Rain and other precipitation cause attenuation and depolarization of high frequency satellite signals. Some characteristics of rain can be measured by dual-polarized radar. These characteristics can then be used to predict the effects of the rain on satellite-path propagation. This thesis describes briefly the theory of radar and satellite link measurements. Methods for calibrating the equipment and deriving actual experimental values from measured power are presented in detail. A set of computer programs to approximately predict radar and link values from measured rain rate are developed. Predicted and measured values may then be compared by a researcher to evaluate system operation and assess the importance of the event data. A discussion of the use of sampled data and these comparisons concludes the report. / Master of Science

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"July, 2003" / Includes bibliographical references (leaves 177-183) / xxii, 183 leaves : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, School of Chemistry and Physics, Discipline of Physics and Mathematical Physics, 2004

Many applications of remote sensing in agriculture have been developed since 60 years but mostly since the launch of Landsat 1 in 1972. With time, improvements in spatial, spectral and temporal resolution have been made and generated a resurgence of remote sensing popularity. Combined with agricultural systems modelling, remote sensing data such as weather radar measurements can help to obtain an accurate tool in real-time for agricultural decision-makers. Indeed, precipitation and relative humidity (RH) could become available for the agricultural decision-makers using the McGill Doppler S-band radar. At present, precipitation measurements are available with a spatial resolution of 1 km up to a range of 240 km and RH data could be available with a resolution of a few kilometres up to a range of 40 km. Both weather variables could be available with a time scale of 5 min if requested. These measurements would compensate for the actual lack of a dense weather station network prevailing in southern Quebec. / So far, the reliability of weather radar measurements has been tested by the scientific community for precipitation data but has never been tested for the RH data. In this study, a comparison between RH measured at three weather stations and RH calculated from weather radar measurements was made using consecutive time interval of 240 hours in 1997 and 336 hours in 1998. A valid t-test designed for simple linear regression analysis with two time series as dependent and explanatory variable, and based on the first-difference ratios (FDR) of the time series clearly showed that RH calculated from radar measurements is comparable to the one measured at weather stations. Thereafter, the possibility of integrating weather radar measurements (precipitation and RH) in a geographic information system (GIS) to map the variability of a crop disease was verified. Results indicated the potential of weather radar measurements in agriculture.

Bibliography: leaves 163-172 / x, 173 leaves : ill ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, 1986

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Weather radars are increasingly used for the study of clouds, understanding the precipitation systems and also for forecasting very short range weather (one hour to a few hours). Now, Doppler Weather Radar (DWR) data are available in India and it is possible to study cloud properties at fine temporal and spatial scales. Radar is a complex system and calibration of a radar is not an easy job. But derived cloud properties strongly depend on the absolute magnitude of the reflectivity. Therefore, there is a need to check how data from two or more radars compare if they measure a common volume. Chennai and SHAR radars are within 66 km from each other, and the data collected during their calibration and intercomparison experiment in 2006 enables the comparison of their reflectivity(Z) values. Individual reflectivity are compared after plotting SHAR versus Chennai in a scatter plot. Fitting a least square linear best fit line shows that the intercept has a value around 6 dBZ and the slope of the line is 1.06. Thus, there is a trend as well, and the difference between the two radars increase with Z, and for Z around 40 dBZ (for SHAR DWR), the difference between the two is around 8.5 dBZ. Visual intercomparison also validated the results. Data from the two radars are compared with Precipitation Radar (PR) data on board TRMM satellite. TRMM radar slightly overestimates compared to Chennai radar above the range of 30 dBZ. After standardized, SHAR data is used for understanding the evolution and propagation of cloud systems. The diurnal variation in convection is strong in the study region, with increase around local evening and morning and weakening around midnight except in December. Average liquid water content in the clouds is about 0.5 gm/m3. There is some seasonal dependence but no clear dependence on cloud size. Smaller systems of May have more liquid water content compared to larger ones. For nowcasting vertically projected maximum reflectivity is taken. A threshold of 30 dBZ is set to identify the cloud systems. Both center of gravity tracking (CG) and cross-correlation (CC) methods are used to track them. Frequent merging and splitting is common in the clouds which makes storm tracking difficult. Tracking by CC is giving better result than that by the CG method in the case of large systems (i.e., clusters). For smaller systems (individual cloud systems), CC method gives better result than CG method but not as good as cluster.