Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Climate Change Modeling”

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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effects of Climate Change on Capacity Expansion Decisions of an Electricity Generation Fleet in the Southeast U.S.

The electric power sector in the United States faces many challenges related to climate change. On the demand side, climate change could shift demand patterns due to increased air temperatures. On the supply side, climate change could lead to deratings of thermal units due to changes in air temperature, water temperature, and water availability. Past studies have typically analyzed these risks separately. Here, we developed an integrated, multimodel framework to analyze how compounding risks of climate-change impacts on demand and supply affect long-term planning decisions in the power system. In the southeast U.S., we found that compounding climate-change impacts could result in a 35% increase in installed capacity by 2050 relative to the reference case. Participation of renewables, particularly solar, in the fleet increased, driven mostly by the expected increase in summertime peak demand. Such capacity requirements would increase investment costs by approximately 31 billion (USD 2015) over the next 30 years, compared to the reference case. These changes in investment decisions align with carbon emission mitigation strategies, highlighting how adaptation and mitigation strategies can converge.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe–Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon–use efficiency (CUE), vegetation C turnover time ( τ veg ), leaf C fraction (F leaf ), specific leaf area (SLA), and leaf area index (LAI)–level photosynthesis (P LAI ), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τ veg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. Furthermore, these results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Thunderstorm Activity Under Intermediate and Extreme Climate Change Scenarios

Assessing how increasing greenhouse gas concentrations may modify regional climates is an ongoing challenge. Relatively little work has examined how climate change may influence processes related to regional thunderstorm activity. This is important to consider in areas where thunderstorms are important for maintaining regional hydroclimates. Here, this study focuses on three convection-allowing climate simulations—namely, a retrospective simulation (1990–2005) and two possible climate change scenarios (2085–2100)—with domains encompassing the conterminous United States. Regional and seasonal variability is noted in the response of thunderstorm activity as measured by thresholds in simulated radar reflectivity factor in the two climate change scenarios. A decrease in thunderstorm activity is projected for the Southern Plains, whereas the Southeast and Midwest experience an increase in thunderstorm activity. An examination of environmental parameters related to thunderstorm activity reveals an overall increase in convective instability but spatially varying changes in convective inhibition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Fusing subnational with national climate action is central to decarbonization: the case of the United States

Approaches that root national climate strategies in local actions will be essential for all countries as they develop new nationally determined contributions under the Paris Agreement. The potential impact of climate action from non-national actors in delivering higher global ambition is significant. Sub-national action in the United States provides a test for how such actions can accelerate emissions reductions. We aggregated U.S. state, city, and business commitments within an integrated assessment model to assess how a national climate strategy can be built upon non-state actions. We find that existing commitments alone could reduce emissions 25% below 2005 levels by 2030, and that enhancing actions by these actors could reduce emissions up to 37%. We show how these actions can provide a stepped-up basis for additional federal action to reduce emissions by 49%—consistent with 1.5 °C. Our analysis demonstrates sub-national actions can lead to substantial reductions and support increased national action.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Antarctic shelf ocean warming and sea ice melt affected by projected El Niño changes

Antarctic shelf ocean warming affects melt of ice shelf/sheets and sea ice but projected changes vary vastly across climate models. A projected increase in El Niño variability has been found to slow future mid-latitude Southern Ocean warming but how this impacts the Antarctic shelf ocean is unknown. Here we show that a projected increase in El Niño variability accelerates Antarctic shelf ocean warming, hastening ice shelf/sheet melt but slowing sea ice reduction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization

How much elevated atmospheric CO2 concentration (eCO2) contributes to the terrestrial carbon sink (NEP) is a debated issue (Friedlingstein et al., 1995; Field & Raupach, 2004; Schimel et al., 2015; Keenan et al., 2016; Huntzinger et al., 2017). The results from Free-Air CO2-Enrichment (FACE) experiments at the site scale show that eCO2 generally increase plant growth and net ecosystem CO2 uptake for a few years after exposure to eCO2, but the effects were highly variable across sites (Jastrow et al., 2005; De Graaff et al., 2006), which poses a challenge for scaling up these local observations. Here, we extract the simulated short-term responses of NEP to eCO2 from global carbon models using a substitute pulse-response approach, and compare them with site-scale responses from FACE experiments in temperate ecosystems. In 12 gridded terrestrial ecosystem models examined, the large-scale NEP sensitivity to eCO2 across the Northern Hemisphere (NH) temperate region is linearly related to the site-scale sensitivity across different ecosystems. We use this emergent relationship, together with the observed response to eCO2 in the FACE site-scale data to estimate a data constrained effect of eCO2 on the NH temperate NEP of 0.73 ± 0.22 Pg C yr-1 per hundred parts per million (ppm) of CO2 increase during the past five decades. This is 26% higher than the mean of the model ensemble. Among the models, those with carbon-nitrogen interactions underestimate the sensitivity of NEP to eCO2, suggesting overly strong nitrogen-limitations on carbon uptake. We further identify that the NEP sensitivity to eCO2 at NH temperate scale is linearly correlated with that at global scale across the models. Extrapolating the constrained NH eCO2 effect to the global terrestrial carbon sink provides an estimate of 4.1 ± 1.5 Pg C yr-1 [100 ppm]-1. Large uncertainties remain regarding the global response broadly inferred from temperate FACE data, due to the lack of observations in boreal and tropical regions, emphasizing the importance of deploying new FACE experiments in those regions.

Liu, Yongwen↗
DOE OSTI2023

A compendium of bacterial and archaeal single-cell amplified genomes from oxygen deficient marine waters

Oxygen-deficient marine waters referred to as oxygen minimum zones (OMZs) or anoxic marine zones (AMZs) are common oceanographic features. They host both cosmopolitan and endemic microorganisms adapted to low oxygen conditions. Microbial metabolic interactions within OMZs and AMZs drive coupled biogeochemical cycles resulting in nitrogen loss and climate active trace gas production and consumption. Global warming is causing oxygen-deficient waters to expand and intensify. Therefore, studies focused on microbial communities inhabiting oxygen-deficient regions are necessary to both monitor and model the impacts of climate change on marine ecosystem functions and services. Here we present a compendium of 5,129 single-cell amplified genomes (SAGs) from marine environments encompassing representative OMZ and AMZ geochemical profiles. Of these, 3,570 SAGs have been sequenced to different levels of completion, providing a strain-resolved perspective on the genomic content and potential metabolic interactions within OMZ and AMZ microbiomes. Hierarchical clustering confirmed that samples from similar oxygen concentrations and geographic regions also had analogous taxonomic compositions, providing a coherent framework for comparative community analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluating the efficacy and equity of environmental stopgap measures

Contemporary environmental policy is rife with measures that do not fully resolve a problem, but instead are proposed to “buy time” for the development and future implementation of more durable solutions. In this perspective, we define such measures as “stopgap measures,” and examine examples from wildfire risk management, hydrochlorofluorocarbon regulation, and Colorado River water management. We introduce an analytical framework to assess stopgaps, and apply this framework to solar geoengineering, a controversial stopgap for climate action. Studying stopgaps as a novel category of policy and management measures can help us understand the why stopgaps emerge, and weigh the equity and efficacy of stopgaps against other policy proposals

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Water Energy Simulation Toolset

The Water-Energy Simulation Toolset (WEST) is an interactive simulation model that helps visualize impacts of different stakeholders on water quantity and quality of a watershed. The case study is applied for the Snake River Basin with the fictional name Cutthroat River Basin. There are four groups of stakeholders of interest: hydropower, agriculture, flood control, and environmental protection. Currently, the quality component depicts nitrogen-nitrate contaminant. Users can easily interact with the model by changing certain inputs (climate change, fertilizer inputs, etc.) to observe the change over the entire system. Users can also change certain parameters to test their management policy.

Nguyen, Thuy↗
DOE OSTI2024

Understanding the Biases in Global Monsoon Simulations from the Perspective of Atmospheric Energy Transport

Understanding global monsoon (GM) variability and projecting its future changes rely heavily on climate models. However, climate models generally show pronounced biases in GM simulations, and the reasons for this remain unclear. Here, in this study, we evaluate the performance of 20 pairs of climate models that participated in both phase 5 of the Coupled Model Intercomparison Project (CMIP5) and phase 6 of CMIP (CMIP6) and identify the sources of their GM simulation biases from an energy transport perspective. The multimodel mean improvement in CMIP6 compared to CMIP5 is demonstrated by the increasing skill scores for various GM metrics from 0.20–0.79 to 0.48–0.83. More specifically, the dry biases in the Northern Hemisphere Summer Monsoon (NHSM) precipitation in CMIP5 [root-mean-square error (RMSE): 1.85 mm day −1 ] are reduced in CMIP6 (RMSE: 1.66 mm day −1 ). This higher simulation skill is associated with higher skill in simulating the precipitation-solstitial mode, monsoon intensity, and monsoon domains. The improvement in the NHSM precipitation simulation results from that in the meridional transport of atmospheric energy. Atmospheric energy budget analysis shows that the negative biases in downward surface longwave radiation and northward energy transport are smaller in CMIP6 than in CMIP5 in the boreal summer, resulting in a more realistic interhemispheric thermal contrast and meridional gradient of moist static energy. However, a major weakness of the CMIP6 models is found in the Southern Hemisphere Summer Monsoon precipitation simulation due to the positive bias in the top-of-the-atmosphere downward longwave radiation. This study shows that reasonably reproducing the meridional global atmospheric energy transportation is necessary for skillful GM simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Exploring the sensitivity of global ocean circulation to future ice loss from Antarctica

The sensitivity of the global ocean circulation and climate to large increases in iceberg calving and meltwater discharges from the Antarctic Ice Sheet (AIS) are rarely studied and poorly understood. The requirement to investigate this topic is heightened by growing evidence that the West Antarctic Ice Sheet (WAIS) is vulnerable to rapid retreat and collapse on multidecadal-to-centennial timescales. Observations collected over the last 30 years indicate that the WAIS is now losing mass at an accelerated and that a collapse may have already begun in the Amundsen Sea sector. In addition, some recent future model simulations of the AIS show the potential for rapid ice sheet retreat in the next 50 – 300 years. Such a collapse would be associated with the discharge of enormous volumes of ice and meltwater to the Southern Ocean. This project funds PI Condron to begin assessing the sensitivity of the global ocean circulation to projected increases in meltwater discharge and iceberg calving from the AIS for the next 50 – 100 years. A series of climate model simulations will determine changes in ocean circulation and temperature at the ice sheet grounding line, the role of mesoscale ocean eddies in mixing and transporting freshwater away from the continent to deep water formation regions, and the likely impact on the northward transport of heat to Europe and North America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Impacts of Climate Change on the Generation Potential of Solar and Wind Energy Systems in India

Low-carbon energy sources like wind and solar are essential for decarbonizing the electricity sector. In addition, the cost of electricity generated from these sources has plummeted over the last decade. Therefore, these energy sources are poised to take a significant share of the total installed capacity soon. However, they are susceptible to the impacts of climate change as their generation potential depends on the weather conditions. Estimating the installed capacity requirements of solar and wind energy to decarbonize the power sector without accounting for these possible changes in generation potential could lead to missing out on the set climate goals and meeting future electricity demand. This study evaluates the effect of climate change on the generation potential of wind and solar energy systems in India for two future periods, 2050 and 2070, under two climate scenarios or Shared Socioeconomic Pathway (SSP): SSP245 and SSP585. Almost all regions show a decrease, and most regions show a significant decline (>5%) in the generation potential of solar Photovoltaic (PV) as compared to 2010 levels under both climate scenarios and future periods. The changes in the generation potential of wind energy are more significant (>10%), and the majority of regions show a decline in generation potential. Southwestern and central regions show an increase in wind generation potential for 2070 as compared to 2050 levels under the SSP245 scenario and the SSP585 scenario, respectively.

climate change↗
NASA NTRS2009

Spatial and Temporal Inter-Relationship between Anomalies and Trends of Temperature, Moisture, Cloud Cover and OLR as Observed by AIRS/AMSU on Aqua

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiled; atmospheric humidity profiles, fractional cloud clover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extra-tropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear Sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to evaluate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year time period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

Susskind, Joel↗
NASA NTRS2008

Spatial and Temporal Inter-Relationships between Anomalies and Trends of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, fractional cloud cover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extratropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to validate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

Susskind, Joel↗
NASA NTRS2014

Heat-Related Mortality in a Warming Climate: Projections for 12 U.S. Cities

Heat is among the deadliest weather-related phenomena in the United States, and the number of heat-related deaths may increase under a changing climate, particularly in urban areas. Regional adaptation planning is unfortunately often limited by the lack of quantitative information on potential future health responses. This study presents an assessment of the future impacts of climate change on heat-related mortality in 12 cities using 16 global climate models, driven by two scenarios of greenhouse gas emissions. Although the magnitude of the projected heat effects was found to differ across time, cities, climate models and greenhouse pollution emissions scenarios, climate change was projected to result in increases in heat-related fatalities over time throughout the 21st century in all of the 12 cities included in this study. The increase was more substantial under the high emission pathway, highlighting the potential benefits to public health of reducing greenhouse gas emissions. Nearly 200,000 heat-related deaths are projected to occur in the 12 cities by the end of the century due to climate warming, over 22,000 of which could be avoided if we follow a low GHG emission pathway. The presented estimates can be of value to local decision makers and stakeholders interested in developing strategies to reduce these impacts and building climate change resilience.

heat-related mortality↗
NASA NTRS2014

Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 kilometers to 0.6 kilometers. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed.

Hamann, U.↗