Build and Execution Environment (BEE) Containerized workflows for HPC and Cloud
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Man-Computer Interactive Data Access System (McIDAS). Continued development of McIDAS and operation in the GARP Atlantic tropical experiment
The complete output of the Synchronous Meteorological Satellite was recorded on one inch magnetic tape. A quality control subsystem tests cloud track vectors against four sets of criteria: (1) rejection if best match occurs on correlation boundary; (2) rejection if major correlation peak is not distinct and significantly greater than secondary peak; (3) rejection if correlation is not persistent; and (4) rejection if acceleration is too great. A cloud height program determines cloud optical thickness from visible data and computer infrared emissivity. From infrared data and temperature profile, cloud height is determined. A functional description and electronic schematics of equipment are given.
Suomi, V. E.↗
Aircraft observations of Venus' near-infrared reflection spectrum - Implications for cloud composition
A comparison of aircraft-based measurement data on Venus' near-infrared (1.2- to 4.1-micron) reflection spectrum with computer generated spectra of a number of cloud candidates shows a 75-% or more concentrated water solution of sulfuric acid to give the only acceptable match to the profile of Venus' strong 3-micron absorption feature. However, the measurement data obtained also show a modest decline in reflectivity from 2.3-micron to 1.2-micron wavelength, which is inconsistent with the flat spectrum of sulfuric acid in this spectral region. It is hypothesized that this decline is due to impurities in the sulfuric acid droplets.
Pollack, J. B.↗
A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data
This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.
CALIOP and MODIS↗
Ten questions on urban building energy modeling
Buildings in cities consume up to 70% of all primary energy. To achieve cities’ energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings. Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers. This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers in this work aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Application of cellular automata approach for cloud simulation and rendering
Current techniques for creating clouds in games and other real time applications produce static, homogenous clouds. These clouds, while viable for real time applications, do not exhibit an organic feel that clouds in nature exhibit. These clouds, when viewed over a time period, were able to deform their initial shape and move in a more organic and dynamic way. With cloud shape technology we should be able in the future to extend to create even more cloud shapes in real time with more forces. Clouds are an essential part of any computer model of a landscape or an animation of an outdoor scene. A realistic animation of clouds is also important for creating scenes for flight simulators, movies, games, and other. Our goal was to create a realistic animation of clouds.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
MODELING THE THERMAL DIFFUSE SOFT AND HARD X-RAY EMISSION IN M17
We present numerical models of very young wind driven superbubbles. The parameters chosen for the simulations correspond to the particular case of the M17 nebula, but are appropriate for any young superbubble in which the wind sources have not completely dispersed their parental cloud. From the simulations, we computed the diffuse emission in the soft ([0.5-1.5] keV) and hard ([1.5-5] keV) X-ray bands. The total luminosity in our simulations agrees with the observations of Hyodo et al., about two orders of magnitude below the prediction of the standard model of Weaver et al.. The difference with respect to the standard (adiabatic) model is the inclusion of radiative cooling, which is still important in such young bubbles. We show that for this type of object the diffuse hard X-ray luminosity is significant compared to that of soft X-rays, contributing as much as 10% of the total luminosity, in contrast with more evolved bubbles where the hard X-ray emission is indeed negligible, being at least four orders of magnitude lower than the soft X-ray emission.
79 ASTRONOMY AND ASTROPHYSICS↗
Stratus: An interactive steady state mixed layer model for personal computers
A steady-state, horizontally homogeneous, cloud-topped marine boundary layer model based primarily on the work of Lilly (1968) and Schubert et al., (1979) is presented. The conservative thermodynamic variables are equivalent potential temperature, theta(sub e), and total water mixing ratio, q + l. Some of the differences between this and Lilly's (1968) model are: radiation is allowed to penetrate into the boundary layer; cloud top values of longwave radiation, equivalent potential temperature, and water vapor mixing ratio are linear functions of height derived from climatological data at California coastal stations; and the closure assumption assumes a weighted average of Lilly's (1968) maximum and minimum entrainment theories. This model was programmed in FORTRAN and will run interactively on an IBM-compatible personal computer. The program allows the user to specify the geographical location, the wind speed, the sea-surface temperature, the large scale horizontal divergence, and the initial guess for cloud top height. Output includes the steady state values of cloud top and cloud base height, mixed layer equivalent potential temperature and total water mixing ratio, and the associated convective and radiative fluxes.
Guinn, Thomas A.↗
The Silver Lining
Clouds are shareable scientific instruments that create the potential for reproducibility by ensuring that all investigators have access to a common execution platform on which computational experiments can be repeated and compared. By virtue of the interface they present, they also lead to the creation of digital artifacts compatible with the cloud, such as images or orchestration templates, that go a long way-and sometimes all the way-to representing an experiment in a digital, repeatable form. In this article, I describe how we developed these natural advantages of clouds in the Chameleon testbed and argue that we should leverage them to create a digital research marketplace that would make repeating experiments as natural and viable part of research as sharing ideas via reading papers is today.
Cloud computing↗
Interstellar absorption lines in the spectrum of zeta Ophiuchi
Extensive high-resolution scans with the Copernicus UV spectrometer are combined with available ground-based data on interstellar lines to obtain temperatures, densities, and abundances in H I clouds and H II regions in the direction of zeta Oph. Column densities are obtained for 21 elements in various ionization stages, and upper limits are reported for 5 elements and 11 molecules. Analysis of radial velocities and growth curves indicates that H2, HD, and most neutral atoms are concentrated in one cloud with a heliocentric velocity of -14.4 km/s and that H II regions exist in addition to the Stroemgren sphere. The electron and proton densities are calculated for the -14.4 km/s cloud, and the temperatures required for the populations of the fine-structure levels in the C I ground state and the excited rotational levels of H2 are computed and indicate that the dense cloud must have some associated hotter regions. Relative to hydrogen, most of the elements in the H I clouds are found to be depleted by factors of 3 to 4000 as compared with solar system abundances, and several elements appear to be depleted in the H II regions as well.
Morton, D. C.↗
To Exascale and Beyond—The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), a Performance Portable Global Atmosphere Model for Cloud-Resolving Scales
The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional “high–resolution” simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real-world climate via a set of four 40 day simulations covering all 4 seasons of the year.
54 ENVIRONMENTAL SCIENCES↗
High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation
Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Data Provenance Hybridization Supporting Extreme-Scale Scientific WorkflowApplications
As high performance computing (HPC) infrastructures continue to grow in capability and complexity, so do the applications that they serve. HPC and distributed-area computing (DAC) (e.g. grid and cloud) users are looking increasingly toward workflow solutions to orchestrate their complex application coupling, pre- and post-processing needs To gain insight and a more quantitative understanding of a workflow’s performance our method includes not only the capture of traditional provenance information, but also the capture and integration of system environment metrics helping to give context and explanation for a workflow’s execution. In this paper, we describe IPPD’s provenance management solution (ProvEn) and its hybrid data store combining both of these data provenance perspectives.
provenance↗
SU-E-J-184: Stereo Time-Of-Flight System for Patient Positioning in Radiotherapy
Purpose: The objective of this work is to test the advantage of using the surface acquired by two stereo Time-of-Flight (ToF) cameras in comparison of the use of one camera only for patient positioning in radiotherapy. Methods: A first step consisted on validating the use of a stereo ToFcamera system for positioning management of a phantom mounted on a linear actuator producing very accurate and repeatable displacements. The displacements between two positions were computed from the surface point cloud acquired by either one or two cameras thanks to an iterative closest point algorithm. A second step consisted on determining the displacements on patient datasets, with two cameras fixed on the ceiling of the radiotherapy room. Measurements were done first on voluntary subject with fixed translations, then on patients during the normal clinical radiotherapy routine. Results: The phantom tests showed a major improvement in lateral and depth axis for motions above 10 mm when using the stereo-system instead of a unique camera (Fig1). Patient measurements validate these results with a mean real and measured displacement differences in the depth direction of 1.5 mm when using one camera and 0.9 mm when using two cameras (Fig2). In the lateral direction, a mean difference of 1 mm was obtained by the stereo-system instead of 3.2 mm. Along the longitudinal axis mean differences of 5.4 and 3.4 mm with one and two cameras respectively were noticed but these measurements were still inaccurate and globally underestimated in this direction as in the literature. Similar results were also found for patient subjects with a mean difference reduction of 35%, 7%, and 25% for the lateral, depth, and longitudinal displacement with the stereo-system. Conclusion: The addition of a second ToF-camera to determine patient displacement strongly improved patient repositioning results and therefore insures better radiation delivery.
60 APPLIED LIFE SCIENCES↗
Towards Cross-Facility Workflows Orchestration through Distributed Automation
Modern science relies on end-to-end workflows that incorporate experimental instruments and utilize edge, cloud, or high-performance computing and storage resources. These components are geographically dispersed across various user facilities and interconnected through high-speed networks. In this paper, we present Zambeze, an automated distributed framework designed to facilitate this new class of cross-facility workflows. Utilizing swarm intelligence principles, Zambeze orchestrates science campaigns by managing distributed autonomous agents. These agents can offer a suite of services, including computing, storage, and data management. We demonstrate the feasibility of Zambeze through a real-world application involving electron microscopy, enhanced with Artificial Intelligence capabilities.
Skluzacek, Tyler↗
Use Case-Informed Framework for Utility Cloud Migration
This white paper presents a comprehensive methodology for assessing utilities’ cloud postures and frameworks. It aims to produce a roadmap and strategy for a cloud-enabled grid future, providing guidance for integrators, asset owners, and operators. Instead of offering a yes or no answer for cloud implementation, this framework offers strategic guidance on responsibly preparing for and deploying cloud solutions. This paper delves into cloud-service models pertinent to the electric sector, dissecting the shared responsibility model and elucidating what on-premise infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) entail. A pivotal consideration within the context of the shared responsibility model is the allocation of responsibility for foundational security aspects—a decision that will be informed by a comprehensive risk assessment. The ensuing discussion will present a checklist of certifications necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and with a strategic roadmap. Furthermore, the paper outlines gaps in understanding the U.S. government’s role in shaping technology development and responsible use. Its purpose is to aid decision-making by offering support for risk-informed solutions that benefit those managing assets and operating in the cloud environment. The primary objective is to enhance the resilience and future readiness of a decarbonized electric grid, with cloud solutions as one viable option. The paper synthesizes information on current and future grid architectures and applications, considering both conservative and progressive energy transitions, along with scalable and distributed computing considerations.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Angle Assessment for Upper Limb Rehabilitation: A Novel Light Detection and Ranging (LiDAR)-Based Approach
The accurate measurement of joint angles during patient rehabilitation is crucial for informed decision making by physiotherapists. Presently, visual inspection stands as one of the prevalent methods for angle assessment. Although it could appear the most straightforward way to assess the angles, it presents a problem related to the high susceptibility to error in the angle estimation. In light of this, this study investigates the possibility of using a new approach to angle calculation: a hybrid approach leveraging both a camera and LiDAR technology, merging image data with point cloud information. This method employs AI-driven techniques to identify the individual and their joints, utilizing the cloud-point data for angle computation. The tests, considering different exercises with different perspectives and distances, showed a slight improvement compared to using YOLO v7 for angle calculation. However, the improvement comes with higher system costs when compared with other image-based approaches due to the necessity of equipment such as LiDAR and a loss of fluidity during the exercise performance. Therefore, the cost–benefit of the proposed approach could be questionable. Nonetheless, the results hint at a promising field for further exploration and the potential viability of using the proposed methodology.
Klein, Luan C. (ORCID:000000016306574X)↗
A two-layer model of the Jovian clouds
Two layer model of Jovian clouds including clear space, showing computed and measured equivalent widths of H quadrupole lines
Danielson, R. E.↗