This thesis presents the development of various methods for measuring rainfall rates using horizontally-pointing millimetre-wave radars. This work builds from the combination of a T-matrix scattering model that allows the scattering from almost arbitrarily pro led rotationally symmetric particles to be calculated, and drop shape models that allow the effects of temperature and pressure on the shape to be taken into account. Many hours of rain data have been collected with 38 and 94 GHz FMCW radars, as well as with a disdrometer and weather station. These have been used to develop single- and dual-frequency techniques for measuring rainfall rate. A temperature, polarisation and attenuation corrected application of simple power-law relationships between reflectivity and rainfall rate has been successfully demonstrated at 38 GHz. However, at 94 GHz it has been found that more detailed functions relating reflectivity, attenuation and rainfall rate are beneficial. A reflectivity-based determination of attenuation has been adapted from the literature and successfully applied to the 94 GHz data, improving the estimate of rainfall rate at longer ranges. The same method for estimating attenuation has also been used in a dualfrequency technique based on the ratio of the extinction coefficients at 38 and 94 GHz, but with less success. However, a dual-frequency reflectivity ratio based approach has been successfully developed and applied, producing good estimates of rainfall rate, as well as reasonable estimates of two drop-size distribution parameters. Simulations of radar measurements of airborne volcanic ash have also been carried out, demonstrating that for most reasonable measurement configurations the optimal frequencies would typically be 35 GHz or 94 GHz, not the more commonly used 3-10 GHz. It has also been shown that various existing millimetre-wave radars could be used to detect ash. Finally, there is a discussion of the optimal frequencies for dual-frequency measurement of volcanic ash.

Traditional methods such as distance weighing, correlation and data driven methods have been used in the estimation of missing precipitation data. Also common is the use of radar (NEXRAD) data to provide better spatial distribution of precipitation as well as infilling missing rain gage data. Conventional regression models are often used to capture highly variant nonlinear spatial and temporal relationships between NEXRAD and rain gage data. This study aims to understand and model the relationships between radar (NEXRAD) estimated rainfall data and the data measured by conventional rain gages. The study is also an investigation into the use of emerging computational data modeling (inductive) techniques and mathematical programming formulations to develop new optimal functional approximations. Radar based rainfall data and rain gage data are analyzed to understand the spatio-temporal associations, as well as the effect of changes in the length or availability of data on the models. The upper and lower Kissimmee basins of south Florida form the test-bed to evaluate the proposed and developed approaches and also to check the validity and operational applicability of these functional relationships among NEXRAD and rain gage data for infilling of missing data. / by Delroy Peters. / Thesis (M.S.)--Florida Atlantic University, 2008. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2008. Mode of access: World Wide Web.

Radar rainfall estimates have become a decision making tool for scientists, engineers and water managers in their tasks for developing hydrologic models, water supply planning, restoration of ecosystems, and flood control. In the present study, the utility of a power function for linking the rain gauge and radar estimates has been assessed. Mean daily rainfall data from 163 rain gauges installed within the South Florida Water Management District network have been used and their records from January 1st, 2002 to October 31st, 2007 analyzed. Results indicate that the power function coefficients and exponents obtained by using a non-linear optimization formulation, show spatial variability mostly affected by type of rainfall events occurring in the dry or wet seasons, and that the linear distance from the radar location to the rain gauge has a significant effect on the computed values of the coefficients and exponents. / by Mario Mayes-Fernandez. / Thesis (M.S.C.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.

"July 2003." Includes bibliographical references (leaves 459-484) Electronic publication; full text available in PDF format; abstract in HTML format. Details the application of a medium frequency Doppler radar to observations of meteorites entering the Earth's atmosphere. Techniques were developed that verified system performance was to specification Electronic reproduction.[Australia] :Australian Digital Theses Program,2001. xx, 485 leaves : ill. ; 30 cm.

No description available.

Thesis (M.S.)--University of Missouri-Columbia, 2008. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 13, 2009) Includes bibliographical references.

<p>Storms in the SE-US often evolve in different environments than those in the central Plains. Many poorly understood aspects of these differing environments may impact the tornadic potential of SE-US storms. Among these differences are potential variations in the CCN concentration owing to differences in land cover, combustion, industrial and urban activity, and proximity to maritime environments. The relative influence of warm and cold rain processes is sensitive to CCN concentration, with higher CCN concentrations producing smaller cloud droplets and more efficient cold rain processes. Cold rain processes result in DSDs with relatively larger drops from melting ice compared to warm rain processes. Differences in DSDs impact cold pool and downdraft size and strength, that influence tornado potential. This study investigates the impact of CCN concentration on DSDs in the SE-US by comparing DSDs from ARPS-EnKF model analyses and forecasts to observed DSDs from portable disdrometer-equipped probes collected by a collaboration between Purdue University, the University of Oklahoma (OU), the National Severe Storms Laboratory (NSSL), and the University of Massachusetts in a tornadic QLCS on 30 April 2017 during VORTEX-SE.</p><p>The ARPS-EnKF configuration, which consists of 40 ensemble members, is used with the NSSL triple-moment microphysics scheme. Surface and radar observations are both assimilated. Data assimilation experiments with CCN concentrations ranging from 100 cm^-3 (maritime) to 2,000 cm^-3 (continental) are conducted to characterize the variability of DSDs and the model output DSDs are verified against the disdrometer observations. The sensitivity of the DSD variability to CCN concentrations is evaluated. Results indicate continental CCN concentrations (close to CCN 1,000 cm³) produce DSDs that align closest to the observed DSDs. Other thermodynamic variables also accord better to observations in intermediate CCN concentration environments.</p>

No description available.

M.S.

This thesis describes the use of a distrometer and two IBM-PC's to collect data in a large propagation experiment. The uses and methods of collecting drop size distribution are discussed as are the uses of IBM-PC's for both data collection and control. Methods of requiring the PC's to operate in real time are also included. / M.S.