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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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NASA NTRS1972

Dynamic response of a semi-infinite elastic cylinder containing an acoustic medium.

The solutions developed in this paper are based on the finite Hankel-Fourier-Laplace transform. The Love-Timoshenko shell equations are reduced through the application of the Fourier-Laplace transforms to the axial space and time variables. The equation of motion for the acoustic fluid contained within the shell are reduced through the application of the finite Hankel-Fourier-Laplace transform to the radial, axial spatial, and time variables. The boundary conditions at the fixed end of the semi-infinite shell are met through the application of loadings symmetric with respect to the origin and the application of a ring loading at the origin which is chosen so as to make the radial deflection there zero. Expressions are found for the transforms of the axial, tangential, and radial shell displacements, the axial, tangential, and radial fluid velocities, and the radiated fluid pressure. Numerical inversion of the Fourier-Laplace transform is accomplished in terms of a series of ultraspherical polynomials and Gauss-Hermite or Gauss-Laguerre quadrature.

Carpenter, R. F., III↗
NASA NTRS2001

Bio-Optical Measurements at Ocean Boundaries in Support of SIMBIOS

The equatorial Pacific is a major component of global biogeochemical cycles, due to upwelling that occurs from the coast of South America to beyond 180 deg. This upwelling has significant implications for global CO2 fluxes, as well as primary and secondary production. In addition, this region of the world's oceans represents a large oceanic province over which validation data for Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) are necessary. This project consists of a mooring program and supporting cruise-based measurements aimed at quantifying the spectrum of biological and chemical variability in the equatorial Pacific and obtaining validation data for SeaWiFS. The project has the following general objectives: (1) to understand the relationships between physical forcing, primary production, nutrient supply and the exchange of carbon dioxide between ocean and atmosphere in the equatorial Pacific; (2) to describe the biological and chemical responses to climate and ocean variability; (3) to describe the spatial, seasonal and inter-annual variability in near surface plant pigments, primary production, carbon dioxide and nutrient distributions; and (4) to obtain near real-time bio-optical measurements for validation of SeaWiFS and subsequent ocean color sensors.

Chavez, Francisco P.↗
NASA NTRS2016

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

climate projection↗
NASA NTRS2016

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km by 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

general circulation model (GCM)↗
NASA NTRS2008

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Molnar, Gyula↗
NASA NTRS1994

Spatial patterns in the length of the sea ice season in the Southern Ocean, 1979-1986

The length of the sea ice season summarizes in one number the ice coverage conditions for an individual location for an entire year. It becomes a particularly valuable variable when mapped spatially over a large area and examined for regional and interannual differences, as is done here for the Southern Ocean over the years 1979-1986, using the satellite passive microwave data of the Nimbus 7 scanning multichannel microwave radiometer. Three prominent geographic anomalies in ice season lengths occur consistently in each year of the data set, countering the general tendency toward shorter ice seasons from south to north: (1) in the Weddell Sea the tendency is toward shorter ice seasons from southwest to northeast, reflective of the cyclonic ice/atmosphere/ocean circulations in the Weddell Sea region. (2) Directly north of the Ross Ice Shelf anomalously short ice seasons occur, lasting only 245-270 days, in contrast to the perennial ice coverage at comparable latitudes in the southern Bellingshausen and Amundsen Seas and in the western Weddell Sea. The short ice season off the Ross Ice Shelf reflects the consistently early opening of the ice cover each spring, under the influence of upwelling along the continental slope and shelf and atmospheric forcing from winds blowing off the Antarctic continent. (3) In the southern Amundsen Sea, anomalously short ice seasons occur adjacent to the coast, owing to the frequent existence of coastal polynyas off the many small ice shelves bordering the sea. Least squares trends in the ice season lengths over the 1979-1986 period are highly coherent spatially, with overall trends toward shorter ice seasons in the northern Weddell and Bellingshausen seas and toward longer ice seasons in the Ross Sea, around much of East Antarctica, and in a portion of the south central Weddell Sea.

Parkinson, Claire L.↗
NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗
NASA NTRS2002

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign.

Kundu, Prasun K.↗
NASA NTRS1979

Initial observations of the nightside ionosphere of Venus from Pioneer Venus Orbiter radio occultations

Results of radio occultation measurements of electron density profiles of the nightside ionosphere of Venus at solar zenith angles from 90 to 164 deg, obtained from the Pioneer Venus Orbiter, are reported. Data were derived from closed-loop S- and X-band signals received by the Deep Space Network upon ionospheric entry and exit of the spacecraft. Nightside electron density profiles are found to be rather uniform in the solar zenith angle range of from 95 to 107 deg, with peak electron densities ranging from 23,000 to 40,000/cu cm, while between 110 and 164 deg, profiles exhibit a high degree of variability and peak electron densities vary from 7,600 to 31,800/cu cm. A possible mechanism for the maintenance of the nightside Venus ionosphere during the long Venus night, which is consistent with the observed spatial and temporal variability of deep ionospheric electron density profiles, is proposed to be impact ionization by precipitating particles, although transport processes from the dayside may also be important.

Kliore, A. J.↗
NASA NTRS1998

Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

Betts, M.↗
NASA NTRS2011

A New Global Mascon Solution Tuned for High-Latitude Ice Studies

A new global mascon solution has been developed with I-arc-degree spatial and IO-day temporal sampling. The global mas cons are estimated from the reduction of nearly 8 years of GRACE K-band range-rate data. Temporal and anisotropic spatial constraints have been applied for land, ocean and ice regions. The solution construction and tuning is focused towards the Greenland and Antarctic ice sheets (GIS and AIS) as well as the Gulf of Alaska mountain glaciers (GoA). Details of the solution development will be discussed, including the mascon parameter definitions, constraints, and the tuning of the constraint damping factor. Results will be presented, exploring the spatial and temporal variability of the ice sheets and GoA regions. A detailed error analysis will be discussed, including solution dependence on iteration, damping factor, forward modeling, and multitechnique comparisons. We also investigate the fundamental resolution of the solution and the spatial correlation of ice sheet inter-annual change. Finally, we discuss future improvements, including specific constraint application for the rest of the major land ice regions and improvements in solution regularization.

Luthcke, S. B.↗
NASA NTRS2015

North Atlantic Simulations in Coordinated Ocean-Ice Reference Experiments Phase II (CORE-II) : Inter-Annual to Decadal Variability - Part II

Simulated inter-annual to decadal variability and trends in the North Atlantic for the 1958−2007 period from twenty global ocean - sea-ice coupled models are presented. These simulations are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The study is Part II of our companion paper (Danabasoglu et al., 2014) which documented the mean states in the North Atlantic from the same models. A major focus of the present study is the representation of Atlantic meridional overturning circulation (AMOC) variability in the participating models. Relationships between AMOC variability and those of some other related variables, such as subpolar mixed layer depths, the North Atlantic Oscillation (NAO), and the Labrador Sea upper-ocean hydrographic properties, are also investigated. In general, AMOC variability shows three distinct stages. During the first stage that lasts until the mid- to late-1970s, AMOC is relatively steady, remaining lower than its long-term (1958−2007) mean. Thereafter, AMOC intensifies with maximum transports achieved in the mid- to late-1990s. This enhancement is then followed by a weakening trend until the end of our integration period. This sequence of low frequency AMOC variability is consistent with previous studies. Regarding strengthening of AMOC between about the mid-1970s and the mid-1990s, our results support a previously identified variability mechanism where AMOC intensification is connected to increased deep water formation in the subpolar North Atlantic, driven by NAO-related surface fluxes. The simulations tend to show general agreement in their representations of, for example, AMOC, sea surface temperature (SST), and subpolar mixed layer depth variabilities. In particular, the observed variability of the North Atlantic SSTs is captured well by all models. These findings indicate that simulated variability and trends are primarily dictated by the atmospheric datasets which include the influence of ocean dynamics from nature superimposed onto anthropogenic effects. Despite these general agreements, there are many differences among the model solutions, particularly in the spatial structures of variability patterns. For example, the location of the maximum AMOC variability differs among the models between Northern and Southern Hemispheres.

Ocean model comparisons↗
NASA NTRS1991

The spatial characteristics of the B helical mode for a choked axisymmetric nozzle

An acoustic near-field study was performed for an axisymmetric conical nozzle operated at a fully expanded Mach number of 1.3. The acoustic measurements were performed in the nozzle exit plane using multiple sensors arranged around the periphery of the nozzle. The acquired data were simultaneously digitized. The acoustic spatial characteristics, describing the large scale structure associated with the preferred shear layer instability mode, were determined for the dominant B screech mode. The nozzle was fitted with a lip thickening device to determine the effect of this geometric variable on the spatial structure of the jet. For the thin-lipped configuration, the flapping structure of the B screech mode was found to precess in a time-dependent manner about the jet axis. An increasing of the nozzle exit lip thickness altered the spatial characteristics of this mode from a flapping to a time-dependent flapping or spinning. Using the auto-bicoherence spectrum, frequency dependencies were found to exist in the acoustic data of the thick-lipped configuration. These dependencies may be related to the nonlinearity of the jet and/or the time-dependent nature of the B mode spatial structure.

Ponton, Michael K.↗
NASA NTRS1995

Acoustic Study of B Helical Mode for Choked Axisymmetric Nozzle

An acoustic near-field study was performed for an axisymmetric conical convergent nozzle operating at a pressure ratio corresponding to a fully expanded Mach number of 1.3. The acoustic measurements were performed in the nozzle exit plane using multiple sensors arranged around the periphery of the nozzle. The acquired data were simultaneously digitized. The acoustic spatial characteristics, describing the large-scale structure associated with the preferred shear layer instability mode, were determined for the dominant B screech mode. The nozzle was fitted with a lip thickening device to determine the effect of this geometric variable on the spatial structure of the jet. For the thin-lipped configuration, the flapping structure of the B screech mode was found to precess in a time- dependent manner about the jet axis. Increasing of the nozzle exit lip thickness altered the spatial characteristics of this mode from a flapping to a time-dependent flapping or spinning. Using the autobicoherence spectrum, frequency dependencies were found to exist in the acoustic data of the thick-lipped configuration. These dependencies may be related to the nonlinearity of the jet and/or the time-dependent nature of the B mode spatial structure.

Ponton, Michael K.↗
NASA NTRS2026

Spatially Refined Satellite Gravimetry Captures Human Signatures in Global Terrestrial Water Storage Trends

Human activities have directly altered the water cycle through water management, aquifer pumping, agricultural irrigation, and land use change. Although satellite gravimetry has transformed global hydrological research, its coarse resolution limits attribution of freshwater change to human activities at many management-relevant scales. Here we assessed global terrestrial water storage (TWS) trends from April 2002 to November 2025 using “stacked” regression of Level-1B intersatellite ranging data, which leverages temporal information and variability to dramatically improve effective spatial resolution relative to standard approaches. We combined this refined product with rigorous uncertainty analysis, autocorrelation-robust geostatistical methods, and literature assessment to evaluate TWS trend associations with land and water use, climate variability, and glacial mass loss. We identified TWS trend hotspots exhibiting significant spatial associations with anthropogenic 40 drivers, including groundwater and surface-water irrigation, rainfed agriculture, deforestation, and reservoir impoundment. Across these regions, cumulative TWS losses (3,122 Gt) substantially exceeded gains (2,432 Gt). Compared with traditional regression of monthly mascons, our approach yielded regional trend magnitudes that are on average 33% larger, revealing that global freshwater depletion, particularly from groundwater pumping, is considerably more acute than previously estimated. Multivariate regression models show that humans account for a significant share of the spatial variability in TWS trends on every non-polar continent except Australia. We detected localized TWS gains linked to rainfed agriculture, surface water irrigation, and reservoir filling that were unresolved in earlier gravimetric studies. The methodology provides a foundation for future gravity missions to independently track decadal freshwater change with unprecedented spatial fidelity.

groundwater↗
NASA NTRS2000

Airborne Laser Altimetry Mapping of the Greenland Ice Sheet: Application to Mass Balance Assessment

In 1998 and '99, the Arctic Ice Mapping (AIM) program completed resurveys of lines occupied 5 years earlier revealing elevation changes of the Greenland ice sheet and identifying areas of significant thinning, thickening and balance. In planning these surveys, consideration had to be given to the spatial constraints associated with aircraft operation, the spatial nature of ice sheet behavior, and limited resources, as well as temporal issues, such as seasonal and interannual variability in the context of measurement accuracy. This paper examines the extent to which the sampling and survey strategy is valid for drawing conclusions on the current state of balance of the Greenland ice sheet. The surveys covered the entire ice sheet with an average distance of 21.4 km between each location on the ice sheet and the nearest flight line. For most of the ice sheet, the elevation changes show relatively little spatial variability, and their magnitudes are significantly smaller than the observed elevation change signal. As a result, we conclude that the density of the sampling and the accuracy of the measurements are sufficient to draw meaningful conclusions on the state of balance of the entire ice sheet over the five-year survey period. Outlet glaciers, however, show far more spatial and temporal variability, and each of the major ones is likely to require individual surveys in order to determine its balance.

Abdalati, W.↗
NASA NTRS1999

Variability of Convective Precipitation from TRMM Microwave Imager (TMI)

Tropical precipitation generally occurs in two distinguishable forms: convective and stratiform. The two different types of precipitation systems have considerably different vertical profiles of latent heat release that has a crucial role in driving the circulation of the atmosphere. Thus, it is very important to study the variability of convective and stratiform precipitation. This paper presents variability of convective precipitation estimated from TRMM Microwave Imager (TMI). The convective/stratiform precipitation areas are classified using a combined texture-based and polarization-based algorithm. Surface rainfall rates are retrieved using the Goddard Profiling algorithm (Gprof). We will examine the spatial and temporal variability of convective precipitation for 1998. In addition, convective precipitation computed from TMI will be compared with those from the space borne Precipitation Radar (PR) and the ground-based radars for several cases.

Hong, Ye↗