Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Climate Change”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗
DOE OSTI2018

Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation

This paper provides projections of water withdrawals and consumption for electricity generation in India through 2050. Based on the results from five energy-economic modeling teams, the paper explores the implications of economic growth, power plant cooling policies, and electricity CO2 emissions reductions on water withdrawals and consumption. To isolate modeling differences, the five teams used harmonized assumptions regarding economic and population growth, the distribution of power plants by cooling technologies, and withdrawals and consumption intensities. The results demonstrate the different but potentially complementary implications of cooling technology policies and efforts to reduce CO2 emissions. The application of closed-loop cooling technologies substantially reduces water withdrawals but increases consumption. The water implications of CO2 emissions reductions, depend critically on the approach to these reductions. Focusing on wind and solar power reduces consumption and withdrawals; a focus on nuclear power increases both; and a focus on hydroelectric power could increase consumptive losses through evaporation.

electricity generation↗
DOE OSTI2015

A modeling study of irrigation effects on global surface water and groundwater resources under a changing climate

Abstract This study investigates the effects of irrigation on global water resources by performing and analyzing Community Land Model 4.0 (CLM4) simulations driven by downscaled/bias‐corrected historical simulations and future projections from five General Circulation Models (GCMs). For each climate scenario, three sets of numerical experiments were performed: (1) a CTRL experiment in which all crops are assumed to be rainfed; (2) an IRRIG experiment in which the irrigation module is activated using surface water (SW) to feed irrigation; and (3) a PUMP experiment in which a groundwater pumping scheme coupled with the irrigation module is activated for conjunctive use of surface water and groundwater (GW) for irrigation. The parameters associated with irrigation and groundwater pumping are calibrated based on a global inventory of census‐based water use compiled by the Food and Agricultural Organization (FAO). Our results suggest that irrigation could lead to two major effects: SW (GW) depletion in regions with irrigation primarily fed by SW (GW), respectively. Furthermore, irrigation depending primarily on SW tends to have larger impacts on low‐flow than high‐flow conditions, suggesting increased vulnerability to drought. By the end of the 21st century, combined effect of increased irrigation water demand and amplified temporal‐spatial variability of water supply may lead to severe local water scarcity for irrigation. Regionally, irrigation has the potential to aggravate/alleviate climate‐induced changes of SW/GW although such effects are negligible when averaged globally. Our study highlights the need to account for irrigation effects and sources in assessing regional climate change impacts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Multimodel Analysis of Future Land Use and Climate Change Impacts on Ecosystem Functioning

Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 2080–2099 period, carbon storage increases by up to 87 ± 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to −0.021 ± 0.007 and −0.004 ± 0.004 for SSP5xRCP85) and increase in runoff (+67 ± 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

land use change↗
NASA NTRS2019

How Do Climate Change Experiments Alter Plot-Scale Climate?

To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs.unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6° Celsius degrees (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1°Celsius degrees (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2° Celsius degrees (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design,and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses.

warming experiment↗
DOE OSTI2020

Predicting soil carbon changes in switchgrass grown on marginal lands under climate change and adaptation strategies

Abstract The United States Great Lakes Region (USGLR) is a critical geographic area for future bioenergy production. Switchgrass ( Panicum virgatum ) is widely considered a carbon (C)‐neutral or C‐negative bioenergy production system, but projected increases in air temperature and precipitation due to climate change might substantially alter soil organic C (SOC) dynamics and storage in soils. This study examined long‐term SOC changes in switchgrass grown on marginal land in the USGLR under current and projected climate, predicted using a process‐based model (Systems Approach to Land‐Use Sustainability) extensively calibrated with a wealth of plant and soil measurements at nine experimental sites. Simulations indicate that these soils are likely a net C sink under switchgrass (average gain 0.87 Mg C ha −1 year −1 ), although substantial variation in the rate of SOC accumulation was predicted (range: 0.2–1.3 Mg C ha −1 year −1 ). Principal component analysis revealed that the predicted intersite variability in SOC sequestration was related in part to differences in climatic characteristics, and to a lesser extent, to heterogeneous soils. Although climate change impacts on switchgrass plant growth were predicted to be small (4%–6% decrease on average), the increased soil respiration was predicted to partially negate SOC accumulations down to 70% below historical rates in the most extreme scenarios. Increasing N fertilizer rate and decreasing harvest intensity both had modest SOC sequestration benefits under projected climate, whereas introducing genotypes better adapted to the longer growing seasons was a much more effective strategy. Best‐performing adaptation scenarios were able to offset >60% of the climate change impacts, leading to SOC sequestration 0.7 Mg C ha −1 year −1 under projected climate. On average, this was 0.3 Mg C ha −1 year −1 more C sequestered than the no adaptation baseline. These findings provide crucial knowledge needed to guide policy and operational management for maximizing SOC sequestration of future bioenergy production on marginal lands in the USGLR.

09 BIOMASS FUELS↗
DOE OSTI2022

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

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A Stochastic Conceptual Modeling Approach for Examining the Effects of Climate Change on Streamflows in Mountain Basins

Abstract This study presents a modeling approach for examining how changes in climate affect streamflow in mesoscale mountain basins dominated by snowmelt runoff. A conceptual snowmelt-runoff model was developed that is forced by daily time series of temperature and precipitation. The model can be run using either observed climate data or artificial climate data generated from a GCM or a stochastic model. The model was applied to a case-study basin, the north fork of the Clearwater River in Idaho, using stochastically generated climate scenarios. Climate scenarios were generated using a contemporaneous auto-regressive integrated moving average (CARIMA) model for temperature and a precipitation model based on a two-state first-order Markov process. A baseline climate scenario was developed that represents recently observed temperature and precipitation conditions and then 15 additional climate scenarios that represent shifts in recent conditions. For each scenario, model application produced an ensemble of 50 streamflow traces each spanning 30 yr. Results show that an increase in temperature among scenarios leads to a decrease in streamflow and vice versa. Decreases in temperature shift the basin runoff to fully snowmelt dominated, whereas increases in temperature increase the frequency of midwinter runoff events. Increasing precipitation leads to increased runoff in cases where the temperature remains the same as the observed record, but not in cases where the temperature increases. The modeling approach presented here can be used by water managers to examine which types of climate change could require modifications in water planning and operations.

13 HYDRO ENERGY↗
DOE OSTI2024

Regional climate change: consensus, discrepancies, and ways forward

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

A common-sense climate index: is climate changing noticeably?

We propose an index of climate change based on practical climate indicators such as heating degree days and the frequency of intense precipitation. We find that in most regions the index is positive, the sense predicted to accompany global warming. In a few regions, especially in Asia and western North America, the index indicates that climate change should be apparent already, but in most places climate trends are too small to stand out above year-to-year variability. The climate index is strongly correlated with global surface temperature, which has increased as rapidly as projected by climate models in the 1980s. We argue that the global area with obvious climate change will increase notably in the next few years. But we show that the growth rate of greenhouse gas climate forcing has declined in recent years, and thus there is an opportunity to keep climate change in the 21st century less than "business-as-usual" scenarios.

Time↗
NASA NTRS2012

Public Perception of Climate Change and the New Climate Dice

"Climate dice", describing the chance of unusually warm or cool seasons, have become more and more "loaded" in the past 30 years, coincident with rapid global warming. The distribution of seasonal mean temperature anomalies has shifted toward higher temperatures and the range of anomalies has increased. An important change is the emergence of a category of summertime extremely hot outliers, more than three standard deviations (3 sigma) warmer than the climatology of the 1951-1980 base period. This hot extreme, which covered much less than 1% of Earth's surface during the base period, now typically covers about 10% of the land area. It follows that we can state, with a high degree of confidence, that extreme anomalies such as those in Texas and Oklahoma in 2011 and Moscow in 2010 were a consequence of global warming, because their likelihood in the absence of global warming was exceedingly small. We discuss practical implications of this substantial, growing, climate change.

Hansen, James↗
NASA NTRS2011

Climate Change Impacts and Responses: Societal Indicators for the National Climate Assessment

The Climate Change Impacts and Responses: Societal Indicators for the National Climate Assessment workshop, sponsored by the National Aeronautics and Space Administration (NASA) for the National Climate Assessment (NCA), was held on April 28-29, 2011 at The Madison Hotel in Washington, DC. A group of 56 experts (see list in Appendix B) convened to share their experiences. Participants brought to bear a wide range of disciplinary expertise in the social and natural sciences, sector experience, and knowledge about developing and implementing indicators for a range of purposes. Participants included representatives from federal and state government, non-governmental organizations, tribes, universities, and communities. The purpose of the workshop was to assist the NCA in developing a strategic framework for climate-related physical, ecological, and socioeconomic indicators that can be easily communicated with the U.S. population and that will support monitoring, assessment, prediction, evaluation, and decision-making. The NCA indicators are envisioned as a relatively small number of policy-relevant integrated indicators designed to provide a consistent, objective, and transparent overview of major variations in climate impacts, vulnerabilities, adaptation, and mitigation activities across sectors, regions, and timeframes. The workshop participants were asked to provide input on a number of topics, including: (1) categories of societal indicators for the NCA; (2) alternative approaches to constructing indicators and the better approaches for NCA to consider; (3) specific requirements and criteria for implementing the indicators; and (4) sources of data for and creators of such indicators. Socioeconomic indicators could include demographic, cultural, behavioral, economic, public health, and policy components relevant to impacts, vulnerabilities, and adaptation to climate change as well as both proactive and reactive responses to climate change. Participants provided inputs through in-depth discussion in breakout sessions, plenary sessions on break-out results, and several panels that provided key insights about indicators, lessons learned through experience with developing and implementing indicators, and thoughts on how the NCA could proceed to develop indicators for the NCA.

Kenney, Melissa A.↗
NASA NTRS2017

Our Globally Changing Climate

Since the Third U.S. National Climate Assessment (NCA3) was published in May 2014, new observations along multiple lines of evidence have strengthened the conclusion that Earth's climate is changing at a pace and in a pattern not explainable by natural influences. While this report focuses especially on observed and projected future changes for the United States, it is important to understand those changes in the global context (this chapter). The world has warmed over the last 150 years, especially over the last six decades, and that warming has triggered many other changes to Earth's climate. Evidence for a changing climate abounds, from the top of the atmosphere to the depths of the oceans. Thousands of studies conducted by tens of thousands of scientists around the world have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; disappearing snow cover; shrinking sea ice; rising sea level; and an increase in atmospheric water vapor. Rainfall patterns and storms are changing, and the occurrence of droughts is shifting.

Wuebbles, D. J.↗
NASA NTRS2012

Climate Change Detection and Attribution of Infrared Spectrum Measurements

Climate change occurs when the Earth's energy budget changes due to natural or possibly anthropogenic forcings. These forcings cause the climate system to adjust resulting in a new climate state that is warmer or cooler than the original. The key question is how to detect and attribute climate change. The inference of infrared spectral signatures of climate change has been discussed in the literature for nearly 30 years. Pioneering work in the 1980s noted that distinct spectral signatures would be evident in changes in the infrared radiance emitted by the Earth and its atmosphere, and that these could be observed from orbiting satellites. Since then, a number of other studies have advanced the concepts of spectral signatures of climate change. Today the concept of using spectral signatures to identify and attribute atmospheric composition change is firmly accepted and is the foundation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) satellite mission being developed at NASA. In this work, we will present an overview of the current climate change detection concept using climate model calculations as surrogates for climate change. Any future research work improving the methodology to achieve this concept will be valuable to our society.

Phojanamongkolkij, Nipa↗
DOE OSTI2012

Renewable Energy and Climate Change

The Intergovernmental Panel on Climate Change issued the Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) at http://srren.ipcc-wg3.de/ (May 2011 electronic version; printed form ISBN 978-1-107-60710-1, 2012). More than 130 scientists contributed to the report.* The SRREN assessed existing literature on the future potential of renewable energy for the mitigation of climate change within a portfolio of mitigation options including energy conservation and efficiency, fossil fuel switching, RE, nuclear and carbon capture and storage (CCS). It covers the six most important renewable energy technologies - bioenergy, direct solar, geothermal, hydropower, ocean and wind, as well as their integration into present and future energy systems. It also takes into consideration the environmental and social consequences associated with these technologies, the cost and strategies to overcome technical as well as non-technical obstacles to their application and diffusion.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2011

Responding to the Consequences of Climate Change

The talk addresses the scientific consensus concerning climate change, and outlines the many paths that are open to mitigate climate change and its effects on human activities. Diverse aspects of the changing water cycle on Earth are used to illustrate the reality climate change. These include melting snowpack, glaciers, and sea ice; changes in runoff; rising sea level; moving ecosystems, an more. Human forcing of climate change is then explained, including: greenhouse gasses, atmospheric aerosols, and changes in land use. Natural forcing effects are briefly discussed, including volcanoes and changes in the solar cycle. Returning to Earth's water cycle, the effects of climate-induced changes in water resources is presented. Examples include wildfires, floods and droughts, changes in the production and availability of food, and human social reactions to these effects. The ~lk then passes to a discussion of common human reactions to these forecasts of climate change effects, with a summary of recent research on the subject, plus several recent historical examples of large-scale changes in human behavior that affect the climate and ecosystems. Finally, in the face for needed action on climate, the many options for mitigation of climate change and adaptation to its effects are presented, with examples of the ability to take affordable, and profitable action at most all levels, from the local, through national.

Hildebrand, Peter H.↗
DOE OSTI2014

Implications of Small Modular Reactors for Climate Change Mitigation

Achieving climate policy targets will require large-scale deployment of low-carbon energy technologies, including nuclear power. The small modular reactor (SMR) is viewed as a possible solution to the problems of energy security as well as climate change. In this paper, we use an integrated assessment model (IAM) to investigate the evolution of a global energy portfolio with SMRs under a stringent climate policy. Technology selection in the model is based on costs; we use results from previous expert elicitation studies of SMR costs. We find that the costs of achieving a 2oC target are lower with SMRs than without. The costs are higher when large reactors do not compete for market share compared to a world in which they can compete freely. When both SMRs and large reactors compete for market share, reduction in mitigation cost is achieved only under advanced assumptions about SMR technology costs and future cost improvements. While the availability of SMRs could lower mitigation costs by a moderate amount, actual realization of these benefits would depend on the rapid up-scaling of SMRs in the near term. Such rapid deployment could be limited by several social, institutional and behavioral obstacles.

Iyer, Gokul C.↗
NASA NTRS2019

Multimodel Analysis of Future Land Use and Climate Change Impacts on Ecosystem Functioning

Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 2080–2099 period, carbon storage increases by up to 87 ± 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to −0.021 ± 0.007 and −0.004 ± 0.004 for SSP5xRCP85) and increase in runoff (+67 ± 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

Krause, A.↗