Investigating historical high-impact tropical cyclones (TCs) and associated record precipitation events remains as important as ever. Assessing potential changes in these compound extremes under plausible future climates can help inform communities in coastal regions, increasing resilience. This study adopts hindcasting ensemble simulations that uses the Community Atmosphere Model (CAM) of the Community Earth System Model (CESM) and its variable resolution capabilities, with grid spacings of 28 km over North Atlantic basin, to investigate TC precipitation in present day and future simulations. Such future simulations account for warming signals for 2, 3 and 4 K global average surface temperature above the preindustrial levels. These different warming levels are generated by modifying thermodynamic initial conditions such as air temperature, specific humidity, and sea surface temperature using the CESM large ensemble. Specifically, this work aims to explore changes in recent storm event’s precipitation, including Ida (2021), Eta (2020), and Michael (2018), under different levels of warming. The model’s simulated tracks will be compared with the observed tracks to determine best performing initializations for lead times every 12 hr interval before landfall of these storms. CAM is initialized using weather forecast model initial conditions from the Global Forecast System of National Centers for Environmental Prediction. The sea surface temperature boundary conditions are set using merged Hadley optimum interpolation of National Oceanic and Atmospheric Administration. This study evaluates the change in the average rainfall rate (3-hourly model output) as well as the upper quantiles (~90-99th) under the various climate scenarios from a pool of 20 member-ensembles for each model initialization period and storm. A systematic approach is used to evaluate the simulated hurricane tracks and precipitation for the storm events for actual and three future climate scenarios. This work demonstrates the use of storyline analysis for exploring the potential impact of future climates on the extreme precipitation of recent historical storms.