edu.ucar.opensky::articles:42663 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-24T17:57:50.847054 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.net/ark:/85065/d7sj1qzd Atmospheric River detection under changing seasonality and mean‐state climate: ARTMIP tier 2 paleoclimate experiments 2025-01-01T00:00:00Z publication https://n2t.net/ark:/85065/d7sj1qzd https://doi.org/10.1029/2024JD042222 Rush, W. D. author Lora, J. M. author Skinner, C. B. author Menemenlis, S. A. author Shields, Christine A. author Ullrich, P. author O’Brien, T. A. author Brands, S. author Guan, B. author Mattingly, K. S. author McClenny, E. author Nardi, K. author Nellikkattil, A. author Ramos, A. M. author Reid, K. J. author Shearer, E. author Tomé, R. author Wille, J. D. author Leung, L. R. author Ralph, F. M. author Rutz, J. J. author Wehner, M. author Zhang, Z. author Lu, M. author Quagraine, K. T. author UCAR/NCAR - Library publisher 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&#8208;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 CO 2 levels of the Last Glacial Maximum to a preindustrial 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 CO 2 simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean&#8208;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. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication <span style="font-family:Arial;font-size:10pt;font-style:normal;font-weight:normal;" data-sheets-root="1">Copyright 2025 American Geophysical Union (AGU).</span> None eng geoscientificInformation