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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Extraction of diffuse correlation spectroscopy flow index by integration of Nth-order linear model with Monte Carlo simulation

Conventional semi-infinite solution for extracting blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements may cause errors in estimation of BFI (αD{sub B}) in tissues with small volume and large curvature. We proposed an algorithm integrating Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in tissue for the extraction of αD{sub B}. The volume and geometry of the measured tissue were incorporated in the Monte Carlo simulation, which overcome the semi-infinite restrictions. The algorithm was tested using computer simulations on four tissue models with varied volumes/geometries and applied on an in vivo stroke model of mouse. Computer simulations shows that the high-order (N ≥ 5) linear algorithm was more accurate in extracting αD{sub B} (errors < ±2%) from the noise-free DCS data than the semi-infinite solution (errors: −5.3% to −18.0%) for different tissue models. Although adding random noises to DCS data resulted in αD{sub B} variations, the mean values of errors in extracting αD{sub B} were similar to those reconstructed from the noise-free DCS data. In addition, the errors in extracting the relative changes of αD{sub B} using both linear algorithm and semi-infinite solution were fairly small (errors < ±2.0%) and did not rely on the tissue volume/geometry. The experimental results from the in vivo stroke mice agreed with those in simulations, demonstrating the robustness of the linear algorithm. DCS with the high-order linear algorithm shows the potential for the inter-subject comparison and longitudinal monitoring of absolute BFI in a variety of tissues/organs with different volumes/geometries.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Time managed virtualization for simulating systems of systems

Software is an integral part of almost every non-trivial system. Yet simulation technologies to understand how software affects system performance lag behind what is available to understand physical behavior. This is not surprising. An abstract model of software tells us what it is supposed to do, not what it actually does. In this respect software is very different from a physical system. Kirchhoff’s laws predict the behavior of an electrical circuit with great precision. The mathematics of fluids do an adequate job of anticipating how a wing will perform in flight. Only the software itself, observed in operation, can tell us how it behaves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Waste IPSC : Thermal-Hydrologic-Chemical-Mechanical (THCM) modeling and simulation.

Waste IPSC Objective is to develop an integrated suite of high performance computing capabilities to simulate radionuclide movement through the engineered components and geosphere of a radioactive waste storage or disposal system: (1) with robust thermal-hydrologic-chemical-mechanical (THCM) coupling; (2) for a range of disposal system alternatives (concepts, waste form types, engineered designs, geologic settings); (3) for long time scales and associated large uncertainties; (4) at multiple model fidelities (sub-continuum, high-fidelity continuum, PA); and (5) in accordance with V&V and software quality requirements. THCM Modeling collaborates with: (1) Other Waste IPSC activities: Sub-Continuum Processes (and FMM), Frameworks and Infrastructure (and VU, ECT, and CT); (2) Waste Form Campaign; (3) Used Fuel Disposition (UFD) Campaign; and (4) ASCEM.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model

Realistic representations of sectoral water withdrawals and consumptive demands and their allocation to surface and groundwater sources are important for improving modeling of the integrated water cycle. To inform future model development, in this work we enhance the representation of water management in a regional Earth system (ES) model with a spatially distributed allocation of sectoral water demands simulated by a regional integrated assessment (IA) model to surface and groundwater systems. The integrated modeling framework (IA-ES) is evaluated by analyzing the simulated regulated flow and sectoral supply deficit in major hydrologic regions of the conterminous U.S, which differ from ES studies looking at water storage variations. Decreases in historical supply deficit are used as metrics to evaluate IA-ES model improvement in representating the complex sectoral human activities for assessing future adaptation and mitigation strategies. We also assess the spatial changes in both regulated flow and unmet demands, for irrigation and nonirrigation sectors, resulting from the individual and combined additions of groundwater and return flow modules. Results show that groundwater use has a pronounced regional and sectoral effect by reducing water supply deficit. The effects of sectoral return flow exhibit a clear east-west contrast in the hydrologic patterns, so the return flow component combined with the IA sectoral demands is a major driver for spatial redistribution of water resources and water deficits in the US. Our analysis highlights the need for spatially distributed sectoral representation of water management to capture the regional differences in interbasin redistribution of water resources and deficits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Residual entropy of ices and clathrates from Monte Carlo simulation

We calculated the residual entropy of ices (Ih, Ic, III, V, VI) and clathrates (I, II, H), assuming the same energy of all configurations satisfying the Bernal–Fowler ice rules. The Metropolis Monte Carlo simulations in the range of temperatures from infinity to a size-dependent threshold were followed by the thermodynamic integration. Convergence of the simulation and the finite-size effects were analyzed using the quasichemical approximation and the Debye–Hückel theory applied to the Bjerrum defects. The leading finite-size error terms, ln N/N, 1/N, and for the two-dimensional square ice model also 1/N{sup 3/2}, were used for an extrapolation to the thermodynamic limit. Finally, we discuss the influence of unequal energies of proton configurations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The Relation between Galaxy ISM and Circumgalactic O vi Gas Kinematics Derived from Observations and ΛCDM Simulations

We introduce the first galaxy–O vi absorption kinematic study for 20 absorption systems (EW > 0.1 Å) associated with isolated galaxies (0.15 ≤ z ≤ 0.55) that have accurate redshifts and rotation curves obtained using Keck/ESI. Our sample is split into two azimuthal angle bins: major axis (Φ < 25°) and minor axis (Φ > 33°). O vi absorption along the galaxy major axis is not correlated with galaxy rotation kinematics, with only 1/10 of systems that could be explained with rotation/accretion models. This is in contrast to corotation commonly observed for Mg ii absorption. O vi along the minor axis could be modeled by accelerating outflows, but only for small opening angles, while the majority of the O vi is decelerating. Along both axes, stacked O vi profiles reside at the galaxy systemic velocity with the absorption kinematics spanning the entire dynamical range of their galaxies. The O vi found in AMR cosmological simulations exists within filaments and in halos of ~50 kpc surrounding galaxies. Simulations show that major-axis O vi gas inflows along filaments and decelerates as it approaches the galaxy, while increasing in its level of corotation. Minor-axis outflows in the simulations are effective within 50–75 kpc; beyond that they decelerate and fall back onto the galaxy. While the simulations show clear O vi kinematic signatures, they are not directly comparable to observations. When we compare kinematic signatures integrated through the entire simulated galaxy halo, we find that these signatures are washed out owing to full velocity distribution of O vi throughout the halo. We illustrate that O vi alone does not serve as a useful kinematic indicator of gas accretion, outflows, or star formation and likely best probes the halo virial temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Effects of energetic particle phase space modifications by instabilities on integrated modeling

Tokamak plasmas can feature a large population of energetic particles (EP) from neutral beam injection or fusion reactions. In turn, energetic particles can drive instabilities, which affect the driving EP population leading to a distortion of the original EP distribution function and of quantities that depend on it. The latter include, for example, neutral beam (NB) current drive and plasma heating through EP thermalization. Those effects must be taken into account to enable reliable and quantitative simulations of discharges for present devices as well as predictions for future burning plasmas. Reduced models for EP transport are emerging as an effective tool for long time-scale integrated simulations of tokamak plasmas, possibly including the effects of instabilities on EP dynamics. Available models differ in how EP distribution properties are modified by instabilities, e.g. in terms of gradients in real or phase space. It is therefore crucial to assess to what extent different assumptions in the transport models affect predicted quantities such as EP profile, energy distribution, NB driven current and energy/momentum transfer to the thermal populations. A newly developed kick model, which includes modifications of the EP distribution by instabilities in both real and velocity space, is used in this work to investigate these issues. Coupled to TRANSP simulations, the kick model is used to analyze NB-heated NSTX and DIII-D discharges featuring unstable Alfvén eigenmodes (AEs). Results show that instabilities can strongly affect the EP distribution function, and modifications propagate to macroscopic quantities such as NB-driven current profile and NB power transferred to the thermal plasma species. Furthermore, those important aspects are only qualitatively captured by simpler fast ion transport models that are based on radial diffusion of energetic ions only.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Advanced EMT and Phasor-Domain Hybrid Simulation With Simulation Mode Switching Capability for Transmission and Distribution Systems

Conventional electromagnetic transient (EMT) and phasor do-main hybrid simulation approaches presently exist for transmission system level studies and their simulation efficiency is generally constrained by the EMT simulation. With an increasing number of distributed energy resources and non-conventional loads being installed in the distribution systems, it is imperative to ex-tend the hybrid simulation application to include distribution systems and integrated transmission and distribution systems. Meanwhile, it is equally important to improve the simulation efficiency as the modeling scope and complexity of the detailed system in the EMT simulation increases. To meet both requirements, this paper introduces an advanced electromagnetic transient (EMT) and phasor domain hybrid simulation approach. This approach has two outstanding features: 1) a comprehensive phasor domain modeling framework which supports positive-sequence, three-sequence, three-phase and mixed three-sequence/three-phase representations; 2) a robust and flexible simulation mode switching scheme which enables simulation switching from hybrid simulation mode back to pure phasor domain dynamic simulation mode to achieve significantly improved simulation efficiency. The proposed method has been tested on integrated transmission and distribution systems, and the results show that with the developed simulation switching feature, the total computational time is significantly reduced compared to running the hybrid simulation for the whole simulation period, while good accuracy is maintained.

Huang, Qiuhua (ORCID:0000000184577429)↗
DOE OSTI2015

Multirate Particle-in-Cell Time Integration Techniques of Vlasov-Maxwell Equations for Collisionless Kinetic Plasma Simulations

A multi-rate PIC formulation was developed that employs large timesteps for slow field evolution, and small (adaptive) timesteps for particle orbit integrations. Implementation is based on a JFNK solver with nonlinear elimination and moment preconditioning. The approach is free of numerical instabilities (ω pe Δt >>1, and Δx >> λ D ), and requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant gains (vs. conventional explicit PIC) may be possible for large scale simulations. The paper is organized as follows: Vlasov-Maxwell Particle-in-cell (PIC) methods for plasmas; Explicit, semi-implicit, and implicit time integrations; Implicit PIC formulation (Jacobian-Free Newton-Krylov (JFNK) with nonlinear elimination allows different treatments of disparate scales, discrete conservation properties (energy, charge, canonical momentum, etc.)); Some numerical examples; and Summary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Turbulence-Resolving Simulations of Hurricane Laura (2020): Insights Into Extreme Winds and Eyewall Turbulence

Extreme weather events pose significant risks to coastal and offshore energy infrastructure. In this work, we investigate the structure of mean winds and turbulence near the surface ( z < 300 m) that occurred during Hurricane Laura in 2020 on the US Gulf Coast. To this end, we perform turbulence-resolving simulations (..delta..x = 33.33 m) that encompass the entire eyewall of Hurricane Laura by introducing a novel method that we will refer to as Moving-Mesoscale to Static-LES Integrated Coupling (MOSAIC). The simulation results are validated against surface, boundary-layer, and mid-tropospheric observations. Our analysis of the extreme wind conditions near the surface indicates that the mean wind and turbulence profiles vary greatly at and near the eyewall, resulting in extreme values of mean wind speed (U > 50 m * s-1) and turbulence kinetic energy (k ~ 50 m2 * s-2) at altitudes above 50 m . To investigate in detail the nature of turbulence within the eyewall of the storm, we conduct higher-resolution simulations (..delta..x = 11.11 m) of a portion of the hurricane. We provide a comprehensive statistical description of turbulence in the eyewall region, highlighting the need to employ ..delta..x ~ 10 m grid spacing to capture the integral length-scales near the surface, second- and higher-order central moments (i.e., skewness and kurtosis), and spectral coherence in the flow accurately. These numerical simulations provide the most detailed description of mean winds and turbulent conditions within the eyewall of a historical tropical cyclone to date, illustrating how high-resolution simulations can enhance limited turbulence measurements in hurricanes and giving insight into the extreme conditions threatening offshore and coastal infrastructure.

17 WIND ENERGY↗
DOE OSTI2021

Integrating static PRA information with risk informed safety margin characterization (RISMC) simulation methods

The overall objective of the project was to develop a computationally feasible and user-friendly mechanized process to integrate traditional probabilistic risk assessment (PRA) and dynamic PRA (DPRA) results. Starting with the systematic identification of items in an existing PRA that need dynamic augmentation, the project used a generic 4-loop pressurized reactor (PWR) and 3-loop PWR as example plants. Station blackout (SBO) and large break loss of coolant accident SBLOCA) were selected as the example initiating events. Using the traditional event-tree (ET)/fault-tree (FT) methodology augmented by dynamic evet tree approach, the potential consequences of the initiating events were simulated with RELAP-3D and MELCOR/RASCAL codes to cover Level 1 through Level 3 of PRA. RAVEN and ADAPT software were used to generate Level 1 simulations with RELAP-3D and Level 2/3 simulations with MELCOR (Level 2)/RASCAL (Level 3), respectively. Example branching conditions (BCs) for SBO included AC power recovery time, valve repair failure time, reactor coolant pump leak time/break size and emergency power supply duration to a total of 9. Example BCs for LOCA included off-site power recovery time, diesel generator power recovery time, auxiliary feed water system operation time, safety relief valve failure to open upon demand, reactor coolant pump seal break time and size to a total of 21. Each RELAP-3D simulation (9,587 scenarios) was labelled OK or Core Damage based on the maximum allowed peak clad temperature (2,100oF). Each MELCOR simulation (4610 scenarios) was labeled as Bin over 10rem or Bin 0-10rem based on the dose at the site boundary. The scenarios were clustered based on the criteria above using the mean shift methodology. Classical PRA (CPRA) and DPRA results were compared to identify the ET sequences that need DPRA augmentation. Several approaches were proposed for the incorporation of these sequences into CPRA using clustering with the mean shift methodology, restructuring the CPRA ETs by adding new BCs/sequences, and using the concept of a limit surface. Procedures for decision making regarding the possible consequences of an initiating event (e.g. core damage or not, site evacuation or not) were developed using a convolutional neural network (CNN), a recurrent neural network (RNN) and a transformer neural network (TNN). The project has led to two PhD degrees, three archival journal papers and five refereed conference proceedings.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Geant4 Event Biasing and Fast Simulation

Geant4 offers advanced event biasing techniques to significantly accelerate simulations involving rare events. Various biasing methods, such as leading particle selection, cross-section biasing, radioactive decay enhancement, and bremsstrahlung splitting, enable efficient event sampling, though they require careful handling. Additionally, Geant4 provides a Fast Simulation Interface, allowing the replacement of standard processes in specific region and for selected particles, enabling faster execution or external code integration. Applications of fast simulation include electromagnetic shower modeling in calorimeters, machine learning inference, and offloading tasks to specialized hardware like GPUs, making Geant4 a powerful tool for computationally demanding simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

Data-intensive management and analysis for scientifc simulations.

Scientific simulations can produce enormous amounts of data, making the analysis of results and management of files a difficult task for scientists. The simulation management and analysis system (Smaash) described here is designed to allow scientists to easily capture, store, organize, monitor, and analyze simulation results. The system is automatic, standardized, and secure. Smaash was built using open-source tools and modularized to be independent of the scientific simulation. The web-based front-end allows the scientist to easily interact with the data, and has proved its usefulness in improving the efficiency of a scientific team's workflow. High performance parallel computing allows scientists to solve complex physical problems through computer simulation. However, the massive amounts of data generated and the complex computing environment can create additional complications. A recent review by Ludaescher et al.(2009) describes how scientific workflows can assist scientists in extracting knowledge from these data-intensive operations by automating components within pipelines. Within the fusion community, Klasky et al.(2008) and colleagues have developed a system that handles the storage management, data movement, metadata generation and management, and a means to analyze the results. In response to scientists needs, a simulation management and analysis system (Smaash) was developed at the University of Chicago and Argonne National Laboratory (USA). Smaash provides an integrated way to monitor simulations and analyze computational results; catalog, store, and retrieve simulations; and prepare output for publications. The system is independent of the particular simulation code, accessible from many HPC and browser-based platforms, and built around open-source software tools. Data security and provenance is considered throughout. The analysis components are hidden behind a web-based front end, enabling scientists to focus on their results and not get bogged down by information overload.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

Fusion Simulation Program Execution Plan

The overall science goal of the FSP is to develop predictive simulation capability for magnetically confined fusion plasmas at an unprecedented level of integration and fidelity. This will directly support and enable effective U.S. participation in research related to the International Thermonuclear Experimental Reactor (ITER) and the overall mission of delivering practical fusion energy. The FSP will address a rich set of scientific issues together with experimental programs, producing validated integrated physics results. This is very well aligned with the mission of the ITER Organization to coordinate with its members the integrated modeling and control of fusion plasmas, including benchmarking and validation activities. Initial FSP research will focus on two critical areas: 1) the plasma edge and 2) whole device modeling including disruption avoidance. The first of these problems involves the narrow plasma boundary layer and its complex interactions with the plasma core and the surrounding material wall. The second requires development of a computationally tractable, but comprehensive model that describes all equilibrium and dynamic processes at a sufficient level of detail to provide useful prediction of the temporal evolution of fusion plasma experiments. The initial driver for the whole device model (WDM) will be prediction and avoidance of discharge-terminating disruptions, especially at high performance, which are a critical impediment to successful operation of machines like ITER. If disruptions prove unable to be avoided, their associated dynamics and effects will be addressed in the next phase of the FSP. The FSP plan targets the needed modeling capabilities by developing Integrated Science Applications (ISAs) specific to their needs. The Pedestal-Boundary model will include boundary magnetic topology, cross-field transport of multi-species plasmas, parallel plasma transport, neutral transport, atomic physics and interactions with the plasma wall. It will address the origins and structure of the plasma electric field, rotation, the L-H transition, and the wide variety of pedestal relaxation mechanisms. The Whole Device Model will predict the entire discharge evolution given external actuators (i.e., magnets, power supplies, heating, current drive and fueling systems) and control strategies. Based on components operating over a range of physics fidelity, the WDM will model the plasma equilibrium, plasma sources, profile evolution, linear stability and nonlinear evolution toward a disruption (but not the full disruption dynamics). The plan assumes that, as the FSP matures and demonstrates success, the program will evolve and grow, enabling additional science problems to be addressed. The next set of integration opportunities could include: 1) Simulation of disruption dynamics and their effects; 2) Prediction of core profile including 3D effects, mesoscale dynamics and integration with the edge plasma; 3) Computation of non-thermal particle distributions, self-consistent with fusion, radio frequency (RF) and neutral beam injection (NBI) sources, magnetohydrodynamics (MHD) and short-wavelength turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Improving the Performance of Integrated Power-Hardware-in-the-Loop and Quasi-Static Time-Series Simulations

This paper introduces a novel multirate cosimulation architecture that overcomes previous challenges integrating faster real-time, microseconds-scale, power-hardware-in-the-loop (PHIL) with larger scale but slower, real-time, seconds-scale, quasi-static time-series (QSTS) simulation. Specifically, an intermediate reduced-equivalent electromagnetic transient (EMT) model duplicates the key power system topology to capture high-speed dynamics and converge hardware-power system interactions between QSTS updates. Exchanging multidimensional parameter vectors (loads, control status, etc.) between the QSTS and EMT models enables capturing the interactions of the rich, high-node-count (thousands of electrical nodes) QSTS model with the hardware. This architecture offers full spatial resolution from QSTS, including individual load dynamics, actual distribution management system controls, and nodal voltages. Simultaneously, the intermediate EMT model provides more detailed high-speed transients of key distributed energy resource hardware interactions. In addition, we use careful PHIL interface design and the exchange of complex power data, rather than current, to further improve performance. This cosimulation architecture is demonstrated by testing a simulated distribution system with an interconnected 500-kVA advanced photovoltaic (PV) inverter in PHIL. In conclusion, the architecture successfully captured PV local volt-volt ampere reactive (volt-VAR) control interactions with the larger network under time-varying electrical and weather conditions.

42 ENGINEERING↗
DOE OSTI2017

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomes of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.

54 ENVIRONMENTAL SCIENCES↗