H13C-1120:
Decadal climatic variability and regional weather simulation: stochastic nature of forest fuel moisture and climatic forcing

Monday, 15 December 2014
Yulia Tsinko, Edward A Johnson and Yvonne E Martin, University of Calgary, Calgary, AB, Canada
Abstract:
Natural range of variability of forest fire frequency is of great interest due to the current changing climate and seeming increase in the number of fires. The variability of the annual area burned in Canada has not been stable in the 20th century. Recently, these changes have been linked to large scale climate cycles, such as Pacific Decadal Oscillation (PDO) phases and El Nino Southern Oscillation (ENSO). The positive phase of the PDO was associated with the increased probability of hot dry spells leading to drier fuels and increased area burned.

However, so far only one historical timeline was used to assess correlations between the natural climate oscillations and forest fire frequency. To counteract similar problems, weather generators are extensively used in hydrological and agricultural modeling to extend short instrumental record and to synthesize long sequences of daily weather parameters that are different from but statistically similar to historical weather. In the current study synthetic weather models were used to assess effects of alternative weather timelines on fuel moisture in Canada by using Canadian Forest Fire Weather Index moisture codes and potential fire frequency.

The variability of fuel moisture codes was found to increase with the increased length of simulated series, thus indicating that the natural range of variability of forest fire frequency may be larger than that calculated from available short records. It may be viewed as a manifestation of a Hurst effect. Since PDO phases are thought to be caused by diverse mechanisms including overturning oceanic circulation, some of the lower frequency signals may be attributed to the long term memory of the oceanic system. Thus, care must be taken when assessing natural variability of climate dependent processes without accounting for potential long-term mechanisms.