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NASA NTRS2013

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

cumulus schemes↗

NASA NTRS1953

A Method for Determining Cloud-Droplet Impingement on Swept Wings

The general effect of wing sweep on cloud-droplet trajectories about swept wings of high aspect ratio moving at subsonic speeds is discussed. A method of computing droplet trajectories about yawed cylinders and swept wings is presented, and illustrative droplet trajectories are computed. A method of extending two-dimensional calculations of droplet impingement on nonswept wings to swept wings is presented. It is shown that the extent of impingement of cloud droplets on an airfoil surface, the total rate of collection of water, and the local rate of impingement per unit area of airfoil surface can be found for a swept wing from two-dimensional data for a nonswept wing. The impingement on a swept wing is obtained from impingement data for a nonswept airfoil section which is the same as the section in the normal plane of the swept wing by calculating all dimensionless parameters with respect to flow conditions in the normal plane of the swept wing.

Dorsch, Robert G.↗

NASA NTRS1990

A comparison of ISCCP and FIRE satellite cloud parameters

One of the goals of the First ISCCP Regional Experiment (FIRE) is the quantification of the uncertainties in the cloud parameter products derived by the International Satellite Cloud Climatology Project (ISCCP). This validation effort has many facets including sensitivity analyses and comparisons to similar data or theoretical results with known accuracies. The FIRE provides cloud-truth data at particular points or along particular lines from surface and aircraft measurement systems. Relating these data to the larger, area-averaged ISCCP results requires intermediate steps using higher resolution satellite data analyses. Errors in the cloud products derived with a particular method can be determined by performing analyses of high resolution satellite data over the area surrounding the point or line measurement. This same analysis technique may then be used to derive cloud parameters over a larger area containing similar cloud fields. It is assumed that the uncertainties found for the small scale analyses are the same for the large scale so that the method has been calibrated for the particular cloud type; i.e., its accuracy is known. Differences between the large scale results using the ISCCP technique and the calibrated method can be computed and used to determine if any significant biases or rms errors occur in the ISCCP results. Selected ISCCP results are compared to cloud parameters derived using the hybrid bispectral threshold method over the FIRE IFO and extended observation areas.

Gibson, Gary G.↗

NASA NTRS2000

Tropospheric Ozone Profile Information Derived From "Cloud Slicing"

This study introduces a new approach to obtain ozone vertical profile information given coincident satellite measurements of both cloud-top pressure and above-cloud column ozone. This method is denoted "cloud slicing". In this study information of cloud-top pressure is derived from Geostationary Orbital Earth Satellite (GOES) infrared data, while above-cloud column ozone is obtained from the Earth Probe total ozone mapping spectrometer (TOMS) instrument. Several case examples are presented showing the feasibility of this technique as well as providing new geophysical results. Because the TOMS instrument measures backscattered UV radiation, it does detect ozone lying below dense water vapor clouds. This opaque property of TOMS can be used directly in conjunction with co-located cloud-top pressure data to derive ozone profile information in the troposphere. The cloud slicing method is an extension of the "Convective Cloud Differential" (CCD) method. In the CCD method, tropospheric column ozone (i.e., the total vertical column of ozone lying in the troposphere) is computed by taking total column ozone with low reflectivity (R less than 0.2) and subtracting from this a nearby measurement of above-cloud column ozone amount under conditions of high reflectivity (R greater than 0.9). (High reflectivity away from snow/ice conditions coincides with strong convection and tropopause-level clouds). The key element in determining tropospheric ozone profile information from the cloud slicing method is to have simultaneous and co-located measurements of both above-cloud column ozone and cloud-top pressure.

Ziemke, Jerald R.↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

CFD↗

DOE OSTI2020

The Numerical Computation of Clear-Sky Transmittance and Reflectance of Solar Radiation for the Modeling of PV System Performance

Modeling of photovoltaics (PV) system performance requires numerical computation of plane-of-array (POA) irradiances that are influenced by atmospheric absorption and scattering. Clear-sky transmittance and reflectance of diffuse irradiance are essential for the understanding of solar radiation related to multiple reflection between land surface and clouds. This study analytically solves the radiative transfer equation for clear-sky conditions and numerically computes the transmittance and reflectance of diffuse irradiance as functions of the optical thickness of the atmosphere. The computation will be implemented in all-sky radiative transfer models to improve their computational efficiency.

14 SOLAR ENERGY↗

NASA NTRS2000

The Atmospheric Channels of GLAS: Near Real-Time Global Lidar Remote Sensing of Clouds and Aerosols from Space

The Geoscience Laser Altimeter System (GLAS) will be placed into orbit in 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESat). From its nearly polar orbit (94 degree inclination), GLAS will provide continuous global measurements of the vertical distribution of clouds and aerosols while simultaneously providing high accuracy topographic profiling of surface features. During the mission, which is slated to last 3 to 5 years, the data collected by GLAS will be in near-real time to produce level 1 and 2 data products at the NASA GLAS Science Computing Facility (SCF) at Goddard Space Flight Center in Greenbelt, Maryland. The atmospheric products include cloud and aerosol layer heights, planetary boundary layer depth, polar stratospheric clouds and thin cloud and aerosol optical depth. These products will be made available to the science community within days of their creation. The processing algorithms must be robust, adaptive, efficient, and clever enough to run autonomously for the widely varying atmospheric conditions that will be encountered. This paper presents an overview of the GLAS atmospheric data products and briefly discusses the design of the processing algorithms.

Palm, Stephen P.↗

NASA NTRS1982

The carbon abundance in the Magellanic Clouds from IUE observations of H II regions

Results are given of observations of the UV spectra of several H II regions in the Magellanic Clouds, with emphasis on obtaining the carbon abundance from the UV lines of C II, C III, and C IV. The observations and results are described, and theoretical model calculations are presented of the H II regions and the relative abundances of H, He, C, N, O, S, Cl, and Ar computed from the UV and visual spectra. In addition, the abundance results for the Magellanic Clouds are compared with the sun, the Orion Nebula, and galactic planetary nebulae. In comparison with solar abundances, carbon is found to be depleted relative to hydrogen in the Magellanic Clouds by an amount larger than that of nitrogen and oxygen in the SMC and by an amount between that of nitrogen and oxygen in the LMC. It is noted that the results are consistent with a scenario that nitrogen and oxygen have greater primary yields in massive stars than carbon, which may be produced predominantly in less massive stars (such that C/N and C/O in galaxies are initially very low and subsequently increase with evolution). Subsequently, the C/N ratio may decrease as secondary production of nitrogen in less massive stars becomes significant.

Dufour, R. J.↗

DOE OSTI2015

Damping Ring R&D at CESR-TA

Accelerators that collide high energy beams of matter and anti-matter are essential tools for the investigation of the fundamental constituents of matter, and the search for new forms of matter and energy. A “Linear Collider” is a machine that would bring high energy and very compact bunches of electrons and positrons (anti-electrons) into head-on collision. Such a machine would produce (among many other things) the newly discovered Higgs particle, enabling a detailed study of its properties. Among the most critical and challenging components of a linear collider are the damping rings that produce the very compact and intense beams of electrons and positrons that are to be accelerated into collision. Hot dilute particle beams are injected into the damping rings, where they are compressed and cooled. The size of the positron beam must be reduced more than a thousand fold in the damping ring, and this compression must be accomplished in a fraction of a second. The cold compact beams are then extracted from the damping ring and accelerated into collision at high energy. The proposed International Linear Collider (ILC), would require damping rings that routinely produce such cold, compact and intense beams. The goal of the Cornell study was a credible design for the damping rings for the ILC. Among the technical challenges of the damping rings; the development of instrumentation that can measure the properties of the very small beams in a very narrow window of time, and mitigation of the forces that can destabilize the beams and prevent adequate cooling, or worse lead to beam loss. One of the most pernicious destabilizing forces is due to the formation of clouds of electrons in the beam pipe. The electron cloud effect is a phenomenon in particle accelerators in which a high density of low energy electrons, build up inside the vacuum chamber. At the outset of the study, it was anticipated that electron cloud effects would limit the intensity of the positron ring, and that an instability associated with residual gas in the beam pipe would limit the intensity of the electron ring. It was also not clear whether the required very small beam size could be achieved. The results of this study are important contributions to the design of both the electron and positron damping rings in which all of those challenges are addressed and overcome. Our findings are documented in the ILC Technical Design Report, a document that represents the work of an international collaboration of scientists. Our contributions include design of the beam magnetic optics for the 3 km circumference damping rings, the vacuum system and surface treatments for electron cloud mitigation, the design of the guide field magnets, design of the superconducting damping wigglers, and new detectors for precision measurement of beam properties. Our study informed the specification of the basic design parameters for the damping rings, including alignment tolerances, magnetic field errors, and instrumentation. We developed electron cloud modelling tools and simulations to aid in the interpretation of the measurements that we carried out in the Cornell Electron-positron Storage Ring (CESR). The simulations provide a means for systematic extrapolation of our measurements at CESR to the proposed ILC damping rings, and ultimately to specify how the beam pipes should be fabricated in order to minimize the effects of the electron cloud. With the conclusion of this study, the design of the essential components of the damping rings is complete, including the development and characterization (with computer simulations) of the beam optics, specification of techniques for minimizing beam size, design of damping ring instrumentation, R&D into electron cloud suppression methods, tests of long term durability of electron cloud coatings, and design of damping ring vacuum system components.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the multiscale modeling framework (MMF), which embeds a kilometer-resolution cloud-resolving model (CRM) within each atmospheric column of a host climate model to replace traditional convection and cloud parameterizations. Machine learning offers a unique opportunity to make MMF more accessible by emulating the embedded CRM and reducing its substantial computational cost. Although many studies have demonstrated proof-of-concept success of achieving stable hybrid simulations, it remains a challenge to achieve near operational-level success with real geography and comprehensive variable emulation that includes, for example, explicit cloud condensate coupling. In this study, we present a stable hybrid model capable of integrating for at least 5 years with near operational-level complexity, including coarse-grid geography, seasonality, explicit cloud condensate and wind predictions, and land coupling. Our model demonstrates skillful online performance, achieving a 5-year zonal mean tropospheric temperature bias within 2 K, water vapor bias within 1 g/kg, and a precipitation root mean square error of 0.96 mm/day. Key factors contributing to our online performance include an expressive U-Net architecture and physical thermodynamic constraints for microphysics. With microphysical constraints mitigating unrealistic cloud formation, our work is the first to demonstrate realistic multi-year cloud condensate climatology under the MMF framework. Despite these advances, online diagnostics reveal persistent biases in certain regions, highlighting the need for innovative strategies to further optimize online performance.

Hu, Zeyuan [NVIDIA Corporation, Santa Clara, CA (U↗

DOE OSTI2013

DID THE INFANT R136 AND NGC 3603 CLUSTERS UNDERGO RESIDUAL GAS EXPULSION?

Based on kinematic data observed for very young, massive clusters that appear to be in dynamical equilibrium, it has recently been argued that such young systems are examples of where the early residual gas expulsion did not happen or had no dynamical effect. The intriguing scenario of a star cluster forming through a single starburst has thereby been challenged. Choosing the case of the R136 cluster of the Large Magellanic Cloud, the most cited one in this context, we perform direct N-body computations that mimic the early evolution of this cluster including the gas-removal phase (on a thermal timescale). Our calculations show that under plausible initial conditions which are consistent with observational data, a large fraction (>60%) of a gas-expelled, expanding R136-like cluster is bound to regain dynamical equilibrium by its current age. Therefore, the recent measurements of velocity dispersion in the inner regions of R136, which indicate that the cluster is in dynamical equilibrium, are consistent with an earlier substantial gas expulsion of R136 followed by a rapid re-virialization (in Almost-Equal-To 1 Myr). Additionally, we find that the less massive Galactic NGC 3603 Young Cluster (NYC), with a substantially longer re-virialization time, is likely to be found to have deviated from dynamical equilibrium at its present age ( Almost-Equal-To 1 Myr). The recently obtained stellar proper motions in the central part of the NYC indeed suggest this and are consistent with the computed models. This work significantly extends previous models of the Orion Nebula Cluster which already demonstrated that the re-virialization time of young post-gas-expulsion clusters decreases with increasing pre-expulsion density.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

An Edge-Cloud Integrated Solution for Buildings Demand Response Using Reinforcement Learning

Buildings, as major energy consumers, can provide great untapped demand response (DR) resources for grid services. However, their participation remains low in real-life. One major impediment for popularizing DR in buildings is the lack of cost-effective automation systems that can be widely adopted. Existing optimization-based smart building control algorithms suffer from high costs on both building-specific modeling and on-demand computing resources. To tackle these issues, this paper proposes a cost-effective edge-cloud integrated solution using reinforcement learning (RL). Beside RL’s ability to solve sequential optimal decision-making problems, its adaptability to easy-to-obtain building models and the off-line learning feature are likely to reduce the controller’s implementation cost. Using a surrogate building model learned automatically from building operation data, an RL agent learns an optimal control policy on cloud infrastructure, and the policy is then distributed to edge devices for execution. Simulation results demonstrate the control efficacy and the learning efficiency in buildings of different sizes. A preliminary cost analysis on a 4-zone commercial building shows the annual cost for optimal policy training is only 2.25% of the DR incentive received. Results of this study show a possible approach with higher return on investment for buildings to participate in DR programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

High Performance, High Fidelity: A GPU‐Accelerated Doubly‐Periodic Configuration of the Simple Cloud‐Resolving E3SM Atmosphere Model Version 1 (DP‐SCREAMv1)

The development of the Simplified Cloud Resolving Energy Exascale Earth System Atmosphere Model (SCREAMv1) enables global storm-resolving simulations on modern GPU-based supercomputers. However, the high computational cost of SCREAMv1 limits its routine use for process-level studies, creating a need for efficient proxy configurations. This study addresses this gap by introducing DP-SCREAMv1, a doubly periodic cloud-resolving model designed to be fully consistent with SCREAMv1 while enabling high-resolution, long-duration simulations at significantly reduced computational expense by simulating a limited doubly periodic domain rather than the entire globe. Built on a C++/Kokkos architecture, DP-SCREAMv1 achieves exceptional performance scalability on GPU systems and includes a rich library of cases for validation and scientific exploration. In this work, we demonstrate short wall-clock times at SCREAMv1's default resolution and show that DP-SCREAMv1 supports routine execution of large-domain, high-resolution experiments that were previously challenging in practice. Furthermore, we show that DP-SCREAMv1 enables routine execution of “Giga-LES” style simulations and facilitates large-domain, high-resolution simulations that were recently considered burdensome to perform. These results document an efficient, fully consistent process-level configuration for SCREAMv1 (DP-SCREAMv1) and illustrate its use for long-duration and large-domain experiments at cloud-resolving to eddy-permitting resolution.

Environmental sciences↗

NASA NTRS1992

Multiple scattering effects on spaceborne lidar

A semianalytic Monte Carlo code originally developed for oceanographic calculations (Poole et al., 1981) has been modified for use in studying multiple scattering of space-based lidar. The approach is very similar to that described by Kunkel and Weinman (1976). The trajectory of each photon is followed from the transmitter through multiple scattering until the photon is either scattered backward out of the atmosphere, scattered forward into the ground and absorbed, or scattered out the sides of the cloud. The probability that the photon will return directly to the detector is computed and summed over all significant scattering events within the field of view of the detector. Multiple scattering of the lidar pulse causes an apparent increase in the transmittance of the medium. Multiple scattering effects for space-based lidar are more significant than for ground-based lidar due to the much larger beam diameter in the atmosphere. These larger diameters are due not only to the greater range between the lidar and the scattering volume, but also the need to maintain relatively large beam divergences to satisfy eye safety restrictions on the laser irradiance at the Earth's surface. The simulations presented here are for a wavelength of 1064 nm and the Deirmendjian C1 phase function, which yields an extinction coefficient of 17.259/km. We have looked at two cases: a space-based lidar at 296 km observing a C1 cloud 293 km from the lidar and, for comparison purposes, a ground-based lidar looking at a C1 cloud with a base height of either 2 km or 5 km. The C1 size distribution roughly approximates that of stratocumulus or altocumulus clouds (aufm Kampe and Weickmann, 1957).

Winker, David M.↗

NASA NTRS1975

Computational study of nonlinear plasma waves. I - Simulation model and monochromatic wave propagation. II - Sideband instability and satellite growth

A hybrid plasma simulation model is described and applied to the study of electrostatic wave propagation in a one-dimensional Maxwellian plasma with periodic boundary conditions. The model employs a cloud-in-cell scheme which can drastically reduce the fluctuations in particle simulation models and greatly ease the computational difficulties of the Vlasov equation approach. A grid in velocity space is introduced and the particles are represented by points in the x-v phase space. The model is tested first in the absence of an applied signal and then in the presence of a small-amplitude perturbation. The method is also used to study propagation of an essentially monochromatic plane wave. Results on amplitude oscillation and nonlinear frequency shift are compared with available theories.

Matsuda, Y.↗

NASA NTRS1992

Maintenance of strong rotational winds in Venus' middle atmosphere by thermal tides

The cloud-level atmosphere of Venus takes little more than four days to complete one rotation, whereas the solid planet below has a 243-day period. Computer simulations of the circulation of the Venus middle atmosphere between 40 and 85 kilometers, as driven by solar radiation absorbed in the clouds, reproduce (1) the observed cloud-level rotation rate, (2) strong vertical shears above and below the cloud tops, and (3) midlatitude jets and strong poleward flow on the day side. Simulated circulations converge to yield nearly the same zonal winds when initialized with both stronger or weaker rotation rates. These results support the hypothesis that the observed cloud-top rotation rate is maintained by statistical balance between fluxes of momentum by thermal tides and momentum advection by mean meridional circulation.

Newman, Matthew↗

DOE OSTI2019

Putting the Cloud to Work for Seismology

The cloud infrastructure developed in the business community has enabled access to cluster computing possible for even the smallest research groups, enabling new kinds of research workflows in geophysics.

58 GEOSCIENCES↗