Dry Lightning and Escalating Wildfire Risk in Northern Canada: The 2023 Extreme Fire Season and Future Projections

Recent wildfire extremes in northern Canada indicate a shift in lightning-driven ignition processes beyond episodic variability. This study examines the atmospheric conditions responsible for the increasing occurrence of dry lightning—cloud-to-ground lightning accompanied by negligible precipitation—across Yukon, the Northwest Territories, and Nunavut. By integrating cloud-to-ground lightning observations with ERA5 reanalysis, we identify a dominant thermodynamic configuration controlling dry-lightning frequency. Dry lightning increases most strongly when anomalously warm near-surface temperatures coincide with enhanced mid-tropospheric moisture (700–500 hPa), forming a pronounced vertical contrast. This structure supports deep convective electrification while limiting surface wetting through efficient sub-cloud evaporation. In contrast, conventional instability and wind-based indices exhibit limited explanatory power for long-term dry-lightning variability. The extreme 2023 wildfire season exemplifies this ignition-efficient configuration rather than representing a rare anomaly. Projections from the CMIP6 multi-model ensemble indicate that continued surface warming and increasing mid-tropospheric moisture will shift this thermodynamic state toward the climatological mean under future warming, particularly under high-emissions scenarios. A physically constrained regression framework suggests that dry-lightning occurrence may increase by more than 50% by the late 21st century. These findings demonstrate that northern Canada is transitioning toward a climate state in which lightning-induced wildfire ignitions are structurally favored. Accounting for evolving vertical thermodynamic conditions is therefore essential for anticipating future high-latitude wildfire risk.

Acknowledgement 
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant RS-2024-00404042 and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00343921).