Thesis (Ph. D.)--University of Oklahoma, 1998. / Includes bibliographical references (leaves 247-257).

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 148-160).

Thesis (Ph. D.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains vii, 136 p. : ill. (some col.). Includes abstract. Includes bibliographical references.

Thesis (Ph. D.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains vii, 105 p. : ill. Includes abstract. Includes bibliographical references (p. 98-105).

Thesis (M.S.)--Ohio State University, 2009. / Title from first page of PDF file. Includes vita. Includes bibliographical references (p. 125-128).

Atmospheric convection can result in weather conditions capable of making a pilot lose control of the aircraft. An example of such weather is thunderstorms. This study was made to evaluate weather forecasts for aircraft pilots during days of convective activity. For this purpose, a literature study was conducted to identify the weaknesses of numerical weather prediction models in their handling of convection, and limita-tions of aviation targeted forecast products were addressed. The study also includes remarks and insights received from experienced aviation forecasters on the subject. The study is limited to Sweden and the forecasts made by the Swedish Meteoro-logical and Hydrological Institute (SMHI). Four main results have been found. Firstly, the numerical weather prediction models in use in Sweden today are insufficient for making detailed forecasts of convection. Secondly, the required additional input from human forecasters is restrained by the imperfections of so-called convective indices. Thirdly, convection forecasts issued more than a few hours ahead of time cannot be trusted as being accurate. Finally, the forecast products available to pilots were found to lack valuable information about convective events. It was concluded that pilots cannot access enough information from these forecast products to be able to plan an altogether safe flight through convective weather beforehand. Hence, it is important to improve forecasts of convection for the purpose of enhancing aviation safety. / Konvektion i atmosfären kan medföra väder med faror som gör att en pilot riskerar att tappa kontroll över sitt flygplan. Åskoväder är ett sådant exempel. Denna studie gjordes för att uppskatta nyttan av väderprognoser för piloter under dagar med konvektiv verksamhet. För att åstadkomma det gjordes en litteraturstudie för att identifiera svagheterna i hanterandet av konvektion hos numeriska väderprognos-modeller. Begränsningar hos prognosprodukter speciellt inriktade på flygverksamhet har också tagits upp. Dessutom innehåller studien iakttagelser från erfarna flyg-inriktade prognosmeteorologer. Studien begränsar sig till Sverige och de prognoser som utfärdas av Sveriges Meteorologiska och Hydrologiska Institut (SMHI). Fyra huvudsakliga resultat erhölls. Det första var att de numeriska väderprognos-modeller som används i Sverige idag är otillräckliga för att skapa pålitliga prognoser för konvektion. För det andra upptäcktes att behovet av en ytterligare analys från prognosmeteorologer försvåras av brister hos så kallade konvektionsindex. Den tredje upptäckten var att prognoser som utfärdas mer än ett par timmar i förväg inte är att lita på. Till sist framställdes att bristerna i de prognosprodukter som finns tillgängliga för piloter saknar en stor del värdefull information angående konvektiv verksamhet. Det fastslogs att piloter inte får tillgång till tillräckligt mycket information från dessa produkter för att kunna planera en säker flygning genom konvektivt väder. Det är således angeläget att förbättra prognoser för konvektion i syfte att öka flygsäkerheten.

Although managers rate concerns about being seen as committed disclosers as an important consideration in their voluntary disclosure decisions, prior research has paid limited attention to how investors view commitment to disclosure. This study experimentally tests two competing perspectives relating to how managers' commitment to disclosure and prior forecast accuracy jointly influence managers' forecasting credibility. The first perspective (the normative perspective) draws on economic theory and the second perspective (the omission bias perspective) draws on theory from psychology. The normative perspective suggests that commitment to disclosure and prior forecast accuracy will independently influence managers' forecasting credibility. In contrast, the omission bias literature suggests that the influence of commitment to disclosure on managers' forecasting credibility depends on managers' prior forecast accuracy. In other words, the normative perspective suggests two main effects, whereas the omission bias perspective suggests a commitment to disclosure x accuracy interaction. To test the competing predictions relating to the joint impact of commitment to disclosure and prior forecast accuracy on managers' forecasting credibility, I conduct an experiment. Results of this experiment support the omission bias perspective. Participants in the role of investors rate more (less) committed managers as more (less) credible, but only when they are also accurate. When managers are inaccurate, however, this relationship reverses. That is, more committed managers are viewed as less credible relative to their less committed peers. These results suggest that managers' concerns about commitment to disclosure are indeed valid, but only when they are accurate. When managers are less accurate, commitment to disclosure hurts, rather than helps, managers' credibility. Participants' valuation judgments as well as their judgments relating to a current disclosure are positively associated with their judgments of managers' forecasting credibility, suggesting that their assessment of managers' credibility may have significant valuation consequences. This study contributes to the voluntary disclosure literature and has implications for managers who provide earnings forecasts and for investors who use these forecasts in their investment decisions. / text

Individual differences in subjective response to alcohol have been implicated as a risk factor for the development of alcohol use disorders. There are, however, a variety of ethical, legal, and practical considerations surrounding alcohol administration studies which limit the extent to which this marker can be used to identify those believed to be at greater risk. The current research contains two related laboratory studies with the overall goal of identifying valid and reliable correlates of individual differences in subjective response to alcohol that can be used to discern emerging adults at greater risk for problematic drinking. Study 1 evaluated the associations between the actual subjective experience of a moderate dose of alcohol (BAC .08%) and three domains of potential correlates: anticipated subjective response based on a hypothetical drinking scenario (targeted .08% BAC); response to other physiological and perceptual challenges (e.g., CO₂ challenge, spinning challenge); and indices of cognitive impairment implicated as risk factors for the development of alcohol use disorders. Study 2 examined each of these domains in relation to transitions in heavy drinking from high school to college to determine whether they were associated with changes in relative risk during this developmental period. Overall, the results provide support for the utility of examining individual differences in subjective response to alcohol based on a hypothetical drinking scenario. The evidence suggests that experienced drinkers are capable of reliably and accurately estimating their subjective response to alcohol, that these anticipated effects are distinct from general beliefs about the effects of alcohol on behavior (i.e., alcohol expectancies), and that they are associated with patterns of drinking in emerging adults. There was little evidence to suggest that individual differences in subjective response to alcohol were associated with subjective response to other physiological or perceptual challenges, or patterns of cognitive impairment previously shown to be related to an increased risk for alcohol dependence. The results of the current study support the utility of using measures of anticipated subjective response as a proxy for individual differences in subjective response to alcohol when the administration of alcohol is either not appropriate or feasible. / text

Climate in Hong Kong is very likely to be modified due to global climate change. In this study the output of General Circulation Models (GCMs) was statistically downscaled to produce future climate projections for the time periods 2046 –2065 and 2081 –2100 for Hong Kong. The future climate projections are based on two emission scenarios provided by the Intergovernmental Panel on Climate Change (IPCC). The emission scenarios, A1B (rapid economic growth with balanced energy technology) and B1 (global environmental sustainability), make assumptions on future human development, and the resulting emissions of greenhouse gases. This study established a method to evaluate GCMs for use in statistical downscaling and utilised six GCMs, selected from the 3rd phase of the Coupled Model Intercomparison Project (CMIP3). They were evaluated based upon their performance in simulating past climate in the southeast China region on three aspects: 1) monthly mean temperature; 2) sensitivity to greenhouse gases and 3) climate variability. Three GCMs were selected for statistical downscaling and climate projection in this study. Downscaling was undertaken by relating large scale climate variables, from NCEP/NCAR reanalysis, a gridded data set incorporating observations and climate models, to local scale observations. Temperature, specific humidity and wind speed were downscaled using multiple linear regressions methods. Rain occurrence was determined using logistic regression and rainfall volume from a generalised linear model. The resultant statistical models were subsequently applied to future climate projections. Overall, all three GCMs, via statistical downscaling, show that daily average, minimum and maximum temperatures, along with specific humidity, will increase under future climate scenarios. Comparing the model ensemble mean projections with current climate (1981 –2010), the annual average temperature in Hong Kong is projected to increase by 1.0 °C (B1) to 1.6 °C (A1B) in 2046 –2065, and by 1.4 °C (B1) to 2.2 °C (A1B) in 2081 –2100. Furthermore, the projections in this study show an increase of high temperature extremes (daily average temperature ≥ 29.6 °C), by three to four times in 2046 –2065 and four to five times in 2081 –2100. The projections of rainfall indicate that annual rainfall will increase in the future. Total annual rainfall is projected to increase by 4.9% (A1B) to 8% (B1) in 2046 –2065, and by 8.7% (B1) to 21.5% (A1B) in 2081 –2100. However, this change in rainfall is seasonally dependent; summer and autumn exhibit an increase in rainfall whilst spring and winter exhibit decreases. In order to test one possible impact of this change in climate, the downscaled climate variables were used to estimate how outdoor thermal comfort (using the Universal Thermal Comfort Index) might change under future climate scenarios in Hong Kong. Results showed that there will be a shift from 'No Thermal Stress' towards 'Moderate Heat Stress' and 'Strong Heat Stress' during the period 2046 –2065, becoming more severe for the later period (2081 –2100). The projections of future climate presented in this study will be important when assessing potential climate change impacts, along with adaptation and mitigation options, in Hong Kong. / published_or_final_version / Geography / Doctoral / Doctor of Philosophy

Since the atmosphere is a chaotic system, small errors in the initial condition of any numerical weather prediction (NWP) model amplify as the forecast evolves. To estimate and possibly reduce the uncertainty of NWP associated with initial-condition uncertainty (ICU), ensemble forecasting has been proposed which is a method of, differently from the traditional deterministic forecasting, running several model forecasts starting from slightly different initial states. In this dissertation, the impact of ICU and short-range ensemble forecasting (SREF) on quantitative precipitation forecasts (QPFs), as well as on sea-level cyclone position and central pressure, is examined for a case of explosive cyclogenesis that occurred over the contiguous United States. A limited-area model (the PSU/NCAR MM4) is run at 80-km horizontal resolution and 15 layers to produce a 25-member, 36-h forecast ensemble. Lateral boundary conditions for the MM4 model are provided by ensemble forecasts from a global spectral model (the NCAR CCM1). The initial perturbations of the ensemble members possess a magnitude and spatial decomposition which closely match estimates of global analysis error, but they were not dynamically-conditioned. Results for 80-km ensemble forecast are compared to forecasts from the then operational Nested Grid Model (NGM), a single 40-km MM4 forecast, and a second 25-member MM4 ensemble based on a different cumulus parameterization and slightly different initial conditions. Acute sensitivity to ICU marks ensemble QPF and the forecasts of cyclone position and central pressure. Ensemble averaging always reduces the rms error for QPF. Nearly 90% of the improvement is obtainable using ensemble sizes as small as 8-10. However, ensemble averaging can adversely affect the forecasts related to precipitation areal coverage because of its smoothing nature. Probabilistic forecasts for five mutually exclusive, completely exhaustive categories are found to be skillful relative to a climatological forecast. Ensemble sizes of --, 10 can account for 90% of improvement in probability density function. Our results indicate that SREF techniques can now provide useful QPF guidance and increase the accuracy of precipitation, cyclone position, and cyclone's central pressure forecasts. With current analysis/forecast systems, the benefit from simple ensemble averaging is comparable to or exceed that obtainable from improvement in the analysis/forecast system.