Sea-effect snowfall in Finland in 1998-2018 based on convection-permitting climate model data

Sea-effect snowfall can occur when cold air moves over a relatively warm and ice-free sea. When intense sea-effect snowfall systems move over land, they can cause considerable damage to infrastructure and disrupt traffic. Sea-effect snowfall is a common phenomenon in Finland, but its spatial and temporal distribution has only recently been studied using a detection method on atmospheric reanalysis data and snow depth observations. 

In this study, we refine the previously used detection method and apply it to convection-permitting regional climate model data. The data has been made with the HARMONIE-Climate (HCLIM) model with a spatial resolution of 3 km for the years 1998-2018. The data has been produced by the Nordic Convection Permitting Climate Projections project (NorCP) group.  

The motivation is two-fold. First, we investigate whether HCLIM can simulate the sea-effect snowfall in Finland realistically and be used in studies of sea-effect snowfall in the past and future. Second, using the high-resolution dataset with non-hydrostatic dynamics, we aim to gain more detailed understanding of the spatial and temporal distribution of sea-effect snowfall in Finland, compared to studies based on coarser data. 

The detection method is based on finding the times and grid boxes with, first, considerable amounts of snowfall and, second, environmental conditions shown in previous literature to favour the occurrence of sea-effect snowfall systems. In this work, we present the spatial and temporal distribution of sea-effect snowfall cases in Finland based on the HCLIM data and show that the annual and monthly mean distributions of sea-effect snowfall days in HCLIM were qualitatively similar to the previously defined climatology. In the future, we plan to use the climate model to study how the sea-effect snowfall climatology in Finland may change due to climate change.