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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Enabling Research Tools for Sustained Climate Assessment

The U.S. Global Change Research Program Sustained Assessment process benefits from long-term investments in Earth science research that enable the scientific community to conduct assessment-relevant science. To this end, NASA initiated several research programs over the past five years to support the Earth observation community in developing indicators, datasets, research products, and tools to support ongoing and future National Climate Assessments. These activities complement NASA's ongoing Earth science research programs. One aspect of the assessment portfolio funds four "enabling tools" projects at NASA research centers. Each tool leverages existing capacity within the center, but has developed tailored applications and products for National Climate Assessments. The four projects build on the capabilities of a global atmospheric reanalysis (MERRA-2), a continental U.S. land surface reanalysis (NCA-LDAS), the NASA Earth Exchange (NEX), and a Regional Climate Model Evaluation System (RCMES). Here, we provide a brief overview of each enabling tool, highlighting the ways in which it has advanced assessment science to date. We also discuss how the assessment community can access and utilize these tools for National Climate Assessments and other sustained assessment activities.

Research↗
NASA NTRS2017

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗
NASA NTRS2019

The Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Mission: Status, Science, Advances

The PACE mission represents NASA’s next investment in ocean color, cloud, and aerosol data records to enable continued and advanced insight into oceanographic and atmospheric responses to Earth’s changing climate. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission represents NASA’s next investment in satellite ocean color and the study of Earth’s ocean-atmosphere system, enabling new insights into oceanographic and atmospheric responses to Earth's changing climate. PACE objectives include extending systematic cloud, aerosol, and ocean biological and biogeochemical data records, making essential ocean color measurements to further understand marine carbon cycles, food web processes, and ecosystem responses to a changing climate, and improving knowledge of how aerosols influence ocean ecosystems and, conversely, how ocean ecosystems and photochemical processes affect the atmosphere. PACE objectives also encompass management of fisheries, large freshwater bodies, and air and water quality and reducing uncertainties in climate and radiative forcing models of the Earth system. PACE observations will provide information on radiative properties of land surfaces and characterization of the vegetation and soils that dominate their reflectance. The primary PACE instrument is a spectrometer that spans the ultraviolet to shortwave infrared, with a ground sample distance of 1-km at nadir. This payload is complemented by two multi-angle polarimeters with spectral ranges that span the visible to near-infrared region. Scheduled for launch in late 2022-to-early 2023, the PACE observatory will enable significant advances in the study of Earth’s biogeochemistry, carbon cycle, clouds, hydrosols, and aerosols in the ocean-atmosphere-land system. Here, we present an overview of the PACE mission, including its developmental history, science objectives, instrument payload, observatory characteristics, and data products.

P Jeremy Werdell↗
NASA NTRS2022

Maine Ecological Forecasting II: Identifying Forest Cover and Assessing Federally Endangered Atlantic Salmon Habitat in Maine Using Earth Observations

Major declines in Atlantic salmon (Salmo salar) populations have occurred alongside dam construction, shifting temperatures, and changing land use and land cover (LULC), restricting the last remaining wild population in the United States to Maine. In collaboration with the Maine Department of Marine Resources and the Downeast Salmon Federation, the NASA DEVELOP team utilized Earth observations to assess changes within critical salmon habitat. The team used the Landsat 5 Thematic Mapper (TM), Landsat 8 Operation Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and National Land Cover Database (NLCD) to refine historical LULC maps from 1985 to 2021. The team also used elevation data from the Shuttle Radar Topography Mission (SRTM) and IDRISI TerrSet Land Change Modeler to forecast LULC change to 2040. From Terra Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, the team derived a time series, summer averages, and anomaly maps between 2000 and 2021. The team analyzed LST in relation to LULC classes, specifically forest cover type, and in-situ stream temperature from the Spatial Hydro-Ecological Decision System (EcoSHEDS). LULC trends from 1985 to 2021 revealed a net transition of coniferous forest to other classes, such as deciduous forest and developed land. The team found an association between warmer temperatures and a greater presence of developed and mixed forest classes per 10,000 acres across Maine. These visualizations and analyses will aid partners in identifying riparian locations with ideal or unfavorable habitat conditions to inform Atlantic salmon population recovery efforts.

Tony Bowman↗
DOE OSTI2022

Understanding the Physics Representation of Deep Learning Models in Environmental Applications

Deep learning (DL) models have been popular in earth and environmental modeling and analysis, which exhibit huge potential in capturing and reconstructing the non-linearity of relevant environmental processes. They are extensively used as analytical tools or emulators for multiple domains (atmosphere, land surface, ocean, and biogeochemistry). Despite their success, their internal working mechanism remains largely unknown. Such a lack of knowledge hinders the identification of physically consistent models that are fully adaptive to non-stationary climate, as well as the development of physics-informed machine learning such as physics-informed neural network (PINN). To establish preliminary knowledge and framework of such physics representation evaluation, this project focuses on an improved understanding of DL models in the environmental applications. DL models are increasingly applied to environmental modeling and prediction. However, they have been evaluated mostly from a performance perspective, and there is a gap in understanding how they represent the known physics internally. Such knowledge is especially critical when applying DL models under climate change conditions, where new inputs are likely outside the ranges of the training datasets. In this project, we reveal how the known physical processes are represented within DL models from both statistical and mechanistic perspectives. Leveraging the traditional model evaluations that focus more on the accuracies of predictions, we establish a framework that examines both the accuracy and physics representation of DL models. This analysis framework can identify DL models that make the correct predictions based on correct physics, thus enhancing the existing explainable artificial intelligence (explainable-AI) portfolio. It lays a foundation for developing novel metrics to evaluate the emerging DL models in environmental applications. This knowledge also informs the development of physics-informed DL models by revealing the direct connections between the known physical processes and specific model components or structures.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Three-Dimensional Model Synthesis of the Global Methane Cycle

A synthesis of the global methane cycle is presented to attempt to generate an accurate global methane budget. Methane-flux measurements, energy data, and agricultural statistics are merged with databases of land-surface characteristics and anthropogenic activities. The sources and sinks of methane are estimated based on atmospheric methane composition and variations, and a global 3D transport model simulates the corresponding atmospheric responses. The geographic and seasonal variations of candidate budgets are compared with observational data, and the available observations are used to constrain the plausible methane budgets. The preferred budget includes annual destruction rates and annual emissions for various sources. The lack of direct flux measurements in the regions of many of these fluxes makes the unique determination of each term impossible. OH oxidation is found to be the largest single term, although more measurements of this and other terms are recommended.

Fung, I.↗
NASA NTRS1992

Shinnery oak bidirectional reflectance properties and canopy model inversion

Field measurements are presented, together with the results of a 3D canopy-model inversion for sand shinnery oak community in western Texas. The spectral bidirectional radiance measurements were in three spectral channels encompassing both the complete land surface and sky hemispheres. The changes in canopy reflectance that occur with variations in solar zenith angle and view direction for two seasons of the year were evaluated, and the 3D radiation-interaction model was inverted to estimate the oak leaf area index and canopy density from the reflectance data.

Deering, Donald W.↗
NASA NTRSDate not supplied

Development of the 10% NASA CRM High-Lift Common Research Model (CRM-HL)

A 10%-scale Common Research Model-high lift version (CRM-HL) was developed to support extensive experimental investigations in the areas of active flow control, control surface optimization for landing and take-off, acoustic technology development, and computational fluid dynamics code validation to name a few. The CRM-HL was designed to have modular components that will enable the model to be tested in the following three forms: (1) conventional high-lift (CHL) configuration, (2) Active Flow Control (AFC) enabled simple hinged flap high-lift (SHL) configuration, and (3) CHL configuration with noise reduction treatments for the slats and/or the flaps. This paper describes the design, analysis, and fabrication of the CRM-HL for testing in the NASA Langley Research Center (LaRC) 14 by 22-Foot Subsonic Tunnel (14x22) and other wind tunnels as deemed appropriate by the research community such as the Qinetiq 5 Meter tunnel.

Jared S. Fell↗
DOE OSTI2022

SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice

Abstract. Accurate modeling of cryospheric surface albedo is essential for our understanding of climate change as snow and ice surfaces regulate the global radiative budget and sea-level through their albedo and mass balance. Although significant progress has been made using physical principles to represent the dynamic albedo of snow, models of glacier ice albedo tend to be heavily parameterized and not explicitly connected with physical properties that govern albedo, such as the number and size of air bubbles, specific surface area (SSA), presence of abiotic and biotic light absorbing constituents (LACs), and characteristics of any overlying snow. Here, we introduce SNICAR-ADv4, an extension of the multi-layer two-stream delta-Eddington radiative transfer model with the adding–doubling solver that has been previously applied to represent snow and sea-ice spectral albedo. SNICAR-ADv4 treats spectrally resolved Fresnel reflectance and transmittance between overlying snow and higher-density glacier ice, scattering by air bubbles of varying sizes, and numerous types of LACs. SNICAR-ADv4 simulates a wide range of clean snow and ice broadband albedo (BBA), ranging from 0.88 for (30 µm) fine-grain snow to 0.03 for bare and bubble-free ice under direct light. Our results indicate that representing ice with a density of 650 kg m−3 as snow with no refractive Fresnel layer, as done previously, generally overestimates the BBA by an average of 0.058. However, because most naturally occurring ice surfaces are roughened “white ice”, we recommend modeling a thin snow layer over bare ice simulations. We find optimal agreement with measurements by representing cryospheric media with densities less than 650 kg m−3 as snow and larger-density media as bubbly ice with a Fresnel layer. SNICAR-ADv4 also simulates the non-linear albedo impacts from LACs with changing ice SSA, with peak impact per unit mass of LACs near SSAs of 0.1–0.01 m2 kg−1. For bare, bubble-free ice, LACs actually increase the albedo. SNICAR-ADv4 represents smooth transitions between snow, firn, and ice surfaces and accurately reproduces measured spectral albedos of a variety of glacier surfaces. This work paves the way for adapting SNICAR-ADv4 to be used in land ice model components of Earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Decoupling in the Vertical Shape of HCHO During a Sea Breeze Event: the Effect on Trace Gas Satellite Retrievals and Column-to-Surface Translation

The effect of sea breeze circulation on stratification of the vertical formaldehyde (HCHO) concentration vertical profiles is explored using a regional atmospheric chemical transport model (CTM) for three synoptically stagnant days focused on the east coast of the U.S in June 2018. During this event, a significant thermal contrast between the Atlantic Ocean and the terrestrial regions (12–17 °C), observed by moderate resolution imaging spectroradiometer (MODIS) and well-captured by the WRF-CMAQ model (15–18 °C), is conducive to monsoon-like flow, perpendicular to the shorelines, carrying clean marine air masses over the land within a few hundreds of meters above the surface. In contrast, the westerly continental polluted air masses prevail in higher altitudes. These two conflicting flows result in atypical vertical shapes of HCHO concentrations increasing with altitude. This decoupling pattern is so pronounced that we observe total column HCHO negatively correlate with surface concentrations. Comparisons of an accredited global model, GEOS-CF, to surface wind measurements and MODIS skin temperature indicate its poor representation of the sea breeze timing and strength, resulting in GEOS-CF HCHO vertical shapes being drastically different from the WRF-CMAQ. Based on radiative transfer calculations, the differences in the vertical distribution of HCHO between the WRF-CMAQ and that of GEOS-CF in the first 3 km are sufficient to induce a 20–30% error in air mass factors (thus total vertical HCHO column abundances). Through an experiment involving converting HCHO total columns to surface mixing ratios, we demonstrate that GEOS-CF allocates noticeably more HCHO molecules (40–150%) to the surface layer due to the misrepresentation of the vertical shape of HCHO during the sea breeze event. It is known that a significant fraction of the human population lives in coastal areas prone to detrimental effects caused by air pollution, and elevated pollutant concentrations usually occur in synoptically stagnant atmospheric conditions when local circulation patterns come into play; accordingly, our experiments emphasize the importance of the effect a priori profiles can have on satellite-derived applications under such conditions. To ensure that the quantitative representation of satellite-based trace gas retrievals on a daily basis is trustworthy and useable for air quality applications, atmospheric models providing a priori profiles for satellite retrievals should be well-tuned to reproduce complex local circulation such as sea-land breezes.

sea breeze↗
NASA NTRS1994

Mars Pathfinder meteorological observations on the basis of results of an atmospheric global circulation model

The Mars Pathfinder Meteorological Package (ASI/MET) will measure the local pressure, temperature, and winds at its future landing site, somewhere between the latitudes 0 deg N and 30 deg N. Comparable measurements have already been obtained at the surface of Mars by the Viking Landers at 22 deg N (VL1) and 48 deg N (VL2), providing much useful information on the martian atmosphere. In particular the pressure measurements contain very instructive information on the global atmospheric circulation. At the Laboratoire de Meteorologie Dynamique (LMD), we have analyzed and simulated these measurements with a martian atmospheric global circulation model (GCM), which was the first to simulate the martian atmospheric circulation over more than 1 year. The model is able to reproduce rather accurately many observed features of the martian atmosphere, including the long- and short-period oscillations of the surface pressure observed by the Viking landers. From a meteorological point of view, we think that a landing site located near or at the equator would be an interesting choice.

Forget, Francois↗
NASA NTRS2020

Quantification of the Land Surface and Brown Ocean Influence on Tropical Cyclone Intensification Over Land

An investigation of TC Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the Brown Ocean effect (BOE), and to develop a comprehensive analysis framework for landfalling tropical cyclones (TCs) in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e. all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

Brown Ocean Effect↗
DOE OSTI2022

Surface temperatures reveal the patterns of vegetation water stress and their environmental drivers across the tropical Americas

Vegetation is a key component in the global carbon cycle as it stores ~450 GtC as biomass, and removes about a third of anthropogenic CO2 emissions. However, in some regions, the rate of plant carbon uptake is beginning to slow, largely because of water stress. Here, we develop a new observation-based methodology to diagnose vegetation water stress and link it to environmental drivers. We used the ratio of remotely sensed land surface to near surface atmospheric temperatures (LST/Tair) to represent vegetation water stress, and built regression tree models (random forests) to assess the relationship between LST/Tair and the main environmental drivers of surface energy fluxes in the tropical Americas. We further determined ecosystem traits associated with water stress and surface energy partitioning, pinpointed critical thresholds for water stress, and quantified changes in ecosystem carbon uptake associated with crossing these critical thresholds. Additionally, we found that the top drivers of LST/Tair, explaining over a quarter of its local variability in the study region, are (1) radiation, in 58% of the study region; (2) water supply from precipitation, in 30% of the study region; and (3) atmospheric water demand from vapor pressure deficits (VPD), in 22% of the study region. Regions in which LST/Tair variation is driven by radiation are located in regions of high aboveground biomass or at high elevations, while regions in which LST/Tair is driven by water supply from precipitation or atmospheric demand tend to have low species richness. Carbon uptake by photosynthesis can be reduced by up to 80% in water-limited regions when critical thresholds for precipitation and air dryness are exceeded simultaneously, that is, as compound events. Our results demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes over tropical regions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

The Second Phase of the Global Land Atmosphere Coupling Experiment (GLACE-2): Impact of Land Initialization on Subseasonal Forecasts

The recently-completed second phase of the Global Land-Atmosphere Coupling Experiment (GLACE-2) focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the multi-institutional numerical experiment is described, along with a determination and characterization of multi-model "consensus" skill. The models show modest but significant land-derived skill in predicting air temperatures out to two months, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forecast skill is much weaker than that for air temperature. The skill for predicting air temperature, and to some extent precipitation, increases with the magnitude of the initial soil moisture anomaly. GLACE-2 results are examined further to provide insight into the asymmetric impacts of wet and dry soil moisture initialization on skill.

Koster, Randal↗
NASA NTRS1988

Development of a ground hydrology model suitable for global climate modeling using soil morphology and vegetation cover, and an evaluation of remotely sensed information

The long-term purpose was to contribute to scientific understanding of the role of the planet's land surfaces in modulating the flows of energy and matter which influence the climate, and to quantify and monitor human-induced changes to the land environment that may affect global climate. Highlights of the effort include the following: production of geo-coded, digitized World Soil Data file for use with the Goddard Institute for Space Studies (GISS) climate model; contribution to the development of a numerical physically-based model of ground hydrology; and assessment of the utility of remote sensing for providing data on hydrologically significant land surface variables.

Zobler, L.↗
NASA NTRS1988

Global land-surface primary productivity based upon Nimbus-7 37 GHz data

Accumulation and renewal of organic matter as quantified through net primary productivity (NPP) is considered a very major function of the biosphere, and its estimation is crucial in understanding the carbon cycle. A physically-based model relating NPP to the difference of vertically and horizontally polarized brightness temperatures (Delta T) observed at 37 GHz frequency of the scanning multichannel microwave radiometer on board the Nimbus-7 satellite is used for fitting areally averaged values of NPP and Delta T for five biomes. The land-surface NPP within 80 deg N to 55 deg S is then calculated using the Delta T data and compared with other estimates.

Choudhury, B. J.↗
NASA NTRS1987

Anticipation of the landing shock phenomenon in flight simulation

An aircraft landing may be described as a controlled crash because a runway surface is intercepted. In a simulation model the transition from aerodynamic flight to weight on wheels involves a single computational cycle during which stiff differential equations are activated; with a significant probability these initial conditions are unrealistic. This occurs because of the finite cycle time, during which large restorative forces will accompany unrealistic initial oleo compressions. This problem was recognized a few years ago at Ames Research Center during simulation studies of a supersonic transport. The mathematical model of this vehicle severely taxed computational resources, and required a large cycle time. The ground strike problem was solved by a described technique called anticipation equations. This extensively used technique has not been previously reported. The technique of anticipating a significant event is a useful tool in the general field of discrete flight simulation. For the differential equations representing a landing gear model stiffness, rate of interception and cycle time may combine to produce an unrealistic simulation of the continuum.

Mcfarland, Richard E.↗
DOE OSTI2022

Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and subtropical Africa. In Madagascar, the condition is widespread and endemic in 74% of all administrative districts in the country. Despite the significant burden of the disease, high-resolution risk maps have yet to be produced to guide national control programs. This study used an ecological niche modeling (ENM) and precision mapping approach to estimate environmental suitability and disease transmission risk. The results show that suitability for schistosomiasis is widespread and covers 264,781 km 2 (102,232 sq miles). Covariates of significance to the model were the accessibility to cities, distance to water, enhanced vegetation index (EVI), annual mean temperature, land surface temperature (LST), clay content, and annual precipitation. Disease transmission risk is greatest in the central highlands, tropical east coast, arid-southwest, and northwest. An estimated 14.9 million people could be at risk of schistosomiasis; 11.4 million reside in rural areas, while 3.5 million are in urban areas. This study provides valuable insight into the geography of schistosomiasis in Madagascar and its potential risk to human populations. Because of the focal nature of the disease, these maps can inform national surveillance programs while improving understanding of areas in need of medical interventions.

60 APPLIED LIFE SCIENCES↗