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

Palaeoclimate reconstruction is of paramount importance because the more we know about the patterns of past variability the better we understand the present climate. Precipitation is a key climate variable shaping the culture and economy of China. However, few studies are concerned with past changes in precipitation. The existing few are either reconstructed by one reconstruction approach or based on a single proxy, limiting reconstructions to a small region and a short period of time. The study presents the first high-resolution multi-proxy palaeoprecipitation reconstruction of China as a whole. Proxies used in the study are of annual-to-decadal resolution, mainly including historical written evidence, tree-ring chronologies and stable isotopic records. In accordance with the principle of “uniformity in the nature”, about 80 proxy series extend the precipitation records as far back in time as 2,000 years ago when there was a significant increase in natural proxy and documentary records of climate all over China. The top three popular reconstruction approaches are borrowed from multi-proxy temperature reconstructions to reconstruct the palaeoprecipitation. A pioneering attempt is taken to evaluate and compare these approaches in reconstructing precipitation over a long term in a large scale. The three common practices are respectively simple average, composite-plus-scale method, and covariance-based climate field reconstruction. All three reconstruction methods are modified catering to the unique characteristics of precipitation, especially in terms of its large spatial variance. Local reconstructions are carried out first before a national index in reconstructed. Though based on the same documentary and natural proxies, three reconstruction approaches adopt different rationales to decipher the precipitation variability, represented by different statistical models. Each model is assessed by conventional statistics and cross-compared. These models are found complementary to each other while the common shared among three models are considered the closest to the true precipitation condition. Though geographically biased to Eastern China, historical documents still capture the most inter-annual to multi-centennial variations in palaeoprecipitation, indicating the possible control of Asian Monsoon climate on China’s overall precipitation. Tree-ring widths preform worst due in part to the attribute of strong locality. Each reconstruction approach turns out to have its own strength and weakness. Three major falls at multi-centennial timescale are detected in most reconstructed precipitation series, which are at AD600-800, AD1000-1300 and AD1500-1700. Spectral analyses demonstrate a rhythmic pattern of around 400-500 years for all reconstructions. When the proxies are not extrapolated, an additional cycle of 700-800 years is significant in precipitation variability over the past 2,000 years. A cross-comparison with European reconstructions show a high agreement in precipitation variability for the past two millennia, leading to the suspect of dry Medieval Warm Period and wet Little Ice Age over the whole Eurasia. / published_or_final_version / Geography / Master / Master of Philosophy

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

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This work was carried out to investigate the mechanisms of solid-solid separation in electrostatic precipitators. The separation of mixture of pure compounds from each other and the components of an industrial dust has been studied in a wire-and-duct type laboratory-scale electrostatic precipitator. Particle size distribution affected the separation most, but both the dielectric constant and electrical resistivity of the dust can be important. Operating voltage and air velocity in the precipitator also affected the separation along the precipitator length. The SRI computer model of precipitator performance gave reasonable predictions of separation under conditions of negligible re-entrainment. / An apparently unique relationship between separation and recovery was experimentally observed with components which do not re-entrain appreciably; a similar behaviour is theoretically predicted from the Deutsch Equation of collection efficiency or the SRI model.

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. [...]

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This dissertation examines the causes of variations in tropical cyclone precipitation (TCP) and the relationship between TCP and river discharge in Texas. The dissertation has three major objectives: 1) investigate the spatial and temporal variations of TCP in Texas from 1950 to 2009, 2) construct seasonal statistical forecast models for TCP and identify the primary factors controlling TCP in Texas, and 3) examine how TCP contributes to the extreme precipitation and river discharge in watersheds surrounding the city of Houston. An automated extraction method is developed to identify TCP from 60 years of precipitation data from Cooperative Observing Network gauges. Texas receives an average of 123.5 mm of TCP/year, which is ~13% of the state’s mean annual precipitation. September is the month with the most TCP, and it receives an average of 18.5 mm. Long-term trends (>50 years) in TCP are evident at some locations, but there are no statistically significant long-term trends in aggregated annual TCP metrics. Despite the lack of long-term trends, TCP metrics show some spectral power at periodicities of ~2-3 years, ~5-8 years, and >10 years. Areas within 400 km of the coast have higher risk of extreme daily TCP (>100 mm), but inland Texas can also occasionally experience extreme TCP. In some areas in southeastern Texas the probability of receiving >100 mm of daily TCP in any given year is ~0.30 (i.e., daily TCP exceeds 100 mm, on average, 1 out every 3 years). The best seasonal forecast models of TCP can explain >20% variance based on three or fewer predictors. ENSO is the most important control of TCP in Texas. La Niña, the major driver in all TCP models, reduces the vertical wind shear in the Caribbean and tropical Atlantic and therefore generates more precipitating storms in Texas. Maximum Potential Velocity (MPV) in the Gulf of Mexico and vorticity in the Atlantic Hurricane Development Region (MDR) are also important predictors of TCP and they can increase the R2 by ~0.2. The negative relationship between MPV and vorticity with the TCP are due to the fact that TCs with weaker wind speed and slower translation speed tend to contribute much more to both extreme and total TCP. Sea level pressure in the Gulf of Mexico, SST in the Caribbean and North Atlantic Oscillation are also identified as useful predictors in some of the models. TCP is associated with many of the annual maximum discharge events in watersheds near Houston. Urbanization can significantly increase river discharge generated by TCP. Both the annual maximum discharge and 90 percentile discharge have increased significantly in many watersheds in Houston. Although no long-term trend can be observed in the TCP and TCP-related extreme discharge, there may be an increased risk of floods from TCP because of the statistically significant increases in annual maximum discharge that have been observed. There are also increased uncertainties in flood risk because extreme precipitation, including TCP, is projected to become more variable in the future.

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