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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The ARM Data-oriented Metrics and Diagnostics Package for Climate Models - A New Tool for Evaluating Climate Models with Field Data

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Inter-comparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Thiele, O.↗
NASA NTRS1998

NASA's Earth Observing System: The Transition from Climate Monitoring to Climate Change Prediction

Earth's 4.5 billion year history is a study in change. Natural geological forces have been rearranging the surface features and climatic conditions of our planet since its beginning. There is scientific evidence that some of these natural changes have not only led to mass extinctions of species (e.g., dinosaurs), but have also severely impacted human civilizations. For instance, there is evidence that a relatively sudden climate change caused a 300-year drought that contributed to the downfall of Akkadia, one of the most powerful empires in the Middle-East region around 2200 BC. More recently, the "little ice age" from 1200-1400 AD forced the Vikings to abandon Greenland when temperatures there dropped by about 1.5 C, rendering it too difficult to grow enough crops to sustain the population. Today, there is compelling scientific evidence that human activities have attained the magnitude of a geological force and are speeding up the rate of global change. For example, carbon dioxide levels have risen 30 percent since the industrial revolution and about 40 percent of the world's land surface has been transformed by humans. We don't understand the cause-and-effect relationships among Earth's land, ocean, and atmosphere well enough to predict what, if any, impacts these rapid changes will have on future climate conditions. We need to make many measurements all over the world, over a long period of time, in order to assemble the information needed to construct accurate computer models that will enable us to forecast climate change. In 1988, the Earth System Sciences Committee, sponsored by NASA, issued a report calling for an integrated, long-term strategy for measuring the vital signs of Earth's climate system. The report urged that the measurements must all be intimately coupled with focused process studies, they must facilitate development of Earth system models, and they must be stored in an information system that ensures open access to consistent, long-term data. This committee emphasized that the only feasible way to collect these consistent, long-term data is through the use of space-based Earth "remote sensors" (instruments that can measure from a distance things like temperature).

King, Michael D.↗
NASA NTRS2007

A New Paradigm for Assessing the Role of Agriculture in the Climate System and in Climate Change

This paper discusses the diverse climate forcings that impact agricultural systems, and contrasts the current paradigm of using global models downscaled to agricultural areas (a top-down approach) with a new paradigm that first assesses the vulnerability of agricultural activities to the spectrum of environmental risk including climate (a bottom-up approach). To illustrate the wide spectrum of climate forcings, regional climate forcings are presented including land-use/land-cover change and the influence of aerosols on radiative and biogeochemical fluxes and cloud/precipitation processes, as well as how these effects can be teleconnected globally. Examples are presented of the vulnerability perspective, along with a small survey of the perceived drought impacts in a local area, in which a wide range of impacts for the same precipitation deficits are found. This example illustrates why agricultural assessments of risk to climate change and variability and of other environmental risks should start with a bottom-up perspective.

Pielke, Roger A., Sr.↗
NASA NTRS2010

Contributions to Future Stratospheric Climate Change: An Idealized Chemistry-Climate Model Sensitivity Study

Within the framework of an idealized model sensitivity study, three of the main contributors to future stratospheric climate change are evaluated: increases in greenhouse gas concentrations, ozone recovery, and changing sea surface temperatures (SSTs). These three contributors are explored in combination and separately, to test the interactions between ozone and climate; the linearity of their contributions to stratospheric climate change is also assessed. In a simplified chemistry-climate model, stratospheric global mean temperature is most sensitive to CO2 doubling, followed by ozone depletion, then by increased SSTs. At polar latitudes, the Northern Hemisphere (NH) stratosphere is more sensitive to changes in CO2, SSTs and O3 than is the Southern Hemisphere (SH); the opposing responses to ozone depletion under low or high background CO2 concentrations, as seen with present-day SSTs, are much weaker and are not statistically significant under enhanced SSTs. Consistent with previous studies, the strength of the Brewer-Dobson circulation is found to increase in an idealized future climate; SSTs contribute most to this increase in the upper troposphere/lower stratosphere (UT/LS) region, while CO2 and ozone changes contribute most in the stratosphere and mesosphere.

Hurwitz, M. M.↗
NASA NTRS2018

CLIMATE LECTURE 3: Building a Climate Model

Climate, or the average of day-to-day weather, can be very different at various points on Earth. The local climate in the Arabian Desert is hot and dry, while that in the Amazon River basin is hot and humid with frequent rain. In upstate New York, the climate changes from being warm in the summer with sporadic rain to cold in the winter with sporadic snow. Hawaii, on the other hand, has a pleasant climate all year long. However, the day-to-day weather at all of these locations is much more variable. There can be dry days in the Amazon jungle, and rainy days in the Arabian Desert. There are some days in winter that are warmer than some days in summer. For further contrast, daylight in Antarctica lasts up to six months at a time with freezing cold day-in day-out. Can a climate model be built that can reproduce all of this complex behavior?

Russell, Gary↗
NASA NTRS2019

Equilibrium Climate Sensitivity Estimated by Equilibrating Climate Models

The methods to quantify equilibrium climate sensitivity are still debated. We collect millennial length simulations of coupled climate models and show that the global mean equilibrium warming is higher than those obtained using extrapolation methods from shorter simulations. Specifically, 27 simulations with 15 climate models forced with a range of CO2 concentrations show a median 17% larger equilibrium warming than estimated from the first 150 years of the simulations. The spatial patterns of radiative feedbacks change continuously, in most regions reducing their tendency to stabilizing the climate. In the equatorial Pacific, however, feedbacks become more stabilizing with time. The global feedback evolution is initially dominated by the tropics, with eventual substantial contributions from the midlatitudes. Time dependent feedbacks underscore the need of a measure of climate sensitivity that accounts for the degree of equilibration, so that models, observations, and paleo proxies can be adequately compared and aggregated to estimate future warming.

Maria Rugenstein↗
NASA NTRSDate not supplied

Exploring the Climatic Impact of Bi-Modal Dust Particle Size Distributions During the MY34/2018 Global Dust Storm with the NASA Ames Mars Global Climate Model.

We have implemented a bi-modal dust lifting scheme in the NASA Ames Mars Global Climate Model (GCM) and investigated the climatic impact on the MY34/2018 Global Dust Storm (GDS). We found that the climate is measurably responsive to the inclusion of a second, smaller dust mode. Dust tends to be lifted through a deeper column in the atmosphere, which is reflected in the climate as changes to atmospheric temperature, tide amplitudes, and surface temperatures. Adding a modest fraction of a smaller dust mode improves simulations during the GDS compared to Curiosity semi-diurnal tide observations as well as Mars Climate Sounder (MCS) T15 brightness temperatures

R A Urata↗
DOE OSTI2022

Climate warming causes photobiont degradation and carbon starvation in a boreal climate sentinel lichen

The long-term potential for acclimation by lichens to changing climates is poorly known, despite their prominent roles in forested ecosystems. Although often considered “extremophiles,” lichens may not readily acclimate to novel climates well beyond historical norms. In a previous study, Evernia mesomorpha transplants in a whole-ecosystem climate change experiment showed drastic mass loss after 1 yr of warming and drying; however, the causes of this mass loss were not addressed. We examined the causes of this warming-induced mass loss by measuring physiological, functional, and reproductive attributes of lichen transplants. Severe loss of mass and physiological function occurred above +2°C of experimental warming. Loss of algal symbionts (“bleaching”) and turnover in algal community compositions increased with temperature and were the clearest impacts of experimental warming. Enhanced CO 2 had no significant physiological or symbiont composition effects. The functional loss of algal photobionts led to significant loss of mass and specific thallus mass (STM), which in turn reduced water-holding capacity (WHC). Although algal genotypes remained detectable in thalli exposed to higher stress, within-thallus photobiont communities shifted in composition toward greater diversity. The strong negative impacts of warming and/or lower humidity on Evernia mesomorpha were driven by a loss of photobiont activity. Analogous to the effects of climate change on corals, the balance of symbiont carbon metabolism in lichens is central to their resilience to changing conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

DISCOVR strain pipeline screening – Part II: Winter and summer season areal productivities and biomass compositional shifts in climate-simulation photobioreactor cultures

Assessing the seasonal biomass productivity and compositional shift dynamics under simulated outdoor culture conditions of the top 22 algae strains selected during Tier I flask screening is an important step in the further prioritization of strains with regard to outdoor pond cultivation. These top 22 strains were subjected to Tier II testing in the PNNL Laboratory Environmental Algae Pond Simulator (LEAPS) photobioreactors, simulating light and temperature conditions of 20 cm deep outdoor ponds during the Arizona winter and summer season. All strains were grown in two consecutive nutrient-replete batch culture experiments at their particular optimal medium salinity to quantify their respective seasonal linear-phase areal biomass productivities. To determine biomass compositional shifts in response to nutrient-depletion, the LEAPS cultures were allowed to enter a 9-day nutrient depletion phase at the end of the second batch run. The following strains were evaluated in winter-season climate-simulated cultures and are listed in the order from highest (7.9 g m -2 day -1 ) to lowest (2.3 g m -2 day -1 ) areal N-replete biomass productivity: Monoraphidium minutum 26B-AM, Tetraselmis striata LANL1001, Chlorella vulgaris LRB AZ-1201, Micractinium reisseri NREL14-F2, Monoraphidium sp. MONOR1, Chlorella vulgaris NREL4-C12, Scenedesmus obliquus UTEX393, Scenedesmus acutus LRB-AP-0401, Nannochloropsis oceanica CCAP849/10, and Stichococcus minutus CCALA727. The following strains were evaluated in summer-season climate-simulated cultures and are listed in the order from highest (31.8 g m -2 day -1 ) to lowest (14.2 g m -2 day -1 ) areal N-replete biomass productivity: Picochlorum renovo NREL39-A8, Scenedesmus obliquus UTEX393, Porphyridium cruentum CCMP675, Picochlorum celeri TG2-WT-CSM/EMRE, Chlorella sorokiniana DOE1116, Stichococcus minor CCMP819, Picochlorum oklahomensis CCMP2329, Chlorella sorokiniana DOE1412 (UTEXB3016), Scenedesmus rubescens NREL46B-D3, Picochlorum soloecismus DOE101, Tetraselmis striata LANL1001, Scenedesmus obliquus DOE 0152.z, and Agmenellum quadruplicatum UTEX2268. All LEAPS cultures experienced a significant reduction in areal biomass productivity in response to nutrient-depletion, from 7-16% in the winter season simulation and up to 1-60% in the summer season simulation. Finally, for 10 of the strains tested, the carbohydrate content more than doubled upon nutrient depletion, and for 9 strains, the lipid content increased by over 50% of the initial content.

09 BIOMASS FUELS↗
DOE OSTI2021

The Importance of Weather and Climate to Energy Systems: A Workshop on Next Generation Challenges in Energy–Climate Modeling

More than 80 international participants, representing weather, climate, and energy systems research, joined two 4-hour remote sessions to highlight and prioritize ongoing and future challenges in energy-climate modelling. The workshop had two primary goals: to build a deeper engagement across the “energy” and “climate” research communities, and to identify and begin to address the scientific challenges associated with modelling climate risk in energy systems.

17 WIND ENERGY↗
DOE OSTI2020

Impacts of Wildfire Aerosols on Global Energy Budget and Climate: The Role of Climate Feedbacks

Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, the Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols’ impacts on global climate with emphasis on the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be -0.78 ± 0.29 W m -2 , which is mostly from shortwave RE due to aerosol–cloud interactions (REaci; -0.70 ± 0.20 W m -2 ). The associated global annual-mean surface air temperature (SAT) change ΔT is -0.64 ± 0.16 K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to reamplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ΔT) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ΔT) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N) but increases in the Southern Hemisphere tropical ocean, which is associated with the southward shift of the intertropical convergence zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal forest fire aerosol indirect effects, through intensifying the cross-equator atmospheric heat transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of Tropical Cyclone Wind Forcing on the Global Climate in a Fully Coupled Climate Model

Tropical cyclones (TCs) alter upper-ocean temperature and influence ocean heat content via enhanced turbulent mixing. A better understanding of the role of TCs within the climate system requires a fully coupled modeling framework, where TC-induced ocean responses feed back to the atmosphere and subsequently to the climate mean state and variability. Here, we investigate the impacts of TC wind forcing on the global ocean and the associated feedbacks within the climate system using the fully coupled Community Earth System Model version 1.3 (CESM1.3). Using the low-resolution version of CESM1.3 (1° atmosphere and ocean grid spacing) with no intrinsic TCs, we conduct a suite of sensitivity experiments by inserting TC winds extracted from a high-resolution (0.25° atmosphere grid spacing) TC-permitting simulation into the low-resolution model. Results from the low-resolution TC experiment are compared to a low-resolution control simulation to diagnose TCs’ impact. We found that the added TC winds can increase ocean heat content by affecting ocean vertical mixing, air–sea enthalpy fluxes, and cloud amount. Here, the added TCs can influence mean SST, precipitation, ocean subsurface temperature, and ocean mixed layer depth. We found a strengthening of the wind-driven subtropical cells and a weakening of the Atlantic meridional overturning circulation due to the changes of surface buoyancy fluxes. TCs in the model cause anomalous equatorward ocean heat convergence in the deep tropics and an increase of poleward ocean heat transport out of the subtropics. Our modeling results provide new insights into the multiscale interactions between TCs and the coupled climate system.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

meteorological parameters↗
NASA NTRS2015

Climate Data Initiative: A Geocuration Effort to Support Climate Resilience

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. In this paper, we introduce the concept of geocuration and define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium We present the Climate Data Initiative (CDI) project as an exemplar example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. We describe the geocuration process used in CDI project, lessons learned, and suggestions to improve similar geocuration efforts in the future.

virtual collections↗
NASA NTRS2020

Using Climate Models to Learn: Investigating the Phenomenon of Increasing Surface Air Temperatures Using a Global Climate Modeling Approach

Since 1880, Earth’s average global temperature has increased by approximately 1.4 °F (0.8 °C). Approximately two-thirds of the warming has occurred since 1975 (Wuebbles, Easterling, Hayhoe, et al. 2017). Despite consensus about global climate change (GCC) within the scientific community, students struggle to comprehend - why temperatures are increasing globally - at what rate this change is occurring, and - how climate scientists predict Earth’s future climate. These challenges are due, in part, to the abstraction inherent to understanding GCC, a phenomenon that occurs over long periods of time (past and future), and over large regions (regional and global). With the adoption of the Next Generation Science Standards (NGSS Lead States 2013), GCC is emphasized at the secondary school level, with a focus on analyzing and understanding the evidence for GCC (HS-ESS3-1), climate modeling (HS-ESS2-6, HS-ESS3-5), and the impact of humans on the environment (HS-LS2-7, HS-ESS3-6).

climate models↗
DOE OSTI2024

The National Climate Data Base (NCDB): A Bias-Corrected High-Resolution Climate Dataset

Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.

climate data↗
NASA NTRS2017

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Climate Change; GCMs; Climate Model Subset; Repres↗