Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth’s hydroclimate. However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single-forcing climate model experiments under the aegis of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO2 levels of the Last Glacial Maximum to a pre-industrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds. In the low CO2 simulation, the algorithms generally agree on the sign of AR changes but there is substantial spread in their magnitude, indicating that mean-state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases.

Over the last several decades, heat waves have notably increased in frequency, intensity, and duration in the United States. Studies have credited these trends to a warming climate, and therefore, it is expected that extended periods of consistent and abnormally hot temperatures will continue to occur through the 21st century. Heat waves alone can have harmful impacts on the human body, but when coupled with high humidity, these events can become especially threatening. While other studies have assessed the human health effects of extreme humid heat waves, this study aims to determine the source region and pathway of air parcels during these events, while also understanding the land-surface processes that amplify and dampen the amount of atmospheric moisture present as an air parcel reaches a target region. Through the use of the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, atmospheric moisture exchanges and concentrations are analyzed for the three days prior to a humid heat wave at Boston, MA, Burlington, VT, Albany, NY, and Philadelphia, PA, between June and August of 1980-2019. Four major source regions are identified as being largely responsible for the atmospheric moisture present during heat waves across these cities: the Atlantic Ocean, Gulf of Mexico, Great Lakes, and terrestrial evapotranspiration from the Midwest and Mid-Atlantic regions of the United States. Geographical location and proximity to water of each city has a notable influence on source region and number of humid heat waves occurring throughout the period of study. At Boston and Philadelphia, the two leading sources of moisture are the Atlantic Ocean and Gulf of Mexico, while at Burlington and Albany, the Great Lakes and terrestrial evapotranspiration are more dominant. Stark differences are also noted between the source regions and trajectories of humid versus dry heat waves at a given location. Examining the sources and paths of air parcels leading up to extreme heat events, as well as analyzing the atmospheric-land interactions that take place during that time, will provide a comprehensive understanding into the importance of a given moisture source region on a particular location, and how a warming climate may ultimately alter the degree to which a source region is responsible for atmospheric moisture in the future.