Publication Date

Fall 2021

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Meteorology and Climate Science

Advisor

Patrick T. Brown

Subject Areas

Meteorology

Abstract

Energy providers are shifting their supply from carbon based forms of energy to renewable sources in response to policy changes aimed at reducing pollution and anthropogenic influence on the environment. Wind and solar energies are notable sources that have been adopted around the globe and are increasing in installation and efficiency, but relying on weather-dependent sources of energy has limitations. Variability in energy supply and demand becomes further dependent on the state of the climate, and thus predictability of that state is critical. Climate modes are correlated with climate variables and are used to make mid-term (>10 days), seasonal, and even decadal climate forecasts. The modes are correlated through teleconnections, which are brought about through changes to the quasi-stationary atmospheric circulation. The research presented herein concerns three climate modes, the El Niño Southern Oscillation, Pacific-North America pattern, and North Atlantic Oscillation, and their teleconnections to wind, sunlight, and temperature on seasonal time scales. We explore these teleconnections through statistical relationships between climate modes and climate variables in the historical record. We look at concurrent relationships to get a better understanding of physical causality and we look at time-lagged relationships to see if there is obvious predictability. It is found that in most locations large scale modes of variability do not provide a major constraint on seasonal wind and solar power and thus their variability is largely a result of internal atmospheric dynamics.

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