ORCID

https://orcid.org/0000-0002-7509-7463

Date of Award

Summer 2024

Language

English

Embargo Period

7-22-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Atmospheric and Environmental Sciences

Program

Atmospheric Science

First Advisor

Oliver Timm

Committee Members

Justin Minder, Brian Rose, Liming Zhou, Thomas Giambelluca

Keywords

Dynamical downscaling, regional climate modeling, climate variability, climate change, moisture budget analysis, self-organizing map

Subject Categories

Atmospheric Sciences | Climate

Abstract

Hawaiian rainfall variability is strongly influenced by anthropogenic climate change and natural variability (e.g., Pacific Decadal Oscillation (PDO), Pacific North American (PNA) pattern, El Niño–Southern Oscillation (ENSO)). For local decision-makers and resource managers, understanding the drivers of rainfall variability and change in Hawai‘i is crucial for climate adaptation and mitigation planning. Previous studies have applied statistical and dynamical downscaling to produce high-resolution rainfall projections for the Hawaiian Islands region. However, to date, downscaling has only been used to investigate the influence of anthropogenic forcing on late-century rainfall projections for the Hawaiian Islands. For regions like Hawai’i, that are highly vulnerable to the effects of climate change and influenced by natural variability, there is a need for regional climate projections that investigate the influence of anthropogenic climate change in the presence of natural variability. A better understanding of the local and large-scale processes that drive rainfall variability and change in Hawai’i could help improve forecasts and climate projections and ultimately aid climate adaptation and mitigation planning across the State. Thus, this research addresses the following questions: 1) What is the role of natural variability in near-term rainfall projections over Hawai‘i? 2) What physical mechanisms drive the near-term rainfall changes over Hawai‘i? and 3) What is the relationship between the largescale circulation, natural climate variability, and wintertime Hawaiian rainfall disturbances?

First, the Weather Research and Forecasting (WRF) model was applied for dynamical downscaling to analyze near-term (2026–2035) rainfall projections over the Hawaiian Islands region. Of key interest is understanding the relative role of the anthropogenic forcing compared to natural variability in the near-term projections. Results indicate that increases in rainfall are iii expected across the islands, with the largest increases along the windward slopes of Big Island and Maui, during the wet season. In a future climate, it is also expected that the positive PDO phase will bring increases in rainfall to the windward slopes of Big Island and decreases or no change elsewhere. Overall, results suggest that natural variability will continue to mask anthropogenic climate change in the near-term future, making it difficult to detect a robust signal above the noise.

Second, to investigate the physical mechanisms that drive near-term rainfall changes in Hawai‘i, a moisture budget analysis was performed over the Hawaiian Islands region using both the downscaled WRF output and the driving global climate model (GCM) data. The moisture budget was decomposed into thermodynamic, dynamic, and eddy-driven components. Results indicate that the dynamic component dominates the near-term hydrological changes over the Hawaiian Islands region during both seasons, indicating that the near-term rainfall changes are driven primarily by changes in the mean circulation. Though less dominant, the thermodynamic component, i.e., changes in humidity accompanied by warming, plays an important role in the Hawaiian Islands moisture budget as well. It was also found that the transient-eddy component plays an important role in the wet season moisture budget, which can be attributed to increased synoptic activity during winter (i.e., Kona lows and cold fronts).

Third, to investigate the large-scale drivers of rainfall variability and change in Hawai‘i, the Self-Organizing Map (SOM) was applied to investigate the relationship between the large-scale circulation over the North Pacific, and its relationship to natural climate modes (e.g., PNA and ENSO) and wintertime rainfall disturbances in Hawai‘i (e.g., Kona lows, cold fronts). The SOM was trained with daily 250-hPa zonal wind anomalies from European Centre for Medium-Range Weather Forecasts reanalysis (ERA5). Results indicate that a zonally retracted jet is iv associated with the negative PNA/ENSO phase and above-normal rainfall across Hawai‘i, while a zonally extended jet is associated with the positive PNA/ENSO phase and below-normal rainfall across Hawai‘i. Further, to investigate future changes in the variability of the large-scale circulation, simulations from the Canadian Earth System Model version 5 (CanESM5) were projected onto the ERA5-trained SOM. Generally, results indicate that zonally retracted and poleward shifted jets are expected to become more frequent in a future climate (2071–2100). Overall, these results suggest that Hawai‘i will experience increased PNA/ENSO variability, increased frequencies in cold fronts and Kona lows, and decreases in wet season rainfall in a future climate. Further, these results highlight the usefulness of the SOM in bridging the gap between anthropogenic-induced changes in the large-scale circulation and local rainfall-producing weather types.

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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