Assessing Precipitation Changes and Mechanisms Over the Northeastern United States

Extreme precipitation (EP), defined as precipitation falling in the heaviest 1% of all wet days, has increased more in the Northeast than in any other region of the United States, yet there is still a lack of systematic assessment of precipitation changes and mechanisms in this region. To address this research gap, I first investigate the historical changes in both total and extreme precipitation by using multiple datasets, including station and gridded observations and a reanalysis product. Then I explore the climatological mechanism driving the changes in extreme precipitation over seasons using station observations, daily weather maps, reanalysis data, and an Atlantic hurricane database. Lastly, I run an ensemble of regional climate model experiments using the Weather Research and Forecasting (WRF) model to evaluate the performance, limitations, and uncertainties of WRF in simulating precipitation and temperature across a subregion of the Northeast, the Lake Champlain Basin. My results show that both total and extreme precipitation have increased in the Northeast since 1901. Annual EP experienced an abrupt increase across 1996 (53% more EP post-1996 as compared to 1901–1995), which was driven by significant EP increases in fall and spring. Spatially, coastal areas received more total and extreme precipitation on average, but increases across the changepoints are distributed fairly uniformly across the Northeast. Eighty-nine percent of the abrupt EP increase after 1996 is explained by large events in early fall, early summer, and late winter. By meteorological cause, tropical cyclones account for almost half of that increase (48%), followed by fronts (25%) and extratropical cyclones (15%). The dominant circulation drivers of the EP increase are warmer Atlantic sea surface temperatures, increased water vapor, and a wavier jet stream. I find that WRF simulations generally reproduce the observed precipitation seasonal cycle, but have wet biases. The simulation of mean precipitation by WRF is most sensitive to the choice of radiation, cumulus, and microphysics scheme. My findings provide valuable information to both interpret and contextualize regional climate model simulations and their use in impacts assessments across the Lake Champlain Basin and broader Northeast.