No description available.

No description available.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 180-190).

Thesis (Ph. D.)--University of Oklahoma, 1993. / Includes bibliographical references (leaves 189-195).

Thesis (Ph.D.)--University of Oklahoma, 1987. / Bibliography: leaves 180-185.

Thesis (M. Phil.)--University of Hong Kong, 1976.

Atmospheric oscillations, which mostly associate with climate patterns, have great influences on global climate variables, and they usually lead to extreme climate conditions and events, which cause lots of adverse impacts on our socioeconomic statuses. This study aims to identify the influence of climate patterns on the global precipitation anomaly. Four major climate patterns are investigated, and they are El Niño/La Niña–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Arctic Oscillation (AO) and Antarctic Oscillation (AAO). This study adopts the NINO3.4, DMI, AO index and AAO index to represent the climate patterns of ENSO, IOD, AO and AAO, respectively. The other research data used include precipitation data from the Global Precipitation Climatology Project (GPCP). The multiple linear regression method is used to study the relationships between the climate patterns and the global precipitation anomalies. Then, the precipitation anomalies all over the globe is modeled by those four climate pattern indexes. The signs and magnitudes of the regression coefficients for those indexes can reflect the relations of the climate patterns with the precipitations and their strength. Part of the results from the regression analysis matches well with the general understanding about the impact of those climate patterns. The influences of the climate patterns can be explained by their impact on the Walker circulation, monsoon system, jet stream, convection and atmospheric moisture transport. This suggests that the regression method is able to represent the teleconnection between the climate patterns and precipitation anomalies. Further, for each calendar month of the year, the variations of the relationships between precipitation anomalies and climate indexes show that the influences of the climate patterns on the precipitation anomalies vary throughout the year. The variations are mainly due to the different general circulation patterns in different seasons. The strengths of the relations also vary, and they mostly change with the strength of the climate patterns. Usually the stronger the climate pattern, the stronger the relationship. The variation of the heating from the sun also explain some of the seasonal variations of the relationships. Overall, this study indicates that the precipitation anomalies in Asia near the tropics and subtropics are significantly related to ENSO and IOD. Precipitation anomalies in Australia show significant relation with ENSO, IOD and AAO. AO has the greatest influence on the precipitation anomalies over Europe. For Africa, IOD and AAO have large influence on the precipitation anomalies on the east part and south part respectively. The south part of the North America is mainly affected by ENSO, while AO is dominant over the regions located at higher latitudes. ENSO is the dominant climate pattern affecting the precipitation anomalies in South America, and further, AAO and IOD also show some significant influences. / published_or_final_version / Civil Engineering / Master / Master of Philosophy

Instruments have been designed and assembled for the summation of areas of precipitation on a weather radar map. One technique uses the output from a system scanning the map to deflect the trace on the cathoderay tube of an oscilloscope in discrete steps depending on the intensity of the precipitation. This trace is photographed. Since the brightness of the trace is constant, exposure is a function of scan-time. Because scan-time is proportional to area scanned, the density on film resulting from this exposure is a function of area. Densitometry then yields these areas. A more convenient technique makes use of the fact that scan-time is proportional to the number of cycles of the a.c. output from the scanner, and areal summation is accomplished with an electronic counter. Examples of measurements are presented, and their meteorological value is discussed. [...]

No description available.

The intensity returns obtained by a radar from precipitation are well known to fluctuate violently in space and time. We present a systematic study of the resolution dependence time series with overlapping time resolutions spanning 10 orders of magnitude (0.77 ms to 4 months), of the fluctuating radar echo from precipitation. The results undermine the current assumptions of homogeneity of rainfield at scales smaller than the radar resolution, due to Marshall and Hitschfeld (1953), by showing that the only length scales identifiable in the time series are those of the radar pulse volume, the wavelength, and a very small inner scale of the order of millimeters. An analysis of the multiscaling nature of the time series of echo fluctuations reveals multiscaling behaviour at scales down to the resolution or pulse volume scale. Since there are no a priori scales in the rainfield we proceed to model the fluctuating radar echo by assuming a multiscaling model of rainfield variability which extends to sub-resolution scales. A systematic analysis of the statistical behaviour of computed reflectivities from this variability gives a full statistical description of reflectivity originating from multiscaling variability, and solves the scalar multifractal radar observer's problem. Computation of time series of reflectivities from a time-space representation of this variability reveals quantitative and qualitative behaviours consistent with those of observed echo fluctuation time series. We conclude that a multiscaling model of the rainfield which extends to the smallest scales of the rainfield is consistent with observation.