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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

Snow Cover↗
NASA NTRS2016

Annual Greenland Accumulation Rates (2009-2012) from Airborne Snow Radar

Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor its surface mass balance in order to improve sea-level rise predictions. Snow accumulation is the largest component of the ice sheet's surface mass balance, but in situ observations thereof are inherently sparse and models are difficult to evaluate at large scales. Here, we quantify recent Greenland accumulation rates using ultra-wideband (2-6.5 gigahertz) airborne snow radar data collected as part of NASA's Operation IceBridge between 2009 and 2012. We use a semi-automated method to trace the observed radiostratigraphy and then derive annual net accumulation rates for 2009-2012. The uncertainty in these radar-derived accumulation rates is on average 14 percent. A comparison of the radarderived accumulation rates and contemporaneous ice cores shows that snow radar captures both the annual and longterm mean accumulation rate accurately. A comparison with outputs from a regional climate model (MAR - Modele Atmospherique Regional for Greenland and vicinity) shows that this model matches radar-derived accumulation rates in the ice sheet interior but produces higher values over southeastern Greenland. Our results demonstrate that snow radar can efficiently and accurately map patterns of snow accumulation across an ice sheet and that it is valuable for evaluating the accuracy of surface mass balance models.

surface melt↗
NASA NTRS2017

Observation of Polar Mesosphere Summer Echoes using the Northernmost MST Radar at Eureka (80 deg N)

We investigate long-term Polar Mesosphere Summer Echoes (PMSEs) observations conducted by the northern most geographically located MST radar at Eureka (80 deg N, 86 deg W). While PMSEs are a well recognized summer phenomenon in the polar regions, previous calibrated studies at Resolute Bay and Eureka using 51.5 MHz and33 MHz radars respectively, showed that PMSE backscatter signal strengths are relatively weak in the polar cap sites, compared to the auroral zone sites (Swarnalingam et al., 2009b; Singer et al., 2010). Complications arise with PMSEs in which the echo strength is controlled by the electrons, which are, in turn, influenced by heavily charged ice particles as well as the variability in the D-region plasma. In recent years, PMSE experiments were conducted inside the polar cap utilizing a 51 MHz radar located at Eureka. In this paper, we investigate calibrated observations, conducted during 2009-2015. Seasonal and diurnal variations of the backscatter signal strengths are discussed and compared to previously published results from the ALOMAR radar, which is a radar of similar design located in the auroral zone at Andenes, Norway (69 deg N, 16 deg E). At Eureka, while PMSEs are present with a daily occurrence rate which is comparable to the rate observed at the auroral zone site for at least two seasons, they show a great level of inter-annual variability. The occurrence rate for the strong echoes tends to be low. Furthermore, comparison of the absolute backscatter signal strengths at these two sites clearly indicates that the PMSE backscatter signal strength at Eureka is weak. Although this difference could be caused by several factors, we investigate the intensity of the neutral air turbulence at Eureka from the measurements of the Doppler spectrum of the PMSE backscatter signals. We found that the level of the turbulence intensity at Eureka is weak relative to previously reported results from three high latitude sites.

Swarnalingam, N.↗
NASA NTRS2017

Detection of Hail Storms in Radar Imagery Using Deep Learning

In 2016, hail was responsible for 3.5 billion and 23 million dollars in damage to property and crops, respectively, making it the second costliest weather phenomenon in the United States. In an effort to improve hail-prediction techniques and reduce the societal impacts associated with hail storms, we propose a deep learning technique that leverages radar imagery for automatic detection of hail storms. The technique is applied to radar imagery from 2011 to 2016 for the contiguous United States and achieved a precision of 0.848. Hail storms are primarily detected through the visual interpretation of radar imagery (Mrozet al., 2017). With radars providing data every two minutes, the detection of hail storms has become a big data task. As a result, scientists have turned to neural networks that employ computer vision to identify hail-bearing storms (Marzbanet al., 2001). In this study, we propose a deep Convolutional Neural Network (ConvNet) to understand the spatial features and patterns of radar echoes for detecting hailstorms.

natural hazard↗
NASA NTRS2017

AMSNEXRAD Automated Detection of Meteorite Strewnfields in Doppler Weather Radar

For several years meteorite recovery in the United States has been greatly enhanced by using Doppler weather radar images to determine possible fall zones for meteorites produced by witnessed fireballs. While most fireball events leave no record on the Doppler radar, some large fireballs do. Based on the successful recovery of 10 meteorite falls 'under the radar', and the discovery of radar on more than 10 historic falls, it is believed that meteoritic dust and or actual meteorites falling to the ground have been recorded on Doppler weather radar.

Michael Hankey↗
NASA NTRS2017

Compatibility Tests Between the Mars Vehicle System Test Bed and RIMFAX Radar Antenna Prototype for the Mars 2020 Mission

NASA's Mars 2020 rover will carry a wideband (150 megahertz to 1200 megahertz) ground penetrating radar—RIMFAX (Radar Imager for Mars’ subsurFace eXperiment ), contributed by FFI (Forsvarets forskningsinstitutt) of Norway—to survey the subsurface geology of Mars. RIMFAX will take radar soundings while the rover drives across the Martian terrain, which presents possible compatibility issues between rover and radar operations. In order to study this risk, a prototype RIMFAX antenna was attached to the flight-analogous rover Vehicle System Test Bed (VSTB) in a mechanically representative location. The prototype antenna collected spectral and time-domain data across a variety of driving operations in order to assess the radar sensitivity to rover-generated noise. Conversely, the prototype antenna was driven while an engineering-model UHF (Ultra High Frequency) antenna used for rover telecom measured received in-band power to ensure that the rover hardware was not at risk of damage. Evaluation of the data by the instrument science team showed that while rover noise was apparent to the receiver, data post-processing would yield greater than 40 decibels margin to the science requirements. Similarly, power levels received by the UHF antenna were well below damage thresholds.

Gonzales, Edward↗
NASA NTRS2019

Tri-Frequency Synthetic Aperture Radar for the Measurements of Snow Water Equivalent

SWESARR (Snow Water Equivalent Synthetic Aperture Radar and Radiometer) is an airborne instrument developed at the NASA Goddard Space Flight Center for the retrieval of Snow Water Equivalent. SWESARR was specifically designed to measure co-located active and passive signals using a high resolution and multi-frequency Synthetic Aperture Radar (SAR) and a multifrequency radiometer. SWESARR’s Synthetic Aperture Radar (SAR) system is made up of three independent radar units that operate in the X, Ku-Low, and Ku-High bands with bandwidths up to 200 MHz, and acquires data in two polarizations (dual-polarization radar). The difference in sensitivity of the backscatter signals to snow microstructure, in conjunctions with radiometer measurements, permits an accurate estimation of the snow water equivalent (SWE).

Rincon, Rafael↗
NASA NTRS2020

Comparison of Raindrop Size Distribution between NASA’s S-Band Polarimetric Radar and Two-Dimensional Video Disdrometers

The ground-based-radar-derived raindrop size distribution (DSD) parameters—mass-weighted drop diameter Dmass and normalized intercept parameter NW—are the sole resource for direct validation of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission Core Observatory satellite-based retrieved DSD. Both Dmass and NW are obtained from radar-measured reflectivity ZH and differential reflectivity ZDR through empirical relationships. This study uses existing relationships that were determined for the GPM ground validation (GV) program and directly compares the NASA S-band polarimetric radar (NPOL) observables of ZH and ZDR and derivedDmass and NW with those calculated by two-dimensional video disdrometer (2DVD). The joint NPOL and 2DVD datasets were acquired during three GPM GV field campaigns conducted in eastern Iowa, southern Appalachia, and western Washington State. The comparative study quantifies the level of agreement for ZH, ZDR, Dmass, and log(NW) at an optimum distance (15–40 km) from the radar as well as at distances greater than 60 km from radar and over mountainous terrain. Interestingly, roughly 10%–15% of the NPOL ZH–ZDR pairs were well outside the envelope of 2DVD-estimated ZH–ZDR pairs. The exclusion of these pairs improved the comparisons noticeably.

Ali Tokay↗
NASA NTRS2004

Backscattering enhancement with a finite beam width for millimeter - wavelength weather radars

Backscattering enhancement from random hydrometeors should increase as wavelengths of radars reach millimeter regions. For 95 GHz radars, the reflectivity of backscattering is expected to increase by 2 dB, due to multiple scattering including backscattering enhancement, for water droplets of diameter of 1 mm with a density of 5×103 m−3. Previous theoretical studies of backscattering enhancement considered infinitely extending plane waves. In this paper, we expand the theory to spherical waves with a Gaussian antenna pattern, including depolarizing effects. While the differences from the plane wave results are not great when the optical thickness is small, as the latter increases the differences become significant, and essentially depend on the ratio of radar footprint radius to the mean free path of hydrometeors. In this regime, for a radar footprint that is smaller than the mean free path, the backscattering-enhancement reflectivity corresponding to spherical waves is significantly less pronounced than in the case of the plane wave theory. Hence this reduction factor must be taken into account when analyzing radar reflectivity factors for use in remote sensing applications.

Im, Eastwood↗
NASA NTRS2018

Multi-frequency Tomography Radar Observations of Snow Stratigraphy at Fraser during SnowEx

SnowEx is a multi-year airborne snow campaign led by NASA. The purpose of SnowEx is to figure out how much water is stored in Earth’s terrestrial snow-covered regions. As part of the 2017 NASA SnowEx campaign, we deployed a portable triple-frequency (9.6GHz, 13.5GHz and 17.2GHz) and fully polarimetric frequency-modulated continuous-wave (FMCW) radar at Fraser, Colorado. The radar was installed on a 60cmx60cm frame to enable a full reconstruction of the three-dimensional variability per each radar channel. The tomography technique uses the radar echo from the multiple viewing positions and provides a unique access to the vertical structure of the snow layer. With current setup, the range resolution is 30cm. In this paper, we will review the radar design and signal-processing algorithm – time domain back projection. The generated vertical images show the snow stratigraphy, which is consistent with ground snow pit measurement. The continuous operation demonstrates diurnal thawing and refreezing process. The snow density is retrieved by comparing to the snow free image.

Esteban-Fernandez, Daniel↗
NASA NTRS2019

An upgraded G-band differential absorption radar system for future airborne studies

A proof-of-concept, 170 GHz frequency-modulated, continuous-wave (FMCW) radar has been developed for measuring water vapor profiles within the cloudy boundary layer from an airborne platform. The measurement concept exploits the differential absorption accrued by two or more transmitted frequencies in the vicinity of the 183 GHz water absorption line to retrieve range-resolved humidity profiles, so-called differential absorption radar (DAR). The upgraded system design includes important considerations for monostatic radar operation with an open fuselage viewport (i.e. no radome). The radar features an all-solid-state tansmitter with > 0:4 W continuous transmit power, a 60 cm primary aperture and corresponding 58 dB antenna gain, and more than 80 dB transmit/receive isolation, enabling near thermal-noise-limited sensitivity with a 8 dB noise figure receiver. Ice-cloud radar returns are detected beyond 8 km in height from the ground, demonstrating the high sensitivity of the system. In addition to in-cloud humidity profiling capabilities, deployment of a water vapor DAR from an airborne platform enables measurements of total column water vapor (TCWV) for all weather and surface scenarios. Precision estimates and potential biases for future TCWV measurements are discussed.

Monje, Raquel↗
NASA NTRS2020

Comparison of Raindrop Size Distribution between NASA's S-Band Polarimetric Radar and Two-Dimensional Video Disdrometers

The ground-based-radar-derived raindrop size distribution (DSD) parameters—mass-weighted drop diameter D mass and normalized intercept parameter NW—are the sole resource for direct validation of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM ) mission Core Observatory satellite-based retrieved DSD. Both D mass and NW are obtained from radar-measured reflectivity Z Hand differential reflectivity ZDR through empirical relationships. This study uses existing relationships that were determined for the GPM ground validation (GV) program and directly compares the NASA S-band polarimetric radar (NPOL) observables of Z Hand Z DR and derived D mass and NW with those calculated by two-dimensional video disdrometer (2DVD). The joint NPOL and 2DVD datasets were acquired during three GPM GV field campaigns conducted in eastern Iowa, southern Appalachia, and western Washington State. The comparative study quantifies the level of agreement for ZH, ZDR, D mass, and log (NW) at an optimum distance (15–40 km) from the radar as well as at distances greater than 60 km from radar and over mountainous terrain. Interestingly, roughly 10%–15% of the NPOLZH–Z DR pairs were well outside the envelope of 2DVD-estimatedZH–Z DR pairs. The exclusion of these pairs improved the comparisons noticeably.

Ali Tokay↗
NASA NTRS2021

Generating Flood Probability Map Based on Combined Use of Synthetic Aperture Radar and Optical Imagery

Despite a lot of efforts to respond flood hazards with remote sensing data, it is still difficult to generate an accurate flood map using solely optical or radar imagery. While optical data is relatively high-resolution and does not suffer from speckle noise compared to radar data, it is very likely to be impacted by cloud and shadow. On the other hand, radar imagery can be used in all weather conditions due to its capability of penetrating clouds. Although a significant improvement of flood monitoring capability is achieved by using radar data, it is still challenging to map urban floods because of strong backscattering by man-made structures. Therefore, complementary use of optical and radar imagery in flood response is required, particularly in urban areas. In this study, we have adopted the Bayesian Joint Probability function to combine two different flood products generated from SAR and optical imagery. Flood detection with SAR data relies on the difference of backscatter signals between standing water and rougher land surface, while a Normalized Difference Water Index (NDWI) approach is used for optical data. Specifically, Planet Dove data with its 3m spatial resolution is used with higher weight values to detect flood extent in urban areas.

floods↗
NASA NTRS2021

Application of Non-Uniform Beam Filling (NUBF) Doppler Velocity Error Correction on Airborne Radar Measurements

Non-uniform beam filling (NUBF) within an atmospheric radar sampling volume can cause significant Doppler velocity errors when the radar is located on a fast-moving platform. A case of strong NUBF errors was identified in ER-2 X-band Radar (EXRAD) data from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) 2020 field campaign. A basic NUBF correction was employed using an estimate of the along-track radar reflectivity gradient. The relationship is verified empirically using co-located Doppler velocity measurements from the higher resolution Cloud Radar System (CRS).

Matthew L. Walker McLinden↗
NASA NTRSDate not supplied

Ground to Air Testing of a Fused Optical-Radar Aircraft Detection and Tracking System

Onboard detection and tracking capability are integral to the sensing component in collision avoidance systems needed to safely operate autonomous urban air taxis and small Unmanned Aircraft Systems. Ground-based validation of detection and tracking systems is an important milestone towards the end goal of real-time collision avoidance using onboard sensors and algorithms. In this work, we evaluate three Extended Kalman Filter(EKF)based fusion trackers with radar and vision detection inputs, and compare them with baseline trackers for each sensor type. Performance is assessed using field collected data of ground to air test flights with the sensors co-located on a stable platform with an instrumented multirotor acting as the intruder performing a waypoint pattern at a distance of1.1km to 0.3km to simulate a head-on collision geometry. Fusing an image-based morphological detector with a radar detector using an EKF covered 74% of the ground truth position updates logged by the flight controller on the multirotor within 50 meters after accounting for alignment offsets while covering 15% more ground truth updates relative to radar only. Removing timestamps when the intruder aircraft is occluded by trees and only considering timestamps where the radar has an update, the EKF image-based morphological detector combined with the radar detector covered 90% of the of the ground truth position updates within 50metersand 97% within 100 meters.

Chester V Dolph↗
NASA NTRS2021

Brief Communication: An Empirical Relation Between Center Frequency and Measured Thickness for Radar Sounding of Temperate Glaciers

Radar sounding of the thickness of temperate glaciers is challenged by substantial volume scattering, surface scattering and high attenuation rates. Lower-frequency radar sounders are often deployed to mitigate these effects, but the lack of a global synthesis of their success limits progress in system and survey design. Here we extend a recent global compilation of glacier thickness measurements (GlaThiDa) with the center frequency for radar-sounding surveys. From a maximum reported thickness of ∼ 1500 m near 1 MHz, the maximum thickness sounded decreases by ∼ 500 m per frequency decade. Between 25–100 MHz, newer airborne radar sounders generally outperform older, ground-based ones. Based on globally modeled glacier thicknesses, we conclude that a multi-element, ≤30 MHz airborne radar sounder could survey most temperate glaciers more efficiently.

Joseph A MacGregor↗
NASA NTRS2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Robert S. Schrom↗
NASA NTRS2021

Terminal Descent Radar System Testbed for Future Planetary Landers

Terminal Descent Radars (TDR), or landing radars, have been an integral element of Guidance, Navigation and Control (GN\&C) sensor suites of robotic exploration missions to the Moon and Mars. As plans for new, exciting exploration missions to the Moon, Mars and other planetary bodies are being developed, there is a need for a new generation of TDRs that are smaller, consume less power and are less expensive than previous sensors. The challenge of designing such a landing sensor is twofold: the first is to have well-vetted software tools that allow us to explore the design space for a particular mission scenario and analyze performance of relevant radar architectures. The second challenge is to reduce mass and power requirements of a landing radar without compromising reliability and performance. New design approaches that address these challenges need to be tested and demonstrated in realistic Entry-Descent-Landing (EDL)/Deorbit-Descent-Landing (DDL) scenarios. In this paper, we describe a TDR testbed developed at the Jet Propulsion Laboratory. The testbed is a closed-loop design, analysis and verification capability used to design and evaluate the next generation of landing radars for a variety of EDL/DDL scenarios.

Tope, Michael↗