH THEORY FOR CONVECTIVE WHITE DWARF ENVELOPES

A calibration of the mixing-length parameter in the local mixing-length theory (MLT) is presented for the lower part of the convection zone in pure-hydrogen-atmosphere white dwarfs. The parameterization is performed from a comparison of three-dimensional (3D) CO5BOLD simulations with a grid of one-dimensional (1D) envelopes with a varying mixing-length parameter. In many instances, the 3D simulations are restricted to the upper part of the convection zone. The hydrodynamical calculations suggest, in those cases, that the entropy of the upflows does not change significantly from the bottom of the convection zone to regions immediately below the photosphere. We rely on this asymptotic entropy value, characteristic of the deep and adiabatically stratified layers, to calibrate 1D envelopes. The calibration encompasses the convective hydrogen-line (DA) white dwarfs in the effective temperature range 6000 ≤ T {sub eff} (K) ≤15, 000 and the surface gravity range 7.0 ≤ log g ≤ 9.0. It is established that the local MLT is unable to reproduce simultaneously the thermodynamical, flux, and dynamical properties of the 3D simulations. We therefore propose three different parameterizations for these quantities. The resulting calibration can be applied to structure and envelope calculations, in particular for pulsation, chemical diffusion, and convective mixing studies. On the other hand, convection has no effect on the white dwarf cooling rates until there is a convective coupling with the degenerate core below T {sub eff} ∼ 5000 K. In this regime, the 1D structures are insensitive to the MLT parameterization and converge to the mean 3D results, hence they remain fully appropriate for age determinations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Multi-objective optimization of interatomic potentials with application to MgO

The parameterization of a functional form for an interatomic potential is treated as a problem in multi-objective optimization. An autonomous, machine-learning approach based on the identification of the Pareto hypersurface of errors in predicted properties allows the development of an ensemble of parameterizations with high materials fidelity and robustness. The efficacy of this approach is illustrated for the simple example of a Buckingham potential for MgO. This approach also provides a strong foundation for uncertainty quantification of potential parameterizations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Neutrino mass and mass ordering: no conclusive evidence for normal ordering

The extraction of the neutrino mass ordering is one of the major challenges in particle physics and cosmology, not only for its implications for a fundamental theory of mass generation in nature, but also for its decisive role in the scale of future neutrinoless double beta decay experimental searches. It has been recently claimed that current oscillation, beta decay and cosmological limits on the different observables describing the neutrino mass parameter space provide robust decisive Bayesian evidence in favor of the normal ordering of the neutrino mass spectrum. We further investigate these strong claims using a rich and wide phenomenology, with different sampling techniques of the neutrino parameter space. Contrary to the findings of Jimenez et al., no decisive evidence for the normal mass ordering is found. Neutrino mass ordering analyses must rely on priors and parameterizations that are ordering-agnostic: robust results should be regarded as those in which the preference for the normal neutrino mass ordering is driven exclusively by the data, while we find a difference of up to a factor of 33 in the Bayes factors among the different priors and parameterizations exploited here. An ordering-agnostic prior would be represented by the case of parameterizations sampling over the two mass splittings and a mass scale, or those sampling over the individual neutrino masses via normal prior distributions only. In this regard, we show that the current significance in favor of the normal mass ordering should be taken as 2.7σ (i.e. moderate evidence), mostly driven by neutrino oscillation data. Let us stress that, while current data favor NO only mildly, we do not exclude the possibility that this may change in the future. Eventually, upcoming oscillation and cosmological data may (or may not) lead to a more significant exclusion of IO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Modified gravity constraints from the full shape modeling of clustering measurements from DESI 2024

We present cosmological constraints on deviations from general relativity (GR) from the first-year of clustering observations from the Dark Energy Spectroscopic Instrument (DESI) in combination with other available datasets including the CMB data from Planck with CMB-lensing from Planck and ACT, BBN constraints on the physical baryon density, the galaxy weak lensing and clustering from DESY3 and supernova data from DESY5. We first consider the μ(a,k)–Σ(a,k) modified gravity (MG) parameterization (as well as η(a,k)) in a ΛCDM and a w 0 w a CDM cosmological backgrounds. Using a functional form for time-only evolution gives μ 0 = 0.11 +0.44 -0.54 from DESI(FS+BAO)+BBN and a wide prior on n s . Using DESI(FS+BAO)+CMB+DESY3+DESY5-SN, we obtain μ 0 = 0.05 ± 0.22 and Σ 0 = 0.008 ± 0.045 and similarly μ 0 = 0.02 +0.19 -0.24 and η 0 = 0.09 +0.36 -0.60 , in an ΛCDM background. In w 0 w a CDM we obtain μ 0 = -0.24 +0.32 -0.28 and Σ 0 = 0.006 ± 0.043, consistent with GR, and we still find a preference of the data for a dynamical dark energy with w 0 > -1 and w a < 0. Using functional dependencies in both time and scale gives μ 0 and Σ 0 with a same level of precision as above but other scale MG parameters remain hard to constrain. We then move to binned parameterizations in a ΛCDM background starting with two bins in redshift and obtain, μ 1 = 1.02 ± 0.13, μ 2 = 1.04 ± 0.11, Σ 1 = 1.021 ± 0.029 and Σ 2 = 1.022 +0.027 -0.023 , all consistent with the unity value of GR in the binning formalism. We then extend the analysis to combine two bins in redshift and two in scale giving 8 MG parameters that we find all consistent with GR. We note that we find here that the tension reported in previous studies about Σ 0 being inconsistent with GR when using Planck PR3 data goes away when we use the recent LoLLiPoP+HiLLiPoP likelihoods. As noted in previous studies, this seems to indicate that the tension is indeed related to the CMB lensing anomaly in PR3 which is also resolved when using the recent likelihoods. We then constrain the class of Horndeski theory in the effective field theory of dark energy approach. We consider both EFT-basis and α-basis in the analysis. Assuming a power law parameterization for the EFT function Ω, which controls non-minimal coupling, we obtain Ω 0 = 0.012 +0.001 -0.012 and s 0 = 0.996 +0.54 -0.20 from the combination of DESI(FS+BAO)+DESY5SN+CMB in a ΛCDM background, which are consistent with GR. Similar results are obtained when using the α-basis and assuming no-braiding (α B = 0) giving c M < 1.14 at 95% CL in a ΛCDM background, also in agreement with GR. However, we see a mild yet consistent indication for c B > 0 when α B is allowed to vary which will require further study to determine whether this is due to systematics or new physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spatio-temporal differences in leaf physiology are associated with fire, not drought, in a clonally integrated shrub

Abstract In highly disturbed environments, clonality facilitates plant survival via resprouting after disturbance, resource sharing among interconnected stems and vegetative reproduction. These traits likely contribute to the encroachment of deep-rooted clonal shrubs in tallgrass prairie. Clonal shrubs have access to deep soil water and are typically thought of as relatively insensitive to environmental variability. However, how leaf physiological traits differ among stems within individual clonal shrubs (hereafter ‘intra-clonal’) in response to extreme environmental variation (i.e. drought or fire) is unclear. Accounting for intra-clonal differences among stems in response to disturbance is needed to more accurately parameterize models that predict the effects of shrub encroachment on ecosystem processes. We assessed intra-clonal leaf-level physiology of the most dominant encroaching shrub in Kansas tallgrass prairie, Cornus drummondii, in response to precipitation and fire. We compared leaf gas exchange rates from the periphery to centre within shrub clones during a wet (2015) and extremely dry (2018) year. We also compared leaf physiology between recently burned shrubs (resprouts) with unburned shrubs in 2018. Resprouts had higher gas exchange rates and leaf nitrogen content than unburned shrubs, suggesting increased rates of carbon gain can contribute to recovery after fire. In areas recently burned, resprouts had higher gas exchange rates in the centre of the shrub than the periphery. In unburned areas, leaf physiology remained constant across the growing season within clonal shrubs (2015 and 2018). Results suggest single measurements within a shrub are likely sufficient to parameterize models to understand the effects of shrub encroachment on ecosystem carbon and water cycles, but model parameterization may require additional complexity in the context of fire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrating crop growth models with remote sensing for predicting biomass yield of sorghum

Abstract Plant phenotypes are often descriptive, rather than predictive of crop performance. As a result, extensive testing is required in plant breeding programmes to develop varieties aimed at performance in the target environments. Crop models can improve this testing regime by providing a predictive framework to (i) augment field phenotyping data and derive hard-to-measure phenotypes and (ii) estimate performance across geographical regions using historical weather data. The goal of this study was to parameterize the Agricultural Production Systems sIMulator (APSIM) crop growth models with remote-sensing and ground-reference data to predict variation in phenology and yield-related traits in 18 commercial grain and biomass sorghum hybrids. Genotype parameters for each hybrid were estimated using remote-sensing measurements combined with manual phenotyping in West Lafayette, IN, in 2018. The models were validated in hybrid performance trials in two additional seasons at that site and against yield trials conducted in Bushland, TX, between 2001 and 2018. These trials demonstrated that (i) maximum plant height, final dry biomass and radiation use efficiency (RUE) of photoperiod-sensitive and -insensitive forage sorghum hybrids tended to be higher than observed in grain sorghum, (ii) photoperiod-sensitive sorghum hybrids exhibited greater biomass production in longer growing environments and (iii) the parameterized and validated models perform well in above-ground biomass simulations across years and locations. Crop growth models that integrate remote-sensing data offer an efficient approach to parameterize larger plant breeding populations.

Yang, Kai-Wei↗
DOE OSTI2021

Spatial biases of information influence global estimates of soil respiration: how can we improve global predictions?

Soil respiration (Rs), the efflux of CO2 from soils to the atmosphere, is a major component of the terrestrial carbon cycle, but is poorly constrained from regional to global scales. The global soil respiration database (SRDB) is a compilation of in-situ Rs observations from around the globe that has been consistently updated with new measurements over the past decade. It is unclear whether the addition of data to new versions of the SRDB has produced better-constrained global Rs estimates. We compared two versions of the SRDB (v3.0 n=5173 and v5.0 n=10366) to determine how additional data influenced the global sum and uncertainty of Rs as predicted by a quantile regression forest model. A model parameterized using SRDBv3 yielded a global Rs sum of 88.6 Pg C yr-1, and associated uncertainty of 29.9 (mean absolute error) and 57.9 (standard deviation) Pg C yr-1, whereas parameterization using SRDBv5 yielded 96.5 Pg C yr-1 and associated uncertainty of 30.2 (mean average error) and 73.4 (standard deviation) Pg C yr-1. Empirically estimated global heterotrophic respiration (Rh) from v3 and v5 were 49.9-50.2 (mean 50.1) and 53.3-53.5 (mean 53.4) Pg C yr-1, respectively. Interestingly, SRDBv5’s inclusion of new data from underrepresented regions (e.g., Asia, Africa, South America) thus resulted in overall higher model uncertainty. The SRDBv5 is still biased towards northern latitudes and temperate zones, so we tested that an optimized global distribution of Rs measurements resulted in a global sum of 96.4 ± 21.4 Pg C yr-1 and lower model uncertainty. These results support current global estimates of Rs but highlight spatial inconsistencies that influence model parameterization and interpretation that should be addressed to improve regional- to global-scale predictions.

Stell, Emma↗
DOE OSTI2018

Environmental limitation mapping of potential biomass resources across the conterminous U nited S tates

Abstract Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long‐term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstock Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM‐ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long‐term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low‐temperature response, summer high‐temperature response, and soil pH , salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.

09 BIOMASS FUELS↗
DOE OSTI2017

Terrestrial biosphere models underestimate photosynthetic capacity and CO 2 assimilation in the Arctic

Terrestrial biosphere models (TBMs) are highly sensitive to model representation of photosynthesis, in particular the parameters maximum carboxylation rate and maximum electron transport rate at 25°C (V c,max.25 and J max.25 , respectively). Many TBMs do not include representation of Arctic plants, and those that do rely on understanding and parameterization from temperate species. We then measured photosynthetic CO 2 response curves and leaf nitrogen (N) content in species representing the dominant vascular plant functional types found on the coastal tundra near Barrow, Alaska. The activation energies associated with the temperature response functions of Vc,max and Jmax were 17% lower than commonly used values. When scaled to 25°C, Vc,max.25 and J max.25 were two- to five-fold higher than the values used to parameterize current TBMs. This high photosynthetic capacity was attributable to a high leaf N content and the high fraction of N invested in Rubisco. Leaf-level modeling demonstrated that current parameterization of TBMs resulted in a two-fold underestimation of the capacity for leaf-level CO 2 assimilation in Arctic vegetation. Our study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-D-19A-04: Parameter Characterization of Electron Beam Monte Carlo Phase Space of TrueBeam Linacs

Purpose: For TrueBeam Monte Carlo simulations, Varian does not distribute linac head geometry and material compositions, instead providing a phase space file (PSF) for the users. The PSF has a finite number of particle histories and can have very large file size, yet still contains inherent statistical noises. The purpose of this study is to characterize the electron beam PSF with parameters. Methods: The PSF is a snapshot of all particles' information at a given plane above jaws including type, energy, position, and directions. This study utilized a preliminary TrueBeam PSF, of which validation against measurement is presented in another study. To characterize the PSF, distributions of energy, position, and direction of all particles are analyzed as piece-wise parameterized functions of radius and polar angle. Subsequently, a pseudo PSF was generated based on this characterization. Validation was assessed by directly comparing the true and pseudo PSFs, and by using both PSFs in the down-stream MC simulations (BEAMnrc/DOSXYZnrc) and comparing dose distributions for 3 applicators at 15 MeV. Statistical uncertainty of 4% was limited by the number of histories in the original PSF. Percent depth dose (PDD) and orthogonal (PRF) profiles at various depths were evaluated. Results: Preliminary results showed that this PSF parameterization was accurate, with no visible differences between original and pseudo PSFs except at the edge (6 cm off axis), which did not impact dose distributions in phantom. PDD differences were within 1 mm for R{sub 7} {sub 0}, R{sub 5} {sub 0}, R{sub 3} {sub 0}, and R{sub 1} {sub 0}, and PRF field size and penumbras were within 2 mm. Conclusion: A PSF can be successfully characterized by distributions for energy, position, and direction as parameterized functions of radius and polar angles; this facilitates generating sufficient particles at any statistical precision. Analyses for all other electron energies are under way and results will be included in the presentation.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Development of a golden beam data set for the commissioning of a proton double-scattering system in a pencil-beam dose calculation algorithm

Purpose: The purpose of this investigation is to determine if a single set of beam data, described by a minimal set of equations and fitting variables, can be used to commission different installations of a proton double-scattering system in a commercial pencil-beam dose calculation algorithm. Methods: The beam model parameters required to commission the pencil-beam dose calculation algorithm (virtual and effective SAD, effective source size, and pristine-peak energy spread) are determined for a commercial double-scattering system. These parameters are measured in a first room and parameterized as function of proton energy and nozzle settings by fitting four analytical equations to the measured data. The combination of these equations and fitting values constitutes the golden beam data (GBD). To determine the variation in dose delivery between installations, the same dosimetric properties are measured in two additional rooms at the same facility, as well as in a single room at another facility. The difference between the room-specific measurements and the GBD is evaluated against tolerances that guarantee the 3D dose distribution in each of the rooms matches the GBD-based dose distribution within clinically reasonable limits. The pencil-beam treatment-planning algorithm is commissioned with the GBD. The three-dimensional dose distribution in water is evaluated in the four treatment rooms and compared to the treatment-planning calculated dose distribution. Results: The virtual and effective SAD measurements fall between 226 and 257 cm. The effective source size varies between 2.4 and 6.2 cm for the large-field options, and 1.0 and 2.0 cm for the small-field options. The pristine-peak energy spread decreases from 1.05% at the lowest range to 0.6% at the highest. The virtual SAD as well as the effective source size can be accurately described by a linear relationship as function of the inverse of the residual energy. An additional linear correction term as function of RM-step thickness is required for accurate parameterization of the effective SAD. The GBD energy spread is given by a linear function of the exponential of the beam energy. Except for a few outliers, the measured parameters match the GBD within the specified tolerances in all of the four rooms investigated. For a SOBP field with a range of 15 g/cm{sup 2} and an air gap of 25 cm, the maximum difference in the 80%–20% lateral penumbra between the GBD-commissioned treatment-planning system and measurements in any of the four rooms is 0.5 mm. Conclusions: The beam model parameters of the double-scattering system can be parameterized with a limited set of equations and parameters. This GBD closely matches the measured dosimetric properties in four different rooms.

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics

Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with these quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Aerosol–Ice Formation Closure: A Southern Great Plains Field Campaign

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. Furthermore, the closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

58 GEOSCIENCES↗
DOE OSTI2015

Evaluation of Subgrid-scale Hydrometeor Transport Schemes using a High-resolution Cloud-resolving Model

Potential ways of parameterizing vertical turbulent fluxes of hydrometeors are examined using a high-resolution cloud-resolving model. The cloud-resolving model uses the Morrison microphysics scheme, which contains prognostic variables for rain, graupel, ice, and snow. A benchmark simulation with a horizontal grid spacing of 250 m of a deep convection case carried out to evaluate three different ways of parameterizing the turbulent vertical fluxes of hydrometeors: an eddy-diffusion approximation, a quadrant-based decomposition, and a scaling method that accounts for within-quadrant (subplume) correlations. Results show that the down-gradient nature of the eddy-diffusion approximation tends to transport mass away from concentrated regions, whereas the benchmark simulation indicates that the vertical transport tends to transport mass from below the level of maximum to aloft. Unlike the eddy-diffusion approach, the quadri-modal decomposition is able to capture the signs of the flux gradient but underestimates the magnitudes. The scaling approach is shown to perform the best by accounting for within-quadrant correlations, and improves the results for all hydrometeors except for snow. A sensitivity study is performed to examine how vertical transport may affect the microphysics of the hydrometeors. The vertical transport of each hydrometeor type is artificially suppressed in each test. Results from the sensitivity tests show that cloud-droplet-related processes are most sensitive to suppressed rain or graupel transport. In particular, suppressing rain or graupel transport has a strong impact on the production of snow and ice aloft. Lastly, a viable subgrid-scale hydrometeor transport scheme in an assumed probability density function parameterization is discussed.

cloud-resolving model↗
DOE OSTI2020

Relationships between Immersion Freezing and Crystal Habit for Arctic Mixed-Phase Clouds—A Numerical Study

Abstract The number concentration of ice particles in Arctic mixed-phase clouds is a major controlling factor of cloud lifetime. The relationships between ice nucleation mode and ice crystal habit development are not yet constrained by observations. This study uses a habit-predicting microphysical scheme within a 3D large-eddy simulation model to evaluate the relationship between immersion freezing and ice habit in a simulated Arctic mixed-phase cloud case. Three immersion freezing parameterizations are considered: a volume-dependent freezing scheme (VF), a parameterization limited to activated droplets (C-AC), and a parameterization limited to coarse aerosol particles (C-CM). Both C-AC and C-CM are based on classical nucleation theory. The freezing rate with VF is found to be greater in downdraft regions than in updraft regions due to the downdraft having a higher number concentration of large droplets. The C-AC cases show active freezing of small droplets near cloud top, whereas in the C-CM cases, mainly the 8–32- μ m-sized droplets freeze in updraft regions near the cloud base. Because the initial crystal size is assumed to affect the axis ratio of hexagonal plates, the VF cases produce crystals with larger axis ratios, resulting in smaller mode radii than the C-AC cases. In all cases, irregular polycrystals dominate near cloud top and a band-like structure develops within the cloud, which qualitatively agrees with previous observations. In the VF and C-CM cases, unactivated large droplets arising from coarse-mode aerosol particles contributed significantly to the freezing rate, producing an important influence on crystal habit.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Convection–Kelvin Wave Coupling in a Global Convection-Permitting Model

A convectively coupled equatorial Kelvin wave (CCKW) was observed over the equatorial Indian Ocean in early November 2011 during the DYNAMO field campaign. This study examines the structure of the CCKW event using two simulations made using the MPAS model: one with 3-km grid spacing without convective parameterization and another with a 15-km grid and parameterized convection. Both simulations qualitatively capture the observed structure of the CCKW, including its vertical tilt and progression of cloud/precipitation structures. The two simulations, however, differ substantially in the amplitude of the CCKW-associated precipitation. While the 3-km run realistically captures the observed modulation of precipitation by the CCKW, the 15-km simulation severely underestimates its magnitude. To understand the difference between the two MPAS simulations regarding wave–convection coupling within the CCKW, the relationship of precipitation with convective inhibition, saturation fraction, and surface turbulent fluxes is investigated. Results show that the 15-km simulation underestimates the magnitude of the CCKW precipitation peak in association with its unrealistically linear relationship between moisture and precipitation. Precipitation, both in observations and the 3-km run, is predominantly controlled by saturation fraction and this relationship is exponential. In contrast, the parameterized convection in the 15-km run is overly sensitive to convective inhibition and not sensitive enough to environmental moisture. The implications of these results on CCKW theories are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud-Resolving ICON Simulations of Secondary Ice Production in Arctic Mixed-Phase Stratocumuli Observed during M-PACE

Field measurements and modeling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations ni. Here, we explore sensitivities with respect to the complexity of different INP parameterizations under the premise that ni is governed by SIP. Idealized, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during the Mixed-Phase Arctic Cloud Experiment (M-PACE) with the Icosahedral Nonhydrostatic (ICON) model. The impact of the droplet shattering (DS) of raindrops and collisional breakup (BR) in addition to the existing Hallet–Mossop rime splintering mechanism were investigated. Overall, 12 different model experiments (12-h runs) were performed and analyzed. Despite the considerable amount of uncertainty remaining with regard to SIP mechanisms and their process representation in numerical models, we conclude from these experiments that (i) only simulations where DS dominates the SIP signal (potentially amplified by BR) capture observed ice-phase and liquid-phase cloud properties, and (ii) SIP events cluster around the convective outflow region and are structurally linked to mesoscale cloud organization. In addition, interactions with primary nucleation parameterizations of varied complexity were investigated. Here, our simulations show that (i) a stable long-lived mixed-phase cloud (MPC) can be maintained in the absence of primary nucleation once SIP is established, (ii) experiments using a computationally more efficient relaxation-based parameterization of primary nucleation are statistically invariant from simulations considering prognostic INP, and (iii) primary nucleation at cloud-top controls the areal extent of the mixed-phase cloud region, and reduces SIP efficacy via DS due to increased depletion of cloud liquid throughout the entire cloud column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Improving Boundary-layer Turbulence and Cloud Processes in CAM with a Higher-order Turbulence Closure Scheme and ASR Measurement

In this study, a simplified intermediately prognostic higher-order turbulence closure (IPHOC) is implemented in the Community Atmosphere Model, version 5 (CAM5), to provide a consistent treatment of subgrid-scale cloud processes, except for deep convection. The planetary boundary layer (PBL) height is prognosticated to better resolve the discontinuity of temperature and moisture above the PBL top. Singlecolumn model tests show that fluxes of liquid water potential temperature and total water, cloud fraction, and liquid water content are improved with this approach. The simplified IPHOC package replaces the boundary layer dry and moist turbulence parameterizations, the shallow convection parameterization, and the liquid-phase part of the cloud macrophysics parameterization in CAM5. CAM5-IPHOC improves the simulation of the low-level clouds off the west coasts of continents and the storm track region in the Southern Hemisphere (SH). The transition from stratocumulus to cumulus clouds is more gradual. There are also improvements on the cloud radiative forcing, especially shortwave, in the subsidence regime. The improvements in the relationships among low cloud amount, surface relative humidity, lower tropospheric stability, and PBL depth are seen in some stratocumulus regions. CAM5-IPHOC, however, produces weaker precipitation at the South Pacific convergence zone than CAM5 because of less energy flux into the SH atmosphere. The more downward surface shortwave radiative cooling and the less top-of-theatmosphere longwave cloud radiative heating in the SH relative to the Northern Hemisphere explains the anomalous cooling and the lesser energy flux into the SH, which is related to the underestimate of extratropical middle/high clouds in the SH.

58 GEOSCIENCES↗