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Filters: partyWithName: Pacific Islands CSC (X) > partyWithName: Thomas W. Giambelluca (X)

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Abstract (from http://climatechangeresponses.biomedcentral.com/articles/10.1186/s40665-016-0015-2): Background Detailed assessments of species responses to climate change are uncommon, owing to the limited nature of most ecological and local climate data sets. Exceptions, such as the case of the Haleakalā silversword, can provide important insights into the complexity of biological responses to changing climate conditions. We present a time series of decadal population censuses, combined with a pair of early population projections, which together span the past 80 years of demographic history for this alpine plant. Results The time series suggests a strong population recovery from the 1930s through the 1980s, likely...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/joc.4862/abstract): Spatial patterns of rainfall in Hawai‘i are among the most diverse in the world. As the global climate warms, it is important to understand observed rainfall variations to provide context for future changes. This is especially important for isolated oceanic islands where freshwater resources are limited, and understanding the potential impacts of climate change on the supply of freshwater is critical. Utilizing a high-resolution gridded data set of monthly and annual rainfall for Hawai‘i from January 1920 to December 2012, seasonal and annual trends were calculated for every 250-m pixel across the state and mapped to produce spatially...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/2014JD022059/abstract): Seasonal mean rainfall projections for Hawai‘i are given based on statistical downscaling of the latest Coupled Model Intercomparison Project phase 5 (CMIP5) global model results for two future representative concentration pathways (RCP4.5 and RCP8.5). The spatial information content of our statistical downscaling method is improved over previous efforts through the inclusion of spatially extensive, high-quality monthly rainfall data set and the use of improved large-scale climate predictor information. Predictor variables include moisture transport in the middle atmosphere (700 hPa), vertical temperature gradients, and geopotential...
Abstract: The aim of this paper is to present a statistical downscaling method in which the relationships between present-day daily weather patterns and local rainfall data are derived and used to project future shifts in the frequency of heavy rainfall events under changing global climate conditions. National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) reanalysis data from wet season months (November to April) 1958–2010 are composited for heavy rain days at 12 rainfall stations in the Hawaiian Islands. The occurrence of heavy rain events (days with amounts above the 90th percentile estimated from all wet season rain days 1958–2010) was found to be strongly correlated...