Thesis advisor: Jeremy Shakun / As recently measured amounts of global atmospheric carbon dioxide concentrations have risen 40% from pre-Industrial levels and will likely reach double by mid-century, climate scientists have expressed concern over the future state of the climate system, and have attempted to gauge the consequences of such a large forcing. The principal parameter for climate scientists is equilibrium climate sensitivity, which is the change in temperature following a doubling of atmospheric CO2 concentrations. Current estimates of climate sensitivity span too expansive of a range to provide a clear understanding of the magnitude of temperature changes one can expect. Therefore, I conduct many individual multivariate analyses as a means of narrowing these ranges of sensitivity and to investigate geographical distributions of sensitivity, at the very least. To do so, I analyze four major climate forcings: greenhouse gas, atmospheric dust, ice volume, and insolation. Using several multiple linear regressions, I calculate the relative weighting of each forcing in driving the temperature signal in 47 local temperature proxy records. The paleoclimate proxy records chosen span glacial cycles over the past 800 kyr. These results provide insight into the geographical distributions of the relative influences of each of the forcings, while working to constrain the range of sensitivity estimates through the weighting of the greenhouse gas forcing. Separating out the individual climate inputs allows me to conclude what percentage of climate change was caused by CO2 in the past, and by implication how much warming might be expected due to GHG forcing in the future. / Thesis (BS) — Boston College, 2015. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Earth and Environmental Sciences.

This document is a summary of research conducted to develop and apply climate analysis tools toward a better understanding of the past and future of hydroclimate variability in the state of Utah. Two pilot studies developed data management and climate analysis tools subsequently applied to our region of interest. The first investigated the role of natural atmospheric forcing in the inter-annual variability of precipitation of the Sahel region in Africa, and found a previously undocumented link with the East Atlantic mode, which explains 29% of variance in regional precipitation. An analysis of output from an operational seasonal climate forecast model revealed a failure in the model to reproduce this linkage, thus highlighting a shortcoming in model performance. The second pilot study studied long-term trends in the strength of the Great Plains low-level jet, an driver of storm development in the region’s wet spring season. Our analysis showed that since 1979 the low-level jet has strengthened as shifted the timing of peak activity, resulting in shifts both in time and location for peak precipitation, possibly the result of anthropogenic forcing. Our third study used a unique tree-ring dataset to create a reconstruction of April 1 snow water equivalent, an important measure of water supply in the Intermountain West, for the state of Utah to 1850. Analysis of the reconstruction shows the majority of snowpack variability occurs monotonically over the whole state at decadal to multidecadal frequencies. The final study evaluated decadal prediction performance of climate models participating in the Coupled Model Intercomparison Project 5. We found that the analyzed models exhibit modest skill in prediction of the Pacific Decadal Oscillation and better skill in prediction of global temperature trends post 1960.

Cultural heritage and human comfort: The issue of indoor climate in historic buildings in the twentieth centuryI

This PhD project explores the political influence of four sets of non-governmental actors upon the international politics of global warming. The forms of influence attributable to Working Group 1 of the Intergovernmental Panel on Climate Change (the body set up to advise governments on the science of climate change), the mass media's coverage of global warming, and the political involvement of both the fossil fuel lobbies and environmental groups in the policy debate on climate change, are understood via use of literatures on the dimensions of power appropriate to understanding the significance of non-state actors. The project stems from a widely acknowledged absence of a detailed understanding of the role of non-governmental organisations in international environmental politics, which extends to the international politics of global warming. The influence of each group of actors is conceptualised in different ways, so that the forms of power used to describe the various groups are not compared. Rather, the aim of the thesis is to assess what a less state-centred reading of the international politics of global warming, derived from a discussion of the role of the above actors, has to offer existing explanations. The analysis of these groups of actors sheds light on different aspects of the way the issue of climate change has been addressed at the international level. The conclusions drawn about the influence of these actors are used to critique the popular use of Regime accounts in international environmental politics that focus upon the process of institutional bargaining between states, which are argued to provide an inadequate basis for explanation of the global politics of climate change.

Changes in the physical properties of the atmosphere are caused by geographic influences and dynamic effects. The nature of the surface of the earth over which the air passes is usually the main factor in modifying the air in the lower levels of the troposphere. The ocean area of Hudson Bay in northeastern Canada presents an extensive surface for modification of air. Continental polar air crossing Hudson Bay and continuing into eastern Canada is modified not only by the underlying surface but also by the dynamic effects occurring in the atmosphere during its trajectory over these regions. The amount of modification is of major importance in the climate of the surrounding area, and in the meteorology of North American air masses. It was the purpose of this study: 1. To compute the changes in the physical properties that occur in continental polar air over Hudson Bay, Consequently, a project was undertaken to determine the amount of ice that forms on Hudson Bay in winter. The effect of the formation of ice in changing the modification of air was then studied. [...]

The first part of this thesis is an assessment of the ability of global climate models to reproduce observed features of the leading Empirical Orthogonal Function (EOF) mode of North Pacific sea surface temperature (SST) anomalies known as the Pacific Decadal Oscillation (PDO). The simulations from 13 global climate models I am analyzing were performed under phase 3 of the coupled model intercomparison project (CMIP3). In particular, I am investigating whether these climate models capture tropical influences on the PDO, and the influences of the PDO on North American surface temperature and precipitation. My results are that 1) the models as group produce a realistic pattern of the PDO. The simulated variance of the PDO index is overestimated by roughly 30%. 2) The tropical influence on North Pacific SSTs is biased systematically in these models. The simulated response to El Niño-Southern Oscillation (ENSO) forcing is delayed compared to the observed response. This tendency is consistent with model biases toward deeper oceanic mixed layers in winter and spring and weaker air-sea feedbacks in the winter half-year. Model biases in mixed layer depths and air-sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by roughly 30%. Finally, model power spectra of the PDO signal and its ENSO-forced component are “redder” than observed due to errors originating in the tropics and extratropics. 3) The models are quite successful at capturing the influence of both the tropical Pacific related and the extratropical part of the PDO on North American surface temperature. 4) The models capture some of the influence of the PDO on North American precipitation mainly due to its tropical Pacific related part. In the second part of this thesis, I investigate the ability of one such coupled ocean- atmosphere climate model, carefully initialized with observations, to dynamically predict the future evolution of the PDO on seasonal to decadal time scales. I am using forecasts produced by the Canadian climate data assimilation and prediction system employing the Canadian climate model CanCM3 for seasonal (CHFP2) and CanCM4 for decadal (DHFP1) predictions. The skill of this system in predicting the future evolution of the PDO index is then inferred from a set of historical “forecasts” called hindcasts. In this manner, hindcasts are issued over the past 30 years (seasonal), or over the past 50 years (decadal) when they can be verified against the observed historical evolution of the PDO index. I find that 1) CHFP2 is successful at predicting the PDO at the seasonal time scale measured by mean-square skill score and correlation skill. Weather “noise” unpredictable at the seasonal time scale generated by substantial North Pacific storm track activity that coincides with a shallow oceanic mixed layer in May and June appear to pose a prediction barrier for the PDO. PDO skill therefore depends on the start season of the forecast. PDO skill also varies as a function of the target month. Variations in North Pacific storminess appear to impact PDO skill by means of a lagged response of the ocean mixed layer to weather “noise”. In CHFP2, times of increasing North Pacific storm track activity are followed by times of reduced PDO skill, while the North Pacific midwinter suppression of storm track activity with decreasing storminess is followed by a substantial recovery in PDO skill. 2) This system is capable of forecasting the leading 14 EOF modes of North Pacific SST departures, that explain roughly three quarters of the total SST variance. CHFP2 is less successful at predicting North Pacific SSTs, i.e., the combination of all the EOF modes, at the seasonal time scale. 3) Besides the skill in Pacific SST, CHFP2 skillfully predicts indices that measure the atmospheric circulation regime over the North Pacific and North America such as the Pacific/North American pattern (PNA) (skillful for three out of four start seasons) and the North Pacific index (NPI) (skillful for all four start seasons). 4) CHFP2 is successful at forecasting part of the influence of Pacific SST on North American climate at the seasonal time scale. Measured by 12-month average anomaly correlation skill, in this system the PDO is a better predictor for North American precipitation (skillful for all four start seasons) than temperature (skillful for one out of four start seasons). In CHFP2, ENSO is a better predictor for North American temperature (skillful for all four start seasons) than the PDO. Both ENSO and the PDO are, however, good predictors for North American precipitation (skillful for all four start seasons). Finally, DHFP1 is less successful at forecasting the PDO at the decadal time scale. Ten-year forecasts of the PDO index exhibit significantly positive correlation skill exclusively in the first year of the forecast. When the correlation skill of the predicted index averaged over lead years is considered, the PDO skill in this system stays significantly positive during the first three years of the decadal forecast. In other words, this climate data assimilation and prediction system is expected to skillfully predict the future three year averaged evolution of the PDO index, but not the evolution of the index in each year individually. / Graduate

Thesis (doctoral)--University of Tartu, 2005. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Rhode Island, 2006. / Includes bibliographical references (leaves 269-279).

PhD. (Environmental Management) / Climate change and variability has rapidly emerged as one of the most serious threats to sustainable development especially for developing African countries such as Rwanda. Since most of the agricultural activities in African countries are rain-fed, any adverse change in climate is likely to have a devastating effect on output and the livelihood of the majority of the population in the affected countries. Therefore, there should be continuous and regular preparedness to on-going climate variability. Climate change and variability derived information, are most likely to improve the agricultural outcomes when it is integrated into a framework for decision making to mitigate specific risks. It is in that regard, this research aims at analyzing climate change and variability and their impacts on the yields of major food crops in Rwanda. The raw climatic data (temperatures and precipitations) used in this study were obtained from the Rwandan Meteorological Center based in Kigali and Rwanda Environment Management Authority (REMA) while the agricultural records were collected from the National Institute of Statistics of Rwanda (NISR) and the Ministry of Agriculture and Animal Resources (MINAGRI). Length and completeness of records were the basic criteria used to select weather stations in order to have the most complete dataset. Five major crops, namely beans, cassava, Irish potatoes, maize, and sweet potatoes were selected for investigation because they are grown over large areas in most parts of the country during the two agricultural seasons i.e. season A (September-January) and season B (February-June). This research uses a number of statistical techniques in an attempt to quantify the magnitude and significance in temperature, rainfall, number of rainy days, aridity index and rainfall erosivity changes and variability taking place over Rwanda. The same techniques were applied in determining the magnitude and significance of inter-annual variations in food crop yields over Rwanda. A geographical information system (GIS) was used to present spatially the results on maps...

In the context of distinctive international business phenomena of global environmental concern i.e., climate change, this dissertation addresses two research questions. Does multinational enterprise (MNE) orientation (global- or regional-orientation) have an influence on the carbon performance of the multinational? Is there any significant home country effect that drives carbon performance? Stakeholders are increasingly watching the green performance of the firms and investors are looking for information of how firms deal with externalities such as carbon emission. Environmental capabilities are increasingly becoming the core competence of a multinational enterprise. This also enables the MNE to be an active entity and play a key role in global environmental governance. Defining carbon performance as the capability of firms to integrate climate change strategy into the overall strategy, this dissertation used resource-based view and institutional theory as the theoretical framework along with the concept of regionalization of firms. We argue that differences in integrating strategy to reduce carbon emission (carbon performance) are related to MNE orientation and home country effect. Using a sample of 324 firm-years drawn from the carbon disclosure project reports 2011, 2012, and 2013, we analyzed the data running a logistic regression. We found that global-oriented MNEs had better carbon performance compared with regional-oriented MNEs (p This result was against the hypothesized relationship. One of the reasons for this result could be projected good image by the firms in environmentally non-sensitive industries because of cost advantage. Lower environmental institutional distance between home and host country of a firm increased the likelihood of its carbon performance regardless of its orientation as global or regional (p