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At least 793 records · Page 44

Side-by-Side Comparison of Subhourly Clipping Models: Preprint

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to inter-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of said approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating two different clipping correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons will be performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The models can improve accuracy up to 3% in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

clipping↗

ORDEM2010 and MASTER-2009 Modeled Small Debris Population Comparison

The latest versions of the two premier orbital debris engineering models, NASA s ORDEM2010 and ESA s MASTER-2009, have been publicly released. Both models have gone through significant advancements since inception, and now represent the state-of-the-art in orbital debris knowledge of their respective agencies. The purpose of these models is to provide satellite designers/operators and debris researchers with reliable estimates of the artificial debris environment in near-Earth orbit. The small debris environment within the size range of 1 mm to 1 cm is of particular interest to both human and robotic spacecraft programs. These objects are much more numerous than larger trackable debris but are still large enough to cause significant, if not catastrophic, damage to spacecraft upon impact. They are also small enough to elude routine detection by existing observation systems (radar and telescope). Without reliable detection the modeling of these populations has always coupled theoretical origins with supporting observational data in different degrees. This paper details the 1 mm to 1 cm orbital debris populations of both ORDEM2010 and MASTER-2009; their sources (both known and presumed), current supporting data and theory, and methods of population analysis. Fluxes on spacecraft for chosen orbits are also presented and discussed within the context of each model.

Krisko, Paula H.↗

ORDEM 3.0 and MASTER-2009 Modeled Small Debris Population Comparison

The latest versions of the two premier orbital debris engineering models, NASA's ORDEM 3.0 and ESA's MASTER-2009, have been publicly released within the last year. Both models have gone through significant advancements since inception, and now represent the state-of-the-art in orbital debris knowledge of their respective agencies. The purpose of these models is to provide satellite designers/operators and debris researchers with reliable estimates of the artificial debris environment in near-Earth orbit. The small debris environment within the size range of 1 mm to 1 cm is of particular interest to both human and robotic spacecraft programs. These objects are much more numerous than larger trackable debris but are still large enough to cause significant, if not catastrophic, damage to spacecraft upon impact. They are also small enough to elude routine detection by existing observation systems (radar and telescope). Without reliable detection the modeling of these populations has always coupled theoretical origins with supporting observational data in different degrees. This paper describes the population generation and categorization of both ORDEM 3.0 and MASTER-2009; their sources (both known and presumed), current supporting data and theory, and methods of population verification. Fluxes on spacecraft for chosen orbits are presented and discussed. Future collaborative analysis is noted.

Krisko, P. H.↗

ORDEM 3.0 and MASTER-2009 Modeled Small Debris Population Comparison

The latest versions of the two premier orbital debris engineering models, NASA's ORDEM 3.0 and ESA's MASTER-2009, have been publically released. Both models have gone through significant advancements since inception, and now represent the state-of-the-art in orbital debris knowledge of their respective agencies. The purpose of these models is to provide satellite designers/operators and debris researchers with reliable estimates of the artificial debris environment in low Earth orbit (LEO) to geosynchronous orbit (GEO). The small debris environment within the size range of 1 mm to 1 cm is of particular interest to both human and robotic spacecraft programs, particularly in LEO. These objects are much more numerous than larger trackable debris and can have enough momentum to cause significant, if not catastrophic, damage to spacecraft upon impact. They are also small enough to elude routine detection by existing observation systems (radar and telescope). Without reliable detection the modeling of these populations has always coupled theoretical origins with supporting observational data in different degrees. In this paper, we present and detail the 1 mm to 1 cm orbital debris populations from both ORDEM 3.0 and MASTER-2009 in LEO. We review population categories: particle sources for MASTER-2009, particle densities for ORDEM 3.0. We describe data sources and their uses, and supporting models. Fluxes on spacecraft for chosen orbits are also presented and discussed within the context of each model.

Krisko, P. H.↗

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to subhourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

accuracy↗

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to sub-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗

Open‐source photovoltaic model pipeline validation against well‐characterized system data

Abstract All freely available plane‐of‐array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib‐python and pvpltools‐python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853‐1 and 61853‐2 testing, and the input data for each model were sourced from these system‐specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system‐specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system‐specific data.

14 SOLAR ENERGY↗

Use-Inspired, Process-Oriented GCM Selection: Prioritizing Models for Regional Dynamical Downscaling

Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).

54 ENVIRONMENTAL SCIENCES↗

Developing a simulator-based satellite dataset for using machine learning techniques to derive aerosol-cloud-precipitation interactions in models and observations in a consistent framework

Aerosol-cloud-precipitation interactions (ACPI) remain a major uncertainty in understanding the Earth’s radiation budget and water cycle (including extremes). After decades of active research, various observationally based metrics have been developed to constrain ACPI in Earth System Models (ESMs), but direct comparison of model and data estimates can confound scientific understanding because limitations and uncertainties in sampling and retrieval procedures may combine with model deficiencies in process representations of ACPI to obstruct understanding. Furthermore, conventional ACPI metrics often vary from one regime to another, and the ACPI process representation in ESMs is also typically derived based on only a limited area/regime (even though the parameterization applies globally). To bridge the gap between models and data and to correctly describe ACPI in all regimes, we propose to construct a new CALIPSO-CloudSat merged dataset that is produced by the same algorithms used in satellite simulators in ESMs, and to use machine learning techniques to derive new ACPI metrics that can be accurately estimated by satellites and can provide meaningful constraints on cloud microphysical process representations in ESMs. The dataset will include measured and retrieved variables for aerosol, cloud, and precipitation from CALIPSO and CloudSat, and environmental variables from meteorological reanalysis. The data will be used to train a neural network to construct the ACPI metrics as a function of environmental conditions. The new ACPI formula will be used to constrain the ACPI in the Energy Exascale Earth System Model (E3SM), and to augment/reformulate the ACPI process representation in the E3SM to improve the simulation of the evolution of the atmosphere under different environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

Comparison of candidate IGRF models

Three candidate models for the International Geomagnetic Reference Field (IGRF) for the years 1965, 1970, 1975, and 1980 are evaluated using magnetic observatory and satellite data. The models were submitted by the USGS, the IGS, and NASA. Comparison based on annual means data shows the differences between models to be small, although the NASA model appears slightly more accurate in 1965 and 1975 and the IGS model in 1970. Evaluation with Magsat scalar and vector satellite data at 1980 shows the USGS and NASA models to be of comparable accuracy, while the IGS model displays larger residuals. The NASA model best represents the scalar POGO data at 1965 and 1970. Contoured differences between the models in components X, Y, Z, and F at the earth's surface at 1965, 1970, 1975 and 1980 are displayed and discussed.

Langel, R. A.↗

Analytical methods for the development of Reynolds stress closures in turbulence

Analytical methods for the development of Reynolds stress models in turbulence are reviewed in detail. Zero, one and two equation models are discussed along with second-order closures. A strong case is made for the superior predictive capabilities of second-order closure models in comparison to the simpler models. The central points are illustrated by examples from both homogeneous and inhomogeneous turbulence. A discussion of the author's views concerning the progress made in Reynolds stress modeling is also provided along with a brief history of the subject.

Speziale, Charles G.↗

Mars Global Surveyor: Aerobraking and Observations Support Using a Mars Global Circulation Model

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. The primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-110 km) for seasonal dates and locations during Phase I aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase I aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars' middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.

Hollingsworth, Jeffery L.↗

Mars Global Surveyor: Aerobraking and Observations Support Using a Mars Global Circulation Model

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. The primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-1 10 km) for seasonal dates and locations during Phase 1 aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase I aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.

Hollingsworth, Jeffery L.↗

Mars Global Surveyor: Aerobraking and Observations Support Using a Mars Global Circulation Model

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. Using a global atmospheric circulation model for Mars, the focus of this JRI has been to provide support for the Mars Global Surveyor (MGS) spacecraft aerobraking activities and interpretation guidance of preliminary observations. ne primary atmospheric model applied in this investigation has been a high-top version of the NASA Ames Mars general circulation model (MGCM). Comparisons with an atmospheric model designed primarily for engineering purposes (Mars-GRAM) has also been carried out. From a suite of MGCM simulations, we have assessed plausible spatial and temporal variability in atmospheric density at high altitudes (e.g., 70-110 km) for seasonal dates and locations during Phase 1 aerobraking. Diagnostic tools have been developed to analyze circulation fields from the MGCM simulations, and these tools have been applied in the creation of a Mars climate catalogue database. Throughout Phase 1 aerobraking activities, analysis products have been provided to the MGS aerobraking atmospheric advisory group (AAG). Analyses of circulation variability at the coupling level between the MGCM and a Mars thermospheric global circulation model (MTGCM) has also been assessed. Finally, using a quasi-geostrophic dynamical formulation with the MGCM simulations, diagnosis of breaking planetary (Rossby) waves in Mars' middle atmosphere has been carried out. Titles of papers presented at scientific workshops and seminars, and a publication in the scientific literature are provided.

Hollingsworth, Jeffery L.↗

Discovery of the Accretion-Powered Millisecond Pulsar SWIFT 51756.9-2508 with a Low-Mass Companion

We report on the discovery by the Swift Gamma-Ray Burst Explorer of the eighth known transient accretion-powered millisecond pulsar: SWIFT J1756.9-2508, as part of routine observations with the Swift Burst Alert Telescope hard X-ray transient monitor. The pulsar was subsequently observed by both the X-Ray Telescope on Swift and the Rossi X-Ray Timing Explorer Proportional Counter Array. It has a spin frequency of 182 Hz (5.5 ms) and an orbital period of 54.7 minutes. The minimum companion mass is between 0.0067 and 0.0086 Solar Mass, depending on the mass of the neutron star, and the upper limit on the mass is 0.030 Solar Mass (95% confidence level). Such a low mass is inconsistent with brown dwarf models. and comparison with white dwarf models suggests that the companion is a He-dominated donor whose thermal cooling has been at least modestly slowed by irradiation from the accretion flux. No X-ray bursts. dips, eclipses or quasi-periodic oscillations were detected. The current outburst lasted approx. 13 days and no earlier outbursts were found in archival data.

Krimm, H.A.↗

Distribution and Sources of Tropospheric Aerosols Over the Western North Atlantic During ACTIVATE (February-March 2020)

The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a five-year (2019-2023) NASA Earth-Venture Suborbital-3 (EVS-3) mission to robustly characterize aerosol-cloud-meteorology interactions during February-June, with a focus on marine boundary layer clouds. This characterization requires understanding of aerosol composition, distribution, transport pathways, and sources. Here we use the GEOS-Chem chemical transport model driven by the MERRA-2 reanalysis to simulate tropospheric carbon monoxide (CO) and aerosols over the western North Atlantic Ocean (WNAO) during the first field deployment of ACTIVATE (February-March 2020). CO is used as a tracer to diagnose transport pathways for continental pollution outflow to the WNAO. The aerosol simulation represents all major aerosols including sulfate-nitrate-ammonium (SNA), mineral dust, sea salt, black and organic carbon aerosols. Model-simulated mixing ratios of SNA and organic carbon are compared with aircraft observations. We show that intensive aerosol mass measurements in the lower troposphere over the North American outflow region during ACTIVATE provide strong constraints on model aerosol wet scavenging. Comparisons of model aerosol extinctions with the airborne High Spectral Resolution Lidar-2 (HSRL-2) measurements indicate that the model generally captures continental outflow of aerosols and enhanced extinctions associated with sea salt. Simulated aerosol optical depths (AODs) and extinction vertical profiles are also compared with satellite retrievals from MODIS/Aqua and CALIOP/CALIPSO, respectively. CALIOP sometimes observes enhanced aerosol extinction at altitudes between ~1.5km and ~2.0km south of 32°N. The model reproduces this enhancement and attributes it to coarse-mode sea salt associated with high relative humidity. The relative contributions of continental and oceanic sources to the aerosol loading, AOD, and their distributions over the study domain will also be discussed.

aerosols↗

Intern-Artificial Intelligence Benchmarking

Benchmarks provide a standardized method for evaluating different AI models, enabling reproducibility and comparison between models, and facilitating scientific progress. As AI models continue to develop rapidly, incorporating new datasets, capabilities, and architectures becomes more complicated. Therefore, the current static benchmarks become increasingly irrelevant. The MLCommons team argues that to make AI benchmarks more relevant, it involves making the benchmarks themselves more dynamic, as well as technical innovations that make it easier for scientists and researchers at all levels to use and contribute to the benchmarks. The current progress in technical innovation is a software that allows for a detailed view of a collection of AI benchmarks to be output in various formats that are easily readable and accessible.

Krishnan, Anjay [Fermilab]↗

Comparison of the Beckmann model with bidirectional reflectance measurements.

The Beckmann model is compared with recently reported bidirectional reflectance measurements. Comparisons revealed that monochromatic specular and bidirectional reflectance measurements are not adequately described by corresponding results evaluated from the model using mechanically acquired surface roughness parameters (rms height and rms slope). Significant improvement between measurements and predictions of the model is observed when optically acquired surface roughness parameters are used. Specular reflectance measurements for normal to intermediate polar angles of incidence are adequately represented by the model provided values of optical roughness multiplied by cosine of polar angle of incidence are less than 27 times average optical rms slope.

Smith, T. F.↗