National Oceanic and Atmospheric Administration RISA Program
09/01/20 – 08/31/21
Thomas Giambelluca, and Oliver Elison Timm (SUNY Albany)
Significant changes have been observed in temperature and rainfall in Hawai‘i over the past century. In the case of rainfall trends, it is still not clear whether these changes can be attributed to global warming. Detection and attribution (DA) is a formalized approach to distinguish externally generated trend signals, e.g., effects of anthropogenic climate change, from naturally occurring low-frequency variability. The attribution step goes beyond the pure statistical analysis of separating noise from the signal. It asks for the causes of the detected trend signals. Here we propose to apply DA methods to address the following questions that have, so far, not been fully answered for the regional climate changes observed in Hawai‘i: (1) Can the observed long-term changes in Hawaiian rainfall be attributed to anthropogenic forcing? (2) What are the individual contributions from greenhouse gas forcing, aerosol forcing, and natural forcing factors (solar and volcanic) to rainfall variability and long-term trends? and (3) How much uncertainty can be expected in future climate change projections due to the influence of internal variability?