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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quantitative Precipitation Estimation of Extremes in CONUS With Radar Data

When constructing an accurate, continental, in-situ-based, kilometer-scale, long-term record of the precipitation field and its spatiotemporal changes remains a significant challenge. Here, we determine the extreme-value behavior of the NEXRAD Stage IV radar-based quantitative precipitation estimate. We find that the climatology of 5-year daily return values in the contiguous United States East of the Rocky Mountains shows only slight variability on spatial scales smaller than (Formula presented.) ~100 km. In light of this finding, we test whether rain-gauge-only daily precipitation data sets can produce accurate extreme-value behavior at spatial scales finer than the spacing between gauges. We find that the 5-year daily return values are accurate at locations far from rain gauges only if the interpolation between gauges is carried out appropriately for extremes. Precipitation statistics derived from in-situ rain gauge data are therefore of sufficient spatial resolution to faithfully capture daily extremes over much of the eastern United States.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Delta K measurements with synthetic aperture radar data

Delta K measurements are obtained from the interference of two electromagnetic waves of different frequencies. Constructive interference occurs when 2pi phase differences between the two frequencies correspond to a surface wavelength. Previous Delta K measurements have used two discrete frequencies for this purpose. Range pulses and Doppler signatures of a synthetic aperture radar system were filtered to obtain a sequence of Delta K values. Those Delta K values which correspond to the wavelengths of known surfaces show maximum constructive interference. SAR data can therefore be used for Delta K measurements, indicating the possibility of selective Delta K filtering during data gathering.

Larson, R. W.↗
NASA NTRS1986

Off-line processing of ERS-1 synthetic aperture radar data with high precision and high throughput

The first European remote sensing satellite ERS-1 will be launched by the European Space Agency (ESA) in 1989. The expected lifetime is two to three years. The spacecraft sensors will primarily support ocean investigations and to a limited extent also land applications. Prime sensor is the Active Microwave Instrumentation (AMI) operating in C-Band either as Synthetic Aperture Radar (SAR) or as Wave-Scatterometer and simultaneously as Wind-Scatterometer. In Europe there will be two distinct types of processing for ERS-1 SAR data, Fast Delivery Processing and Precision Processing. Fast Delivery Proceessing will be carried out at the ground stations and up to three Fast Delivery products per pass will be delivered to end users via satellite within three hours after data acquisition. Precision Processing will be carried out in delayed time and products will not be generated until several days or weeks after data acquisition. However, a wide range of products will be generated by several Processing and Archiving Facilities (PAF) in a joint effort coordinated by ESA. The German Remote Sensing Data Center (Deutsches Fernerkundungsdatenzentrum DFD) will develop and operate one of these facilities. The related activities include the acquisition, processing and evaluation of such data for scientific, public and commercial users. Based on this experience the German Remote Sensing Data Center is presently performing a Phase-B study regarding the development of a SAR processor for ERS-1. The conceptual design of this processing facility is briefly outlined.

Gredel, J.↗
NASA NTRS2010

A New Display Format Relating Azimuth-Scanning Radar Data and All-Sky Images in 3-D

Here we correlate features in a sequence of all-sky images of 630 nm airglow with the three-dimensional (3-D) structure of electron densities in the F region above Arecibo. Pairs of 180 azimuth scans (using the Gregorian and line feeds) of the two-beam incoherent scatter radar (ISR) have been plotted in cone pictorials of the line-of-sight electron densities. The plots include projections of the 630 nm airglow onto the ground using the same spatial scaling as for the ISR data. Selected sequential images from the night of 16-17 June 2004 correlate ionospheric plasma features with scales comparable to the ISR density-cone diameter. The entire set of over 100 images spanning about eight hours is available as a movie. The correlation between the airglow and the electron densities is not unexpected, but the new display format shows the 3-D structures better than separate 2-D plots in latitude and longitude for the airglow and in height and time for the electron densities. Furthermore, the animations help separate the bands of airglow from obscuring clouds and the star field.

Swartz, Wesley E.↗
NASA NTRS1992

Identification of sea ice types in spaceborne synthetic aperture radar data

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

Kwok, Ronald↗
NASA NTRS1995

Optimal Signal Processing of Frequency-Stepped CW Radar Data

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Ybarra, Gary A.↗
NASA NTRS1995

Optimal Signal Processing of Frequency-Stepped CW Radar Data

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Ybarra, Gary A.↗
NASA NTRS1977

Necessity to adapt land use and land cover classification systems to readily accept radar data

A hierarchial, four level, standardized system for classifying land use/land cover primarily from remote-sensor data (USGS system) is described. The USGS system was developed for nonmicrowave imaging sensors such as camera systems and line scanners. The USGS system is not compatible with the land use/land cover classifications at different levels that can be made from radar imagery, and particularly from synthetic-aperture radar (SAR) imagery. The use of radar imagery for classifying land use/land cover at different levels is discussed, and a possible revision of the USGS system to more readily accept land use/land cover classifications from radar imagery is proposed.

Drake, B.↗
NASA NTRS1978

LDAR observations of a developing thunderstorm correlated with field mill, ground strike location, and weather radar data including the first report of the design and capabilities of a new, time-of-arrival Ground-strike Location System (GSLS)

An experiment designed to observe and measure a thunderstorm prior to, during, and after its development over the Kennedy Space Center was successful. Correlated measurements of airborne field strength, ground-based field strength, LDAR lightning discharge location in the clouds, weather radar percipitation echoes, plus ground strike location with the new KSC Ground Strike Location System (GSLS) were gathered, and reported. This test marks the first operational use of the GSLS System, and this report contains the first report of its design and capabilities.

Poehler, H. A.↗
NASA NTRS1999

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Tao, Wei-Kuo↗
NASA NTRS2019

Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS

New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight into the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008–2017 using the Kling–Gupta efficiency (KGE), a performance metric combining correlation, bias, and variability. As a reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the ERA5-HRES fourth-generation reanalysis, reflecting the significant advances in earth system modeling during the last decade. The (re)analyses generally performed better in winter than in summer, while the opposite was the case for the satellite-based datasets. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements implemented in the IMERG satellite P retrieval algorithm. IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms, while the opposite was observed in regions of complex terrain. The ERA5-EDA ensemble average exhibited higher correlations than the ERA5-HRES deterministic run, highlighting the value of ensemble modeling. The WRF regional convection-permitting climate model showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings provide some guidance to choose the most suitable P dataset for a particular application.

Hylke E. Beck↗