Extreme weather events in northeastern New Brunswick (Canada) for the period 1950–2012: Comparison of newspaper archive and weather station data - Mallet, Julie; Fortin, Guillaume; Germain, Daniel (Canadian Geographer, 2018)
In the context of global warming, changes in extreme weather and climate events are expected, particularly those associated with changes in temperature and precipitation regimes and those that will affect coastal areas. The main objectives of this study were to establish the number of extreme events that have occurred in northeastern New Brunswick, Canada in recent history, and to determine whether their occurrence has increased. By using archived regional newspapers and data from three meteorological stations in a national network, the frequency of extreme events in the study area was established for the time period 1950–2012. Of the 282 extreme weather events recorded in the newspaper archives, 70% were also identified in the meteorological time series analysis. The discrepancy might be explained by the synergistic effect of co-occurring non-extreme events, and increased vulnerability over time, resulting from more people and infrastructure being located in coastal hazard zones. The Mann Kendall and Pettitt statistical tests were used to identify trends and the presence of break points in the weather data time series. Results indicate a statistically significant increase in average temperatures and in the number of extreme events, such as extreme hot days, as well as an increase in total annual and extreme precipitation. A significant decrease in the number of frost-free days and extreme cold days was also found, in addition to a decline in the number of dry days.
MAG ID: 2762324269

Influence of instrumentation on long temperature time series - Acquaotta, Fiorella; Fratianni, Simona; Aguilar, Enric; Fortin, Guillaume (Climatic Change, 2019)
In time series of essential climatological variables, many discontinuities are created not by climate factors but changes in the measuring system, including relocations, changes in instrumentation, exposure or even observation practices. Some of these changes occur due to reorganization, cost-efficiency or innovation. In the last few decades, station movements have often been accompanied by the introduction of an automatic weather station (AWS). Our study identifies the biases in daily maximum and minimum temperatures using parallel records of manual and automated observations. They are selected to minimize the differences in surrounding environment, exposition, distance and difference in elevation. Therefore, the type of instrumentation is the most important biasing factor between both measurements. The pairs of weather stations are located in Piedmont, a region of Italy, and in Gaspe Peninsula, a region of Canada. They have 6years of overlapping period on average, and 5110 daily values. The approach implemented for the comparison is divided in four main parts: a statistical characterization of the daily temperature series; a comparison between the daily series; a comparison between the types of events, heat wave, cold wave and normal events; and a verification of the homogeneity of the difference series. Our results show a higher frequency of warm (+10%) and extremely warm (+35%) days in the automated system, compared with the parallel manual record. Consequently, the use of a composite record could significantly bias the calculation of extreme events.
MAG ID: 2971678736