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At least 235 records · Page 13

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NASA NTRS1984

Interannual length-of-day variation with relation to the southern oscillation/El Nino

The atmospheric and oceanic mass transport associated with the southern oscillation/El Nino will inevitably induce an interannual variation in the length of day. An empirical correlation study is conducted by comparing the Southern Oscillation Index time series and the interannual length-of-day variation (obtained by removing the long-period and short-period variations from a BIH length-of-day series) for the period 1957-1983. The two series have an encouraging qualitative correlation, in particular with respect to El Nino events; and the linear correlation coefficient is found to be 0.55. It is believed that much, if not most, interannual length-of-day variation is caused by the southern oscillation, and the true correlation is considerably higher than its apparent value considering the fact that the Southern Oscillation Index is merely an indicator derived from two local atmospheric measurements.

Chao, B. F.↗

NASA NTRS1985

A relation between the short time variations of cosmic rays and geomagnetic field change

An event is reported of approx. 37 min periodicity in cosmic ray intensity observed at Akeno(38 deg 47 N, 138 deg 30 E. 900m above s.l., cutoff 10.4 GV) during 1300 approx. 1900 UT on April 25th, 1984, just a day before Forbush decrease of April 26th. This event seemed to be followed by the periodic variations of the geomagnetic field observed at Kakioka (36 deg 23 N, 140 deg 18 E). The regression coefficient between them was obtained approx. 0.07%/10nT. It is shown that in general the power spectral density of cosmic rays in the frequency of 0.0001 approx. 0.001Hz correlates positively with the fluctuations of geomagnetic field (Dst field) around approx. 1.2x0.0001Hz. From the analysis of 47 days data (April 14th to June 13th, 1984) the regression curve was obtained as y=0.275x sup 0.343 with the correlation coefficient of 0.48, where x and y mean Fourier components of Dst field summed over 1.04 approx. 1.39x0.001Hz and cosmic ray power spectral density averaged over 0.0001 approx. 0.001Hz.

Saki, T.↗

NASA NTRS2014

AE Geomagnetic Index Predictability for High Speed Solar Wind Streams: A Wavelet Decomposition Technique

High speed solar wind streams cause geomagnetic activity at Earth. In this study we have applied a wavelet interactive filtering and reconstruction technique on the solar wind magnetic field components and AE index series to allowed us to investigate the relationship between the two. The IMF Bz component was found as the most significant solar wind parameter responsible by the control of the AE activity. Assuming magnetic reconnection associated to southward directed Bz is the main mechanism transferring energy into the magnetosphere, we adjust parameters to forecast the AE index. The adjusted routine is able to forecast AE, based only on the Bz measured at the L1 Lagrangian point. This gives a prediction approximately 30-70 minutes in advance of the actual geomagnetic activity. The correlation coefficient between the observed AE data and the forecasted series reached values higher than 0.90. In some cases the forecast reproduced particularities observed in the signal very well.The high correlation values observed and the high efficacy of the forecasting can be taken as a confirmation that reconnection is the main physical mechanism responsible for the energy transfer during HILDCAAs. The study also shows that the IMF Bz component low frequencies are most important for AE prediction.

Space weather↗

NASA NTRS1974

Correlation analysis of X-ray emission from Cygnus X-1

Normalized autocorrelation and cross-correlation coefficients have been calculated for the X-ray emission of Cygnus X-1 in two energy bins, 2.1-5.1 keV and 5.1-12 keV. The analysis shows a strong correlation between the pulsations in the two energy bins, with the low-energy pulsations lagging behind the high-energy ones, or alternatively a shorter duration of the pulse trains in the high-energy bin. The power spectral density derived from the autocorrelation functions indicates a larger contribution of the high-frequency components for the higher-energy X-rays.

Brinkman, A. C.↗

NASA NTRS1990

Thermal forcing on the tropical Pacific from satellite data

Monthly fields of latent heat flux and surface solar irradiance derived from spaceborne sensors were combined to estimate the surface thermal forcing on the tropical Pacific from 1980 to 1983. The annual cycle and the anomalies associated with 1982-1983 ENSO episode were examined. Along the equator and during the early phase of the episode the reduction of solar irradiance into the ocean is found to be compensated to some extent by the decrease in evaporative cooling. The distribution of correlation coefficients demonstrated that outside the equatorial waveguides, surface thermal forcing plays a significant role in the seasonal change of sea surface temperature and surface solar irradiance is main driving force. Significant correlation is also found between anomalous latent heat flux and anomalous change of sea surface temperature over a broad area in the equatorial and southern tropical Pacific, indicating that surface thermal forcing may play a larger role than expected in the anomalous sea surface temperature change, particularly in the reestablishment of the cold tongue at end of the episode.

Liu, W. Timothy↗

NASA NTRSDate not supplied

Sensitivity Analysis of the Human Research Program’s Impact 1.0 Model

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Leave One Out (LOO) are methods of conducting sensitivity analysis on non-linear simulation models like the IMPACT Model. The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The “partial” part is due to the adjustments made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. LOO removes a medical condition from test suite and calculates the change in the outcome. This is used to identify the influence of the condition input in the model The inputs to the sensitivity procedures include the number of occurrences of each of the one hundred plus IMPACT medical conditions generated over the simulations, and the IMPACT outputs from the MEDPRAT mathematical model. The outputs total task time lost (TTL), number of return to definitive care (RTDC), and number of loss of crew lives (LOCL). The IMPACT team will report the results of using PRCC and LOO on IMPACT 1.0. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty, and input values could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMPACT 1.0.

Sensitivity Anaylsis↗

NASA NTRS1975

Quantitative suspended sediment mapping using aircraft remotely sensed multispectral data

Suspended sediment is an important environmental parameter for monitoring water quality, water movement, and land use. Quantitative suspended sediment determinations were made from analysis of aircraft remotely sensed multispectral digital data. A statistical analysis and derived regression equation were used to determine and plot quantitative suspended sediment concentration contours in the tidal James River, Virginia, on May 28, 1974. From the analysis, a single band, Band 8 (0.70-0.74 microns), was adequate for determining suspended sediment concentrations. A correlation coefficient of 0.89 was obtained with a mean inaccuracy of 23.5 percent for suspended sediment concentrations up to about 50 mg/l. Other water quality parameters - secchi disc depth and chlorophyll - also had high correlations with the remotely sensed data. Particle size distribution had only a fair correlation with the remotely sensed data.

Johnson, R. W.↗

NASA NTRS1976

Flight test design for efficient extraction of aircraft parameters

This paper considers the design of flight control inputs which result in a minimization of the nonuniqueness problem of parameter identification due to statistical correlation. The performance index for the control design is taken as a linear weighted sum of the squares of the correlation coefficients of the aerodynamic stability and control derivatives as computed from the Cramer-Rao lower bound matrix. An optimal input design is demonstrated for an F-8 aircraft with supercritical wing. Reduced correlations are noted and corresponding estimates and confidence levels presented.

Wells, W. R.↗

NASA NTRS1982

Tropical cyclone track and genesis forecasting using satellite microwave sounder data

Although many dynamical and statistical prediction schemes are available to forecasters, tropical cyclone track errors are still large. One primary difficulty is that tropical cyclones exist over the data-sparse tropical oceans. Satellite sounders, however, routinely provide numerous data over these areas. Mean layer temperatures from the Scanning Microwave Spectrometer on board the Nimbus 6 satellite are decomposed using empirical orthogonal functions, and the expansion coefficients are related to deviations from the persistence forecast location, to speed change, to direction change and to intensity change. The significance of the regression equations is tested by a null hypothesis of zero correlation coefficient. It appears that significant information about tropical cyclone motion exists in the satellite-estimated mean layer temperatures, especially at upper levels. A physical interpretation of the statistical results is offered, and a one-storm-out independent test is used to test the stability of the equations. Finally, some further work is suggested.

Kidder, S. Q.↗

NASA NTRS1983

Cape Canaveral, Florida range reference atmosphere 0-70 km altitude

The RRA contains tabulations for monthly and annual means, standard deviations, skewness coefficients for wind speed, pressure temperature, density, water vapor pressure, virtual temperature, dew-point temperature, and the means and standard deviations for the zonal and meridional wind components and the linear (product moment) correlation coefficient between the wind components. These statistical parameters are tabulated at the station elevation and at 1 km intervals from sea level to 30 km and at 2 km intervals from 30 to 90 km altitude. The wind statistics are given at approximately 10 m above the station elevations and at altitudes with respect to mean sea level thereafter. For those range sites without rocketsonde measurements, the RRAs terminate at 30 km altitude or they are extended, if required, when rocketsonde data from a nearby launch site are available. There are four sets of tables for each of the 12 monthly reference periods and the annual reference period.

Tingle, A.↗

NASA NTRS2008

Relativistic Electrons at Geostationary Orbit: Modeling Results

We developed a new prediction model for forecasting relativistic (greater than 2MeV) electrons, which provides a VERY HIGH correlation between predicted and actually measured electron fluxes at geostationary orbit. This model implies the multi-step particle acceleration and is based on numerical integrating two linked continuity equations for primarily accelerated particles and relativistic electrons. The model includes a source and losses, and used solar wind data as only input parameters. We used the coupling function which is a best-fit combination of solar wind/interplanetary magnetic field parameters, responsible for the generation of geomagnetic activity, as a source. The loss function was derived from experimental data. We tested the model for four year period 2004-2007. The correlation coefficient between predicted and actual values of the electron fluxes for whole four year period as well as for each of these years is stable and incredibly high (about 0.9). The high and stable correlation between the computed and actual electron fluxes shows that the reliable forecasting these electrons at geostationary orbit is possible.

Khazanov, George V.↗

NASA NTRS2008

Prediction Model for Relativistic Electrons at Geostationary Orbit

Khazanov, George V.↗

NASA NTRS2024

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗

DOE OSTI2024

Climatic Drivers for the Variation of Gross Primary Productivity Across Terrestrial Ecosystems in the United States

Abstract Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future.

Environmental Sciences & Ecology↗

NASA NTRS2010

A Ground-Based Comparison of the Muscle Atrophy Research and Exercise System (MARES) and a Standard Isokinetic Dynamometer

PURPOSE: 1) To compare the test-to-test reliability of Muscle Atrophy Research and Exercise System (MARES) with a standard laboratory isokinetic dynamometer (ISOK DYN) and; 2) to determine if measures of peak torque and total work differ between devices. METHODS: Ten subjects (6M, 4F) completed two trials on both MARES and an ISOK DYN in a counterbalanced order. Peak torque values at 60 deg & 180 deg / s were obtained from five maximal repetitions of knee extension (KE) and knee flexion (KF). Total work at 180 deg / s was determined from the area under the torque vs. displacement curve during twenty maximal repetitions of KE and KF. Reliability of measures within devices was interpreted from the intraclass correlation coefficient (ICC) and compared between devices using the ratio of the within-device standard deviations. Indicators of agreement for the two devices were evaluated from: 1) a calculation of concordance (rho) and; 2) the correlation between the mean of measures versus the delta difference between measures (m u vs delta). RESULTS: For all outcome measures ICCs were high for both the ISOK DYN (0.95-0.99) and MARES (0.90-0.99). However, ratios of the within-device standard deviation were 1.3 to 4.3 times higher on MARES. On average, a wide range (3.3 to 1054 Nm) of differences existed between the values obtained. Only KE peak torque measured at 60 deg & 180 deg / s showed similarities between devices (rho = 0.91 & 0.87; Pearson's r for m u vs delta = -0.22 & -0.37, respectively). CONCLUSION: Although MARES was designed for use in microgravity it was quite reliable during ground-based testing. However, MARES was consistently more variable than an ISOK DYN. Future longitudinal studies evaluating a change in isokinetic peak torque or total work should be limited within one device.

Hackney, K. J.↗

NASA NTRS2019

A Global Climatology of Extratropical Transition Part II: Statistical Performance of the Cyclone Phase Space

This study analyzes the differences between an objective, automated identification of tropical cyclones (TCs) that undergo extratropical transition (ET), and the designation of ET determined subjectively by human forecasters in best-track data in all basins globally. The objective identification of ET is based on the cyclone phase space (CPS), calculated from the Japanese 55-year Reanalysis (JRA-55) or the ECMWF Interim Reanalysis (ERA-Interim). The resulting classification into “ET storms” and “non-ET storms” underlies the global climatology of ET presented in Part I of this study. Here, the authors investigate how well the CPS classifications agree with those in the best-track records calculated from JRA-55 or from ERA-Interim data. According to F1 scores and Matthews correlation coefficients (MCCs), the classification of ET storms in the CPS agrees best with the best-track classification in the Western North Pacific (MCC > 0.7) and the North Atlantic (MCC > 0.5). In other basins, the correlation between the CPS classification and the best-track classification is only slightly higher than that of a random classification. The JRA-55 classification achieves higher performance scores than does the ERA-Interim classification, and the differences are statistically significant in all basins. The lower performance of ERA-Interim is mainly due to a higher false alarm rate, particularly in the Eastern North Pacific. Overall, the results show that while the CPS-based classifications are good enough to be useful for many purposes, there is almost certainly room for improvement – in the representation of the storms in reanalyses, in our objective metrics of ET, and in our scientific understanding of the ET process.

Melanie Bieli↗

DOE OSTI2023

Considering Factors for Ion Concentrations in Precipitation at the Savannah River Site

Precipitation was collected from three different areas on the Savannah River Site during 2021. The precipitation was analyzed for concentrations of 29 different ions and compared with data on factors such as wind speed, wind direction, rain drop sizes, and more. The 2021 ion concentrations were also compared to the ion concentrations from previous years at the site as well as from Santee National Wildlife Refuge which is nearby. The historical ion concentrations data was gathered from the National Atmospheric Deposition Program. Scatter plots and correlation coefficients were used to identify what factors may have the greatest impact on ion concentration in rainwater. The data generally followed the same trends with a few notable outliers. There initially seemed to be a strong correlation between the mean diameter and some ion concentrations as both increased in July. However, ion concentrations in different areas were related to different wind directions, thus spatial variability must be considered. These factors, spatial variability of atmospheric particles and wind direction, impact concentrations of ions in precipitation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1981

Two-dimensional turbulence models

Two-dimensional turbulence models are compared with experimental measurements made using an array of instrumented towers. The spatial correlation coefficient, the two-point spectrum or cross spectrum, and the coherence function are discussed. The prediction techniques in general agree reasonably well with the experimental results. Measurements of the integral length scale however, do not correlate well with the prediction model.

Frost, W.↗