Shih-Chieh Kao

Motivating Complex Dependence Structures in Data Mining: A Case Study with Anomaly Detection in Climate

While data mining aims to identify hidden knowledge from massive and high dimensional datasets, the importance of dependence structure among time, space, and between different variables is less emphasized. Analogous to the use of probability density functions in modeling individual variables, it is now possible to characterize the complete dependence space mathematically through the application of copulas. By adopting copulas, the multivariate joint probability distribution can be constructed without constraint to specific types of marginal distributions. Some common assumptions, like normality and independence between variables, can also be relieved. This study provides fundamental introduction and illustration of dependence structure, aimed at the potential applicability of copulas in general data mining. The case study in hydro-climatic anomaly detection shows that the frequency of multivariate anomalies is affected by the dependence level between variables. The appropriate multivariate thresholds can be determined through a copula-based approach.

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama-Coosa-Tallapoosa River Basin

Probable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics-based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama-Coosa-Tallapoosa (ACT) river basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms, were conducted. The depth-area-duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Our results showed that PMP driven by projected future climate forcings is higher than 1981–2010 baseline values by around 20% in the 2021–2050 near-future and 44% in the 2071–2100 far-future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserves more in-depth examination.

Sensitivity of Probable Maximum Flood in a Changing Environment

This study uses integrated hydrometeorological simulations over the Alabama-Coosa-Tallapoosa (ACT) River Basin in the southeastern United States to understand the impact of climate change on probable maximum precipitation.

The Second Assessment of the Effects of Climate Change on Federal Hydropower

.................................................................................................................................. iii ACKNOWLEDGEMENTS ............................................................................................................ v LIST OF FIGURES ....................................................................................................................... xi LIST OF TABLES ........................................................................................................................ xv EXECUTIVE SUMMARY ........................................................................................................ xvii ABBREVIATIONS, ACRONYMS, AND INITIALISMS ........................................................ xxv LIST OF VARIABLES.............................................................................................................. xxxi

Geographic analysis & visualization of climate extremes for the Quadrennial Defense Review

We have developed demonstrable capabilities in the area of geographic analysis and visualization for climate extremes, uncertainty and impacts. The capabilities were used for to provide climate science support to an international climate change war game, where real-world policy makers, as well as business, political and science leaders from around the world, engaged in a mock policy negotiations. We have since further developed the capabilities for supporting the development of the Quadrennial Defense Review (QDR) by the Office of the Secretary of Defense within the United States Department of Defense (DOD).