Estimation of Snowfall Depth Considering RCP 4.5 Climate Change Scenario

초록

Snowfall depth is related to various meteorological variables such as temperature and precipitation and it is generated in nonlinear manner. This study constructs snowfall forecasting model using neural network which can consider nonlinear process of snowfall. We construct the forecasting models using temperature, precipitation, and snowfall depth observed from starting time of observation in each station to 1999. And snowfalls are calculated for all stations by using temperature and precipitation in the period of 2000 to 2011. This study estimates the snowfall depth by using temperature and precipitation based on RCP 4.5 climate change scenario data. And we estimates the frequency based daily snowfall depth(50yr, 100yr and 200yr) for three different target periods(Target I : 1971∼2010, Target II : 2011∼2040, Target III : 2041∼2070, Target IV : 2071∼2100) under climate change. The snowfall depth due to climate change is analyzed based on Target period 1 and it has decreased. The results of this study could be used