Probabilistic projections of climatological forest fire danger in Finland

• Published in: Climate research 2014-01, Vol.60 (1), p.73-85
• Main Authors: Mäkelä, Hanna M., Venäläinen, Ari, Jylhä, Kirsti, Lehtonen, Ilari, Gregow, Hilppa
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Climatology. Bioclimatology. Climate change; Conservation, protection and management of environment and wildlife; Earth, ocean, space; Exact sciences and technology; External geophysics; Fundamental and applied biological sciences. Psychology; Meteorology; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking
• ISSN: 0936-577X; 1616-1572
• DOI: 10.3354/cr01223

A multiple regression model was applied to estimate the future number of forest fire danger days (FDDs) in boreal climate conditions in Finland. The model used anomalies of June−August mean temperature and precipitation as predictors. Joint probability distribution functions (PDFs) created during the ENSEMBLES project for the SRES A1B scenario were employed to describe the future climate. The PDFs showed that the summertime mean temperature will, on average, rise in our study area by 1.5°C by 2010−2029 and by 4°C by 2080−2099. For precipitation, the PDFs showed a wide spread. Apart from western Finland, a majority of sample points suggested an increase in precipitation by the end of the century. Despite the general precipitation increase, average FDDs are likely to increase in the whole study area. Depending on the study region, the probability of FDD increase was 56 to 75% for 2010−2029 and 71 to 91% for 2080−2099. The largest probabilities of an increase were found in northern Finland and the smallest in eastern Finland. On average, FDDs were projected to increase by 1 d during the near future and by 7 to 10 d by the end of this century. The relative increase in FDDs was largest in northern Finland, by 12% in 2010−2029 and 55% in 2080−2099. The large uncertainty in future summertime precipitation is reflected in the estimation of future FDDs. Better estimates of spatial and temporal distribution of future precipitation would make the FDD assessment more robust.