Accounting for 41.7% of China’s total land area, grasslands are linked to the livelihoods of over 20 million people. Although grassland fires cause severe damage in China every year, their spatiotemporal patterns and climate drivers are not well understood. In this study, we used grassland fire record forms provided by the National Forestry and Grassland Administration and grassland fire location data from the Wildfire Atlas of China to examine the spatiotemporal patterns and and seasonality of fires in China for the period from 2008 to 2020. We found that most grassland fires occurred in Inner Mongolia in northern China, specifically in the Hulun Buir and Xilingol grasslands. We found distinct differences in fire seasonality in northern China, which has a major fire season in April, versus southwestern China, where the major fire season occurs in February, March and April. April grassland fires in northern China are the result of strong winds, typically from the west, and spring drought. A secondary fire season in northern China occurs in October and is also driven by strong winds. The fire season in southwestern China seems to be less shaped by climatic factors such as wind speed, precipitation, and drought. This study provides support for decision-making by fire prevention and fire management authorities in China.

Climate change is already significantly affecting the frequency of wildfires in most regions of the world, and the risk of wildfires is expected to amplify further with global warming. Accordingly, there is growing concern about the mechanisms and impacts of extreme fires. In this study, a coupling of the Weather Research and Forecasting model and the Rothermel Fire model (WRF-Fire) is employed to reproduce the spread of fire within the national boundary of inner Mongolia from 21 to 27 May 2009. Simulations were run with or without feedback from fire-to-atmosphere models, and the study focused on how the energy flux of simulated fires changes the local meteorological environment. The coupled simulation could reproduce the burned area well, and the wind speed was the dominant factor in the fire spread, with a maximum value no more than 6.4 m/s, when the terrain height changes little and the proportion of grassland is low. After the feedback, the propagation speed of the fire accelerated, accompanying the release of latent and sensible heat, and local circulation formed near the front of the fire, leading to a convergence and divergence zone in the downwind area. It is worth noting that during a period of more than 140 h of simulation, the area of the fire field increased by 17% from ignition time. Therefore, considering the fire–atmosphere interaction is necessary for accurately predicting fire behavior.