Last Updated on 2026-05-13
One impact of global warming is an increase in surface air temperatures. As these temperatures are drivers in plant and animal growth, temperature trends can help predict changes in plant and animal fauna. Trends are also useful in determining human infrastructure needs. Temperature records from various parts of New Brunswick are available and allow us to look at trends over the past 100 years or more. One way of doing this is by examining decadal mean temperatures. These 10-year means can be derived from Environment Canada’s (EC) weather data sets; by averaging over a decade we can reduce some of the ‘noise’ resulting from annual fluctuations and determine if trends in one direction or another are apparent. The homogenized data sets provided by Environment Canada provide one way to look at these decadal annual and seasonal trends. This is an updated version of an older page, and now includes data from the most recent complete decade – 2010-2019. Locations were selected from a list of available weather stations in New Brunswick – several of these stations have only a few years of data and thus were not useful for observation of trends over long periods of time. The available here stations are: Fredericton (8101605), Edmundston (8101303), Miramichi (8100898), Moncton (8103201), Saint John (8104901), and Sussex (8105210).
Seasons are defined as sets of months; with Spring being March, April, May; Summer as June, July, and August; Autumn (Fall) as September, October, and November; and Winter as December, January and February. Those definitions are important to remember as we in the Maritimes sometimes tend to think of March, for example, as a winter month. We also tend to speak of ‘short’ winters or ‘long’ autumns, or, if January and February are colder than usual, we might say we had a ‘cold’ winter and ignore the impact on the Winter average of a mild December. With the definitions used here, however, the seasons are always the same duration and the same months.
The decadal means were calculated by averaging each of the seasonal mean temperatures from the homogenized dataset. For example, for the ‘2000’ decade 2000 is year 1 and 2009 is year 10. I’ve also included a seasonal / monthly chart (the second chart below) based on annual means – you can see just how much ‘noisier’ the plot is, even though the trends are similar.
Interactive charts: