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Steven A. Rutledge and V. Chandrasekar

Abstract

Great strides have been made over the past decades in educating radar meteorologists. These advances appear to be loosely associated with the arrival of new hardware in the field, for example, Doppler radars followed by polarimetric radars. Many radar meteorologists received a substantial portion of their early training through participation in field programs utilizing this new hardware. In this study, a brief look at the evolution of radar education will first be offered, followed by an assessment of the current state of this field. Finally, a view of the future will be offered. Future educational thrusts in radar meteorology will take full advantage of Internet technology, allowing radar systems to be brought into remote classrooms in a “virtual” sense. This study is purposely limited to meteorological radar and is focused on graduate-level education.

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A. Mudukutore, V. Chandrasekar, and E. A. Mueller

Abstract

The measurement of the differential propagation phase and copolar correlation coefficient are affected by the differential phase pattern of the antenna system when operating in an alternate horizontal and vertical transmitting scheme. Direct phase pattern measurements of a large dish such as that of the CSU CHILL is difficult because of the need to obtain phase reference. A simple technique is devised to measure the differential phase pattern of the CSU CHILL antenna system. The measurements are subsequently used in the evaluation of the antenna imposed limit on the copolar correlation coefficient.

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Vinodkumar, A. Chandrasekar, K. Alapaty, and Dev Niyogi

Abstract

This study investigates the impact of the Flux-Adjusting Surface Data Assimilation System (FASDAS) and the four-dimensional data assimilation (FDDA) using analysis nudging on the simulation of a monsoon depression that formed over India during the 1999 Bay of Bengal Monsoon Experiment (BOBMEX) field campaign. FASDAS allows for the indirect assimilation/adjustment of soil moisture and soil temperature together with continuous direct surface data assimilation of surface temperature and surface humidity. Two additional numerical experiments [control (CTRL) and FDDA] were conducted to assess the relative improvements to the simulation by FASDAS. To improve the initial analysis for the FDDA and the surface data assimilation (SDA) runs, the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) simulation utilized the humidity and temperature profiles from the NOAA Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS), surface winds from the Quick Scatterometer (QuikSCAT), and the conventional meteorological upper-air (radiosonde/rawinsonde, pilot balloon) and surface data. The results from the three simulations are compared with each other as well as with NCEP–NCAR reanalysis, the Tropical Rainfall Measuring Mission (TRMM), and the special buoy, ship, and radiosonde observations available during BOBMEX. As compared with the CTRL, the FASDAS and the FDDA runs resulted in (i) a relatively better-developed cyclonic circulation and (ii) a larger spatial area as well as increased rainfall amounts over the coastal regions after landfall. The FASDAS run showed a consistently improved model simulation performance in terms of reduced rms errors of surface humidity and surface temperature as compared with the CTRL and the FDDA runs.

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V. Chandrasekar, Yoong-Goog Cho, D. Brunkow, and A. Jayasumana

Abstract

The Virtual CHILL (VCHILL) system makes it possible to transfer the educational and research experience of the Colorado State University dual polarization radar to remote locations over the Internet. The VCHILL operation includes remote control of radar and display of radar images, as well as the ability to locally process high-bandwidth radar data transferred over data networks. The low-bandwidth VCHILL operation allows the distant users to access the archived and real-time data estimated at the radar site and simultaneously display them on their local systems. A parallel receiver was developed exclusively for the high-bandwidth VCHILL. End-system architectures were designed to accommodate the demands of the high-bandwidth VCHILL operations in real time. A graphic user interface was also developed with the objective of easy installation and usage at various end-user institutions. The VCHILL not only expands the education experience provided by the radar system, but also stimulates the development of innovative research applications for atmospheric remote sensing. The VCHILL is being used by several universities for research and education.

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S. Lim, V. Chandrasekar, P. Lee, and A. P. Jayasumana

Abstract

Monitoring of precipitation using higher-frequency radar systems such as X band is becoming popular. At X-band frequency, weather radar signals are attenuated along their paths due to precipitation. A network-based reflectivity retrieval technique has been developed for the Collaborative Adaptive Sensing of the Atmosphere (CASA) system, which is a radar network that can observe a weather event simultaneously by multiple radars. This paper describes the design and implementation of an architectural framework for real-time processing of the network-based attenuation correction system. The benchmarks presented here show that the system accomplishes networked attenuation correction within a few seconds, making it well suited for the CASA system. This paper presents the performance of the network-based attenuation correction system in terms of the metrics of attenuation correction as well as computational performance using CASA Integrated Project 1 (IP1) data during 2007–09 field experiments. The results show that the network-based attenuation correction algorithm works robustly in real time while retrieving attenuation-corrected reflectivity.

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Gianfranco Scarchilli, Eugenio Goroucci, V. Chandrasekar, and Thomas A. Seliga

Abstract

The accuracy of radar measurements and their derived parameters, such as rainfall rate, are compromised by errors caused by propagation effects at C-band frequencies. The radar measurements of reflectivity factor Z and differential reflectivity Z DR are affected by the absolute and differential attenuation through the rain medium. Another useful radar-derived parameter, differential propagation phase shift ΦDP, is contaminated by the differential phase on backscatter δ, which attains significant values in rainfall at C-band frequencies. In this paper we present a technique to correct these propagation and backscatter effects by application of an algorithm that corrects first Z and Z DR, using relationships between the specific and differential attenuations versus phase shift, which is followed by estimation of the differential backscatter phase shift parameter δ from the corrected Z DR. Simulation results are presented to demonstrate the effectiveness of this correction procedure for two cases: (a) uniform rainfall along the path, and (b) rainfall varying with range. We also present estimates of accuracy in the measurement of radar-derived rainfall rates made after applying this correction procedure.

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V. Chandrasekar, William A. Cooper, and V. N. Bringi

Abstract

Axis ratios were determined for about 3500 raindrop images recorded in summertime rainshowers by an instrumented aircraft. These ratios were used to determine the mean axis ratios and oscillation amplitudes of raindrops. A filtering algorithm using Fourier descriptors was applied to the raindrop images to reduce the quantization noise and the systematic errors, and simulations were used to estimate the standard errors of the measurement procedure. Drops with diameters <4 mm were observed to be slightly more spherical than would be expected for drops in equilibrium. Oscillation amplitudes were found to be typically ±10% in axis ratio for light to moderate rainfall rates, and such oscillations can account for the departures from equilibrium values. The effects of these axis ratios and oscillations on the differential radar reflectivity of rain are calculated and discussed.

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L. Liu, V. N. Bringi, V. Chandrasekar, E. A. Mueller, and A. Mudukutore

Abstract

Recent research has suggested that the copolar correlation coefficient termed ρhν(0) can be used to identity large hail and improve polarization estimates of rainfall. The typical measured values of ρhν(0) at S band vary approximately between 0.8 and 1.0. For applications to hail identification, the required accuracy should be within ±0.01, while for rainfall improvement a higher accuracy is necessary, for example, within ±0.001. The statistics of the estimator of ρhν(0) using the Gaussian spectrum approximation from both an analytical approach and using simulations are discussed. The standard deviation and bias in ρ^hν(0) are computed as a function of number of samples. Doppler spectral width, and mean value of ρhν(0). The effect of finite signal-to-noise ratio and phase noise are also studied using simulations. Several other estimators of ρhν(0) are evaluated, Time series data collected with the Colorado State University–University of Chicago and Illinois State Water Survey (CSU–CHILL) radar are analyzed and compared with the simulations. Antenna pattern effects as they affect the accuracy of ρ^hν(0) are also discussed.

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Annakaisa von Lerber, Dmitri Moisseev, David A. Marks, Walter Petersen, Ari-Matti Harri, and V. Chandrasekar

Abstract

Currently, there are several spaceborne microwave instruments suitable for the detection and quantitative estimation of snowfall. To test and improve retrieval snowfall algorithms, ground validation datasets that combine detailed characterization of snowfall microphysics and spatial precipitation measurements are required. To this endpoint, measurements of snow microphysics are combined with large-scale weather radar observations to generate such a dataset. The quantitative snowfall estimates are computed by applying event-specific relations between the equivalent reflectivity factor and snowfall rate to weather radar observations. The relations are derived using retrieved ice particle microphysical properties from observations that were carried out at the University of Helsinki research station in Hyytiälä, Finland, which is about 64 km east of the radar. For each event, the uncertainties of the estimate are also determined. The feasibility of using this type of data to validate spaceborne snowfall measurements and algorithms is demonstrated with the NASA GPM Microwave Imager (GMI) snowfall product. The detection skill and retrieved surface snowfall precipitation of the GPROF detection algorithm, versions V04A and V05A, are assessed over southern Finland. On the basis of the 26 studied overpasses, probability of detection (POD) is 0.90 for version V04A and 0.84 for version V05A, and corresponding false-alarm rates are 0.09 and 0.10, respectively. A clear dependence of detection skill on cloud echo top height is shown: POD increased from 0.8 to 0.99 (V04A) and from 0.61 to 0.94 (V05A) as the cloud echo top altitude increased from 2 to 5 km. Both versions underestimate the snowfall rate by factors of 6 (V04A) and 3 (V05A).

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R. Cifelli, V. Chandrasekar, S. Lim, P. C. Kennedy, Y. Wang, and S. A. Rutledge

Abstract

The efficacy of dual-polarization radar for quantitative precipitation estimation (QPE) has been demonstrated in a number of previous studies. Specifically, rainfall retrievals using combinations of reflectivity (Z h), differential reflectivity (Z dr), and specific differential phase (K dp) have advantages over traditional ZR methods because more information about the drop size distribution (DSD) and hydrometeor type are available. In addition, dual-polarization-based rain-rate estimators can better account for the presence of ice in the sampling volume.

An important issue in dual-polarization rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), an optimization algorithm has been developed and used for a number of years to estimate rainfall based on thresholds of Z h, Z dr, and K dp. Although the algorithm has demonstrated robust performance in both tropical and midlatitude environments, results have shown that the retrieval is sensitive to the selection of the fixed thresholds.

In this study, a new rainfall algorithm is developed using hydrometeor identification (HID) to guide the choice of the particular rainfall estimation algorithm. A separate HID algorithm has been developed primarily to guide the rainfall application with the hydrometeor classes, namely, all rain, mixed precipitation, and all ice.

Both the data collected from the S-band Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar and a network of rain gauges are used to evaluate the performance of the new algorithm in mixed rain and hail in Colorado. The evaluation is also performed using an algorithm similar to the one developed for the Joint Polarization Experiment (JPOLE). Results show that the new CSU HID-based algorithm provides good performance for the Colorado case studies presented here.

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