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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Theory of optimal weighting of data to detect climatic change

A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

Bell, T. L.↗
DOE OSTI2020

Global Market and Economic Welfare Implications of Changes in Agricultural Yields Due to Climate Change

The economic welfare effects of climate change on global agriculture will be mediated by several complex biophysical and economic processes. For a given emissions scenario, these include: (1) the response of the climate system to anthropogenic forcing, (2) the response of crop yields to climate system and carbon dioxide changes, given baseline improvements in crop yields, (3) the response of agricultural markets to crop yield changes, and (4) the economic welfare implications of such market responses. In this paper, we use information about the first two processes from available climate-crop model comparison studies to analyze implications for the third and fourth processes. Applying the range of crop yield changes in a Global Integrated Assessment Model (GCAM) highlights several important economic relationships. First, we find a consistent relationship between global cropland area and yield change that is approximately orthogonal to the relationship between regional cropland area and yield change. Second, we find that the change in economic welfare, expressed as total surplus change per unit economic output, peaks during the 21st century. Third, we find that, at the global level, changes in yield affect both producer surplus and consumer surplus. Specifically, surplus changes to producers and consumers are always opposite in sign, although which economic actors gain or lose varies with the sign of yield change for any given commodity. Taken together, these results contribute to a growing body of research on climate-induced changes on agriculture by highlighting several economic relationships that are robust to differences in the underlying biophysical responses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying uncertainty in aggregated climate change risk assessments

High-level assessments of climate change impacts aggregate multiple perils into a common framework. This requires incorporating multiple dimensions of uncertainty. Here we propose a methodology to transparently assess these uncertainties within the ‘Reasons for Concern’ framework, using extreme heat as a case study. We quantitatively discriminate multiple dimensions of uncertainty, including future vulnerability and exposure to changing climate hazards. High risks from extreme heat materialise after 1.5–2 °C and very high risks between 2–3.5 °C of warming. Risks emerge earlier if global assessments were based on national risk thresholds, underscoring the need for stringent mitigation to limit future extreme heat risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Boundary spanning increases knowledge and action on invasive species in a changing climate

Abstract Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary‐spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary‐spanning activities could support proactive, research‐informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary‐spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non‐members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non‐members and short‐term members more frequently identifying range‐shifting neonative species and their impacts on native communities as higher priorities compared to long‐term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range‐shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication : Although real‐world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary‐spanning efforts to address other global change challenges to conservation.

Evans, Annette E.↗
DOE OSTI2020

River Regulation Alleviates the Impacts of Climate Change on US Thermoelectricity Production

Climate change and anthropogenic activities can both influence stream temperature, which is a critical indicator of thermoelectric power generation potential. Previous studies emphasized the vulnerability of power-generation systems to climate warming (ref 1, 2). Despite the fact that two-thirds of the global rivers are regulated by dams (ref 3), the relative impacts of water management and climate change on stream temperature and thermoelectric production have not yet been evaluated. Using an integrated modeling system applied to the conterminous United States, simulations confirm the dominant role of climate change in shaping the future trends of stream temperature. However, water management, reservoir regulation in particular, can mitigate the stream temperature warming and reduce the frequency and magnitude of extreme high stream temperatures through redistribution of the seasonal streamflow. Moreover, water management can alleviate the loss of power plant usable capacity from climate change to the level of reduced warming from emission mitigation. By regulating the flow and temperature regimes, water management is a promising adaptation measure to alleviate climate change induced effects in the water-energy nexus.

Zhang, Xiao↗
DOE OSTI2021

Impact of vegetation physiology and phenology on watershed hydrology in a semiarid watershed in the Pacific Northwest in a changing climate

Concurrent with changes in climate conditions, increases in atmospheric composition and transport can affect land surface processes by regulating physiological and phenological responses of plants, and consequently perturb water, carbon, and nitrogen (N) dynamics at multiple scales. Howerver, the relationships bwtween plants physiological and phenological and land surface processes in a changing climate are less well known due to the limitation of representing palnts properties in traditional hydrological models. In this study, we use the Community Land Model version 5 (CLM5) to investigate how projected changes in large scale atmospheric conditions can affect hydrologic and biogeochemical dynamics in the Upper Columbia-Priest Rapids (UCPR) watershed, a typical semi-arid watershed located in the north-western United States dominated by croplands. Six numerical experiments considering climate change, CO2 concentration, and N deposition consistent with the Representative Concentration Pathways (RCPs) 4.5 and 8.5 are performed at 1-km resolution over the period of 2015-2099. Our results show that, compared with historical results (1985-2014), the elevated CO2 directly increases plants N uptake rates that provide additional leaf N to enhance photosynthesis by the end of 21st century (2070-2099). The higher GPP leads to changes in stomatal resistance and increased leaf area index (LAI) that affect evaporatranspiration (ET) and its components. As a result of stomatal responses to a higher CO2 concentration, ET over corn fields declines by 24.6 mm yr-1 under RCP4.5, and by 64.0 mm yr-1 under RCP8.5, respectively by the end of the century from its historical mean of 428 mm yr-1. Meanwhile, ET over soybean fields increases by 27.7 mm yr-1 under RCP4.5 and 9.98 mm yr-1 under RCP8.5 from its historical mean of 507 mm yr-1 as a result of CO2 fertilization as soybeans are able to uptake more N to increase LAI significantly. Furtherfore, the changes in physiological and phenological in corn and soybean can strongly modulate water budget terms over the watershed in response to expected changes in greenhouse gas concentrations and atmospheric composition. Additionally, increases in CO2 concentration and N deposition are beneficial for improving water use efficiency of corn and soybean, therefore lead to less water consumption per unit gram of carbon produced from these crops. Our study elucidates the need to jointly consider effects of surface climate and atmospheric composition and transport in understanding and predicting watershed hydrologic and biogeochemical responses, especially for an agricultural watershed.

Zhu, Bowen↗
DOE OSTI2020

Climate change alters flood magnitudes and mechanisms in climatically-diverse headwaters across the northwestern United States

Abstract Flooding caused by high streamflow events poses great risk around the world and is projected to increase under climate change. This paper assesses how climate change will alter high streamflow events by changing both the prevalence of different driving mechanisms (i.e. ‘flood generating processes’) and the magnitude of differently generated floods. We present an analysis of simulated changes in high streamflow events in selected basins in the hydroclimatically diverse Pacific Northwestern United States, classifying the events according to their mechanism. We then compare how the different classes of events respond to changes in climate at the annual scale. In a warmer future, high flow events will be caused less frequently by snowmelt and more frequently by precipitation events. Also, precipitation-driven high flow events are more sensitive to increases in precipitation than are snowmelt-driven high flow events, so the combination of the increase in both frequency and magnitude of precipitation-driven high flow events leads to higher flood likelihood than under each change alone. Our comparison of the results from two emissions pathways shows that a reduction in global emissions will limit the increase in magnitude and prevalence of these precipitation-driven events.

S Chegwidden, Oriana (ORCID:0000000313763835)↗
DOE OSTI2015

A Geographic Mosaic of Climate Change Impacts on Terrestrial Vegetation: Which Areas Are Most at Risk?

Changes in climate projected for the 21st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2021

Methodology to Assess the Changing Risk of Yield Failure Due to Heat and Drought Stress Under Climate Change

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return period between yields falling 15% below previous five year Olympic average yield) responds to changes of the underlying yield distributions under climate change. Relative distributions are used to capture differences in the entire yield distribution between baseline and climate change scenarios, and to further decompose them into changes in the location and shape of the distribution. The methodology is applied here for the case of rainfed wheat and grain maize across Europe using an ensemble of crop models under three climate change scenarios with simulations conducted at 25 km resolution. Under climate change, maize generally displayed shorter return periods of yield failures (with changes under RCP 4.5 between −0.3 and 0 years compared to the baseline scenario) associated with a shift of the yield distribution towards lower values and changes in shape of the distribution that further reduced the frequency of high yields. This response was prominent in the areas characterized in the baseline scenario by high yields and relatively long return periods of failure. Conversely, for wheat, yield failures were projected to become less frequent under future scenarios (with changes in the return period of −0.1 to +0.4 years under RCP 4.5) and were associated with a shift of the distribution towards higher values and a change in shape increasing the frequency of extreme yields at both ends. Our study offers an approach to quantify the changes in yield distributions that drive crop yield failures. Actual risk assessments additionally require models that capture the variety of drivers determining crop yield variability and scenario climate input data that samples the range of probable climate variation.

Climate risk assessment↗
DOE OSTI2015

A Climate Change Vulnerability Assessment Report for the National Renewable Energy Laboratory: May 23, 2014 -- June 5, 2015

The U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), in Golden, Colorado, focuses on renewable energy and energy efficiency research. Its portfolio includes advancing renewable energy technologies that can help meet the nation's energy and environmental goals. NREL seeks to better understand the potential effects of climate change on the laboratory--and therefore on its mission--to ensure its ongoing success. Planning today for a changing climate can reduce NREL's risks and improve its resiliency to climate-related vulnerabilities. This report presents a vulnerability assessment for NREL. The assessment was conducted in fall 2014 to identify NREL's climate change vulnerabilities and the aspects of NREL's mission or operations that may be affected by a changing climate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2013

Achieving Climate Change Absolute Accuracy in Orbit

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5-50 micron), the spectrum of solar radiation reflected by the Earth and its atmosphere (320-2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a "NIST [National Institute of Standards and Technology] in orbit." CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

Wielicki, Bruce A.↗
DOE OSTI2015

Climate change impacts on US agriculture and forestry: benefits of global climate stabilization

Increasing atmospheric carbon dioxide levels, higher temperatures, altered precipitation patterns, and other climate change impacts have already begun to affect US agriculture and forestry, with impacts expected to become more substantial in the future. There have been numerous studies of climate change impacts on agriculture or forestry, but relatively little research examining the long-term net impacts of a stabilization scenario relative to a case with unabated climate change. We provide an analysis of the potential benefits of global climate change mitigation for US agriculture and forestry through 2100, accounting for landowner decisions regarding land use, crop mix, and management practices. The analytic approach involves a combination of climate models, a crop process model (EPIC), a dynamic vegetation model used for forests (MC1), and an economic model of the US forestry and agricultural sector (FASOM-GHG). We find substantial impacts on productivity, commodity markets, and consumer and producer welfare for the stabilization scenario relative to unabated climate change, though the magnitude and direction of impacts vary across regions and commodities. Although there is variability in welfare impacts across climate simulations, we find positive net benefits from stabilization in all cases, with cumulative impacts ranging from $32.7 billion to $54.5 billion over the period 2015-2100. Our estimates contribute to the literature on potential benefits of GHG mitigation and can help inform policy decisions weighing alternative mitigation and adaptation actions.

agricultural modeling↗
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↗