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The Influence of Large-Scale Modes of Climate Variability on Spatiotemporal Rainfall Patterns and Vegetation Response in Hawaiʻi
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|Title:||The Influence of Large-Scale Modes of Climate Variability on Spatiotemporal Rainfall Patterns and Vegetation Response in Hawaiʻi|
|Authors:||Frazier, Abby Gail|
|Contributors:||Giambelluca, Thomas (advisor)|
Geography and Environment (department)
spatial trend analysis
show 10 moreecology
Empirical orthogonal function
MODIS vegetation index
|Date Issued:||Aug 2016|
|Publisher:||[Honolulu] : [University of Hawaii at Manoa], [August 2016]|
|Abstract:||The geographically isolated Hawaiian Islands are not immune to the effects of climate change. As the global climate changes, understanding historical rainfall variations and their effects on vegetation is important to provide context for future changes. This dissertation seeks to characterize the spatiotemporal variability in rainfall in Hawai‘i since 1920, and examine how climate variability impacts vegetation. Utilizing a high-resolution gridded data set of annual and seasonal rainfall, trends were calculated at every pixel across the state to produce trend maps of Hawai‘i. From 1920 to 2012, over 90 percent of the state experienced drying trends, with the western part of Hawai‘i Island experiencing the largest significant long-term declines. A running trend analysis revealed areas with persistent trends through time. To determine the influence of natural variability and anthropogenic factors on the rainfall time series, an empirical orthogonal function (EOF) analysis was performed on the gridded seasonal rainfall. The leading components were modeled with indices of large-scale climate variability using multiple linear regression (MLR), and pattern correlation coefficients (PCC) were calculated between recent trends and future expected changes from downscaling results. The MLR and PCC results give weak and inconclusive evidence for detection of anthropogenic signals in the observed rainfall trends. The final component of this research was a case study that expanded on previous work examining vegetation response to El Niño-induced drought. Drought at the forest line on Haleakalā, Maui was characterized over a 95 year period using the Standardized Precipitation Index (SPI) and the role of ENSO was investigated. Vegetation response to drought from 2000-2014 was determined both above and below the forest line using two remotely-sensed vegetation indices (VI). The forest line area experienced 28 drought events from 1920-2014, most of which were associated with ENSO events. A multi-year drought from 2008-2014 was the most extreme drought on record and resulted in significant browning both above and below the forest line, while other droughts resulted in greening. Overall, this work contributes to our understanding of natural climate variability in Hawai‘i and how vegetation responds. The information presented here will inform future water resource planning and management.|
|Description:||PhD University of Hawaii at Manoa 2016|
Includes bibliographical references (leaves 116–137).
|Pages/Duration:||xi, 137 leaves|
|Rights:||All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.|
|Appears in Collections:||
Ph.D. - Geography|
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