Assessment of increase in forest fire risk in Russia till the late 21st century based on scenario experiments with fifth-generation climate models

Abstract

Proposed are the methods for assessing the number of days per month with the forest fire risk based on monthly mean values of air temperature, relative humidity, and the amount of precipitation. Obtained are the quantitative estimates of the contribution of each of the above meteorological parameters to the linear regression equation. Prognostic estimates of the number of days with the forest fire risk per season for short-, medium-, and long-range prospects of climate changes are computed using the scenarios of climate change till the late 21st century based on the fifth-generation physical and mathematical models. Revealed is a dependence of the area covered with forest a fire on the number of fire-risk days per season.