Graduation date: 1955

Thesis (M.S.)--Oregon State University, 1984. / Typescript (photocopy). Includes bibliographical references (leaves 88-90). Also available on the World Wide Web.

Stochastic weather generators create multiple series of synthetic daily weather (precipitation, maximum temperature, etc.), and ideally these series will have statistical properties similar to those of the input historical data. The synthetic output has many applications and for example, can be used in sectors such as agriculture and hydrology. This work used a ?hybrid? weather generator which consists of a parametric Markov chain for generating precipitation occurrence and a nonparametric k-nearest neighbor method for generating values of maximum temperature, minimum temperature, and precipitation. The hybrid weather generator was implemented and validated for use at 11 different locations in the Southeastern United States. A total of 36 graphic diagnostics were used to assess the model?s performance. These diagnostics revealed that the weather generator successfully created synthetic series with most statistical properties of the historical data including extreme wet and dry spell lengths and days of first and last freeze. Climate forecasts are typically provided for seasons or months. Alternatively, process models used for risk assessment often operate at daily time scales. If climate forecasts were incorporated into the daily weather input for process models, stakeholders could then use these models to assess possible impacts on their sector of interest due to anticipated changes in climate conditions. In this work, an ?ad hoc? resampling approach was developed to create sets of daily synthetic weather series consistent with seasonal climate forecasts in the Southeastern United States. In this approach, the output of the hybrid weather generator was resampled based on forecasts in two different formats: the commonly used tercile format and a probability distribution function. This resampling approach successfully created sets of synthetic series which reflected different forecast scenarios (i.e. wetter or drier conditions). Distributions of quarterly total precipitation from the resampled synthetic series were found to be shifted with respect to the corresponding historical distributions, and in some cases, the occurrence and intensity statistics of precipitation in the new weather series had changed with respect to the historical values.

Thesis (M.S.)--University of Montana, 2006. / Mode of access: Internet. Title from title screen. Description based on contents viewed Feb. 13, 2007. Includes bibliographical references (p. 118-121).

Hourly precipitation data from thirty cooperative stations in Kentucky from 1965 to 1996 were used to determine the diurnal distribution of precipitation rates. Descriptive summaries for the diurnal distribution for each climate division in Kentucky and for Kentucky as a whole were calculated. In each case, the trends were similar. Precipitation rates increased into the afternoon and then decreased until sunrise. A stochastic model was developed to estimate mean seasonal precipitation rates in Kentucky by using regional and localized parameters. More than half of the variation (r2 = 0.57) in precipitation rates can be explained by the following variables: 1) Distance away from the moisture source, the Gulf of Mexico; 2) Roughness of topography; 3) Degree of urbanization. Precipitation rates decrease in a northeasterly direction across Kentucky as air moves farther away from the Gulf of Mexico along its path of migration. The maritime tropical air mass migrating out of the Gulf of Mexico loses its water vapor over its path of migration. As a result, less water vapor is available for precipitation processes in areas farther away. As a precipitation event moves over rougher terrain and more urbanized areas, precipitation rates decrease as well. A rougher terrain absorbs more solar radiation because it has more surface area. An urbanized area absorbs more solar radiation because of the urban structures (e.g., buildings, asphalt, roofs). As a result, both will radiate more heat causing the air to be buoyant at the surface to either enhance convection or increase vertical air motions. Increased vertical air motions will cause an increase in air resistance acting upon precipitation falling, thereby, causing a decrease in the amount falling to the surface per hour.

An agroclimatic risk assessment for agricultural production across the Canadian prairie provinces has been assembled to address challenges related to frost, heat units, and moisture. Based on 30 years of daily climate data from 1971 though 2000 from 230 climate stations, the assessment provides a series of risk maps depicting the likelihood to achieve certain thresholds of frost dates or durations, heat unit accumulations, growing season rainfall, crop water demand (CWD), and crop water deficits. Maps for each parameter provide a spatial representation of 50%, 25%, and 10% risks and the coefficient of variation. / October 2007

Climate Change Effects and Water Vulnerability in the Molalla Pudding River Basin, Oregon, USA

The dragonfly communities in Sweden may be affected in many ways. Loss of habitats, habitat alteration or even environmental toxins might have a negative impact on the communities. A new threat to the communities and to the species in general is climate change. In this study I examined whether the dragonfly composition had changed in an area in central Sweden between 1997 and 2010. I did a nestedness matrix to see if the dragonfly composition (only using partivoltine species) was more or less nested in 2010 than it was in 1997, i.e. if there was more unexpected species recorded in the area. I also looked at the surrounding of the lakes and whether the species were considered to be generalist species or specialist species. I found that the dragonfly composition had changed during these 13 years and that the composition was more nested in 1997 than in 2010, i.e. there was more unexpected species in the 2010 survey. I also recorded seven new species for the area and that six species had disappeared. Six species had gone from being generalists to being specialists. The surroundings had not changed significantly and I thus see climate change as a possible explanation to these changes.

Understanding the dynamical relationships between low frequency forcings and the interannual variability of the Earths atmosphere is critical for accurate extended-range forecasts and climate prediction. This thesis investigates possible dynamical couplings between the stratosphere and troposphere by implementing lagged multivariate linear regressions. These regressions were chosen to untangle the separate responses of distinct atmospheric forcings upon zonal mean climate variability. The regressions incorporate monthly meteorological data with indices of four dominant forcings of low frequency atmospheric variability: the El Nino Southern Oscillation, the Quasi-Biennial Oscillation, the 11-year solar cycle, and volcanic activity. The analysis uses data from both the NCAR/NCEP and ECMWF reanalyses for two distinct time periods to expose possible satellite measurement influences. One period consists of all data since 1958, while the other period includes only data since 1979, a period of extensive satellite observations. Diagnostic tools include piecewise potential vorticity inversions, an assessment of anomalous Eliassen-Palm fluxes, stream function analyses, and general circulation model diagnoses. The examination reveals robust patterns associated with each forcing, consistent with existing theories in climate dynamics of the coupling mechanisms between the stratosphere and the troposphere. To better predict climate variability, however, the next step is to investigate the nonlinearities known to play an important role in this system.

This study examined the variability in the observed relationship between safety climate and injuries in the extant literature by meta-analytically examining possible moderators of the safety climate-injury relationship at both the individual and group levels of analysis. Hypotheses were posited regarding the effects of six moderators: study design (i.e., retrospective or prospective), the time frame for gathering injury data, the degree of content contamination and deficiency in safety climate measures, the source of injury data (i.e., archival or self-report), and the operationalization of injury severity. Results revealed that the safety climate-injury relationship is stronger at the group level (? = -.23) than at the individual level of analysis (? = -.18). Meaningful moderators included the time frame between the measurement of safety climate and injuries for prospective group-level studies, safety climate content contamination for group-level studies, and safety climate content deficiency for individual-level studies. Longer time frames for gathering injury data and safety climate content deficiency were found to decrease effect sizes while content contamination was associated with stronger effect sizes. Methodological recommendations are proposed for future research of the safety climate-injury relationship including prospective longitudinal study designs with data collected and analyzed at the group-level of analysis and injuries operationalized at a greater level of severity.