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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Discrete Fracture Network Modeling and Simulation of Subsurface Transport for the Topopah Springs and Lava Flow Aquifers at Pahute Mesa, FY 15 Progress Report

This progress report for fiscal year 2015 (FY15) describes the development of discrete fracture network (DFN) models for Pahute Mesa. DFN models will be used to upscale parameters for simulations of subsurface flow and transport in fractured media in Pahute Mesa. The research focuses on modeling of groundwater flow and contaminant transport using DFNs generated according to fracture characteristics observed in the Topopah Spring Aquifer (TSA) and the Lava Flow Aquifer (LFA). This work will improve the representation of radionuclide transport processes in large-scale, regulatory-focused models with a view to reduce pessimistic bounding approximations and provide more realistic contaminant boundary calculations that can be used to describe the future extent of contaminated groundwater. Our goal is to refine a modeling approach that can translate parameters to larger-scale models that account for local-scale flow and transport processes, which tend to attenuate migration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Automated model generation and parameter estimation of building energy models using an ontology-based framework

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower to more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Effect of Terrestrial and Marine Organic Aerosol on Regional and Global Climate: Model Development, Application, and Verification with Satellite Data

In this DOE project the improvements to parameterization of marine primary organic matter (POM) emissions, hygroscopic properties of marine POM, marine isoprene derived secondary organic aerosol (SOA) emissions, surfactant effects, new cloud droplet activation parameterization have been implemented into Community Atmosphere Model (CAM 5.0), with a seven mode aerosol module from the Pacific Northwest National Laboratory (PNNL)'s Modal Aerosol Model (MAM7). The effects of marine aerosols derived from sea spray and ocean emitted biogenic volatile organic compounds (BVOCs) on microphysical properties of clouds were explored by conducting 10 year CAM5.0-MAM7 model simulations at a grid resolution 1.9° by 2.5° with 30 vertical layers. Model-predicted relationship between ocean physical and biological systems and the abundance of CCN in remote marine atmosphere was compared to data from the A-Train satellites (MODIS, CALIPSO, AMSR-E). Model simulations show that on average, primary and secondary organic aerosol emissions from the ocean can yield up to 20% increase in Cloud Condensation Nuclei (CCN) at 0.2% Supersaturation, and up to 5% increases in droplet number concentration of global maritime shallow clouds. Marine organics were treated as internally or externally mixed with sea salt. Changes associated with cloud properties reduced (absolute value) the model-predicted short wave cloud forcing from -1.35 Wm -2 to -0.25 Wm -2 . By using different emission scenarios, and droplet activation parameterizations, this study suggests that addition of marine primary aerosols and biologically generated reactive gases makes an important difference in radiative forcing assessments. All baseline and sensitivity simulations for 2001 and 2050 using global-through-urban WRF/Chem (GU-WRF) were completed. The main objective of these simulations was to evaluate the capability of GU-WRF for an accurate representation of the global atmosphere by exploring the most accurate configuration of physics options in GWRF for global scale modeling in 2001 at a horizontal grid resolution of 1° x 1°. GU-WRF model output was evaluated using observational datasets from a variety of sources including surface based observations (NCDC and BSRN), model reanalysis (NCEP/ NCAR Reanalysis and CMAP), and remotely-sensed data (TRMM) to evaluate the ability of GU-WRF to simulate atmospheric variables at the surface as well as aloft. Explicit treatment of nanoparticles produced from new particle formation in GU-WRF/Chem-MADRID was achieved by expanding particle size sections from 8 to 12 to cover particles with the size range of 1.16 nm to 11.6m. Simulations with two different nucleation parameterizations were conducted for August 2002 over a global domain at a 4º by 5º horizontal resolution. The results are evaluated against field measurement data from the 2002 Aerosol Nucleation and Real Time Characterization Experiment (ANARChE) in Atlanta, Georgia, as well as satellite and reanalysis data. We have also explored the relationship between clean marine aerosol optical properties and ocean surface wind speed using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E) on board the AQUA satellite. Detailed data analyses were carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to April 2011. We show that for very low (less than 4 m s -1 ) and very high (more than 12 m s -1 ) wind speed conditions the mean CALIPSO-derived aerosol optical depth (AOD) has little dependency on the surface wind speed. For an intermediate (between 4 and 12 m s -1 ) marine AOD was linearly correlated with the surface wind speed values, with a slope of 0.0062 s m -1 . Results of our study suggest that considerable improvements to both optical properties of marine aerosols and their production mechanisms can be achieved by discriminating clean marine aerosols (or sea salt particles) from all other types of aerosols present over the ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Electron transport in unipolar InGaN/GaN multiple quantum well structures grown by NH{sub 3} molecular beam epitaxy

Unipolar-light emitting diode like structures were grown by NH{sub 3} molecular beam epitaxy on c plane (0001) GaN on sapphire templates. Studies were performed to experimentally examine the effect of random alloy fluctuations on electron transport through quantum well active regions. These unipolar structures served as a test vehicle to test our 2D model of the effect of compositional fluctuations on polarization-induced barriers. Variables that were systematically studied included varying quantum well number from 0 to 5, well thickness of 1.5 nm, 3 nm, and 4.5 nm, and well compositions of In{sub 0.14}Ga{sub 0.86}N and In{sub 0.19}Ga{sub 0.81}N. Diode-like current voltage behavior was clearly observed due to the polarization-induced conduction band barrier in the quantum well region. Increasing quantum well width and number were shown to have a significant impact on increasing the turn-on voltage of each device. Temperature dependent IV measurements clearly revealed the dominant effect of thermionic behavior for temperatures from room temperature and above. Atom probe tomography was used to directly analyze parameters of the alloy fluctuations in the quantum wells including amplitude and length scale of compositional variation. A drift diffusion Schrödinger Poisson method accounting for two dimensional indium fluctuations (both in the growth direction and within the wells) was used to correctly model the turn-on voltages of the devices as compared to traditional 1D simulation models.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2012

Development and validation of a radial inflow turbine model for simulation of the SNL S-CO 2 split-flow loop

A one-dimensional model for a radial inflow turbine has been developed for super-critical carbon dioxide (S-CO 2 ) Brayton cycle applications. The model accounts for the main phenomena present in the volute, nozzle, and impeller of a single-stage turbine. These phenomena include internal losses due to friction, blade loading, and angle of incidence and parasitic losses due to windage and blade-housing leakage. The model has been added as a component to the G-PASS plant systems code. The model was developed to support the analysis of S-CO 2 cycles in conjunction with small-scale loop experiments. Such loops operate at less than a MWt thermal input. Their size permits components to be reconfigured in new arrangements relatively easily and economically. However, the small thermal input combined with the properties of carbon dioxide lead to turbomachines with impeller diameters of only one to two inches. At these sizes the dominant phenomena differ from those in larger more typical machines. There is almost no treatment in the literature of turbomachines at these sizes. The present work therefore is aimed at developing turbomachine models that support the task of S-CO 2 cycle analysis using small-scale tests. Model predictions were compared against data from an experiment performed for Sandia National Laboratories in the split-flow Brayton cycle loop currently located at Barber-Nichols Inc. The split-flow loop incorporates two turbo-alternator-compressor (TAC) units each incorporating a radial inflow turbine and a radial flow compressor on a common shaft. The predicted thermodynamic conditions at the outlet of the turbine on the main compressor shaft were compared with measured values at different shaft speeds. Two modifications to the original model were needed to better match the experiment data. First, a representation of the heat loss from the volute downstream of the sensed inlet temperature was added. Second, an empirical multiplicative factor was applied to the Euler head and another to the head loss to bring the predicted outlet pressure into better agreement with the experiment. These changes also brought the overall efficiency of the turbine into agreement with values cited by Barber Nichols for small turbines. More generally, the quality of measurement set data can in the future be improved by additional steps taken in the design and operation of the experimental apparatus. First, a thermocouple mounted at the nozzle inlet would provide a better indication of temperature at this key point. Second, heat losses from the turbine should be measured directly. Allowing the impeller to free wheel at inlet conditions and measuring the temperature drop between inlet and outlet would provide a more accurate measure of heat loss. Finally, the enthalpy change during operation is more accurately obtained by measuring the torque on the stator using strain gauges rather than by measuring pressure and temperature at inlet and outlet to infer thermodynamic states.

42 ENGINEERING↗
DOE OSTI2014

MODELING AND SIMULATION OF SOLID FLUIDIZATION IN A RESIN COLUMN

The objective of the present work is to model the resin particles within the column during fluidization and sedimentation processes using computation fluid dynamics (CFD) approach. The calculated results will help interpret experimental results, and they will assist in providing guidance on specific details of testing design and establishing a basic understanding of particle’s hydraulic characteristics within the column. The model is benchmarked against the literature data and the test data (2003) conducted at Savannah River Site (SRS). The paper presents the benchmarking results and the modeling predictions of the SRS resin column using the improved literature correlations applicable for liquid-solid granular flow.

42 ENGINEERING↗
DOE OSTI2025

An intercomparison of wall fluxes in a turbulent thermal convection chamber: Direct numerical simulations and wall-modeled large-eddy simulations enhanced by machine learning

Thermal convection in a closed chamber is driven by a warm bottom, a cold top, and side walls at various temperatures. Although wall fluxes are the source of convection energy, accurately modeling these fluxes (i.e., the wall model) is challenging. In large-eddy simulations (LESs), many wall models are traditionally derived from the canonical boundary layer, which may be unsuitable for thermal convection bounded by both horizontal and vertical walls. This study conducts a model intercomparison of dry convection in a cubic-meter chamber using three direct numerical simulations (DNSs) and four LESs with different wall models. The LESs employ traditional wall models, a new wall model employing physics-aware neural networks, and a refined grid near the walls. The experiment involves four cases with varying sidewall temperatures. Our results show that LESs capture the main flow features and the trends of mean fluxes. The physics-aware neural networks and refined wall grids can improve the temporally averaged local fluxes when the large-scale circulation has a preferred direction. Even without the local improvement of wall fluxes, the LES flow quantities (temperature and velocities) can still largely match those in DNSs, provided the mean flux largely matches the DNSs. Additionally, DNSs reveal that a variation in corner treatments has minimal impacts on the flow quantities away from corners. Finally, LESs underestimate the mean fluxes of the entire wall due to their inability to resolve corner regions, but their mean flux away from the corner can better match DNS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: new models and constraints from the eBOSS measurement

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman-α forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with 40963 hydrodynamical cells in a 120 Mpc (∼ 81 Mpc/h) comoving box and individually provide sub-percent level convergence of the Lyman-α forest 1d flux power spectrum. We build a Gaussian process emulator for the Lyssa simulations in the lym1d likelihood framework to interpolate the power spectrum at arbitrary parameter values. We validate this emulator based on leave-one-out tests and based on the parameter constraints for simulations outside of the training set. We also perform comparisons with a previous emulator, showing a percent level accuracy and a good recovery of the expected cosmological parameters. Using this emulator we derive constraints on the linear matter power spectrum amplitude and slope parameters A Lyα and n Lyα . While the best-fit Planck ΛCDM model has A Lyα = 8.79 and n Lyα = -2.363, from DR14 eBOSS data we find that A Lyα < 7.6 (95% CI) and n Lyα = -2.369 ± 0.008. The low value of A Lyα , in tension with Planck, is driven by the correlation of this parameter with the mean transmission of the Lyman-α forest. This tension disappears when imposing a well-motivated external prior on this mean transmission, in which case we find A Lyα = 9.8 ± 1.1 in accordance with Planck.

Walther, Michael↗
DOE OSTI2024

Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models

Purpose To calibrate Cancer Intervention and Surveillance Modeling Network (CISNET)'s SimCRC, MISCAN-Colon, and CRC-SPIN simulation models of the natural history colorectal cancer (CRC) with an emulator-based Bayesian algorithm and internally validate the model-predicted outcomes to calibration targets.Methods We used Latin hypercube sampling to sample up to 50,000 parameter sets for each CISNET-CRC model and generated the corresponding outputs. We trained multilayer perceptron artificial neural networks (ANNs) as emulators using the input and output samples for each CISNET-CRC model. We selected ANN structures with corresponding hyperparameters (i.e., number of hidden layers, nodes, activation functions, epochs, and optimizer) that minimize the predicted mean square error on the validation sample. We implemented the ANN emulators in a probabilistic programming language and calibrated the input parameters with Hamiltonian Monte Carlo-based algorithms to obtain the joint posterior distributions of the CISNET-CRC models' parameters. We internally validated each calibrated emulator by comparing the model-predicted posterior outputs against the calibration targets.Results The optimal ANN for SimCRC had 4 hidden layers and 360 hidden nodes, MISCAN-Colon had 4 hidden layers and 114 hidden nodes, and CRC-SPIN had 1 hidden layer and 140 hidden nodes. The total time for training and calibrating the emulators was 7.3, 4.0, and 0.66 h for SimCRC, MISCAN-Colon, and CRC-SPIN, respectively. The mean of the model-predicted outputs fell within the 95% confidence intervals of the calibration targets in 98 of 110 for SimCRC, 65 of 93 for MISCAN, and 31 of 41 targets for CRC-SPIN.Conclusions Using ANN emulators is a practical solution to reduce the computational burden and complexity for Bayesian calibration of individual-level simulation models used for policy analysis, such as the CISNET CRC models. In this work, we present a step-by-step guide to constructing emulators for calibrating 3 realistic CRC individual-level models using a Bayesian approach.

artificial neural networks↗
DOE OSTI2017

A single-column particle-resolved model for simulating the vertical distribution of aerosol mixing state: WRF-PartMC-MOSAIC-SCM v1.0

Abstract. The PartMC-MOSAIC particle-resolved aerosol model was previously developed to predict the aerosol mixing state as it evolves in the atmosphere. However, the modeling framework was limited to a zero-dimensional box model approach without resolving spatial gradients in aerosol concentrations. This paper presents the development of stochastic particle methods to simulate turbulent diffusion and dry deposition of aerosol particles in a vertical column within the planetary boundary layer. The new model, WRF-PartMC-MOSAIC-SCM, resolves the vertical distribution of aerosol mixing state. We verified the new algorithms with analytical solutions for idealized test cases and illustrate the capabilities with results from a 2-day urban scenario that shows the evolution of black carbon mixing state in a vertical column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

On multidomain multiscale modeling and simulation of a novel partial pressure and temperature swing adsorptive reactor ($\mathrm{PPTSAR}$) with application to the water gas shift reaction

Here in this work, a dynamic, multidomain, multiscale model of a novel Partial Pressure and Temperature Swing Adsorptive Reactor (PPTSAR) Process is developed and simulated for a Water Gas Shift Reaction (WGSR) application. The proposed model couples the reactor wall, catalyst/adsorbent pellet, and fluid mixture domains at their respective scales to comprehensively model mass, momentum, and energy transport phenomena occurring within each domain. The resulting model elucidates the PPTSAR’s start-up, transient, and long-term, periodic, dynamic behavior, during both adsorption/reaction and desorption operating modes. In the WGSR application considered, the use of two PPTSARs is shown to allow continuous operation that delivers CO conversion greater than 95% with simultaneous complete CO 2 capture.

42 ENGINEERING↗
DOE OSTI2014

Fully three-dimensional simulation and modeling of a dense plasma focus

A dense plasma focus (DPF) is a pulsed-power machine that electromagnetically accelerates and cylindrically compresses a shocked plasma in a Z-pinch. The pinch results in a brief (~ 100 ns) pulse of X-rays, and, for some working gases, also a pulse of neutrons. A great deal of experimental research has been done into the physics of DPF reactions, and there exist mathematical models describing its behavior during the different time phases of the reaction. Two of the phases, known as the inverse pinch and the rundown, are approximately governed by magnetohydrodynamics, and there are a number of well-established codes for simulating these phases in two dimensions or in three dimensions under the assumption of axial symmetry. There has been little success, however, in developing fully three-dimensional simulations. In this work we present three-dimensional simulations of DPF reactions and demonstrate that three-dimensional simulations predict qualitatively and quantitatively different behavior than their two-dimensional counterparts. One of the most important quantities to predict is the time duration between the formation of the gas shock and Z-pinch, and the three-dimensional simulations more faithfully represent experimental results for this time duration and are essential for accurate prediction of future experiments.

Dense plasma focus, magnetohydrodynamics, simulati↗
DOE OSTI2019

A top-down assessment using OMI NO 2 suggests an underestimate in the NO x emissions inventory in Seoul, South Korea, during KORUS-AQ

Abstract. In this work, we investigate the NO x emissions inventory inSeoul, South Korea, using a regional ozone monitoring instrument (OMI) NO 2 product derived from the standard NASA product. We first develop a regional OMI NO 2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO 2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO 2 values in the regional product that are1.37 times larger in the Seoul metropolitan region and &gt;2 times larger near substantial point sources. These two modifications also yield an OMI NO 2 product that is in better agreement with the Pandora NO 2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NO x emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO 2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NO x emissions rate of 227±94 kt yr –1 , while the bottom-up inventory itself within a 40 km radius of Seoul yields a NO x emissions rate of198 kt yr –1 . Using the top-down approach on the regional OMI NO 2 product, we derive the NO x emissions rate from Seoul to be 484±201 kt yr –1 , and a 353±146 kt yr –1 NO x emissions rate using the standard NASA OMI NO 2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO 2 products respectively. To supplement this finding, we compare the NO 2 and NO y simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate.When NO x emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO 2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF),there are small differences ( ~8 %) in OMI NO 2 compared tousing the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Furthermore the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NO x emissions estimates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

HIGH-FIDELITY SIMULATION-DRIVEN MODEL DEVELOPMENT FOR COARSE-GRAINED COMPUTATIONAL FLUID DYNAMICS

Nuclear reactor safety analysis requires identifying various credible accident scenarios and determining their consequences. For a full-scale nuclear power plant system behavior, it is impossible to obtain sufficient experimental data for a broad range of risk-significant accident scenarios. In single-phase flow convective problems, Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) can provide us with high fidelity results when physical data are unavailable. However, these methods are computationally expensive and cannot be afforded for simulation of long transient scenarios in nuclear accidents despite extraordinary advances in high performance scientific computing over the past decades. The major issue is the inability to make the transient computation parallel, thus making number of time steps required in high-fidelity methods unaffordable for long transients. In this work, we propose to apply a high fidelity simulation-driven approach to model sub-grid scale (SGS) effect in Coarse Grained Computational Fluid Dynamics CG-CFD. This approach aims to develop a statistical surrogate model instead of the deterministic SGS model. We chose to start with a turbulent natural convection case with volumetric heating in a horizontal fluid layer with a rigid, insulated lower boundary and isothermal (cold) upper boundary. This scenario of unstable stratification is relevant to turbulent natural convection in a molten corium pool during a severe nuclear reactor accident, as well as in containment mixing and passive cooling. The presented approach demonstrates how to create a correction for the CG-CFD solution by modifying the energy balance equation. A global correction for the temperature equation proves to achieve a significant improvement to the prediction of steady state temperature distribution through the fluid layer.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

On the Linearity of Local and Regional Temperature Changes from 1.5°C to 2°C of Global Warming

Because of the Paris Agreement it is imperative there is greater understanding of the consequences of limiting global warming to the target 1.5° and 2°C levels above preindustrial conditions. It is challenging to quantify changes across a small increment of global warming, so a pattern-scaling approach may be considered. Here we investigate the validity of such an approach by comprehensively examining how well local temperatures and warming trends in a 1.5°C world predict local temperatures at global warming of 2°C. Ensembles of transient coupled climate simulations from multiple models under different scenarios were compared and individual model responses were analyzed. For many places, the multimodel forced response of seasonal-average temperatures is approximately linear with global warming between 1.5° and 2°C. Yet, individual model results vary and large contributions from nonlinear changes in unforced variability or the forced response cannot be ruled out. In some regions, such as East Asia, models simulate substantially greater warming than is expected from linear scaling. Examining East Asia during boreal summer, we find that increased warming in the simulated 2°C world relative to scaling up from 1.5°C is related to reduced anthropogenic aerosol emissions. Our results indicate that, where forcings other than those due to greenhouse gas emissions change, the warming experienced in a 1.5°C world is a poor predictor for local climate at 2°C of global warming. In addition to the analysis of the linearity in the forced climate change signal, we find that natural variability remains a substantial contribution to uncertainty at these low-warming targets.

54 ENVIRONMENTAL SCIENCES↗