Thesis (M.S.)--University of Wisconsin--Madison, 1969. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--Florida State University, 2006. / Advisor: Sharon E. Nicholson, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed June 16, 2006). Document formatted into pages; contains xvi, 152 pages. Includes bibliographical references.

In an effort to improve upon rainfall forecasts produced by simple storm advection methods (nowcasts) and to broach the gap between them and the forecasts of complex Numerical Weather Prediction (NWP) models, in terms of the spatial detail and length of lead-time each provides, the research presented explores the possibility of combining elements of each into a physically-based algorithm for rainfall forecasting. It is an algorithm that uses as its foundation the rainfall prediction model of Mark French and Witold Krajewski, developed in 1994. Their model was designed to take advantage of the high resolution rainfall observations and tracking abilities provided by weather radar and to achieve a rainfall forecast by augmenting extrapolation techniques with a representation of storm dynamics in the form of "rising parcel" theory. The new algorithm/model retains those features but incorporates NWP data to assist with forecasting, using it as a means to enable an informed choice of algorithm pathways and, more specifically, to identify the ingredients of precipitation, namely ascending air of high moisture content. A case study application of the new rainfall forecasting model to storms in Northern England shows its performance, at a lead-time of one hour, compares favourably with respect to extrapolation and persistence techniques and also NWP forecasts, and that it is able to provide more assured forecasts than persistence and nowcasts at longer lead-times. The robustness of the model is tested and confirmed by way of another case study, this time using Mediterranean storms and with predictions made in the context of urban hydrology. The case studies help to identify aspects of the model that need improvement, with representation of orographic forcing being a key one. Both the model's encouraging performance and its pinpointed weaknesses provide impetus for further research in the area of integrated mesoscale-hydrometeorological modelling for flood forecasting.

This study examines historical variations in flood frequency and magnitude in the Yorkshire Ouse basin, northern England, over the last 900 years. The causes of temporal and spatial variations in flooding are evaluated through investigation o f climatic and land-use controls. Documentary evidence o f flooding and climate suggests that a series of large floods between 1263 and 1360 were associated with climatic deterioration from the Medieval Optimum. A shift to generally milder conditions between 1361 and 1549 resulted in no floods being documented in the Ouse basin The frequency o f large magnitude floods increased dramatically between 1550 and 1680, as a result o f low temperatures, increased surface wetness, more frequent snowfall and a southward shift of prevailing storm tracks over middle latitudes, associated with the onset of the "Little Ice Age’. In contrast, during a wanner phase of the Little Ice Age, between 1681 and 1763, the frequency of localised summer flooding increased in the Ouse basin due to more frequent high intensity, short duration convective storms. Extensive lowland flooding became more common between 1764 and 1799 due to an increase in heavy rainfall, followed by a 50-year period characterised by relatively moderate flood frequencies and magnitudes. The later half of the nineteenth century experienced high flood frequencies and magnitudes, particularly in the 1870s and early-1880s, coinciding with high rainfall totals and a high incidence of cyclonic flood generation. Gauged flood and climate data, and land-use records indicate that the period between 1900 and 1916 was characterised by very low flood frequencies and magnitudes, associated with low rainfall, warm temperatures, and an increase in westerly flood generation. Between 1916 and 1943 there were marked variations in flood magnitude between the rural northern rivers and southern industrialised rivers. Magnitudes generally increased on northern rivers, whilst on some southern tributaries of the Ouse, flood magnitudes declined as a result of widespread channel improvement and flood defence schemes. Around 1944 a marked and sustained increase in flood frequency on northern rivers was associated with an increase in the incidence of heavy daily rainfall, greater westerly flood generation and large-scale upland and lowland drainage. Very low flood frequencies and magnitudes between 1969'and 1977 resulted from extremely low rainfall totals. Whereas the most recent period, between 1978 and 1996 has experienced some of the highest flood frequencies and magnitudes on record, associated with an increase in the frequency of floods generated under cyclonic and south-westerly synoptic situations, and a number of land-use changes promoting more rapid runoff including, large increases in upland livestock numbers, an increase in the area under winter-cereals and the cumulative effects of moorland gripping.

A millimetric wave transmission link of the radar type has been established at the University of British Columbia campus. It operates at 74 GHz and has a 1.8 km total transmission length. The RF source is an unmodulated klystron and a phase-locked receiver is used to detect the received signal. The main objective is to measure the excess path attenuation due to precipitation. For this purpose a weather station has been constructed. It consists of 5 tipping-bucket rain gauges distributed along the path and apparatus for the measurement of temperature and wind velocity. The level of the microwave signal and the outputs of the weather sensors are transmitted to a central station. There, initial processing and data recording on magnetic tape are performed on a continuous basis by a Nova 840 minicomputer. Subsequently, data is further processed on an IBM 370. Of the 1400 hours of data recorded during a four month period, approximately 25 hours included simultaneous rain and microwave data and were sufficiently "reliable" to analyse. The processed experimental data are compared with the theory of Ryde and Ryde over the range of rain rates observed (0 to 10 mm/hour). / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2020 / Several studies indicated a growing trend in terms of frequency and severity of extreme events. Extreme rainfall could cause disasters that lead to loss of property and life. The aim of the study was to model the monthly rainfall variability in selected provinces of South Africa using extreme value distributions. This study investigated the best-fit probability distributions in the five provinces of South Africa. Five probability distributions: gamma, Gumbel, log-normal, Pareto and Weibull, were fitted and the best was selected from the five distributions for each province. Parameters of these distributions were estimated by the method of maximum likelihood estimators. Based on the Akaike information criteria (AIC) and Bayesian information criteria (BIC), the Weibull distribution was found to be the best-fit probability distribution for Eastern Cape, KwaZulu-Natal, Limpopo and Mpumalanga, while in Gauteng the best-fit probability distribution was found to be the gamma distribution. Monthly rainfall trends detected using the Mann–Kendall test revealed significant monotonic decreasing long-term trend for Eastern Cape, Gauteng and KwaZulu-Natal, and insignificant monotonic decreasing longterm trends for Limpopo and Mpumalanga. Non-stationary generalised extreme value distribution (GEVD) and non-stationary generalized Pareto distribution (GPD) were applied to model monthly rainfall data. The deviance statistic and likelihood ratio test (LRT) were used to select the most appropriate model. Model fitting supported stationary GEVD model for Eastern Cape, Gauteng and KwaZulu-Natal. On the other hand, model fitting supported non-stationary GEVD models for maximum monthly rainfall with nonlinear quadratic trend in the location parameter and a linear trend in the scale parameter for Limpopo, while in Mpumalanga the non-stationary GEVD model, which has a nonlinear quadratic trend in the scale parameter and no variation in the location parameter fitted well to the maximum monthly rainfall data. Results from the non-stationary GPD models showed that inclusion of the time covariate in our models was not significant for Eastern Cape, hence the bestfit model was the stationary GPD model. Furthermore, the non-stationary GPD model with a linear trend in the scale parameter provided the best-fit for KwaZulu-Natal and Mpumalanga, while in Gauteng and Limpopo the nonstationary GPD model with a nonlinear quadratic trend in the scale parameter fitted well to the monthly rainfall data. Lastly, GPD with time-varying thresholds was applied to model monthly rainfall excesses, where a penalised regression cubic smoothing spline was used as a time-varying threshold and the GPD model was fitted to cluster maxima. The estimate of the shape parameter showed that the Weibull family of distributions is appropriate in modelling the upper tail of the distribution for Limpopo and Mpumalanga, while for Eastern Cape, Gauteng and KwaZulu-Natal, the exponential family of distributions was found to be appropriate in modelling the upper tail of the distribution. The dissertation contributes positively to the body of knowledge in extreme value theory application to rainfall data and makes recommendations to the government agencies on the long-term rainfall variability and their negative impact on the economy.

Rainfall can be the most erosive agent with respect to rainfall induced erosion, particularly within the context of a tropical maritime environment. Mauritius provides an example of such an environment, which, due to its location and elevated topography, is subject to frequent erosive rainfall events as well as occasional cyclones which potentially threaten loss of soil and may accelerate land degradation. Such intense rainfall forms a key part of the “R-factor” in the USLE and RUSLE soil loss equations, which are commonly used worldwide in deriving the soil loss of an area. This project focuses on various attributes of rainfall erosivity on the central and western parts of Mauritius over a six year assessment period. A steep rainfall gradient exists; 600mm in the western plains and 4000mm per year in the higher central region. Rainfall and erosivity attributes are investigated in these two regions on the island to assess the role that topographic elevation has on rainfall erosivity. Using the EI30 method to find the “R-factor”, erosivity is calculated for the period of 2003 – 2008. Varying time intervals were used in calculating EI30 to determine the value that high resolution data has in erosivity calculations and is compared to the use of the Modified Fournier Index. This project also speculates on the potential impacts of changing rainfall intensity and erosivity associated with climate change in the future. A difference was found in the erosivity experienced in the elevated central interior and the rain-shadowed western lava plains. Stations on the western plains recorded 25% of the erosivity experienced by stations in the interior and large differences were found in the number of erosive events, rainfall, erosive rainfall totals, seasonality, and annual erosivity totals of erosivity. The central interior showed greater variability in R-factor values; however these remained similar in extent despite the large difference in total annual rainfall and the number of events that each station recorded. High resolution data did account for erosivity that lower resolution does not, but the extent of erosivity for all stations within the respective regions were markedly similar. Use of the Modified Fournier Index caused erosivity to be overestimated on the island when compared to the EI30 method. Changes in erosivity are speculated to occur with changes in rainfall intensities but the central interior of the island will notice fluctuations in climate (with respect to rainfall erosivity) more than the western plains. / Dissertation (MSc)--University of Pretoria, 2012. / Geography, Geoinformatics and Meteorology / Unrestricted

"This paper describes the procedure and results of a surface isotherm analysis of the North Indian Ocean for June 1920, a dry monsoon year, and June 1933, a wet monsoon year. It was found that June sea-surface temperatures were higher during the year of excessive rainfall as compared to a year of deficient rainfall. This positive parallelism is evidence which supports the hypothesis that the amount of rainfall over India during the southwest monsoon depends upon the variation of the surface temperature of the North Indian Ocean"--Abstract. / "August 15, 1952." / Typescript. / "Submitted to the Graduate Council of Florida State University in partial fulfillment of the requirements for the degree of Master of Science." / Includes bibliographical references (leaf 14).

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