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Title: Lightning Variability in Dynamically Downscaled Simulations of Alaska’s Present and Future Summer Climate
Abstract Lightning is a key driver of wildfire activity in Alaska. Quantifying its historical variability and trends has been challenging because of changes in the observational network, but understanding historical and possible future changes in lightning activity is important for fire management planning. Dynamically downscaled reanalysis and global climate model (GCM) data were used to statistically assess lightning data in geographic zones used operationally by fire managers across Alaska. Convective precipitation was found to be a key predictor of weekly lightning activity through multiple regression analysis, along with additional atmospheric stability, moisture, and temperature predictor variables. Model-derived estimates of historical June–July lightning since 1979 showed increasing but lower-magnitude trends than the observed record, derived from the highly heterogeneous lightning sensor network, over the same period throughout interior Alaska. Two downscaled GCM projections estimate a doubling of lightning activity over the same June–July season and geographic region by the end of the twenty-first century. Such a substantial increase in lightning activity may have significant impacts on future wildfire activity in Alaska because of increased opportunities for ignitions, although the final outcome also depends on fire weather conditions and fuels.  more » « less
Award ID(s):
1757348
NSF-PAR ID:
10166149
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Journal of Applied Meteorology and Climatology
Volume:
59
Issue:
6
ISSN:
1558-8424
Page Range / eLocation ID:
1139 to 1152
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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