Convective storms produce heavier downpours and become more intense with climate change. Such changes could be even amplified in high-latitudes since the Arctic is warming faster than any other region in the world and subsequently moistening. However, little attention has been paid to the impact of global warming on intense thunderstorms in high latitude continental regions, where they can produce flash flooding or ignite wildfires. We use a model with kilometer-scale grid spacing to simulate Alaska’s climate under present and end of the century high emission scenario conditions. The current climate simulation is able to capture the frequency and intensity of hourly precipitation compared to rain gauge data. We apply a precipitation tracking algorithm to identify intense, organized convective systems, which are projected to triple in frequency and extend to the northernmost regions of Alaska under future climate conditions. Peak rainfall rates in the core of the storms will intensify by 37% in line with atmospheric moisture increases. These results could have severe impacts on Alaska’s economy and ecology since floods are already the costliest natural disaster in central Alaska and an increasing number of thunderstorms could result in more wildfires ignitions.

A new algorithm is described that can separate precipitation output from convection‐permitting models into three different types of precipitation: (a) convective, (b) stratiform, and (c) orographically enhanced precipitation. The algorithm is based on physical processes that underlie these types of precipitation and it is applicable over both ocean and land surfaces. It is particularly well suited for mountainous areas or other regions exhibiting complex terrain. The algorithm's performance is first demonstrated for a selection of well‐understood weather events and then for a 10‐year convection‐permitting climate simulation over Norway. The algorithm correctly separates convection embedded in frontal systems from stratiform precipitation and also properly identifies orographically enhanced precipitation when the frontal systems interact with local orography. The results suggest that this can be a powerful new tool for investigating characteristics of precipitation in convection‐permitting climate simulations, particularly in a climate change context and as researchers move towards models that explicitly resolve convection and its related processes.