On the Spatial and Time Scales of Coastal Upwelling and the El Niño Southern Oscillation

Abstract

This dissertation investigates the fundamental spatial scales and time scales of two major climate phenomena with implications for ecosystems and global weather patterns: mid-latitude coastal upwelling and the El Niño Southern Oscillation (ENSO). First, coastal upwelling, driven by alongshore winds and characterized by cold sea surface temperatures (SSTs) and high upper-ocean nutrient content, is an important physical process sustaining some of the oceans’ most productive ecosystems. Despite the importance of such regions, coastal upwelling remains poorly represented in global climate models. The width of the coastal upwelling zone and the depth from which the upwelling originates are two fundamental features of coastal upwelling systems, as they play a significant role in determining both the SST and the transport of nutrients toward the surface. Here, I aim to characterize the width and depth scales associated with the coastal upwelling zone and to identify a set of empirical scaling laws for these length scales. Using high-resolution, regional ocean simulations of an idealized coastal upwelling system, I estimated the width of the upwelling zone and the source depth from which the water upwells across a range of values for the wind stress, stratification, and Coriolis frequency. In addition to the mean upwelling source depth, I construct an upwelling source depth distribution using passive tracers. My results indicate that there are two distinct horizontal length scales needed to characterize the upwelling zone---the width of the offshore region where upwelling occurs and the width of the offshore region where isopycnals deform significantly from horizontal. Ultimately, I develop a new set of empirical scaling laws for these key length scales that are consistent with the results of my idealized numerical simulations as well as self-consistent with the derivation of the mean source depth that depends on the proposed length scale for isopycnal deformation. Using realistic, regional ocean simulations of the California coast, I also investigate the effects of wind stress variability on the upwelling source depth in the California coastal upwelling system. Previous work has indicated that strong wind events may have a disproportionately large effect on driving coastal upwelling and suggests that the mean alongshore wind stress alone may not determine the upwelling circulation. But this lesson was ignored in studies of the upwelling source depth. The results of my numerical experiments show that upwelling source depth is deeper when the wind stress varies on shorter timescales. I further show that this result is a direct consequence of the nonlinear response of the upwelling source depth to the variable wind stress on short timescales. Additionally, I find that the scaling relations previously predicted for the source depth as a function of a time-independent wind stress do not seem to hold when the wind stress is time variable. These results demonstrate that to fully understand and predict the upwelling source depth and its distribution, it is important to consider both the mean and temporal variability of the alongshore wind stress. The second part of this dissertation concerns ENSO, which is the strongest driver of year-to-year global climate variability. An important unresolved question is whether ENSO is driven by weather variability or is self-sustained and would exist without the presence of random weather noise. The recharge oscillator (RO) model has been successfully used to understand different aspects of the ENSO. Fitting the RO to observations and climate model simulations consistently suggested that ENSO is a damped oscillator whose variability is sustained and made irregular by external weather noise. I investigate the methods that have been previously used to estimate the growth rate of ENSO by applying them to simulations of both damped and self‐sustained RO regimes. I find that fitting a linear RO to simulated time series leads to parameters that imply a damped oscillator even when the fitted data were produced by a model that is self‐sustained. Fitting a nonlinear RO also leads to a significant bias toward the damped regime. As such, it seems challenging to determine whether ENSO is a damped or a self‐sustained oscillation by fitting such models to observations, and the possibility that ENSO is self‐sustained cannot be ruled out.