Severe weather outbreaks are violent weather events that can cause major damage and injury. Unfortunately, forecast models can mistakenly predict the intensity of these events. Frequently, the prediction of outbreaks is inaccurate with regards to their intensity, hindering the efforts of forecasters to confidently inform the public about intensity risks. This research aims to improve outbreak intensity forecasting using severe weather parameters and an outbreak ranking index to predict outbreak intensity. Areal coverage values of gridded severe weather diagnostic variables, computed from the North American Regional Reanalysis (NARR) database for outbreaks spanning 1979 to 2013, will be used as predictors in an artificial intelligence modeling ensemble to predict outbreak intensity. NARR fields will be dynamically downscaled to a National Severe Storms Laboratory-defined WRF 4-km North American domain on which areal coverages will be computed. The research will result in a model that will predict verification information on the model performance.

Scholars from various disciplines have long attempted to identify the variables most closely associated with individual preparedness. Therefore, we now have much more knowledge regarding these factors and their association with individual preparedness behaviors. However, it has not been sufficiently discussed how decisive many of these factors are in encouraging preparedness. In this article, we seek to examine what factors, among the many examined in previous studies, are most central to engendering emergency preparedness in individuals particularly for tornadoes by utilizing a relatively uncommon machine learning technique in disaster management literature. Using unique survey data, we find that in the case of tornado preparedness the most decisive variables are related to personal experiences and economic circumstances rather than basic demographics. Our findings contribute to scholarly endeavors to understand and promote individual tornado preparedness behaviors by highlighting the variables most likely to shape tornado preparedness at an individual level.

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<p> It has been hypothesized that some measurable properties of $Z_{DR}$ arcs in supercells may change in the minutes prior to tornadogenesis and tornadogenesis failure, and that $Z_{DR}$ arc area will change with SRH and can be used as a real-time proxy to estimate SRH. Output form the Cloud Model 1 (CM1) along with a polarimetric emulator is used to simulate $Z_{DR}$ arcs in 9 tornadic and 9 non-tornadic supercells. A random forest algorithm is used to automatically identify the $Z_{DR}$ arcs. Finally the inflow sector SRH is calculated at times when $Z_{DR}$ arcs are identified. To analyze the change in intensity and area a comparison between the average $Z_{DR}$ value inside and outside of the arc, as well as the spatial size of the arc and storm was done. Model calculated SRH is then compared to these metrics.</p> <p> </p> <p> It has also been observed that hail fallout complicates the automatic identification of $Z_{DR}$ arcs. In this study, three experiments are run where the simulated $Z_{DR}$ arcs are produced. One using all categories of hydrometeors, one where wet growth and melting of hail is excluded, and one excluding the contribution to $Z_{DR}$ from the hail hydrometeor category. The same analysis as above is repeated for all three experiments. Finally observed $Z_{DR}$ arcs are analyzed to see if these results are applicable to the real world. </p>

High dimensional space-time datasets are available nowadays in various aspects of life such as economy, agriculture, health, environment, etc. Meanwhile, it is challenging to reveal possible connections between climate change and weather extreme events such as hurricanes or tornadoes. In particular, the relationship between tornado occurrence and climate change has remained elusive. Moreover, modeling multivariate spatio-temporal data is computationally expensive. There is great need to computationally feasible models that account for temporal, spatial, and inter-variables dependence. Our research focuses on those areas in two ways. First, we investigate connections between changes in tornado risk and the increase in atmospheric instability over Oklahoma. Second, we propose two multiscale spatio-temporal models, one for multivariate Gaussian data, and the other for matrix-variate Gaussian data. Those frameworks are novel additions to the existing literature on Bayesian multiscale models. In addition, we have proposed parallelizable MCMC algorithms to sample from the posterior distributions of the model parameters with enhanced computations. / Doctor of Philosophy / Over 1000 tornadoes are reported every year in the United States causing massive losses in lives and possessions according to the National Oceanic and Atmospheric Administration. Therefore, it is worthy to investigate possible connections between climate change and tornado occurrence. However, there are massive environmental datasets in three or four dimensions (2 or 3 dimensional space, and time), and the relationship between tornado occurrence and climate change has remained elusive. Moreover, it is computationally expensive to analyze those high dimensional space-time datasets. In part of our research, we have found a significant relationship between occurrence of strong tornadoes over Oklahoma and meteorological variables. Some of those meteorological variables have been affected by ozone depletion and emissions of greenhouse gases. Additionally, we propose two Bayesian frameworks to analyze multivariate space-time datasets with fast and feasible computations. Finally, our analyses indicate different patterns of temperatures at atmospheric altitudes with distinctive rates over the United States.

在當前全球受到全球暖化所帶來許許多多氣候異常現象，造成人類生命財產安全的嚴重影響，世界各國莫不致力於節能減碳，開發再生能源來取代目前的石化燃料。 美國在1970年代能源危機期間所提出的ESCO(Energy Service Company) 的概念，如今又獲得各國的青睞。 台灣於引進此一新的概念也有十年之久，在業界也一直不斷有專家，技術人員不斷的投入努力，經濟部能源局近年來也不斷的倡導節能服務的好處，甚至還推動一些補貼措施。 本研究主要是以Everett M. Rogers的創新擴散模型為理論基礎，研究台灣ESCO產業為何無法如高科技消費性電子產品般很快速的擴散到社會每一個角落，有哪些因素阻礙了台灣ESCO產業的發展。 本研究主要得到的結論如下，阻礙台灣ESCO產業擴散的因素可從三個構面來分析，第一個構面為創新擴散構面，Rogers所提出的五種創新認知屬性對於台灣ESCO產業的擴散都有一定程度的影響。另外在溝通管道上所採用的B2B行銷方式對於客戶決策也會影響擴散的速度。至於時間因素，本研究認為五年是比較恰當的觀察台灣ESCO產業發展的觀察期間。第二個構面可以從台灣獨特的經濟特質來說明，台灣以中小企業為主的經濟環境無法如歐美般有Super-ESCO規模的公司，這也導致了客戶信賴度以及未能產生以服務為導向的ESCO能源服務，台灣若還是以設備買賣為主要ESCO產業的商業模式，是會阻礙此產業的發展。第三個構面為政府的角色，台灣政府在投入ESCO產業的資源及推動此產業發展的企圖心不若美國政府。 本研究經研究結論後，提出具體的建議: 一、 要加速此產業的創新擴散就必須加強 Rogers創新擴散模型中的可觀察性屬性。 二、 跨越產業鴻溝的重點在於讓早期採用者滿意ESCO的方案。運用保齡球道理論，讓早期採用者所形成的利基市場對於ESCO節能服務能夠滿意，產生具示範效果的成功案例，才能伺機擴張至其他的利基市場，最後形成龍捲風暴，順利跨越此產業的鴻溝。。 三、 本研究對於台灣ESCO產業的發展的看法是審慎保守的。台灣ESCO產業的發展絕不是短短幾年就可以看到成效，本研究建議以五年為一個觀察期。目前以中小企業為主的ESCO業者必須要儘快的建立自己的優勢，儘早建立口碑，未來才有機會生存。 / Global warming is the most seriously problem we are facing in 21th century. All the countries devoted to reduce the carbon emission in order to minimize the impact of climate change. The business model of ESCO (Energy Service Company), which has been created in US during 1970 energy crisis, now has been advocated worldwide. The ESCO business model has been introduced into Taiwan for more than 10 years. There are many talent people, specialist engaged in this business. Taiwan government has also promoted ESCO some subsidies. However, even the society put a lot of efforts to develop ESCO business, why this business cannot spread out as consumer electronics? This thesis adopts the theory of “Diffusion of innovation” from Everett M. Rogers, 1962. The main purpose of this study is to find out why ESCO service business model cannot diffuse like other high-tech products. Are there any obstacles slow down the development of this industry? This thesis comes to the conclusion of three faces, which can significantly influence the development of ESCO business in Taiwan. The first face based on the diffusion of innovation theory, the five attributes of innovation defined by Rogers will affect the development of ESCO industry in Taiwan. Of course, the B2B marketing approach will delay the propagation of the ESCO industry. Moreover, this study suggest that 5 years watching window should be appropriate to monitor the development of the ESCO industry in Taiwan. The second face is the Taiwan unique economics environment. The ESCO industry in Taiwan is formed mostly by Middle-small size enterprises. In comparison with US, there is no Super-ESCO company exists in Taiwan. This study found out the truth that the client is not confident on middle-small size company to provide ESCO service. The common business model of ESCO industry in Taiwan is still focusing on selling the energy efficient product instead of providing energy service to the client. The study believes that this kind of business model will severely impact the development of this industry. The third face of the conclusion is the government role in Taiwan. The study found out that Taiwan government didn’t allocate enough resources to assist developing ESCO business. This thesis not only indicated the obstacles to slow down the ESCO business in Taiwan but also provide some constructive initiatives. 1. We have to concentrate on the visible attributes in diffusion of innovation theory for ESCO industry. 2. In order to cross the chasm, ESCO has to satisfy the early adapters in the beginning. They can also build up the bowling pin model to keep the existing niche market and explore the adjacent niche market when the opportunity comes. Thus, ESCO can create tornado period and cross the chasm in the industry. 3. The study is conservative about the development of Taiwan ESCO industry. We suggest that 5 years watching window should be proper to monitor the development of Taiwan ESCO industry. The ESCO companies in Taiwan should establish their strengths the sooner the better in order to survive for the future severe market competition.