State Water Survey Research Articles

Illinois State Water Survey Bulletin 75: New Precipitation Frequency Study for Illinois

ABSTRACTStorm frequency estimates and their temporal distributions are important in determining estimates of runoff or peak flow rates in many engineering and hydrological problems. Illinois State Water Survey Bulletin 70 has been serving as the design rainfall standard in Illinois since its publication in 1989. Although Bulletin 70 represented the best available data at the time of its publication, the standards needed to be reevaluated and updated after more than three decades and with the growing evidence of the nonstationary nature of heavy precipitation. The trends in heavy precipitation in Illinois prompted the creation of a new frequency study named Bulletin 75, providing precipitation frequencies for event durations ranging from 5 min to 10 days and for recurrence intervals ranging from 2 months to 500 years. The results are presented for the same 10 geographic sections in Illinois as in Bulletin 70 to maintain the continuity of hydrologic studies and compatibility with regulations. The primary goal of this paper is to outline some of the key methodological issues and challenges, to compare the results with the previous sources, and to highlight the effects of the changing precipitation standards on the development of amendments to existing ordinances. Lake County in Illinois, as one of the most affected urban areas with the highest change in heavy precipitation, was selected to illustrate issues related to the application of modified precipitation standards.

Uncertain Waters: Participatory groundwater modelling in Chicago’s suburbs

Groundwater exists in underground aquifers and is largely hidden and intangible to water users. As such, groundwater models are one of the main vehicles through which groundwater is made legible. They are critical for water supply planning purposes. However, models are imperfect representations of limited data and contain much uncertainty, posing challenges for the water supply planning process. In this paper, we draw on a case from the Greater Chicago area to examine efforts by the authors and the Illinois State Water Survey to engage with local water managers to develop future water supply scenarios. Much of this area has been dependent upon the Cambrian-Ordovician Aquifer System for over 150 years. Over this period, water levels have declined by over 300 m and aquifers are expected to be unviable by 2030. Here we advance the growing field of participatory groundwater modelling (PGM) to identify forms of uncertainty and their influence on understandings of water supply and risk perceptions of depletion. Conceptually, we draw on the idea of models as world builders, where uncertainties are elucidated through knowledge production in the act of model building, while model development is simultaneously influenced by expectations, beliefs, and ambiguity surrounding those using the models. Through planning meetings and focus group discussions between groundwater modelers and water supply stakeholders, we identify four forms of interconnected uncertainty that hinder planning efforts: 1) hydrogeologic uncertainty, 2) modelling uncertainty; 3) water demand uncertainty; and 4) urban planning uncertainty. We describe our PGM efforts to reduce uncertainty and find stakeholder perceptions are as important as model uncertainties in water management decisions. Participatory modelling is effective in reducing and clarifying these four forms of uncertainty, particularly applied to short-term management decisions in a rapidly changing system. We conclude that future participatory modelling efforts need to focus on reducing communication barriers between scientists and local users.

Water Supply Planning Considering Uncertainties in Future Water Demand and Climate: A Case Study in an Illinois Watershed

AbstractEnsuring an adequate, reliable, clean, and affordable water supply for citizens and industries requires informed, long‐range water supply planning, which is critically important for water security. A balance between water supply and demand must be considered for a long‐term plan. However, water demand projections are often highly uncertain. Climate change could impact the hydrologic processes, and consequently, threaten water supply. Thus, understanding the uncertainties in future water demand and climate is critical for developing a sound water supply plan. In Illinois, regional water supply planning attempts to explore the impacts of future water demand and climate on water supply using scenario analyses and hydrologic modeling. This study is aimed at developing a water supply planning framework that considers both future water demand and climate change impacts. This framework is based on the Soil and Water Assessment Tool to simulate the watershed hydrology and conduct scenario analyses that consider the uncertainties in both future water demand and climate as well as their impacts on water supply. The framework was applied to water supply planning efforts in the Kankakee River watershed. The Kankakee River watershed model was calibrated and validated to observed streamflow records at four long‐term United States Geological Survey streamflow gages. Because of the many model parameters involved, the calibration process was automated and was followed by a manual refinement, resulting in good model performance. Long‐range water demand projections were prepared by the Illinois State Water Survey. Six future water demand scenarios were established based on a suite of assumptions. Climate scenarios were obtained from the Coupled Model Intercomparison Projection Phase 5 datasets. Three representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, are used in the study. The scenario simulation results demonstrated that climate change appears to have a greater impact on water availability in the study area than water demand. The framework developed in this study can also be used to explore the impacts of uncertainties of water demand and climate on water supply and can be extended to other regions and watersheds.

Polarimetric Radar Signatures of Dendritic Growth Zones within Colorado Winter Storms

AbstractX-band polarimetric radar observations of winter storms in northeastern Colorado on 20–21 February, 9 March, and 9 April 2013 are examined. These observations were taken by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU-CHILL) radar during the Front Range Orographic Storms (FROST) project. The polarimetric radar moments of reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP exhibited a range of signatures at different times near the −15°C temperature level favored for dendritic ice crystal growth. In general, KDP was enhanced in these regions with ZDR decreasing and ZH increasing toward the ground, suggestive of aggregation (or riming). The largest ZDR values (~3.5–5.5 dB) were observed during periods of significant low-level upslope flow. Convective features observed when the upslope flow was weaker had the highest KDP (>1.5° km−1) and ZH (>20 dBZ) values. Electromagnetic scattering calculations using the generalized multiparticle Mie method were used to determine whether these radar signatures were consistent with dendrites. Particle size distributions (PSDs) of dendrites were retrieved for a variety of cases using these scattering calculations and the radar observations. The PSDs derived using stratiform precipitation observations were found to be reasonably consistent with previous PSD observations. PSDs derived where riming may have occurred likely had errors and deviated significantly from these previous PSD observations. These results suggest that this polarimetric radar signature may therefore be useful in identifying regions of rapidly collecting dendrites, after considering the effects of riming on the radar variables.

Transformation of the CSU–CHILL Radar Facility to a Dual-Frequency, Dual-Polarization Doppler System

Abstract This paper describes the transformation of the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) National Radar Facility from a single-frequency (S band) dual-polarization Doppler weather radar system to a dual-frequency (S and X bands) dual-polarization Doppler system with coaxial beams. A brief history regarding the development of dual-wavelength radars is first presented. In the past, dual-wavelength measurements were used to detect hail using the dual-wavelength ratio defined as the ratio of intrinsic (or attenuation corrected) X-band reflectivity to the S-band reflectivity. Departures of this ratio from unity were taken to indicate the presence of hail, produced by Mie scattering at the shorter wavelength by hail. Most dual-wavelength radars were developed with attempts to match beams for S and X bands, which implies that the sample volumes for the two frequencies were essentially the same. The X-band channel of the CSU–CHILL radar takes a different approach, that of making use of the already existing dual-offset-fed antenna designed to give a 1° beamwidth at S band, resulting in an X-band beamwidth of approximately 0.3°, with very high gain. Thus, the X band provides about a factor of 3 more resolution than the S-band component while maintaining the same sensitivity as the S-band component. Examples of cold season and warm season data from the X-band and S-band radar components are presented, demonstrating the successful transformation of the CSU–CHILL radar into a unique multifrequency, multipolarization system. The new CSU–CHILL dual-wavelength, dual-polarization weather radar will serve as an important asset for the scientific community.

Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings

Abstract The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHV reductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing >55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.

Gaussian Model Adaptive Processing in Time Domain (GMAP-TD) for Weather Radars

Abstract The Gaussian model adaptive processing in the time domain (GMAP-TD) method for ground clutter suppression and signal spectral moment estimation for weather radars is presented. The technique transforms the clutter component of a weather radar return signal to noise. Additionally, an interpolation procedure has been developed to recover the portion of weather echoes that overlap clutter. It is shown that GMAP-TD improves the performance over the GMAP algorithm that operates in the frequency domain using both signal simulations and experimental observations. Furthermore, GMAP-TD can be directly extended for use with a staggered pulse repetition time (PRT) waveform. A detailed evaluation of GMAP-TD performance and comparison against the GMAP are done using simulated radar data and observations from the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar using uniform and staggered PRT waveform schemes.

Biophysical and Social Barriers Restrict Water Quality Improvements in the Mississippi River Basin

in the Mississippi River Basin Mark B. David,*,† Courtney G. Flint,‡ Gregory F. McIsaac,† Lowell E. Gentry,† Mallory K. Dolan,‡ and George F. Czapar †Department of Natural Resources and Environmental Sciences, University of Illinois , W503 Turner Hall, 1102 S. Goodwin Avenue, Urbana, Illinois 61801, United States ‡Department of Sociology, Social Work & Anthropology, Utah State University, 0730 Old Main Hill, Logan, Utah 84322-0730, United States Illinois State Water SurveyPrairie Research Institute, University of Illinois, 2204 Griffith Dr., Champaign, Illinois 61820-7495, United States

Wideband Waveform Design Principles for Solid-State Weather Radars

Abstract The use of solid-state transmitters is becoming increasingly viable for atmospheric radars and is a key part of the strategy to realize any dense network of low-powered radars. However, solid-state transmitters have low peak powers and this necessitates the use of pulse compression waveforms. In this paper frequency diversity in a wideband waveform design is proposed to mitigate the low sensitivity of solid-state transmitters. In addition, the waveforms mitigate the range-eclipsing problem associated with long pulse compression. An analysis of the performance of pulse compression using mismatched compression filters designed to minimize sidelobe levels is presented. The impact of the range sidelobe level on the retrieval of Doppler moments is discussed. Realistic simulations are performed based on both the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) and the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project I (IP1) radar data.

UWATER‐PA: Ubiquitous WebGIS Analysis Toolkit for Extensive Resources—Pumping Assessment

Introduction According to the National Research Council (2010), a significant challenge in the GISciences is the creation and development of tools that enable the results of scientific modeling to be easily understood. For science-informed decision making as well as for the purposes of informing and engaging ordinary citizens in discussions regarding geographical technologies, the National Research Council (2010) argues that it is indispensible to develop tools that can easily present scientific modeling results and translate scientific understanding into the process of decision making. Yang and Lin (2011) at the Illinois State Water Survey (ISWS) address this challenge in the context of assessing the effect of pumping on changes of groundwater levels (i.e., drawdown) of a confined aquifer by making freely available the GIS-based software uWATER-PA to calculate drawdown based on the Theis equation (Theis 1935). The model was developed using the Microsoft Visual Basic 2008 programming language and implemented as an extension (add-in) to ArcGIS Explorer Desktop (AGX), a free GIS by ESRI Inc. Compared to ESRI’s flagship product ArcGIS, AGX has a simplified user interface (UI) and reduced functionality. The uWATER-PA software is built on top of the uWATER framework previously developed by the ISWS (Yang and Lin 2010). The purpose of the uWATER framework is to extend AGX by enabling the execution of both spatial and attribute query functions, which are common in a more advanced GIS (e.g., ArcGIS),

Predicting the Seasonal Shift in Mosquito Populations Preceding the Onset of the West Nile Virus in Central Illinois

In the midwestern United States, the summertime rise in infection rate by the West Nile virus is associated with a seasonal shift in the abundance of two mosquito populations, Culex restuans and Culex pipiens. This seasonal shift usually precedes the time of the peak infection rate in mosquitoes by 2–3 weeks and generally occurs earlier in the summer with above normal temperatures and later in the summer with below-normal temperatures. Two empirical models were developed to predict this seasonal shift in mosquito species, or the “crossover,” and have been run operationally since 2004 by the Midwestern Regional Climate Center located at the Illinois State Water Survey. These models are based on daily temperature data and have been verified by use of a unique dataset of daily records of mosquito species abundance collected by the Illinois Natural History Survey. An unfortunate characteristic of the original temperature models was that the crossover date often was reached with little or no lead time. In 2009, the models were modified to incorporate National Weather Service (NWS) model output statistics (MOS) 10-day temperature forecasts. This paper evaluates the effectiveness of these models to predict the crossover date and thus the period of increased risk of West Nile virus in the Midwest. For the 8-yr period from 2002 to 2009, 6 yr had at least one model predicting the crossover within one week of the actual crossover date, and for 7 yr at least one of the model predictions was within 2 weeks of the actual crossover date. Incorporation of MOS temperature forecasts for a 10-day period, although not substantially changing the predicted crossover date, greatly improved the forecast lead time by about 9 days. From a disease management point of view, this improvement in advanced notice is significant. In 2009, there was an unprecedented early crossover date and a failed forecast. The poor forecast was likely caused by an unusually early summer prolonged and intense heat wave, followed immediately by a record cold July.

Design and Performance Characteristics of the New 8.5-m Dual-Offset Gregorian Antenna for the CSU–CHILL Radar

Abstract The Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) national weather radar facility has been operated by the Colorado State University under a cooperative agreement with the U.S. National Science Foundation from 1990 to the present. The radar is configured to measure the elements of the 3 × 3 polarimetric covariance matrix based on using a two-transmitter and two-receiver system in the horizontal–vertical polarization basis. This S-band Doppler, dual-polarized radar facility is used for observations of precipitation with the highest possible data quality. To achieve this, a new dual-offset 8.5-m Gregorian antenna was custom designed and built by VertexRSI (now General Dynamics SATCOM) in Kilgore, Texas, to replace the circa 1994 center-fed parabolic reflector antenna. Here, the design features used to achieve the stringent specifications in terms of the sidelobe envelope and off-axis cross-polar levels are described, and the way in which they were validated at the manufacturer’s long- and short-range pattern measurement facility. Measurements in several different storm types, including stratiform rain and an intense hailstorm, and ground clutter (from mountains) are used to illustrate the new antenna performance. The linear depolarization ratio (LDR) system limit is shown to be −40 dB or better, which should lead to more insights into the microphysics of convective precipitation at subfreezing temperatures (e.g., hail formation, improved hydrometeor-type classification), and in winter precipitation in general (e.g., aggregation processes, rimed versus unrimed particles). In the case of the intense hailstorm, it is shown that measurement artifacts resulting from strong cross-beam gradients of reflectivity, up to 40 dB km−1 at 40-km range, have been greatly reduced or eliminated. Previously noted measurement artifacts with the 1994 antenna at storm tops in intense convection have been eliminated with the dual-offset antenna. The ground (mountain) clutter example shows greatly reduced returns (in terms of near-zero mean Doppler velocity areas) because of rapid falloff in the sidelobe levels with increasing elevation angle. The greatly improved antenna performance as compared with the 1994 antenna are expected to result in corresponding data quality improvements leading to more accurate measurement of rain rate and hydrometeor classification.

Drought Indices Based on the Climate Forecast System Reanalysis and Ensemble NLDAS

Abstract Drought indices derived from the Climate Forecast System Reanalysis (CFSR) are compared with indices derived from the ensemble North American Land Data Assimilation System (NLDAS) and the North American Regional Reanalysis (NARR) over the United States. Uncertainties in soil moisture, runoff, and evapotranspiration (E) from three systems are assessed by comparing them with limited observations, including E from the AmeriFlux data, soil moisture from the Oklahoma Mesonet and the Illinois State Water Survey, and streamflow data from the U.S. Geological Survey (USGS). The CFSR has positive precipitation (P) biases over the western mountains, the Pacific Northwest, and the Ohio River valley in winter and spring. In summer, it has positive biases over the Southeast and large negative biases over the Great Plains. These errors limit the ability to use the standardized precipitation indices (SPIs) derived from the CFSR to measure the severity of meteorological droughts. To compare with the P analyses, the Heidke score for the 6-month SPI derived from the CFSR is on average about 0.5 for the three-category classification of drought, floods, and neutral months. The CFSR has positive E biases in spring because of positive biases in downward solar radiation and high potential evaporation. The negative E biases over the Great Plains in summer are due to less P and soil moisture in the root zone. The correlations of soil moisture percentile between the CFSR and the ensemble NLDAS are regionally dependent. The correlations are higher over the area east of 100°W and the West Coast. There is less agreement between them over the western interior region.

S-Band Dual-Polarization Radar Observations of Winter Storms

AbstractThis study is based on analyses of dual-polarization radar observations made by the 11-cm-wavelength Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) system during four significant winter storms in northeastern Colorado. It was found that values of specific differential phase KDP often reached local maxima of ∼0.15°–0.4° km−1 in an elevated layer near the −15°C environmental temperature isotherm. The passage of these elevated positive KDP areas is shown to be linked to increased surface precipitation rates. Calculations using a microwave scattering model indicate that populations of highly oblate ice particles with moderate bulk densities and diameters in the ∼0.8–1.2-mm range can generate KDP (and differential reflectivity ZDR) values that are consistent with the radar observations. The persistent correlation between the enhanced KDP level and the −15°C temperature regime suggests that rapidly growing dendrites likely played a significant role in the production of the observed KDP patterns. The detection of organized regions of S-band KDP values greater than ∼0.1°–0.2° km−1 in winter storms may therefore be useful in identifying regions of active dendritic particle growth, as a precursor to aggregate snowfall.

A New Dual-Polarization Radar Rainfall Algorithm: Application in Colorado Precipitation Events

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 (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) have advantages over traditional Z–R 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 Zh, Zdr, and Kdp. 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.

Watershed Modeling to Assessing Impacts of Potential Climate Change on Water Supply Availability

Climate change could have impacts on hydrologic systems threatening, availability of water supply resources. In Illinois, regional water supply planning efforts are attempting to better understand potential impacts on low flow and surface water availability through analysis of hydrologic sensitivity to a range of climate scenarios. This paper explores the development, calibration and validation of Fox River watershed model using the soil and water assessment tool (SWAT) and the model’s application to assess impacts of potential climate change. The watershed model is calibrated and validated using daily flow records at three gauging stations. Automatic model calibration followed by manual refinement of parameter values was performed. Calibration results were generally good for monthly and annual time step but only satisfactory for daily simulations. Based on simulations of global climate models produced for IPCC fourth assessment report, climate scenarios were prepared by the Illinois State Water Survey for water supply planning initiatives in north-east and east-central Illinois. These scenarios showed ranges of temperature change between 0°C to +3.3°C and annual precipitation changes between −127 to +127 mm in the next 50 years, excluding the 5% extreme ends of those climate model simulations considered. Changes in climate were reflected using adjustments to the historical record, instead of using direct outputs from individual climate models. The watershed model was used to assess the impact of potential climate change. Application results indicate that annual precipitation change of 127 mm on average increases annual water yield and 7-day low flows by 28% and 19%, respectively. In contrast, a temperature change of +3.3°C results in average reductions of annual water yield by 13% and 7-day low flows by 10%. Seasonal effects were investigated through evaluation of changes in average monthly flows. Increasing precipitation resulted in significant changes in streamflows in late summer and fall months where as increasing temperature greatly affects winter flows due to snowmelt. The key implication is that climate change-induced variability of streamflows could have major impacts on water supply availability in the Fox River watershed and in particular, increased periods of drought could result in deficit of supplies during seasons of peak water use. It must be noted that this analysis does not examine the potential impacts of population growth and water use on water supply availability, which are also expected to have substantial influences in the region.

Polarimetric Spectral Filter for Adaptive Clutter and Noise Suppression

Abstract In this paper, spectral decompositions of differential reflectivity, differential phase, and copolar correlation coefficient are used to discriminate between weather and nonweather signals in the spectral domain. This approach gives a greater flexibility for discrimination between different types of scattering sources present in a radar observation volume. A spectral filter, which removes nonweather signals, is defined based on this method. The performance of this filter is demonstrated on the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) observations. It is shown that the resulting filter parameters are adaptively defined for each range sample and do not require an assumption on spectral properties of ground clutter.

Orthogonal Channel Coding for Simultaneous Co- and Cross-Polarization Measurements

Abstract Dual-polarization weather radars typically measure the radar reflectivity at more than one polarization state for transmission and reception. Historically, dual-polarization radars have been operated at copolar and cross-polar states defined with respect to the transmit polarization states. Recently, based on the improved understanding of the propagation properties of electromagnetic waves in precipitation media, the simultaneous transmit and receive (STAR) mode has become common to simplify the hardware. In the STAR mode of operation, horizontal and vertical polarization states are transmitted simultaneously and samples of both horizontal and vertical copolar returns are obtained. A drawback of the current implementation of STAR mode is its inability to measure parameters obtained from cross-polar signals such as linear depolarization ratio (LDR). In this paper, a technique to obtain cross-polar signals with STAR mode waveform is presented. In this technique, the horizontally and vertically polarized transmit waveforms are coded with orthogonal phase sequences. The performance of the phase-coded waveform is determined by the properties of the phase codes. This orthogonal phase coding technique is implemented in the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar. This paper outlines the methodology and presents the performance of the cross-polar and copolar parameter estimation based on the simulation as well as data collected from the CSU–CHILL radar.

Clutter Suppression for Staggered PRT Waveforms

Abstract 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.

Retrieval of Reflectivity in a Networked Radar Environment

Abstract A system for reflectivity and attenuation retrieval for rain medium in a networked radar environment is described. Electromagnetic waves backscattered from a common volume in networked radar systems are attenuated differently along the different paths. A solution for the specific attenuation distribution is proposed by solving the integral equation for reflectivity and attenuation. The set of governing integral equations describing the backscatter and propagation of common resolution volume are solved simultaneously with constraints on total path attenuation. The proposed algorithm is evaluated based on simulated X-band radar observations synthesized from S-band measurements collected by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar. Retrieved reflectivity and specific attenuation using the proposed method show good agreement with simulated reflectivity and specific attenuation. Preliminary demonstration of the network-based retrieval using data from the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) IP-1 radar network are also presented.