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At least 1,657 records · Page 92

UQ Methods for HPDA and Cybersecurity Models, Data, and Use Cases

This report describes our initial research to quantify uncertainties in the identification and characterization of possible attack states in a network. As a result, we should be able to estimate the current state in which the network is operating, based on a wide variety of network data, and attach a defensible measure of confidence to these state estimates. The output of this research will be new uncertainty quantification (UQ) methods to help develop a process for model development and apply UQ to characterize attacks/adversaries, create an understanding of the degree to which methods scale to "big" data, and offer methods for addressing model approaches with regard to validation and accuracy.

97 MATHEMATICS AND COMPUTING↗

Mobility Data and Models Informing Smart Cities

DOE SMART Mobility Urban Science Efforts are helping use/develop key data sets, models, and roles for DOE in engaging across seven Smart City Finalists as well as for ensuring useful/useable insights. Austin, Texas, was targeted for analyses of opportunity (model and data maturity). Other Urban Science/broader SMART initiatives were also helped by this research.

33 ADVANCED PROPULSION SYSTEMS↗

Prioritizing the selection of CMIP6 model ensemble members for downscaling projections of CONUS temperature and precipitation

Given the mismatch between the large volume of data archived for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and limited personnel and computational resources for downscaling, only a small fraction of the CMIP6 archive can be downscaled. In this work, we develop an approach to robustly sample projected hydroclimate states in CMIP6 for downscaling to test whether the selection of a single initial condition (IC) ensemble member from each CMIP6 model is sufficient to span the range of modeled hydroclimate over the conterminous United States (CONUS) and CONUS sub-regions. We calculate the pattern-centered root mean square difference of IC ensemble member anomalies relative to each model’s historical climatology for shared socioeconomic pathway (SSP) projections over 30-year time periods and compare the ratio of inter-model to intra-model variability for this metric. Regardless of SSP, inter-model variability is generally much greater than intra-model variability at the scales of the CONUS as a whole, as well as for most CONUS sub-regions. However, for some variables and scenarios, inter- and intra-model variability are similar at sub-CONUS scales, indicating that selecting a single IC ensemble member per model may be sufficient to sample the range of projected hydroclimate states in the 21st Century across CONUS, but for specific regions and variables, more careful selection of ensemble members may be necessary. Regionally resolved Taylor diagrams identify where more IC ensemble member downscaling efforts should be focused if resources are available to do so. Our results suggest that, with parsimonious sampling, the requisite computational expense of downscaling temperature and precipitation fields over the CONUS for subsequent CMIP activities may increase only marginally despite the great increase in data volumes with each successive CMIP phase.

54 ENVIRONMENTAL SCIENCES↗

Nuclear Energy Cost Estimates for Net Zero World Initiative – 2024 Update

This report provides recommended parameters for incorporating nuclear energy systems into decarbonization modeling scenarios. The values are primarily intended for the Net Zero World (NZW) Initiative but are expected to prove useful to other related efforts. Both costs and operational metrics are provided in the study for large reactors and small modular reactors (SMR).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Investigation of Ga 2 O 3 as a new transparent conductive oxide for photovoltaics applications

This small innovation project intended to leverage recent activity and advances in ultrawide-bandgap oxide power electronics toward the investigation of Ga 2 O 3 as a transparent conductive oxide (TCO) for use in photovoltaics (PV). Ga 2 O 3 ’s theoretical advantage over incumbent TCOs is its very large bandgap of 4.8 eV, ensuring optical transparency of photons with λ ≥ 260 nm, effectively the full terrestrial solar spectrum. At the time of proposal writing, literature on Ga 2 O 3 as a TCO/optical material was relatively sparse — what little existed was focused on for UV sensors and/or emitters, with none related to PV. As such, this project was intended to help determine the potential of Ga 2 O 3 as a PV-oriented TCO by investigating its deposition using tools common to the PV and electronics industries — atomic layer deposition (ALD) and RF sputtering (RS), both of which are already used in PV manufacturing — and its resultant optical and electronic properties. Final project goals were to test its application to Si and III-V solar cells. Controllable film thickness and excellent uniformity was established for both methods deposition methods, with ALD providing higher precision for thinner films and RS more effective for growing thicker films. The as-deposited films were found to be amorphous in nature. Spectroscopic ellipsometry (SE) confirmed bandgaps of at least 4.8 eV and non-parasitic absorption across both AM0 and AM1.5G spectra; a refractive index approaching the expected value of 1.8 was also observed, with some degree of tunability based on process parameters. Using this initial optical data, a transfer matrix model, which interfaces with in-house EQE and LIV models, was developed to simulate Ga 2 O 3 optical effects on various solar cells, included potential in antireflection coatings (ARCs). Despite promising optical properties, the resultant resistivity / conductivity metrics did not meet expectations, regardless of deposition process. Although thick RS-deposited films, using both undoped and 1 at% Ge (n-type) doped sintered targets — demonstrated high net carrier concentrations (via C-V), and low specific resistance Ohmic contacts were demonstrated, transmission line measurements (TLM) showed very high resistivity. Further analysis indicated high vertical film conductivity, but very low lateral conductivity. Deeper characterization revealed a relatively high density of nano/microcrystalline inclusions that were ostensibly the source of the vertical conductivity, with the amorphous matrix serving as an effective insulator (likely due to high concentrations of electronic trap states). Despite extensive work to increase film polycrystallinity — demonstrated via high temperature annealing — sufficient lateral conductivity for TCO use was not achieved. The final phase of the project shifted focus toward investigation of ALD-deposited Ga 2 O 3 ’s potential as a passivant and/or passivating contact for both Si and III-V solar cells, with expectation of performance similar to Al 2 O 3 . However, initial rounds of testing using our baseline ALD process yielded minimal (but not quite zero) passivation of both GaInP and Si surfaces. Dielectric passivation is well-known to be highly process sensitive; given the unoptimized nature of the process used, this work was deemed inconclusive. The final outlook with respect to feasibility of Ga 2 O 3 as a PV-oriented TCO is, ultimately, still uncertain. The work performed in this project confirmed the optical properties and deposition methods, but the achieved electrical properties do not meet technological needs; literature reports in recent years are somewhat inconsistent and potentially untrustworthy, but generally appear to be in line with our results. At the very least it is clear that, should Ga 2 O 3 still be under consideration for PV TCO and/or selective contact applications, a significant amount of optimization and study is still needed.

14 SOLAR ENERGY↗

Testing the Delayed Gamma Capability in MCNP6

The mission of the Domestic Nuclear Detection Office is to quickly and reliably detect unauthorized attempts to import or transport special nuclear material for use against the United States. Developing detection equipment to meet this objective requires accurate simulation of both the detectable signature and detection mechanism. A delayed particle capability was initially added to MCNPX 2.6.A in 2005 to sample the radioactive fission product parents and emit decay particles resulting from the decay chain. To meet the objectives of detection scenario modeling, the capability was designed to sample a particular time for emitting particular multiplicity of a particular energy. Because the sampling process of selecting both time and energy is interdependent, to linearize the time and emission sampling, atom densities are computed at several discrete time steps, and the time-integrated production is computed by multiplying the atom density by the decay constant and time step size to produce a cumulative distribution function for sampling the emission time, energy, and multiplicity. The delayed particle capability was initially given a time-bin structure to help reasonably reproduce, from a qualitative sense, a fission benchmark by Beddingfield, which examined the delayed gamma emission. This original benchmark was only qualitative and did not contain the magnitudes of the actual measured data but did contain relative graphical representation of the spectra. A better benchmark with measured data was later provided by Hunt, Mozin, Reedy, Selpel, and Tobin at the Idaho Accelerator Center; however, because of the complexity of the benchmark setup, sizable systematic errors were expected in the modeling, and initial results compared to MCNPX 2.7.0 showed errors outside of statistical fluctuation. Presented in this paper is a more simplified approach to benchmarking, utilizing closed form analytic solutions to the granddaughter equations for particular sets of decay systems. We examine five different decay chains (two-stage decay to stable) and show the predictability of the MCNP6 delayed gamma feature. Results do show that while the default delayed gamma calculations available in the MCNP6 1.0 release can give accurate results for some isotopes (e.g., 137 Ba), the percent differences between the closed form analytic solutions and the MCNP6 calculations were often >40% ( 28 Mg, 28 Al, 42 K, 47 Ca, 47 Sc, 60 Co). With the MCNP6 1.1 Beta release, the tenth entry on the DBCN card allows improved calculation within <5% as compared to the closed form analytic solutions for immediate parent emissions and transient equilibrium systems. While the tenth entry on the DBCN card for MCNP6 1.1 gives much better results for transient equilibrium systems and parent emissions in general, it does little to improve daughter emissions of secular equilibrium systems. Finally, hypotheses were presented as to why daughter emissions of secular equilibrium systems might be mispredicted in some cases and not in others.

42 ENGINEERING↗

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗

Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project

Abstract. The Atlantic meridional overturning circulation (AMOC) is an important part of our climate system. The AMOC is predicted to weaken under climate change; however, theories suggest that it may have a tipping point beyond which recovery is difficult, hence showing quasi-irreversibility (hysteresis). Although hysteresis has been seen in simple models, it has been difficult to demonstrate in comprehensive global climate models. Here, we outline a set of experiments designed to explore AMOC hysteresis and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP). These experiments include adding additional freshwater (hosing) for a fixed length of time to examine the rate and mechanisms of AMOC weakening and whether the AMOC subsequently recovers once hosing stops. Initial results are shown from eight climate models participating in the Sixth Coupled Model Intercomparison Project (CMIP6). The AMOC weakens in all models as a result of the freshening, but once the freshening ceases, the AMOC recovers in half of the models, and in the other half it stays in a weakened state. The difference in model behaviour cannot be explained by the ocean model resolution or type nor by details of subgrid-scale parameterisations. Likewise, it cannot be explained by previously proposed properties of the mean climate state such as the strength of the salinity advection feedback. Instead, the AMOC recovery is determined by the climate state reached when hosing stops, with those experiments where the AMOC is weakest not experiencing a recovery.

54 ENVIRONMENTAL SCIENCES↗

Exfoliation Propensity of Oxide Scale in Heat Exchangers Used for Supercritical CO2 Power Cycles

Supercritical CO2 (sCO2) Brayton cycle systems offer the possibility of improved efficiency in future fossil energy power generation plants operating at temperatures of 650 C and above. As there are few data on the oxidation/corrosion behavior of structural alloys in sCO2 at these temperatures, modeling to predict the propensity for oxide exfoliation is not well developed, thus hindering materials selection for these novel cycles. The ultimate goal of this effort is to provide needed data on scale exfoliation behavior in sCO2 for confident alloy selection. To date, a model developed by ORNL and EPRI for the exfoliation of oxide scales formed on boiler tubes in high-temperature, high-pressure steam has proven useful for managing exfoliation in conventional steam plants. A major input provided by the model is the ability to predict the likelihood of scale failure and loss based on understanding of the evolution of the oxide morphologies and the conditions that result in susceptibility to exfoliation. This paper describes initial steps taken to extend the existing model for exfoliation of steam-side oxide scales to sCO2 conditions. The main differences between high-temperature, high-pressure steam and sCO2 that impact the model involve (i) significant geometrical differences in the heat exchangers, ranging from standard pressurized tubes seen typically in steam-producing boilers to designs for sCO2 that employ variously-curved thin walls to create shaped flow paths for extended heat transfer area and small channel cross-sections to promote thermal convection and support pressure loads; (ii) changed operating characteristics with sCO2 due to the differences in physical and thermal properties compared to steam; and (iii) possible modification of the scale morphologies, hence properties that influence exfoliation behavior, due to reaction with carbon species from sCO2. The numerical simulations conducted were based on an assumed sCO2 operating schedule and several generic heat exchanger channel shapes and cross-sectional areas. Implications for the evolution of stresses in the oxide scales formed on sCO2 heat exchangers, and ensuing critical oxide thicknesses for exfoliation, were derived and compared with expectations for an equivalent conventional tubular heat exchanger in a steam cycle (for a given alloy).

Sabau, Adrian S↗

Fragmentation Prediction for a Brittle Ceramic: An Integrated Two-Scale Model Approach

A new implementation of a multi-scale fragmentation model is introduced that combines existing independent macro and micro-scale models into a single material model within the Library of Advanced Materials for Engineering (LAME) that can be used directly by the finite element structural mechanics code SIERRA/SM, developed at Sandia National Laboratories. The implementation not only joins existing independent fragmentation models into a single framework, but also enables further development by virtue of being integrated into SIERRA/SM. Integration with a finite element structural mechanics code for a true two-way coupling of the fragmentation models that were previously independent. Hereafter, the prior implementation will be referred to as the sequentially applied fragmentation model. In contrast, the newly developed model will be called the integrated two-scale model. The sequentially applied fragmentation model consists of two independent models applied sequentially to account for the macro-scale and microscale fragmentation. The macro-scale fragmentation behavior is calculated using an elastic gradient damage explicit material model developed to model fracture in brittle materials. The micro-scale fragmentation model is an implementation of the 1D cohesive-zone model developed by Zhou, et al. The micro-scale model is implemented by post-processing the macro-scale data that provides initial conditions for the 1D analysis. The micro-scale model is necessary to predict the resulting fragment size distribution at length scales inaccessible to the finite element based macro-scale model. The full range of fragmentation behavior is then predicted by combining the results from the two independent models. The sequentially applied fragmentation model was used to predict the fragments that result from impact loading of a brittle material, which in that case was a ceramic cylinder of commercial UO{sub 2} nuclear fuel. Understanding the fragmentation behavior of such materials is important for evaluating the risk of airborne particulate release under impact loading scenarios. This work will verify the implementation of the integrated two-scale model using the same experiment modeled by the existing sequentially applied model. The purpose of this manuscript is to introduce the new integrated two-scale fragmentation model and validate the implementation against the existing sequentially applied model for a specific case of impact loading of a brittle material. This validation case will not fully utilize the benefits of having the model integrated into the finite element code as a material model. Rather, this study will demonstrate consistency between the two fragmentation models to ensure that the success of the sequentially applied model will be duplicated by the integrated two-scale approach. Once validated, further development of the model can be made by utilizing the integration into the finite element code to create a fully two-way coupled fragmentation model that will be extended to include higher fidelity models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multiscale Informatics for Low-Temperature Propane Oxidation: Further Complexities in Studies of Complex Reactions

We have developed a multi-scale approach (Burke, M. P.; Klippenstein, S. J.; Harding, L. B. Proc. Combust. Inst. 2013, 34, 547–555.) to kinetic model formulation that directly incorporates elementary kinetic theories as a means to provide reliable, physics-based extrapolation to unexplored conditions. Here, we extend and generalize the multi-scale modeling strategy to treat systems of considerable complexity – involving multi-well reactions, potentially missing reactions, non-statistical product branching ratios, and non-Boltzmann (i.e. non-thermal) reactant distributions. The methodology is demonstrated here for a subsystem of low-temperature propane oxidation, as a representative system for low-temperature fuel oxidation. A multi-scale model is assembled and informed by a wide variety of targets that include ab initio calculations of molecular properties, rate constant measurements of isolated reactions, and complex systems measurements. Active model parameters are chosen to accommodate both “parametric” and “structural” uncertainties. Theoretical parameters (e.g. barrier heights) are included as active model parameters to account for parametric uncertainties in the theoretical treatment; experimental parameters (e.g. initial temperatures) are included to account for parametric uncertainties in the physical models of the experiments. RMG software is used to assess potential structural uncertainties due to missing reactions. Additionally, branching ratios among product channels are included as active model parameters to account for structural uncertainties related to difficulties in modeling sequences of multiple chemically activated steps. The approach is demonstrated here for interpreting time-resolved measurements of OH, HO2, n-propyl, i-propyl, propene, oxetane, and methyloxirane from photolysis-initiated low-temperature oxidation of propane at pressures from 4 to 60 Torr and temperatures from 300 to 700 K. In particular, the multi-scale informed model provides a consistent quantitative explanation of both ab initio calculations and time-resolved species measurements. The present results show that interpretations of OH measurements are significantly more complicated than previously thought – in addition to barrier heights for key transition states considered previously, OH profiles also depend on additional theoretical parameters for R + O2 reactions, secondary reactions, QOOH + O2 reactions, and treatment of non-Boltzmann reaction sequences. Extraction of physically rigorous information from those measurements may require more sophisticated treatment of all of those model aspects, as well as additional experimental data under more conditions, to discriminate among possible interpretations and ensure model reliability. Keywords: Optimization, Uncertainty quantification, Chemical mechanism, Low-Temperature Oxidation, Non-Boltzmann

Chemical mechanism↗

Tolerance of the Brachial Plexus to High-Dose Reirradiation

Purpose: To study the tolerance of the brachial plexus to high doses of radiation exceeding historically accepted limits by analyzing human subjects treated with reirradiation for recurrent tumors of the head and neck. Methods and Materials: Data from 43 patients who were confirmed to have received overlapping dose to the brachial plexus after review of radiation treatment plans from the initial and reirradiation courses were used to model the tolerance of this normal tissue structure. A standardized instrument for symptoms of neuropathy believed to be related to brachial plexus injury was utilized to screen for toxicity. Cumulative dose was calculated by fusing the initial dose distributions onto the reirradiation plan, thereby creating a composite plan via deformable image registration. The median elapsed time from the initial course of radiation therapy to reirradiation was 24 months (range, 3-144 months). Results: The dominant complaints among patients with symptoms were ipsilateral pain (54%), numbness/tingling (31%), and motor weakness and/or difficulty with manual dexterity (15%). The cumulative maximum dose (Dmax) received by the brachial plexus ranged from 60.5 Gy to 150.1 Gy (median, 95.0 Gy). The cumulative mean (Dmean) dose ranged from 20.2 Gy to 111.5 Gy (median, 63.8 Gy). The 1-year freedom from brachial plexus–related neuropathy was 67% and 86% for subjects with a cumulative Dmax greater than and less than 95.0 Gy, respectively (P=.05). The 1-year complication-free rate was 66% and 87%, for those reirradiated within and after 2 years from the initial course, respectively (P=.06). Conclusion: The development of brachial plexus–related symptoms was less than expected owing to repair kinetics and to the relatively short survival of the subject population. Time-dose factors were demonstrated to be predictive of complications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Probabilistic Risk Assessment of Spent Fuel Pool Cooling System Failure Considering Safety and Security Initiating Events

In order to quantify the probable risk associated with a safety system, nuclear safety risk evaluation process is applied which is generally performed in three steps. The first step is to calculate the damage frequency of a critical system. This step is followed by the radioactive source term estimation due to the potential system damage. The final step is the assessment of off-site consequences. The safety risk formula is shown by Eq. (1). P{sub F} is the probability of safety system failure (the probability used describes a random, independent event), and C is the consequence value. R{sub SAF} = P{sub F} * C (1) The security risk associated with an attack on critical infrastructure and/or special nuclear materials theft is usually evaluated using three- term risk equation (probability of attack, probability of adversary success, and consequence). A security threat and the related initiating events are not considered in a pure safety risk analysis. The vulnerability of the physical protection system is performed independently even though the consequence resulting from a security initiating event can be similar to a safety related initiating event and thus gets double counted. The security risk can be calculated using Eq. (2) R{sub SEC} = P{sub A} * P{sub S} * C (2) PA is the probability of attack, P{sub S} is the probability of adversary success (P{sub S} = 1 - P{sub I} P{sub N}). P{sub I} being the probability of interruption which accounts for the probabilities of detection of all timely detection elements along an adversary path. PN being the probability of neutralization: the result of engagement of the response force with the adversaries after the interruption has occurred. C is the consequence magnitude from a successful attack. The two security probabilities do not describe random, independent events. As a result, because of the differences in the randomness and independence of the respective safety and security probabilities, the safety and the security risks are currently calculated separately. The consequence term in nuclear safety and security risk evaluation have the same definition. An effort is made here to study the effect on the overall risk by considering security initiating events along with the subsequent failure of the intermediate safety element. The target selected is a spent fuel storage pool for analyzing the public risk arising from the interplay between nuclear security and safety initiating events. EASI (Estimate of Adversary Sequence Interruption) model is used to calculate the probability of interruption related to a security system that leads to the calculation of the security initiating event frequency. Further progression of this initiating security event to a top event is analyzed using a Probabilistic Safety Assessment (PSA) tool, SAPHIRE (version 8) to obtain a joint pool damage frequency. For the progression of events leading to a top event, the failure of the intermediate safety elements is assumed to be external random events such as heavy load drop and fire events. The objectives of this study is to (1) determine the double accounting of frequency of failure, risk and allocated resources in the scenario of a non-random security initiating event leading to a safety random event chain (2) compare the damage frequency from pure security with the frequency of combined security-safety failure event and pure safety failure events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Instability saturation by the oscillating two-stream instability in a weakly relativistic plasma

The two-stream instability has wide range of astrophysical applications starting from gamma-ray bursts and pulsar glitches to cosmology. We consider one dimensional weakly relativistic Zakharov equations and describe nonlinear saturation of the oscillating two-stream instability using a three dimensional dynamical system resulting form a truncation of the nonlinear Schrodinger equation to three modes. The equilibrium points of the model are determined and their stability natures are discussed. Using the tools of nonlinear dynamics such as the bifurcation diagram, Poincaré maps, and Lyapunav exponents, existence of periodic, quasi-periodic, and chaotic solutions are established in the dynamical system. Interestingly, we observe the multistable behavior in this plasma model. The system has multiple attractors depending on the initial conditions. We also notice that the relativistic parameter plays the role of control parameter in the model. The theoretical results presented in this paper may be helpful for better understanding of space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems

Given the magnitude of soil carbon stocks in northern ecosystems, and the vulnerability of these stocks to climate warming, land surface models must accurately represent soil carbon dynamics in these regions. We evaluate soil carbon stocks and turnover rates, and the relationship between soil carbon loss with soil temperature and moisture, from an ensemble of eleven global land surface models. We focus on the region of NASA's Arctic-Boreal vulnerability experiment (ABoVE) in North America to inform data collection and model development efforts. Models exhibit an order of magnitude difference in estimates of current total soil carbon stocks, generally under- or overestimating the size of current soil carbon stocks by greater than 50 PgC. We find that a model's soil carbon stock at steady-state in 1901 is the prime driver of its soil carbon stock a hundred years later—overwhelming the effect of environmental forcing factors like climate. The greatest divergence between modeled and observed soil carbon stocks is in regions dominated by peat and permafrost soils, suggesting that models are failing to capture the frozen soil carbon dynamics of permafrost regions. Using a set of functional benchmarks to test the simulated relationship of soil respiration to both soil temperature and moisture, we find that although models capture the observed shape of the soil moisture response of respiration, almost half of the models examined show temperature sensitivities, or Q10 values, that are half of observed. Significantly, models that perform better against observational constraints of respiration or carbon stock size do not necessarily perform well in terms of their functional response to key climatic factors like changing temperature. This suggests that models may be arriving at the right result, but for the wrong reason. The results of this work can help to bridge the gap between data and models by both pointing to the need to constrain initial carbon pool sizes, as well as highlighting the importance of incorporating functional benchmarks into ongoing, mechanistic modeling activities such as those included in ABoVE.

54 ENVIRONMENTAL SCIENCES↗

Role of Sea‐Surface Salinity in Simulating Historical Decadal Variations of Atlantic Meridional Overturning Circulation in a Coupled Climate Model

Abstract Extending climate prediction from seasonal to decadal timescales requires realistic initialization of not only upper ocean heat content but also the Atlantic meridional overturning circulation (AMOC). However, it remains a major challenge to realistically initialize AMOC in a coupled system while also maintaining a balanced atmosphere‐ocean initial state. This study demonstrates the feasibility of generating fully coupled historical states with realistic AMOC variability. Employing a forced ocean—sea‐ice (FOSI) model simulation as the “truth,” we show reproducibility of key features of historical AMOC decadal variability in a fully coupled model by restoring sea‐surface salinity, in addition to sea‐surface temperature restoring widely used in seasonal prediction. The atmospheric state of the restored coupled model solution is much closer to that of the free coupled simulation than to the observations used in FOSI, pointing to potential advantages of using this approach for initializing decadal predictions with reduced ocean initialization shock.

54 ENVIRONMENTAL SCIENCES↗

Anomalies in the topology of the temperature fluctuations in the cosmic microwave background: An analysis of the NPIPE and FFP10 data releases

We present a topological analysis of the temperature fluctuation maps from the Planck 2020 Data Release 4 NPIPE dataset and the Planck 2018 Data Release 3 FFP10 dataset. We performed a multiscale analysis in terms of the homology characteristics of the maps, invoking relative homology to account for the analysis in the presence of masks. We performed our analysis for a range of smoothing scales spanning sub- and super-horizon scales corresponding to a full width at half maximum (FWHM) of 5',10',20',40',80',160',320', and 640', and employed simulations based on the standard model for comparison, which assumes the initial fluctuation field to be an isotropic and homogeneous Gaussian random field. Examining the behavior of topological components, represented by the 0D homology group, we find the observations to be approximately 2σ or less deviant from the simulations for all resolutions and scales for the NPIPE dataset. For the FFP10 dataset, we detect a 2.96σ deviation between the observations and simulations at N = 128, FWHM = 80'. For the topological loops, represented by the first homology group, the simulations and observations are consistent within 2σ for most resolutions and scales for both the datasets. However, for the NPIPE dataset, we observe a high deviation between the observation and simulations in the number of loops at FWHM = 320', but at a low dimensionless threshold ν = –2.5. Under a Gaussian assumption, this would amount to a deviation of ~4σ. However, the distribution in this bin is manifestly non-Gaussian and does not obey Poisson statistics either. In the absence of a true theoretical understanding, we simply note that the significance is higher than what may be resolved by 600 simulations, yielding an empirical p-value of at most 0.0016. Specifically in this case, our tests indicate that the numbers arise from a statistically stable regime, despite being based on small numbers. For the FFP10 dataset, the differences are not as strong as for the NPIPE dataset, indicating a 2.77σ deviation at this resolution and threshold. The Euler characteristic, which is the alternating sum of the ranks of relative homology groups, reflects the deviations in the components and loops. To assess the significance of combined levels for a given scale, we employed the empirical and theoretical versions of the χ 2 test as well as the nonparametric Tukey depth test. Although all statistics exhibit a stable distribution, we favor the empirical version of the χ 2 test in the final interpretation, as it indicates the most conservative differences. For the NPIPE dataset, we find that the components and loops differ at more than 95%, but agree within the 99% confidence level with respect to the base model at N = 32, FWHM = 320'. The Euler characteristic at this resolution displays a per mil deviation. In contrast, the FFP10 dataset shows that the observations are consistent with the base model within the 95% confidence level, at this and smaller scales. This is consistent with the observations of the Planck analysis pipeline via Minkowski functionals. For the largest smoothing scale, N = 16, FWHM = 640', both datasets exhibit an anomalous behavior of the loops, where FFP10 data exhibit a deviation that is larger by an order of magnitude than that of the NPIPE dataset. In contrast, the values for the topological components and the Euler characteristic agree between observations and model to within a confidence level of 99%. However, for the largest scales, the statistics are based on low numbers and may have to be regarded with caution. Even though both datasets exhibit mild to significant discrepancies, they also exhibit contrasting behaviors at various instances. Therefore, we do not find it feasible to convincingly accept or reject the null hypothesis. Disregarding the large-scale anomalies that persist at similar scales in WMAP and Planck, observations of the cosmic microwave background are largely consistent with the standard cosmological model within 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗

A Generic Modeling and Development Approach for WECC Composite Load Model

The composite load model (CLM) proposed by Western Electricity Coordinating Council (WECC) gains increasing traction in the industry, particularly in North America. At the same time, it is recognized that further improvements in the structure, initialization and aggregation methods are needed. However, lack of an open implementation of WECC CLM becomes a roadblock for many researchers to work on improving it. This paper presents the first open reference implementation of WECC CLM. Individual load components and the CLM are first developed and tested in Matlab, then translated to the high performance computing (HPC), parallel simulation platform GridPACK. Main contributions of the paper include: 1) presenting some important yet undocumented details of modeling and initializing the CLM, particularly for a parallel simulation platform like GridPACK; 2) implementation details of the load components such as the single-phase air conditioner motor; 3) implementing the CLM in a modular and extensible manner. The implementation has been tested at both the component as well as system levels and bench-marked against commercial simulation programs.

Huang, Qiuhua↗