The Python ART Radar Toolkit

The Python ARM Radar Toolkit, Py-ART, is a Python module containing a collection of weather radar algorithms and utilities. Py-ART is used by the Atmospheric Radiation Measurement (ARM) Climate Research Facility for working with data from a number of its precipitation and cloud radars, but has been designed so that it can be used by others in the radar and atmospheric communities to examine, processes, and analyze data from many types of weather radars.

What can Py-ART do?

Py-ART has the ability to ingest (read) from a number of common weather radar formats including Sigmet/IRIS, MDV, CF/Radial, UF, and NEXRAD Level II archive files. Radar data can be written to NetCDF files which conform to the CF/Radial convension.

Py-ART also contains routines which can produce common radar plots including PPIs and RHIs.

Algorithms in the module are able to performs a number of corrections on the radar moment data in antenna coordinate including attenuation correction of the reflectivity, velocity dealiasing, and correction of the specific (Kdp) and differential (PhiDP) phases.

A sophisticated mapping routines is able to efficiently create uniform Cartesian grids of radar fields from one or more radars. Routines exist in Py-ART for plotting these grids as well as saving them to NetCDF files.

GitHub repository

Python-3 Ground Penetrating Radar

Wireless Monostatic Ground Penetrating Radar with one receiving-transmitting antenna Python-3.

Features

• FREQUENCES: 100 / 50 / 38 / 25 MHz
• ANTENNA LENGTH: from 1 m to 4 m, depends on selected frequency
• WEIGHT: from 10 kg to 20 kg, depends on selected frequency
• TIME RANGE: from 1 to 1500 ns, step 1 ns
• SCAN RATE: 28 scans per second
• SAMPLES PER SCAN: 1024 samples per scan
• RESOLUTION: 16 bit
• FILTERS: Preset and Customized digital filters.
• GAIN: 9 points digital gain function
• DATA TRANSFER: through built-in Wi-Fi to PC.
• POWER: Built-in battery 12 V, 9 A*h with battery life more than 7 h

Python-3 georadar is a portable digital subsurface sounding radar carried by a single operator, especially used for deep surveys (up to 50 meters* in favorable ground). The unit is designed for solving a long-range of geotechnical, geological, engineering and other tasks wherever nondestructive operational environmental monitoring is needed. In the sounding process, the operator is getting real-time information as a radiolocation profile (sometimes also referred to as radargram) on a display. At the same time, data are recorded on a hard disc for further use (processing, printout, interpretation, etc.). Examples of radiolocation profiles you can see below.

Pachube opens the Internet of things to end users

Sensor data integration platform’s new service allows its customers’ customers to access information collected about them IN sensor networks of old, the data produced by, for example, heat or humidity sensors would remain in closed networks, accessible only by the organisation that runs the network.

The basic principle of the ‘Internet of things’ is that sensor data should in fact be openly available for integration with other data sets and for independent application developers to use to build new, innovative systems.

Pachube is a UK-based company that provides real-time data infrastructure for the Internet of things. “We make it very easy for devices to publish to the web in a format that’s easy for people to understand,” explains founder Usman Haque. “We also make it very easy for application developers to build things on top of all that data.”

“Essentially, Pachube is bit like Twitter for machines,” he says.

The pitch to sensor manufacturers is as follows: “If you’re a manufacturer, all you have to do is write a little bit of firmware which goes on your device, and we’ll take care of the rest. On the input end, we’ve got a standard interface for handling data in a variety of formats, and at the other end, we can convert that data into formats such as JSON, which is very popular among web developers.”

Information Age

A Polarimetric Radar Forward Operator for Model Evaluation

A polarimetric radar forward operator has been developed as a tool for the systematic evaluation of microphysical parameterization schemes in high-resolution numerical weather prediction (NWP) models. The application of such a forward operator allows a direct comparison of the model simulations to polarimetric radar observations. While the comparison of observed and synthetic reflectivity gives information on the quality of quantitative precipitation forecasts, the information from the polarimetric quantities allows for a direct evaluation of the capacity of the NWP model to realistically describe the processes involved in the formation and interactions of the hydrometeors and, hence, the performance of the microphysical parameterization scheme. This information is expected to be valuable for detecting systematic model errors and hence improve model physics. This paper summarizes the technical characteristics of the synthetic polarimetric radar (SynPolRad). Different polarimetric radar quantities are computed from model forecasts using a T-matrix scattering code and ice phase hydrometeors are explicitly considered. To do so, the sensitivities of the scattering processes to the microphysical characteristics of different ice hydrometeors are investigated using sensitivity studies. Furthermore, beam propagation effects are considered, including attenuation and beam bending. The performance of SynPolRad and the consistence of the assumptions made in the derivation of the input parameters are illustrated in a case study. The resulting synthetic quantities as well as hydrometeor classification are compared with observations and are shown to be consistent with the model assumptions.- Reference

An Analysis of Errors in Drop Size Distribution Retrievals and Rain Bulk Parameters with a UHF Wind Profiling Radar and a Two-Dimensional Video Disdrometer

Vertically pointed wind profiling radars can be used to obtain measurements of the underlying drop size distribution (DSD) for a rain event by means of the Doppler velocity spectrum. Precipitation parameters such as rainfall rate, radar reflectivity factor, liquid water content, mass-weighted mean drop diameter, and median volume drop diameter can then be calculated from the retrieved DSD. The DSD retrieval process is complicated by the presence of atmospheric turbulence, vertical ambient air motion, selection of fall speed relationships, and velocity thresholding. In this note, error analysis is presented to quantify the effect of each of those factors on rainfall rate. The error analysis results are then applied to two precipitation events to better interpret the rainfall-rate retrievals.

It was found that a large source of error in rain rate is due to unaccounted-for vertical air motion. For example, in stratiform rain with a rainfall rate of R = 10 mm h⁻¹, a mesoscale downdraft of 0.6 m s⁻¹ can result in a 34% underestimation of the estimated value of R. The fall speed relationship selection and source of air density information both caused negligible errors. Errors due to velocity thresholding become more important in the presence of significant contamination near 0 m s⁻¹, such as ground clutter. If particles having an equivalent volume diameter of 0.8 mm and smaller are rejected, rainfall rate errors from −4% to −10% are possible, although these estimates depend on DSD and rainfall rate.- Reference

Coupled Contributions in the Doppler Radar Spectrum Width Equation

Contrary to accepted usage, the second central moment of the Doppler spectrum is not the sum of the second central moments of individual spectral broadening mechanisms. A rigorous theoretical derivation of the spectrum width observed with short dwell times reveals that the sum cannot strictly be taken for the variances associated with various spectral broadening mechanisms and that an added-term coupling shear with turbulence is needed. Furthermore, shear and antenna rotation are coupled. The theoretical expressions derived herein apply to radars with fixed or scanning beams.- Reference

Clutter Suppression for Staggered PRT Waveforms

This paper presents a clutter suppression methodology for staggered pulse repetition time (PRT) observations. It is shown that spectral moments of precipitation echoes can be accurately estimated even in cases where clutter-to-signal ratios are high by using a parametric time domain method (PTDM).

Based on radar signal simulations, the accuracy of the proposed method is evaluated for various observation conditions. The performance of PTDM is demonstrated by the implementation of the staggered PRT at the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL). Based on this study, it is found that the accuracy of the retrieval is comparable to the current state of the art methods applied to the uniformly sampled observations and that the estimated velocity is unbiased for the complete Nyquist range.- Reference

Effects of Multiple Scattering on Attenuation-Based Retrievals of Stratiform Rainfall from CloudSat

An attenuation-based method to retrieve vertical profiles of rainfall rates from height derivatives/gradients of CloudSat nadir-pointing W-band reflectivity measurements is discussed. This method takes advantage of the high attenuation of W-band frequency signals in rain and the low variability of nonattenuated reflectivity due to strong non-Rayleigh scattering from rain drops. The retrieval uncertainties could reach 40%–50%. The suggested method is generally applicable to rainfall rates (R) in an approximate range from about 2–3 to about 20–25 mm h⁻¹. Multiple scattering noticeably affects the gradients of CloudSat measurements for R values greater than about 5 mm h⁻¹. To avoid a retrieval bias caused by multiple-scattering effects, a special correction for retrievals is introduced. For rainfall rates greater than about 25 mm h⁻¹, the influence of multiple scattering gets overwhelming, and the retrievals become problematic, especially for rainfalls with higher freezing-level altitudes. The attenuation-based retrieval method was applied to experimental data from CloudSat covering the range of rainfall rates. CloudSat retrievals were compared to the rainfall estimates available from a National Weather Service ground-based scanning precipitation radar operating at S band. Comparisons between spaceborne and conventional radar rainfall retrievals were generally in good agreement and indicated the mutual consistency of both quantitative precipitation estimate types. The suggested CloudSat rainfall retrieval method is immune to the absolute calibration of the radar and to attenuation caused by the melting layer and snow regions. Since it does not require surface returns, it is applicable to measurements above both land and water surfaces.- Reference

Quality Assessment of Weather Radar Wind Profiles during Bird Migration

Wind profiles from an operational C-band Doppler radar have been combined with data from a bird tracking radar to assess the wind profile quality during bird migration. The weather radar wind profiles (WRWPs) are retrieved using the well-known volume velocity processing (VVP) technique. The X-band bird radar performed range–height scans perpendicular to the main migration direction and bird densities were deduced by counting and normalizing the observed echoes. It is found that the radial velocity standard deviation (σ_r) obtained from the VVP retrieval is a skillful indicator of bird migration. Using a threshold of 2 m s⁻¹ on σ_r, more than 93% of the bird-contaminated wind vectors are rejected while over 70% of the true wind vectors are accepted correctly. For high bird migration densities the raw weather radar wind vectors have a positive speed bias of 8.6 ± 3.8 m s⁻¹, while the quality-controlled wind vectors have a negligible speed bias. From the performance statistics against a limited area numerical weather prediction model, it is concluded that all (significant) bird contamination is removed and that high-quality weather radar wind profiles can be obtained, even during the bird migration season.- Reference

An Evaluation of Two NEXRAD Wind Retrieval Methodologies and Their Use in Atmospheric Dispersion Models

Two entirely different methods for retrieving 3D fields of horizontal winds from Next Generation Weather Radar (NEXRAD) radial velocities have been evaluated using radar wind profiler measurements to determine whether routine wind retrievals would be useful for atmospheric dispersion model applications. The first method uses a physical algorithm based on four-dimensional variational data assimilation, and the second simpler method uses a statistical technique based on an analytic formulation of the background error covariance. Both methods can be run in near–real time, but the simpler method was executed about 2.5 times as fast as the four-dimensional variational method. The observed multiday and diurnal variations in wind speed and direction were reproduced by both methods below 1.5 km above the ground in the vicinity of Oklahoma City, Oklahoma, during July 2003. However, wind retrievals overestimated the strength of the nighttime low-level jet by as much as 65%. The wind speeds and directions obtained from both methods were usually similar when compared with profiler measurements, and neither method outperformed the other statistically. Within a dispersion model framework, the 3D wind fields and transport patterns were often better represented when the wind retrievals were included along with operational data. Despite uncertainties in the wind speed and direction obtained from the wind retrievals that are higher than those from remote sensing radar wind profilers, the inclusion of the wind retrievals is likely to produce more realistic temporal variations in the winds aloft than would be obtained by interpolation using the available radiosondes, especially during rapidly changing synoptic- and mesoscale conditions.- Reference

An Orientation-Selective Orthogonal Lapped Transform

A novel critically sampled orientation-selective orthogonal lapped transform called the lapped Hartley transform (LHT) is derived. In a first step, overlapping basis functions are generated by modulating basis functions of a 2-D block Hartley transform by a cosine wave. To achieve invertibility and orthogonality, an iterative filter is applied as prefilter in the analysis and as postfilter in the synthesis operation, respectively. Alternatively, filtering can be restricted to analysis or synthesis, ending up with a biorthogonal transform (LHT-PR, LHT-PO). A statistical analysis based on a 4000-image data base shows that the LHT and LHT-PO have better redundancy removal properties than other block or lapped transforms. Finally, image compression and noise removal examples are given, showing the advantages of the LHT especially in images containing oriented textures. - Reference

Texture Analysis and Classification With Linear Regression Model Based on Wavelet Transform

The wavelet transform as an important multiresolution analysis tool has already been commonly applied to texture analysis and classification. Nevertheless, it ignores the structural information while capturing the spectral information of the texture image at different scales. In this paper, we propose a texture analysis and classification approach with the linear regression model based on the wavelet transform. This method is motivated by the observation that there exists a distinctive correlation between the sample images, belonging to the same kind of texture, at different frequency regions obtained by 2-D wavelet packet transform. Experimentally, it was observed that this correlation varies from texture to texture. The linear regression model is employed to analyze this correlation and extract texture features that characterize the samples. Therefore, our method considers not only the frequency regions but also the correlation between these regions. In contrast, the pyramid-structured wavelet transform (PSWT) and the tree-structured wavelet transform (TSWT) do not consider the correlation between different frequency regions. Experiments show that our method significantly improves the texture classification rate in comparison with the multiresolution methods, including PSWT, TSWT, the Gabor transform, and some recently proposed methods derived from these. - Reference

Multiple Scattering Effects in Pulsed Radar Systems: An Intercomparison Study

In this paper, two different numerical methods capable of computing multiple scattering effects in pulsed-radar systems are compared. Both methods are based on the solution of the time-dependent vectorial form of the radiative transfer equation: one exploits the successive order of scattering approximation, the other a forward Monte Carlo technique.

Different benchmark results are presented (including layers of monodisperse spherical water and ice particles), which are of specific interest for W-band spaceborne cloud radars such as CloudSat’s or EarthCARE’s cloud profiling radars. Results demonstrate a good agreement between the two methods. The pros and cons of the two models are discussed, with a particular focus on the validity of the second order of scattering approximation.- Reference

Simulating Range Oversampled Doppler Radar Profiles of Inhomogeneous Targets

A new technique for generating range oversampled profiles of Doppler radar signals that have been backscattered by distributed targets is presented in this paper. The technique was developed for spaceborne cloud radars, but it can just as well be used for ground-based precipitation or wind-profiling radars. The technique is more versatile than the traditional inverse FFT technique and faster than the individual hydrometeor simulation (Monte Carlo) technique. Doppler radar signals from backscattering hydrometeors are essentially correlated stochastic variables. The technique uses an accurate description of covariances between voltages measured for different pulses and at different positions (range gates) along a profile. A matrix formalism is developed to subsequently transform uncorrelated Gaussian noise into correlated receiver voltages with the appropriate covariances. In particular, the new technique deals with target variability in a physically consistent manner, accounting for the effects of inhomogeneity both within the instantaneous field of view and between subsequent pulses. The new technique is showcased with examples of simulated 95-GHz Doppler radar observations by the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) space mission. - Reference

A Technique for the Automatic Detection of Insect Clutter in Cloud Radar Returns

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program operates 35-GHz millimeter-wavelength cloud radars (MMCRs) in several climatologically distinct regions. The MMCRs, which are centerpiece instruments for the observation of clouds and precipitation, provide continuous, vertically resolved information on all hydrometeors above the ARM Climate Research Facilities (ACRF). However, their ability to observe clouds in the lowest 2–3 km of the atmosphere is often obscured by the presence of strong echoes from insects, especially during the warm months at the continental midlatitude Southern Great Plains (SGP) ACRF. Here, a new automated technique for the detection and elimination of insect-contaminated echoes from the MMCR observations is presented. The technique is based on recorded MMCR Doppler spectra, a feature extractor that conditions insect spectral signatures, and the use of a neural network algorithm for the generation of an insect (clutter) mask. The technique exhibits significant skill in the identification of insect radar returns (more than 92% of insect-induced returns are identified) when the sole input to the classifier is the MMCR Doppler spectrum. The addition of circular polarization observations by the MMCR and ceilometer cloud-base measurements further improve the performance of the technique and form an even more reliable method for the removal of insect radar echoes at the ARM site. Recently, a 94-GHz Doppler polarimetric radar was installed next to the MMCR at the ACRF SGP site. Observations by both radars are used to evaluate the potential of the 94-GHz radar as being insect free and to show that dual wavelength radar reflectivity measurements can be used to identify insect radar returns. - Reference

Potential Role Of Dual- Polarization Radar In The Validation Of Satellite Precipitation Measurements: Rationale and Opportunities

Ground based dual-polarization radars provide physical insight into the development and interpretation of spaceborne precipitation measurements - Reference

The Detection of Buried Pipes From Time-of-Flight Radar Data

Ultrawideband radar is commonly used in the frequency range of 50–500 MHz to detect buried pipes at a depth of about 1–2 m depending on the soil characteristics. The typical feature used to locate the pipes is the hyperbolic pattern of the time of flight generated by a linear scan of the antenna above the surface. When the pipes are close together, the hyperbolas overlap, and a straightforward least squares fit is not possible. The Hough transform provides one possible solution. This paper extends the Hough transform by introducing a weighting factor depending on the differentials of the unknown parameters with respect to the experimental errors, namely, the probe position error and the time-of-flight error. This enables optimally placed sets of data pairs to be given greater weight than “ill-conditioned” sets, as for example when all data pairs lie near one end of the arc. The result is a decrease in the background amplitude with respect to the maximum of the peaks in the Hough accumulator space. It is shown that this improvement persists even when many arcs are present. A mathematical analysis with analytical results is given for the case of four unknowns: pipe radius $R$ , pipe center position ($Y$, $Z$), and soil propagation velocity $V$. The results are presented through simulations introducing controlled uncertainties in the probe position, the time of flight, and its bin size. The simulations demonstrate the correlations that occur between the radius, depth, and velocity for given experimental uncertainties. - Reference

Geometric Morphometrics for Biologists

Miriam Leah Zelditch, Donald L. Swiderski, H. David Sheets and William L. Fink, 2004: Geometric Morphometrics for Biologists. A Primer. Elsevier Inc. - 416 p.

ISBN: 978-0-12-778460-1

Description. This book is an introductory textbook for a course on geometric morphometrics, written for graduate students and upper division undergraduates, covering both theory of shape analysis and methods of multivariate analysis. It is designed for students with minimal math background; taking them from the process of data collection through basic and more advanced statistical analyses. Many examples are given, beginning with simple although realistic case-studies, through examples of complex analyses requiring several different kinds of methods. The book also includes URL's for free software and step-by-step instructions for using the software.

ScienceDirect - Elsevier B.V.