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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Dynamics of Dust Particles Released from Oort Cloud Comets and Their Contribution to Radar Meteors

The Oort Cloud Comets (OCCs), exemplified by the Great Comet of 1997 (Hale-Bopp), are occasional visitors from the heatless periphery of the solar system. Previous works hypothesized that a great majority of OCCs must physically disrupt after one or two passages through the inner solar system, where strong thermal gradients can cause phase transitions or volatile pressure buildup. Here we study the fate of small debris particles produced by OCC disruptions to determine whether the imprints of a hypothetical population of OCC meteoroids can be found in the existing meteor radar data. We find that OCC particles with diameters D < or approx. 10 microns are blown out from the solar system by radiation pressure, while those with D > or approx. 1 mm have a very low Earth-impact probability. The intermediate particle sizes, D approx. 100 microns represent a sweet spot. About 1% of these particles orbitally evolve by Poynting-Robertson drag to reach orbits with semimajor axis a approx. 1 AU. They are expected to produce meteors with radiants near the apex of the Earth s orbital motion. We find that the model distributions of their impact speeds and orbits provide a good match to radar observations of apex meteors, except for the eccentricity distribution, which is more skewed toward e approx. 1 in our model. Finally, we propose an explanation for the long-standing problem in meteor science related to the relative strength of apex and helion/antihelion sources. As we show in detail, the observed trend, with the apex meteors being more prominent in observations of highly sensitive radars, can be related to orbital dynamics of particles released on the long-period orbits.

Nesvorny, David↗
NASA NTRS2021

Estimation of Snow Mass Information via Assimilation of C-Band Synthetic Aperture Radar Backscatter Observations Into an Advanced and Surface Model

This study assimilated Sentinel-1 C-band backscatter observations over snow-covered terrain into the Noah-Multiparameterization land surface model using support vector machine (SVM) regression and an ensemble Kalman filter to improve the modeled terrestrial snow mass estimates. The data assimilation (DA) experiment was conducted across Western Colorado from September 2016 to August 2017. As part of the DA experiments, the impact of a rule-based update was evaluated by comparing snow water equivalent (SWE) estimates via DA (with [ DAv1 ] and without [ DAv2 ] the rule-based update) against SNOTEL SWE measurements. Results confirmed that rule-based update helped minimize SVM controllability issues, and in turn, improved the accuracy of SWE estimates relative to both open loop (OL) and DAv2 . Comparison of SWE estimates from Sentinel-1 DAv1 against SNOTEL SWE revealed that 75% of stations showed improvements in bias and correlation coefficient relative to the OL. Assimilated SWE estimates also showed statistical improvements during both the snow accumulation and snow ablation periods. However, unbiased root mean square error showed a slight increase during the snow ablation period due to the large variability in the electromagnetic response of C-band backscatter over deep and/or wet snow. Improvement of the SWE estimates also resulted in improving river discharge estimates compared to in situ measurements. River discharge using Sentinel-1 DAv1 improved the Nash–Sutcliffe efficiency at all available stations. These results suggest that physically constrained SVM can serve as an efficient observation operator for snow mass DA through explicit consideration of the first-order C-band scattering mechanisms over different terrestrial snow conditions.

Jongmin Park↗
NASA NTRS2006

Debris Flux Comparisons From The Goldstone Radar, Haystack Radar, and Hax Radar Prior, During, and After the Last Solar Maximum

The continual monitoring of low Earth orbit (LEO) debris environment using highly sensitive radars is essential for an accurate characterization of these dynamic populations. Debris populations are continually evolving since there are new debris sources, previously unrecognized debris sources, and debris loss mechanisms that are dependent on the dynamic space environment. Such radar data are used to supplement, update, and validate existing orbital debris models. NASA has been utilizing radar observations of the debris environment for over a decade from three complementary radars: the NASA JPL Goldstone radar, the MIT Lincoln Laboratory (MIT/LL) Long Range Imaging Radar (known as the Haystack radar), and the MIT/LL Haystack Auxiliary radar (HAX). All of these systems are highly sensitive radars that operate in a fixed staring mode to statistically sample orbital debris in the LEO environment. Each of these radars is ideally suited to measure debris within a specific size region. The Goldstone radar generally observes objects with sizes from 2 mm to 1 cm. The Haystack radar generally measures from 5 mm to several meters. The HAX radar generally measures from 2 cm to several meters. These overlapping size regions allow a continuous measurement of cumulative debris flux versus diameter from 2 mm to several meters for a given altitude window. This is demonstrated for all three radars by comparing the debris flux versus diameter over 200 km altitude windows for 3 nonconsecutive years from 1998 through 2003. These years correspond to periods before, during, and after the peak of the last solar cycle. Comparing the year to year flux from Haystack for each of these altitude regions indicate statistically significant changes in subsets of the debris populations. Potential causes of these changes are discussed. These analysis results include error bars that represent statistical sampling errors, and are detailed in this paper.

Stokely, C. L.↗
NASA NTRS2014

Drop Size Distribution - Based Separation of Stratiform and Convective Rain

For applications in hydrology and meteorology, it is often desirable to separate regions of stratiform and convective rain from meteorological radar observations, both from ground-based polarimetric radars and from space-based dual frequency radars. In a previous study by Bringi et al. (2009), dual frequency profiler and dual polarization radar (C-POL) observations in Darwin, Australia, had shown that stratiform and convective rain could be separated in the log10(Nw) versus Do domain, where Do is the mean volume diameter and Nw is the scaling parameter which is proportional to the ratio of water content to the mass weighted mean diameter. Note, Nw and Do are two of the main drop size distribution (DSD) parameters. In a later study, Thurai et al (2010) confirmed that both the dual-frequency profiler based stratiform-convective rain separation and the C-POL radar based separation were consistent with each other. In this paper, we test this separation method using DSD measurements from a ground based 2D video disdrometer (2DVD), along with simultaneous observations from a collocated, vertically-pointing, X-band profiling radar (XPR). The measurements were made in Huntsville, Alabama. One-minute DSDs from 2DVD are used as input to an appropriate gamma fitting procedure to determine Nw and Do. The fitted parameters - after averaging over 3-minutes - are plotted against each other and compared with a predefined separation line. An index is used to determine how far the points lie from the separation line (as described in Thurai et al. 2010). Negative index values indicate stratiform rain and positive index indicate convective rain, and, moreover, points which lie somewhat close to the separation line are considered 'mixed' or 'transition' type precipitation. The XPR observations are used to evaluate/test the 2DVD data-based classification. A 'bright-band' detection algorithm was used to classify each vertical reflectivity profile as either stratiform or convective, depending on whether or not a clearly-defined melting layer is present at an expected height, and if present, maximum reflectivity within the melting layer as well as the corresponding height are determined. We will present results of quantitative comparisons between the XPR observations-based classifications and the simultaneous 2DVD data-based classifications. Time series comparisons will be presented for thirteen events in Huntsville.

Thurai, Merhala↗
NASA NTRS2017

Concentric Eyewall Asymmetries in Hurricane Gonzalo (2014) Observed by Airborne Radar

Two eyewall replacement cycles were observed in Hurricane Gonzalo by the NOAA P3 Tail (TA) radar and the recently developed NASA High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar. These observations captured detailed precipitation and kinematic features of Gonzalo's concentric eyewalls both before and after the outer eyewall's winds became the vortex maximum winds. The data were analyzed relative to the deep-layer environmental wind shear vector. During the beginning eyewall replacement cycle stages, the inner and outer eyewalls exhibited different asymmetries. The inner eyewall asymmetry exhibited significant low-level inflow, updrafts, and positive tangential acceleration in the downshear quadrants, consistent with observational and theoretical studies. The outer eyewall asymmetry exhibited these features in the left-of-shear quadrants, further downwind from those of the inner eyewall. It is suggested that the low-level inflow occurring at the outer but not at the inner eyewall in the downwind regions signals a barrier effect that contributes to the eventual decay of the inner eyewall. Toward the later eyewall replacement stages, the outer eyewall asymmetry shifts upwind, becoming more aligned with the asymmetry of the earlier inner eyewall. This upwind shift is consistent with the structural evolution of eyewall replacement as the outer eyewall transitions into the primary eyewall of the storm.

Didlake, Anthony C.↗
NASA NTRS1985

Gravity wave spectra observed by Doppler radar: Comparison of a model with mesospheric observations

It was proposed that mesoscale fluctuations of wind and temperature in the free atmosphere are due to gravity waves. Critical tests of this hypothesis must involve the comparison of models based on the theory of buoyancy waves with suitable measurements. The MST (mesosphere-stratosphere-troposphere) radar technique is particularly attractive for this purpose, because it can measure several independent power spectra simultaneously. Observed spectra are derived from mesospheric data taken by the Poker Flat MST radar during June 1983. The spectra were compared with the model spectra for three days when suitable data were available. It was concluded that the mesoscale fluctuations were dominated by gravity waves, and the contribution of two-dimensional turbulence was small.

Vanzandt, T. E.↗
NASA NTRS1977

Geologic interpretation of new observations of the surface of Venus

New radar observations of the surface of Venus provide further evidence of a diverse and complex geologic evolution. The radar bright feature 'Beta' (24 deg N, 85 deg W) is seen to be a 700 km diameter region elevated a maximum of approximately 10 km relative to its surroundings with a 60 x 90 km wide depression at its summit. 'Beta' is interpreted to be a large volcanic construct, analogous to terrestrial and Martian shield volcanoes. Two large, quasi-circular areas of low reflectivity, examples of a class of features interpreted to be impact basins by previous investigators who were without the benefit of actual topographic information, are shown in altimetry maps to be depressions. Thus the term 'basin' can be applied, although we urge a non-genetic usage until more complete understanding of their origin is achieved through analysis of future observations.

Saunders, R. S.↗
NASA NTRS2011

Sensitivity of Spaceborne and Ground Radar Comparison Results to Data Analysis Methods and Constraints

With the availability of active weather radar observations from space from the Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TR.MM) satellite, numerous studies have been performed comparing PR reflectivity and derived rain rates to similar observations from ground-based weather radars (GR). These studies have used a variety of algorithms to compute matching PR and GR volumes for comparison. Most studies have used a fixed 3-dimensional Cartesian grid centered on the ground radar, onto which the PR and GR data are interpolated using a proprietary approach and/or commonly available GR analysis software (e.g., SPRINT, REORDER). Other studies have focused on the intersection of the PR and GR viewing geometries either explicitly or using a hybrid of the fixed grid and PR/GR common fields of view. For the Dual-Frequency Precipitation Radar (DPR) of the upcoming Global Precipitation Measurement (GPM) mission, a prototype DPR/GR comparison algorithm based on similar TRMM PR data has been developed that defines the common volumes in terms of the geometric intersection of PR and GR rays, where smoothing of the PR and GR data are minimized and no interpolation is performed. The PR and GR volume-averaged reflectivity values of each sample volume are accompanied by descriptive metadata, for attributes including the variability and maximum of the reflectivity within the sample volume, and the fraction of range gates in the sample average having reflectivity values above an adjustable detection threshold (typically taken to be 18 dBZ for the PR). Sample volumes are further characterized by rain type (Stratiform or Convective), proximity to the melting layer, underlying surface (land/water/mixed), and the time difference between the PR and GR observations. The mean reflectivity differences between the PR and GR can differ between data sets produced by the different analysis methods; and for the GPM prototype, by the type of constraints and categorization applied to the data. In this paper, we will show results comparing the 3-D gridded analysis "black box" approach to the GPM prototype volume-matching approach, using matching TRMM PR and WSR-88D ground radar data. The affects of applying data constraints and data categorizations on the volume-matched data to the results will be shown, and explanations of the differences in terms of data and analysis algorithm characteristics will be presented. Implications of the differences to the determination of PR/DPR calibration differences and use of ground radar data to evaluate the PR and DPR attenuation correction algorithms will be discussed.

Morris, Kenneth R.↗
NASA NTRS2017

MCRadar: A Monte Carlo Solver for Cloud and Precipitation Radar

Multiple scattering produces anomalous echoes in observed radar profiles that cannot be explained by other phenomena. These effects are most obvious for spaceborne platforms, at shorter wavelengths, and in convection, as multiple scattering is governed by antenna beam width, optical depth, and albe do; however, multiple scattering has been observed in a range of precipitating conditions. To account for the effects of multiple scattering, Monte Carlo integration is employed in a flexible framework to enable arbitrary radar configurations with finite Gaussian beams for three-dimensional atmospheric scenarios. The three-dimensional nature of the model, coupled with the finite antenna response, also allows for consideration of nonuniform beam filling effects that often coincide with multiple scattering. Examples of airborne and spaceborne radars at various wavelengths are used to illustrate the effects of multiple scattering and nonuniform beam filling. The MCRadar code is currently available in the development version of ARTS.

Adams, Ian Stuart↗
DOE OSTI2021

Polarimetric Signatures in Landfalling Tropical Cyclones

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: 1) hydrometeor size sorting within the eyewall convection, 2) vertical displacement of the melting layer within the inner core, and 3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting-layer displacements are shown that exceed 1 km in altitude compared to melting-layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo-top altitudes are low (≤10 km MSL), nearer the -15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Aircraft microwave observations and simulations of deep convection from 18 to 183 GHz. I - Observations

Aircraft passive microwave observations of deep atmospheric convection at frequencies between 18 and 183 GHz are presented in conjunction with visible and infrared satellite and aircraft observations and ground-based radar observations. Deep convective cores are indicated in the microwave data by negative brightness temperature, T/(B) deviations from the land background (270 K) to extreme T(B) values below 100 K at 37, 92, and 183 GHz and below 200 K at 18 GHz. These T(B) minima, due to scattering by ice held aloft by the intense updrafts, are well correlated with areas of high radar reflectivity. For this land background case, T(B) is inversely correlated with rain rate at all frequencies due to T(B)-ice-rain correlations. Mean Delta-T between vertically polarized and horizontally polarized radiance in precipitation areas is approximately 6 K at both 18 GHz and 37 GHz, indicating nonspherical precipitation-size ice particles with a preferred horizontal orientation. Convective cores not observed in the visible and infrared data are clearly defined in the microwave observations, and borders of convective rain areas are well defined using the high-frequency (90 GHz and greater) microwave observations.

Adler, Robert F.↗
NASA NTRS2017

Radar Detectability Studies of Slow and Small Zodiacal Dust Cloud Particles. III. The Role of Sodium and the Head Echo Size on the Probability of Detection

We present a path forward on a long-standing issue concerning the flux of small and slow meteoroids, which are believed to be the dominant portion of the incoming meteoric mass flux into the Earth's atmosphere. Such a flux, which is predicted by dynamical dust models of the Zodiacal Cloud, is not evident in ground-based radar observations. For decades this was attributed to the fact that the radars used for meteor observations lack the sensitivity to detect this population, due to the small amount of ionization produced by slow-velocity meteors. Such a hypothesis has been challenged by the introduction of meteor head echo (HE) observations with High Power and Large Aperture radars, in particular the Arecibo 430 MHz radar. Janches et al. developed a probabilistic approach to estimate the detectability of meteors by these radars and initially showed that, with the current knowledge of ablation and ionization, such particles should dominate the detected rates by one to two orders of magnitude compared to the actual observations. In this paper, we include results in our model from recently published laboratory measurements, which showed that (1) the ablation of Na is less intense covering a wider altitude range; and (2) the ionization probability, Beta ip, for Na atoms in the air is up to two orders of magnitude smaller for low speeds than originally believed. By applying these results and using a somewhat smaller size of the HE radar target we offer a solution that reconciles these observations with model predictions.

meteorites↗
DOE OSTI2020

Fireworks on Weather Radar and Camera

High-sensitivity weather radars easily detect nonmeteorological phenomena characterized by weak radar returns. Fireworks are the example presented here. To understand radar observations, an experiment was conducted in which the National Severe Storms Laboratory (NSSL)’s research (3-cm wavelength) dual-polarization radar and a video camera were located at 1 km from fireworks in Norman, Oklahoma. The fireworks from the 4 July 2017 celebration were recorded by both instruments. The experiment is described. Few bursts recorded by the camera are analyzed to obtain the height of the explosion, its maximum diameter, number of stars, and the duration of the visible image. Radar volume scans are examined to characterize the height of the observation, the maximum reflectivity, and its distribution with height. The fireworks location is close to the Terminal Doppler Weather Radar (TDWR) that operates in single polarization at a 5-cm wavelength and monitors hazardous weather over the Oklahoma City airport. A third radar with data from the event is the Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman. It has a wavelength of 10 cm and supports technical developments at the Radar Operation Center. Reflectivity factors measured by the three radars are compared to infer the size of dominant scatterers. The polarimetric characteristics of fireworks returns are analyzed. Although these differ from those of precipitation, they are indistinguishable from insect returns. Radar observation of larger fireworks in Fort Worth, Texas, with a WSR-88D is included and compared with the observations of the smaller fireworks in Norman. We expect the detectability of explosions would be similar as of fireworks. Pinpointing locations would be useful to first responders, or air quality forecasters. We note a benefit of fireworks recognition in weather radar data is that it can prevent contamination of precipitation accumulations.

54 ENVIRONMENTAL SCIENCES↗