SEARCH · Engineering Papers
Results for “Climate sensitivity”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Climate Warming Alters Nutrient Storage in Seasonally Dry Forests: Insights From a 2,300 m Elevation Gradient
Understanding potential response of forest carbon (C) and nutrient storage to warming is important for climate mitigation policies. Unfortunately, those responses are difficult to predict in seasonally dry forests, in part, because ecosystem processes are highly sensitive to both changes in temperature and precipitation. We investigated how warming might alter stocks of C, nitrogen (N), and phosphorus (P) in vegetation and the entire regolith (soil + weathered bedrock or “saprock”) using a space-for-time substitution along a bioclimatic gradient in the Sierra Nevada, California. The pine-oak and mixed-conifer forests between 1,160–2,015 m elevation have more optimal climates (not too dry or hot) for ecosystem productivity, soil weathering, and cycling of essential elements than the oak savannah (405 m) and subalpine forest (2,700 m). We found decreases in overstory vegetation nutrient stocks with decreasing elevation because of enhanced water limitation and greater occurrence of disturbances. Stocks of C, N, and P in the entire regolith peaked at the pine-oak and mixed-conifer forests across the bioclimatic gradient, driven by thicker regolith profiles and greater nutrient input rates. These observations suggest long-term warming will decrease ecosystem nutrient storage at the warmer, transitional pine-oak zone, but will increase nutrient storage at the colder, subalpine zone. Assuming steady-state conditions, we found the mean residence time of ecosystem C decreased with projected rising air temperatures and increased following a major drought event across the bioclimatic gradient. Our study emphasizes potentially elevation-dependent changes in nutrient storage and C persistence with warming in seasonally dry forests.
Enriched Molecular-Level View of Saline Wetland Soil Carbon by Sensitivity-Enhanced Solid-State NMR
Soil organic matter (SOM) plays a major role in mitigating greenhouse gas emission and regulating earth’s climate, carbon cycle, and biodiversity. Wetland soils account for one-third of all SOM; however, globally, coastal wetland soils are eroding faster due to increasing sea-level rise. Our understanding of carbon sequestration dynamics in wetlands lags behind that of upland soils. Here, we employ solid-state nuclear magnetic resonance (ssNMR) to investigate the molecular-level structure of biopolymers in wetland soils spanning 11 centuries. High-resolution multidimensional spectra, enabled by dynamic nuclear polarization (DNP), demonstrate enduring preservation of molecular structures within herbaceous plant cores, notably condensing aromatic motifs and carbohydrates, even over a millennium, with the preserved cores constituting a decreasing minority among molecules from decomposition and repolymerization with depth and age. Such preserved cores occur alongside molecules from the decomposition of loosely packed parent biopolymers. These findings emphasize the relative vulnerability of coastal wetland SOM when exposed to oxygenated water due to geological and anthropogenic changes.
Controls and variability of soil respiration temperature sensitivity across China
Understanding the temperature sensitivity (Q 10 ) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q 10 , a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q 10 at regional scales. Here, therefore, we used a machine learning approach to predict Q 10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q 10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q 10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic carbon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrating soil controls on the spatial pattern of Q 10 . These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q 10 , which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change.
California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model
Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.
Quantifying CanESM5 and EAMv1 sensitivities to Mt. Pinatubo volcanic forcing for the CMIP6 historical experiment
Large volcanic eruptions reaching the stratosphere have caused marked perturbations to the global climate including cooling at the Earth's surface, changes in large-scale circulation and precipitation patterns and marked temporary reductions in global ocean heat content. Many studies have investigated these effects using climate models; however, uncertainties remain in the modelled response to these eruptions. This is due in part to the diversity of forcing datasets that are used to prescribe the distribution of stratospheric aerosols resulting from these volcanic eruptions, as well as uncertainties in optical property derivations from these datasets. To improve this situation for the sixth phase of the Coupled Model Intercomparison Project (CMIP6), a two-step process was undertaken. First, a combined stratospheric aerosol dataset, the Global Space-based Stratospheric Aerosol Climatology (GloSSAC; 1979–2016), was constructed. Next, GloSSAC, along with information from ice cores and Sun photometers, was used to generate aerosol distributions, characteristics and optical properties to construct a more consistent stratospheric aerosol forcing dataset for models participating in CMIP6. This “version 3” of the stratospheric aerosol forcing has been endorsed for use in all contributing CMIP6 simulations. Recent updates to the underlying GloSSAC from version 1 to version 1.1 affected the 1991–1994 period and necessitated an update to the stratospheric aerosol forcing from version 3 to version 4. As version 3 remains the official CMIP6 input, quantification of the impact on radiative forcing and climate is both relevant and timely for interpreting results from experiments such as the CMIP6 historical simulations. This study uses two models, the Canadian Earth System Model version 5 (CanESM5) and the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1), to estimate the difference in instantaneous radiative forcing in simulated post-Pinatubo climate response when using version 4 instead of version 3. Differences in temperature, precipitation and radiative forcings are generally found to be small compared to internal variability. An exception to this is differences in monthly temperature anomalies near 24 km altitude in the tropics, which can be as large as 3 °C following the eruption of Mt. Pinatubo.
Envelope-driven comfort risk in residential demand response
Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.
Ultrafine Condensation Particle Counter Instrument Handbook
The Model 3776 Ultrafine Condensation Particle Counter (UCPC; pictured in Appendix A) is designed for researchers interested in airborne particles smaller than 20 nm. With sensitivity to particles down to 2.5 nm in diameter, this UCPC is ideally suited for atmospheric and climate research, particle formation and growth studies, combustion and engine exhaust research, and nanotechnology research.
The Role of Leaf Area Changes Within Plant CO 2 Physiological Impacts on the Global Hydrological Cycle
Rising atmospheric CO 2 concentrations enhance greenhouse warming and drive changes to plant physiology, leading to innumerable climate impacts. This study explores the impacts of plant responses on hydrological cycling at 2x preindustrial CO 2 concentrations by analyzing simulations that isolate plant physiological effects using the Community Earth System Model versions 1 and 2. We find that leaf area growth increases canopy evaporation, which offsets transpiration declines, and dampens changes in global mean evapotranspiration, precipitation, and runoff in a CESM2 experiment with dynamic leaf area. These leaf area impacts are also evident in the differences between CESM1 and CESM2, with CESM2 better capturing observed leaf area magnitudes but potentially overestimating leaf area-CO 2 sensitivity, highlighting the importance of plant CO 2 physiology on hydrological cycle changes and the need to improve its representation in climate models.
Climate effects of future aerosol reductions for achieving carbon neutrality in China
To limit the global warming to 1.5 °C above pre-industrial levels, beyond which the most dangerous impacts of climate change will occur, achieving carbon neutrality by the mid-21st century is essential. As the largest developing country and a significant contributor to carbon dioxide (CO 2 ) emissions, China has announced its ambitious climate commitment to pass carbon peak before 2030 and to achieve carbon neutrality by 2060. Both climate policies and regional clean air actions have been implemented for reductions in fossil fuel emissions, including the emissions of short-lived aerosols and precursors. Furthermore, in the context of pursuing carbon neutrality in China, aerosol reductions due to clean air actions and pollution control policies are very likely to have a great impact on climate. In this study, climate effects of aerosol reductions due to China's clean air actions under localized future emission scenarios are investigated using the Community Earth System Model version 1 (CESM1). Fully coupled and atmosphere-only experiments in years of carbon peak (2030) and carbon neutrality (2060) are performed with anthropogenic emissions of aerosols and precursors under “Current-goals” (Current) and “Carbon-Neutral” (Neutral) scenarios from the Dynamic Projection for Emissions in China (DPEC) model that consider socioeconomic development, climate policy, and pollution control actions (Figs. S1–S4 online). In addition, a present-day emissions simulation (PD) is conducted as the reference case (Supplementary materials online). Another sensitivity simulation is also conducted, with black carbon (BC) emissions set to follow the Neutral experiment but other emissions kept at the present-day levels (Neutral_BC), to quantify the relative roles of reducing strongly absorbing BC and other aerosols on future climate towards carbon neutrality. Greenhouse gases concentrations are kept at the 2015 levels in all simulations (Text S1 online).
Perovskite- and Dye-Sensitized Solar-Cell Device Databases Auto-generated Using ChemDataExtractor
The number of scientific publications reporting cutting-edge third-generation photovoltaic devices is increasing rapidly, owing to the pressing need to develop renewable-energy technologies that address the climate-change crisis. Consequently, the field could benefit from a central repository where photovoltaic-performance metrics, such as the power-conversion efficiency (η) are recorded. We present two automatically generated databases that contain photovoltaic properties and device material data for dye-sensitized solar cells (DSCs) and perovskite solar cells (PSCs), totalling 660,881 data entries representing 57,678 photovoltaic devices. The databases were generated by applying the text-mining toolkit ChemDataExtractor on a corpus of 25,720 articles. A multi-faceted evaluation, incorporating manual and automatic methods, was applied to ensure that the data contained therein were of the highest quality, with precision metrics ranging from 73.1% to 95.8%. The DSC database contains 475,045 entries representing 41,680 devices, and the PSC database contains 185,836 entries representing 15,818 devices. The databases are available in MongoDB and JSON formats, which can be queried in Python, R, Java and MATLAB for data-driven photovoltaic materials discovery.
Characterizing the localization of organic C on mineral surfaces: a correlative microscopy/spectroscopy approach
It is estimated that organic carbon (OC) in soils exceeds the amount of OC in atmosphere and in vegetation pools combined.1 Given the current changes in climate and increasing temperatures in the environment, the fraction of OC sequestered in soils and sediments is more sensitive to decomposition and release as CO 2 in the atmosphere. Evidence implies that sorption and association of dissolved OC with inorganic soil components, i.e., soil minerals, is a key mechanism that contributes to stabilization and retention of OC in soil environment. Studies have shown a direct correlation between sorption of dissolved OC and soil mineral surface properties and their surface area. In addition, properties of organic compounds such as chemical structure and functional groups play a significant role in interaction of dissolved organic species with mineral surfaces. Association of OC with minerals via ligand exchange reactions, polyvalent tertiary bonding, or complexation with metal ions, is found to be preferential and dependent on the organic compounds’ functional groups.
Stratospheric aerosol injection can weaken the carbon dioxide greenhouse effect
Abstract Stratospheric aerosol injection is a proposed method for offsetting greenhouse gas-induced warming by introducing scattering aerosols into the lower stratosphere to reflect sunlight. Here we explore a potentially more efficient alternative: weakening the Earth’s greenhouse effect by deploying absorptive aerosols in the upper stratosphere (~10 hPa). These aerosols warm the carbon dioxide emission level—where outgoing longwave radiation is most sensitive to temperature—thereby enhancing top-of-atmosphere infrared emission without altering atmospheric carbon dioxide concentrations. Idealized climate model simulations indicate that this approach can reduce global temperatures an order of magnitude more efficiently per unit aerosol mass than conventional scattering-based interventions. Although based on simplified model experiments lacking interactive aerosol processes and operational constraints, our results identify a distinct physical mechanism for climate intervention, arguing for further research into the impacts—especially potential unintended side effects—of injecting absorptive aerosols into the upper stratosphere as an alternative solar radiation management strategy.
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.
Photosynthetic capacity is reduced by warming but unaffected by elevated CO2 in seedlings of five boreal tree species
Abstract Increasing atmospheric CO2 concentrations fuel global warming, with boreal regions warming at a faster rate than many other areas. Boreal forests are an important component of the global carbon cycle, yet we have little data on photosynthetic responses of boreal trees to elevated CO2 (EC) and warming. We grew seedlings of 5 widespread North American boreal tree species (from Betula, Larix, Picea, and Pinus) under current (410 ppm) or elevated (750 ppm) CO2 and either ambient (+0 °C) or increased (+4 °C or +8 °C) temperature, then measured photosynthetic traits over a range of leaf temperatures. Our results were generally consistent across species: photosynthetic capacity (maximum rates of Rubisco carboxylation, Vcmax, and electron transport, Jmax) was unaffected by EC but decreased under +8 °C warming. Accordingly, net photosynthesis measured at the growth CO2 concentration (Agrowth) was reduced under warming and increased under EC. The thermal optimum for Agrowth (ToptA) increased by ∼1.8 °C with EC but increased with warming in only two species. In contrast, the activation energies and thermal optima for Vcmax and Jmax, which are used to estimate photosynthesis in Earth System Models, were unaffected by growth environment. There were a few interactions between growth, CO2, and warming. These results suggest increased photosynthesis of widespread boreal tree species under EC may be offset by future reductions in photosynthetic capacity related to warming. We also show that the temperature sensitivities of parameters used to estimate global photosynthesis in large-scale models are generally unaffected by simulated climate change in these species.
Examining the Impacts of Microphysical-Dynamical Feedbacks on Convective Clouds in Different Aerosol Environments Using Enhanced Observational and Modeling Strategies
This project investigated how microphysical–dynamical feedbacks influence deep convective clouds across a range of aerosol conditions, storm lifecycles, and meteorological regimes, and how these sensitivities depend on the modeling framework used to represent convection and microphysics. Using the Aerosol, Cloud, Precipitation, and Climate (ACPC) Working Group model intercomparison simulations of isolated deep convection in the Houston region, we found a robust warm-phase aerosol response in most cloud-resolving models. Increased aerosol loading tended to suppress warm-rain production, increase cloud water, and reduce surface rainfall and near-surface evaporation. These impacts were typically strongest early in the convective lifecycle, with the largest aerosol-driven differences occurring during the first half of storm evolution. The ice-phase response, on the other hand, varied widely across modeling frameworks, and differed in sign, timing, and vertical structure. Ice microphysical pathways and parameterizations are therefore leading sources of uncertainty in aerosol–deep convection interactions. Theoretical analyses further suggested that aerosol-driven invigoration through cold-phase processes was much weaker than previously hypothesized for cold-based storms, and in warm-based storms could even reduce updraft strength. These results imply that any invigoration signal is more likely linked to warm-phase processes and peaks early in storm development.
Unlocking Dysprosium Constraints for China’s 1.5 °C Climate Target
Some key low-carbon technologies, ranging from wind turbines to electric vehicles, are underpinned by the strong rare-earth-based permanent magnets of the Nd, Pr (Dy)–Fe–Nb type (NdFeB). These NdFeB magnets, which are sensitive to demagnetization with temperature elevation (the Curie point), require the addition of variable amounts of dysprosium (Dy), where an elevation of the Curie point is needed to meet operational conditions. Given that China is the world’s largest REE supplier with abundant REE reserves, the impact of an ambitious 1.5 °C climate target on China’s Dy supply chain has sparked widespread concern. Here, we explore future trends and innovation strategies associated with the linkage between Dy and NdFeBs under various climate scenarios in China. We find China alone is expected to exhaust the global present Dy reserve within the next 2–3 decades to facilitate the 1.5 °C climate target. By implementing global available innovation strategies, such as material substitution, reduction, and recycling, it is possible to avoid 48%–68% of China’s cumulative demand for Dy. Nevertheless, ongoing efforts in REE exploration and production are still required to meet China’s growing Dy demand, which will face competition from the United States, European Union, and other countries with ambitious climate targets. Here our analysis urges China and those nations to form wider cooperation in REE supply chains as well as in NdFeB innovation for the realization of a global climate-safe future.
Resolving Away Stratocumulus Biases in Modern Global Climate Models
Abstract Increased horizontal and vertical resolution in global atmospheric models can reduce a significant amount of the biases associated with subtropical marine stratocumulus. The sensitivity of offshore and coastal marine stratocumulus to different horizontal and vertical resolutions has been investigated by using Energy Exascale Earth System Model (E3SM) coupled with the novel Framework for Improvement by Vertical Enhancement which has been demonstrated as a viable tool to improve the representation of marine stratocumulus while saving computational cost. Our study shows that high vertical resolution is the key to improve marine stratocumulus simulations in E3SM. Concurrent horizontal and vertical resolution increases are needed for substantial overall reduction of stubborn marine stratocumulus biases over the coastal region but not necessarily in the offshore area.