Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “CLIMATE”

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.

At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analysis of heat and mass transfer potential of a dew-point cooling tower in different climatic conditions

In this study, the performance of the Dew-Point Cooling Tower (DPCT) was analyzed for different factors in a variety of climate conditions. For this purpose, a dedicated numerical model describing heat and mass transfer processes was developed and validated. The results of the numerical simulations allowed to analyze the potential of utilizing the heat and mass transfer process with the dew-point phenomenon for water cooling. It was established that the operational parameters that have a high impact on the performance of the DPCT are: inlet water temperature and inlet air humidity ratio. It was also established that DPCT achieves the highest COP and Specific Cooling Capacity for cold subtropical highland climates and that it achieves highest Wet-bulb Effectiveness for monsoon-influenced humid subtropical climates. In conclusion, the regions where all the efficiency factors achieved above-average values included warm, arid, and desert climates.

42 ENGINEERING↗
DOE OSTI2025

Climate-extreme modeling framework for sustainable flood management in the Arabian Peninsula

Evaluating extreme precipitation events (EPEs) is essential for building climate-resilient water management strategies, but it remains a major challenge in ungauged basins. Using the 26,070 km 2 Wadi al-Rummah basin in central Saudi Arabia as a case study, we developed an alternative, reliable, cost-effective satellite-based framework that combines empirically derived EPE thresholds, imagery-calibrated 2D hydrodynamic modeling, GRACE water-storage diagnostics, and bias-corrected CMIP6 projections to assess flood hazards and recharge potential under current and future climate scenarios in ungauged basins. The integrated approach and the resulting findings followed four key steps: (1) Identified a 22.5 mm EPE threshold, the 80th percentile of 3-day GPM/IMERG rainfall (2000–2024), aligned with flood-triggering events (Nov 2018: 23–28 mm; Apr, 2023: 42 mm); (2) Developed and calibrated a RiverFlow2D model using Sentinel-2 and PlanetScope imagery for the November 2018 flood, accurately reproducing flood depth and extent (RMSE ≤0.31 m; fuzzy-Dice ≥0.91), and estimating runoff (41 %), infiltration (25 %), and evaporation (34 %); (3) Independently validated the model with the April 2023 event (RMSE ≤0.35 m; fuzzy-Dice ≥0.86); (4) Conducted climate projections (2025–2100) from five bias-corrected NEX-GDDP CMIP6 models that revealed a 34 % increase in EPE intensity under SSP2-4.5 and 48 % under SSP5-8.5 scenarios, relative to 20th-century baselines. Our findings indicate that while intensifying extremes in the 21st century increase flood risk, the results highlight the potential for episodic recharge if effective retention strategies are employed, and offer a transferable model for climate-informed planning in data-scarce arid regions.

CMIP6↗
DOE OSTI2017

Effects of climate change on streamflow extremes and implications for reservoir inflow in the United States

The magnitude and frequency of hydrometeorological extremes are expected to increase in the conterminous United States (CONUS) over the rest of this century, and their increase will significantly impact water resource management. While previous efforts focused on the effects of reservoirs on downstream discharge, the effects of climate change on reservoir inflows in upstream areas are not well understood. We evaluated the large-scale climate change effects on extreme hydrological events and their implications for reservoir inflows in 178 headwater basins across CONUS using the Variable Infiltration Capacity (VIC) hydrologic model. The VIC model was forced with a 10-member ensemble of global circulation models under the Representative Concentration Pathway 8.5 that were dynamically downscaled using a regional climate model (RegCM4) and bias-corrected to 1/24° grid cell resolution. The results projected an increase in the likelihood of flood risk by 44% for a majority of subbasins upstream of flood control reservoirs in the central United States and increased drought risk by 11% for subbasins upstream of hydropower reservoirs across the western United States. Increased risk of both floods and droughts can potentially make reservoirs across CONUS more vulnerable to future climate conditions. In conclusion, this study estimates reservoir inflow changes over the next several decades, which can be used to optimize water supply management downstream.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

An automatic performance model-based scheduling tool for coupled climate system models

The prediction of the climate system is highly depended on the efficient integration of observations and simulations of the Earth. This is regarded as a canonical example of the cyber-physical system. The climate system model, the simulation engine in this cyber-physical system, is one of most challenging applications in scientific computing. It utilizes the multi-physics simulation that couples multiple components, conducts decadal to millennium simulations, and has long been an important application on supercomputers. However, current climate system models suffer from the inefficient task scheduling methods resulting in an intolerable simulation time. Take the Community Earth System Model (CESM), the most widely used climate system model, as an example, one major reason that CESM suffers from bad performances is the huge overhead to rationally distribute processes among the coupled heterogeneous components. According to the report of NCAR, every percent improvement in CESM performance frees up to the equivalent of $250,000 in computing resources in their scientific experiments. To address such challenge, our paper firstly constructs a lightweight and accurate performance model for effectively capturing and predicting the heterogeneous time-to-solution performance of end-to-end CESM components with a given simulation configuration. Then, based on the performance model, we further propose an efficient scheduling strategy based on rectangular packing method to determine the best process layout among different components, and the process numbers assigned to each component. Our evaluations show that we can achieve 58% average run time reductions on CESM comparing to the widely used sequential process layout for a scale of 144 to 480 cores on typical CPU clusters. And we can save 4 million CPU hours when we conduct one standard scientific experiment (a 2870-year simulation), which equals to save $40,089 with a charge of $0.01 per CPU hour. Meanwhile, 26% extra performance improvements could also be gained in our methods comparing to the heuristic branch and bound algorithm with the guidance of the known curve-fitting performance model.

58 GEOSCIENCES↗
DOE OSTI2026

Climate-eutrophication-anoxia interactions in Late Glacial Soppensee, Switzerland: Forcings, non-linear responses and recovery

Combined effects of climate warming and anthropogenic nutrient loadings lead to lake eutrophication and anoxia globally. Because of chemical feedbacks, lakes under multiple stressors often respond in non-linear ways. However, it remains unclear whether climate change alone can lead to non-linear lake responses in the absence of anthropogenic nutrient disturbances. Here, we investigate the interactions between climate variability, nutrient cycling and trophic state changes, mixing regimes, anoxia and related chemical feedback in a small kettle-hole lake in Switzerland during Late Glacial times (15.2–12.6 cal ka BP), a period known for high-amplitude climate change in pre-anthropogenic times. After its formation during Heinrich Stadial 1 (>15 cal ka BP), Soppensee was oligotrophic and well-mixed. Soppensee became eutrophic and developed anoxia at 14.25 cal ka BP. Phosphorus (P) was released from sediments through the reductive dissolution of Fe-oxyhydroxides, fuelling eutrophication. Eutrophication lagged the Bølling warming (14.65 cal ka BP) by 400 years, suggesting that rising temperatures were not the trigger for eutrophication. Instead, eutrophication responded non-linearly to forest closure (threshold at 76 % arboreal pollen AP), which shielded Soppensee from wind mixing, enhancing lake stratification, anoxia and P release, intensifying eutrophication. These conditions ended during the 200-years cold period of the Aegelsee Oscillation (GI-1d, ca. 14.0 cal ka BP) when the landscape regionally opened (AP<76 %); the lake became well-mixed, oxygenated and P was efficiently sequestered. Throughout the Allerød (13.9–12.8 cal ka BP), enhanced Fe input prompted diagenetic vivianite formation, sequestering P in sediments, naturally remediating lake eutrophication despite closed forests, warm temperatures, lake stratification and anoxia.

Environmental sciences↗
DOE OSTI2023

Evaluating Multimodel Ensemble Seasonal Climate Forecasts on Rangeland Plant Production in the California Annual Grassland

Seasonal precipitation and temperature directly affect total plant production in the California Annual Grassland (CAG). Technological advances have resulted in skillful seasonal climate forecasts (i.e., significant correlations between actual and forecasted climate), which could be input into plant production models to inform stocking and other rangeland management decisions. This study presents a procedure for forecasting plant production in the CAG ecosystem to predict annual plant production for grazing, restoration, or other rangeland management practices using a combination of historical gridMET climate data and seasonal hindcasts (i.e., retrospective forecasts, from the North American Multi-Model Ensemble program). Further, the results of this study first confirmed high forecast skill, throughout the growing season at all sites. We also identified skillful plant production forecasts across most of the growing season at two sites and in three of the seven forecasting months at one study site. Forecasting climate and end-of-year plant production across the growing season at three CAG sites allowed us to identify the places and times in the growing season when forecasting might be most helpful in informing management decisions. Integrating plant production forecasting into rangeland management practices could significantly improve rangeland management outcomes. These procedures provide a user guide for creating plant production forecasts for any given area of interest and may be applicable across a wide range of other agricultural and rangeland management systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Influences of nitrogen fertilization and climate regime on the above-ground biomass yields of miscanthus and switchgrass: A meta-analysis

Perennial grasses are touted as sustainable feedstocks for energy production. Such benefits, however, may be offset if excessive nitrogen (N) fertilization leads to economic and environmental issues. Moreover, as yields respond to changes in climate, nutrient requirements will change, and thus guidance on minimal N inputs is necessary to ensure sustainable bioenergy production. Here, a pairwise meta-analysis was conducted to investigate the effects of N fertilization (amount and duration) and climate on the above-ground biomass yields of miscanthus ( Miscanthus x giganteus ) and switchgrass ( Panicum virgatum L. ). Both regression models and meta-analyses showed that switchgrass was more responsive to N than miscanthus, although both showed significant and positive N effects. Meta-analysis further showed that the positive growth response of miscanthus to N application increased with N addition rates of 60–300 kg N ha -1 year -1 , but the magnitude of the response decreased with the number of years of fertilization (duration). N effects on switchgrass biomass increased and peaked at rates of 120–160 kg N ha -1 year -1 and 5–6 years of N inputs, but diminished for rates >300 kg N ha -1 year -1 and >7 years. Meta-analysis further revealed that the influences of N on switchgrass increased with both mean annual temperature and precipitation. Miscanthus yields were less responsive to climate than switchgrass yields. This meta-analysis helps fill a gap in estimation of biofeedstock yields based on N fertilization and could help better estimate minimum N requirements and soil management strategies for miscanthus and switchgrass cultivation across climatic conditions, thereby improving the efficiency and sustainability of bioenergy cropping systems.

09 BIOMASS FUELS↗
DOE OSTI2017

Quantifying the impacts of agricultural management and climate change on soil organic carbon changes in the uplands of Eastern China

In order to implement optimal farming practices for increasing soil organic carbon (SOC) in agro-ecosystems, there is a need for understanding how management practices and climate change alter SOC levels. This study quantified the influence of agricultural management practices and climatic factors on SOC changes in Eastern China’s upland-crop fields in northern Jiangsu Province for the period of 2010–2039, by using the DeNitrification-DeComposition (DNDC, version 9.5) model. We utilized the currently most detailed soil database, which is at a scale of 1:50,000, containing 17,024 soil polygons derived from 983 upland soil profiles. Across all the examined scenarios of agricultural management practices, our results show that the carbon sequestration potential in the upper layer soil (0–50 cm) of the study area varied from 6.93 to 155.11 Tg C during 2010–2039, with an average rate of 59 to 1317 kg C ha-1 year-1. As a promising alternative, the combined scenario of crop residue return rate of 50% and farmyard manure incorporation rate of 50% is recommended for agricultural management practice in this region. Meanwhile, climate conditions play a significant role in the annual SOC changes as well. Air temperature increase of 2–4 °C leads to 3.41–7.51 Tg C decrease in SOC under conventional management for the entire study region. Decreasing or increasing precipitation by 20% would increase 0.57 Tg C or decrease 1.09 Tg C under the conventional management scenario, respectively. Additionally, among all the soil groups, the fluvo-aquic soils have the highest C sequestration rate in most scenarios. Our findings could be used to inform optimal agricultural management toward climate mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO x ), ammonia (NH 3 ), and nitrous oxide (N 2 O). Here, the propensity of NO x and NH 3 to generate ozone and fine particulate matter (PM) and associated impacts on health are highly variable, whereas the climate impacts of long-lived N 2 O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially-resolved, monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the agricultural emissions of Nr from across the United States. We then apply a reduced-form air pollution health effects model to assess air quality impacts from NO x and NH 3 and a social cost of N 2 O to assess the climate impacts. Assuming an $\$$8.2 million Value of a Statistical Life (VSL) and a $\$$13,100/ton social cost of N 2 O, the air quality impacts are a factor of ~7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Machine learning-based bias-corrected future projections of ozone concentrations from a chemistry-climate model

Reliable projection of future near-surface ozone is crucial for air quality management and health risk assessment. However, potential biases in spatial distribution, magnitude and trends in ozone concentrations simulated by global chemistry-climate models limit their applicability in regional-scale evaluations. In this study, LightGBM, a machine learning (ML) algorithm is applied to correct biases in CESM2-simulated ozone concentrations over China, the United States and Europe and calibrate future ozone projections under two diverse Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) scenarios from 2020 to 2060. The ML-based correction significantly improves the spatial distribution and reduces the model bias by 40%–60%. It also reverses the potentially incorrect trend of ozone change under SSP1-2.6 in eastern China. When applying ML-based bias correction to CESM2 future projections, warm season mean ozone concentrations decrease across China, the United States, and Europe by –13.5, –17.9, and –13.7 µg/m³, respectively, between 2020 and 2060 in SSP1-2.6, while they increase by 9.4, 2.0, and 5.2 µg/m³ in SSP5-8.5. Decomposition analysis show that changes in anthropogenic emissions dominate future ozone changes in both scenarios, while strong climate penalty from ozone changes occurs in polluted eastern China and climate benefit is found in western China, the United States and Europe under SSP5-8.5. These findings demonstrate the value of combining ML with chemistry-climate models to produce more accurate air quality projections, thereby informing more effective and region-specific environmental protection strategies.

Chemistry Model↗
DOE OSTI2018

Biased Estimates of Changes in Climate Extremes From Prescribed SST Simulations

Large climate model ensembles are widely used to quantify changes in climate extremes. Here we demonstrate that model-based estimates of changes in the probability of temperature extremes at 1.5°C global warming regionally differ if quantified using prescribed sea surface temperatures (SSTs) instead of using a fully coupled climate model. Based on the identical climate model used in two experimental setups, we demonstrate that particularly over the tropics and Australia estimates of the changes in the odds of annual temperature extremes can be up to more than a factor of 5 to 10 larger using prescribed SSTs rather than a fully coupled model configuration. The two experimental designs imply a different perspective on framing projections. If experiments conditional on prescribed observed SSTs are interpreted as unconditional real-world projections, they project changes in extremes that are systematically biased high and overconfident. Our results illustrate the importance of carefully considering experimental design when interpreting projections of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Timescale for Detecting the Climate Response to Stratospheric Aerosol Geoengineering

Stratospheric aerosol geoengineering could be used to maintain global mean temperature despite increased atmospheric greenhouse gas (GHG) concentrations, for example to meet a 1.5C or 2C target. While this might reduce many climate change impacts, the resulting climate would not be the same as one with the same global mean temperature due to lower GHG concentrations. The primary question we consider is how long it would take to detect these differences in a hypothetical deployment. We use a recently available 20-member ensemble of stratospheric sulfate aerosol geoengineering simulations in which SO2 is injected at four different latitudes to maintain not just the global mean temperature, but also the interhemispheric and equator-to-pole gradients. This multiple-latitude strategy better matches the climate changes from increased GHG, while the ensemble allows us both to estimate residual differences even when they are small compared to natural variability, and to estimate the statistics of variability. We first construct a linear emulator to predict the model responses for different scenarios. Under an RCP4.5 scenario in which geoengineering maintains a 1.5C target (providing end-of-century cooling of 1.7C), the change in global mean precipitation is projected to have a signal-to-noise ratio (SNR) greater than one after only 11 years. However, in this scenario, the projected temperature and precipitation changes at a grid-scale are typically small enough that in many regions this threshold is still not reached by the end of this century. These results provide some context for the projected magnitude of climate-changes associated with a limited deployment of stratospheric aerosol cooling.

42 ENGINEERING↗
DOE OSTI2019

Modeling Climate Change Impacts on an Arctic Polygonal Tundra: 1. Rates of Permafrost Thaw Depend on Changes in Vegetation and Drainage

Model projections of permafrost thaw during the next century diverge widely. Here we used ecosys to examine how climate change will affect permafrost thaw in a polygonal tundra at Barrow AK. The model was tested against diurnal and seasonal variation in energy exchange, soil heat flux, soil temperature ( T s ), and active layer depth (ALD) measured during 2014 and 2015, and interannual variation in ALD measured from 1991 to 2015. During RCP 8.5 climate change from 2015 to 2085, increases in T a and precipitation ( P ) to 6.2 °C and 27% above current values, and in atmospheric CO 2 concentrations ( C a ) to 763 μmol mol -1 , altered energy exchange by increasing leaf area index of dominant sedge relative to that of moss. Increased Ca and sedge leaf area index imposed greater stomatal control of transpiration and reduced soil heat fluxes, slowing soil warming, limiting increases in evapotranspiration, and thereby causing gradual soil wetting. Consequently, increases in surface T s and ALD of 2.4–4.7 °C and 21–24 cm above current values were modeled after 70 years. ALD increase was slowed if model boundary conditions were altered to improve landscape drainage. These rates were smaller than those of earlier modeling studies, some of which did not account for changes in vegetation, but are closer to those derived from current studies of warming impacts in the region. Therefore, accounting for climate change effects on vegetation density and composition, and consequent effects on surface energy budgets, will cause slower increases in T s and ALD to be modeled during climate change simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Changes in Wood Biomass and Crop Yields in Response to Projected CO 2 , O 3 , Nitrogen Deposition, and Climate

As the world's population increases, so will the demand for food and timber resources. Though carbon dioxide (CO 2 ) fertilization and, to a lesser extent, nitrogen (N) deposition are expected to increase future resource production, changes in ozone (O 3 ) and climate have the potential to decrease production due to increased phytotoxic damage, drought, and heat stress. To determine how crop and timber production may change in the future, we use the Community Land Model version 4.5 with prognostic crops to simulate responses of wood biomass and crop yields to CO 2 , O 3 , N deposition, and climate under Representative Concentration Pathway 8.5 forcings. Generally, rising CO 2 increases wood biomass and crop yields, while projected climate change causes decreases. Small projected changes in O 3 and N deposition do not strongly affect yields, though additional research is needed on future O 3 and N deposition trends and impacts. By the end of the 21st century, global wood biomass increases by ~16% due to the dominating impact of CO 2 . The positive effect of CO 2 on future crop yields is muted by the negative impacts of climate, with a ~5% net global increase. Future projections suggest that rice and wheat yields typically increase under the combination of future forcings, whereas soy and corn yields are regionally variable. While short-term resource management strategies can benefit from planting heat-tolerant species and cultivars, technological advances and intensification, among other management strategies not included here, must be employed to meet the future demand for these resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

High Climate Sensitivity in the Community Earth System Model Version 2 (CESM2)

The Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long-term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. We report CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.

58 GEOSCIENCES↗
DOE OSTI2020

A Partial Coupling Method to Isolate the Roles of the Atmosphere and Ocean in Coupled Climate Simulations

This study describes the formulation and application of a partial coupling method that disentangles the coupling between the atmosphere and ocean and isolates the atmosphere- and ocean-driven components of the coupled climate interactions. In contrast to strategies using stand-alone simulations with prescribed atmosphere or ocean states, the climate components in the partially coupled method remain coupled, but the impact of ocean circulation changes is removed from the air-sea interaction using temperature-like tracers. The partially coupled simulation thereby suppresses the ocean-driven interaction and isolates an atmosphere-driven interaction only. The ocean-driven component can be inferred by comparing climate response in the partially coupled simulation with that of a standard fully coupled one. The partial coupling approach is applied to decompose the fully coupled climate response to CO 2 quadrupling into atmosphere- and ocean-driven components. The linearity of the decomposition is validated by simulating the ocean-driven response using another complimentary partially coupled simulation forced only with the atmosphere-driven anomalous surface fluxes. A comparison of the two partially coupled simulations with the fully coupled simulation indicates that the sum of the atmosphere- and ocean-driven components accurately describes the fully coupled response. The decomposition identifies several robust atmosphere- and ocean-driven features of the global warming and provides new insights into the impacts of atmospheric feedbacks on the Atlantic overturning circulation and sea ice response to CO 2 increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Fast Climate Responses to Aerosol Emission Reductions During the COVID-19 Pandemic

The reduced human activities and associated decreases in aerosol emissions during the COVID-19 pandemic are expected to affect climate. Assuming emission changes during lockdown, back-to-work and post-lockdown stages of COVID-19, climate model simulations show a surface warming over continental regions of the Northern Hemisphere. In January–March, there was an anomalous warming of 0.05–0.15 K in eastern China, and the surface temperature increase was 0.04–0.07 K in Europe, eastern United States, and South Asia in March–May. The longer the emission reductions undergo, the warmer the climate would become. The emission reductions explain the observed temperature increases of 10–40% over eastern China relative to 2019. A southward shift of the ITCZ is also seen in the simulations. This study provides an insight into the impact of COVID-19 pandemic on global and regional climate and implications for immediate actions to mitigate fast global warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulating Observations of Southern Ocean Clouds and Implications for Climate

Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds.

54 ENVIRONMENTAL SCIENCES↗