Throughout this study, interactions between lightning and forest fires were investigated. General characteristics of lightning such as seasonality, diurnal variability, spatial distribution, and polarity as well as precipitation were related to forest fires. In general, most of the lightning strikes occurred in Interior Alaska, where the summer is relatively warm and dry. A majority of the annual lightning strikes (91%) occurred in June and July with a maximum around mid-July. This demonstrates that most of the strikes are related to convective activity and are not due to the passage of fronts. The sharp decrease in August relates to the high amount of cloudiness, which suppresses convection, as August is the month with the highest annual precipitation in Interior Alaska. On one occasion, the stroke count from only 4 consecutive days accounted for almost 40% of the annual total, thus there is a great deal of interannual variability. The diurnal variability of lightning strikes showed an increase from the late morning (10:00 AST) until the afternoon (17:00 AST). After 22:00 AST, the lightning count decreased sharply. (Alaska Standard Time is about 2 hours ahead of solar time.) No systematic differences in the polarity of lightning were observed in the diurnal and seasonal course. Positive strikes, however, which only account for about 20% of all lightning strikes, were around 3 times more likely to cause a forest fire.
The connection between lightning strikes, forest fires, and acreage burned was more complex, due to the many factors that influence these conditions such as antecedent conditions, soil moisture, vegetation, and human intervention. The number of stations that recorded precipitation for each day from May to August for the years 2000 to 2002 were totaled and compared to the number of forest fires started. An expected negative correlation was found; when there was a high amount of rain there were few fires, and during dry periods, many fires began. If we are able to enhance our understanding of what conditions give way to forest fires, we can more accurately predict them and establish necessary parameters for controlled burns.