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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Normal modes in an overmoded circular waveguide coated with lossy material

The normal modes in an overmoded waveguide coated with a lossy material are analyzed, particularly for their attenuation properties as a function of coating material, layer thickness, and frequency. When the coating material is not too lossy, the low-order modes are highly attenuated even with a thin layer of coating. This coated guide serves as a mode suppressor of the low-order modes, which can be particularly useful for reducing the radar cross section (RCS) of a cavity structure such as a jet inlet. When the coating material is very lossy, low-order modes fall into two distinct groups: highly and lowly attenuated modes. However, as a/lambda (a = radius of the cylinder; lambda = the free-space wavelength) increases, the separation between these two groups becomes less distinctive. The attenuation constants of most of the low-order modes become small, and decrease as a function of lambda sup 2/a sup 3.

Lee, C. S.↗
NASA NTRS1986

Normal modes in an overmoded circular waveguide coated with lossy material

The normal modes in an overmoded waveguide coated with a lossy material are analyzed, particularly for their attenuation properties as a function of coating material, layer thickness, and frequency. When the coating material is not too lossy, the low-order modes are highly attenuated even with a thin layer of coating. This coated guide serves as a mode suppressor of the low-order modes, which can be particularly useful for reducing the radar cross section of a cavity structure such as a jet engine inlet. When the coating material is very lossy, low-order modes fall into two distinct groups: highly and lowly attenuated modes. However, as a/lambda (a = radius of the cylinder; lambda = the free-space wavelength) increases, the separation between these two groups becomes less distinctive. The attenuation constants of most of the low-order modes become small and decrease as a function of lambda-squared/a-cubed.

Lee, C. S.↗
NASA NTRS1990

Tropical Rainfall Measuring Mission (TRMM) project. VII - Techniques for radar data processing

The paper describes algorithms for rain-rate profiling with an airborne or space-borne radar. Some problems involved in the radar measurements from an airborne or space-borne platform are discussed. An outline of a dual-frequency algorithm is described and its performance is confirmed by a computer simulation and an airborne experiment. A single-frequency algorithm is developed by introducing a path-integrated rain rate estimated from an attenuation of surface echoes or from microwave brightness temperature. The computer simulation shows good performance for an airborne or space-borne radar.

Meneghini, Robert↗
NASA NTRS1991

Polarization radar measurements in rain at 5 and 9 GHz

Potential techniques for measuring rainfall rate R and rainwater content W at 9 and 5 GHz are explored. An investigation is made of a previous technique to use the polarization propagation differential phase shift with increasing distance from the radar Phi(H-V) to estimate and remove the effects of specific and polarization differential attenuation from Z(H) and Z(DR), respectively. It is shown that in rain this technique is sensitive to variations in the drop-size distribution. It is confirmed that Phi(H-V) can be used to extend the distance over which useful measurements of Z(H) and Z(DR) can be obtained. While residual errors introduced by attenuation and the 'noise' from the correction scheme itself eclipse the potential of many possible techniques for quantitative rainfall measurements at these frequencies, the attenuation recovery scheme is argued to be adequate for obtaining useful polarization microphysical measurements, particularly above the melting level, even after encounters with rain.

Jameson, A. R.↗
NASA NTRS2003

Surface Penetrating Radar Simulations for Jupiter's Icy Moons

The icy moons of Jupiter (Europa, Callisto, and Ganymede) are of similar overall composition but show different surface features as a result of different sub-surface processes. Furthermore, each of these moons could have a liquid ocean of water buried underneath the icy crust, but their depth can only be speculated. For Europa, estimates put the thickness of the ice shell anywhere between 2-30 km, with'a few models predicting up to 100 km. Much of the uncertainties are due to the largely unknown temperature gradients and levels of water impurities across different surface layers. One of the most important geological processes is the possible transportation of heat by ice convection. If the ice is convecting, then an upper limit of about 20 km is set for the depth of the ocean underneath. Convection leads to a sharp increase in temperature followed by a thick region of nearly constant temperature. If ice is not convecting, then an exponentially increasing temperature profile is expected. The crust is thought to be a mixture of ice and rock, and although the exact percentage of rock is not known, it is expected to be low. Additionally, the ice crust could contain salt, similar to sea ice on Earth. The exact amount of salt and how that amount changes with depth is also unknown. In preparation for the Jupiter Icy Moons Orbiter (JIMO) mission, we performed simulations for a surface-penetrating radar investigating signatures for different possible surface and sub-surface structures of these moons in order to estimate the applicability of using radar with a frequency range between 1 and 50 MHz. This includes simulations of power requirements, attenuation losses, layer resolutions for scenarios with and without the presence of a liquid ocean underneath the ice, cases of convecting and non-convecting ice, different impurities within the ice, and different surface roughnesses.

Markus, Thorsten↗
NASA NTRS2020

The GPM Ground Validation Program

We present a detailed overview of the structure and activities associated with the NASA-led ground-validation component of the NASA-JAXA Global Pre­cipitation Measurement (GPM) mission. The overarching philosophy and approaches for NASA's GV program are presented with primary focus placed on aspects of direct validation and a summary of physical validation campaigns and results. We describe a spectrum of key instruments, methods, field campaigns and data products developed and used by NASA's GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASA's Level-I science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated Multi­satellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the US) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

precipitation↗
NASA NTRS2011

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗
NASA NTRS2011

A Ground Validation Network for the Global Precipitation Measurement Mission

A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA's Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to "matchup" the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was -1.88 dBZ. The PR-GR bias was found to increase with the amount of PR attenuation correction applied, with the PR-GR bias reaching -3.07 dBZ in cases where the attenuation correction applied is greater than 6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%-40%.

Schwaller, Mathew R.↗
NASA NTRS2000

Application of Statistical Methods of Rain Rate Estimation to Data From The TRMM Precipitation Radar

The TRMM Precipitation Radar is well suited to statistical methods in that the measurements over any given region are sparsely sampled in time. Moreover, the instantaneous rain rate estimates are often of limited accuracy at high rain rates because of attenuation effects and at light rain rates because of receiver sensitivity. For the estimation of the time-averaged rain characteristics over an area both errors are relevant. By enlarging the space-time region over which the data are collected, the sampling error can be reduced. However. the bias and distortion of the estimated rain distribution generally will remain if estimates at the high and low rain rates are not corrected. In this paper we use the TRMM PR data to investigate the behavior of 2 statistical methods the purpose of which is to estimate the rain rate over large space-time domains. Examination of large-scale rain characteristics provides a useful starting point. The high correlation between the mean and standard deviation of rain rate implies that the conditional distribution of this quantity can be approximated by a one-parameter distribution. This property is used to explore the behavior of the area-time-integral (ATI) methods where fractional area above a threshold is related to the mean rain rate. In the usual application of the ATI method a correlation is established between these quantities. However, if a particular form of the rain rate distribution is assumed and if the ratio of the mean to standard deviation is known, then not only the mean but the full distribution can be extracted from a measurement of fractional area above a threshold. The second method is an extension of this idea where the distribution is estimated from data over a range of rain rates chosen in an intermediate range where the effects of attenuation and poor sensitivity can be neglected. The advantage of estimating the distribution itself rather than the mean value is that it yields the fraction of rain contributed by the light and heavy rain rates. This is useful in estimating the fraction of rainfall contributed by the rain rates that go undetected by the radar. The results at high rain rates provide a cross-check on the usual attenuation correction methods that are applied at the highest resolution of the instrument.

Meneghini, R.↗
NASA NTRS1985

Numerical methods for analyzing electromagnetic scattering

Attenuation properties of the normal modes in an overmoded waveguide coated with a lossy material were analyzed. It is found that the low-order modes, can be significantly attenuated even with a thin layer of coating if the coating material is not too lossy. A thinner layer of coating is required for large attenuation of the low-order modes if the coating material is magnetic rather than dielectric. The Radar Cross Section (RCS) from an uncoated circular guide terminated by a perfect electric conductor was calculated and compared with available experimental data. It is confirmed that the interior irradiation contributes to the RCS. The equivalent-current method based on the geometrical theory of diffraction (GTD) was chosen for the calculation of the contribution from the rim diffraction. The RCS reduction from a coated circular guide terminated by a PEC are planned schemes for the experiments are included. The waveguide coated with a lossy magnetic material is suggested as a substitute for the corrugated waveguide.

Lee, S. W.↗
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 NTRS1998

Comparison of Radar Rainfall Retrieval Algorithms in Convective Rain During TOGA COARE

The authors compare deterministic and stochastic rain-rate retrieval algorithms by applying them to 14-GHz nadir-looking airborne radar reflectivity profiles acquired in tropical convective rain during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment, The deterministic algorithms both use the path-integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the k-R relation, while the second corrects the Z-R relation. The stochastic algorithms are based on applying an extended Kalman filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. The authors find that the stochastic algorithm, which uses the PIA, is the most robust algorithm with regard to incorrect assumptions about the drop size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA, The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions.

Durden, Stephen L.↗
NASA NTRS1990

Multiband radar characterization of forest biomes

The utility of airborne and orbital SAR in classification, assessment, and monitoring of forest biomes is investigated through analysis of orbital synthetic aperature radar (SAR) and multifrequency and multipolarized airborne SAR imagery relying on image tone and texture. Preliminary airborne SAR experiments and truck-mounted scatterometer observations demonstrated that the three dimensional structural complexity of a forest, and the various scales of temporal dynamics in the microwave dielectric properties of both trees and the underlying substrate would severely limit empirical or semi-empirical approaches. As a consequence, it became necessary to develop a more profound understanding of the electromagnetic properties of a forest scene and their temporal dynamics through controlled experimentation coupled with theoretical development and verification. The concatenation of various models into a physically-based composite model treating the entire forest scene became the major objective of the study as this is the key to development of a series of robust retrieval algorithms for forest biophysical properties. In order to verify the performance of the component elements of the composite model, a series of controlled laboratory and field experiments were undertaken to: (1) develop techniques to measure the microwave dielectric properties of vegetation; (2) relate the microwave dielectric properties of vegetation to more readily measured characteristics such as density and moisture content; (3) calculate the radar cross-section of leaves, and cylinders; (4) improve backscatter models for rough surfaces; and (5) relate attenuation and phase delays during propagation through canopies to canopy properties. These modeling efforts, as validated by the measurements, were incorporated within a larger model known as the Michigan Microwave Canopy Scattering (MIMICS) Model.

Dobson, M. Craig↗
NASA NTRS1997

Rain Profiling Algorithm for the TRMM Precipitation Radar

This paper describes an outline of the algorithm that estimates the instantaneous profiles of the true radar reflectivity factor and rainfall rate from the radar reflectivity profiles observed by the Precipitation Radar (PR) onboard the TRMM satellite. The major challenge of the algorithm lies in the correction of rain attenuation with the non-uniform beam filling effect. The algorithm was tested with synthetic data and the result is shown.

Iguchi, Toshio↗
NASA NTRS1993

Description and availability of airborne Doppler radar data

An airborne, forward-looking, pulse, Doppler radar has been developed in conjunction with the joint FAA/NASA Wind Shear Program. This radar represents a first in an emerging technology. The radar was developed to assess the applicability of an airborne radar to detect low altitude hazardous wind shears for civil aviation applications. Such a radar must be capable of looking down into the ground clutter environment and extracting wind estimates from relatively low reflectivity weather targets. These weather targets often have reflectivities several orders of magnitude lower than the surrounding ground clutter. The NASA radar design incorporates numerous technological and engineering achievements in order to accomplish this task. The basic R/T unit evolved from a standard Collins 708 weather radar, which supports specific pulse widths of 1-7 microns and Pulse Repetition Frequencies (PRF) of less than 1-10 kHz. It was modified to allow for the output of the first IF signal, which fed a NASA developed receiver/detector subsystem. The NASA receiver incorporated a distributed, high-speed digital attenuator, producing a range bin to range bin automatic gain control system with 65 dB of dynamic range. Using group speed information supplied by the aircraft's navigation system, the radar signal is frequency demodulated back to base band (zero Doppler relative to stationary ground). The In-phase & Quadrature-phase (I/Q) components of the measured voltage signal are then digitized by a 12-bit A-D converter (producing an additional 36 dB of dynamic range). The raw I/Q signal for each range bin is then recorded (along with the current radar & aircraft state parameters) by a high-speed Kodak tape recorder.

Harrah, S. D.↗
NASA NTRS1974

Millimeter wavelength propagation studies

The investigations conducted for the Millimeter Wavelength Propagation Studies during the period December, 1966, to June 1974 are reported. These efforts included the preparation for the ATS-5 Millimeter Wavelength Propagation Experiment and the subsequent data acquisition and data analysis. The emphasis of the OSU participation in this experiment was placed on the determination of reliability improvement resulting from the use of space diversity on a millimeter wavelength earth-space communication link. Related measurements included the determination of the correlation between radiometric temperature and attenuation along the earth-space propagation path. Along with this experimental effort a theoretical model was developed for the prediction of attenuation statistics on single and spatially separated earth space propagation paths. A High Resolution Radar/Radiometer System and Low Resolution Radar System were developed and implemented for the study of intense rain cells in preparation for the ATS-6 Millimeter Wavelength Propagation Experiment.

Hodge, D. B.↗
NASA NTRS1989

Experimental tests of range-profiling algorithms

The natural tendency in the design of a spaceborne weather radar is to select frequencies at 10 GHz or higher. A major disadvantage of this approach is that increased attenuation limits the maximum rain rate that can be accurately estimated. Here, a way to lessen this problem is suggested which uses estimates of path attenuation to reconstruct a profile of the rain rate.

Meneghini, R.↗
NASA NTRS2021

Joint cloud water path and rainwater path retrievals from airborne ORACLES observations

This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ∼10 %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g/sq. m and almost all CWPs (99 %) between 6 to 445 g/sq. m. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g/sq. m of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm/h or 1000 mm/d), however, RWP is observed to exceed 2500 g/sq. m. CWP (RWP) is found to be approximately 30 g/sq. m (7 g/sq. m) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

algorithm↗