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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Application of Land Surface Data Assimilation to Simulations of Sea Breeze Circulations

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite- observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The sea/land breeze is a well-documented mesoscale circulation that affects many coastal areas of the world including the northern Gulf Coast of the United States. The focus of this paper is to examine how the satellite assimilation technique impacts the simulation of a sea breeze circulation observed along the Mississippi/Alabama coast in the spring of 2001. The technique is implemented within the PSUNCAR MM5 V3-5 and applied at spatial resolutions of 12- and 4-km. It is recognized that even 4-km grid spacing is too coarse to explicitly resolve the detailed, mesoscale structure of sea breezes. Nevertheless, the model can forecast certain characteristics of the observed sea breeze including a thermally direct circulation that results from differential low-level heating across the land-sea interface. Our intent is to determine the sensitivity of the circulation to the differential land surface forcing produced via the assimilation of GOES skin temperature tendencies. Results will be quantified through statistical verification techniques.

Mackaro, Scott↗
NASA NTRS2002

Land Surface Data Assimilation and the Northern Gulf Coast Land/Sea Breeze

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The sea/land breeze is a well-documented mesoscale circulation that affects many coastal areas of the world including the northern Gulf Coast of the United States. The focus of this paper is to examine how the satellite assimilation technique impacts the simulation of a sea breeze circulation observed along the Mississippi/Alabama coast in the spring of 2001. The technique is implemented within the PSU/NCAR MM5 V3-4 and applied on a 4-km domain for this particular application. It is recognized that a 4-km grid spacing is too coarse to explicitly resolve the detailed, mesoscale structure of sea breezes. Nevertheless, the model can forecast certain characteristics of the observed sea breeze including a thermally direct circulation that results from differential low-level heating across the land-sea interface. Our intent is to determine the sensitivity of the circulation to the differential land surface forcing produced via the assimilation of GOES skin temperature tendencies. Results will be quantified through statistical verification techniques.

Lapenta, William M.↗
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 NTRS1984

A statistical correlation method for the retrieval of atmospheric moisture profiles by microwave radiometry

A statistical correlation technique is applied to the retrieval of vertical moisture profiles under clear-sky conditions from down-looking radiometric measurements of atmospheric radiation at microwave wavelengths. For a given set of channels, the method selects the optimum radiometric channels for estimating water vapor at specific pressure levels between the surface and 300 mb. The water vapor mixing ratio at these pressure levels is then calculated from a linear combination of the selected channel brightness temperatures. To test its validity the algorithm was applied, in a numerical experiment, to fifty independent tropical radiosondes. The rms absolute deviation of the estimated moisture profiles from the actual profiles was comparable to that obtained using an iterative retrieval method reported earlier. The statistical method, however, requires several orders of magnitude less computer time than the iterative method; it is suitable for high speed processing of large amounts of data.

Kakar, R. K.↗
NASA NTRS2020

Non-linear Least Square Fitting Technique for the Determination of Field Line Resonance Frequency in Ground Magnetometer Data: Application to Remote Sensing of Plasmaspheric Mass Density

The accurate determination of the Field Line Resonance (FLR) frequency of a resonating geomagnetic field line is necessary to remotely monitor the plasmaspheric mass density during geomagnetic storms and quiet times alike. Under certain assumptions the plasmaspheric mass density at the equator is inversely proportional to the square of the FLR frequency. The most common techniques to determine the FLR frequency from ground magnetometer measurements are the amplitude ratio and phase difference techniques, both based on geomagnetic field observations at two latitudinally separated ground stations along the same magnetic meridian. Previously developed automated techniques have used statistical methods to pinpoint the FLR frequency using the amplitude ratio and phase difference calculations. We now introduce a physics-based automated technique, using non-linear least square fitting of the ground magnetometer data to the analytical resonant wave equations, that reproduces the wave characteristics on the ground, and from those determine the FLR frequency. One of the advantages of the new technique is the estimation of physics-based errors of the FLR frequency, and as a result of the equatorial plasmaspheric mass density. We present analytical results of the new technique, and test it using data from the Inner-Magnetospheric Array for Geospace Science (iMAGS) ground magnetometer chain along the coast of Chile and the east coast of the United States. We compare the results with the results of previously published statistical automated techniques.

A. Boudouridis↗
NASA NTRS2021

Dealing with Ion LET Uncertainties: An Application of Generalized Linear Models

Although most SEE rate estimation methods presume a fit to SEE cross section vs. LET, fitting SEE data is challenging because the data are not compatible with the assumptions of many common fitting techniques (e.g. linear regression. The difficulty of fitting such data is compounded when the LET of the ion responsible for an SEE is uncertain. We modify a Generalized Linear Model SEE data fitting methodology to accommodate uncertain LET and apply the method to the problem of backside heavy-ion SEE testing to demonstrate the utility of the method, explore the dependence of systematic errors that arise from improper treatment of LET uncertainty and develop guidelines for minimizing such systematic errors when proper treatment is not possible. Additional applications are suggested and assessed for suitability of treatment by the model.

Single-event effects↗
NASA NTRS2023

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗
NASA NTRS1972

Planetary resonances, bi-stable oscillation modes, and solar activity cycles

The natural resonance structure of the planets in the solar system yields resonance periods of 11.08 and 180 years. The 11.08 year period is due to resonance of the sidereal periods of the three inner planets. The 180-year period is due to synodic resonances of the four major planets. These periods are also observed in the sunspot time series. The 11-year sunspot cycles from 1 to 19 are separated into categories of positive and negative cycles, Mode 1 and Mode 2 cycles, and typical and anomalous cycles. Each category has a characteristic shape, magnitude, or duration, so that statistical prediction techniques are improved when a cycle can be classified in a given category. These categories provide evidence for bistable modes of solar oscillation. The next minimum is expected in 1977 and the next maximum in 1981 or later. These epoch values are 2.5 years later than those based on typical cycle characteristics.

Sleeper, H. P., Jr.↗
NASA NTRS1971

Engineering experimental program on the effects of near-space radiation on lithium doped solar cells

The results of an experimental evaluation of the real-time degradation characteristics of lithium-diffused silicon solar cells are reported. A strontium-90 radioisotope was used for simulation of a typical earth-orbital electron environment. The experiment was performed in an ion pump vacuum chamber with samples maintained at -50, +20, +50, and +80 C. Samples were illuminated during the 6-month exposure run with solar cell 1-5 characteristics measured periodically in situ. This 6-month exposure corresponded to a 1 MeV equivalent fluence of approximately 10 to the 14th power electrons/sq cm. Several types of lithium cells were irradiatied and compared directly with conventional N/P cells. The best lithium cells compared favorably with N/P cells, particularly at the higher test temperatures. With a slight improvement of initial performance characteristics, lithium cells appear feasible for 5 to 10 year missions at synchronous altitude. Based on the reported results and those of other irradiation experiments, lithium cells would appear to be superior to N/P cells in proton-dominated earth-orbital environments. Another important conclusion of the effort was that illuminated/loaded cells degrade more rapidly than do dark/unloaded cells. The irradiation experiment provided data of high quality with a high degree of confidence because of the experimental and statistical analysis techniques utilized.

Source record↗
NASA NTRS1972

Goddard trajectory determination subsystem: Mathematical specifications

The mathematical specifications of the Goddard trajectory determination subsystem of the flight dynamics system are presented. These specifications include the mathematical description of the coordinate systems, dynamic and measurement model, numerical integration techniques, and statistical estimation concepts.

Wagner, W. E.↗
NASA NTRS1974

Implementation of ILLIAC 4 algorithms for multispectral image interpretation

Research has focused on the design and partial implementation of a comprehensive ILLIAC software system for computer-assisted interpretation of multispectral earth resources data such as that now collected by the Earth Resources Technology Satellite. Research suggests generally that the ILLIAC 4 should be as much as two orders of magnitude more cost effective than serial processing computers for digital interpretation of ERTS imagery via multivariate statistical classification techniques. The potential of the ARPA Network as a mechanism for interfacing geographically-dispersed users to an ILLIAC 4 image processing facility is discussed.

Ray, R. M.↗
NASA NTRS1975

Measurements of SO2 absorption coefficients using a tunable dye laser

High-resolution measurements of SO2 absorption coefficients in the UV are presented in the wavelength interval between 2962 and 3011 A using a frequency-doubled dye laser as the radiation source. These measurements have application to pollution monitoring of SO2 using the differential absorption scattering (DAS) technique. The spectral resolution of the measurements was 0.2 A (determined by the linewidth of the dye laser) and the generated spectra exhibited considerable rotational structure on the (000) double prime to (060) prime, (070) prime, and (080) prime electronic-vibrational transitions. The latter transitions correspond to center wavelengths of 3001.8, 2981.0, and 2962 A, respectively. The laser measurements were obtained with a signal-processing technique which eliminated calibration procedures associated with conventional optical-absorption measurements. Using this technique, the statistical uncertainty associated with measured absorption coefficients has been reduced to less than plus or minus 2% with a wavelength uncertainty of the laser source of plus or minus 0.1 A.

Thompson, R. T., Jr.↗
NASA NTRS1976

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Waller, M. C.↗