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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Using nuclear observations to improve climate research and GHG emission estimates – the NuClim project

Project NuClim (Nuclear observations to improve Climate research and GHG emission estimates) aims to use high-quality measurements of atmospheric radon activity concentration and ambient radioactivity to advance climate science and improve radiation protection and nuclear surveillance capabilities. It is supported by new metrological capabilities developed in the EMPIR project 19ENV01 traceRadon. This work reviews the scientific objectives of project NuClim in terms of both climate science and radiological protection, and provides an overview of the NuClim field campaign and the various nuclear measurements being implemented within the scope of the project.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

The sensitivity of a general circulation model to Saharan dust heating

During the Northern summer, sporadic outbreaks of wind borne Saharan dust are carried out over the Atlantic by the tropical easterlies. Optical depths due to the dust can reach 3 near the African coast, and the dust cloud can be detected as far west as the Caribbean Sea (Carlson, 1979). In order to obtain insight into the possible effects of Saharan dust on the weather and climate of North Africa and the tropical Atlantic Ocean, simulation experiments have been performed with the Climate Model of the Goddard Laboratory for Atmospheric Sciences. The most recent version of the model is described by Randall (1982). The model produces realistic simulations of many aspects of the observed climate and its seasonal variation.

Randall, D. A.↗
NASA NTRS2000

Diurnal Variability of the Hydrologic Cycle and Radiative Fluxes: Comparisons Between Observation and a GCM

The simulated diurnal cycle is in many ways an ideal test bed for new physical parameterizations. The purpose of this paper is to compare observations from the Tropical Rainfall Measurement Mission, the Earth Radiation Budget Experiment, the International Satellite Cloud Climatology Project, the Clouds and the Earth's Radiant Energy System Experiment, and the Anglo-Brazilian Amazonian Climate Observation Study with the diurnal variability of the Amazonian hydrologic cycle and radiative energy budget as simulated by the Colorado State University general circulation model, and to evaluate improvements and deficiencies of the model physics. The model uses a prognostic cumulus kinetic energy (CKE) to relax the quasi-equilibrium closure of the Arakawa-Schubert cumulus parameterization. A parameter, alpha, is used to relate the CKE to the cumulus mass flux. This parameter is expected to vary with cloud depth, mean shear, and the level of convective activity, but up to now a single constant value for all cloud types has been used. The results of the present study show clearly that this approach cannot yield realistic simulations of both the diurnal cycle and the monthly mean climate state. Improved results are obtained using a version of the model in which alpha is permitted to vary with cloud depth.

Lin, Xin↗
NASA NTRS2015

The AgMIP Coordinated Global and Regional Assessments (CGRA) of Climate Change Impacts on Agriculture and Food Security

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to construct a protocol-based framework enabling regional assessments (led by regional experts and modelers) that can provide consistent inputs to global economic and integrated assessment models. These global models can then relay important global-level information that drive regional decision-making and outcomes throughout an interconnected agricultural system. AgMIPs community of nearly 800 climate, crop, livestock, economics, and IT experts has improved the state-of-the-art through model intercomparisons, validation exercises, regional integrated assessments, and the launch of AgMIP programs on all six arable continents. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) of climate change impacts on agriculture and food security to link global and regional crop and economic models using a protocol-based framework. The CGRA protocols are being developed to utilize historical observations, climate projections, and RCPsSSPs from CMIP5 (and potentially CMIP6), and will examine stakeholder-driven agricultural development and adaptation scenarios to provide cutting-edge assessments of climate changes impact on agriculture and food security. These protocols will build on the foundation of established protocols from AgMIPs 30+ activities, and will emphasize the use of multiple models, scenarios, and scales to enable an accurate assessment of related uncertainties. The CGRA is also designed to provide the outputs necessary to feed into integrated assessment models (IAMs), nutrition and food security assessments, nitrogen and carbon cycle models, and additional impact-sector assessments (e.g., water resources, land-use, biomes, urban areas). This presentation will describe the current status of CGRA planning and initial prototype experiments to demonstrate key aspects of the protocols before wider implementation ahead of the IPCC Sixth Assessment Report.

models↗
NASA NTRS2018

A Study of the Carbon Cycle Using NASA Observations and the GEOS Model

The Goddard Earth Observing System (GEOS) model has been developed in the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center. From its roots in chemical transport and as a General Circulation Model, the GEOS model has been extended to an Earth System Model based on a modular construction using the Earth System Modeling Framework (ESMF), combining elements developed in house in the GMAO with others that are imported through collaborative research. It is used extensively for research and for product generation, both as a free-running model and as the core of the GMAO's data assimilation system. In recent years, the GMAO's modeling and assimilation efforts have been strongly supported by Piers Sellers, building on both his earlier legacy as an observationally oriented model developer and his post-astronaut career as a dynamic leader into new territory. Piers' long-standing interest in the carbon cycle and the combination of models with observations motivates this presentation, which will focus on the representation of the carbon cycle in the GEOS Earth System Model. Examples will include: (i) the progression from specified land-atmosphere surface fluxes to computations with an interactive model component (Catchment-CN), along with constraints on vegetation distributions using satellite observations; (ii) the use of high-resolution satellite observations to constrain human-generated inputs to the atmosphere; (iii) studies of the consistency of the observed atmospheric carbon dioxide concentrations with those in the model simulations. The presentation will focus on year-to-year variations in elements of the carbon cycle, specifically on how the observations can inform the representation of mechanisms in the model and lead to integrity in global carbon dioxide simulations. Further, applications of the GEOS model to the planning of new carbon-climate observations will be addressed, as an example of the work that was strongly supported by Piers in the last months of his leadership of Earth Science at NASA Goddard.

Pawson, Steven↗
NASA NTRS2012

The Added Value to Global Model Projections of Climate Change by Dynamical Downscaling: A Case Study over the Continental U.S. using the GISS-ModelE2 and WRF Models

Dynamical downscaling is being increasingly used for climate change studies, wherein the climates simulated by a coupled atmosphere-ocean general circulation model (AOGCM) for a historical and a future (projected) decade are used to drive a regional climate model (RCM) over a specific area. While previous studies have demonstrated that RCMs can add value to AOGCM-simulated climatologies over different world regions, it is unclear as to whether or not this translates to a better reproduction of the observed climate change therein. We address this issue over the continental U.S. using the GISS-ModelE2 and WRF models, a state-of-the-science AOGCM and RCM, respectively. As configured here, the RCM does not effect holistic improvement in the seasonally and regionally averaged surface air temperature or precipitation for the individual historical decades. Insofar as the climate change between the two decades is concerned, the RCM does improve upon the AOGCM when nudged in the domain proper, but only modestly so. Further, the analysis indicates that there is not a strong relationship between skill in capturing climatological means and skill in capturing climate change. Though additional research would be needed to demonstrate the robustness of this finding in AOGCM/RCM models generally, the evidence indicates that, for climate change studies, the most important factor is the skill of the driving global model itself, suggesting that highest priority should be given to improving the long-range climate skill of AOGCMs.

Racherla, P. N.↗
DOE OSTI2021

Increasing large wildfires over the western United States linked to diminishing sea ice in the Arctic

Abstract The compound nature of large wildfires in combination with complex physical and biophysical processes affecting variations in hydroclimate and fuel conditions makes it difficult to directly connect wildfire changes over fire-prone regions like the western United States (U.S.) with anthropogenic climate change. Here we show that increasing large wildfires during autumn over the western U.S. are fueled by more fire-favorable weather associated with declines in Arctic sea ice during preceding months on both interannual and interdecadal time scales. Our analysis (based on observations, climate model sensitivity experiments, and a multi-model ensemble of climate simulations) demonstrates and explains the Arctic-driven teleconnection through regional circulation changes with the poleward-shifted polar jet stream and enhanced fire-favorable surface weather conditions. The fire weather changes driven by declining Arctic sea ice during the past four decades are of similar magnitude to other leading modes of climate variability such as the El Niño-Southern Oscillation that also influence fire weather in the western U.S.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Comparison of Radiative Energy Flows in Observational Datasets and Climate Modeling

This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10Wm(exp -2) each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30Wmexp -2) over trade wind cumulus regions, yet smaller CRE by about -30Wm(exp -2) over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15Wm(exp -2) smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.

Raschke, Ehrhard↗
NASA NTRS2001

Demonstration of Imaging Fourier Transform Spectrometer (FTS) Performance for Planetary and Geostationary Earth Observing

The combination of massively parallel spatial sampling and accurate spectral radiometry offered by imaging FTS makes it extremely attractive for earth and planetary remote sensing. We constructed a breadboard instrument to help assess the potential for planetary applications of small imaging FTS instruments in the 1 - 5 micrometer range. The results also support definition of the NASA Geostationary Imaging FTS (GIFTS) instrument that will make key meteorological and climate observations from geostationary earth orbit. The Planetary Imaging FTS (PIFTS) breadboard is based on a custom miniaturized Bomen interferometer that uses corner cube reflectors, a wishbone pivoting voice-coil delay scan mechanism, and a laser diode metrology system. The interferometer optical output is measured by a commercial infrared camera procured from Santa Barbara Focalplane. It uses an InSb 128x128 detector array that covers the entire FOV of the instrument when coupled with a 25 mm focal length commercial camera lens. With appropriate lenses and cold filters the instrument can be used from the visible to 5 micrometers. The delay scan is continuous, but slow, covering the maximum range of +/- 0.4 cm in 37.56 sec at a rate of 500 image frames per second. Image exposures are timed to be centered around predicted zero crossings. The design allows for prediction algorithms that account for the most recent fringe rate so that timing jitter produced by scan speed variations can be minimized. Response to a fixed source is linear with exposure time nearly to the point of saturation. Linearity with respect to input variations was demonstrated to within 0.16% using a 3-point blackbody calibration. Imaging of external complex scenes was carried out at low and high spectral resolution. These require full complex calibration to remove background contributions that vary dramatically over the instrument FOV. Testing is continuing to demonstrate the precise radiometric accuracy and noise characteristics.

Revercomb, Henry E.↗
NASA NTRS2011

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Whiteman, David N.↗
NASA NTRS1983

The sensitivity of a general circulation model to Saharan dust heating

Evidence is accumulating that tropospheric aerosols, such as Saharan dust, can significantly influence weather and climate. The Climate Model of the Goddard Laboratory for Atmospheric Sciences is presently used to assess the possible effects of Saharan dust on the weather and climate of North Africa and the tropical Atlantic Ocean. The three-dimensional model solves the conservation equations for the horizontal wind vector, potential temperature, water vapor mixing ratio, and surface pressure. Parameterizations are included for turbulent exchange at the earth surface, cumulus convection, large scale saturation, diurnally varying solar radiation, and terrestrial radiation. Realistic simulations are thereby produced for many aspects of the observed climate.

Randall, D.↗
NASA NTRSDate not supplied

Managing Traffic on the Three-Way Street: Steps Toward Closing the Aerosol Forcing Uncertainty Gap

Understanding changes in the radiative forcing of climate is critical for any effort to attribute, mitigate, or predict climate change. Although greenhouse gases (GHGs) contribute most of the radiative forcing, uncertainty in the climate forcing by airborne particles (aerosols) dominates the uncertainty in forcing changes overall. Yet, aerosol forcing has remained virtually undiminished for more than 20 years despite considerable advances in most of the key contributing elements. Satellite and suborbital measurements, as well as modeling, each have essential roles to play in reducing the uncertainty in the aerosol forcing of climate. This presentation will begin by briefly covering the reasons why aerosols are important for climate study, and will then summarize what we are learning about aerosols from current satellite remote-sensing work, and allude to the roles of suborbital measurements and models. Emphasis will be placed on nascent efforts to link satellite data with models, the need to continue as planned current programs supporting advanced, global-scale satellite and surface-based aerosol and precursor gas observations, climate modeling, as well as intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved. The talk will conclude by highlighting new efforts needed to obtain systematic in situ measurements of aerosol microphysical and chemical properties, along with a greater research focus on integrating the unique contributions of measurements and modeling toward reducing the aerosol climate forcing uncertainty gap.

aerosol↗
NASA NTRS2016

Capturing Complete Spatial Context in Satellite Observations of Greenhouse Gases

Scientific consensus from a 2015 pre-Decadal Survey workshop highlighted the essential need for a wide-swath (mapping) low earth orbit (LEO) instrument delivering carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) measurements with global coverage. OCO-2 pioneered space-based CO2 remote sensing, but lacks the CH4, CO and mapping capabilities required for an improved understanding of the global carbon cycle. The Carbon Balance Observatory (CARBO) advances key technologies to enable high-performance, cost-effective solutions for a space-based carbon-climate observing system. CARBO is a compact, modular, 15-30° field of view spectrometer that delivers high-precision CO2, CH4, CO and solar induced chlorophyll fluorescence (SIF) data with weekly global coverage from LEO. CARBO employs innovative immersion grating technologies to achieve diffraction-limited performance with OCO-like spatial (2 x 2 sq.km) and spectral (λ/Δλ≈ 20,000) resolution in a package that is >50% smaller, lighter and more cost-effective. CARBO delivers a 25- to 50-fold increase in spatial coverage compared to OCO-2 with no loss of detection sensitivity. Individual CARBO modules weigh < 20 kg, opening diverse new space-based platform opportunities.

Miller, Charles E.↗
DOE OSTI2023

Soil organic matter diagenetic state informs boreal forest ecosystem feedbacks to climate change

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition of detrital inputs to soil over time – is useful for tracing the net response of SOC at the timescales relevant to climate change not usually discernible from fluxes and stocks alone. Here, we test two hypotheses using a mesic boreal forest climate transect: (1) the SOC diagenetic state is maintained across this climosequence, and (2) the maintenance of the SOC diagenetic state is a consequence of coupled soil C and N cycling, signifying the role of enhanced N cycling supporting SOC inputs that maintain SOC stocks within the warmer-climate forests. Shifts in nonvascular to vascular plant inputs with climate observed in these and other boreal forests highlighted the need to carefully separate biogeochemical indicators of SOC source from those signifying diagenetic alteration. We thus evaluated and applied lignin biomarkers to assess the diagenetic alteration of SOC in these boreal forest organic soils and directly compared the lignin diagenetic state with that of soil organic nitrogen (SON) assessed through amino acid composition. The lignin diagenetic state remained constant across the climate transect, indicating a balance between the input and removal of lignin in these mesic boreal forests. When combined with previous knowledge of these forest ecosystems, including the diagenetic state of SON and direct measures of C fluxes and stocks, the results indicate a coupled increase in C and N cycling with climate warming that supports forest productivity and maintains SOC stocks. This balance could markedly shift as other factors begin to limit forest productivity (e.g., trace nutrients, water) with further climate change or affect forest nutrient allocation (e.g., forest age or compositional change). Further application of the approach presented here could be used to detect the limits of this and other ecosystem–climate feedbacks, by providing a tractable and parameterizable index of the lignin state across large spatial scales, necessary for ecosystem-scale parameterizations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

The Critical Role of the Routing Scheme in Simulating Peak River Discharge in Global Hydrological Models

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge which is crucial in flood simulations has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a (Inter-Sectoral Impact Model Intercomparison Project phase 2a) project. The runoff simulations were used as input for the global river routing model CaMa-Flood (Catchment-based Macro-scale Floodplain). The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC (Global Runoff Data Centre) stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about two-thirds of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

peak river discharge↗
DOE OSTI2023

Multigenic resistance to Xylella fastidiosa in wild grapes ( Vitis sps.) and its implications within a changing climate

Xylella fastidiosa is a bacterium that infects crops like grapevines, coffee, almonds, citrus and olives. There is little understanding of the genes that contribute to plant resistance, the genomic architecture of resistance, and the potential role of climate in shaping resistance, in part because major crops like grapevines (Vitis vinifera) are not resistant to the bacterium. Here we study a wild grapevine species, V. arizonica, that segregates for resistance. Using genome-wide association, we identify candidate resistance genes. Resistance-associated kmers are shared with a sister species of V. arizonica but not with more distant species, suggesting that resistance evolved more than once. Finally, resistance is climate dependent, because individuals from low (< 10 °C) temperature locations in the wettest quarter were typically susceptible to infection, likely reflecting a lack of pathogen pressure in colder climates. In fact, climate is as effective a predictor of resistance phenotypes as some genetic markers. We extend our climate observations to additional crops, predicting that increased pathogen pressure is more likely for grapevines and almonds than some other susceptible crops.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Clumped isotope constraints on changes in latest Pleistocene hydroclimate in the northwestern Great Basin: Lake Surprise, California

Abstract During the Last Glacial Maximum (LGM) and subsequent deglaciation, the Great Basin in the southwestern United States was covered by numerous extensive closed-basin lakes, in stark contrast with the predominately arid climate observed today. This transition from lakes in the Late Pleistocene to modern aridity implies large changes in the regional water balance. Whether these changes were driven by increased precipitation rates due to changes in atmospheric dynamics, decreased evaporation rates resulting from temperature depression and summer insolation changes, or some combination of the two remains uncertain. The factors contributing to these large-scale changes in hydroclimate are critical to resolve, given that this region is poised to undergo future anthropogenic-forced climate changes with large uncertainties in model simulations for the 21st century. Furthermore, there are ambiguous constraints on the magnitude and even the sign of changes in key hydroclimate variables between the Last Glacial Maximum and the present day in both proxy reconstructions and climate model analyses of the region. Here we report thermodynamically derived estimates of changes in temperature, precipitation, and evaporation rates, as well as the isotopic composition of lake water, using clumped isotope data from an ancient lake in the northwestern Great Basin, Lake Surprise (California). Compared to modern climate, mean annual air temperature at Lake Surprise was 4.7 °C lower during the Last Glacial Maximum, with decreased evaporation rates and similar precipitation rates to modern. During the mid-deglacial period, the growth of Lake Surprise implied that the lake hydrologic budget briefly departed from steady state. Our reconstructions indicate that this growth took place rapidly, while the subsequent lake regression took place over several thousand years. Using models for precipitation and evaporation constrained from clumped isotope results, we determine that the disappearance of Lake Surprise coincided with a moderate increase in lake temperature, along with increasing evaporation rates outpacing increasing precipitation rates. Concomitant analysis of proxy data and climate model simulations for the Last Glacial Maximum are used to provide a robust means to understand past climate change, and by extension, predict how current hydroclimates may respond to expected future climate forcings. We suggest that an expansion of this analysis to more basins across a larger spatial scale could provide valuable insight into proposed climate forcings, and aid in climate model process depiction. Ultimately, our analysis highlights the importance of temperature-driven evaporation as a mechanism for lake growth and retreat in this region.

Geology↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27604-DND

Satellite-based hyperspectral observations provide high information content for the Earth's atmospheric and surface properties; however, in order to analyze hyperspectral data efficiently, fast and accurate radiative transfer model is needed. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate radiative transfer in the cloudy atmosphere from far IR to visible and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5 and LBLRTM. The PCRTM calculated radiance spectra agree with the Modtran and LBLRTM within 0.02%. We will demonstrate the application of the PCRTM forward model for atmospheric and surface property inversions and for climate observation studies.

X Liu↗