| Summary: | The work presented in this dissertation is driven by three fundamental questions in climate science: (1) What is the natural variability of our climate system? (2) What components of this variability are predictable? (3) How does climate change affect variability and predictability? Determining the variability and predictability of the chaotic and nonlinear climate system is an inherently challenging problem. Climate scientists face the additional complications from limited and error-filled observational data of the true climate system and imperfect dynamical climate models used to simulate the climate system. This dissertation contains four chapters, each of which explores at least one of the three fundamental questions by providing novel approaches to address the complications. Chapter 1 examines the uncertainty in the observational record. As surface temperature data is among the highest quality historical records of the Earth’s climate, it is a critical source of information about the natural variability and forced response of the climate system. However, there is still uncertainty in global and regional mean temperature series due to limited and inaccurate measurements. This chapter provides an assessment of the global and regional uncertainty in temperature from 1880-present in the NASA Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (GISTEMP). Chapter 2 extends the work of Chapter 1 to the regional spatial scale and monthly time scale. An observational uncertainty ensemble of historical global surface temperature is provided for easy use in future studies. Two applications of this uncertainty ensemble are discussed. First, an analysis of recent global and Arctic warming shows that the Arctic is warming four times faster than the rest of the global, updating the oft-provided statistic that Arctic warming is double that of the global rate. Second, the regional uncertainty product is used to provide uncertainty on country-level temperature change estimates from 1950-present. Chapter 3 ...
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