Frequency diversity wideband digital receiver and signal processor for solid-state dual-polarimetric weather radars

2012 Summer.Includes bibliographical references.The recent spate in the use of solid-state transmitters for weather radar systems has unexceptionably revolutionized the research in meteorology. The solid-state transmitters allow transmission of low peak powers without losing the radar range resolution by allowing the use of pulse compression waveforms. In this research, a novel frequency-diversity wideband waveform is proposed and realized to extenuate the low sensitivity of solid-state radars and mitigate the blind range problem tied with the longer pulse compression waveforms. The latest developments in the computing landscape have permitted the design of wideband digital receivers which can process this novel waveform on Field Programmable Gate Array (FPGA) chips. In terms of signal processing, wideband systems are generally characterized by the fact that the bandwidth of the signal of interest is comparable to the sampled bandwidth; that is, a band of frequencies must be selected and filtered out from a comparable spectral window in which the signal might occur. The development of such a wideband digital receiver opens a window for exciting research opportunities for improved estimation of precipitation measurements for higher frequency systems such as X, Ku and Ka bands, satellite-borne radars and other solid-state ground-based radars. This research describes various unique challenges associated with the design of a multi-channel wideband receiver. The receiver consists of twelve channels which simultaneously downconvert and filter the digitized intermediate-frequency (IF) signal for radar data processing. The product processing for the multi-channel digital receiver mandates a software and network architecture which provides for generating and archiving a single meteorological product profile culled from multi-pulse profiles at an increased data date. The multi-channel digital receiver also continuously samples the transmit pulse for calibration of radar receiver gain and transmit power. The multi-channel digital receiver has been successfully deployed as a key component in the recently developed National Aeronautical and Space Administration (NASA) Global Precipitation Measurement (GPM) Dual-Frequency Dual-Polarization Doppler Radar (D3R). The D3R is the principal ground validation instrument for the precipitation measurements of the Dual Precipitation Radar (DPR) onboard the GPM Core Observatory satellite scheduled for launch in 2014. The D3R system employs two broadly separated frequencies at Ku- and Ka-bands that together make measurements for precipitation types which need higher sensitivity such as light rain, drizzle and snow. This research describes unique design space to configure the digital receiver for D3R at several processing levels. At length, this research presents analysis and results obtained by employing the multi-carrier waveforms for D3R during the 2012 GPM Cold-Season Precipitation Experiment (GCPEx) campaign in Canada

Electronic scan weather radar: scan strategy and signal processing for volume targets

2013 Fall.Includes bibliographical references.Following the success of the WSR-88D network, considerable effort has been directed toward searching for options for the next generation of weather radar technology. With its superior capability for rapidly scanning the atmosphere, electronically scanned phased array radar (PAR) is a potential candidate. A network of such radars has been recommended for consideration by the National Academies Committee on Weather Radar Technology beyond NEXRAD. While conventional weather radar uses a rotating parabolic antenna to form and direct the beam, a phased array radar superimposes outputs from an array of many similar radiating elements to yield a beam that is scanned electronically. An adaptive scan strategy and advanced signal designs and processing concepts are developed in this work to use PAR effectively for weather observation. An adaptive scan strategy for weather targets is developed based on the space-time variability of the storm under observation. Quickly evolving regions are scanned more often and spatial sampling resolution is matched to spatial scale. A model that includes the interaction between space and time is used to extract spatial and temporal scales of the medium and to define scanning regions. The temporal scale constrains the radar revisit time while the measurement accuracy controls the dwell time. These conditions are employed in a task scheduler that works on a ray-by-ray basis and is designed to balance task priority and radar resources. The scheduler algorithm also includes an optimization procedure for minimizing radar scan time. In this research, a signal model for polarimetric phased array weather radar (PAWR) is presented and analyzed. The electronic scan mechanism creates a complex coupling of horizontal and vertical polarizations that produce the bias in the polarimetric variables retrieval. Methods for bias correction for simultaneous and alternating transmission modes are proposed. It is shown that the bias can be effectively removed; however, data quality degradation occurs at far off boresight directions. The effective range for the bias correction methods is suggested by using radar simulation. The pulsing scheme used in PAWR requires a new ground clutter filtering method. The filter is designed to work with a signal covariance matrix in the time domain. The matrix size is set to match the data block size. The filter's design helps overcome limitations of spectral filtering methods and make efficient use of reducing ground clutter width in PAWR. Therefore, it works on modes with few samples. Additionally, the filter can be directly extended for staggered PRT waveforms. Filter implementation for polarimetric retrieval is also successfully developed and tested for simultaneous and alternating staggered PRT. The performance of these methods is discussed in detail. It is important to achieve high sensitivity for PAWR. The use of low-power solid state transmitters to keep costs down requires pulse compression technique. Wide-band pulse compression filters will partly reduce the system sensitivity performance. A system for sensitivity enhancement (SES) for pulse compression weather radar is developed to mitigate this issue. SES uses a dual-waveform transmission scheme and an adaptive pulse compression filter that is based on the self-consistency between signals of the two waveforms. Using SES, the system sensitivity can be improved by 8 to 10 dB

X-band synthetic aperture radar methods

Spaceborne Synthetic Aperture Radars (SARs), operating at L-band and above, offer microwave observations of the Earth at very high spatial resolution in almost all-weather conditions. Nevertheless, precipitating clouds can significantly affect the signal backscattered from the ground surface in both amplitude and phase, especially at X band and beyond. This evidence has been assessed by numerous recent efforts analyzing data collected by COSMO-SkyMed (CSK) and TerraSAR-X (TSX) missions at X band. This sensitivity can be exploited to detect and quantify precipitations from SARs at the spatial resolution of a few hundred meters, a very appealing feature considering the current resolution of precipitation products from space. Forward models of SAR response in the presence of precipitation have been developed for analyzing SAR signature sensitivity and developing rainfall retrieval algorithms. Precipitation retrieval algorithms from SARs have also been proposed on a semi-empirical basis. This chapter will review experimental evidences, modelling approaches, retrieval methods and recent applications of X-band SAR data to rainfall estimation

A polarimetric radar operator to evaluate precipitation from the COSMO atmospheric model

Weather radars provide real-time measurements of precipitation at a high temporal and spatial resolution and over a large domain. A drawback, however, it that these measurements are indirect and require careful interpretation to yield relevant information about the mechanisms of precipitation. Radar observations are an invaluable asset for the numerical forecast of precipitation, both for data assimilation, parametrization of subscale phenomena and model verification. This thesis aims at investigating new uses for polarimetric radar data in numerical weather prediction. The first part of this work is devoted to the design of an algorithm able to automatically detect the location and extent of the melting layer of precipitation , an important feature of stratiform precipitation, from vertical radar scans. This algorithm is then used to provide a detailed characterization of the melting layer, in several climatological regions, providing thus relevant information for the parameterization of melting processes and the evaluation of simulated freezing level heights. The second part of this work uses a multi-scale approach based on the multifractal framework to evaluate precipitation fields simulated by the COSMO weather model with radar observations. A climatological analysis is first conducted to relate multifractal parameters to physical descriptors of precipitation. A short-term analysis, that focuses on three precipitation events over Switzerland, is then performed. The results indicate that the COSMO simulations exhibit spatial scaling breaks that are not present in the radar data. It is also shown that a more advanced microphysics parameterization generates larger extreme values, and more discontinuous precipitation fields, which agree better with radar observations. The last part of this thesis describes a new forward polarimetric radar operator, able to simulate realistic radar variables from outputs of the COSMO model, taking into account most physical aspects of beam propagation and scattering. An efficient numerical scheme is proposed to estimate the full Doppler spectrum, a type of measurement often performed by research radars, which provides rich information about the particle velocities and turbulence. The operator is evaluated with large datasets from various ground and spaceborne radars. This evaluation shows that the operator is able to simulate accurate Doppler variables and realistic distributions of polarimetric variables in the liquid phase. In the solid phase, the simulated reflectivities agree relatively well with radar observations, but the polarimetric variables tend to be underestimated. A detailed sensitivity analysis of the radar operator reveals that, in the liquid phase, the simulated radar variables depend very much on the hypothesis about drop geometry and drop size distributions. In the solid phase, the potential of more advanced scattering techniques is investigated, revealing that these methods could help to resolve the strong underestimation of polarimetric variables in snow and graupel

Atmospheric Instrument Systems and Technology in the Goddard Earth Sciences Division

Studies of the Earths atmosphere require a comprehensive set of observations that rely on instruments flown on spacecraft, aircraft, and balloons as well as those deployed on the surface. Within NASAs Goddard Space Flight Center (GSFC) Earth Sciences Division-Atmospheres, laboratories and offices maintain an active program of instrument system development and observational studies that provide: 1) information leading to a basic understanding of atmospheric processes and their relationships with the Earths climate system, 2) prototypes for future flight instruments, 3) instruments to serve as calibration references for satellite missions, and 4) instruments for future field validation campaigns that support ongoing space missions. Our scientists participate in all aspects of instrument activity, including component and system design, calibration techniques, retrieval algorithm development, and data processing systems. The Atmospheres Program has well-equipped labs and test equipment to support the development and testing of instrument systems, such as a radiometric calibration and development facility to support the calibration of ultraviolet and visible (UV/VIS), space-borne solar backscatter instruments. This document summarizes the features and characteristics of 46 instrument systems that currently exist or are under development. The report is organized according to active, passive, or in situ remote sensing across the electromagnetic spectrum. Most of the systems are considered operational in that they have demonstrated performance in the field and are capable of being deployed on relatively short notice. Other systems are under study or of low technical readiness level (TRL). The systems described herein are designed mainly for surface or airborne platforms. However, two Cubesat systems also have been developed through collaborative efforts. The Solar Disk Sextant (SDS) is the single balloon-borne instrument. The lidar systems described herein are designed to retrieve clouds, aerosols, methane, water vapor pressure, temperature, and winds. Most of the lasers operate at some wavelength combination of 355, 532, and 1064 nm. The various systems provide high sensitivity measurements based on returns from backscatter or Raman scattering including intensity and polarization. Measurements of the frequency (Doppler) shift of light scattered from various atmospheric constitutes can also be made. Microwave sensors consist of both active (radar) and passive (radiometer) systems. These systems are important for studying processes involving water in various forms. The dielectric properties of water affect microwave brightness temperatures, which are used to retrieve atmospheric parameters such as rainfall rate and other key elements of the hydrological cycle. Atmosphere radar systems operate in the range from 9.6 GHz to 94 GHz and have measurement accuracies from -5 to 1 dBZ; radiometers operate in the 50 GHz to 874 GHz range with accuracies from 0.5 to 1 degree K; conical and cross-track scan modes are used. Our passive optical sensors, consisting of radiometers and spectrometers, collectively operate from the UV into the infrared. These systems measure energy fluxes and atmospheric parameters such as trace gases, aerosols, cloud properties, or altitude profiles of various species. Imager spatial resolution varies from 37 m to 400 m depending on altitude; spectral resolution is as small as 0.5 nm. Many of the airborne systems have been developed to fly on multiple aircraft

Investigation of Advanced Radar Techniques for Atmospheric Hazard Detection with Airborne Weather Radar

In 2013 ProSensing Inc. conducted a study to investigate the hazard detection potential of aircraft weather radars with new measurement capabilities, such as multi-frequency, polarimetric and radiometric modes. Various radar designs and features were evaluated for sensitivity, measurement range and for detecting and quantifying atmospheric hazards in wide range of weather conditions. Projected size, weight, power consumption and cost of the various designs were also considered. Various cloud and precipitation conditions were modeled and used to conduct an analytic evaluation of the design options. This report provides an overview of the study and summarizes the conclusions and recommendations

Characterization of snowfall using ground-based passive and active remote sensors.

Snowfall is a key quantity in the global hydrological cycle and has an impact on the global energy budget as well. In sub-polar and polar latitudes, snowfall is the predominant type of precipitation and rainfall is often initiated via the ice phase. Currently, the spatial distribution of snowfall is poorly captured by numerical weather prediction and climate models. In order to evaluate the models and to improve our understanding of snowfall microphysics, global observations of snowfall are needed. This can only be obtained by space-borne active and passive remote sensors. In order to be able to penetrate even thick snow clouds, sensors operating in the microwave frequency region are favoured. The challenge for snowfall retrieval development lies first in the complexity of snowfall microphysics and its interactions with liquid cloud water. Secondly, comprehensive knowledge is needed about the interaction of electromagnetic radiation with snowfall in order to finally relate the radiative signatures to physical quantities. A general advantage of ground-based observations is that simultaneous measurements of in-situ and remote sensing instruments can be obtained. Such a six-month dataset was collected within this thesis at an alpine site. The instrumentation included passive microwave radiometers that covered the frequency range from 22 up to \unit[150]{GHz} as well as two radar systems operating at 24.1 and 35.5 GHz. These data were complemented by optical disdrometer, ceilometer and various standard meteorological measurements. State-of-the-art single scattering databases for pristine ice crystals and complex snow aggregates were used within this thesis to investigate the sensitivity of ground--based passive and active remote sensors to various snowfall parameters such as vertical snow and liquid water distribution, snow particle habit, snow size distribution and ground surface properties. The comparison of simulations with measurements within a distinct case study revealed that snow particle scattering can be measured with ground--based passive microwave sensors at frequencies higher than 90 GHz. Sensitivity experiments further revealed that ground-based sensors have clear advantages over nadir measuring instruments due to a stronger snow scattering signal and lower sensitivity to variable ground surface emissivity. However, passive sensors were also found to be highly sensitive to liquid cloud water that was frequently observed during the entire campaign. The simulations indicate that the uncertainties of sizes distribution and snow particle habit are not distinguishable with a passive-only approach. In addition to passive microwave observations, data from a low-end radar system that is commonly used for rainfall were investigated for its capabilities to observe snowfall. For this, a snowfall specific data processing algorithm was developed and the re-processed data were compared to collocated measurements of a high-end cloud radar. If the focus can be narrowed down to medium and strong snowfall within the lowest 2-3 km height, the reflectivity and fall velocity measurements of the low-end system agree well with the cloud radar. The cloud radar dataset was used to estimate the uncertainty of retrieved snowfall rate and snow accumulation of the low-end system. Besides the intrinsic uncertainties of single-frequency radar retrievals the estimates of total snow accumulation by the low-end system lay within 7% compared to the cloud radar estimates. In a more general approach, the potential of multi-frequency radar systems for derivation of snow size distribution parameters and particle habit were investigated within a theoretical simulation study. Various single-scattering databases were combined to test the validity of dual-frequency approaches when applied to non-spheroid particle habits. It was found that the dual-frequency technique is dependent on particle habit. It could be shown that a rough distinction of snow particle habits can be achieved by a combination of three frequencies. The method was additionally tested with respect to signal attenuation and maximum particle size. The results obtained by observations and simulations within this thesis strongly suggest the further development of simultaneous ground-based in-situ and remote sensing observations of snowfall. Extending the sensitivity studies of this study will help to define the most suitable set of sensors for future studies. A combination of these measurements with a further development of single-scattering databases will potentially help to improve our understanding of snowfall microphysics

Use of Dual Polarization Radar in Validation of Satellite Precipitation Measurements: Rationale and Opportunities

Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed