Narrow cold-frontal rain bands (NCFR) often produce short-duration and high-intensity precipitation that can lead to flooding and debris flow in California (CA). On 27 January 2021, an atmospheric river (AR) associated with an intense surface cyclone made landfall over coastal northern CA, which featured a prominent NCFR. This study uses high-resolution West WRF simulations to accurately resolve the gap and core structure of the NCFR and provides reliable precipitation estimations, compensating for limitations of radar and satellite observations. This NCFR was supported by robust synoptic-scale quasi-geostrophic (QG) forcing for ascent and frontogenesis. It propagated southward from Cape Mendocino to Big Sur in 12 hours before stalling and rotating counter-clockwise in central/southern CA due to upstream Rossby wave breaking and amplifying upper-tropospheric trough. With the lower to middle tropospheric flow backed considerably to the south-southwest over the NCFR, the increase of the vertical wind shear caused the transition from parallel to trailing stratiform precipitation. The stall and pivot of the AR and NCFR led to intense rainfall with a 2-day precipitation accumulation greater than 300 mm over central CA. In addition, under the potential instability and frontogenesis, a moist absolutely unstable layer between 850 hPa to 700 hPa was captured at the leading edge of the NCFR, which indicated slantwise deep layer lifting and high precipitation efficiency. This study reveals synoptic-scale and mesoscale drivers of rainfall outside orographic lifting and reaffirms the importance of high-resolution numerical modeling for the prediction of extreme precipitation and related natural hazards.

Atmospheric Rivers (ARs) intricately connect with diverse weather systems, spanning planetary-scale to mesoscale levels, influencing extreme weather events through the transportation of abundant moisture and the shaping of regional circulation patterns. In March 2019, a strong AR originating from the Gulf of Mexico fueled a record-breaking bomb cyclone in Colorado, resulting in widespread winter weather hazards across several states. Experimental model simulations and trajectory analysis indicate that mid-tropospheric latent heat release played a key role in the deepening of the cyclone. The latent heat release promoted the generation of a lower tropospheric positive potential vorticity (PV) anomaly and a stronger low-level cyclonic circulation, enhancing the cyclone, low-level jet stream, and associated water vapor transport. Additionally, it generated an upper tropospheric negative PV anomaly and strong upper-level anticyclonic circulation, influencing the structure of the trough-ridge couplet and the associated Rossby wave. Reductions in the initial intensity of the AR and disallowing latent heat release both weakened the cyclone. However, disallowing latent heat release significantly disturbed the synoptic-scale structure of the storm and embedded Rossby wave, resulting in a stronger impact. Thus, the reduction of diabatic PV generation, under the influence of AR activities, was crucial in the explosive intensification of the cyclone. Few studies have explored interactions between ARs and continental cyclones, and this paper highlights the need for further research on AR-associated extreme weather events inland.

The results of prior work indicated that the Southeast United States (SEUS) region contains extreme Quantitative Precipitation Forecast (QPF) skill that is lower than other regions in the U.S. (e.g., the Western and Northeast US). A hypothesis is that this skill is influenced by a diversity of storm types such as Atmospheric Rivers (ARs), Mesoscale Convective Systems (MCS) and Tropical Cyclones (TCs) occurring within distinct synoptic patterns, which have resulted in significant floods such as in Nashville (2010) and Waverly (2021) Tennessee. Similarly, previous investigations have identified that synoptic patterns with higher integrated vapor transport (IVT) potentially have greater QPF skill than those with lower IVT. There is further opportunity to investigate pattern-wise contribution of storm types and QPF skill in SEUS. This study identified six synoptic patterns associated with heavy precipitation in Tennessee. These patterns exhibited distinct seasonality, with three patterns occurring in the cool season, two in the warm season, and one in the transition season. Approximately, 66 % of heavy precipitation in cool season and 47 % in transition season is associated with coincident ARs and MCS. Pattern-wise QPF skill derived from the GEFS Reforecast dataset illustrated that the cool season pattern with the highest IVT and largest fraction of ARs has better skill, whereas the warm season pattern with the highest CAPE and integrated water vapor has worse skill at multiple lead times. These results provide insights into the dynamical characteristics and predictability of heavy precipitation by storm type over the SEUS.