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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Assessment of Tropospheric Concentrations of NO2 from the TROPOMI/Sentinel-5 Precursor for the Estimation of Long-Term Exposure to Surface NO2 over South Korea

Since April 2018, the TROPOspheric Monitoring Instrument (TROPOMI) has provided data on tropospheric NO2 column concentrations (CTROPOMI) with unprecedented spatial resolution. This study aims to assess the capability of TROPOMI to acquire high spatial resolution data regarding surface NO2 mixing ratios. In general, the instrument effectively detected major and moderate sources of NO2 over South Korea with a clear weekday–weekend distinction. We compared the CTROPOMI with surface NO2 mixing ratio measurements from an extensive ground-based network over South Korea operated by the Korean Ministry of Environment (SKME; more than 570 sites), for 2019. Spatiotemporally collocated CTROPOMI and SKME showed a moderate correlation (correlation coefficient, r = 0.67), whereas their annual mean values at each site showed a higher correlation (r = 0.84). The CTROPOMI and SKME were well correlated around the Seoul metropolitan area, where significant amounts of NO2 prevailed throughout the year, whereas they showed lower correlation at rural sites. We converted the tropospheric NO2 from TROPOMI to the surface mixing ratio (STROPOMI) using the EAC4 (ECMWF Atmospheric Composition Reanalysis 4) profile shape, for quantitative comparison with the SKME. The estimated STROPOMI generally underestimated the in-situ value obtained, SKME (slope = 0.64), as reported in previous studies.

TROPOMI↗
NASA NTRS1976

Closure and ratio correlation analysis of lunar chemical and grain size data

Major element and major element plus trace element analyses were selected from the lunar data base for Apollo 11, 12 and 15 basalt and regolith samples. Summary statistics for each of the six data sets were compiled, and the effects of closure on the Pearson product moment correlation coefficient were investigated using the Chayes and Kruskal approximation procedure. In general, there are two types of closure effects evident in these data sets: negative correlations of intermediate size which are solely the result of closure, and correlations of small absolute value which depart significantly from their expected closure correlations which are of intermediate size. It is shown that a positive closure correlation will arise only when the product of the coefficients of variation is very small (less than 0.01 for most data sets) and, in general, trace elements in the lunar data sets exhibit relatively large coefficients of variation.

Butler, J. C.↗
NASA NTRS1989

Remote sensing of earth terrain

A mathematically rigorous and fully polarimetric radar clutter model used to evaluate the radar backscatter from various types of terrain clutter such as forested areas, vegetation canopies, snow covered terrains, or ice fields is presented. With this model, the radar backscattering coefficients for the multichannel polarimetric radar returns can be calculated, in addition to the complex cross correlation coefficients between elements of the polarimetric measurement vector. The complete polarization covariance matrix can be computed and the scattering properties of the clutter environment characterized over a broad range of incident angle and frequencies.

Kong, J. A.↗
NASA NTRS2015

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

Evaluation↗
NASA NTRS2014

Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S.

Monitoring groundwater drought using land surface models is a valuable alternative given the current lack of systematic in situ measurements at continental and global scales and the low resolution of current remote sensing based groundwater data. However, uncertainties inherent to land surface models may impede drought detection, and thus should be assessed using independent data sources. In this study, we evaluated a groundwater drought index (GWI) derived from monthly groundwater storage output from the Catchment Land Surface Model (CLSM) using a GWI similarly derived from in situ groundwater observations. Groundwater observations were obtained from unconfined or semi-confined aquifers in eight regions of the central and northeastern U.S. Regional average GWI derived from CLSM exhibited strong correlation with that from observation wells, with correlation coefficients between 0.43 and 0.92. GWI from both in situ data and CLSM was generally better correlated with the Standard Precipitation Index (SPI) at 12 and 24 month timescales than at shorter timescales, but it varied depending on climate conditions. The correlation between CLSM derived GWI and SPI generally decreases with increasing depth to the water table, which in turn depends on both bedrock depth (a CLSM parameter) and mean annual precipitation. The persistence of CLSM derived GWI is spatially varied and again shows a strong influence of depth to groundwater. CLSM derived GWI generally persists longer than GWI derived from in situ data, due at least in part to the inability of coarse model inputs to capture high frequency meteorological variability at local scales. The study also showed that groundwater can have a significant impact on soil moisture persistence where the water table is shallow. Soil moisture persistence was estimated to be longer in the eastern U.S. than in the west, in contrast to previous findings that were based on models that did not represent groundwater. Assimilation of terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission improved the correlation between CLSM based regional average GWI and that based on in situ data in six of the eight regions. Practical issues regarding the application of GRACE assimilated groundwater storage for drought detection are discussed. An important conclusion of this study is that model parameters that control the depth to the water table, including bedrock depth, strongly influence the evolution and persistence of simulated groundwater and require careful configuration for drought monitoring.

hydrology↗
NASA NTRS2021

Relationship between Horizontal Wind Velocity and Normalized Surface Cross Section Using Data from the HIWRAP Dual-Frequency Airborne Radar

The High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) dual-frequency conically scanning airborne radar provides estimates of the range-profiled mean Doppler and backscattered power from the precipitation and surface. A velocity–azimuth display analysis yields near-surface estimates of the mean horizontal wind vector υh in cases in which precipitation is present throughout the scan. From the surface return, the normalized radar cross section (NRCS) is obtained, which, by a method previously described, can be corrected for path attenuation. Comparisons between υh and the attenuation-corrected NRCS are used to derive transfer functions that provide estimates of the wind vector from the NRCS data under both rain and rain-free conditions. A reasonably robust transfer function is found by using the mean NRCS (⟨NRCS⟩) over the scan along with a filtering of the data based on a Fourier series analysis of υh and the NRCS. The approach gives good correlation coefficients between υh and ⟨NRCS⟩ at Ku band at incidence angles of 30° and 40°. The correlation degrades if the Ka-band data are used rather than the Ku band.

R Meneghini↗
NASA NTRS1975

Estimating snow depth using VHRR data from NOAA environmental satellites

The NOAA environmental satellites provide daily coverage of the earth in the visible and thermal spectral bands. The ground resolution of the very high resolution radiometer is 1 km at nadir. This improved resolution in the visible permits more detailed observations of snow features than was possible with previous operational satellites. A densitometer examination of a visible-band image from Feb. 11, 1973, which shows heavy snow cover in considerable detail over areas extending from Alabama to North Carolina, indicates that, in general, there is direct correlation between increasing brightness and increasing snow depths. A power regression analysis of greatest satellite brightness versus greatest snow depth for 201 data pairs produced a correlation coefficient of 0.86. Similar analysis of five late winter and early spring cases resulted in much lower correlations.

Mcginnis, D. F., Jr.↗
NASA NTRS2016

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGONNE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 x AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

Choi, Myungje↗
NASA NTRS2021

Organized kinetic energy backscatter in the hurricane boundary layer from radar measurements

The fluid mechanics of hurricanes strongly depends on boundary layer energetics due to the warm-core nature of the system with peak velocities located at lower levels. One barrier that has inhibited a more complete characterization of energy transfer in the boundary layer is a lack of observations that resolve large, turbulent eddies. In particular, the occurrence and structure of upscale energy transfer (backscatter) in the hurricane boundary layer as well as the effects of backscatter on the vortex intensity are unknown. The analysis presented here of very high-resolution, three-dimensional wind observations from Hurricane Rita (2005) at peak intensity reveals large regions of organized backscatter in the boundary layer associated with coherent, turbulent eddies. Strong forwardscatter is also found next to the backscatter regions due to the interaction between adjacent eddies. Two components of the stress tensor are primarily responsible for this alternating scatter structure, as shown by large correlation coefficients between the fields: the radial–vertical component (τ13) and the azimuthal–vertical component (τ23) with average correlations of 79% and 49 %, respectively. The Leonard, Reynolds and cross-term stress components are also provided. The impact of the sub-filter-scale energy transfer is estimated by computing the kinetic energy budget for the resolved-scale and eddy-scale motions. The results show that the sub-filter-scale energy transfer term is of the same order as the other terms in the eddy-scale budgets, contributing between 16% and 40% to the local time tendency with an average contribution of approximately 30 %. These results indicate that the coherent turbulent eddies can affect the vortex dynamics through wave–wave nonlinear interactions, which can subsequently influence the wave–mean flow interactions. This is the first study to examine the full sub-filter-scale

Sydney Sroka↗
NASA NTRS2016

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). 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 so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. 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 could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

medical equipment↗
NASA NTRS1980

Remote sensing of benthic microalgal biomass with a tower-mounted multispectral scanner

A remote sensing instrument was mounted on a 50-ft tower overlooking North Inlet Estuary, South Carolina in order to conduct a remote sensing study of benthic microalgae. The instrument was programmed to take multispectral imagery data along a 90 deg horizontal frame in six spectral bands ranging from 400-1050 nm and had a ground resolution of about 3 cm. Imagery measurements were encoded in digital form on magnetic tape and were stored, decoded, and manipulated by computer. Correlation coefficients were calculated on imagery data and chlorophyll a concentrations derived from ground truth data. The most significant correlation occurred in the blue spectral band with numerical values ranging from -0.81 to -0.88 for three separate sampling periods. Mean values of chlorophyll a for a larger section of mudflat were estimated using regression equations. The scanner has provided encouraging results and promises to be a useful tool in sampling the biomass of intertidal benthic microalgae.

Jobson, D. J.↗
NASA NTRS1998

A Priori Analyses of Three Subgrid-Scale Models for One-Parameter Families of Filters

The decay of isotropic turbulence a compressible flow is examined by direct numerical simulation (DNS). A priori analyses of the DNS data are then performed to evaluate three subgrid-scale (SGS) models for large-eddy simulation (LES): a generalized Smagorinsky model (M1), a stress-similarity model (M2), and a gradient model (M3). The models exploit one-parameter second- or fourth-order filters of Pade type, which permit the cutoff wavenumber k(sub c) to be tuned independently of the grid increment (delta)x. The modeled (M) and exact (E) SGS-stresses are compared component-wise by correlation coefficients of the form C(E,M) computed over the entire three-dimensional fields. In general, M1 correlates poorly against exact stresses (C < 0.2), M3 correlates moderately well (C approx. 0.6), and M2 correlates remarkably well (0.8 < C < 1.0). Specifically, correlations C(E, M2) are high provided the grid and test filters are of the same order. Moreover, the highest correlations (C approx.= 1.0) result whenever the grid and test filters are identical (in both order and cutoff). Finally, present results reveal the exact SGS stresses obtained by grid filters of differing orders to be only moderately well correlated. Thus, in LES the model should not be specified independently of the filter.

Pruett, C. David↗
NASA NTRS2013

On the Nature of the mHz X-Ray QPOs from ULX M82 X-1: Evidence for Timing-Spectral (anti) Correlation

Using all the archival XMM-Newton X-ray (3-10 keV) observations of the ultraluminous X-ray source (ULX) M82 X-1 we searched for a correlation between its variable mHz quasi-periodic oscillation (QPO) frequency and its energy spectral power-law index. These quantities are known to correlate in stellar mass black holes (StMBHs) exhibiting Type-C QPOs (approx 0.2-15 Hz). The detection of such a correlation would strengthen the identification of its mHz QPOs as Type-C and enable a more reliable mass estimate by scaling its QPO frequencies to those of Type-C QPOs in StMBHs of known mass. We resolved the count rates of M82 X-1 and a nearby bright ULX (source 5/X42.3+59) through surface brightness modeling and identify observations in which M82 X-1 was at least as bright as source 5. Using only those observations, we detect QPOs in the frequency range of 36-210 mHz during which the energy spectral power-law index varied from 1.7-2.2. Interestingly, we find evidence for an anti-correlation (Pearsons correlation coefficient = -0.95) between the power-law index and the QPO centroid frequency. While such an anti-correlation is observed in StMBHs at high Type-C QPO frequencies (approx 5-15 Hz), the frequency range over which it holds in StMBHs is significantly smaller (factor of approx 1.5-3) than the QPO range reported here from M82 X-1 (factor of 6). However, it remains possible that contamination from source 5 can bias our result. Joint Chandra/XMM-Newton observations in the future can resolve this problem and confirm the timing-spectral anti-correlation reported here.

Pasham, Dheeraj R.↗
NASA NTRS1995

Performance of Residual Carrier Array Feed Combining in Correlated Noise

An array feed combining system for the recovery of SNR loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34 meter DSS-13 antenna. In this system, the defocused signal field captured by a focal plane array feed is recovered using real-time signal processing and signal combining techniques. The current signal processing and signal combining algorithms are optimum under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. Experimental data at DSS-13 indicate that these noise processes are indeed mutually correlated. The main result of this paper is an analytical derivation of the actual SNR performance of the current suboptimal signal combining algorithm in this correlated noises environment. The analysis here shows that the combined signal SNR can either be improved or degraded depending on the relation between the array signal and noise correlation coefficient phases. Further performance improvement will require the development of signal combining methods that take into account the correlated noises.

Residual↗
NASA NTRS1972

Evaluation of the pulse-contour method of determining stroke volume in man.

The pulse-contour method for determining stroke volume has been employed as a continuous rapid method of monitoring the cardiovascular status of patients. Twenty-one patients with ischemic heart disease and 21 patients with mitral valve disease were subjected to a variety of hemodynamic interventions. The pulse-contour estimations, using three different formulas derived by Warner, Kouchoukos, and Herd, were compared with indicator-dilution outputs. A comparison of the results of the two methods for determining stroke volume yielded correlation coefficients ranging from 0.59 to 0.84. The better performing Warner formula yielded a coefficient of variation of about 20%. The type of hemodynamic interventions employed did not significantly affect the results using the pulse-contour method. Although the correlation of the pulse-contour and indicator-dilution stroke volumes is high, the coefficient of variation is such that small changes in stroke volume cannot be accurately assessed by the pulse-contour method. However, the simplicity and rapidity of this method compared to determination of cardiac output by Fick or indicator-dilution methods makes it a potentially useful adjunct for monitoring critically ill patients.

Alderman, E. L.↗
NASA NTRS1991

Results of a sub-scale model rotor icing test

A heavily instrumented sub-scale model of a helicopter main rotor was tested in the NASA Lewis Research Center Icing Research Tunnel (IRT) in September and November 1989. The four-bladed main rotor had a diameter of 1.83 m (6.00 ft) and the 0.124 m (4.9 in) chord rotor blades were specially fabricated for this experiment. The instrumented rotor was mounted on a Sikorsky Aircraft Powered Force Model, which enclosed a rotor balance and other measurement systems. The model rotor was exposed to a range of icing conditions that included variations in temperature, liquid water content, and median droplet diameter, and was operated over ranges of advance ratio, shaft angle, tip Mach number (rotor speed) and weight coefficient to determine the effect of these parameters on ice accretion. In addition to strain gage and balance data, the test was documented with still, video, and high speed photography, ice profile tracings, and ice molds. The sensitivity of the model rotor to the test parameters, is given, and the result to theoretical predictions are compared. Test data quality was excellent, and ice accretion prediction methods and rotor performance prediction methods (using published icing lift and drag relationships) reproduced the performance trends observed in the test. Adjustments to the correlation coefficients to improve the level of correlation are suggested.

Flemming, Robert J.↗
NASA NTRS1991

Results of a sub-scale model rotor icing test

A heavily instrumented sub-scale model of a helicopter main rotor was tested in the NASA Lewis Research Center Icing Research Tunnel (IRT) in September and November 1989. The four-bladed main rotor had a diameter of 1.83 m (6.00 ft) and the 0.124 m (4.9 in) chord rotor blades were specially fabricated for this experiment. The instrumented rotor was mounted on a Sikorsky Aircraft Powered Force Model, which enclosed a rotor balance and other measurement systems. The model rotor was exposed to a range of icing conditions that included variations in temperature, liquid water content, and median droplet diameter, and was operated over ranges of advance ratio, shaft angle, tip Mach number (rotor speed) and weight coefficient to determine the effect of these parameters on ice accretion. In addition to strain gage and balance data, the test was documented with still, video, and high speed photography, ice profile tracings, and ice molds. The sensitivity of the model rotor to the test parameters is given, and the result to theoretical predictions are compared. Test data quality was excellent, and ice accretion prediction methods and rotor performance prediction methods (using published icing lift and drag relationships) reproduced the performance trends observed in the test. Adjustments to the correlation coefficients to improve the level of correlation are suggested.

Flemming, Robert J.↗