Attributable Human‐Induced Changes in the Likelihood and Magnitude of the Observed Extreme Precipitation during Hurricane Harvey
A specialized extreme value statistical analysis is used to characterize historical trends in severe storms in the Houston, Texas area. The analysis explicitly accounts for both natural and human influences on severe storms during hurricane season in the Gulf Coast region and systematically quantifies uncertainty in the features of these storms.
Our analysis specifically identifies increases in the magnitude (at least 19% stronger) and likelihood (at least 3.5 times more likely) of a storm like Hurricane Harvey, and that these changes are attributable to human-induced climate change. The results of our analysis suggest that changes in the features of Hurricane Harvey were much larger than expected, motivating more in-depth studies of the event.
In late August 2017, record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas area, leading to widespread flooding. We analyzed observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of the El Niño/Southern Oscillation. We find that human-induced climate change likely increased the chances of the observed precipitation accumulations during Hurricane Harvey in the most affected areas of Houston by a factor of at least 3.5. Further, precipitation accumulations in these areas were likely increased by at least 18.8% (best estimate of 37.7%), which is larger than the 6-7% associated with an attributable warming of 1 degree C in the Gulf of Mexico and Clausius-Clapeyron scaling. In a Granger causality sense, these statements provide lower bounds on the impact of climate change and motivate further attribution studies using dynamical climate models.