Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Radar”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Wideband Waveform Design principles for Solid-state Weather Radars

The use of solid-state transmitter is becoming a key part of the strategy to realize a network of low cost electronically steered radars. However, solid-state transmitters have low peak powers and this necessitates the use of pulse compression waveforms. In this paper a frequency diversity wideband waveforms design is proposed to mitigate low sensitivity of solid-state transmitters. In addition, the waveforms mitigate the range eclipsing problem associated with long pulse compression. An analysis of the performance of pulse compression using mismatched compression filters designed to minimize side lobe levels is presented. The impact of range side lobe level on the retrieval of Doppler moments are presented. Realistic simulations are performed based on CSU-CHILL radar data and Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project I (IP1) radar data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Scanning ARM Precipitation Radar (SAPR) Quasi-Vertical Profile (QVP)

The Quasi-Vertical Profiles (QVP) VAP averages quality-controlled radar measurements along the axis of the azimuth. QVP allows quick insight into domain mean hydrometeor (e.g., snow, rain, melting layer) location and polarimetric data. QVP data are derived from Corrected Moments in Antenna Coordinates Version 2 (CMAC2) using code within the Python ARM Radar Toolkit (Py-ART), an open-source architecture for interacting with radar data in the Python programming language.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

NASA/JPL's Imaging Radar Outreach Program

In order to build a user community for future NASA imaging radar products and programs, outreach activities have been implemented by JPL. These include: education outreach, public awareness outreach, and outreach to areas of the scientific and applications community who are not traditional imaging radar users. A key component is the NASA/JPL Imaging Radar Home Page on the World Wide Web.

Radar Products Radar Programs Imaging Radar SIR-C ↗
NASA NTRS1993

Optimal Estimation of Rain Rate Profiles From Radar Returns at Attenuating Wavelengths

There are significant inherent ambiguities when one tries to determine a particular vertical rain intensity profile from a given time profile of radar echo powers measured by a downward-looking (spaceborne or airborne) radar at a single attenuating frequency. In this paper, we quantify these ambiguities mathematically, and examine their effects on the performance of rain-rate retrieval algorithms initially proposed for use by the Precipitation Radar of the Tropical Rainfall Measuring Mission (TRMM).

vertical rain intensity profiles spaceborne radar ↗
DOE OSTI2018

Toward Exploring the Synergy Between Cloud Radar Polarimetry and Doppler Spectral Analysis in Deep Cold Precipitating Systems in the Arctic

The study of Arctic ice and mixed-phase clouds, which are characterized by a variety of ice particle types in the same cloudy volume, is challenging research. This study illustrates a new approach to qualitative and quantitative analysis of the complexity of ice and mixed-phase microphysical processes in Arctic deep precipitating systems using the combination of Ka-band zenith-pointing radar Doppler spectra and quasi-vertical profiles of polarimetric radar variables measured by a Ka/W-band scanning radar. The results illustrate the frequent occurrence of multimodal Doppler spectra in the dendritic/planar growth layer, where locally generated, slower-falling particle populations are well separated from faster-falling populations in terms of Doppler velocity. The slower-falling particle populations contribute to an increase of differential reflectivity (Z DR ), while an enhanced specific differential phase (K DP ) in this dendritic growth temperature range is caused by both the slower and faster-falling particle populations. Another area with frequent occurrence of multimodal Doppler spectra is in mixed-phase layers, where both populations produce Z DR and K DP values close to 0, suggesting the occurrence of a riming process. A Joint analysis of the Doppler spectra and the polarimetric radar variables provides important insight into the microphysics of snow formation and allows the separation of the contributions of ice of different habits to the values of reflectivity and Z DR .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Anisotropic Melt Inclusions as a Confounding Signal for Ice‐Penetrating Radar Observations

Ice-penetrating radar is a powerful geophysical tool for understanding the subsurfaces of Earth, Mars, and icy moons. Radar reflectivity, attenuation, and birefringence are used to infer subsurface hydrology, englacial temperature, water content, and crystal orientation fabric. However, conventional radar sounding analyses either ignore melt or use classical mixing models which assume spherical melt inclusions, obscuring anisotropic contributions of melt. Here, we use geometric mixing models to calculate the reflectivity, attenuation, and birefringence of temperate ice containing anisotropic melt. We find that anisotropic melt can introduce significant deviations in radar measurements. For instance, melt anisotropy may impact reflectivity-based estimates of water content by up to 30% volume fraction, while attenuation-based estimates may vary by up to 43%. Critically, a melt volume fraction of just $f$ ~ 10 -5 can reproduce birefringence signals previously attributed to ice fabric. We conclude that melt anisotropy may significantly impact analyses of englacial hydrology, subglacial hydrology, and ice fabric.

58 GEOSCIENCES↗
DOE OSTI2016

Three-dimensional radar imaging techniques and systems for near-field applications

The Pacific Northwest National Laboratory has developed three-dimensional holographic (synthetic aperture) radar imaging techniques and systems for a wide variety of near-field applications. These applications include radar cross-section (RCS) imaging, personnel screening, standoff concealed weapon detection, concealed threat detection, through-barrier imaging, ground penetrating radar (GPR), and non-destructive evaluation (NDE). Sequentially-switched linear arrays are used for many of these systems to enable high-speed data acquisition and 3-D imaging. In this paper, the techniques and systems will be described along with imaging results that demonstrate the utility of near-field 3-D radar imaging for these compelling applications.

microwave imaging↗
DOE OSTI2024

Training the next generation of researchers in exploring cloud dynamics and microphysics using millimeter-wavelength radars

Millimeter-wavelength radars, with their ability to collect observations and high spatiotemporal resolution, have become cornerstone instruments for investigating cloud and precipitation microphysics and dynamics in the last two decades. Since the1990s the US Department of Energy Atmospheric Radiation Measurement (ARM) program has invested in mm-wavelength radar technology progressively adding scanning capability, additional frequencies and polarimetric capability. In addition, atmospheric observatories including those technologies have been operated overseas. Those technologies have enhanced our understanding of cloud and precipitation processes. Only a few universities operate those instruments and use them for educational purposes. The central role of mm- wavelength radars and their role will be further highlighted in the next decade. NASA and other international space agencies are planning to launch millimeter-wavelength (i.e., Ku, Ka, W, G- bands) Doppler radar in space to improve our understanding of cloud and precipitation formation, evolution and their impacts on global climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

First observations of tracking clouds using scanning ARM cloud radars

Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud field and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Empirical Relations between Size Parameters of Ice Hydrometeor Populations and Radar Reflectivity

Empirical power-law relations between the equivalent radar reflectivity factor Z e and the slope parameter of the gamma function Λ (i.e., Λ = cZ $^{d}_{e}$ used to describe ice hydrometeor size distributions) are derived. The Λ parameter can also be considered as a size parameter since it is proportional to the inverse of the hydrometeor characteristic size, which is an important geophysical parameter describing the entire distribution. Two datasets from two-dimensional microphysical probes, collected during aircraft flights in subtropical and midlatitude regions, were used to obtain Λ by fitting measured size distributions. Reflectivity for different radar frequencies was calculated from microphysical probe data by using nonspherical-particle models. The derived relations have exponent d values that are approximately from -0.35 to -0.40, and the prefactors c are approximately between 30 and 55 (Λ: cm -1 ; Z e : mm 6 m -3 ). There is a tendency for d and c to decrease when radar frequency increases from K u band (~14 GHz) to W band (~94 GHz). Correlation coefficients between Z e and Λ can be very high (~0.8), especially for lower frequencies. Such correlations are similar to those for empirical relations between reflectivity and ice water content (IWC), which are used in many modeling and remote sensing applications. Close correspondences of reflectivity to both Λ and IWC are due to a relatively high correlation between these two microphysical parameters. Finally, expected uncertainties in estimating Λ from reflectivity could be as high as a factor of 2, although estimates at lower radar frequencies are more robust. Stratifying retrievals by temperature could result in relatively modest improvement of Λ estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Polarimetric Radar Relations for Quantification of Snow Based on Disdrometer Data

Abstract Accurate measurements of snow amounts by radar are very difficult to achieve. The inherent uncertainty in radar snow estimates that are based on the radar reflectivity factor Z is caused by the variability of snow particle size distributions and snow particle density as well as the large diversity among snow growth habits. In this study, a novel method for snow quantification that is based on the joint use of radar reflectivity Z and specific differential phase KDP is introduced. An extensive dataset of 2D-video-disdrometer measurements of snow in central Oklahoma is used to derive polarimetric relations for liquid-equivalent snowfall rate S and ice water content IWC in the forms of bivariate power-law relations S = and along with similar relations for the intercept N0s and slope Λs of the exponential snow size distribution. The physical basis of these relations is explained. Their multipliers are sensitive to variations in the width of the canting angle distribution and to a lesser extent the particles’ aspect ratios and densities, whereas the exponents are practically invariant. This novel approach is tested against the S(Z) relation using snow disdrometer measurements in three geographical regions (Oklahoma, Colorado, and Canada). Significant improvement in snow estimates relative to the traditional Z-based methods is demonstrated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Bulk-Density Representations of Branched Planar Ice Crystals: Errors in the Polarimetric Radar Variables

Abstract Recent interest in interpreting polarimetric radar observations of ice and evaluating microphysical model output with these observations has highlighted the importance of accurately computing the scattering of microwave radiation by branched planar ice crystals. These particles are often represented as spheroids with uniform bulk density, reduced from that of solid ice to account for the complex, nonuniform structure of natural branched crystals. In this study, the potential errors that arise from this assumption are examined by comparing scattering calculations of branched planar crystals with those of homogeneous, reduced-density plate crystals and spheroids with the same mass, aspect ratio, and maximum dimension. The results show that this assumption leads to significant errors in backscatter cross sections at horizontal and vertical polarization, specific differential phase (KDP), and differential reflectivity (ZDR), with the largest ZDR errors for ice crystals with the most extreme aspect ratios (<0.01) and effective densities < 250 kg m−3. For example, the maximum errors in X-band ZDR are 4.5 dB for 5.6-mm branched planar crystals. However, substantial errors are present at all weather radar frequencies, with resonance scattering effects at Ka and W band amplifying the low-frequency errors. The implications of these results on the interpretation of polarimetric radar observations and forward modeling of the polarimetric radar variables from microphysical model output are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

How Well Can We Represent the Spectrum of Convective Clouds in a Climate Model? Comparisons between Internal Parameterization Variables and Radar Observations

Current climate models cannot resolve individual convective clouds, and hence parameterizations are needed. The primary goal of convective parameterization is to represent the bulk impact of convection on the gridbox-scale variables. Spectral convective parameterizations also aim to represent the key features of the subgrid-scale convective cloud field such as cloud-top-height distribution and in-cloud vertical velocities in addition to precipitation rates. Ground-based radar retrievals of these quantities have been made available at Darwin, Australia, permitting direct comparisons of internal parameterization variables and providing new observational references for further model development. A spectral convective parameterization [the convective cloud field model (CCFM)] is discussed, and its internal equation of motion is improved. Results from the ECHAM–HAM model in single-column mode using the CCFM and the bulk mass flux Tiedtke–Nordeng scheme are compared with the radar retrievals at Darwin. The CCFM is found to outperform the Tiedtke–Nordeng scheme for cloud-top-height and precipitation-rate distributions. Radar observations are further used to propose a modified CCFM configuration with an aerodynamic drag and reduced entrainment parameter, further improving both the convective cloud-top-height distribution (important for large-scale impact of convection) and the in-cloud vertical velocities (important for aerosol activation). This study provides a new development in the CCFM, improving the representation of convective cloud spectrum characteristics observed in Darwin. This is a step toward an improved representation of convection and ultimately of aerosol effects on convection. It also shows how long-term radar observations of convective cloud properties can help constrain parameters of convective parameterization schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Polarimetric Radar Characteristics of Simulated and Observed Intense Convective Cores for a Midlatitude Continental and Tropical Maritime Environment

This study contrasts midlatitude continental and tropical maritime deep convective cores using polarimetric radar observables and retrievals from selected deep convection episodes during the MC3E and TWPICE field campaigns. The continental convective cores produce stronger radar reflectivities throughout the profiles, while maritime convective cores produce more positive differential reflectivity Z dr and larger specific differential phase K dp above the melting level. Hydrometeor identification retrievals revealed the presence of large fractions of rimed ice particles (snow aggregates) in the continental (maritime) convective cores, consistent with the Z dr and K dp observations. The regional cloud-resolving model simulations with bulk and size-resolved bin microphysics are conducted for the selected cases, and the simulation outputs are converted into polarimetric radar signals and retrievals identical to the observational composites. Both the bulk and the bin microphysics reproduce realistic land and ocean (L-O) contrasts in reflectivity, polarimetric variables of rain drops, and hydrometeor profiles, but there are still large uncertainties in describing Z dr and K dp of ice crystals associated with the ice particle shapes/orientation assumptions. Sensitivity experiments are conducted by swapping background aerosols between the continental and maritime environments, revealing that background aerosols play a role in shaping the distinct L-O contrasts in radar reflectivity associated with raindrop sizes, in addition to the dominant role of background thermodynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Characteristic Raindrop Size Retrievals from Measurements of Differences in Vertical Doppler Velocities at Ka- and W-Band Radar Frequencies

A Ka-band (~35 GHz) and W-band (~94 GHz) radar method to catch profiles of characteristic raindrop sizes, such as mean mass-weighted drop diameters D m , from measurements of the difference in the mean vertical Doppler velocities (DDV) is analyzed. This retrieval approach is insensitive to radar calibration errors, vertical air motions, and attenuation effects. The D m –DDV relations are derived using long-term measurements of drop size distributions (DSDs) from different observational sites and do not assume a functional DSD shape. Unambiguous retrievals using this approach are shown to be available in the D m range of approximately 0.5–2 mm, with average uncertainties of around 21%. Potential retrieval ambiguities occurring when larger drop populations exist can be avoided by using a Ka-band vertical Doppler velocity threshold. The performance of the retrievals is illustrated using a long predominantly stratiform rain event observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site. An intercomparison of DDV-based estimates of characteristic raindrop sizes with independent estimates available from ground-based disdrometer measurements reveal good agreement, with a correlation coefficient of 0.88, and mean differences between radar and disdrometer-based D m of approximately 14% for the entire range of unambiguous retrievals. The Ka–W-band DDV method to retrieve mean mass-weighted drop sizes is applicable to measurements from new dual-wavelength ARM cloud radars that are being deployed at a variety of observational facilities. An illustration for the retrievals at the Oliktok Point ARM facility is also given in this work.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

UNRAVEL: A Robust Modular Velocity Dealiasing Technique for Doppler Radar

Unfold Radar Velocity (UNRAVEL) is an open-source modular Doppler velocity dealiasing algorithm for weather radars. UNRAVEL is an algorithm that does not need external reference velocity data, making it easily applicable. The proposed algorithm includes 11 core modules and 2 dealiasing strategies. UNRAVEL is an iterative algorithm. The goal is to build the dealiasing results starting with the strictest possible continuity tests in azimuth and range and, after each step, relaxing the parameters to include more results from a progressively growing number of reference points. UNRAVEL also has modules that perform 3D continuity checks. Thanks to this modular design, the number of dealiasing strategies can be expanded in order to optimize the dealiasing results. While the first driver dealiases Doppler velocity from each tilt independently from one another, the second driver also performs a three-dimensional continuity check of the velocity using successive elevations. The proposed dealiasing algorithm is tested using severe weather data from an S-band Doppler radar that have been aliased to mimic aliased radial velocity patterns that would be observed by a C-band Doppler radar. Artificially aliasing S-band data permits creation of a reference to which the performance of various dealiasing techniques can be compared. Comparisons show that UNRAVEL consistently outperforms other established dealiasing algorithms for the test period selected in this work.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Wave-by-Wave Forecasting via Assimilation of Marine Radar Data

Abstract This work describes a phase-resolving wave-forecasting algorithm that is based on the assimilation of marine radar image time series. The algorithm is tested against synthetic data and field observations. The algorithm couples X-band marine radar observations with a phase-resolving wave model that uses the linear mild slope equations for reconstruction of water surface elevations over a large domain of O (km) and a prescribed time window of O (min). The reconstruction also enables wave-by-wave forecasting through forward propagation in space and time. Marine radar image time series provide the input wave observations through a previously given relationship between backscatter intensity and the radial component of the sea surface slope. The algorithm assimilates the wave slope information into the model via a best-fit wave source function at the boundary that minimizes the slope reconstruction error over an annular region at the outer ranges of the radar images. The wave model is then able to propagate the waves across a polar domain to a location of interest at nearer ranges. The constraints on the method for achieving real-time forecasting are identified, and the algorithm is verified against synthetic data and tested using field observations.

Engineering↗