A geostatistical approach to create a new climate types map at regional scale: case study of New Brunswick, Canada

Abstract

Regional climate is particularly important for different activities such as forestry, agriculture, transport, coastal areas, and wildlife. In New Brunswick (NB), ten climate types were classified by combining climate and geographical data from 45 national meteorological stations for the period 1981–2010. A multiple regression technique/model was used for the interpolation of climatic parameters then clustering was done based on the three main parameters from a principal component analysis. Our results indicate a strong correlation between most climate variables with latitude and altitude while longitude and distance to the sea plays a more marginal role in climate spatial distribution. Furthermore, the climate map produced coincides with a map produced from a previous study of the NB province based on 1954–1979 data. However, the boundaries between most climate zones in those two maps changed slightly due to inconsistent period variation (1954–1979 vs 1981–2010), the methods used as well as the number and location of the weather stations (76 vs 45). Many climate type limits changes observed in the study area were probably connected with the climate change since mid-1950s.