Includes bibliographical references / A good understanding of seasonal climate and the limit to which it can be predicted is crucial in addressing various socio-economic challenges in Africa. However, how to improve the capability of the dynamical models of the climate system in reproducing the regional seasonal climate variability and in replicating the role of various atmospheric circulation anomalies on the regional variability remains a major challenge. Thus far, understanding of seasonal climate over these regions, as well as the ability of climate models to predict them, has focused on the agreement of simulations of dynamical models of the climate system, rather than considering outliers as potentially vital contributors to understanding and predictability. This thesis uses discrepancy in a large ensemble of climate simulations as a tool to investigate variability in dominant seasonal rainfall and temperature patterns (i.e. classes) over West and Southern Africa, to examine the capability of climate models in reproducing the variability, and to study the predictability of the seasonal climates over South Africa. The dominant classes of variability (of rainfall and maximum temperature fields) in both regions are examined based on the Self-Organizing Map (SOM) classifications. The sequences in which each class occurs cannot be linked simply to a single common index of global scale atmospheric circulation anomalies, implying that the chaotic regional atmospheric circulations that modulate the global scale modes of variability are indispensable. The climate model examined adequately reproduces the dominant classes of seasonal climate over West and Southern Africa.

Temperature, pressure, and relative humidity within Jinapsan Cave on Guam were compiled and analyzed over a five-month period to gain a better understanding of this environment. Temperatures within the cave hover around ~26°C with no apparent influences except the mean annual temperature, with humidity values over 90%. There is high fidelity between outside and internal air pressures indicating no pressure differential exists and pressure changes are a result of kinematic wave flow. A mild correlation exists between a cave speleothem’s drip rate and outside pressure. The cave’s tidal pool compared to oceanic tides show a lag of 1-2 hours and amplitude dampening. The tidal pool’s temperature is 25.7°C, signifying no mass transfer of water occurs. Tropical cave studies are rare, but are important for paleoclimate research using cave speleothems as proxies. This study determined cave meteorological factors that affect speleothem development to allow for more accurate paleoclimate studies.

One of the greatest hazards from hurricanes is the flooding due to storm surge. Emergency managers traditionally plan for storm surge by looking at the worst possible impact and design their plans accordingly. This is a safe course of action, but can also be a wasted expense if the worst case does not occur. Risk-based planning is a way to incorporate the likelihood or probability of an impact occurring into emergency planning. With respect to storm surge, though, there is very little information regarding probability of occurrence. This research uses data from a commonly accepted storm surge model, SLOSH from the National Weather Service, to develop probabilities of impact. The process and products are prototypes utilizing data from the 2007 SLOSH model run for the New Orleans basin. Products developed include a map of probability, probabilities of exceedance, and a list of model storms that generate surge at given locations.

Daily temperature variations across an area can often be attributed to differences in land use/land cover (LULC). This study focuses on the relationships between the diurnal temperature ranges (DTRs) of 145 weather stations, classified as urban, agriculture, evergreen forests, deciduous forests, pine forests, and mixed forests. Paired samples t-tests were employed to test for significant DTR differences due to LULC type, season, and air mass type. Conflicting with previous research, agricultural areas reported the lowest DTRs, which may be due to the vegetation or to other physiographic variables. The forest types showed very few significant DTR differences. All of the LULC types experienced an annual bimodal DTR pattern, with peaks in April and October. Results of this study show that air mass has the largest influence on DTR (over LULC and season), therefore, the annual variability of air mass occurrence is most likely cause of the bimodal pattern.

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Predicting wildfire activity has been a major concern for fire weather forecasters and fire managers in recent decades. Identifying mid-tropospheric circulation patterns that are conducive to higher rates of spread has been widely employed as a predictive tool. This study classifies circulation patterns at the 500 mb level for 3865 fire days from 1970 through 2004 in the central hardwood region of the Midwestern United States. Several circulation patterns were identified that are associated with enhanced fire activity relative to other patterns. All patterns with elevated fire activity were associated with either flow from dry air source regions, or patterns that placed the region on the periphery of a high pressure system. Weather variables associated with each type of circulation pattern were also analyzed and were found to vary among patterns. Circulation patterns with greater fire activity were identified as being drier than patterns with lesser activity. The findings of this study provide crucial information to fire managers and forecasters, which can help them achieve their ultimate goal of minimizing loss of life and property.

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Inland Antarctic lakes are among the harshest environments in the world for life to inhabit. Ice cover causes low levels of light and temperature, and prevents mixing by wind, resulting in low nutrient levels and truncated food chains. Such ecosystems are widely regarded as sensitive indicators of climate change, and it is therefore useful to build up a strong physical and biological understanding of them. In 2003 an automatic probe (Palethorpe et al. 2004) was deployed on Crooked Lake, an ultra-oligotrophic freshwater lake in Eastern Antarctica which has been the subject of limnological studies since 1990. The probe measured several physical parameters in, above, and below the ice layer at temporal resolutions of up to one measurement every five minutes. A physics-based model was developed to simulate the growth and melt of the lake ice over time, considering all heat and radiation fluxes. Meteorological data were used as inputs to the model, with ice thickness the main output. The model fitted Crooked Lake ice thickness well, despite having narrow mechanistic constraints on parameter values. A number of simpler models were also developed which provided comparable goodness of fit, and illustrated that air temperature is the dominant variable in such systems. The issue of optimum complexity was addressed using model selection criteria, and some criteria selected a simple model over the physics-based model. However when both were subjected to long-term model runs with superimposed global warming scenarios, the simple model was shown to be unstable. In addition, a 1992-93 biological dataset was analysed. Populations were shown to exhibit a significant annual cycle, but no significant smaller-scale population oscillations, suggesting that higher sample rates were required to identify such phenomena. A prototype procedure was developed using simulated data to inform field sampling strategies, in the aim of identifying the population dynamics that are predicted by many plankton models.

The variability of atmospheric circulation is reconstructed over the last two centuries from surface pressure observations extending into the 18th and 19th centuries at 51 locations across Europe. Daily observations from London and Paris exist for 1697-1706; these are analyzed and compared to modem data. The monthly pressure data have been rigorously checked to ensure compatibility with modem observational standards. The pressure series have undergone relative homogeneity tests using a technique developed to deal specifically with these data, and the results compared to those obtained using well-established homogeneity methods. The method developed here was shown to be the most appropriate, particularly for the earlier data. Empirical orthogonal function (BOF) analysis was used to test the stability of circulation patterns over different periods. The three most important modes of variation were found: EOF 1) describing the overall covariance of pressure; EOF 2) the strength of the zonal flow over Europe; and EOF 3) the degree of cycloncity or anti-cyclonicity in the eastern North Atlantic. The ability of the sparser network of 20 stations available from the early 19th century to adequately recover the patterns and variability of the full network is demonstrated. Time series of the North Atlantic Oscillation, the mid-latitude westerly winds, and an index representing the strength of the westerly air flow between London and Paris have been constructed and extend back to the 18th century, as well as the period 1697-1706 for Paris and London. Correlations between eight temperature series from western and central Europe and the circulation indices demonstrate the importance of the atmospheric circulation in determining European temperatures. Running correlations calculated over windows of 25 years reveal striking non-stationarity in circulation-climate relationships. Spectral analyses of the circulation indices suggest a shift from high-frequency oscillatory behaviour in the 19th century to lower frequency behaviour in the 20th