Eastern China is perennially hit by mesoscale convective systems (MCSs), yet it remains an open question as to whether and how their general properties change throughout the annual cycle. By leveraging high‐resolution satellite observations and a hybrid tracking algorithm, we present a 20‐year (2001–2020) climatology of MCSs over eastern China during eight subseasonal‐to‐seasonal (S2S) monsoon stages. MCSs contribute up to 50% of the stage‐total precipitation and over 60% of the rainband‐zone precipitation during the Pre‐Meiyu and Meiyu episodes, and their contributions remain non‐trivial during the transition seasons. We discover two contrasting regimes of MCSs that alternate immediately upon the Pre‐Meiyu and the Fall onsets. The wintertime regime features fast‐propagating shallow systems initiated at night in a strongly sheared and dry environment. The summertime regime, instead, features an outbreak of MCSs in the south, where the systems often initiate in the afternoon and propagate 2–3 times slower than the cold‐season ones. Based on multivariate clustering analysis, the nighttime MCSs that dictate the winter stages often initiate over a deep nocturnal boundary layer with moist rear inflows upgliding above it. In contrast, the afternoon‐initiated MCSs under the summertime regime feature a pronounced convective available potential energy (CAPE) "tongue" and upslope flows in their southeast quadrant. The southwesterly moist ascending flows are likely to shallow the convective inhibition at the tip of the CAPE tongue and facilitate the intense updrafts of the MCSs. Findings here may offer insights into S2S weather prediction and facilitate agricultural and water management throughout the year.

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth's hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.Plain Language Summary Atmospheric rivers (ARs) are long and narrow weather features often referred to as "rivers in the sky." They often transport water from lower latitudes to higher latitudes typically across climate zones and produce precipitation necessary for local climates. Understanding ARs in a warming climate is challenging because of the variety of ways an AR can be defined on gridded data sets. Unlike weather features such as tropical cyclones where identification methodologies are similar, algorithms that determine the characteristics of ARs vary depending on the science question posed. Because there is no real consensus on AR identification methodology, we aim to quantify the algorithmic uncertainty in AR metrics and precipitation. We compare 16 different ways of defining an AR on gridded data sets and present the range of possibilities in which an AR could change under global warming. Generally, ARs are projected to increase but the amount SHIELDS ET AL.