The fire plume height (smoke injection height) is an important parameter for calculating the transport and lifetime of smoke particles, which can significantly affect regional and global air quality and atmospheric radiation budget. To develop an observation‐based global fire plume‐rise dataset, a modified one‐dimensional plume‐rise model was used with observation‐based fire size and Maximum Fire Radiative Power (MFRP) data, which are derived from satellite fire hotspot measurements. The resulting dataset captured well the observed plume height distribution derived from the Multi‐angle Imaging SpectroRadiometer (MISR) measurements. The fraction of fire plumes penetrating above the boundary layer is relatively low at 20% at the time of MISR observation (10:30 am LT) but increases to an average of ∼55% in the late afternoon, implying that the MISR observation data sampled in late morning underestimate the average daytime fire plume heights and plume mixing into the free troposphere. Therefore, adjustments are required through dynamic modeling or parameterization of fire plume height as a function of meteorological and fire conditions when the MISR dataset is applied in climate model simulations. We conducted sensitivity simulations using the Community Atmospheric Models version 5 (CAM5). Model results show that the incorporation of fire plume rise in the model tends to significantly increase fire aerosol impacted regions. We applied the offline plume rise data to develop an online fire plume height parameterization, allowing for simulating the feedbacks of climate/weather on fire plume rise in climate models.