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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impacts of Ice-Shelf Melting on Water-Mass Transformation in the Southern Ocean from E3SM Simulations

Abstract The Southern Ocean overturning circulation is driven by winds, heat fluxes, and freshwater sources. Among these sources of freshwater, Antarctic sea ice formation and melting play the dominant role. Even though ice-shelf melt is relatively small in magnitude, it is located close to regions of convection, where it may influence dense water formation. Here, we explore the impacts of ice-shelf melting on Southern Ocean water-mass transformation (WMT) using simulations from the Energy Exascale Earth System Model (E3SM) both with and without the explicit representation of melt fluxes from beneath Antarctic ice shelves. We find that ice-shelf melting enhances transformation of Upper Circumpolar Deep Water, converting it to lower density values. While the overall differences in Southern Ocean WMT between the two simulations are moderate, freshwater fluxes produced by ice-shelf melting have a further, indirect impact on the Southern Ocean overturning circulation through their interaction with sea ice formation and melting, which also cause considerable upwelling. We further find that surface freshening and cooling by ice-shelf melting cause increased Antarctic sea ice production and stronger density stratification near the Antarctic coast. In addition, ice-shelf melting causes decreasing air temperature, which may be directly related to sea ice expansion. The increased stratification reduces vertical heat transport from the deeper ocean. Although the addition of ice-shelf melting processes leads to no significant changes in Southern Ocean WMT, the simulations and analysis conducted here point to a relationship between increased Antarctic ice-shelf melting and the increased role of sea ice in Southern Ocean overturning.

Jeong, Hyein↗
DOE OSTI2021

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

42 ENGINEERING↗
DOE OSTI2021

Concurrent Changes in Extreme Hydroclimate Events in the Colorado River Basin

Extreme events resulting in catastrophic damage have more than doubled in the last five years, costing hundreds of lives and thousands of homes, and heavily undermining regional economic stability. At present, most of these hydroclimatic extreme events are documented by the media as individual events; however, in scientific terms, many are better understood as concurrent events—concurrent extremes of both temperature and precipitation (e.g., drought, floods). This paper considers concurrent changes in hydroclimate extremes, including heatwaves, drought, flooding, and low flows, in six historical-to-future (1970–1999, 2070–2099) Earth System Model (ESM) climate scenarios for the Colorado River basin. Results indicate that temperature-driven Impacts (heatwaves, drought) have the strongest responses while precipitation-driven Impacts have weaker responses. All Impacts exhibit an increase in magnitude from synoptic to annual time scales, with heatwaves increasing in strength about three times at the annual time scale versus the synoptic, while low flows only increase slightly. Critical watersheds in the Colorado were identified, highlighting the Blue River basin, Uncompahgre, East Taylor, Salt/Verde watersheds, locations of important water infrastructures, water resources, and hydrological research. Our results indicate that concurrent extreme hydroclimate events are projected to increase in the future and intensify within critical regions of the Colorado River basin. Considering extreme hydroclimate events concurrently is an important step towards linking economic and social effects of these events and their associated instabilities on a regional scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The impact of alkali‐ion intercalation on redox chemistry and mechanical deformations: Case study on intercalation of Li, Na, and K ions into FePO 4 cathode

Abstract Batteries made of charge carriers from Earth‐crust abundant materials (e.g., Na, K, and Mg) have received extensive attention as an alternative to Li‐ion batteries for grid storage. However, a lack of understanding of the behavior of these larger ions in the electrode materials hinders the development of electrode structures suitable for these large ions. In this study, we investigate the impact of alkali ions (Li, Na, and K) on the redox chemistry and mechanical deformations of iron phosphate composite cathodes by using electrochemical techniques and in situ digital image correlation. Na‐ion and Li‐ion intercalation demonstrate a nearly linear correlation between electrochemical strains and the state of charge and discharge. The strain development shows nonlinear dependance on the state of charge and discharge for K ions. Strain rate calculations show that K ion intercalation results in a progressive increase in the strain rate for all cycles. Li and Na intercalation induce nearly constant strain rates with the exception of the first discharge cycle of Na intercalation. When the same amount of ions are inserted into the electrode, the electrode shows the lowest strain generation upon Li intercalation compared to larger alkali ions. Na and K ions induce similar volumetric changes in the electrode when the state of charge and discharge is around 30%. Although the electrode experiences larger absolute strain generation at the end of the discharge cycles upon Na intercalation, strain rates were found to be greater for K ions. Potential‐dependent behaviors also demonstrate more sluggish redox reactions during K intercalation, compared to Li and Na. Our quantitative analysis suggests that the strain rate, rather than the absolute value of strain, is the critical factor in amorphization of the crystalline electrode.

25 ENERGY STORAGE↗
DOE OSTI2025

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗
DOE OSTI2024

Evaluating the impact of peat soils and snow schemes on simulated active layer thickness at pan-Arctic permafrost sites

Abstract Permafrost stability is significantly influenced by the thermal buffering effects of snow and active-layer peat soils. In the warm season, peat soils act as a barrier to downward heat transfer mainly due to their low thermal conductivity. In the cold season, the snowpack serves as a thermal insulator, retarding the release of heat from the soil to the atmosphere. Currently, many global land models overestimate permafrost soil temperature and active layer thickness (ALT), partially due to inaccurate representations of soil organic matter (SOM) density profiles and snow thermal insulation. In this study, we evaluated the impacts of SOM and snow schemes on ALT simulations at pan-Arctic permafrost sites using the Energy Exascale Earth System Model (E3SM) land model (ELM). We conducted simulations at the Circumpolar Active Layer Monitoring (CALM) sites across the pan-Arctic domain. We improved ELM-simulated site-level ALT using a knowledge-based hierarchical optimization procedure and examined the effects of precipitation-phase partitioning methods (PPMs), snow compaction schemes, and snow thermal conductivity schemes on simulated snow depth, soil temperature, ALT, and CO 2 fluxes. Results showed that the optimized ELM significantly improved agreement with observed ALT (e.g. RMSE decreased from 0.83 m to 0.15 m). Our sensitivity analysis revealed that snow-related schemes significantly impact simulated snow thermal insulation levels, soil temperature, and ALT. For example, one of the commonly used snow thermal conductivity schemes (quadratic Sturm or SturmQua) generally produced warmer soil temperatures and larger ALT compared to the other two tested schemes. The SturmQua scheme also amplified the model’s sensitivity to PPMs and predicted deeper ALTs than the other two snow schemes under both current and future climates. The study highlights the importance of accurately representing snow-related processes and peat soils in land models to enhance permafrost dynamics simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impacts of Synoptic-Scale Dynamics on Clouds and Radiation in High Southern Latitudes

High-latitudinal mixed-phase clouds significantly affect Earth's radiative balance. Observations of cloud and radiative properties from two field campaigns in the Southern Ocean and Antarctica were compared with two global climate model simulations. A cyclone compositing method was used to quantify “dynamics-cloud-radiation” relationships relative to the extratropical cyclone centers. Observations show larger asymmetry in cloud and radiative properties between western and eastern sectors at McMurdo compared with Macquarie Island. Most observed quantities at McMurdo are higher in the western (i.e., post-frontal) than the eastern (frontal) sector, including cloud fraction, liquid water path (LWP), net surface shortwave and longwave radiation (SW and LW), except for ice water path (IWP) being higher in the eastern sector. Here, the two models were found to overestimate cloud fraction and LWP at Macquarie Island but underestimate them at McMurdo Station. IWP is consistently underestimated at both locations, both sectors, and in all seasons. Biases of cloud fraction, LWP, and IWP are negatively correlated with SW biases and positively correlated with LW biases. The persistent negative IWP biases may have become one of the leading causes of radiative biases over the high southern latitudes, after correcting the underestimation of supercooled liquid water in the older model versions. By examining multi-scale factors from cloud microphysics to synoptic dynamics, this work will help increase the fidelity of climate simulations in this remote region.

58 GEOSCIENCES↗
DOE OSTI2024

Rare Earth Carbide (Nd-C and Ce-C) Synthesis and Characterization to Inform Phase Equilibrium in Advanced Nuclear Fuels

As advances are being made regarding the performance of nuclear fuels, uranium carbides, and composites, such as (U,Zr)C and UO2 + UCx, have recently gained significant interest for deployment in nuclear space propulsion and high temperature gas-cooled reactors, respectively. However, the phase equilibria of several fission products in carbide systems remain unknown and may impact the overall fuel performance, specifically for particle nuclear fuels that are designed for commercial nuclear energy. Furthermore, comprehensive thermodynamic data on Rare Earth (RE) carbides, such as the Nd-C and Ce-C binary systems, remain limited. Presented in this study are the synthesis methods and characterizations of several Nd-C and Ce-C compositions. The findings from this research provide insights on the stability of RE-C binaries that form in irradiated nuclear fuels and address a critical knowledge gap in the current state of thermodynamics for two key RE-C systems.

Cavazos, Steven J. (ORCID:0009000130329363)↗
DOE OSTI2024

Sustainable and Energy-Efficient Production of Rare-Earth Metals via Chloride-Based Molten Salt Electrolysis

Neodymium metal is a critical component of rare earth magnets, essential for electric vehicles and the green energy transition, but its production has severe environmental impacts across its mining, separation, purification, and metal electrowinning steps. Specifically, conventional neodymium electrowinning in oxyfluoride molten salts using a consumable graphite anode generates greenhouse gases, e.g., carbon dioxide and perfluorocarbon (PFC). We propose an alternative chloride-based molten salt electrolysis process utilizing a novel dimensionally stable anode (DSA). Our process lowers the specific electrical energy consumption compared to the state of the art, while producing reusable chlorine gas and eliminating direct CO 2 and PFC emissions. Chloride-based molten salt electrolysis of NdCl 3 (1.65 M) added to a LiCl–KCl eutectic (45:55 wt %), while using a RuO 2 -coated DSA enables high Coulombic efficiency (>80%), low specific energy consumption (2.3 kWh/kg-Nd), and excellent electrowon Nd product purity (>97 wt %). Life cycle analysis, excluding the common input feedstock (Nd 2 O 3 ), shows that the global warming potential for the proposed chloride-based electrolysis approach is 5 kg CO 2 equivalent, compared to 9–16 kg CO 2 equivalent for the conventional process, representing a 44–69% reduction in CO 2 emissions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evaluation and improvement of the parameterization of aerosol hygroscopicity in global climate models using in-situ surface measurements (Final Report)

Aerosols are tiny particles suspended on the atmosphere that can interact with incoming solar radiation and affect the Earth radiative budget. They do so by scattering and absorbing solar radiation, and these properties vary depending on the aerosol size and chemical composition. Moreover, by taking up water from the surrounding air, hygroscopic aerosol particles will grow in size and change their chemical composition, thus modifying their optical properties (scattering and absorption) and their final impact on radiative forcing calculations. An accurate knowledge of aerosol hygroscopicity is crucial for estimating the net radiative impact of aerosols. We took a three-pronged approach to improve our understanding of aerosol hygroscopicity and how it is implemented in Earth system models. In the first part of our project, we developed a benchmark dataset from existing aerosol hygroscopic growth measurements made by tandem nephelometer humidogram systems. We analyzed, using a standardized methodology, observations from 26 in-situ stations around the globe. Measurement data was collected from multiple data providers, reviewed and harmonized to create a consistent dataset of the scattering enhancement factor due to aerosol water uptake. This dataset is archived in several publicly available databases for use by interested researchers. In the second part of the project, we used the benchmark hygroscopicity dataset to perform a global study on aerosol hygroscopicity and aerosol optical properties. Measurements show a global picture of scattering enhancement with larger values for Arctic and marine sites and lower for urban and desert sites. We assessed the RH dependence of aerosol radiative forcing and showed that the overall effect of aerosol hygroscopicity on DARF is an increase in the absolute forcing effect (negative sign) by a factor of up to 4 compared to dry conditions (RH<40%). Finally, we explored using aerosol single scattering albedo (SSA) and scattering Angstrom exponent (SAE) as possible proxies for aerosol hygroscopicity. SSA showed more promise as a surrogate for the scattering enhancement factor than SAE, but neither was ideal. In the third part of the project we evaluated the output of ten Earth system models (ESMs) against the benchmark hygroscopicity dataset. ESMs utilize various schemes for aerosol hygroscopicity which had not been previously tested against observations on a global scale. We found that ESMs currently overestimate scattering enhancement due to hygroscopic growth. Model parameterizations of hygroscopicity and model chemistry are two main factors driving the observed diversity in hygroscopicity simulations among the models. In addition, our study makes several suggestions for modelers, including improving the parameterizations of organic and sea salt aerosol hygroscopicity. Future hygroscopicity model evaluation experiments should include the model data related to particles size which was not available for our study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

IAM-FIRE: a Climate Emulator–Based Framework to Project Wildfire Impacts and Risks for Integrated Assessment Models

Most Integrated Assessment Models (IAMs) underrepresent dynamic feedbacks from climate-driven disturbances such as wildfires, potentially overestimating the permanence of land-based carbon sinks. In particular, representing the impacts of forest fires is becoming increasingly important, as these are expected to intensify in the coming years. We introduce IAM-FIRE (Integrated Assessment Model – Fire Impacts & Risks Emulator), a novel framework that enables the projection of wildfire burned area (BA) and carbon emissions (CE) directly from IAM outputs. IAM-FIRE combines a spatial climate emulator, land-use downscaling, vegetation productivity modelling, and an empirical fire model to generate global annual wildfire impacts for arbitrary socioeconomic and emissions scenarios at 0.5° resolution for the period 2020–2100. Calibrated against GFEDv5 observations and using inputs from the Global Change Analysis Model (GCAM), we report projections BA and CE derived from IAM-FIRE for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-6.6 and SSP5-7.6. The model reproduces historical global trends for total BA, including the observed global decline since the early 2000s, and for forest BA. Projected fire trajectories differ strongly among scenarios: total BA range from declines under SSP1-2.6 (-3.36 Mha yr-1) to increases under SSP3-6.6 (+1.6 Mha yr-1). Corresponding total CE show a similar divergence ranging from -15 to +10.6 TgC yr-1. Socioeconomic development exerts a dominant suppressing effect on wildfire impacts while climate change and CO2-driven increases in vegetation productivity amplify fire risk, particularly under high-emissions pathways. Compared with CMIP6 fire-enabled Earth System Models, IAM-FIRE exhibits greater sensitivity to radiative forcing and a stronger role for human-driven fire suppression, highlighting substantial structural uncertainties in future fire projections. By providing a computationally efficient and internally consistent approach to represent wildfire impacts within IAMs, IAM-FIRE enables systematic exploration of fire–climate–land feedbacks and supports improved assessments of mitigation permanence and climate risks in future integrated scenarios.

Rouhette, Theo↗
DOE OSTI2023

Contrasting the Biophysical and Radiative Effects of Rising CO 2 Concentrations on Ozone Dry Deposition Fluxes

Abstract The dry deposition of ozone from the atmosphere to ecosystems is an important coupling mechanism between atmospheric chemistry and terrestrial biogeochemical processes. In most Earth system models, dry deposition is simulated using a resistor‐in‐series approach that aims to parameterize the governing biological, chemical, and physical processes through a series of functional approximations. Here, we evaluate the influence of carbon cycle‐climate responses on this parameterization using the results of the Energy Exascale Earth System Model v1.1 Biogeochemistry simulation campaign. This simulation campaign was designed in part to explore the biophysical and radiative effects of rising historical CO 2 concentrations on the Earth system. We find that while the global annual ozone dry deposition is relatively insensitive to these effects, regionally the influence can be up to 10%. The strongest regional sensitivities in ozone dry deposition are predominantly in higher latitudes over land in the northern hemisphere and are dominated by the radiative effect of CO 2 , with little net influence of biophysical responses. Of all the impacts of the radiative effect of CO 2 , we point to the potential importance of accurately representing ozone deposition to snow in Earth System Models and provide recommendations for future simulation campaigns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Projected changes in African easterly wave activity due to climate change

African easterly waves significantly influence regional hydroclimate, making it crucial to understand how global warming will impact their activity. Here, we investigate future changes in wave activity and assess the underlying mechanisms using an ensemble of Earth system models. We find a robust increase in wave activity over the Sahel–Sahara region by the end of the 21st century under two emission scenarios. This intensification is linked to increased baroclinicity associated with a strengthening of the meridional temperature gradient between the Guinea Coast and the Sahara. Our results also indicate that low-level warming enhances the waves by reinforcing monsoon flow, leading to increased convergence and vertical motion along the intertropical discontinuity. These energetic alterations significantly modify the conditions that currently produce these waves. Overall, our findings suggest that changes in wave activity could impact the transport of Saharan dust and mesoscale convective activity over the Sahel.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of ITCZ width on global climate: ITCZ-MIP

Abstract. The width of the Inter-Tropical Convergence Zone (ITCZ) affects tropical rainfall, Earth's albedo, large-scale circulation, and climate sensitivity. To better understand the ITCZ width and its effects on global climate, we present a protocol to force changes in ITCZ width in climate models. Starting from an aquaplanet configuration with a slab ocean, adding surface heat fluxes in the deep tropics forces the ITCZ to narrow, and subtracting them causes it to widen. The protocol successfully generates changes in ITCZ width in all four climate models used in this study. ITCZ width in each model responds linearly to forcing magnitude and sign. Comparing across the four climate models, a response to varying ITCZ width that is remarkably consistent among models is the ITCZ strength, which is greater the narrower the ITCZ. On the other hand, the effect of varying ITCZ width on climate sensitivity is divergent among our four models, varying even in sign. Results from this pilot study highlight the connections between surface fluxes, ITCZ width, and the wider climate. A comprehensive model intercomparison project (MIP) has the potential to advance understanding of both the physical processes shaping ITCZ width and its influence on remote atmospheric circulations and global climate.

Geology↗
DOE OSTI2026

Climate impacts in scenarios: time to close the loop?

Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.

Tebaldi, Claudia↗
DOE OSTI2021

Regional environmental controllers influence continental scale soil carbon stocks and future carbon dynamics

Abstract Understanding the influence of environmental factors on soil organic carbon (SOC) is critical for quantifying and reducing the uncertainty in carbon climate feedback projections under changing environmental conditions. We explored the effect of climatic variables, land cover types, topographic attributes, soil types and bedrock geology on SOC stocks of top 1 m depth across conterminous United States (US) ecoregions. Using 4559 soil profile observations and high-resolution data of environmental factors, we identified dominant environmental controllers of SOC stocks in 21 US ecoregions using geographically weighted regression. We used projected climatic data of SSP126 and SSP585 scenarios from GFDL-ESM 4 Earth System Model of Coupled Model Intercomparison Project phase 6 to predict SOC stock changes across continental US between 2030 and 2100. Both baseline and predicted changes in SOC stocks were compared with SOC stocks represented in GFDL-ESM4 projections. Among 56 environmental predictors, we found 12 as dominant controllers across all ecoregions. The adjusted geospatial model with the 12 environmental controllers showed an R 2 of 0.48 in testing dataset. Higher precipitation and lower temperatures were associated with higher levels of SOC stocks in majority of ecoregions. Changes in land cover types (vegetation properties) was important in drier ecosystem as North American deserts, whereas soil types and topography were more important in American prairies. Wetlands of the Everglades was highly sensitive to projected temperature changes. The SOC stocks did not change under SSP126 until 2100, however SOC stocks decreased up to 21% under SSP585. Our results, based on environmental controllers of SOC stocks, help to predict impacts of changing environmental conditions on SOC stocks more reliably and may reduce uncertainties found in both, geospatial and Earth System Models. In addition, the description of different environmental controllers for US ecoregions can help to describe the scope and importance of global and local models.

58 GEOSCIENCES↗