ENSO modulates wildfire activity in China

Wildfires are significant natural disturbances impacting vegetation, climate, and carbon cycles. Climate change, driven by anthropogenic factors, is increasing wildfire frequency and severity globally, creating positive feedback loops. While high-latitude fires are influenced by high-latitudinal climate modes, low-latitude fires are closely linked to tropical climate drivers, such as ENSO. Subtropical forests, particularly those in China, represent a crucial yet understudied area for understanding wildfire variability and its climatic drivers. Previous studies in China relied on coarse-resolution data, limiting understanding of local-scale climatic influences. This study addresses this gap by presenting the WFAC, a high-resolution dataset enabling detailed analysis of spatiotemporal wildfire characteristics and their climatic drivers.

Existing literature highlights the complex interplay between climate and wildfire activity. Studies have shown increased global wildfire frequency and severity due to anthropogenic climate change, impacting carbon cycles and ecosystems. High-latitude fires are linked to climate modes like the Arctic Oscillation, while low-latitude fires show diverse responses to ENSO. Southeastern Asia and Southwestern North America, for example, exhibit contrasting responses. Research on subtropical forest fires and their climatic drivers is limited. Previous studies in China used coarse-resolution data, hindering understanding of local-scale relationships. This study leverages high-resolution data to refine existing knowledge.

The Wildfire Atlas of China (WFAC) integrates satellite imagery and field observations from the Forest Fire Prevention and Monitoring Information Center (FFPMIC) data product from 2005 to 2018. The dataset includes location, date, and time of 135,246 fire occurrences. Data were aggregated into a 2° × 2° grid at hourly resolution. Gridpoints with fewer than five total fire occurrences were removed. Further aggregation was performed at daily, monthly, and annual scales. Ten distinct fire regions were identified using rotated principal component analysis (RPCA). Fire chronologies were developed for the whole country and each sub-region. Fire-climate relationships were analyzed by correlating fire occurrence time series with climate data (temperature, precipitation, diurnal temperature range (DTR), Palmer Drought Severity Index (PDSI), and Standard Precipitation-Evapotranspiration Index (SPEI)) from the CRU TS4.03 dataset. Correlations were calculated for both original and first-differenced data. Singular value decomposition (SVD) was applied to investigate relationships between fire occurrences and global sea surface temperature (SST) from the HadISST dataset, and further correlations were calculated against 850-hPa geopotential heights (GPH) and wind vector fields from the ERA-Interim reanalysis model. The relationships between fire occurrences and holidays were analyzed by calculating the ratio of fire occurrences on holidays to average daily occurrences.

The WFAC dataset reveals that 84% of wildfires occurred in subtropical China (20–30°N, 100–120°E), predominantly during winter (January-April). A decreasing trend in fire occurrences is observed since a peak in 2007, contrasting global trends in many other regions. Southeastern China's wildfires are positively correlated with diurnal temperature range (DTR) and negatively with precipitation, indicating a drier environment as the primary driver. Southwestern China's wildfires exhibit positive correlations with temperature, highlighting warm conditions as the main influence. A fire occurrence dipole is identified between southwestern and southeastern China, strongly modulated by ENSO. El Niño events increase wildfires in southwestern China but decrease them in southeastern China and northern regions. The opposite pattern is observed during La Niña years. This dipole pattern is strongly correlated with the Niño3.4 ENSO index (r=-0.97, p<0.001). The study also highlights that fire occurrences are significantly higher on traditional Chinese holidays, particularly in specific regions and on specific days within the holiday periods. This suggests human activities and cultural practices continue to have considerable influence despite the fire suppression policies. The analysis of fire occurrences by time of day shows that most fires occur from 14:00 to 18:00, peaking earlier in northern China. The relationship between fire occurrences and climate are stronger for interannual timescales than longer timescales, possibly reflecting the effect of fire suppression policies.

The findings underscore the significant influence of climatic variability on wildfire occurrence in China, despite strict fire suppression policies. The ENSO-modulated dipole pattern highlights the need for region-specific fire control strategies that account for ENSO variability. The strong association between fire occurrences and holidays indicates the importance of human activities. The high-resolution data employed in this study provide crucial insights into local fire-climate relationships, enhancing understanding of wildfire dynamics in subtropical China. The contrasting responses of different regions to ENSO suggest complex interactions between climate variability and fire regimes. Further research could focus on improving fire prediction models by integrating ENSO forecasts, detailed vegetation data, and more thorough exploration of the human factors influencing fire occurrence.

This study provides the first high-resolution fire occurrence dataset for China (WFAC), revealing crucial spatiotemporal patterns and strong climate-fire relationships, particularly the influence of ENSO. The findings highlight the importance of considering ENSO variability in wildfire projections and developing region-specific fire management strategies. Future research should investigate the impacts of climate change on the identified ENSO-fire relationships and further explore the influence of human activities on fire patterns in different regions of China.

The study is limited by the availability of data from the FFPMIC, which only provides data for China. Generalizability to other regions might be limited. While the study explores various climate variables, further investigation of other factors, such as fuel type and ignition sources, might refine the understanding of fire-climate interactions. The study primarily focuses on fire occurrence rather than fire size. Further analyses incorporating fire size could enhance overall insights and understanding.