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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Increased drought and extreme events over continental United States under high emissions scenario

The frequency, severity, and extent of climate extremes in future will have an impact on human well-being, ecosystems, and the effectiveness of emissions mitigation and carbon sequestration strategies. The specific objectives of this study were to downscale climate data for US weather stations and analyze future trends in meteorological drought and temperature extremes over continental United States (CONUS). We used data from 4161 weather stations across the CONUS to downscale future precipitation projections from three Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase Six (CMIP6), specifically for the high emission scenario SSP5 8.5. Comparing historic observations with climate model projections revealed a significant bias in total annual precipitation days and total precipitation amounts. The average number of annual precipitation days across CONUS was projected to be 205 ± 26, 184 ± 33, and 181 ± 25 days in the BCC, CanESM, and UKESM models, respectively, compared to 91 ± 24 days in the observed data. Analyzing the duration of drought periods in different ecoregions of CONUS showed an increase in the number of drought months in the future (2023–2052) compared to the historical period (1989–2018). The analysis of precipitation and temperature changes in various ecoregions of CONUS revealed an increased frequency of droughts in the future, along with longer durations of warm spells. Eastern temperate forests and the Great Plains, which encompass the majority of CONUS agricultural lands, are projected to experience higher drought counts in the future. Drought projections show an increasing trend in future drought occurrences due to rising temperatures and changes in precipitation patterns. Our high-resolution climate projections can inform policy makers about the hotspots and their anticipated future trajectories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario

As the world's fifth-largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state-of-the-art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected –3% to +42% and –27% to +63% precipitation changes in northern and central-southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d –1 (10–34%) over northern CA and increase by 0.1–0.5 mm d –1 (7–32%) over central-southern CA by the end of the 21st century compared with present-day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Variable renewable energy deployment in low-emission scenarios: The role of technology cost and value

While rapid deployment of variable renewable energy (VRE) technologies, namely wind and solar PV, is often projected in 2C pathways generated by integrated assessment models, there is a wide range in projected VRE deployment by mid-century. Such differences could be the result of differences in assumptions about future technology costs and/or differences in model approaches for capturing other aspects of technology competitiveness. Here we introduce a consistent competitiveness metric, profitability-adjusted levelized cost of electricity (or PLCOE), to an integrated assessment model (EPPA) to evaluate the representation of technology competition, including VRE, in low-emission scenarios. We show that representing the value of technology (alongside cost) may significantly impact VRE deployment relative to scenarios without such an adjustment. In addition, we show that varying VRE costs by about 35% in 2050 results in differences in VRE deployment that span much of the range in outcomes (over the same period) observed in likely 2C scenarios assessed by the IPCC, suggesting that both cost and value are key drivers of VRE deployment in such scenarios. Given the central role that VRE technologies play in the electricity mix across most scenarios, we also find that alternative cost assumptions for VRE technologies can lead to changes in electricity prices, the associated demand for electricity, and total final and primary energy consumption. However, the demand for fuels other than electricity is relatively insensitive to VRE assumptions in the 2C scenarios considered here.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Multi-century dynamics of the climate and carbon cycle under both high and net negative emissions scenarios

Abstract. Future climate projections from Earth system models (ESMs) typically focus on the timescale of this century. We use a set of five ESMs and one Earth system model of intermediate complexity (EMIC) to explore the dynamics of the Earth's climate and carbon cycles under contrasting emissions trajectories beyond this century to the year 2300. The trajectories include a very-high-emissions, unmitigated fossil-fuel-driven scenario, as well as a mitigation scenario that diverges from the first scenario after 2040 and features an “overshoot”, followed by a decrease in atmospheric CO2 concentrations by means of large net negative CO2 emissions. In both scenarios and for all models considered here, the terrestrial system switches from being a net sink to either a neutral state or a net source of carbon, though for different reasons and centered in different geographic regions, depending on both the model and the scenario. The ocean carbon system remains a sink, albeit weakened by carbon cycle feedbacks, in all models under the high-emissions scenario and switches from sink to source in the overshoot scenario. The global mean temperature anomaly is generally proportional to cumulative carbon emissions, with a deviation from proportionality in the overshoot scenario that is governed by the zero emissions commitment. Additionally, 23rd century warming continues after the cessation of carbon emissions in several models in the high-emissions scenario and in one model in the overshoot scenario. While ocean carbon cycle responses qualitatively agree in both globally integrated and zonal mean dynamics in both scenarios, the land models qualitatively disagree in zonal mean dynamics, in the relative roles of vegetation and soil in driving C fluxes, in the response of the sink to CO2, and in the timing of the sink–source transition, particularly in the high-emissions scenario. The lack of agreement among land models on the mechanisms and geographic patterns of carbon cycle feedbacks, alongside the potential for lagged physical climate dynamics to cause warming long after CO2 concentrations have stabilized, points to the possibility of surprises in the climate system beyond the 21st century time horizon, even under relatively mitigated global warming scenarios, which should be taken into consideration when setting global climate policy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bioenergy pathways within United States net-zero CO 2 emissions scenarios in the Energy Modeling Forum 37 study

The Energy Modeling Forum 37 study is organized around carbon dioxide (CO 2 ) mitigation scenarios reaching net-zero CO 2 emissions by 2050 in the United States. Here, this paper summarizes the potential contribution of bioenergy use in the electric power, transportation, industrial, and buildings sectors toward meeting that target based on model results. Thirteen modeling teams reported bioenergy consumption in the Reference and Net Zero scenarios. Consumption of bioenergy increased over time in the Reference scenario, from an average across models of 3.2 exajoules (EJ) in 2020 to 3.8 EJ in 2050. Average bioenergy consumption in 2050 increased further to 7.3 EJ in the Net Zero scenario. All scenarios that reach net-zero emissions required some form of carbon dioxide removal to offset emissions that are difficult to reduce. Carbon dioxide removal using bioenergy with CO 2 capture and storage (BECCS) varies widely across models, up to 1000 Mt CO 2 in 2050. Some models rely instead on direct air carbon capture and storage (DACCS), up to 2200 Mt CO 2 , and others use a combination of BECCS and DACCS. Model results show a strong inverse relationship between the amounts of BECCS and DACCS deployed. All modeling teams assumed a carbon sink from land use, land use change, and forestry, further offsetting a portion of emissions from fossil fuels and industry that are expensive to eliminate. Bioenergy consumption in 2050 decreased by an average of 1.5 EJ across eight models in a Net Zero+ scenario relative to the Net Zero scenario, due in part to a lower equilibrium carbon price resulting from optimistic cost assumptions for all energy technologies.

09 BIOMASS FUELS↗
DOE OSTI2021

Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios

The latest scenarios for the sixth Coupled Model Intercomparison Project (CMIP6) provide opportunities to explore future climate and air pollution mitigation pathways with socioeconomic features. However, to what extent inadequate consideration of region-specific policies in the CMIP6 scenarios would affect regional air quality projections is still not clear. Here, we simulated China’s future PM2.5 concentrations and compositions with local policy-based scenarios and the original CMIP6 datasets, for the first time estimating future air quality differences induced by the lack of local pollution control policies in the CMIP6 scenarios. We found that the CMIP6-driven projections overestimate major chemical aerosols by 10% – 70% in 2015 and fail to capture the rapid PM2.5 concentration decline during 2015–2019. Near-term differences further lead to 43% – 49% (5 – 9 µg/m3) PM2.5 overpredictions in 2050 in CMIP6 scenarios compared with policy-based mitigation scenarios. Our study demonstrates the indispensable influences of local policies on regional analyses and suggests that the research community should incorporate more region-specific information in future scenario designs.

Cheng, Jing↗
DOE OSTI2020

Potential impacts of mercury released from thawing permafrost

Abstract Mercury (Hg) is a naturally occurring element that bonds with organic matter and, when converted to methylmercury, is a potent neurotoxicant. Here we estimate potential future releases of Hg from thawing permafrost for low and high greenhouse gas emissions scenarios using a mechanistic model. By 2200, the high emissions scenario shows annual permafrost Hg emissions to the atmosphere comparable to current global anthropogenic emissions. By 2100, simulated Hg concentrations in the Yukon River increase by 14% for the low emissions scenario, but double for the high emissions scenario. Fish Hg concentrations do not exceed United States Environmental Protection Agency guidelines for the low emissions scenario by 2300, but for the high emissions scenario, fish in the Yukon River exceed EPA guidelines by 2050. Our results indicate minimal impacts to Hg concentrations in water and fish for the low emissions scenario and high impacts for the high emissions scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Simulation of radon-222 with the GEOS-Chem global model: Emissions, seasonality, and convective transport

Radon-222 (222Rn) is a short-lived radioactive gas naturally emitted from land surface, and has long been used to assess convective transport in atmospheric models. In this study, we simulate 222Rn using the GEOS-Chem chemical transport model with aims to improve our understanding of 222Rn emissions and surface concentration seasonality, and to characterize convective transport associated with two Goddard Earth Observing System (GEOS) meteorological products, MERRA and GEOS-FP. We evaluate four available 222Rn emission scenarios by comparing model results with surface observations at 51 global surface sites. The default emission scenario in GEOS-Chem yields a moderate agreement with global surface observations (< 70% data within a factor of 2) and a large underestimate of wintertime surface 222Rn concentrations at Northern Hemisphere mid- and high-latitudes due to an oversimplified formulation of 222Rn emission fluxes (1 atom cm-2 s-1 over land with a reduction by a factor of 3 under freezing conditions). We compose a new global 222Rn emission scenario based on Zhang et al. (2011) and show its potential to improve simulated surface 222Rn concentrations and seasonality. The regional components of this emission scenario include spatially and temporally varying emission fluxes derived from previous measurements of soil radium content and soil exhalation models, which are key factors to 222Rn emission flux rates. However, large model underestimates of surface 222Rn concentrations still exist in Asia, suggesting unusually high regional 222Rn emissions. We propose a conservative up-scaling factor of 1.2 for 222Rn emission fluxes in China, as also constrained by the observed deposition fluxes of 210Pb (decay daughter of 222Rn). With this modification, the model shows better agreement with the observations in Europe and North America (>80% data within a factor of 2), and reasonable agreement in Asia (close to 70%). Further constraints on 222Rn emissions would require additional observations of surface 222Rn concentrations and emission fluxes in central U.S., Canada, Africa, and Asia. We also compare and assess convective transport in model simulations driven by MERRA and GEOS-FP using observed 222Rn vertical profiles during northern mid-latitude summertime and from two short-term airborne campaigns. While the simulations with both GEOS products are able to capture the observed vertical gradient of 222Rn concentrations in the lower troposphere (0-4 km), neither correctly represents the level of convective detrainment, resulting in biases in the middle and upper troposphere. Compared to GEOS-FP, MERRA leads to stronger convective transport of 222Rn, which is partially compensated by its weaker large-scale vertical advection, resulting in similar global vertical distributions of 222Rn concentrations between the two simulations.

Zhang, Bo↗
DOE OSTI2024

Projecting Changes in the Frequency and Magnitude of Ozone Pollution Events Under Uncertain Climate Sensitivity

Abstract Climate change is projected to worsen ozone pollution over many populated regions, with larger impacts at higher concentrations. More intense and frequent ozone episodes risk setbacks to human health and environmental policy achievements. However, assessing these changes is complicated by uncertain climate sensitivity, closely related to climate model response, and internal variability in simulations projecting climate's influence on air quality. Here, leveraging a global modeling framework that one‐way couples a human activity model, an Earth system model of intermediate complexity, and an atmospheric chemistry model, we investigate the role of climate sensitivity in climate‐induced changes to high ozone pollution episodes in the United States using multiple greenhouse gas emissions scenarios, representations of climate sensitivity, and initial condition members. We bias correct and evaluate historical model simulations, identifying modeled and observed O 3 episodes using extreme value theory, and extend the approach to projections of mid‐ and end‐century climate impacts. Results show that the influence of climate sensitivity can be as significant as that of greenhouse gas emissions scenario absent precursor emissions changes. Climate change is projected to increase the magnitude of the highest annually occurring O 3 concentrations by over 2.3 ppb on average across the U.S. at mid‐century under a high climate sensitivity and moderate emissions scenario, but the increase is limited to less than 0.3 ppb under lower climate sensitivity. Further, we show that areas in the U.S. currently meeting air quality standards risk being pushed into non‐compliance due to a climate‐induced increase in frequency of high ozone days.

Environmental Sciences & Ecology↗
DOE OSTI2022

Characterizing and quantifying uncertainty in projections of climate change impacts on air quality

Climate change can aggravate air pollution, with important public health and environmental consequences. While major sources of uncertainty in climate change projections - greenhouse gas (GHG) emissions scenario, model response, and internal variability - have been investigated extensively, their propagation to estimates of air quality impacts has not been systematically assessed. Here, we compare these uncertainties using a coupled modeling framework that includes a human activity model, an Earth system model of intermediate complexity, and a global atmospheric chemistry model. Uncertainties in projections of U.S. air quality under 21st century climate change are quantified based on a climate-chemistry ensemble that includes multiple initializations, representations of climate sensitivity, and climate policy scenarios, under constant air pollution emissions. We find that climate-related uncertainties are comparable at mid-century, making it difficult to distinguish the impact of variations in GHG emissions on ozone and particulate matter pollution. While GHG emissions scenario eventually becomes the dominant uncertainty based on the scenarios considered, all sources of uncertainty are significant through the end of the century. The results provide insights into intrinsically different uncertainties in projections of air pollution impacts and the potential for large ensembles to better capture them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Temporal persistence of postfire flood hazards under present and future climate conditions in southern Arizona, USA

Changes to soil hydraulic properties that reduce infiltration capacity following fire can increase flash flood risks. These risks are exacerbated by rainfall intensification associated with a warming climate. However, the potential effects of climate-change-driven rainfall intensification on postfire floods remain largely unexplored. Using rainfall and runoff observations from a 49.4 km 2 watershed in southern Arizona, USA, and a hydrologic model (KINEROS2), we examined the temporal evolution following a historic fire of three crucial hydrologic parameters: soil saturated hydraulic conductivity (K sp ), net capillary drive (G p ), and hydraulic roughness (n c ). We explored how the effect of fire on these parameters may influence peak flow under future climate scenarios derived from CMIP6, specifically the medium emissions scenario (SSP2-4.5) and high emissions scenario (SSP5-8.5). Results demonstrate an increase in K sp from 11 mm h −1 in the first postfire year to 60 mm h −1 in postfire year 3. G p similarly increased from 19 mm in the first postfire year to 30 mm in the third, while nc was relatively constant. The highest simulated Q p occurred in the first postfire year. Under the SSP2-4.5 scenario, the likelihood of a 100-year flood is projected to be twice as large by the middle of the century relative to its historical magnitude. Simulations further indicate that the maximum expected discharge associated with a postfire flood, as derived from historical data, could be triggered by a 10-year rainstorm under the SSP5-8.5 scenario by the late century. Simulations also demonstrate that rainfall intensification will lead to greater persistence of elevated flood hazards following fire by the late century under both the SSP2-4.5 and the SSP5-8.5 scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

National Climate Database (NCDB)

The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation- global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI)- as well as other meteorological data. The goal of the NCDB is to provide unbiased high temporal and spatial resolution climate data needed for renewable energy modeling. The NCDB is modeled using a statistical downscaling approach with Regional Climate Model (RCM)-based climate projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX; linked below). Daily climate projections simulated by the Canadian Regional Climate Model 4 (CanRCM4) forced by the second-generation Canadian Earth System Model (CanESM2) for two Representative Concentration Pathways (RCP4.5 or moderate emissions scenario and RCP8.5 or highest baseline emission scenario) are selected as inputs to the statistical downscaling models. The National Solar Radiation Database (NSRDB) is used to build and calibrate statistical models.

Array↗
DOE OSTI2022

Past and future ocean warming

Changes in ocean heat content (OHC) provide a measure of ocean warming, with impacts on the Earth system. This Review synthesizes estimates of past and future OHC changes using observations and models. The top 2,000 m of the global ocean has significantly warmed since the 1950s, gaining 351 ± 59.8 ZJ (1 ZJ = 10 21 J) from 1958 to 2019. The rate of warming increased from <5 to ~10 ZJ yr –1 from the 1960s to the 2010s. Observed area-averaged warming is largest in the Atlantic Ocean and southern oceans at 1.42 ± 0.09 and 1.40 ± 0.09 × 109 J m –2 , respectively, for the upper 2,000 m over 1958–2019. These observed patterns of heat gains are dominated by heat redistribution. Observationally constrained projections suggest that historic ocean warming is irreversible this century, with net warming dependent on the emission scenario. By 2100, projected warming in the top 2,000 m is 2–6 times that observed so far, ranging from 1,030 [839–1,228] ZJ for a low-emission scenario to 1,874 [1,637–2,109] ZJ for a high-emission scenario. The Pacific is projected to be the largest heat reservoir owing to its size, but area-averaged warming remains strongest in the Atlantic and southern oceans. Ocean warming has extensive impacts that pose risks to marine ecosystems and society. Here, the projected changes necessitate a continuation and improvement of observations and models, along with better uncertainty estimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sensor Placement Optimization Software Applied to Site-Scale Methane-Emissions Monitoring

Advances in sensor technology have increased our ability to monitor a wide range of environments. However, even as the cost of sensors decline, only a limited number of sensors can be installed at any given site. The physical placement of sensors, along with the sensor technology and operating conditions, can have a large impact on our ability to adequately monitor environmental change. This paper introduces a new open-source Python package, called Chama, that determines optimal sensor placement and technology to improve a sensor network’s detection capabilities. Additionally, the methods are demonstrated using site-specific methane emission scenarios that capture uncertainty in wind conditions and emission characteristics. Mixed-integer linear programming formulations are used to determine sensor locations and detection thresholds that maximize detection of the emission scenarios. The optimized sensor networks consistently increase the ability to detect leaks, as compared to sensors placed near each potential emission source or along the perimeter of the site.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Impacts of projected changes in sea surface temperature on ozone pollution in China toward carbon neutrality

The global sea surface temperatures (SSTs) are expected to change diversely in the future under different climate scenarios, which will affect the near-surface ozone (O 3 ) distribution and concentration by influencing meteorological states and large-scale atmospheric circulation. Many countries have planned to reach carbon neutrality by the mid-21st century. Here in this study, the impacts of global and regional SST changes on near-surface O 3 concentrations in China in the middle of the 21st century under the carbon-neutral scenario (Shared Socioeconomic Pathway 1-1.9), compared with the high-emission scenario (Shared Socioeconomic Pathway 5-8.5), and possible physical and chemical mechanisms are investigated using the Community Earth System Model version 1 (CESM1). Under future climate change, the changes in SSTs in the carbon-neutral scenario relative to the high-emission scenario lead to a dipole change in near-surface O 3 concentrations in eastern and western China, with a significant decrease of 0.79 ppbv in the eastern China and a significant increase of 1.05 ppbv in the western China. The cooling of North Pacific Ocean under the carbon-neutral scenario causes a decrease in near-surface O 3 concentrations by 0.48 ppbv in eastern China due to the weakened chemical production and an increase by 0.74 ppbv in western China attributed to the enhanced O 3 transport from Eurasia. Cooling of Southern Hemisphere oceans leads to anomalous upward air motions over eastern China, which weaken the vertical transport of high-altitude O 3 to the surface. Our results suggest that future changes in SSTs in the carbon-neutral scenario will positively benefit O 3 air quality improvement in the polluted eastern China, with the North Pacific and Southern Hemisphere oceans playing important roles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Implications of climate change impacts for emission and land use scenario development

Scenarios of future emissions and land use produced by integrated assessment models have traditionally been developed without accounting for how climate change impacts could affect the emissions and land use trajectories themselves. This omission risks skewing our assessments of the plausible range of future emission pathways and associated Earth system changes. Beyond the salience for emission scenario development, a better integrated representation of human and Earth system changes and feedbacks would enable better anticipation of the implications of alternative socio-economic development pathways. We use the Global Change Analysis Model to investigate whether endogenizing several impacts when generating its baseline emission scenario is warranted. We do so by comparing the emissions and land use change that result from the baseline scenario with and without impacts, where impacts are implemented as exogenous changes to water availability, crop and labor productivity, and energy demand and supply. Our results indicate that the effect on global emissions leads to less than 0.1 °C increase in warming by 2100 and therefore do not support endogenizing impacts. This conclusion is conditional on our modeling framework and the specific impact channels represented but is consistent with other studies that have addressed the magnitude of feedbacks by implementing a two-way coupling. However, we do find regional impacts indicating that local economies and well-being measures may be affected significantly.

climate impacts↗
DOE OSTI2023

Bayesian weighting of climate models based on climate sensitivity

Using climate model ensembles containing members that exhibit very high climate sensitivities to increasing CO 2 concentrations can result in biased projections. Various methods have been proposed to ameliorate this ‘hot model’ problem, such as model emulators or model culling. Here, we utilize Bayesian Model Averaging as a framework to address this problem without resorting to outright rejection of models from the ensemble. Taking advantage of multiple lines of evidence used to construct the best estimate of the earth’s climate sensitivity, the Bayesian Model Averaging framework produces an unbiased posterior probability distribution of model weights. The updated multi-model ensemble projects end-of-century global mean surface temperature increases of 2 °C for a low emissions scenario (SSP1-2.6) and 5 °C for a high emissions scenario (SSP5-8.5). These estimates are lower than those produced using a simple multi-model mean for the CMIP6 ensemble. The results are also similar to results from a model culling approach, but retain some weight on low-probability models, allowing for consideration of the possibility that the true value could lie at the extremes of the assessed distribution. Our results showcase Bayesian Model Averaging as a path forward to project future climate change that is commensurate with the available scientific evidence.

59 BASIC BIOLOGICAL SCIENCES↗