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At least 379 records · Page 21

Runaway electron plateau current profile reconstruction from synchrotron imaging and Ar-II line polarization angle measurements in DIII-D

Abstract Current profile reconstructions are obtained for high current ( I p ≃ 550 kA) post-disruption runaway electron (RE) plateau plasmas in DIII-D. Two novel methods of measuring the RE current profile in high-current RE plateaus are introduced and compared: localization of the q = 2 rational surface using visible synchrotron emission (SE) imaging and the measurement of the polarization angle of line-integrated Ar-II line emission. The two methods are found to be consistent with each other within the data uncertainties. Different simulations of the RE current profile are compared with the measurements: the toroidal fluid RE model is found to best fit the data, within the measurement uncertainties. In addition to introducing two novel methods to measure the RE current profile and validating present simulation capabilities, this work demonstrates that instabilities can grow at q = 2 and q = 1 surfaces without necessarily causing a RE final loss instability. Numerical simulations are also presented to elucidate the role of these instabilities on synchrotron emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Stellar and weak lensing profiles of massive galaxies in the Hyper-Suprime Cam survey and in hydrodynamic simulations

ABSTRACT We perform a consistent comparison of the mass and mass profiles of massive (M⋆ > 1011.4 M⊙) central galaxies at z ∼ 0.4 from deep Hyper Suprime-Cam (HSC) observations and from the Illustris, TNG100, and Ponos simulations. Weak lensing measurements from HSC enable measurements at fixed halo mass and provide constraints on the strength and impact of feedback at different halo mass scales. We compare the stellar mass function (SMF) and the Stellar-to-Halo Mass Relation (SHMR) at various radii and show that the radius at which the comparison is performed is important. In general, Illustris and TNG100 display steeper values of α where $M_{\star } \propto M_{\rm vir}^{\alpha }$. These differences are more pronounced for Illustris than for TNG100 and in the inner rather than outer regions of galaxies. Differences in the inner regions may suggest that TNG100 is too efficient at quenching in situ star formation at Mvir ≃ 1013 M⊙ but not efficient enough at Mvir ≃ 1014 M⊙. The outer stellar masses are in excellent agreement with our observations at Mvir ≃ 1013 M⊙, but both Illustris and TNG100 display excess outer mass as Mvir ≃ 1014 M⊙ (by ∼0.25 and ∼0.12 dex, respectively). We argue that reducing stellar growth at early times in $M_\star \sim 10^{9-10} \, \mathrm{M}_{\odot }$ galaxies would help to prevent excess ex-situ growth at this mass scale. The Ponos simulations do not implement AGN feedback and display an excess mass of ∼0.5 dex at r < 30 kpc compared to HSC which is indicative of overcooling and excess star formation in the central regions. The comparison of the inner profiles of Ponos and HSC suggests that the physical scale over which the central AGN limits star formation is r ≲ 20 kpc. Joint comparisons between weak lensing and galaxy stellar profiles are a direct test of whether simulations build and deposit galaxy mass in the correct dark matter haloes and thereby provide powerful constraints on the physics of feedback and galaxy growth. Our galaxy and weak lensing profiles are publicly available to facilitate comparisons with other simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Load Profiles Data for the EVI-RoadTrip Web Tool

The dataset contains EVI-RoadTrip outputs, minute-by-minute load profiles in kW for each station in the simulation based on assumed utilization and network density. The load profiles are aggregated to lower spatial resolution (e.g., state-level, corridor-level) by summation of all station loads associated with the respective geography. This results in a load profile for each scenario that summarizes the corridor's, state's, or county's load profile in minute-level resolution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermodynamic Profiling Through ASSIST Observations and TROPoe Retrievals

This report reviews the most relevant theoretical aspects of thermodynamic profiling techniques based on spectral observations from ASSIST-II infrared radiometers and TROPoe retrievals. The ASSIST+TROPoe system is a cutting-edge remote sensing technology deployed during the AWAKEN and WFIP3 field campaigns to estimate high-frequency profiles of temperature and humidity in the atmosphere. These profiles are highly valuable for characterizing atmospheric stratification, improving wind models, and understanding the impacts of wind plants on the climate. In this document, we discuss the operating principles of ASSIST, the physics of atmospheric infrared radiation, and the mathematical framework and capabilities of TROPoe. Sources of uncertainties in both the instrument and the retrieval method are also thoroughly addressed. This guide is designed to help users of ASSIST, TROPoe, and thermodynamic data in collecting, estimating, and applying thermodynamic profiles rigorously and scientifically.

17 WIND ENERGY↗

Electrification Futures Study Flexible Load Profiles

This data set includes hourly profiles for flexible load developed for the Electrification Futures Study (EFS). The load profiles represent projected end-use electricity demand that is assumed to be flexible (i.e., can be shifted throughout a day) for various scenarios of flexibility (Base, Enhanced), electrification (Reference, Medium, High), and technology advancement (Slow, Moderate, Rapid), and were developed as inputs into the ReEDS model. The quantity of flexible load is estimated using assumptions on the level of flexibility and customer participation within each subsector modeled in the EFS. Detailed assumptions and modeling implementation will be documented in ongoing EFS analyses. Flexible load profiles are provided for a subset of years (2018, 2020, 2024, 2030, 2040, 2050) and are aggregated to the state and sector level. Total electricity load profiles can be found in a related EFS data set (https://dx.doi.org/10.7799/1593122). NOTE: Due to the file size, Mac users may experience issues decompressing the zip files using the Mac Archive Utility. In those cases, decompressing using the command line is recommended. - Mai, Trieu, Paige Jadun, Jeffrey Logan, Colin McMillan, Matteo Muratori, Daniel Steinberg, Laura Vimmerstedt, Ryan Jones, Benjamin Haley, and Brent Nelson. 2018. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. National Renewable Energy Laboratory. NREL/TP-6A20-71500. https://doi.org/10.2172/1459351. - Murphy, Caitlin, Trieu Mai, Yinong Sun, Paige Jadun, Matteo Muratori, Brent Nelson, Ryan Jones. Forthcoming. Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States. National Renewable Energy Laboratory. - Sun, Yinong, Paige Jadun, Brent Nelson, Matteo Muratori, Caitlin Murphy, Jeffrey Logan, and Trieu Mai. Forthcoming. Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification. National Renewable Energy Laboratory.

buildings↗

Estimating tropical-forest density profiles from multibaseline interferometric SAR

Vertical profiles of forest density are potentially robust indicators of forest biomass, fire susceptibility and ecosystem function. Tropical forests, which are among the most dense and complicated targets for remote sensing, contain about 45% of the world's biomass. Remote sensing of tropical forest structure is therefore an important component to global biomass and carbon monitoring. This paper shows preliminary results of a multibasline interfereomtric SAR (InSAR) experiment over primary, secondary, and selectively logged forests at La Selva Biological Station in Costa Rica. The profile shown results from inverse Fourier transforming 8 of the 18 baselines acquired. A profile is shown compared to lidar and field measurements. Results are highly preliminary and for qualitative assessment only. Parameter estimation will eventually replace Fourier inversion as the means to producing profiles.

profiles↗

Improved Hurricane Boundary Layer Observations with the Imaging Wind and Rain Airborne Profiler

During the NOAA/NESDIS 2005 Hurricane Season (HS2005) and the 2006 Winter Experiment, the University of Massachusetts (UMass) installed two instruments on the NOAA N42RF WP-3D research aircraft: the Imaging Wind and Rain Airborne Profiler (IWRAP) and the Simultaneous Frequency Microwave Radiometer (SFMR). IWRAP is a dual-band (C- and Ku), dual-polarized pencil-beam airborne radar that profiles the volume backscatter and Doppler velocity from rain and that also measures the ocean backscatter response. It simultaneously profiles along four separate incidence angles while conically scanning at 60 RPM. SFMR is a C-band nadir viewing radiometer that measures the emission from the ocean surface and intervening atmosphere simultaneously at six frequencies. It is designed to obtain the surface wind speed and the column average rain rate. Both instruments have previously been flown during the 2002, 2003 and 2004 hurricane seasons. For the HS2005, the IWRAP system was modified to implement a raw data acquisition system. The importance of the raw data system arises when trying to profile the atmosphere all the way down to the surface with a non-nadir looking radar system. With this particular geometry, problems arise mainly from the fact that both rain and ocean provide a return echo coincident in time through the antenna s main lobe. This paper shows how this limitation has been removed and presents initial results demonstrating its new capabilities to derive the atmospheric boundary layer (ABL) wind field within the inner core of hurricanes to much lower altitudes than the ones the original system was capable of, and to analyze the spectral response of the ocean backscatter and the rain under different wind and rain conditions.

tropical cyclones↗

How Certain are We of the Uncertainties in Recent Ozone Profile Trend Assessments of Merged Limbo Ccultation Records? Challenges and Possible Ways Forward

Most recent assessments of long-term changes in the vertical distribution of ozone (by e.g. WMO and SI2N) rely on data sets that integrate observations by multiple instruments. Several merged satellite ozone profile records have been developed over the past few years; each considers a particular set of instruments and adopts a particular merging strategy. Their intercomparison by Tummon et al. revealed that the current merging schemes are not sufficiently refined to correct for all major differences between the limb/occultation records. This shortcoming introduces uncertainties that need to be known to obtain a sound interpretation of the different satellite-based trend studies. In practice however, producing realistic uncertainty estimates is an intricate task which depends on a sufficiently detailed understanding of the characteristics of each contributing data record and on the subsequent interplay and propagation of these through the merging scheme. Our presentation discusses these challenges in the context of limb/occultation ozone profile records, but they are equally relevant for other instruments and atmospheric measurements. We start by showing how the NDACC and GAW-affiliated ground-based networks of ozonesonde and lidar instruments allowed us to characterize fourteen limb/occultation ozone profile records, together providing a global view over the last three decades. Our prime focus will be on techniques to estimate long-term drift since our results suggest this is the main driver of the major trend differences between the merged data sets. The single-instrument drift estimates are then used for a tentative estimate of the systematic uncertainty in the profile trends from merged data records. We conclude by reflecting on possible further steps needed to improve the merging algorithms and to obtain a better characterization of the uncertainties involved.

Merging Algorithms↗

A Tool for Model-Based Generation of Scenario-driven Electric Power Load Profiles

Power consumption during all phases of spacecraft flight is of great interest to the aerospace community. As a result, significant analysis effort is exerted to understand the rates of electrical energy generation and consumption under many operational scenarios of the system. Previously, no standard tool existed for creating and maintaining a power equipment list (PEL) of spacecraft components that consume power, and no standard tool existed for generating power load profiles based on this PEL information during mission design phases. This paper presents the Scenario Power Load Analysis Tool (SPLAT) as a model-based systems engineering tool aiming to solve those problems. SPLAT is a plugin for MagicDraw (No Magic, Inc.) that aids in creating and maintaining a PEL, and also generates a power and temporal variable constraint set, in Maple language syntax, based on specified operational scenarios. The constraint set can be solved in Maple to show electric load profiles (i.e. power consumption from loads over time). SPLAT creates these load profiles from three modeled inputs: 1) a list of system components and their respective power modes, 2) a decomposition hierarchy of the system into these components, and 3) the specification of at least one scenario, which consists of temporal constraints on component power modes. In order to demonstrate how this information is represented in a system model, a notional example of a spacecraft planetary flyby is introduced. This example is also used to explain the overall functionality of SPLAT, and how this is used to generate electric power load profiles. Lastly, a cursory review of the usage of SPLAT on the Cold Atom Laboratory project is presented to show how the tool was used in an actual space hardware design application.

power load profile↗

Changes in Jupiter's Zonal Wind Profile Preceding and During the Juno Mission

We present five epochs of WFC3 HST Jupiter observations taken between 2009-2016 and extract global zonal wind profiles for each epoch. Jupiter's zonal wind field is globally stable throughout these years, but significant variations in certain latitude regions persist. We find that the largest uncertainties in the wind field are due to vortices or hot-spots, and show residual maps which identify the strongest vortex flows. The strongest year-to-year variation in the zonal wind profiles is the 24 deg N jet peak. Numerous plume outbreaks have been observed in the Northern Temperate Belt and are associated with decreases in the zonal velocity and brightness. We show that the 24 deg N jet peak velocity and brightness decreased in 2012 and again in late 2016, following outbreaks during these years. Our February 2016 zonal wind profile was the last highly spatially resolved measurement prior to Juno s first science observations. The final 2016 data were taken in conjunction with Juno's perijove 3 pass on 11 December 2016, and show the zonal wind profile following the plume outbreak at 24 deg N in October 2016.

Jupiter↗

Evaluating a Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product.TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

TEMPO↗

Validation of IASI Satellite Ammonia Observations at the Pixel Scale Using In Situ Vertical Profiles

Satellite ammonia (NH 3 ) observations provide unprecedented insights into NH3 emissions, spatiotemporal variabilities and trends, but validation with in situ measurements remains lacking. Here, total columns from the Infrared Atmospheric Sounding Interferometer (IASI) were intercompared to boundary layer NH 3 profiles derived from aircraft- and surface-based measurements primarily in Colorado, USA, in the summer of 2014. IASI-NH 3 version 3 near real-time data set compared well to in situ derived columns (windows ±15 km around centroid, ±1 h around overpass time) with a correlation of 0.58, a slope of 0.78 ± 0.14 and an intercept of 2.1 × 10 15 ±1.5 × 10 15 molecules cm −2 . Agreement degrades at larger spatiotemporal windows, consistent with the short atmospheric lifetime of NH 3 . We also examined IASI version 3R data, which relies on temperature retrievals from the ERA Reanalysis, and a third product generated using aircraft-measured temperature profiles. The overall agreement improves slightly for both cases, and neither is biased within their combined measurement errors. Thus, spatiotemporal averaging of IASI over large windows can be used to reduce retrieval noise. Nonetheless, sampling artifacts of airborne NH 3 instruments result in significant uncertainties of the in situ-derived columns. For example, large validation differences exist between ascent and descent profiles, and the assumptions of the free tropospheric NH 3 profiles used above the aircraft ceiling significantly impact the validation. Because short-lived species like NH 3 largely reside within the boundary layer with complex vertical structures, more comprehensive validation is needed across a wide range of environments. More accurate and widespread in situ NH 3 data sets are therefore required for improved validations of satellite products.

Ammonia↗

Reduced Dimensionality Analysis of TEMPO Ozone Profile Retrievals Using the Compact Phase Space (CPSR) Algorithm

TEMPO ozone (O 3 ) profile retrievals are expected to have fidelity in the troposphere due the sensitivities of the associated averaging kernels. However, those averaging kernels are severely rank deficiency meaning that a visual inspection of the vertical structure of the averaging kernel profile sensitivities is misleading due linear dependencies in the profile. The Compact Phase Space Retrieval (CPSR) algorithm use singular value decompositions of the averaging kernels and the ‘compressed’ retrieval solution error covariance to project the transformed averaging kernels into a space that removes the linear dependencies and accounts for the solution error uncertainties. In this oral presentation and poster, we apply the CPSR dimensional reduction analysis to TEMPO and TROPOMI O 3 profile retrievals for 13:45 UTC March 29, 2024 to study the phase space characteristics of the transformed averaging kernels as a function of latitude for North America. Our results show that TEMPO generally has more phase space vertical structure in the troposphere than TROPOMI. TEMPO has four to five dominant modes, and TROPOMI has five to six dominant modes. That means that dimensional reduction can reduce the TEMPO resource requirements by ~77% and the TROPOMI requirements by ~81%. Finally, we found that after removing linear dependences and after accounting for solution uncertainties TEMPO still has sensitivities throughout the troposphere.

TEMPO↗

End-Use Load Profiles for the U.S. Building Stock

The United States is embarking on an ambitious transition to a 100% clean energy economy by 2050, which will require improving the flexibility of electric grids. One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High quality end-use load profiles (EULPs) provide this information, and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation. To help fill this gap, the U.S. Department of Energy (DOE) funded a three-year project, End-Use Load Profiles for the U.S. Building Stock, that culminated in this publicly available dataset of calibrated and validated 15-minute resolution load profiles for all major residential and commercial building types and end uses, across all climate regions in the United States. These EULPs were created by calibrating the ResStock and ComStock physics-based building stock models using many different measured datasets, as described in the "Technical Report Documenting Methodology" linked in the submission.

Array↗

Hourly Electricity Demand Profiles for Each County in the Contiguous United States

This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation. The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.

14 SOLAR ENERGY↗

Profile Generation for GPU Targets

GPU accelerators are ubiquitous, but their ecosystem is far less evolved than the host one. Compiler heuristics are often tuned for CPUs and reused for GPU. Similarly, tooling and more evolved optimization techniques are historically not available on GPU targets. In this work, we address one of these shortcomings and enable profile generation and profile-guided optimizations (PGO) for GPU targets. While this is only a single step towards a CPU equivalent ecosystem for offload devices, it shows how old misconceptions on the limitations of GPUs are often not warranted anymore. Through our implementation in LLVM/Offload, we enable device-side PGO for full scientific applications and open up tooling opportunities, including code coverage analysis and compiler-built-in roofline analysis. Our evaluation highlights the performance implications of profile generation, the insights gained from these profiles, and the (missed) opportunities in utilizing the information for GPU compilation.

McDonough, Ethan Luis [Lawrence Livermore National↗

Development of a Time-Height Profile Assimilation Technique for Large-Eddy Simulation

Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

data assimilation↗