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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Characterization of Mesoscale Convective Systems by Means of Composite Radar Reflectivity Data

A mesoscale convective system (MCS) is broadly defined as a cloud and precipitation system of mesoscale dimensions (often too large for most aircraft to circumnavigate) with deep-convective activity concentrated in at least part of the MCS, or present during part of its evolution. A large areal fraction of MCSs is stratiform in nature, yet estimates from MCSs over the Great Plains, the Southeast, and tropical waters indicate that at least half of the precipitation is of convective origin. The presence of localized convection is important, because within convective towers cloud particles and hydrometeors are carried upward towards the cloud top. Ice crystals then move over more stratiform regions, either laterally, or through in situ settling over decaying and spreading convection. These ice crystals then grow to precipitation-size particles in mid- to upper tropospheric mesoscale updrafts. The convective portion of a MCS is often a more or less continuous line of thunderstorms, and may be either short-lived or long-lived. Geerts (1997) presents a preliminary climatology of MCSs in the southeastern USA, using just one year of composite digital radar reflectivity data. In this study MCSs are identified and characterized by means of visual inspection of animated images. A total of 398 MCSs were identified. In the warm season MCSs were found to be about twice as frequent as in the cold season. The average lifetime and maximum length of MCSs are 9 hours, and 350 km, respectively, but some MCSs are much larger and more persistent. In the summer months small and short-lived MCSs are relatively more common, whereas in winter larger and longer-lived systems occur more frequently. MCSs occur more commonly in the afternoon, in phase with thunderstorm activity, but the amplitude of the diurnal cycle is small compared to that of observed thunderstorms. It is estimated that in the Southeast more than half of all precipitation and severe weather results from MCSs.

Geerts, Bart↗
NASA NTRS1993

Maximum a posteriori classification of multifrequency, multilook, synthetic aperture radar intensity data

We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.

Rignot, E.↗
NASA NTRS1980

Servomechanism for Doppler shift compensation in optical correlator for synthetic aperture radar

A method and apparatus for correcting Doppler shifts in synthetic aperture radar data is described. An optical correlator for synthetic aperture radar data has a means for directing a laser beam at a signal film having radar return pulse intensity information recorded on it. A resultant laser beam passes through a range telescope, an azimuth telescope, and a Fourier transform filter located between the range and azimuth telescopes, and forms an image for recording on an image film. A compensation means for Doppler shift in the radar return pulse intensity information includes a beam splitter for reflecting the modulated laser beam, after having passed through the Fourier transform filter, to a detection screen having two photodiodes mounted on it.

Constaninides, N. J.↗
NASA NTRS2022

Relationship of Multiwavelength Radar Measurements to Ice Microphysics from the IMPACTS Field Program

Coincident radar data with Doppler radar measurements at X, Ku, Ka, and W bands on the NASA ER-2 aircraft overflying the NASA P3 aircraft acquiring in-situ microphysical measurements are used to characterize the relationship between radar measurements and ice microphysical properties. The data were obtained from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS. Direct measurements of the condensed water content as well as coincident Doppler radar measurements were acquired, facilitating improved estimates of ice particle mass, a variable that is an underlying factor for calculating and therefore retrieving the radar reflectivity (Z_(e)), median mass diameter (D_(m)), particle terminal velocity, and snowfall rate (S). The relationship between the measured ice water content (IWC) and that calculated from the particle size distributions (PSD) using relationships developed in earlier studies, and between the calculated and measured radar reflectivity at the four radar wavelengths, are quantified. Relationships are derived between the measured IWC and properties of the PSD, D_(m), Z_(e) at the four radar wavelengths and the dual-wavelength ratio. Because IWC and Z_(e) are measured directly, the coefficients in the mass-dimensional relationship that best match both the IWC and Z_(e) are derived. The relationships developed here, and the mass-dimensional relationship that uses both the measured IWC and Z_(e) to find a best match for both variables, can be used in studies that characterize the properties of wintertime snow clouds.

Andrew Heymsfield↗
NASA NTRS2021

Goldstone Orbital Debris Radar: A Historical Review from a Decade of Observations (2007 – 2017)

The NASA Orbital Debris Program Office (ODPO) has utilized the Goldstone bistatic radar since the early1990’s to statistically characterize the low Earth orbit(LEO) sub-centimeter population. The radar provides a unique capability to detect orbital debris population sizes down to an approximate size of 3 mm for altitudes less than 1000 km, and even smaller sizes at lower altitudes. Due to the limited number of hours that are available from this radar each year, it is often used to validate measurements obtained by other radar data sources in the range of orbital debris sizes where the radar systems have an overlap. Additionally, the Goldstone radar provides significantly improved sensitivity than is available from other ground-based radar data sources, which enables it to observe orbital debris populations that, although smaller, still represent a significant risk to both robotic and human missions in LEO. Over the decade of observations from 2007 to2017, a number of significant on-orbit events have occurred including the anti-satellite test againstFengyun-1C, and the accidental collision between Cosmos 2251 and Iridium 33. The orbital debris flux as measured by the Goldstone radar over this important time period is reviewed in this paper, as well as the evolution of the environment over the ensuing years since these events. In addition, the measurements provided by this radar in the years prior to the deployment of large constellations into the environment, as well as the significant increase in missions and mission participants in recent years, is of interest since it provides a baseline for monitoring the effects of these and other changes in the coming years. In 2018, the Goldstone bistatic orbital debris radar pointing geometry changed due to the decommissioning of the nearby receiver antenna, Deep Space Station (DSS) 15, located approximately 500 m from the transmitter antenna. The historical combination of the DSS-14 transmitter and DSS-15receiver enabled all of LEO to be observed using a single pointing due to the close proximity of the two antenna stations and the resulting beam overlap of the bistatic radar geometry. The updated bistatic Goldstone geometry, following the decommissioning of DSS-15,utilizes one of the pair of DSS-25 or DSS-26 antennas that are located approximately 10 km from the transmitter station. The resulting beam overlap with this pointing is such that in LEO, only a small fraction of LEO altitude coverage is observable at one time. Given the operational change of the radar, it is of interest to review the data collected by the original Goldstone bistatic radar over the final decade preceding this change.

Rossina Miller↗
NASA NTRS1990

Satellite radar for monitoring forest resources

An evaluation is made of the computer analysis results of a study which used Seasat satellite radar data obtained in 1978 and Shuttle Imaging Radar-B data obtained in 1984. The change-detection procedures employed demonstrate that deforestation and reforestation activities can be effectively monitored on the basis of radar data gathered at satellite altitudes. The computer-processing techniques applied to the data encompassed (1) overlay display, (2) ratios, (3) differences, (4) principal-component analysis, and (5) classification; of these, overlay display is noted to quickly and easily yield a qualitative display of the multidate data.

Hoffer, Roger M.↗
NASA NTRS1980

Wallops waveform analysis of SEASAT-1 radar altimeter data

Fitting a six parameter model waveform to over ocean experimental data from the waveform samplers in the SEASAT-1 radar altimeter is described. The fitted parameters include a waveform risetime, skewness, and track point; from these can be obtained estimates of the ocean surface significant waveheight, the surface skewness, and a correction to the altimeter's on board altitude measurement, respectively. Among the difficulties encountered are waveform sampler gains differing from calibration mode data, and incorporating the actual SEASAT-1 sampled point target response in the fitted wave form. There are problems in using the spacecraft derived attitude angle estimates, and a different attitude estimator is developed. Points raised in this report have consequences for the SEASAT-1 radar altimeter's ocean surface measurements are for the design and calibration of radar altimeters in future oceanographic satellites.

Hayne, G. S.↗
NASA NTRS1984

An attempt to extend the ATI technique to estimate convective rain volumes using satellite data

Digital satellite and radar data of a thunderstorm event that occurred on June 12, 1981 are examined. The processing of both data sets is described. Cumulative area versus count values, and threshold count values for IR and visible satellite data for 13 consecutive time steps are analyzed. The IR and visible satellite images are compared. The relation between radar reflectivity, temperature, and echo height is studied.

Doneaud, A. A.↗
NASA NTRS2022

Using Trajectory Smoothness Metrics to Identify Drones in Radar Track Data

The identification of unmanned aircraft systems (UAS) using trajectory data is considered. Specifically, a number of smoothness metrics are proposed, which can be used to distinguish UAS from other aerial objects even when they are engaged in accelerative maneuvers (non-constant-velocity flight). The metrics are evaluated on a data set from a UAS sense-and-avoid field test, which contains track data of aerial objects recorded by a vehicle-board radar system during a flight test. The metrics are found to effectively differentiate UAS from other objects such as birds for this data set. In addition, an initial statistical performance analysis of one of the smoothness metrics is undertaken, using 15 data sets deriving from multiple flight tests. The smoothness metric is shown to identify the target UAS with 95% accuracy (95% true positive rate), while achieving a false positive rate of less than 9%.

Sandip Roy↗
NASA NTRS1996

Application of SIR-C SAR to Hydrology

The progress, results and future plans regarding the following objectives are presented: (1) Determine and compare soil moisture patterns within one or more humid watersheds using SAR data, ground-based measurements, and hydrologic modeling; (2) Use radar data to characterize the hydrologic regime within a catchment and to identify the runoff producing characteristics of humid zone watersheds; and (3) Use radar data as the basis for scaling up from small scale, near-point process models to larger scale water balance models necessary to define and quantify the land phase of GCM's (Global Circulation Models).

Engman, Edwin T.↗
NASA NTRS1999

Dependence of Z-R Relations on the Rain Type Classification Scheme

The TRMM Global Validation Program is giving us a unique opportunity to compare radar datasets from different sites since they are analyzed in a relatively uniform procedure. Monthly Ze-R relations for four different sites (i.e, Melbourne Florida, Houston Texas, Darwin Australia and Kwajalein Atoll) were derived. The relations were obtained using the Window Probability Matching Method (WPMM). This version of the PMM relies on matching unconditional probabilities of rain rates, R, and radar reflectivity, Ze, using rain gauge and radar data, respectively. This procedure was done separately for convective and stratiform rain type using the Steiner classification procedure. The radar and gauge data from all sites were quality controlled using the same algorithms, which include also an automatic procedure to filter unreliable rain gauge data upon comparison to radar data. An adjusted power law Z-R for each rain type was also derived by comparing the radar-gauge coincident pairs in order to adjust the total monthly rainfall to match the gauges. The obtained PMM based Ze-R relations are found to be curved lines in log-log space rather than any straight line power law. While the PMM based Ze-R curves were always distinctly different between the convective and stratiform rain, the power law based Z-R, in few cases, was found to be the same for both types. In general, a given reflectivity was matched to a much lower rain intensity in the convective rainfall as compared to that in stratiform rainfall. These findings are inherently contradictory to previous findings based on disdrometer data and suggest some precaution for using the latter Z-R relations on radar data when the partition of stratiform and convective rainfall amount is in concern. The inverse trends in the relations might be caused by effects such as partial beam fillings, the use of different classification schemes, as well as having a distinct difference in the Z-R relations between the initial convective and the trailing transition regions as suggested by recent findings.

Amitai, Eyal↗
NASA NTRS1992

Observation of mesoscale ocean features in the northeast Pacific using Geosat radar altimetry data

Mesoscale circulation in the Gulf of Alaska is studied by means of processed Geosat radar altimetry results with comparisons to observations of mesoscale eddies and surface circulation. The first set of Geosat data is treated by sea-surface height (SSH) binning in 1-deg latitude x 2-deg longitude boxes and analyzed by complex empirical orthogonal functions and 2D spectral analysis. The second set is taken from ascending Geosat tracks and analyzed as a time series. The Geosat data are compared to observational data including mesoscale eddies and fluctuations in mean surface circulation as well as sea-surface signals generated by numerical models. The data demonstrate the feasibility of a westward propagation of sea-level anomalies, and the Geosat SSH data are found to agree well with model solutions of seasonal variations in sea level in the northeast Pacific.

Matthews, Paul E.↗
NASA NTRS1989

Application of an optimal filter for inflatable sphere data processing

The improvement in the sphere data processing, concerning the signal to noise ratio, is discussed. Frequency analysis of the radar data is effectuated. It reveals a specific frequency component in the radar angle error, which may originate from the tracking radar mechanism itself. An optimal (Wiener) filter is applied to the radar data in order to suppress the systematic angular error components selectively. Using this technique, a significant improvement in the signal to noise ratio is achieved. The resolution of sphere measurements, previously limited by the length of the polynomial filter in the sphere data processing algorithm, is improved.

Lee, H. S.↗
DOE OSTI2020

Mapped Moments to a Cartesian Grid (MMCG) Value-Added Product Report

Objective analysis (OA) is a method of mapping unstructured data to a structured grid. In the context of scanning radar data, OA is used to interpolate data in antenna coordinates (range, azimuth, and elevation) onto a regularly spaced Cartesian grid (Trapp and Doswell 2000). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Mapped Moments to a Cartesian Grid (MMCG) Value-Added Product (VAP) uses the Python ARM Radar Toolkit (Py-ART), a data model-driven interactive architecture for working with weather radar data, to map the data to a Cartesian grid (Helmus and Collis 2016). MMCG, with Py-ART built in, has the ability to take radar data in antenna coordinates and map the gates to a Cartesian grid using inverse distance weight functions such as Cressman (square) and Barnes (exponential), but also can filter the data during the interpolation. MMCG also allows arbitrary formulations for the radius of influence, which are matched to particular radar scanning strategies. This creates a complex parameter space for optimizing the retention of storm structure detail while minimizing artifacts. MMCG takes data processed with ARM’s Corrected Precipitation Radar Moments in Antenna Coordinates (CMAC) VAP and maps it to a Cartesian grid as the output product. A variety of fields that have been mapped to the Cartesian grid are then saved to plots to complement each grid file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Radar / Raw Data

This dataset contains raw data from the UND 94 GHz W-band Cloud Doppler Radar.

17 WIND ENERGY↗
DOE OSTI2025

Radar / Processed Data

This dataset contains processed raw data from the UND 94 GHz W-band Cloud Doppler Radar.

17 WIND ENERGY↗