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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35

Model predictive control for matrix converter operating in current control mode with load current estimation

A matrix converter system operating in current control mode is provided. The matrix converter includes a switching matrix coupled between a low voltage side and a high voltage side, wherein the matrix converter is coupled at its low voltage side to a generator for receiving an input power including an input current and transforming the input power into an output power at its high voltage side, wherein a load is coupled to the high voltage side. The control system includes a load observer and a model predictive controller (MPC). The load observer is configured to estimate a load current that flows to the load from the high voltage side of the matrix converter as a function of a switching state of the switching matrix, an output voltage output at the high voltage side of the matrix converter, and the input current. The MPC is configured to select the switching state of the switching matrix to meet one or more control objectives defined by minimization of a multi-objective function that tracks the output voltage and the input current using the estimated load current.

24 POWER TRANSMISSION AND DISTRIBUTION↗

235 U(n, f) Independent fission product yield and isomeric ratio calculated with the statistical Hauser–Feshbach theory

In this work, we have developed a Hauser–Feshbach fission fragment decay model, HF 3 D, which can be applied to the statistical decay of more than 500 primary fission fragment pairs (1,000 nuclides) produced by the neutron induced fission of 235 U. The HF 3 D model numerically integrates fission fragment yield and their initial excitation energy, spin and parity distributions for these 1,000 nuclides. The fission fragment yield Y ( A ) and the total kinetic energy are model inputs, and we estimate them from available experimental data for the 235 U(n th ,f) system. The model parameters in the statistical decay calculation are adjusted to reproduce some fission observables, such as the neutron emission multiplicity v - , its distribution P ( ν ), and the mass dependence v - ( A ). The calculated fission product yield (FPY) and isomeric ratio (IR) are compared with experimental data. The calculated independent FPY Y I ( A ) at the thermal energy reproduces the experimental data well, while the calculated IRs tend to be lower than the Madland–England model prediction. The HF 3 D model is extended to higher incident neutron energies up to the second-chance fission threshold. We demonstrate for the first time that most of the IRs stay constant, although the production of isomeric state changes as the incident energy increases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is −4.6 +/- 1.5 W/sq m for cloud-free and −2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

Globalsatellite measurements↗

Nonlocal hyperconcentration on entangled photons using photonic module system

Entanglement distribution will inevitably be affected by the channel and environment noise. Thus distillation of maximal entanglement nonlocally becomes a crucial goal in quantum information. Here we illustrate that maximal hyperentanglement on nonlocal photons could be distilled using the photonic module and cavity quantum electrodynamics, where the photons are simultaneously entangled in polarization and spatial-mode degrees of freedom. The construction of the photonic module in a photonic band-gap structure is presented, and the operation of the module is utilized to implement the photonic nondestructive parity checks on the two degrees of freedom. We first propose a hyperconcentration protocol using two identical partially hyperentangled initial states with unknown coefficients to distill a maximally hyperentangled state probabilistically, and further propose a protocol by the assistance of an ancillary single photon prepared according to the known coefficients of the initial state. In the two protocols, the total success probability can be improved greatly by introducing the iteration mechanism, and only one of the remote parties is required to perform the parity checks in each round of iteration. Estimates on the system requirements and recent experimental results indicate that our proposal is realizable with existing or near-further technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Introducing the SLICE Method for estimating pebble-bed reactor inventories at equilibrium operation with SCALE

This paper introduces the SCALE Leap-In method for Cores at Equilibrium (SLICE) for estimating pebble-bed reactor equilibrium core isotopic inventories using capabilities in the SCALE code system, requiring only a small computational cluster and a few days of computation. This method uses an iterative approach that relies on (1) a surrogate spectrum model that captures spatial and time-dependent spectral conditions, (2) a multi-pass model that captures the pebble’s evolving nuclide inventory as a function of location and time in the core, and (3) a full-core model that captures the core’s spatial neutron flux distribution. The SLICE approach is applied to a generic fluoride salt–cooled high-temperature reactor, demonstrating fuel inventory convergence through nuclide concentration inspection across iterations and comparisons for core realizations with varying discretizations. Results agree within ~5% with another state-of-the-art code, with differences attributed to input parameter or modeling assumption variations in the equilibrium generation methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

IDC Reengineering Phase 2 Project Scope

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) operates the International Data Centre (IDC) to support treaty verification activities by Member States. The IDC collects, stores, processes, and distributes data from seismic, hydroacoustic, infrasound, and radionuclide stations. A significant component of the IDC is the seismic, hydroacoustic, and infrasound (SHI) processing system. The IDC has recognized the need to reengineer the SHI processing system and has defined a three-phase reengineering effort. IDC Reengineering Phase 1 (RP1) started in 2011 with the goal to significantly modernize SHI automatic and interactive data processing software, focusing on enhancements to individual components of the system. Reengineering Phase 2 (RP2), started in 2014, addresses the task of specifying a unified architecture for all SHI software, across processing stages, to pave the way for further software development and sustainment in the future. A key objective of RP2 is an architecture sufficient to provide a basis for a cost estimate for the development or enhancement of the software components and subsystems. This report provides a brief description of the scope of the IDC Reengineering Phase 2 project. It describes the goals and objectives of reengineering, the system definition, and the technical scope of the system.This report expands upon the “Scope for IDC Reengineering Phase 2”, July 2014, ECS-DIS-WGB-43-PTS-MATERIAL-12-ADD-1, produced by the IDC.

58 GEOSCIENCES↗

Using probabilistic analysis to assess the reliability of predicted SRB aft-skirt stresses

Probabilistic failure analysis is a tool to predict the reliability of a part or system. Probabalistic techniques were used to predict critical stresses which occur in the solid rocket booster aft-skirt during main engine buildup, immediately prior to lift-off. More than any other hold down post (HDP) load component, the Z loads are sensitive to variations in strains and calibration constants. Also, predicted aft-skirt stresses are strongly affected by HDP load variations. Therefore, the instrumented HDP are not effective load transducers for Z loads, and, when used with aft skirt stress indicator equations, yield estimates with large uncertainty. Monte Carlo simulation proved to be a straight forward way of studying the overlapping effects of multiple parameters on predicted equipment performance. An advantage of probabilistic analysis is the degree of uncertainty of each parameter as stated explicitly by its probability distribution. It was noted, however, that the choice of parameter distribution had a large effect on the simulation results. Many times these distributions must be assumed. The engineer who is designing the part should be responsible for the choice of parameter distribution.

Richardson, James A.↗

ARMAX-Based Transfer Function Model Identification Using Wide-Area Measurement for Adaptive and Coordinated Damping Control

One of the main drawbacks of the existing oscillation damping controllers that are designed based on offline dynamic models is adaptivity to the power system operating condition. With the increasing availability of wide-area measurements and the rapid development of system identification techniques, it is possible to identify a measurement-based transfer function model online that can be used to tune the oscillation damping controller. Such a model could capture all dominant oscillation modes for adaptive and coordinated oscillation damping control. our paper describes a comprehensive approach to identify a low-order transfer function model of a power system using a multi-input multi-output (MIMO) autoregressive moving average exogenous (ARMAX) model. This methodology consists of five steps: 1) input selection; 2) output selection; 3) identification trigger; 4) model estimation; and 5) model validation. The proposed method is validated by using ambient data and ring-down data in the 16-machine 68-bus Northeast Power Coordinating Council system. Our results demonstrate that the measurement-based model using MIMO ARMAX can capture all the dominant oscillation modes. Compared with the MIMO subspace state space model, the MIMO ARMAX model has equivalent accuracy but lower order and improved computational efficiency. The proposed model can be applied for adaptive and coordinated oscillation damping control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identification of the threshold security applied for fuel under reactivity-initiated conditions by self-organizing maps and neural networks - 14386

In recent times, we have 439 reactors distributed in 31 countries that give about 377 GW, covering around 12% of world capacity of energy. Currently, it accounts for an estimated 40 serious accidents reported in nuclear power plants. In this article, turns out the behavior of fuel rod in light-water reactors under accident conditions. Besides, we investigate deeply about reactivity-initiated accidents, by introducing Nordheim-Fuchs model as state equations. The early research showed that pre-irradiated fuels and afterward subjected to a rapid pulse of energy. It adopts the key items necessary to check the threshold of failure. These items are few limits as burning the fuel; the value applied to the peak of energy, pulse width, oxidation layer, and cladding. The kinetic equations of nuclear reactors modeled as a non-linear system. In this way, it can apply the paradigm of artificial intelligence using the self-organized maps. Where the goal is to find the cluster of failure for irradiated fuels until 75 GWd/MTU. The second model based on statistical is the logistic regression theory. Hence, the tests carried out and compared against the results found by neural networks for classification of clusters. It proofs that both approaches present capacity to find the flaws accurately of about 80% of cases. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improving Public Health DSSs by Including Saharan Dust Forecasts Through Incorporation of NASA's GOCART Model Results

Approximately 2-3 billion metric tons of soil dust are estimated to be transported in the Earth's atmosphere each year. Global transport of desert dust is believed to play an important role in many geochemical, climatological, and environmental processes. This dust carries minerals and nutrients, but it has also been shown to carry pollutants and viable microorganisms capable of harming human, animal, plant, and ecosystem health. Saharan dust, which impacts the eastern United States (especially Florida and the southeast) and U.S. Territories in the Caribbean primarily during the summer months, has been linked to increases in respiratory illnesses in this region and has been shown to carry other human, animal, and plant pathogens. For these reasons, this candidate solution recommends integrating Saharan dust distribution and concentration forecasts from the NASA GOCART global dust cycle model into a public health DSS (decision support system), such as the CDC's (Centers for Disease Control and Prevention's) EPHTN (Environmental Public Health Tracking Network), for the eastern United States and Caribbean for early warning purposes regarding potential increases in respiratory illnesses or asthma attacks, potential disease outbreaks, or bioterrorism. This candidate solution pertains to the Public Health National Application but also has direct connections to Air Quality and Homeland Security. In addition, the GOCART model currently uses the NASA MODIS aerosol product as an input and uses meteorological forecasts from the NASA GEOS-DAS (Goddard Earth Observing System Data Assimilation System) GEOS-4 AGCM. In the future, VIIRS aerosol products and perhaps CALIOP aerosol products could be assimilated into the GOCART model to improve the results.

Berglund, Judith↗

A Review of Value of Solar Studies In Theory and In Practice

This brief summarizes a collection of state- and utility-commissioned value-of-solar (VoS) studies and related literature, with a focus on who commissioned the study, which value and cost categories were discussed and/or quantified, and the methods used. Our objective is to compile information on prior VoS studies to inform state regulators and other stakeholders that may pursue related studies or integrate findings into rate design. The brief is organized into three parts: 1) an introduction to distributed solar photovoltaic (DPV) compensation; 2) a review of theoretical research on VoS; and 3) a review of VoS studies. The vast majority of VoS studies have served an informational role of quantifying the net benefits of PV. Three studies were commissioned in states or utility service territories that subsequently implemented VoS tariffs in California, New York, and Austin, Texas. When applied as a tariff, VoS aims to compensate PV output as efficiently as possible by doing so at rates that reflect the marginal benefits and costs of PV through value and cost categories that may vary temporally and/or geographically. This could lead to higher compensation in locations and times where more PV output is more valuable and consequently drive adoption in those locations to provide more societal benefits. Value and cost factors can be broadly grouped into five categories: generation, transmission, distribution, other utility, and other social categories. Those conducting VoS studies must weigh various tradeoffs when deciding which categories to include and quantify. Tradeoffs include prioritizing values based on their magnitude of value or cost impact, as well as taking into account the feasibility of data collection and accurate quantification. Values of higher magnitude and estimation feasibility are quantified in the majority of studies, including the earliest of studies conducted in the 2000s and 2010s. Additionally, some values of higher magnitude but low feasibility in the earliest of studies have become quantifiable in recent years. There are some values with low average system-wide levels but very high magnitude in specific locations or hours. The value magnitude in some cases can be tied to DPV penetration with low value in areas with little congestion and/or low penetration and vice versa. In these cases, values that are easier to quantify are often incorporated, while those that are more difficult are often addressed via a placeholder value. The placeholder value is paired with a discussion around data needs and methods to improve future estimates, as well as a conversation about when these value categories may increase in magnitude and necessitate more rigorous quantification. This brief summarizes findings from two meta-analyses of VoS studies that took place between 2005 and 2018, as well as findings from four additional studies published from 2018 to 2023. Table ES-1 summarizes the various value and cost categories included in each respective study and whether they were quantified, discussed, or omitted. Values such as avoided energy, capacity, transmission capacity, line losses, and avoided environmental costs are quantified in every study. Some categories were deemed harder to quantify and less impactful at the time of the study, so they were discussed but not quantified (e.g., ancillary services). Other categories, including many at the distribution level, were very locationally and/or temporally specific and dependent on high DPV penetration. These were sometimes quantified and at other times discussed. Notably, when it came to utility costs, integration costs were discussed in all cases, though they were deemed to have a small impact. Other utility costs were omitted for the most part; however, the utility-commissioned study (by NorthWestern Energy in Montana) included both lost utility revenue and programmatic/administrative cost categories. While there are some similarities across studies, each had fairly unique methods that are detailed in the body of this brief.

14 SOLAR ENERGY↗

Experimental Investigation of Two-Phase Flow in Consolidating and Intact Salt: Analysis of Capillary Pressure Measurements from Core Labs

Two-phase flow of brine and air through very low permeability porous media is the dominant fluid flow state in and around geologic repositories for nuclear waste disposal. Constitutive models developed for other subsurface media (shale, sandstone, limestone, etc.) have been adopted but never experimentally parameterized for geologic salt. This report summarizes results of scoping capillary pressure and brine saturation measurements on reconsolidated run-of-mine salt and intact geologic salt samples. These measurements were obtained using mercury injection tests and yielded values of threshold pressure, pore-size distribution, and mercury saturation. The brine capillary pressure curve was then inferred from the raw mercury capillary pressure data. This report also summarizes estimates of the constitutive model parameters from the brine saturation and capillary pressure data (Brooks and Corey, 1964; van Genuchten, 1980). The results suggests that the model of van Genuchten (1980) is better suited for brine-air-salt systems. Additional testing is needed for the low brine saturation range of the capillary pressure curve where the present suite of tests did not yield sufficient data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions

In high energy density physics (HEDP) and inertial confinement fusion (ICF), predictive modeling is complicated by uncertainty in parameters that characterize various aspects of the modeled system, such as those characterizing material properties, equation of state (EOS), opacities, and initial conditions. Typically, however, these parameters are not directly observable. What is observed instead is a time sequence of radiographic projections using X-rays. In this work, we define a set of sparse hydrodynamic features derived from the outgoing shock profile and outer material edge, which can be obtained from radiographic measurements, to directly infer such parameters. Our machine learning (ML)-based methodology involves a pipeline of two architectures, a radiograph-to-features network (R2FNet) and a features-to-parameters network (F2PNet), that are trained independently and later combined to approximate a posterior distribution for the parameters from radiographs. We show that the machine learning architectures are able to accurately infer initial conditions and EOS parameters, and that the estimated parameters can be used in a hydrodynamics code to obtain density fields, shocks, and material interfaces that satisfy thermodynamic and hydrodynamic consistency. Finally, we demonstrate that features resulting from an unknown EOS model can be successfully mapped onto parameters of a chosen analytical EOS model, implying that network predictions are learning physics, with a degree of invariance to the underlying choice of EOS model. To the best of our knowledge, our framework is the first demonstration of recovering both thermodynamic and hydrodynamic consistent density fields from noisy radiographs.

97 MATHEMATICS AND COMPUTING↗

Equiatomic quaternary Heusler alloys: A material perspective for spintronic applications

Half-metallic ferromagnetic (HMF) materials show high spin polarization and are therefore interesting to researchers due to their possible applications in spintronic devices. In these materials, while one spin sub band has a finite density of states at the Fermi level, the other sub band has a gap. Because of their high Curie temperature (T{sub C}) and tunable electronic structure, HMF Heusler alloys have a special importance among the HMF materials. Full Heusler alloys with the stoichiometric composition X{sub 2}YZ (where X and Y are the transition metals and Z is a sp element) have the cubic L2{sub 1} structure with four interpenetrating fcc sublattices. When each of these four fcc sublattices is occupied by different atoms (XX′YZ), a quaternary Heusler structure with different structural symmetries (space group F-43m, #216) is obtained. Recently, these equiatomic quaternary Heusler alloys (EQHAs) with 1:1:1:1 stoichiometry have attracted a lot of attention due to their superior magnetic and transport properties. A special class of HMF materials identified recently is known as spin gapless semiconductors (SGS). The difference in this case, compared with HMFs, is that the density of states for one spin band is just zero at the Fermi level, while the other has a gap as in the case of HMFs. Some of the reported SGS materials belong to EQHAs family. This review is dedicated to almost all reported materials belonging to EQHAs family. The electronic structure and hence the physical properties of Heusler alloys strongly depend on the degree of structural order and distribution of the atoms in the crystal lattice. A variety of experimental techniques has been used to probe the structural parameters and degree of order in these alloys. Their magnetic properties have been investigated using the conventional methods, while the spin polarization has been probed by point contact Andreev reflection technique. The experimentally obtained values of saturation magnetization are found to be in agreement with those estimated using the Slater-Pauling rule in most of the cases. Electrical resistivity and Hall measurements are being used to distinguish between SGS and HMF nature in detail. The current spin polarization value, P = 0.70 ± 0.01, for CoFeMnGe is found to be highest among the EQHAs. CoFeMnSi and CoFeCrGa are found to show SGS behavior with high Curie temperatures, thus making them suitable substitutes for diluted magnetic semiconductors. CoRuFeSi is found to have the highest T{sub C} among EQHAs. Theoretical prediction of magnetic properties on the basis of electronic structure calculations has also been reported in a few systems, which are also discussed in this review. Thus, this review presents a consolidated picture of the magnetic and spintronic properties of this important, but relatively new class of Heusler alloys. It is expected that this will stimulate further interest in these alloys, thereby paving the way for the identification of more HMF and SGS materials. As a result of this, it is expected that more efficient spintronic devices using these alloys would emerge in the near future.

36 MATERIALS SCIENCE↗

Updating PV and Battery Bill Savings Calculations for Net Billing: New Best Practices for Input Data and Uncertainty

Jurisdictions are increasingly adopting compensation structures for distributed PV and PV-battery systems that price exported energy lower than energy consumed onsite (net billing rates). Standard methods for calculating the bill savings from PV and PV-battery systems were developed for net metering structures, and applying these same methods to net billing structures (such as using Typical Meteorological Year weather with actual year load) introduces bias errors that underestimate PV-battery system bill savings by between 1.5\% and 9\%, depending on the utility rate. We assess the magnitude of these errors and compare them to other sources of uncertainty when estimating the bill savings from PV and PV-battery systems under more complex utility rates.

14 SOLAR ENERGY↗

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗

A biokinetic model for trivalent or hexavalent chromium in adult humans

Chromium exists in several oxidation states, with the trivalent state (Cr(III)) being the dominant naturally occurring form. Chromium in other oxidation states tends to be converted to the trivalent oxide in the natural environment and in biological systems. Chromium(III) has been shown to be an essential nutrient for humans and several non-human species. Chromium(VI), the second most stable form of chromium, is an important environmental contaminant that is mostly of industrial origin and is associated with lung cancer and nose tumours in chromium workers. This paper proposes a biokinetic model for chromium that addresses the distinctive behaviours of Cr(III) and Cr(VI) following uptake to blood of an adult human. Additionally, the model is based on biokinetic data derived from relatively short-term studies involving administration of chromium tracers to adult human subjects or laboratory animals, supplemented with data on the long-term distribution of chromium in adult humans as estimated from autopsy measurements. The model is part of a comprehensive update of biokinetic models of the International Commission on Radiological Protection, used to project or evaluate radiation doses from occupational intake of radionuclides.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation data for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.

Active-layer thickness↗