Browsing by Author "Mielke, Paul W., committee member"
Now showing 1 - 16 of 16
Results Per Page
Sort Options
Item Open Access Attenuation correction of X-band polarimetric Doppler weather radar signals: application to systems with high spatio-temporal resolution(Colorado State University. Libraries, 2015) Gálvez, Miguel Bustamante, author; Bringi, V. N., advisor; Colom-Ustariz, Jose G., advisor; Jayasumana, Anura, committee member; Pezeshki, Ali, committee member; Mielke, Paul W., committee memberIn the last decade the atmospheric science community has seen widespread and successful application of X-band dual-polarization weather radars for measuring precipitation in the lowest 2 km of the troposphere. These X-band radars have the advantage of a smaller footprint, lower cost, and improved detection of hydrometeors due to increased range resolution. In recent years, the hydrology community began incorporating these radars in novel applications to study the spatio-temporal variability of rainfall from precipitation measurements near the ground, over watersheds of interest. The University of Iowa mobile XPOL radar system is one of the first to be used as an X-band polarimetric radar network dedicated to hydrology studies. During the spring of 2013, the Iowa XPOL radars participated in NASA Global Precipitation Measurement's (GPM) first field campaign focused solely on hydrology studies, called the Iowa Flood Studies (IFloodS). Weather radars operating in the 3.2 cm (X-band) regime can suffer from severe attenuation, particularly in heavy convective storms. This has led to the development of sophisticated algorithms for X-band radars to correct the meteorological observables for attenuation. This is especially important for higher range resolution hydrology-specific X-band weather radars, where the attenuation correction aspect remains relatively unexamined. This research studies the problem of correcting for precipitation-induced attenuation in X-band polarimetric weather radars with high spatio-temporal resolution for hydrological applications. We also examine the variability in scattering simulations obtained from the drop spectra measured by two dimensional video disdrometers (2DVD) located in different climatic and geographical locations. The 2DVD simulations provide a ground truth for various relations (e.g., AH-KDP and AH-ADP) applied to our algorithms for estimating attenuation, and ultimately correcting for it to provide improved rain rates and hydrometeor identification. We developed a modified ZPHI attenuation correction algorithm, with a differential phase constraint, and tuned it for the high resolution IFloodS data obtained by the Iowa XPOL radars. Although this algorithm has good performance in pure rain events, it is difficult to fully correct for attenuation and differential attenuation near the melting layer where a mixed phase of rain and melting snow or graupel exists. To identify these regions, we propose an improved iterative FIR range filtering technique, as first presented by Hubbert and Bringi (1995), to better estimate the differential backscatter phase, δ, due to Mie scattering at X-band from mixed phase precipitation. In addition, we investigate dual-wavelength algorithms to directly estimate the α and β coefficients, of the AH = αKDP and ADP = βKDP relations, to obtain the path integrated attenuation due to rain and wet ice or snow in the region near the melting layer. We use data from the dual-wavelength, dual-polarization CSU-CHILL S-/X-band Doppler weather radar for analyzing the coefficients and compare their variability as a function of height, where the hydrometeors are expected to go through a microphysical transformation as they fall, starting as snow or graupel/hail then melting into rain or a rain-hail mixture. The S-band signal is un-attenuated and so forms a reference for estimating the X-band attenuation and differential attenuation. We present the ranges of the α and β coefficients in these varying precipitation regimes to help improve KDP-based attenuation correction algorithms at X-band as well as rain rate algorithms based on the derived AH.Item Open Access CASA real-time multi-Doppler retrieval system(Colorado State University. Libraries, 2011) Zhang, Sean X., author; Chandrasekaran, V., advisor; Bringi, V. N., committee member; Jayasumana, Anura P., committee member; Mielke, Paul W., committee memberDoppler synthesis of 3D wind products is of great practical importance to observing and understanding severe weather features such as tornadoes and microbursts. It becomes very effective for severe weather events if this modeling can be performed in real-time. A real-time multi-Doppler retrieval system forms an important product of modern weather radar networks. Challenging constraints exists between computing performance, high data resolution, and other quality issues. This Thesis describes the implementation of the operational Real-time Multi-Doppler Retrieval System (R-MDRS) of the Center for Collaborative Adaptive Sensing of the Atmosphere Engineering Research Center (CASA ERC). The R-MDRS is seamlessly integrated into CASA's Distributed Collaborative Adaptive Sensing (DCAS) operational framework and exhibit robust performance that strikes balance between high resolution and real-time processing speeds. A detailed technical description of the CASA R-MDRS implementation is given, including design approach that builds around two core components of the tool: interpolation to a common grid and Doppler synthesis. The R-MDRS generates 3D Wind products in step with network scanning modes and has been effective at detecting convective cells and tornadic activities. Data from 2009 and 2010 weather events are presented and analyzed for evaluating processing time as well as factors that effect data accuracy. These factors include Dual-Doppler candidate pair selection, advection correction, and variations in wind calculation techniques.Item Open Access Comparison of direct shear and triaxial tests for measurement of shear strength of sand(Colorado State University. Libraries, 1991) Rahman, Jamshed, author; Nelson, John D., advisor; Siller, Thomas J., committee member; Mielke, Paul W., committee memberTo ascertain the shear strength parameters of soils for engineering purposes is fundamental to soil mechanics and basic for designing earth-bearing and earth-retaining structures. Direct shear and triaxial tests are the most popular laboratory methods to determine these parameters. The direct shear test is used widely because it is simple and quick. The test has several disadvantages, however. The non-uniform stress-strain behavior, the rotation of principal planes during the test, and the imposition of the failure plane are chief among them. The triaxial test was designed as a possible alternative that eliminates some of these disadvantages. Direct shear test results are always comparable to those of the triaxial test; the difference usually is negligible from a practical point of view. Researchers have tried to unfold the intricacies involved in the direct shear test especially the complicated stress-strain behavior that a soil experiences during this test. Data, however, are lacking that determine the difference and establish a correlation between the results of the two tests. This study compares the two tests for measurement of shear strength parameters of sand. Triaxial and direct shear tests were performed on silica sand under the same density and normal stress conditions. Five sets of triaxial tests and 20 direct shear tests each were performed using four different makes of direct shear machines. The results of the direct shear tests were compared with those of the triaxial tests considering the latter as benchmarks. The possible effect of the structural features of the direct shear equipment on results was briefly studied. The results showed that the shear strengths from direct shear tests are higher than those from the triaxial tests. All four direct shear machines gave cohesion values different from each other and higher than the benchmark value. The Soiltest and Wykeham Farrance machines gave almost the same friction angle that was higher than the benchmark value by 4 degrees. The friction angle value from the ELE machine was higher by 2.7 degrees while those from Clockhouse machine were lower by 4.5 degrees as compared to the benchmark value.Item Open Access Cross validation of observations from the GPM dual-frequency precipitation radar and dual-polarization S-band ground radars(Colorado State University. Libraries, 2018) Biswas, Sounak Kumar, author; Chandrasekar, V., advisor; Cheney, Margaret, committee member; Mielke, Paul W., committee memberThis research presents a comparative study of observations and various products of the Global Precipitation Measurement (GPM) Mission Satellite with dual polarization S-Band Ground Radars. The GPM mission is a joint venture by the NASA and the JAXA. The radar on board the core observatory is a dual-frequency precipitation radar (DPR) capable of simultaneously operating at 13.6 GHz (Ku band) and 35.5 GHz (Ka band). The DPR is expected to revolutionize the way precipitation is measured from space through its dual-frequency observations. Ground Validation is one of the most critical aspects of the GPM mission. The best way of doing this is by direct comparison of the space-based observations with well calibrated dual polarization ground radar measurements. Before any direct comparisons can be made, volume matching of the data is necessary due to the difference in observation geometry and resolution volume of both the system. In this study, a methodology developed by Bolen and Chandrasekar (2001) for aligning TRMM satellite data with ground radar data is followed. This technique was extended by Schwaller and Morris (2011). Radar reflectivity and rainfall rate product comparison study have been performed in detail. Vertical profiles have been studied thoroughly. Various case studies of simultaneous GPM-DPR and ground radar observations have been carefully chosen. Ground validation operational NEXRAD sites have been considered from all over the USA. Comparison studies with research radars such as CSU-CHILL and NASA N-POL have also been conducted. The GPM satellite's profile classification module's products are also evaluated. Results from Hydrometeor classification method by Bechini and Chandrasekar (2015) for ground radars have been extensively used for validating DPR's melting layer detection capability in different types of precipitation system. In this study, a new method developed by Le et al (2017) for identification of snow falling on the ground has been considered. Ground validation comparisons have been performed with observations from ground radars and the results are presented.Item Open Access Description and evaluation of the CASA dual-Doppler system(Colorado State University. Libraries, 2011) Martinez, Matthew Thomas, author; Chandra, Chandrasekar V., advisor; Notaros, Branislav M., committee member; Mielke, Paul W., committee memberLong range weather surveillance radars are designed for observing weather events for hundreds of kilometers from the radar and operate over a large coverage domain independently of weather conditions. As a result a loss in spatial resolution and limited temporal sampling of the weather phenomenon occurs. Due to the curvature of the Earth, long-range weather radars tend to make the majority of their precipitation and wind observations in the middle to upper troposphere, resulting in missed features associates with severe weather occurring in the lowest three kilometers of the troposphere. The spacing of long-range weather radars in the United States limits the feasibility of using dual-Doppler wind retrievals that would provide valuable information on the kinematics of weather events to end-users and researchers. The National Science Foundation Center for Collaborative Adapting Sensing of the Atmosphere (CASA) aims to change the current weather sensing model by increasing coverage of the lowest three kilometers of the troposphere by using densely spaced networked short-range weather radars. CASA has deployed a network of these radars in south-western Oklahoma, known as Integrated Project 1 (IP1). The individual radars are adaptively steered by an automated system known as the Meteorological Command and Control (MCC). The geometry of the IP1 network is such that the coverage domains of the individual radars are overlapping. A dual-Doppler system has been developed for the IP1 network which takes advantage of the overlapping coverage domains. The system is comprised of two subsystems, scan optimization and wind field retrieval. The scan strategy subsystem uses the DCAS model and the number of dual-Doppler pairs in the IP1 network to minimizes the normalized standard deviation in the wind field retrieval. The scan strategy subsystem also minimizes the synchronization error between two radars. The retrieval itself is comprised of two steps, data resampling and the retrieval process. The resampling step map data collected in radar coordinates to a common Cartesian grid. The retrieval process uses the radial velocity measurements to estimate the northward, eastward, and vertical component of the wind. The error in the retrieval is related to the beam crossing angle. The best retrievals occur at beam crossing angles greater than 30 degrees. During operations statistics on the scan strategy and wind field retrievals are collected in real-time. For the scan strategy subsystem statistics on the beam crossing angels, maximum elevation angle, number of elevation angles, maximum observable height, and synchronization time between radars in a pair are collected by the MCC. These statistics are used to evaluate the performance of the scan strategy subsystem. Observations of a strong wind event occurring on April 2, 2010 are used to evaluate the decision process associated with the scan strategy optimization. For the retrieval subsystem, the normalized standard deviation for the wind field retrieval is used to evaluate the quality of the retrieval. Wind fields from an EF2 tornado observed on May 14, 2009 are used to evaluate the quality of the wind field retrievals in hazardous wind events. Two techniques for visualizing vector fields are available, streamlines and arrows. Each visualization technique is evaluated based on the task of visualizing small and large scale phenomenon. Applications of the wind field retrievals include the computation of the vorticity and divergence fields. Vorticity and divergence for an EF2 tornado observed on May 14, 2009 are evaluated against vorticity and divergence for other observed tornadoes.Item Open Access Electronic scan weather radar: scan strategy and signal processing for volume targets(Colorado State University. Libraries, 2013) Nguyen, Cuong Manh, author; Chandra, Chandrasekar V., advisor; Jayasumana, Anura P., committee member; Mielke, Paul W., committee member; Notaros, Branislav, committee memberFollowing 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.Item Open Access Frequency diversity wideband digital receiver and signal processor for solid-state dual-polarimetric weather radars(Colorado State University. Libraries, 2012) Mishra, Kumar Vijay, author; Chandra, Chandrasekar V., advisor; Jayasumana, Anura P., committee member; Mielke, Paul W., committee memberThe 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.Item Open Access Investigation of enhanced-reflectivity features embedded within a wintertime orographic cloud on 28-29 November 1984(Colorado State University. Libraries, 1994) Baker, Ian T., author; Grant, Lewis O., advisor; Mielke, Paul W., committee member; Cotton, William R., committee memberA combination of aircraft, sounding, surface, vertically-pointing ku-Band radar and dual-channel radiometer data was used to investigate the microphysical characteristics of enhanced-reflectivity areas embedded within an orographic cloud in northwestern Colorado on 28-29 November 1984. The orographic cloud was associated with the passage of an open wave and upper-level front over the region, and embedded within the cloud were regularly-spaced areas of increased reflectivity as seen by the vertically-pointing radar. The radiometer observed a cyclical component on both the liquid and vapor channels when oriented in the vertical. Aircraft data reveal that there was supercooled liquid water in the cloud at levels as high as 41 kPa and as far as 55 km upwind of the barrier. 2D-C and 2D-P probe data indicated two crystal regimes, one where concentrations in individual size bins were larger and spectra were broader, indicating crystal growth. In the other, concentrations were smaller and size spectra were narrower. Radar data indicate that the enhanced-reflectivity regions were between 10-20 km apart, with a length dimension on the order of 5 km wide. It is believed that the presence of the enhanced-reflectivity areas is closely linked to the presence of a decoupled layer on the windward side of the barrier, and preliminary evidence points to a gravity-wave mechanism as a physical cause.Item Open Access Microphysical retrieval and profile classification for GPM dual-frequency precipitation radar and ground validation(Colorado State University. Libraries, 2013) Le, Minda, author; Chandrasekar, V. Chandra, advisor; Jayasumana, Anura P., committee member; Mielke, Paul W., committee member; Notaros, Branislav, committee memberThe Global Precipitation Measurement (GPM) mission, planned as the next satellite mission following the Tropical Rainfall Measurement Mission (TRMM), is jointly sponsored by the National Aeronautic and Space Administration (NASA) of USA and the Japanese Aerospace Exploration Agency (JAXA) with additional partners, the Centre National d'Études Spatiales (CNES), the Indian Space Research Organization (ISRO), the National Oceanic and Atmospheric Administration (NOAA), the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), and others. The core satellite of GPM mission will be equipped with a dual-frequency precipitation radar (DPR) operating at Ku- (13.6 GHz) and Ka- (35.5 GHz) band with the capability to cover ±65° latitude of the earth. One primary goal of the DPR is to improve accuracy in estimation of drop size distribution (DSD) parameters of precipitation particles. The estimation of the DSD parameters helps achieve more accurate estimation of precipitation rates. The DSD is also centrally important in the determination of the electromagnetic scattering properties of precipitation media. The combination of data from the two frequency channels, in principle, can provide more accurate estimates of DSD parameters than the TRMM Precipitation radar (TRMM PR) with Ku- band channel only. In this research, a methodology is developed to retrieve DSD parameters for GPM-DPR. Profile classification is a critical module in the microphysical retrieval system for GPM-DPR. The nature of microphysical models and equations for use in the DSD retrieval algorithm are determined by the precipitation type of each profile and the phase state of the hydrometeors. In the GPM era, the Ka- band channel enables the detection of light rain or snowfall in the mid- and high- latitudes compared to the TRMM PR (Ku- band only). GPM-DPR offers dual-frequency observations (measured reflectivity at Ku- band:Ζm (Ku) and measured reflectivity at Ka- band:Ζm (Ku)) along each vertical profile, which provide additional information for investigating the microphysical properties using the difference in measured radar reflectivities at the two frequencies, a quantity often called the measured dual-frequency ratio (DFRm) can be defined (DFRm=Ζm (Ku) — Ζm (Ka)). Both non-Rayleigh scattering effects and attenuation difference control the shape of the DFRm profile. Its pattern is determined by the forward and backscattering properties of the mixed phase and rain media and the backscattering properties of ice. Therefore, DFRm could provide better performance in precipitation type classification and hydrometeor profile characterization than TRMM PR. In this research, two methods, precipitation type classification (PCM) and hydrometeor profile characterization (HPC), are developed to perform profile classification for GPM-DPR using the DFRm profile and its range variability. The methods have been implemented into the GPM-DPR day one algorithm. Ground validation is an integral part of all satellite precipitation missions. Similar to TRMM, the GPM validation falls into the general class of validation and integration of information from space-borne observing platforms with a variety of ground-based measurements. Dual polarization ground radar is a powerful tool that can be used to address a number of important questions that arise in the validation process, especially those associated with precipitation microphysics and algorithm development. Extensive research has also been done regarding accurate retrievals of rain DSDs as well as attenuation correction for dual-polarization ground radar operating at S-, C- and X- band by using polarimetric measurements. However, polarimetric ground radar operating at a single frequency channel has limitation on DSD retrieval beyond rain region. A dual-frequency and dual-polarization Doppler radar (D3R) operating at the same frequency channels as GPM-DPR has been built. In this research, an algorithm is developed to retrieve DSD parameter for this D3R radar, which will serve as the GPM-DPR ground validation instrument.Item Open Access Nowcasting for a high-resolution weather radar network(Colorado State University. Libraries, 2010) Ruzanski, Evan, author; Chandrasekar, V., advisor; Jayasumana, Anura P., committee member; Mielke, Paul W., committee member; Notaros, Branislav M., committee memberShort-term prediction (nowcasting) of high-impact weather events can lead to significant improvement in warnings and advisories and is of great practical importance. Nowcasting using weather radar reflectivity data has been shown to be particularly useful. The Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network provides high-resolution reflectivity data amenable to producing valuable nowcasts. The high-resolution nature of CASA data requires the use of an efficient nowcasting approach, which necessitated the development of the Dynamic Adaptive Radar Tracking of Storms (DARTS) and sinc kernel-based advection nowcasting methodology. This methodology was implemented operationally in the CASA Distributed Collaborative Adaptive Sensing (DCAS) system in a robust and efficient manner necessitated by the high-resolution nature of CASA data and distributed nature of the environment in which the nowcasting system operates. Nowcasts up to 10 min to support emergency manager decision-making and 1-5 min to steer the CASA radar nodes to better observe the advecting storm patterns for forecasters and researchers are currently provided by this system. Results of nowcasting performance during the 2009 CASA IP experiment are presented. Additionally, currently state-of-the-art scale-based filtering methods were adapted and evaluated for use in the CASA DCAS to provide a scale-based analysis of nowcasting. DARTS was also incorporated in the Weather Support to Deicing Decision Making system to provide more accurate and efficient snow water equivalent nowcasts for aircraft deicing decision support relative to the radar-based nowcasting method currently used in the operational system. Results of an evaluation using data collected from 2007-2008 by the Weather Service Radar-1988 Doppler (WSR-88D) located near Denver, Colorado, and the National Center for Atmospheric Research Marshall Test Site near Boulder, Colorado, are presented. DARTS was also used to study the short-term predictability of precipitation patterns depicted by high-resolution reflectivity data observed at microalpha (0.2-2 km) to mesobeta (20-200 km) scales by the CASA radar network. Additionally, DARTS was used to investigate the performance of nowcasting rainfall fields derived from specific differential phase estimates, which have been shown to provide more accurate and robust rainfall estimates compared to those made from radar reflectivity data.Item Open Access Physical mechanisms of extra area effects from weather modification(Colorado State University. Libraries, 1977) Mulvey, G. (Gerald), author; Grant, Lewis O., advisor; Karaki, Susumu, committee member; Corrin, Myron L., committee member; Mielke, Paul W., committee member; Cotton, William R., committee memberOne of the complexities of weather modification, namely extra area effects have long posed an opportunity for the long-term control of the earth's weather. This study investigates the physical mechanisms by which cloud seeding projects may cause extra area effects. The investigations center on one of the simplest of precipitating systems, namely the cold wintertime orographic clouds of the central Rocky Mountains. Three lines of investigation are followed: (1) field studies of seeding material movement in the atmosphere and receiver cloud characteristics, (2) numerical simulation, and (3) historical studies of the affected cloud system. The field observations consist of case studies of the movement and dispersion of silver iodide from ground based generators. These studies, during the winters of 1974-75 and 1975-76, used nuclei counters aboard two aircraft. Aerosol silver concentration measurements were also made during the last experimental year. The surface observations made as part of the field studies included snow collection for silver analysis, radar observation and ice nuclei measurements. The aircraft studies established the fact that regions of above background ice nuclei concentrations extend from the target cloud systems as far as 240 km downwind while exhibiting concentrations from 10 to over 700 ice nuclei per liter active at -20°C. The analysis of silver concentrations in snow confirmed above background silver concentrations exist in snow samples on days during which cloud seeding occurred in the mountains. The numerical cloud models were used to investigate the mode of seeding and the seeding requirements of the downwind cloud systems. Case study r n s using a cumulus model suggested that seeding the upslope cloud would cause little dynamic intensification. It was therefore inferred that the seeding mode was static. The second cloud model, a rapid glaciation model, estimated the seeding requirements in terms of active ice nuclei or ice crystals for precipitation augmentation to be between 1.0 and 5 No1-1. An ice crystal transport model was used to predict 0 the survival time for a spectrum of crystal sizes under a variety of conditions. The results indicate that under certain meteorological conditions crystals typically observed in orographic conditions can survive long enough to reach the downwind upslope cloud in concentrations between 0.5 and 50 No1-1. The historical studies established characteristics of the typical upslope clouds as well as the surf ace features controlling their formation. The radar observations showed convective-like echoes migrating within the upslope cloud over the eastern plains of Colorado downwind of Climax. These studies show that at least two feasible mechanisms through which mountain orographic clouds can affect the precipitation on the eastern plains exist, and, under certain conditions, are operative.Item Open Access Precipitation observations from high frequency spaceborne polarimetric synthetic aperture radar and ground-based radar: theory and model validation(Colorado State University. Libraries, 2010) Fritz, Jason P., author; Chandrasekar, V., advisor; Jayasumana, Anura P., committee member; Notaros, Branislav M., committee member; Mielke, Paul W., committee memberGlobal weather monitoring is a very useful tool to better understand the Earth's hydrological cycle and provide critical information for emergency and warning systems in severe cases. Developed countries have installed numerous ground-based radars for this purpose, but they obviously are not global in extent. To address this issue, the Tropical Rainfall Measurement Mission (TRMM) was launched in 1997 and has been quite successful. The follow-on Global Precipitation Measurement (GPM) mission will replace TRMM once it is launched. However, a single precipitation radar satellite is still limited, so it would be beneficial if additional existing satellite platforms can be used for meteorological purposes. Within the past few years, several X-band Synthetic Aperture Radar (SAR) satellites have been launched and more are planned. While the primary SAR application is surface monitoring, and they are heralded as "all weather'' systems, strong precipitation induces propagation and backscatter effects in the data. Thus, there exists a potential for weather monitoring using this technology. The process of extracting meteorological parameters from radar measurements is essentially an inversion problem that has been extensively studied for radars designed to estimate these parameters. Before attempting to solve the inverse problem for SAR data, however, the forward problem must be addressed to gain knowledge on exactly how precipitation impacts SAR imagery. This is accomplished by simulating storms in SAR data starting from real measurements of a storm by ground-based polarimetric radar. In addition, real storm observations by current SAR platforms are also quantitatively analyzed by comparison to theoretical results using simultaneous acquisitions by ground radars even in single polarization. For storm simulation, a novel approach is presented here using neural networks to accommodate the oscillations present when the particle scattering requires the Mie solution, i.e., particle diameter is close to the radar wavelength. The process of transforming the real ground measurements to spaceborne SAR is also described, and results are presented in detail. These results are then compared to real observations of storms acquired by the German TerraSAR-X satellite and by one of the Italian COSMO-SkyMed satellites both operating in co-polar mode (i.e., HH and VV). In the TerraSAR-X case, two horizontal polarization ground radars provided simultaneous observations, from which theoretical attenuation is derived assuming all rain hydrometeors. A C-band fully polarimetric ground radar simultaneously observed the storm captured by the COSMO-SkyMed SAR, providing a case to begin validating the simulation model. While previous research has identified the backscatter and attenuation effects of precipitation on X-band SAR imagery, and some have noted an impact on polarimetric observations, the research presented here is the first to quantify it in a holistic sense and demonstrate it using a detailed model of actual storms observed by ground radars. In addition to volumetric effects from precipitation, the land backscatter is altered when water is on or near the surface. This is explored using TRMM, Canada's RADARSAT-1 C-band SAR and Level 3 NEXRAD ground radar data. A weak correlation is determined, and further investigation is warranted. Options for future research are then proposed.Item Open Access Quantitative precipitation estimation for an X-band weather radar network(Colorado State University. Libraries, 2013) Chen, Haonan, author; Chandrasekar, V., advisor; Notaros, Branislav M., committee member; Mielke, Paul W., committee memberCurrently, the Next Generation (NEXRAD) radar network, a joint effort of the U.S. Department of Commerce (DOC), Defense (DOD), and Transportation (DOT), provides radar data with updates every five-six minutes across the United States. This network consists of about 160 S-band (2.7 to 3.0 GHz) radar sites. At the maximum NEXRAD range of 230 km, the 0.5 degree radar beam is about 5.4 km above ground level (AGL) because of the effect of earth curvature. Consequently, much of the lower atmosphere (1-3 km AGL) cannot be observed by the NEXRAD. To overcome the fundamental coverage limitations of today's weather surveillance radars, and improve the spatial and temporal resolution issues, the National Science Foundation Engineering Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) was founded to revolutionize weather sensing in the lower atmosphere by deploying a dense network of shorter-range, low-power X-band dual-polarization radars. The distributed CASA radars are operating collaboratively to adapt the changing atmospheric conditions. Accomplishments and breakthroughs after five years operation have demonstrated the success of CASA program. Accurate radar quantitative precipitation estimation (QPE) has been pursued since the beginning of weather radar. For certain disaster prevention applications such as flash flood and landslide forecasting, the rain rate must however be measured at a high spatial and temporal resolution. To this end, high-resolution radar QPE is one of the major research activities conducted by the CASA community. A radar specific differential propagation phase (Kdp)-based QPE methodology has been developed in CASA. Unlike the rainfall estimation based on the power terms such as radar reflectivity (Z) and differential reflectivity (Zdr), Kdp-based QPE is less sensitive to the path attenuation, drop size distribution (DSD), and radar calibration errors. The CASA Kdp-based QPE system is also immune to the partial beam blockage and hail contamination. The performance of the CASA QPE system is validated and evaluated by using rain gauges. In CASA's Integrated Project 1 (IP1) test bed in Southwestern Oklahoma, a network of 20 rainfall gauges is used for cross-comparison. 40 rainfall cases, including severe, multicellular thunderstorms, squall lines and widespread stratiform rain, that happened during years 2007 - 2011, are used for validation and evaluation purpose. The performance scores illustrate that the CASA QPE system is a great improvement compared to the current state-of-the-art. In addition, the high-resolution CASA QPE products such as instantaneous rainfall rate map and hourly rainfall amount measurements can serve as a reliable input for various distributed hydrological models. The CASA QPE system can save lived and properties from hazardous flash floods by incorporating hydraulic and hydrologic models for flood monitoring and warning.Item Open Access Radar and satellite observations of precipitation: space time variability, cross-validation, and fusion(Colorado State University. Libraries, 2017) Chen, Haonan, author; Chandrasekar, V., advisor; Reising, Steven C., committee member; Cheney, Margaret, committee member; Mielke, Paul W., committee memberRainfall estimation based on satellite measurements has proven to be very useful for various applications. A number of precipitation products at multiple time and space scales have been developed based on satellite observations. For example, the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space-based observations and retrievals. The CMORPH products are derived using infrared (IR) brightness temperature information observed by geostationary satellites and passive microwave-(PMW) based precipitation retrievals from low earth orbit satellites. Although space-based precipitation products provide an excellent tool for regional, local, and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, their accuracy is limited due to restrictions of spatial and temporal sampling and the applied parametric retrieval algorithms, particularly for light precipitation or extreme events such as heavy rain. In contrast, ground-based radar is an excellent tool for quantitative precipitation estimation (QPE) at finer space-time scales compared to satellites. This is especially true after the implementation of dual-polarization upgrades and further enhancement by urban scale X-band radar networks. As a result, ground radars are often critical for local scale rainfall estimation and for enabling forecasters to issue severe weather watches and warnings. Ground-based radars are also used for validation of various space measurements and products. In this study, a new S-band dual-polarization radar rainfall algorithm (DROPS2.0) is developed that can be applied to the National Weather Service (NWS) operational Weather Surveillance Radar-1988 Doppler (WSR-88DP) network. In addition, a real-time high-resolution QPE system is developed for the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Dallas-Fort Worth (DFW) dense radar network, which is deployed for urban hydrometeorological applications via high-resolution observations of the lower atmosphere. The CASA/DFW QPE system is based on the combination of a standard WSR-88DP (i.e., KFWS radar) and a high-resolution dual-polarization X-band radar network. The specific radar rainfall methodologies at Sand X-band frequencies, as well as the fusion methodology merging radar observations at different temporal resolutions are investigated. Comparisons between rainfall products from the DFW radar network and rainfall measurements from rain gauges are conducted for a large number of precipitation events over several years of operation, demonstrating the excellent performance of this urban QPE system. The real-time DFW QPE products are extensively used for flood warning operations and hydrological modelling. The high-resolution DFW QPE products also serve as a reliable dataset for validation of Global Precipitation Measurement (GPM) satellite precipitation products. This study also introduces a machine learning-based data fusion system termed deep multi-layer perceptron (DMLP) to improve satellite-based precipitation estimation through incorporating ground radar-derived rainfall products. In particular, the CMORPH technique is applied first to derive combined PMW-based rainfall retrievals and IR data from multiple satellites. The combined PMW and IR data then serve as input to the proposed DMLP model. The high-quality rainfall products from ground radars are used as targets to train the DMLP model. In this dissertation, the prototype architecture of the DMLP model is detailed. The urban scale application over the DFW metroplex is presented. The DMLP-based rainfall products are evaluated using currently operational CMORPH products and surface rainfall measurements from gauge networks.Item Open Access Sand dispersion in a laboratory flume(Colorado State University. Libraries, 1968) Yang, Tsung, author; Shen, H. W., advisor; Simons, Daryl B., committee member; Richardson, Everett V., committee member; Sandborn, Virgil A., committee member; Mielke, Paul W., committee memberThis study is concerned mainly with the longitudinal dispersion of sand particles along the bed of an alluvial channel under conditions of steady, uniform flow. Attention is focused on developing a general one-dimensional stochastic model to describe and predict the longitudinal dispersion process. The method of approach used by Sayre and Conover (1967) for a two-dimensional stochastic model, which described the movement of sand particles along an alluvial bed, is adapted here for the development of a general one-dimensional stochastic model. The parameters used in this general one-dimensional stochastic model can be obtained either from longitudinal dispersion and transport data, or from bed configuration data, or from a combination of both. The statistical analysis of ripple bed configurations indicates that the distribution of bed elevation closely follows a normal distribution, and may possess the ergodic property. The Aris moment equations are used to solve the problem of sand dispersion along an alluvial bed as a special case of the problem of dispersion of suspended sand particles near the bed. The Aris moment equations used in this study are modified forms of the conservation of mass equations for the transport, deposition, and re-entrainment of suspended sediment. When appropriate initial and boundary conditions are used, there is excellent agreement between solutions of the Aris moment equation and results given by the general one—dimensional stochastic model. Fine, medium, and coarse sized radioactive sand grains were used as tracer particles in experiments at two different flow conditions, namely, ripple and dune conditions. In spite of the irregularities of the experimental longitudinal dispersion curves caused by the irregularities of the bed configurations, the mean longitudinal displacement and the variance of the longitudinal distribution of the tracer particles were found to increase linearly with time, as required by the stochastic model. The shape of the experimental longitudinal dispersion curves could also be fairly well represented by the general one-dimensional stochastic model.Item Open Access The development and validation of an X-band dual polarization Doppler weather radar test node for a tropical network(Colorado State University. Libraries, 2012) Galvez, Miguel Bustamante, author; Chandrasekar, V., advisor; Bringi, V. N., committee member; Mielke, Paul W., committee memberAn automated network of three X-band dual polarization Doppler weather radars is in process of being deployed and operational on the western coast of Puerto Rico. Colorado State University and the University of Puerto Rico at Mayaguez have collaborated to install the first polarimetric weather radar network in a tropical environment, known as TropiNet, to observe the lowest 2 km of the troposphere where the National Weather Service NEXRAD radar in Cayey, PR (TJUA) has obstructed views of the west coast, below 1.5 km due to terrain blockage and the Earth curvature problem. The CSU-X25P radar test node was developed, validated, and deployed to Mayaguez, PR in early 2011 to make first observations of this tropical region, and served as a pilot project to verify the infrastructure of the TropiNet network. This research describes the CSU-X25P radar test node, presenting the radar system specifications and an overview of the data acquisition and signal processing sub-systems, and the antenna positioner and control sub-system. The development and validation process included integration, sub-system calibration and test, and a final evaluation by conducting end-to-end calibration of the radar system. Validation of the calculated data moments, include Doppler velocity, reflectivity, differential reflectivity, differential propagation phase, and specific differential phase. The validation was accomplished by comparative analysis of data from coordinated scans between CSU-X25P and the well-established CSU-CHILL S-band polarimetric Doppler weather radar, in Greeley, CO. Upon validation, CSU-X25P was disassembled, packaged, and shipped to Puerto Rico to be fully deployed for operation in a tropical seaside environment. This research presents select observations of severe weather events, such as tropical storms and hurricanes, which attest to the robustness of the radar test node, and the TropiNet network infrastructure.