Title:
Statistical & dynamical multiple-scale predictability of the North Pacific ocean
Statistical & dynamical multiple-scale predictability of the North Pacific ocean
Author(s)
Xu, Tongtong
Advisor(s)
Haas, Kevin A.
Di Lorenzo, Emanuele
Di Lorenzo, Emanuele
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
Prolonged ocean surface warming in North Pacific, such as those extreme events known as marine heatwaves, could lead to significant impact on coastal ecosystems. As such, predicting the North Pacific sea surface temperatures days to weeks to months or even years in advance, especially prolonged marine heatwaves and coastal variability, helps provide guidance to decision makers to understand the future ecosystem variation and to utilize the adverse situation to their benefits. Therefore, it is of vital importance to construct credible and effective ocean forecast systems on various spatial and temporal scales. While statistical models capture the large-scale dynamics and provide forecast skill comparable to the state-of-the-art climate models, regional dynamical models are necessary to resolve high resolution coastal processes and to improve coastal prediction skill. Thus, this thesis combined the use of a Linear Inverse Model (LIM) and the Regional Ocean Modeling System (ROMS), a widely-used empirical model and a commonly-accepted dynamical ocean model, to understand the North Pacific extremes and to evaluate North Pacific forecast on multiple spatial and temporal scales. This includes: (1) using LIM to analyze the statistical behaviors, progression, and prediction of marine heatwaves in Northeast Pacific; (2) using LIM to explore the prediction of North Pacific coastal systems and the impact of tropical versus extratropical Pacific on the prediction; (3) using a multi-scale nesting configuration of ROMS to resolve coastal processes and to explore the near-real time forecast skill around Pt Sal, California; (4) using the fine resolution grid of ROMS to quantify the impact of different forcings, including initial conditions, boundary forcings and atmospheric surface forcings, on the near-real time forecast.
Sponsor
Date Issued
2021-07-29
Extent
Resource Type
Text
Resource Subtype
Dissertation