Classification of Clustered Snow Off Dates Over British Columbia, Canada, from Mean Sea Level Pressure

Abstract

ABSTRACT Atmosphere–ocean teleconnections influence the accumulation and melt of snow in western Canada and can be useful in seasonal forecasting of snowmelt and runoff. Interannual variation in these atmosphere–ocean modes has been shown to influence the accumulation and melt of snow within British Columbia (BC), Canada. We investigate fall mean sea level pressure (MSLP) globally as a predictor of remotely sensed snowmelt dates within BC. We use the last day of continuous snow cover ( ) detected from time series satellite imagery acquired by the Moderate Resolution Imaging Spectroradiometer for the hydrological years 2000–2018. It has been shown that is correlated with continuous snow duration and is also of interest to seasonal forecasters. Global MSLP from the Fifth major global reanalysis produced by the European Centre for Medium-range Weather Forecasts was obtained over hydrological years 1979–2018. An S-mode (time versus location) principal component analysis was carried out on both datasets. The principal component scores were grouped using a k-means clustering routine. Using evolutionary feature selection, the subset of MSLP principal components that provided good linear discrimination of the clusters were found. We explore the atmospheric MSLP principal components that influence the timing of snowmelt over BC and use them to predict the clusters at a seasonal lead time.