Woody, J.Xu, Y.Dyer, J.Lund, RHewaarachchi, A.P.2021-08-052021-08-052021Woody, J.; Xu, Y.; Dyer, J.; Lund, R.; Hewaarachchi, A.P. A Statistical Analysis of Daily Snow Depth Trends in North America. Atmosphere 2021, 12, 820. https:// doi.org/10.3390/atmos12070820http://repository.kln.ac.lk/handle/123456789/23148Several attempts to assess regional snow depth trends have been previously made. These studies estimate trends by applying various statistical methods to snow depths, new snowfalls, or their climatological proxies such as snow water equivalents. In most of these studies, inhomogeneities (changepoints) were not accounted for in the analysis. Changepoint features can dramatically influence trend inferences from climate time series. The purpose of this paper is to present a detailed statistical methodology to estimate trends of a time series of daily snow depths that account for changepoint features. The methods are illustrated in the analysis of a daily snow depth data set from North America.changepoints, genetic algorithms, snow trends, storage model, time series