Forest fires constitute the second largest form of disturbance to the Finnish boreal forest environment, playing a significant role in vegetation succession and landscape transformation. Warning systems aiming to minimize the risk of fires are based on fire danger estimation methods using weather information. In this study, the operational fire danger rating method used in Finland, the Finnish Forest Fire Index, is introduced and its performance evaluated by analysing the relationship between the predicted daily fire danger and observed fire activity. The Finnish Forest Fire Index is a physically‐based soil surface moisture estimation method employing as input traditional surface observations, numerical weather forecast model fields and weather radar measurements. The fire danger index is found to predict high fire danger conditions well, with some decline in performance northward where the observations network is sparser than in the southern part of the country. The model indicated higher hit rates in the prediction of multiple fire (54%) and large fire days (54.3%), which are less dependent on a human‐dominated fire environment than are single fire days. Highlighted future development priorities include the direct application of numerical analyses of meteorological data in the operational computation procedure. In addition, inclusion of the impact of land cover, such as vegetation type, on the fire danger index is under development.
No takes yet. Share an insight, caveat, or question.
Vajda et al. (2013) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: