Bayesian statistical analysis of ground-clutter for the relative calibration of dual polarization weather radars

A new data processing methodology, based on the statistical analysis of ground-clutter echoes and aimed at investigating the stability of the weather radar relative calibration, is presented. A Bayesian classification scheme has been used to identify meteorological and/or ground-clutter echoes. The outcome is evaluated on a training dataset using statistical score indexes through the comparison with a deterministic clutter map. After discriminating the ground clutter areas, we have focused on the spatial analysis of robust and stable returns by using an automated region-merging algorithm. The temporal series of the ground-clutter statistical parameters, extracted from the spatial analysis and expressed in terms of percentile and mean values, have been used to estimate the relative clutter calibration and its uncertainty for both co-polar and differential reflectivity. The proposed methodology has been applied to a dataset collected by a C-band weather radar in southern Italy

A fuzzy logic algorithm for classifying bird and insect radar echoes at S-band

A fuzzy logic algorithm for the separation of bird echoes from insect echoes using Next Generation Radar (NEXRAD) and considering range effects has been developed. The radar used in this study is the S-band (10 cm wavelength) KTLX WSR-88D radar located in Oklahoma City. Insects are known to dominate day time clear air echoes while birds dominate nocturnal echoes during migration season. September has also been found to be peak migrating season for birds. Data was analyzed from all clear air days in September 2017 to verify the composition of clear air echoes. Results confirm insect (bird) dominance during day (night). Also, the membership functions are derived directly from the distributions of radar variables and weighted in an objective manner. Finally, the algorithm is tested on three cases. Two cases with known Monarch butterfly abundance, confirmed by the US Department of Agriculture (USDA) are correctly identified as being insect dominated. One final classification for a 24-hour period further confirms that birds (insects) are responsible for most night (day) time radar echoes

The Bootstrap Dual Polarimetric Spectral Density Estimator

Weather radar moments and polarimetric variables provide useful information about the characteristics and motion of hydrometeors. However, the bulk information may be masked when the meteorological signal of interest is contaminated by clutter. The dual-polarimetric spectral densities (DPSD) may unveil additional information about the polarimetric characteristics of groups of scatterers moving at different Doppler velocities in a given radar resolution volume. Previous DPSD estimation methods required averaging a large number of spectra (obtained from different range gates, radials, or scans), or averaging in frequency to get accurate estimates; though by doing so, the resolution is degraded, and important features of the meteorological phenomenon may be masked, potentially affecting the ability to perform a good spectral analysis. In an attempt to overcome these limitations, the Bootstrap DPSD estimator is developed, which allows the estimation of DPSDs from a single dwell, with minimal resolution loss. Briefly, the estimator pre-processes the weather radar I/Q time-series signals and generates I/Q pseudo-realizations through bootstrap resampling, which are then used to compute PSD estimates that are averaged to obtain the DPSD estimate. Then, a post-processing stage applies a bias correction to the estimates. The Bootstrap DPSD estimator's performance is compared to that of conventional methods for single-dwell as well as for multiple-dwell estimates. Additionally, the performance and limitations of the Bootstrap and conventional DPSD estimators are assessed when identifying signals of different polarimetric signatures of scatterers moving at different radial velocities in the radar volume. The advantages of the Bootstrap DPSD estimator as a tool for polarimetric spectral analysis is demonstrated with a few examples of polarimetric spectral signatures in data from tornado cases, and from a physically-based simulator. It is expected that, with the Bootstrap DPSD and polarimetric spectral analysis, it will be possible to better understand tornado dynamics and their connection to weather radar measurements, as well as to elucidate important scientific questions that motivated this work

Effects of spatial resolution on radar-based precipitation estimation using sub-kilometer X-band radar measurements

Known for the ability to observe precipitation at spatial resolution higher than rain gauge networks and satellite products, weather radars allow us to measure precipitation at spatial resolutions of 1 kilometer (typical resolution for operational radars) and a few hundred meters (often used in research activities). In principle, we can operate a weather radar at resolution higher than 100m and the expectation is that radar data at higher spatial resolution can provide more information. However, there is no systematic research about whether the additional information is noise or useful data contributing to the quantitative precipitation estimation. In order to quantitatively investigate the changes, as either benefits or drawbacks, caused by increasing the spatial resolution of radar measurements, we set up an X-band radar field experiment from May to October in 2017 in the Stuttgart metropolitan region. The scan strategy consists of two quasi-simultaneous scans with a 75-m and a 250-m radial resolution respectively. They are named as the fine scan and the coarse scan, respectively. Both scans are compared to each other in terms of the radar data quality and their radar-based precipitation estimates. The primary results from these comparisons between the radar data of these two scans show that, in contrast to the coarse scan, the fine scan data are characterized with losses of weak echoes, are more subjected to external signals and second-trip echoes (drawback), are more effective in removing non-meteorological echoes (benefit), are more skillful in delineating convective storms (benefit), and show a better agreement with the external reference data (benefit)

Remote Sensing of Earth Resources: A literature survey with indexes (1970 - 1973 supplement). Section 1: Abstracts

Abstracts of reports, articles, and other documents introduced into the NASA scientific and technical information system between March 1970 and December 1973 are presented in the following areas: agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis